<p class="jove_content">We thank Silke Classen from the Research Institute for Ecosystem Analysis and Assessment (gaiac), RWTH Aachen for her assistance in the establishment of the group-specific primer sets used in this protocol. We also thank Peter Martin and Laura Schynawa from the University of Kiel for the cooperation in the water mites&#39; experiments. We also thank the technical lab assistants for keeping the lab running smoothly and preparing the register of companies and catalogue numbers. This work was supported by the German Research Foundation (DFG; project GE 2219/3-1).</p>

<ol>
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<p class="jove_content">The authors have nothing to disclose.</p>

<p class="jove_content">Here, we present an easy and cost-efficient method for PCR-based determination of predator-prey interactions from field samples via group-specific primers for rDNA regions, which can be combined with other non-molecular analyses of the same specimens. However, there are several critical steps within the protocol. Firstly, assuring the specificity of the primers used is essential. Secondly, it is crucial to avoid contamination and loss of gut content material during the preparation of the gastro-intestinal tract and the subsequent extraction of DNA. While cross-sample contamination can lead to false positive detection of prey DNA, loss of gut content material might lead to missing rarely consumed prey species. Verification of the presence of rDNA belonging to the respective subunit and the functional efficiency of templates used for the analyses (section 2 of the protocol) is essential for gathering representative information about the prey consumed. This is in particular crucial, if no DNA of prey groups the consumer is supposed to feed on can be detected<sup class="xref">25</sup><sup>,</sup><sup class="xref">27</sup>. Furthermore, when preparing the PCRs (steps 3.1, 5.1.1 and 5.1.2) it is crucial that the mixture and protocol used exactly fit the criteria in which the respective primer was specified to a certain group of taxa. Otherwise, either amplification of DNA within the PCR reaction might fail completely, or the DNA of taxa not targeted might be amplified as well. Therefore, it is obligatory to use positive and negative controls within each PCR run to assure that the PCR reaction worked and no contamination occurred. Additionally, it is necessary that the array of the samples for each PCR run is documented exactly to enable the correct assignment of prey consumed to the respective consumer specimen. For this task, particular caution needs to be taken while pooling PCR products for parallel detection of multiple prey groups via automated fragment analyses (step 5.2.3).</p>
<p class="jove_content">For the detection of amplified fragments using agarose gel electrophoresis (steps 3.2 and 3.3) agarose gels should be as thin as possible and care has to be taken during the visual inspection of the image to avoid missing fragments with low visual resolution. For results and an appropriate conclusion about prey consumption by a consumer, it is crucial that even rarely consumed prey taxa are being recognized. Thick agarose gels diminish the visibility of potentially low amounts of prey DNA and thus reduce the probability to miss rarely consumed prey and introduce uncertainties in the conclusions drawn from the analysis. Furthermore, from a health perspective, using a less- or non-toxic alternative than ethidium bromide for staining the gels might be advisable. The protocol for subsequent further downstream analysis of amplified fragments via SSCP analyses using polyacrylamide gels includes some steps that should be performed with particular caution. It is important that gel cassette assembled is leak-proof (step 4.1.3) and the polyacrylamide solution is given enough time to polymerize completely (step 4.1.6). Opening the cassette too early will lead to leaking liquid acrylamide solution and, despite the fact that the preparation has to be started from the beginning, extensive cleaning up needs to be done as well. Furthermore, transferring the polyacrylamide gel into the staining bath (step 4.7) and from there onto the UV table (step 4.8) needs to be done very carefully due to the instability of such gels. Otherwise, the gel might tear and fragments could be disrupted, which leads to the necessity to repeat the procedure.</p>
<p class="jove_content">One major requirement for successfully processing data received from automated fragment analyses is that the sample&#39;s internal size standard closely matches the size standard pattern given by the manufacturer (step 5.3.3) to enable determination of the appropriate fragment length. This is especially crucial because otherwise, different fragments, labelled with the same fluorescent staining dye, might be assigned to the wrong prey taxa and therefore lead to a complete misjudgment of predator-prey interactions. Furthermore, electropherograms often show background noise. To establish confidence in the interpretation, it is essential that the peaks of the internal size standard are significantly higher than the background noise of the sample. Consequently, peaks for each marker/primer should only be counted if they are significantly higher than the background noise.</p>
<p class="jove_content">This protocol can be modified to detect several groups of prey taxa of interest within various consumers of interest. Admittedly, group-specific primers may not already be available for every potential prey taxon of interest. Nevertheless, group-specific primers are available not only for several freshwater macroinvertebrate taxa<sup class="xref">28</sup>, but also for a broad range of other taxa (<em>e.g.,</em> several marine macroinvertebrate taxa<sup class="xref">16</sup><sup>,</sup><sup class="xref">30</sup> and common taxa of flying insects<sup class="xref">31</sup>). Thereby, the selection of group-specific primer sets suitable to amplify DNA of all the prey species of a given taxon, but unsuccessful in the amplification of DNA from species not belonging to this taxon, is essential<sup class="xref">32</sup>. Many group-specific primers that are now available have been specified for a given range of taxa (<em>e.g.</em>, 130 taxa of freshwater macroinvertebrates common in the River Rhine system<sup class="xref">28</sup>). Therefore, to avoid false-negative or false-positive results, the specificity of such primers should be rechecked for the range of taxa common in the ecosystem of interest prior to their application for target taxa and consumers not included in the range of taxa for which the primers had been established. Furthermore, if those molecular analyses are not to be combined with other analyses of the exact same individual, dissection of the gastrointestinal tract might be skipped.</p>
<p class="jove_content">Nevertheless, dissecting the gastrointestinal tract of larger specimens also prevents failure of DNA extraction because of too much material, and reduces the presence of consumer-DNA in the sample extract. However, studies have shown that using specific blocking primers, which attach to the DNA of the consumer and thereby block it, for the PCR reaction can effectively enhance the amplification of rare sequences in mixed samples<sup class="xref">33</sup>. Therefore, dissection of the gastrointestinal tract can be avoided, even when dealing with larger consumer specimens, by the use of specific blocking primers. For parallel detection of amplicons derived from multiple group-specific primer sets via automated fragment analyses, care should be taken in the choice of staining dye as label. Thereby, primer sets amplifying fragments of approximately the same length should be labelled with clearly distinguishable fluorescent dyes. Moreover, there are a range of capillary electrophoresis systems available from several manufacturers. Some of these systems supposedly allow the determination of multiple fragments even via unspecific dyes. The protocol presented here could easily be adjusted to detect amplified fragments with any of those systems. Apart from that, to reduce the time needed for the analyses, it would be possible to optimize single multiplex-PCR assays to amplify DNA of prey groups of one fragment analysis batch simultaneously (for instance, simultaneous amplification of 12 prey organisms of beetles<sup class="xref">34</sup> or up to six flying insect taxa<sup class="xref">31</sup>).</p>
<p class="jove_content">A potential disadvantage of gut content analyses in general, and therefore also the analyses described in this protocol, is the low temporal resolution. With such methods, it is only possible to identify recently ingested organisms, which might lead to uncertainties in the importance of single prey organisms<sup class="xref">2</sup>. However, we demonstrated that genetic analysis according to this protocol can easily be combined with analyses of stable isotopes (&#948;<sup>15</sup>N and &#948;<sup>13</sup>C) of the exact same consumer specimens<sup class="xref">25</sup><sup>,</sup><sup class="xref">27</sup>. As a time-integrating natural tracer of predator-prey interactions, stable isotope analyses are frequently used to characterise food web structures<sup class="xref">1</sup>, but potential overlapping isotopic values from different prey species often impede an exact definition of predator-prey interactions<sup class="xref">2</sup>. Therefore, using this protocol for genetic analyses in combination with stable isotope analyses to overcome the disadvantages of each method can further our understanding of food webs and their relationship to nutrient or energy fluxes.</p>

<p class="jove_content">Predator-prey interactions, which constitute the majority of trophic interactions and food web dynamics, are key aspects to characterize the fluxes of matter and energy throughout food webs within and between ecosystems, which is one of the major goals of ecology<sup class="xref">1</sup>. The determination of the source and flow of carbon and nutrients is furthering the understanding of ecological connectivity between ecosystems<sup class="xref">2</sup>. However, ecosystems, such as rivers and their catchments, are not only linked by fluxes of organic matter and nutrients but also by the movements of organisms<sup class="xref">3</sup>. Thus, habitat alterations interrupting the flow of resources that link those systems can strongly alter the food webs of both ecosystems, not only directly but also indirectly by changing the respective composition of predator-prey communities. For instance, changes of food webs have been shown to be linked to the movements of single predator species (<em>e.g.</em>, rainbow trout)<sup class="xref">4</sup>. Such changes potentially threaten biodiversity and the functioning of aquatic ecosystems. Therefore, analyzing predator-prey interactions in the field is essential to determine the impact of human-induced environmental changes, such as water management practices, on the native biodiversity of aquatic ecosystems.</p>
<p class="jove_content">Since tracking trophic linkages is difficult in complex systems, several approaches have been established that enable the assessment of feeding interactions in the field<sup class="xref">5</sup>. Traditionally, investigations of feeding interactions in the field are based on visual identification of prey remains in dissected guts and require an extensive knowledge about morphologic prey diversity. Visual gut content analyses have provided insights in resource use of several groups of consumers (<em>e.g.,</em> seasonal variation in diet of lobster<sup class="xref">6</sup> and fish<sup class="xref">7</sup><sup>,</sup><sup class="xref">8</sup> or feeding preferences of copepods). However, the physical process of digestion makes visual gut content analyses difficult and usually misses soft bodied prey-organisms<sup class="xref">9</sup>. For species feeding by liquid ingestion or for some invertebrate consumers that intensively comminute their food before ingestion, like amphipods, visual identification of prey species in gut contents is impossible<sup class="xref">10</sup>. Due to these limitations, molecular analysis provides a promising alternative.</p>
<p class="jove_content">Molecular analyses have now become a common tool allowing rapid and precise prey detection in gut contents. The range of such techniques is diverse: strategies based on monoclonal antibodies or polymerase chain reactions (PCR) are often used, because of their high specificity and sensitivity<sup class="xref">11</sup>. The development of new monoclonal antibodies is time- and cost-intensive, therefore, the application of other molecular techniques is more useful when antibodies do not already exist<sup class="xref">11</sup>. Another common approach is the amplification of regions of deoxyribonucleic acid (DNA), like ribosomal ribonucleic acid (RNA) genes present in most species, using universal primer sets<sup class="xref">12</sup><sup>,</sup><sup class="xref">13</sup>. When using this technique, it is often not possible to identify the whole range of prey organisms within mixed sources of DNA<sup class="xref">14</sup>. An effective approach to avoid such a drawback is to use group-specific primer sets for genetic gut content analyses. Designed to amplify only DNA regions of particular target groups and exclude all other species<sup class="xref">15</sup><sup>,</sup><sup class="xref">16</sup>, group-specific primers enable identification of prey organisms on the taxonomic level of the specified groups without time- and cost-intensive secondary analyses. However, like all gut content analysis, such analyses provide only a snapshot of feeding behavior. Therefore, combining molecular gut content analyses with analyses of time-integrating natural tracers (<em>e.g.,</em> stable isotopes) is considered beneficial<sup class="xref">1</sup><sup>,</sup><sup class="xref">2</sup>.</p>
<p class="jove_content">Here, we describe a detailed method for PCR-based investigations of predator-prey interactions using group-specific primer sets for nuclear ribosomal DNA (rDNA) regions to be combined with stable isotope analyses of the same specimen. We describe the detection of the DNA of single prey groups via agarose gel electrophoresis. Additionally, we present an opportunity for further downstream analyses of PCR products of such group-specific primers applicable whenever a higher taxonomic resolution than the primers&#39; specificity is required. Because single stranded DNA (ssDNA) fragments form tertiary conformations that are determined by their primary sequence<sup class="xref">17</sup>, small variations in fragments amplified by such group-specific primers lead to conformational changes. Such changes can be detected by single strand conformation polymorphism (SSCP) analyses with polyacrylamide gels<sup class="xref">17</sup><sup>,</sup><sup class="xref">18</sup>, enabling a more precise identification of prey organisms (down to the species level).</p>
<p class="jove_content">While agarose gel electrophoresis is a common and inexpensive tool to visualize DNA fragments and determine their approximate length<sup class="xref">19</sup>, the resolution depends on the amount of DNA and the staining dye used<sup class="xref">20</sup>. Usually, the visualization is straight forward when working with pure DNA samples, but potentially low amounts of prey DNA in the gut contents of consumers can complicate the scoring of agarose gel electrophoresis results. Still, this detection method is feasible to screen a low number of consumer specimens from the field for one or a few prey groups, but complication in the scoring makes the screening of a high number of samples for multiple prey taxa extremely time intensive and thus impracticable. A more sensitive detection method is the automated analysis of fragments via capillary electrophoresis, which additionally allows the determination of the exact length of fragments<sup class="xref">21</sup>. Several microsatellite based studies have shown that by using different fluorescent dyes as labels, it is possible to detect and determine different fragments of comparable length by automated fragment analysis<sup class="xref">22</sup><sup>,</sup><sup class="xref">23</sup><sup>,</sup><sup class="xref">24</sup>. Therefore, we also present a detailed protocol for parallel detection of DNA from multiple prey groups using PCR with labeled group-specific primer sets and detection via automated fragment analysis with an automated sequencer. Additionally, we present results from a case study demonstrating that the detection of prey DNA via automated fragment analysis is an approach which also enables a relative quantification of ingested prey.</p>

<table><tbody><tr><td>liquid nitrogen</td><td>Any</td><td>NA</td><td>For transport of field samples of macroinvertebrates to the laboratory.</td></tr><tr><td>1.5 ml reaction tubes - Safelock</td><td>Any</td><td>NA</td><td>For collection of consumer specimens in the field and subsequent conservation in liquid nitrogen reaction tubes do not necessarily need to be PCR clean. To avoid exploding of the tubes, the lid of the tubes should be punctured with a needle.</td></tr><tr><td>Stereomicroscope</td><td>Any</td><td>NA</td><td>Make sure magnification is suitable to prepare the gastro-intestinaltract of the size of consumer of interest.</td></tr><tr><td>Petri dishes</td><td>Any</td><td>NA</td><td>To dissect the gastro-intestinal tract of consumer specimens under the stereomikroscope.</td></tr><tr><td>Stainless steel foceps: Dumont forceps No. 7</td><td>Bioform</td><td>B40d</td><td>This curved stainless steel forceps can sometimes be very helful to hold specimen fixed inbetween the curved part without puncturing the gastro-intestinal tract.</td></tr><tr><td>Stainless steel foceps: Dumont forceps Electronic No. 5</td><td>Bioform</td><td>B40b</td><td>This fine stainless steel forceps is ideally suited for the preparation of the gastro-intestinal tract of consumer specimens.</td></tr><tr><td>DNA-ExitusPlus</td><td>AppliChem</td><td>A7409,1000RF</td><td>Decontamination solution for the removal of DNA and RNA contaminations</td></tr><tr><td>fuzz-free paper towel</td><td>Any</td><td>NA</td><td></td></tr><tr><td>Lab scale</td><td>Any</td><td>NA</td><td>Precision needs to be at least 0.01 g.</td></tr><tr><td>Microlitre pipettes (0.5-10/10-100/50-200/100-1000 &amp;mu;L)</td><td>Any</td><td>NA</td><td></td></tr><tr><td>Safe-Lock Tubes 2.0 ml</td><td>VWR</td><td>211-2165</td><td>It is crucial that these raction tubes are free of DNA, DNase, RNase and PCR inhibitors (PCR clean)!</td></tr><tr><td>Safe-Lock Tubes 1.5 ml</td><td>VWR</td><td>211-2164</td><td>It is crucial that these raction tubes are free of DNA, DNase, RNase and PCR inhibitors (PCR clean)!</td></tr><tr><td>Sodium chloride &amp;ge;99.5%, p.a., ACS, ISO</td><td>carlroth</td><td>3957.3</td><td>For salt extraction buffer (SEB) and 5M NaCl-solution required for extraction of DNA.</td></tr><tr><td>Tris(hydroxymethyl)-aminomethane Tris</td><td>carlroth</td><td>4855.2</td><td>For salt extraction buffer (SEB) and TBE buffer</td></tr><tr><td>Microlitre pipettes (0.5-10/10-100/50-200/100-1000 &amp;mu;L)</td><td>carlroth</td><td>8043.1</td><td>For salt extraction buffer (SEB) and TBE buffer</td></tr><tr><td>Boric acid &amp;ge;99.8 %, p.a., ACS, ISO</td><td>carlroth</td><td>6943.2</td><td>For TBE buffer. Not needed if commercialy available TBE buffer is obtained.</td></tr><tr><td>Sodium dodecyl sulfate (SDS)</td><td>carlroth</td><td>4360.1</td><td>For extraction of DNA</td></tr><tr><td>Proteinase K lyophil.</td><td>carlroth</td><td>7528.1</td><td>Prepare a working solution containing 10 mg/ml.</td></tr><tr><td>TissueLyser II</td><td>Quiagen</td><td>85300</td><td>Bead mill for homogenization of the samples.</td></tr><tr><td>Stainless Steel Beads, 5 mm</td><td>Quiagen</td><td>69989</td><td>For homogenization of samples.</td></tr><tr><td>Heating Thermoshaker</td><td>Any</td><td>NA</td><td></td></tr><tr><td>Vortex Mixer</td><td>Any</td><td>NA</td><td></td></tr><tr><td>Refrigerated centrifuge: himac CT 15 RE</td><td>Hitachi</td><td>NA</td><td>Refrigerated centrifuge used for centrifugation during the extraction of DNA (Protocol 1).</td></tr><tr><td>Isopropanol</td><td>carlroth</td><td>6752.5</td><td></td></tr><tr><td>Ethanol 99.8 %, p.a.</td><td>Any</td><td>NA</td><td></td></tr><tr><td>Water Molecular biology grade (ddH&lt;sub&gt;2&lt;/sub&gt;O)</td><td>AppliChem</td><td>A7398,1000</td><td>nuclease-free (stream sterilized and DEPC treated) water used for re-suspension of DNA and whenever refered to ddH&lt;sub&gt;2&lt;/sub&gt;O within the manuscript</td></tr><tr><td>Unmodified Olegonucleotides</td><td>Eurofins MWG Operon</td><td>NA</td><td>Primers unlabeled</td></tr><tr><td>Modified olegonucleotides</td><td>Metabion International AG</td><td>NA</td><td>Primers labelled</td></tr><tr><td>peqGOLD Taq all inclusive</td><td>VWR Peqlab</td><td>01-1000</td><td>Taq all inclusive for PCR reaction mixtures (reaction buffer Y and S, dNTPs and MgCl2)</td></tr><tr><td>Primus 96 advanced gradient thermocycler or peqStar96x Universal Gradient</td><td>Peqlab</td><td>NA</td><td>Primer sets were originally established on a Primus 96 advanced gradient thermocycler. As this cycler was quite old, we than checked if our primer sets are efficient and specific under the same conditions using the peqSta96x (which also could simulate the older model). However, tests showed that our primers work well and are still specific (see Koester et al. 2013) without using the simulation of the old machine.</td></tr><tr><td>Standard 96 Well PCR Plates</td><td>VWR Peqlab</td><td>732-2879</td><td>Used for PCR reactions.</td></tr><tr><td>Low Profile Tube Stripes 0.15 ml with Flat Cap Stripes</td><td>VWR Peqlab</td><td>732-3223</td><td>Cap stripes used to close the PCR plates.</td></tr><tr><td>Agarose</td><td>Peqlab</td><td>35-1020</td><td>Used for gel electrophoresis.</td></tr><tr><td>Microwave</td><td>Any</td><td>NA</td><td></td></tr><tr><td>Conical flask</td><td>Any</td><td>NA</td><td></td></tr><tr><td>Measuring cylinder</td><td>Any</td><td>NA</td><td></td></tr><tr><td>Horizontal electrophoresis unit and respective combs with teeth</td><td>Any</td><td>NA</td><td>For agarose gel electrophoresis.</td></tr><tr><td>Electrophoresis Power Supply PS3002</td><td>Life Technologies</td><td>NA</td><td></td></tr><tr><td>Ethidium bromide solution 1 %</td><td>carlroth</td><td>2218.1</td><td>Used to prepare staining bath for agarose gels.</td></tr><tr><td>Formamide</td><td>carlroth</td><td>6749.1</td><td>Needded for the denaturation buffer for SSCP analyses.</td></tr><tr><td>Bromphenol blue</td><td>AppliChem</td><td>A3640.0010</td><td>Needed for the loading dye for agarose gel electrophoresis.</td></tr><tr><td>Sucrose</td><td>carlroth</td><td>4621.1</td><td>Needed for the loading dye for agarose gel electrophoresis.</td></tr><tr><td>100 bp-DNA-Ladder extended</td><td>carlroth</td><td>T835.1</td><td>As size standard for agarose gel electrophoresis.</td></tr><tr><td>UV-Documentation system</td><td>Any</td><td>NA</td><td>To visualize gel electrophoresis results.</td></tr><tr><td>Rotiphorese NF-Acrylamide/Bis-solution 40 % (29:1)</td><td>carlroth</td><td>A121.1</td><td>For the preparation of polyacrylamid gels.</td></tr><tr><td>Ammonium peroxydisulphate</td><td>carlroth</td><td>9592.2</td><td>For the preparation of polyacrylamid gels.</td></tr><tr><td>foldback clips (32 mm)</td><td>Any</td><td>NA</td><td>For the preparation of polyacrylamid gels.</td></tr><tr><td>square-shaped plastic box (21 &amp;times; 6.5 &amp;times; 5 cm)</td><td>Any</td><td>NA</td><td>For the preparation of polyacrylamid gels.</td></tr><tr><td>Tetramethylethylenediamine (TEMED)</td><td>carlroth</td><td>23.67.1</td><td>For the preparation of polyacrylamid gels.</td></tr><tr><td>Beaker</td><td>Any</td><td>NA</td><td></td></tr><tr><td>RC 10 Digital chiller</td><td>VWR</td><td>462-0138</td><td>For SSCP analyses using polyacrylamide gel electrophoresis.</td></tr><tr><td>Vertical electrophoresis unit P10DS (OWL Separation Systems)</td><td>VWR</td><td>700-2361</td><td>For SSCP analyses using polyacrylamide gel electrophoresis.</td></tr><tr><td>Notched glass plate</td><td>VWR</td><td>730-0261</td><td>For SSCP analyses using polyacrylamide gel electrophoresis.</td></tr><tr><td>Blank glass plate</td><td>VWR</td><td>730-0260</td><td>For SSCP analyses using polyacrylamide gel electrophoresis.</td></tr><tr><td>Spacers</td><td>VWR</td><td>730-0262</td><td>For SSCP analyses using polyacrylamide gel electrophoresis.</td></tr><tr><td>Comb with 25 teeth</td><td>VWR</td><td>730-0294</td><td>For SSCP analyses using polyacrylamide gel electrophoresis.</td></tr><tr><td>Shaking platform</td><td>Any</td><td>NA</td><td>For constant shaking of the staining bath.</td></tr><tr><td>GelStar Nucleic Acid Stain (Lonza Rockland, Inc.)</td><td>Biozym</td><td>850535 (50535)</td><td>For staining of polyacrylamide gels.</td></tr><tr><td>GenomeLab DNA Size Standard Kit 400bp</td><td>AB Sciex</td><td>608098</td><td>For automated fragment analyses. Size stanard for Batch B.</td></tr><tr><td>GenomeLab DNA Size Standard Kit 600bp</td><td>AB Sciex</td><td>608095</td><td>For automated fragment analyses. Size stanard for Batch A.</td></tr><tr><td>Sample Loading Solution (SLS)</td><td>AB Sciex</td><td>608082</td><td>For automated fragment analyses.</td></tr><tr><td>Sequenzing plate - 96 Well Polypropylene PCR Microplate</td><td>Costar</td><td>6551</td><td>For automated fragment analyses.</td></tr><tr><td>Plate centrifuge, PerfectSpin P</td><td>VWR Peqlab</td><td>NA</td><td>mini plate centrifuge used to spin down PCR products.</td></tr><tr><td>Buffer plate - 96 Well EIA/RIA Clear Flat Bottom Polystyrene Not Treated Microplate</td><td>Corning</td><td>9017</td><td>For automated fragment analyses.</td></tr><tr><td>GenomeLab Seperation buffer</td><td>AB Sciex</td><td>608012</td><td>For automated fragment analyses.</td></tr><tr><td>Separation Gel - LPAI</td><td>AB Sciex</td><td>608010</td><td>For automated fragment analyses.</td></tr><tr><td>Sequenzer - CEQ8000 Genetic Analysis System</td><td>Beckman Coulter</td><td>NA</td><td>For automated fragment analyses.</td></tr><tr><td>GeneMarker V1.95</td><td>Softgenetics</td><td>NA</td><td>To analyze results of automated fragment analyses.</td></tr></tbody></table>

laboratory protocol for genetic gut content analyses of aquatic macroinvertebrates using group-specific rdna primers

<p class="jove_content">Analyzing food webs is essential for a better understanding of ecosystems. For example, food web interactions can undergo severe changes caused by the invasion of non-indigenous species. However, an exact identification of field predator-prey interactions is difficult in many cases. These analyses are often based on a visual evaluation of gut content or the analysis of stable isotope ratios (&#948;<sup>15</sup>N and &#948;<sup>13</sup>C). Such methods require comprehensive knowledge about, respectively, morphologic diversity or isotopic signature from individual prey organisms, leading to obstacles in the exact identification of prey organisms. Visual gut content analyses especially underestimate soft bodied prey organisms, because maceration, ingestion and digestion of prey organisms make identification of specific species difficult. Hence, polymerase chain reaction (PCR) based strategies, for example the use of group-specific primer sets, provide a powerful tool for the investigation of food web interactions. Here, we describe detailed protocols to investigate the gut contents of macroinvertebrate consumers from the field using group-specific primer sets for nuclear ribosomal deoxyribonucleic acid (rDNA). DNA can be extracted either from whole specimens (in the case of small taxa) or out of gut contents of specimens collected in the field. Presence and functional efficiency of the DNA templates need to be confirmed directly from the tested individual using universal primer sets targeting the respective subunit of DNA. We also demonstrate that consumed prey can be determined further down to species level via PCR with unmodified group-specific primers combined with subsequent single strand conformation polymorphism (SSCP) analyses using polyacrylamide gels. Furthermore, we show that the use of different fluorescent dyes as labels enables parallel screening for DNA fragments of different prey groups from multiple gut content samples via automated fragment analysis.</p>

<p class="jove_content" fo:keep-together.within-page="1">We successfully used steps described in this protocol for diet analyses within different studies. In this section, we present examples describing the applicability of the different sections of the protocol.</p>
<p class="jove_content" fo:keep-together.within-page="1">As an example, to demonstrate the effectiveness of group-specific primer sets established by the authors<sup class="xref">28</sup> and the potential of further downstream analyses of PCR products by SSCP analyses, a feeding experiment was conducted. Individuals of <em>Dikerogammarus villosus</em> as predators and <em>Caenis</em> spp. larvae as prey were captured in the River Rhine and backwaters near Karlsruhe (Germany). In the laboratory, predator and prey taxa were kept separately in filtered stream water at 20 &#176;C and were starved for 36 hours. For the experiment, amphipod specimens were placed in beakers with filtered stream water (100 mL) individually, fed with two to three <em>Caenis</em> larvae for 30 min, and subsequently frozen in liquid nitrogen. The gastrointestinal tract of each <em>D. villosus</em> was dissected and DNA was extracted as described in Protocol 1. DNA extracts were tested with the Caep28S primer set suitable to detect <em>Caenis</em> spp. using the appropriate PCR protocol<sup class="xref">28</sup> as described in Protocol 3. To verify differences between amplified fragments of different <em>Caenis</em> species, PCR was conducted with the gut content samples and pure DNA samples of three <em>Caenis</em> reference species. Agarose gel electrophoresis led to single bands of double stranded DNA, which cannot be distinguished between the different<em> Caenis</em> species with this type of electrophoresis (<strong class="xfig">Figure 2A</strong>). In contrast, by SSCP gel electrophoresis, as described in Protocol 4, it was possible to identify prey organisms to species level by comparing the gut content samples with the reference samples (<strong class="xfig">Figure 2B</strong>). The SSCP fragment pattern of the three reference taxa <em>Caenis beskidensis</em> (<strong class="xfig">Figure 2B</strong>, lane 1), <em>Caenis horaria </em>(<strong class="xfig">Figure 2B</strong>, lane 2)<em>,</em> and <em>Caenis luctuosa</em>&#160;(<strong class="xfig">Figure 2B</strong>, lane 3) consisted of four bands with differentiable patterns. Two gut content samples (<strong class="xfig">Figure 2B</strong>, lane 4 and 5) had a fragment pattern equal to that of <em>C. luctuosa</em> (<strong class="xfig">Figure 2B</strong>, lane 3). The fragment pattern of the third gut content sample (<strong class="xfig">Figure 2B</strong>, lane 6) was identical to that of <em>C. horaria</em> (<strong class="xfig">Figure 2B</strong>, lane 2). Sequence analyses of the two gut content samples identified as <em>C. luctuosa</em> and <em>C. horaria</em> (<strong class="xfig">Figure 2B</strong>, lane 4 and 6) and the respective reference species verified this result (see electronical supplement alignment fasta file).</p>
<p class="jove_content" fo:keep-together.within-page="1"><img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/56132/56132fig2.jpg" /><br />
<strong>Figure 2:</strong> Original image of (<strong>A</strong>) agarose gel electrophoresis and (<strong>B</strong>) SSCP analysis of PCR fragments of gut content and reference samples amplified with the Caep28S primer set. Lanes 1-3 show the reference samples of the species <em>Caenis beskidensis</em> (1), <em>Caenis horaria</em> (2) and <em>Caenis luctuosa</em> (3). In lanes 4-6, the fragment pattern of different gut content samples of the amphipod <em>Dikerogammarus villosus</em> are presented. Lane 7 shows the fragment pattern of a 100 bp DNA ladder. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56132/56132fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a></p>
<p class="jove_content" fo:keep-together.within-page="1">Furthermore, a laboratory experiment was conducted in which water mites belonging to the species <em>Hygrobates fluviatilis </em>were fed on chironomid larvae to not only determine if DNA of chironomid individuals consumed can be detected in the water mites, but also to test if the amount of DNA detected depends on the elapsed time since consumption of the prey<sup class="xref">29</sup>. After starving the mites for approximately one week, each mite was offered one chironomid larva as food. Each 3-4 water mite individuals were fixed in ethanol (absolute) for genetic analysis using the Chiro18S primer set specific to the dipteran family Chironomidae<sup class="xref">28</sup> at 1, 2, 3, 7, 9, 24, 32 and 50 h after being fed<sup class="xref">29</sup>. As a degree of consumption by the water mite individuals, the respective prey individuals were classified into the following five feeding categories: 1 = completely sucked out, integument completely emptied (&#62;90%), 2 = almost completely sucked out (&#62;75-90%), 3 = semi sucked out (&#62;50-75%), 4 = only partially sucked out (&#62;5-50%), 5 = no visible change in the prey&#39;s body structure (&#8804;5%)<sup class="xref">29</sup>. DNA was extracted from the water mites as described in Protocol 1 (without steps 1.2.1 and 1.2.2) and the presence of 18S rDNA in the extract and the functional efficiency of the template were verified as described in Protocol 2. Detection of prey DNA was performed according to Protocol 4 using only the Chiro18S primer set with the forward primer labeled with a fluorescent dye (see <strong>Table 2</strong>) and the DNA Size Standard Kit - 400. To allow comparisons between samples analysed within different runs of an automated sequencer, the ratio between sample peak height and the peak height of the nearest internal standard (<em>i.e.</em>, 360 bp in this case) of each sample were calculated and used as a proxy for the amount of DNA detected. Results showed that chironomid DNA was detectable in virtually all individuals of <em>Hygrobates fluviatilis </em>fed on chironomid larvae<sup class="xref">29</sup>. From the shortest interval (1 h after feeding) to the longest period after feeding (50 h) the relative amount of detected prey DNA was significantly reduced (<strong class="xfig">Figure 3A</strong>)<sup class="xref">29</sup>. Furthermore, the relation between time after feeding and the prey classification as a proxy for the ingested amount of prey DNA could be confirmed (<strong class="xfig">Figure 3B</strong>)<sup class="xref">29</sup>. The reduction of prey DNA detected with increasing time after feeding was most likely completely reflected by the degradation of DNA and digestion of the prey, because egestion of prey DNA is highly implausible due to the lack of an anus in water mites<sup class="xref">29</sup>. These results confirm the suitability of this approach for the quantification of ingested prey.</p>
<p class="jove_content" fo:keep-together.within-page="1"><img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/56132/56132fig3.jpg" /><br />
<strong>Figure 3:</strong> Relationships between the national ln height-ratio (sample-peak heights/standard<sub>360</sub> peak height) and (<strong>A</strong>) time after feeding of mites and (<strong>B</strong>) feeding category (n = 23). &#34;Experimental and Applied Acarology, First detection of prey DNA in <em>Hygrobates fluviatilis</em> (Hydrachnidia, Acari): a new approach for determining predator-prey relationships in water mites, 67, 376, P. Martin, M. Koester, L. Schynawa, R. Gergs, (&#169; Springer International Publishing Switzerland 2015)&#34; With permission of Springer. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56132/56132fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a></p>
<p class="jove_content" fo:keep-together.within-page="1">To investigate the importance of predation by the invasive amphipod <em>D. villosus</em> in the field, intensive stable isotope analyses of &#948;<sup>13</sup>C and &#948;<sup>15</sup>N of <em>D. villosus</em> and potential food resources were furthered by molecular detection of recently ingested prey within the gut contents of the exact same individuals. In total, 206 <em>D. villosus</em> individuals from different sites were collected and the gastrointestinal tract of each individual was dissected and DNA was extracted according to Protocol 1. The presence and functional efficiency of the templates used was assured as described in Protocol 2. Recent predation by the <em>D. villosus</em> individuals on multiple macroinvertebrate prey taxa was tested as described in Protocol 4. Overall, only 16% of the <em>D. villosus</em> gut contents tested positive for DNA belonging to any of the 16 targeted macroinvertebrate prey taxa, and therefore supported the results of the stable isotope analyses that indicated a low predacious feeding behavior of the invasive amphipod in the field<sup class="xref">27</sup>. While, within the genetic analyses, DNA of 12 tested prey taxa was found in at least 1 gut content sample, DNA of the 4 other prey taxa was never detected (<strong class="xfig">Figure 4</strong>)<sup class="xref">27</sup>.</p>
<p class="jove_content" fo:keep-together.within-page="1"><img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/56132/56132fig4.jpg" /><br />
<strong>Figure 4:</strong> <strong>Histogram illustrating the respective number of <em>D. villosus</em> individuals from all ten sites whose gut contents tested positive for macroinvertebrate prey DNA.</strong> PCR was carried out with 16 group-specific primer sets as indicated. &#34;Hydrobiologia, Is <em>Dikerogammarus villosus</em> (Crustacea, Gammaridae) a &#39;killer shrimp&#39; in the River Rhine system?, 768, 2016, 310, Koester Meike, Bayer Bastian, Gergs Ren&#233;, (&#169; Springer International Publishing Switzerland 2015)&#34; With permission of Springer. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56132/56132fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a></p>
<p class="jove_content" fo:keep-together.within-page="1"><strong>Supplemental File. </strong>Sequence_alignement_feeding_trial.fasta <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56132/Sequence_alignement_feeding_trial.fasta" target="_blank">Please click here to download this file.</a></p>

Watch this Scientific Journal Video about Laboratory Protocol for Genetic Gut Content Analyses of Aquatic Macroinvertebrates Using Group-specific rDNA Primers at JoVE.com

Laboratory Protocol for Genetic Gut Content Analyses of Aquatic Macroinvertebrates Using Group-specific rDNA Primers

<p class="jove_content">Most common gut content analyses of macroinvertebrates are visual. Requiring intense knowledge about morphological diversity of prey organisms, they miss soft bodied prey and, due to strong comminution of prey, are nearly impossible for some organisms, including amphipods. We provide detailed, novel genetic approaches for macroinvertebrate prey identification in the diet of amphipods.</p>

Analyzing food webs is essential for a better understanding of ecosystems. For example, food web interactions can undergo severe changes caused by the ...

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8.8K Views.  University of Koblenz-Landau. Most common gut content analyses of macroinvertebrates are visual. Requiring intense knowledge about morphological diversity of prey organisms, they miss soft bodied prey and, due to strong comminution of prey, are nearly impossible for some organisms, including amphipods. We provide detailed, novel genetic approaches for macroinvertebrate prey identification in the diet of amphipods.

Video: Laboratory Protocol for Genetic Gut Content Analyses of Aquatic Macroinvertebrates Using Group-specific rDNA Primers

Evolutionary Relationships

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">Forming an Evolutionary Hypothesis
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">NOTE: A cladogram is an important tool for forming an evolutionary hypothesis. A cladogram is a tree-shaped chart used to depict the hypothetical genealogical relationships between species. The tips or leaves of the chart represent specific species and the branches of the tree are different lengths. The different lengths represent the degree of change between each of the species. The common ancestor of all of the species that a specific line branches from is located at a node, where the branches intersect. Species that share a node are called a sister group.
</div></li><li data-sub-note-item="1-2"><div class="lab-step">To begin, look at the provided blank cladogram and make a hypothesis about where the assigned animals should be placed on the tree. If a blank cladogram has not been provided please <a target="_blank" href="/files/ftp_upload/10562/Blank_Cladogram.png">download one here</a>.
</div></li><li data-sub-note-item="1-3"><div class="lab-step">Next, observe the image of the fossilized animal.
</div></li><li data-sub-note-item="1-4"><div class="lab-step">Using the morphology, or physical characteristics, of the fossil, make a hypothesis about where on your cladogram it should be placed. Add a new line or mark to indicate your proposed position for the fossil.
</div></li></ul></li><li data-note-item="2" data-parent-collapse="">Comparing Gene Sequences Using BLAST
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="2-1"><div class="lab-step">NOTE: Historically, cladograms have been constructed through the comparison of morphology. Now, genetic sequences can also be compared between species of interest to construct cladograms. DNA sequences are not usually preserved in fossils, so for this lab you will use the BLAST database to compare the DNA sequences of living species that are closely related to the fossil to thousands of other living species.
</div></li><li data-sub-note-item="2-2"><div class="lab-step">Before beginning this lab, your instructor will have downloaded the three preserved gene sequences to a folder on your desktop.
</div></li><li data-sub-note-item="2-3"><div class="lab-step">Navigate to the BLAST homepage, which the instructor should have left open in your browser, and click on Saved Strategies from the menu at the top of the page.
</div></li><li data-sub-note-item="2-4"><div class="lab-step">Click Open on the Evolutionary_Relationships_Gene1.txt file.
</div></li><li data-sub-note-item="2-5"><div class="lab-step">Then, click View to go to the Standard Nucleotide BLAST search page. You should be able to see the DNA sequence in the Query Sequence box at the top-right of the screen.
</div></li><li data-sub-note-item="2-6"><div class="lab-step">Scroll to the bottom of the screen and click the BLAST button. Note: It will take a few moments to process and analyze the data. 
</div></li><li data-sub-note-item="2-7"><div class="lab-step">When the data has been processed, a graphic summary will appear.  NOTE: Your query sequence is represented by the blue line at the top of the box. Each of the lines below the blue line represents another sequence in the BLAST database that matches your query. The length and location of these bars represent where and how much of the sequence match up to the query. The color of the bar represents its score, or how identical the sequence is to the query. Below the graphic summary is the Sequences producing significant alignments list, which contains descriptions of the DNA sequences retrieved from the database that most closely align with the query sentence. These are listed in descending order, from the most similar at the top to the least similar at the bottom. On the right, there are several statistics on how closely related each database sequence is to the experimental sequence. The higher the Max, Total, Query Coverage, and Identity scores are, the more similar the query and retrieved sequences are to each other. Similarly, the lower the E value number, the less likely the sequences match was found by random chance and more significantly the alignment is accurate. An E value of 0 indicates a highly significant match.
</div></li><li data-sub-note-item="2-8"><div class="lab-step">Click on the name of the description of the most similar alignment listed. This will take you further down the page to the exact DNA sequence alignment between the retrieved sequence and the query sequence.
</div></li><li data-sub-note-item="2-9"><div class="lab-step">Click on the Sequence ID number. This will open a new tab with more specific information on the retrieved gene sequence.
</div></li><li data-sub-note-item="2-10"><div class="lab-step">Identify and record the scientific and common names of the organism, which should be listed next to Source.
</div></li><li data-sub-note-item="2-11"><div class="lab-step">Identify and record the protein that the gene codes for, which should be listed next to Definition.
</div></li><li data-sub-note-item="2-12"><div class="lab-step">Close the tab and hit Back to return to the Sequences producing significant alignments list.
</div></li><li data-sub-note-item="2-13"><div class="lab-step">Then, repeat steps 7 &#8211; 9 for the next most similar sequences.
</div></li><li data-sub-note-item="2-14"><div class="lab-step">After collecting several species names, return to the Sequences producing significant alignments list and click Select: All to check all of the boxes next to the names of each listed alignment sequence.
</div></li><li data-sub-note-item="2-15"><div class="lab-step">Click on Distance of tree results to create a phylogram based on the similarity of all of the BLAST result gene sequences to the query gene sequence.  Note: Your query fossil relative sequence will be highlighted in yellow.
</div></li><li data-sub-note-item="2-16"><div class="lab-step">Record your sequence&#8217;s location in relation to the other taxon groups shown in the tree.
</div></li><li data-sub-note-item="2-17"><div class="lab-step">Finally, return to the Saved Strategies tab and upload the next saved gene sequence.
</div></li><li data-sub-note-item="2-18"><div class="lab-step">Query the remaining two fossil relative DNA sequences as previously demonstrated (steps 1 &#8211; 16).
</div></li></ul></li><li data-note-item="3" data-parent-collapse="">Data Analysis
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="3-1"><div class="lab-step">Based on your gene sequence results, come up with a second hypothesis about where your fossil specimen fit in the original cladogram.
</div></li><li data-sub-note-item="3-2"><div class="lab-step">Compare this placement with your first hypothesis.
</div></li><li data-sub-note-item="3-3"><div class="lab-step">Compare your tree with your classmates&#8217;. If any of your classmates put the fossil on a different branch, ask them how they came to that decision.
</div></li></ul></li></ol>

Evolutionary Relationships: Using BLAST to Test Evolutionary Hypotheses - Procedure

Związki ewolucyjne

Forming an Evolutionary Hypothesis
ExpandNOTE: A cladogram is an important tool for forming an evolutionary hypothesis. A cladogram is a tree-shaped chart ...

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JoVE Lab Manual

Evolution

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Microbial and Fungal Diversity

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">Examining Microbial Colony Structures
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">To begin, collect your allocated culture plates and then remove the Parafilm and lid from one of them.
</div></li><li data-sub-note-item="1-2"><div class="lab-step">Place the uncovered plate under a dissecting microscope and then observe the individual communities within each quadrant of the plate.
</div></li><li data-sub-note-item="1-3"><div class="lab-step">As the colonies are identified, fill out the observed colony properties in the appropriate column in the table.  <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/28/Table_1_Microbial_diversity.xlsx" style="display:block;margin:20px;" target="__blank">Click Here to download Table 1</a>
</div></li><li data-sub-note-item="1-4"><div class="lab-step">Then, repeat the observations for each of the other two bacterial species.
</div></li><li data-sub-note-item="1-5"><div class="lab-step">To perform Gram staining of your three bacterial species, first label the ends of three microscope slides with the initials of each bacteria species, your initials, and the date. HYPOTHESES: In this experiment, the experimental hypothesis might be that it is possible to elucidate different bacterial species and shapes using Gram staining, and that Gram-positive bacteria will stain purple with crystal violet whereas Gram-negative bacteria will appear pink due to the safranin counterstain. The null hypothesis could be that all of the bacterial types will retain both stains equally, and staining will not help elucidate their species or shape.
</div></li><li data-sub-note-item="1-6"><div class="lab-step">To begin the first stain, attach a clip to the slide for ease of handling. For each bacterial smear, remember to be sure to use a cleaned and flame-sterilized inoculating loop.
</div></li><li data-sub-note-item="1-7"><div class="lab-step">Place two loopfuls of sterile distilled water onto the center of the slide.
</div></li><li data-sub-note-item="1-8"><div class="lab-step">After sterilizing the loop again, cool the loop by touching an uninoculated portion of the agar several times.
</div></li><li data-sub-note-item="1-9"><div class="lab-step">Then, remove a small amount of culture from an isolated colony and mix it with the water on the slide.
</div></li><li data-sub-note-item="1-10"><div class="lab-step">Allow the slide to dry at room temperature and heat-fix the smear by quickly passing it through a flame.
</div></li><li data-sub-note-item="1-11"><div class="lab-step">Once dry, pipette several drops of crystal violet onto the slide and let it sit for two to three minutes.
</div></li><li data-sub-note-item="1-12"><div class="lab-step">Carefully rinse the slide with distilled water by aiming the direct flow towards the top of the slide, allowing the water to gently flow down. Do not aim the water flow directly at the smear.
</div></li><li data-sub-note-item="1-13"><div class="lab-step">Next, cover the slide with Gram&#39;s iodine, leave it to sit again for two minutes, and then gently rinse with distilled water.
</div></li><li data-sub-note-item="1-14"><div class="lab-step">Decolorize the slide with 95% ethanol until stain no longer washes away.
</div></li><li data-sub-note-item="1-15"><div class="lab-step">Immediately, rinse the slide with distilled water. This will limit over-decolorizing.
</div></li><li data-sub-note-item="1-16"><div class="lab-step">Then, add several drops of safranin counterstain and leave for 30 s. This will stain any Gram-negative cells present.
</div></li><li data-sub-note-item="1-17"><div class="lab-step">Gently rinse the slide with distilled water and blot dry with absorbent paper.
</div></li><li data-sub-note-item="1-18"><div class="lab-step">After staining the other two slides in the same manner (steps 6 &#8211; 17), observe each with a microscope.
</div></li><li data-sub-note-item="1-19"><div class="lab-step">Use a low power objective first to make coarse adjustments. When you find an ideal section, move on to the higher magnifications.
</div></li><li data-sub-note-item="1-20"><div class="lab-step">After further imaging and adjusting the smear with a medium power objective, add immersion oil directly to the smear. NOTE: The oil is needed for high power objectives that will provide the best micrographs.
</div></li><li data-sub-note-item="1-21"><div class="lab-step">Now, use colored pencils to draw the observed bacteria in the appropriate magnification circles and fill in the observed characteristics in the appropriate column, noting the bacteria&#39;s shape and whether it is Gram-positive, identified by darker purple staining, or Gram-negative, identified with pink staining. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/28/Table_2_Microbial_diversity.xlsx" style="display:block;margin:20px;" target="__blank">Click Here to download Table 2</a>
</div></li><li data-sub-note-item="1-22"><div class="lab-step">Finally, repeat the observation, drawing, and characterization for the other two stained bacterial slides.
</div></li></ul></li><li data-note-item="2" data-parent-collapse="">Examining Fungal Structures
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="2-1"><div class="lab-step">Remove the <em>S. cerevisiae</em> plate from the incubator and place a drop of water onto a microscope slide.
</div></li><li data-sub-note-item="2-2"><div class="lab-step">Using a sterilized inoculating loop, smear a film of yeast into the drop of water and place a cover slip over the slide.
</div></li><li data-sub-note-item="2-3"><div class="lab-step">Place the slide under the microscope at the lowest magnification, increasing the magnification to the oil immersion setting to see the individual yeast cells.
</div></li><li data-sub-note-item="2-4"><div class="lab-step">Observe the general shape and structure of the yeast and identify any cells that are undergoing asexual reproduction by budding.
</div></li><li data-sub-note-item="2-5"><div class="lab-step">Now, draw the cells in the appropriate magnification circles.
</div></li><li data-sub-note-item="2-6"><div class="lab-step">When you are done observing the yeast, replace the <em>S. cerevisiae</em> slide with a prepared Ascomycetes apothecium slide and set the microscope to the lowest magnification.
</div></li><li data-sub-note-item="2-7"><div class="lab-step">Using colored pencils, draw the structures at low and high magnifications, including the asci and ascospores.
</div></li><li data-sub-note-item="2-8"><div class="lab-step">Finally, place a button mushroom, <em>Agaricus bisporus</em>, under the dissecting microscope and draw the features, including the pileus, or cap, the gills, and the stipe, or stalk.
</div></li></ul></li><li data-note-item="3" data-parent-collapse="">Results
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="3-1"><div class="lab-step">Using the coloring of the bacteria recorded in the table, determine which species are Gram-positive and which are Gram-negative.
</div></li><li data-sub-note-item="3-2"><div class="lab-step">Then, look at the shapes recorded in the table to determine which bacterial species are bacillus, coccus, or spirillum.
</div></li><li data-sub-note-item="3-3"><div class="lab-step">Next compare your illustrations of the yeast cells to your illustrations of the bacterial cells. NOTE: Yeast from the Ascomycetes phylum, such as <em>S. cerevisiae</em>, can reproduce asexually, which can be observed through the budding of the cells under a microscope.
</div></li><li data-sub-note-item="3-4"><div class="lab-step">Record any observations of yeast cells budding.  NOTE: Ascomycetes can also reproduce sexually via mitosis and haploid spore formation.
</div></li><li data-sub-note-item="3-5"><div class="lab-step">Record any observations of spore or asci formation you observed in the table.
</div></li><li data-sub-note-item="3-6"><div class="lab-step">NOTE: Fungus from the Basidiomycota phylum exhibit clearly observable gills under the pileus.
</div></li><li data-sub-note-item="3-7"><div class="lab-step">Record any fungal species that demonstrated gills under the pileus.
</div></li></ul></li></ol>

Microbial Colony and Fungal Diversity - Procedure

Różnorodność mikrobiologiczna i grzybicza

Examining Microbial Colony Structures
ExpandTo begin, collect your allocated culture plates and then remove the Parafilm and lid from one of them.
Place ...

Species Distribution and Biogeography

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">Simulating Colonization and Extinction on Islands
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">Form groups of three. One member of the group will simulate colonization by throwing balls into the groups of cups representing the islands. Another will simulate extinction by rolling dice to randomly remove balls from the cups. The third group member will record the data.
</div></li><li data-sub-note-item="1-2"><div class="lab-step">Take time to familiarize yourself with the four island stations. NOTE: There are two large islands with 12 cups and two small islands with 6 cups. Two of the stations will have tape lines that are 2 m away from the cups. These are the far islands. The other two stations will have tape lines that are 1 m away from the cups. These are the near islands. Thus, the stations are far large and near large and far small and near small. HYPOTHESES: In this experiment, one alternate hypothesis might be that the larger islands with more cups will support a greater number of species than the smaller islands. The null hypothesis might be that all islands will support this same number of species regardless of size. Another alternate hypothesis might be that islands closer to the mainland will have a higher colonization rate than islands farther from the mainland. The null hypothesis might be that all islands will have the same colonization rate regardless of their distance from the mainland. Additionally, in all trials we may hypothesize that the colonization rate will be expected to decrease as more species inhabit an island whereas the extinction rate will increase as more species are found on the island. The null hypothesis might be that the colonization rate and extinction rates are expected to stay the same across all numbers of species on the island.
</div></li><li data-sub-note-item="1-3"><div class="lab-step">First, choose one of the four stations as a starting place.
</div></li><li data-sub-note-item="1-4"><div class="lab-step">From the line of tape at this location, the colonization simulator must throw the ball to the island and try to get the ball into a cup. NOTE: One round consists of five throws, each throw representing a colonization attempt. If the ball lands in a cup that does not already have a ball in it, this is a successful colonization attempt and the ball should be left in the cup.
</div></li><li data-sub-note-item="1-5"><div class="lab-step">The data collector should place a tally on the colonizers box for the round in the recording sheet found at the station. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/29/Tables_1-4_Island_biogeography.xlsx" style="display:block;margin:20px;" target="_blank">Click Here to download Tables 1-4</a>
</div></li><li data-sub-note-item="1-6"><div class="lab-step">If the ball does not land in a cup, retrieve it. This is an unsuccessful colonization attempt.
</div></li><li data-sub-note-item="1-7"><div class="lab-step">If a ball lands in a cup that already has a ball in it, retrieve it. This is also an unsuccessful colonization attempt.
</div></li><li data-sub-note-item="1-8"><div class="lab-step">Add the number of species at the beginning of the round with the tally of colonizers.
</div></li><li data-sub-note-item="1-9"><div class="lab-step">The data collector should record this number in the column entitled &#8220;Number of species after colonization&#8221; in the recording sheet found at the station.
</div></li><li data-sub-note-item="1-10"><div class="lab-step">The extinction simulator should now roll a die. If the trial is occurring at a large island site, choose one of the two colored dice at random with eyes closed.
</div></li><li data-sub-note-item="1-11"><div class="lab-step">Remove the ball if there is one present from the cup that is of the same color as the die and labeled with the number rolled by that die.
</div></li><li data-sub-note-item="1-12"><div class="lab-step">The data collector should count the removal as an extinction in the station recording table. NOTE: In a trial at the small island station, follow the same procedure except that it is only necessary to match the number rolled by the die to the cup. If there is no ball in the cup, no extinction is recorded. For both the large and small islands, repeat the extinction roll for a total of two rolls if there are 3 - 8 species present on the island and three rolls if there are 9 - 12 species on the island. If there are fewer than three species on the island, do not roll the die again.
</div></li><li data-sub-note-item="1-13"><div class="lab-step">This is the end of one round. After this, count the total number of species currently in the cups at this station and then tally this number into the &#8220;Number of species at beginning of round&#8221; column on the station recording sheet for the next round.
</div></li><li data-sub-note-item="1-14"><div class="lab-step">Groups should switch stations after five rounds at one table to control for the throwing ability of the colonization simulators. Repeat the trials and rotation through the stations until 20 rounds have been recorded in total for all groups combined at all four stations.
</div></li><li data-sub-note-item="1-15"><div class="lab-step">Count the tally marks for the number of species at the beginning of the round, colonizers, total number of species after colonization, and extinctions for each round at each island station.
</div></li><li data-sub-note-item="1-16"><div class="lab-step">Look at your data recording sheet. How many times were there zero species at the beginning of a round? How many times was there only one species at the beginning of a round? Repeat this calculation for 0 through 12 species present at the beginning of a round.
</div></li><li data-sub-note-item="1-17"><div class="lab-step">Then, tally these values in the corresponding rows of the &#8220;Rounds with this many species&#8221; column in the appropriate colonization rate calculation table. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/29/Tables_5-8_Island_biogeography.xlsx" style="display:block;margin:20px;" target="_blank">Click Here to download Tables 5-8</a>
</div></li><li data-sub-note-item="1-18"><div class="lab-step">In the colonization attempts column, multiply these values by five to represent the total number of Ping-Pong balls thrown.
</div></li><li data-sub-note-item="1-19"><div class="lab-step">Look at your data recording sheet once more and calculate the total number of colonizers for each value in the number of species at beginning of round column.
</div></li><li data-sub-note-item="1-20"><div class="lab-step">Record these values in the &#8220;Successful colonization attempts&#8221; column of the appropriate colonization rate calculation table.
</div></li><li data-sub-note-item="1-21"><div class="lab-step">Divide the successful colonization attempts by the colonization attempts for each initial species value and record this in the &#8220;Colonization rate&#8221; column of the appropriate colonization rate calculation table.
</div></li><li data-sub-note-item="1-22"><div class="lab-step">Repeat the process for determining the colonization rate for all of the island trials. 
</div></li><li data-sub-note-item="1-23"><div class="lab-step">To calculate the extinction rate for each of the trials, return to the data recording sheet for the near large island trial. Count the number of times that the number of species after colonization matched each number from 1 to 12, as previously described.
</div></li><li data-sub-note-item="1-24"><div class="lab-step">Record these values in the &#8220;Rounds with this many species&#8221; column in the appropriate extinction rate calculation table. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/29/Tables_9-12_Island_biogeography.xlsx" style="display:block;margin:20px;" target="_blank">Click Here to download Tables 9-12</a>
</div></li><li data-sub-note-item="1-25"><div class="lab-step">To calculate extinction attempts, multiply the value in the &#8220;Rounds with this many species&#8221; cells by 1 if the species after colonization value is 0 &#8211; 2, by 2 if the value is 3 &#8211; 8, and by 3 if the value is 9 or above. NOTE: These values correspond with the number of times the die was rolled during the extinction simulation.
</div></li><li data-sub-note-item="1-26"><div class="lab-step">Then, using the data contained in the data recording sheet, count the number of extinctions that occurred for each value in the &#8220;Number of species after colonization&#8221; column.
</div></li><li data-sub-note-item="1-27"><div class="lab-step">Record these values in the &#8220;Extinctions&#8221; column of the appropriate extinction rate calculation table.
</div></li><li data-sub-note-item="1-28"><div class="lab-step">Record these values in the &#8220;Extinctions&#8221; column of the appropriate extinction rate calculation table.
</div></li><li data-sub-note-item="1-29"><div class="lab-step">Repeat the process for calculating the extinction rate for all of the island trials. 
</div></li><li data-sub-note-item="1-30"><div class="lab-step">After this, plot the colonization and extinction rates versus the number of species for each of the island stations.
</div></li><li data-sub-note-item="1-31"><div class="lab-step">Draw the best-fit lines for the colonization and extinction rates in each of the four graphs.
</div></li><li data-sub-note-item="1-32"><div class="lab-step">Compare the colonization rate between the near and far islands. Determine the distance that had a greater dynamic equilibrium of species and develop a hypothesis to explain your observation. 
</div></li><li data-sub-note-item="1-33"><div class="lab-step">Next, compare the extinction rates between the large and small islands. Determine the size that had a greater dynamic equilibrium number of species.
</div></li><li data-sub-note-item="1-34"><div class="lab-step">Observe the slopes of the colonization rates in the plots. Determine if they are positive or negative. 
</div></li><li data-sub-note-item="1-35"><div class="lab-step">Observe the slopes of the extinction rates in the plots. Determine if they are positive or negative. 
</div></li></ul></li></ol>

Rozmieszczenie gatunków i biogeografia

Simulating Colonization and Extinction on Islands
ExpandForm groups of three. One member of the group will simulate colonization by throwing balls into ...

Ecology

Community Diversity

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">Measuring Biodiversity in Areas with Different Disturbance Regimes
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">NOTE: In this experiment, you will compare the biodiversity in a less disturbed area against a more highly disturbed area. HYPOTHESES: The experimental hypothesis could be that a less disturbed area will contain a greater diversity of species than a highly disturbed area. The null hypothesis could be that there will be no difference in diversity between less disturbed and highly disturbed areas. 
</div></li><li data-sub-note-item="1-2"><div class="lab-step">To begin, divide into groups of 2-4 and collect a hula hoop, ball, measuring tape, set of printed tables, 10 utility flags, and an ID guide from the front of the class.
</div></li><li data-sub-note-item="1-3"><div class="lab-step">Additionally, collect a shovel and 10 collecting bottles for the soil sampling exercise.
</div></li><li data-sub-note-item="1-4"><div class="lab-step">Once in the field, your instructor will show you the two habitats you will study - choose one habitat to begin.
</div></li><li data-sub-note-item="1-5"><div class="lab-step">Place one flag in each of four corners to form a rectangular sampling area.
</div></li><li data-sub-note-item="1-6"><div class="lab-step">Measure the length and width of the sampling area in meters, and then multiply the two numbers to determine the area.
</div></li><li data-sub-note-item="1-7"><div class="lab-step">Standing in the middle of the sampling area, throw a tennis ball into the air, and then Mark the location where it lands with a flag.
</div></li><li data-sub-note-item="1-8"><div class="lab-step">Repeat this random throw four additional times to determine all five of your random sampling points.
</div></li><li data-sub-note-item="1-9"><div class="lab-step">Keeping your flag at the center, place a hula hoop around it. The area within the hula hoop is a quadrat.
</div></li><li data-sub-note-item="1-10"><div class="lab-step">Identify all of the different species in the quadrat and record them as species A, B, and so on in Table 1, provided by your instructor.
</div></li><li data-sub-note-item="1-11"><div class="lab-step">Once all of the plants have been recorded, use a shovel to collect one cup of soil from each of the sites and put the samples bottles labeled with your names and the site name and quadrat number.
</div></li><li data-sub-note-item="1-12"><div class="lab-step">Repeat the plant identification and soil sampling for the remaining four quadrats in the first habitat, recording your observations in Table 1.
</div></li><li data-sub-note-item="1-13"><div class="lab-step">Once you have completed recording in the first habitat, move on to the second field, again marking out a rectangular sampling area.
</div></li><li data-sub-note-item="1-14"><div class="lab-step">Repeat the random placement of quadrats using the tennis ball, and then record the species present in each quadrat in Table 2. 
</div></li><li data-sub-note-item="1-15"><div class="lab-step">Finally, collect one cup of soil from each of the disturbed habitats&#39; quadrats, for a total of five cups from the disturbed and five cups from the undisturbed habitats.
</div></li></ul></li><li data-note-item="2" data-parent-collapse="">Measuring Biodiversity Along a Transect
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="2-1"><div class="lab-step">NOTE: The next part of the study will test for edge effects, or a change along a gradient from where one ecosystem type meets another to the core habitat of the ecosystem. HYPOTHESES: The experimental hypothesis is that there will be a greater diversity of species closer to the edge of the ecosystem than in the center, or core, of the ecosystem. The null hypothesis is that there is no change in diversity along the transect from edge to core habitat.
</div></li><li data-sub-note-item="2-2"><div class="lab-step">Place a flag at the perimeter of the field where it meets another habitat, like a forest or parking lot.
</div></li><li data-sub-note-item="2-3"><div class="lab-step">Extend a tape measure towards the center of the field, perpendicular to the edge of the field. This will be the transect.
</div></li><li data-sub-note-item="2-4"><div class="lab-step">Place a flag at the zero meter of the transect (the edge of the other habitat) then place additional flags at 10 m, 20 m, 30 m, and 40 m into the core of the habitat for a total of five flagged locations.
</div></li><li data-sub-note-item="2-5"><div class="lab-step">Starting at the 0 m point along the transect, place the hula hoop at the flagged location. Record the species present in the quadrat in Table 4.
</div></li><li data-sub-note-item="2-6"><div class="lab-step">Now repeat the quadrant placement and species recording at the 10 m, 20 m, 30 m, and 40 m marks.
</div></li><li data-sub-note-item="2-7"><div class="lab-step">Next, place two more transects from different starting points at the perimeter of the field extending into the core area.
</div></li><li data-sub-note-item="2-8"><div class="lab-step">Mark the 10-meter points along these transects, and again use these as markers to place quadrats. Record the species found in each of these quadrats in Table 4.
</div></li></ul></li><li data-note-item="3" data-parent-collapse="">Processing the Soil Samples
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="3-1"><div class="lab-step">HYPOTHESES: The experimental hypothesis is that the two landscapes under different disturbance regimes will differ in their soil composition and pH. The null hypothesis is that there will be no difference in the soil composition or pH between the two sites. 
</div></li><li data-sub-note-item="3-2"><div class="lab-step">To begin, remove soil from one bottle of the first site sampled and fill the pH color compartment of the soil sample kit to the soil fill line.
</div></li><li data-sub-note-item="3-3"><div class="lab-step">Pour the pH test capsule into the test chamber, then fill the capsule with distilled water until it reaches the water fill line.
</div></li><li data-sub-note-item="3-4"><div class="lab-step">Place the cap on the compartment and shake it.
</div></li><li data-sub-note-item="3-5"><div class="lab-step">Allow the color to develop for about a minute, and then compare the soil to the color chart to determine the pH.
</div></li><li data-sub-note-item="3-6"><div class="lab-step">Repeat the pH analysis for the second sampled site, filling out Table 3 for the recorded pH.
</div></li><li data-sub-note-item="3-7"><div class="lab-step">To process the soil samples for nitrogen, phosphorus, and potassium, remove 20 mL of soil from the bottle of the first site sampled.
</div></li><li data-sub-note-item="3-8"><div class="lab-step">Place the soil in a clean container with 100 mL of distilled water.
</div></li><li data-sub-note-item="3-9"><div class="lab-step">Repeat this process for the second site, labeling each container, and then allow them to sit for one hour.
</div></li><li data-sub-note-item="3-10"><div class="lab-step">After one hour, use a dropper to fill each of the nitrogen, phosphorous, and potassium comparators to the fill line with solution from the first sampled site.
</div></li><li data-sub-note-item="3-11"><div class="lab-step">Add the appropriate capsule to each of the comparators for each chemical test.
</div></li><li data-sub-note-item="3-12"><div class="lab-step">Cap and shake the comparators thoroughly, and then compare the solution in the test chamber to the color chart, recording the results as the appropriate number on the scale into Table 3.
</div></li><li data-sub-note-item="3-13"><div class="lab-step">Repeat the nitrogen, phosphorous, and potassium tests for each of the sampled sites. NOTE: Rinse the comparator thoroughly between samples
</div></li></ul></li><li data-note-item="4" data-parent-collapse="">Results
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="4-1"><div class="lab-step">To calculate the Shannon-Weiner Diversity for each of the observed sites, first open a new Excel spreadsheet.
</div></li><li data-sub-note-item="4-2"><div class="lab-step">Label cell A1 'species name', and cell B1 'total count'.
</div></li><li data-sub-note-item="4-3"><div class="lab-step">Starting from the second row and in column A, fill in the sheet for each species found in the first site, using the data recorded in Table 1.
</div></li><li data-sub-note-item="4-4"><div class="lab-step">Calculate the total number of each species found in the entire sampling effort and record this in the B column of the Excel spreadsheet.
</div></li><li data-sub-note-item="4-5"><div class="lab-step">Now, label cell G1 'total count of all species', and in cell H1, write a formula, or highlight the appropriate cells to sum all of the count values entered in column B: = SUM(B2: BX)
</div></li><li data-sub-note-item="4-6"><div class="lab-step">Label cell C1 'proportion of each species' and in cell C2, type the formula for the proportion of the total of each species at the site. = B2/H$1
</div></li><li data-sub-note-item="4-7"><div class="lab-step">Drag this formula down for each row of data represented in column B.
</div></li><li data-sub-note-item="4-8"><div class="lab-step">Label cell D1 'natural log proportion of species' and in cell D2, type the formula for the natural log of the proportion of species at the site. =LN(C2)
</div></li><li data-sub-note-item="4-9"><div class="lab-step">Drag this formula down for each row of data represented in column C.
</div></li><li data-sub-note-item="4-10"><div class="lab-step">Add the formula into cell E1 for the proportion of species multiplied by the natural log of the proportion of species: ps* ln ps
</div></li><li data-sub-note-item="4-11"><div class="lab-step">In cell E2, type the formula multiplying the proportion of species by the natural log of the proportion of species at each site, and then drag this formula down for each row of data represented in column D. = C2 * D2 
</div></li><li data-sub-note-item="4-12"><div class="lab-step">Label cell G2 as 'sum of ps * ln ps', and then, in cell H2, type a formula summing all of the values in column E. = SUM(E3 - EX) 
</div></li><li data-sub-note-item="4-13"><div class="lab-step">Label cell G3 'Shannon-Weiner Index', and in cell H3, enter the formula for the Shannon-Weiner Diversity Index. = (EXP - 1 * H2) NOTE: This is the calculated Shannon-Weiner Diversity Index for the first sampled site, and will be used for comparison between the two sites.
</div></li><li data-sub-note-item="4-14"><div class="lab-step">Repeat the data analysis in a new sheet using the data collected for the second site, which was recorded in Table 2. NOTE: Areas with greater index values are considered to have greater species diversity. Note whether you see differences between your sites.
</div></li><li data-sub-note-item="4-15"><div class="lab-step">Repeat the Shannon-Weiner Diversity calculations using a total count of all the species at each distance along the transect, then create a table of all of these values in a new Excel sheet.
</div></li><li data-sub-note-item="4-16"><div class="lab-step">Click on the Data tab in Excel, and then on the 'Data Analysis' button.
</div></li><li data-sub-note-item="4-17"><div class="lab-step">Select 'Regression' and click 'Okay'.
</div></li><li data-sub-note-item="4-18"><div class="lab-step">For the Input Y Range, highlight the Shannon-Weiner Diversity values, and for the Input X range, highlight the distance values.
</div></li><li data-sub-note-item="4-19"><div class="lab-step">Select an output location for the regression results and click 'Okay'.
</div></li><li data-sub-note-item="4-20"><div class="lab-step">Check the P-value box in the intercept row to see if there is a significant correlation between distance from edge to core habitat and biodiversity. NOTE: A value of less than 0.05 rejects the null hypothesis of no change in diversity along the transect, while a value greater than 0.05 does not reject the null hypothesis.
</div></li><li data-sub-note-item="4-21"><div class="lab-step">Next, to perform t-tests for determining soil composition differences between sites, open a new Excel spreadsheet.
</div></li><li data-sub-note-item="4-22"><div class="lab-step">In cell A1, type 'Site 1:pH', and in cell B1, type 'Site 2:pH'.
</div></li><li data-sub-note-item="4-23"><div class="lab-step">Fill in cells A2 through A6 and cells B2 through B6 with the soil pH collected in the disturbed and undisturbed sites, respectively.
</div></li><li data-sub-note-item="4-24"><div class="lab-step">Click the Data tab in Excel and then select 'Data Analysis'.
</div></li><li data-sub-note-item="4-25"><div class="lab-step">Now scroll down and select 't-Test: Two-Sample Assuming Equal Variances' and select 'Okay'.
</div></li><li data-sub-note-item="4-26"><div class="lab-step">Click the drop down next to Variable 1 Range and highlight cells A2 through A6 in the spreadsheet, then click the dropdown next to Variable 2 Range and highlight cells B2 through B6 in the spreadsheet.
</div></li><li data-sub-note-item="4-27"><div class="lab-step">In the box for hypothesized mean difference, type zero as our null hypothesis. This means that there is no difference between the two disturbance regimes.
</div></li><li data-sub-note-item="4-28"><div class="lab-step">Leave the Labels box unchecked and set the alpha value to 0.05.
</div></li><li data-sub-note-item="4-29"><div class="lab-step">Select 'Output Range', and in the box, click an empty space in the spreadsheet.
</div></li><li data-sub-note-item="4-30"><div class="lab-step">Click 'Okay'. A table of t-Test results should be outputted in the spreadsheet.
</div></li><li data-sub-note-item="4-31"><div class="lab-step">The relevant data are the means for each of the sites and the alpha value. If this second value is less than our alpha value of 0.05, we can reject the null hypothesis that there is no difference in pH between the two sites, and the hypothesis that disturbed versus undisturbed sites differ in their pH value would gain support. If this value is greater than 0.05, however, we may not reject our null hypothesis.
</div></li><li data-sub-note-item="4-32"><div class="lab-step">Repeat this analysis for each of the other three soil variables, creating a new spreadsheet for each of the phosphorus, potassium, and nitrogen elements. 
</div></li><li data-sub-note-item="4-33"><div class="lab-step">Note whether your pH and nutrient level results were different in each condition, and discuss with your group how this might affect the community and diversity in the different sites.
</div></li></ul></li></ol>

Community Diversity: Measuring Biodiversity in Different Areas - Procedure

Różnorodność społeczności

Measuring Biodiversity in Areas with Different Disturbance Regimes
ExpandNOTE: In this experiment, you will compare the biodiversity in a less disturbed ...

Hardy-Weinberg and Genetic Drift

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">Class Simulation
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">Begin by opening a new spreadsheet file. Following the Hardy-Weinberg equation where p is the frequency of a dominant allele A in a population, and q is defined as the frequency of a recessive allele B, input frequency p of allele A into cell B2, and frequency q of allele B into cell B3.
</div></li><li data-sub-note-item="1-2"><div class="lab-step">Assign the value 0.5 to cell C2.
</div></li><li data-sub-note-item="1-3"><div class="lab-step">Following the 1 &#8211; p = q equation, enter the formula &#8220;= 1 &#8211; C2&#8221; into cell C3 to calculate the frequency q of allele B. NOTE: Cells C2 and C3 will represent the gene pool used in the next few steps.
</div></li><li data-sub-note-item="1-4"><div class="lab-step">Label cells E2 and F2 &#8220;Allele 1&#8221; and &#8220;Allele 2&#8221; respectively, then enter the RAND code for random formula into cell E3. =IF (RAND()</div></li><li data-sub-note-item="1-5"><div class="lab-step">Select cell E3 and drag the bottom right corner of the cell down to E27 to duplicate the formula into 25 cells, creating an allele for the other offspring, and enter the same formula that was used in cell E3 into cell F3.
</div></li><li data-sub-note-item="1-6"><div class="lab-step">Add a third column of data starting with the description &#8220;Genotype&#8221; in cell G2, and add the CONCATENATE function to cell G3 to combine the two randomly generated alleles and to create a genotype.
</div></li><li data-sub-note-item="1-7"><div class="lab-step">Drag this formula down for 25 cells and label cells H2, I2, and J2 AA, AB, and BB respectively.
</div></li><li data-sub-note-item="1-8"><div class="lab-step">Then, input one IF function as shown here into cells H3, I3, and J3. Drag the formulas down for 25 rows per column. The formulas will return a 1 if the genotype in this row matches the genotype in the header row, and a 0 if the genotype in this row is one of the other two genotypes. H3: = IF (G3=&#8221;AA&#8221;,1,0) I3: =IF(OR(G3=&#8221;AB,G3=&#8221;BA&#8221;),1,0) J3: =IF(G3=&#8221;BB&#8221;,1,0)
</div></li><li data-sub-note-item="1-9"><div class="lab-step">Then, label cell D28 as &#8220;SUM&#8221;, add the formula to cell H28, and drag the formula to cells I28 and J28 to get the total number of each genotype.
</div></li><li data-sub-note-item="1-10"><div class="lab-step">Next, label cells H30 and J30 &#8220;A&#8221; and &#8220;B&#8221; respectively and label cell D31 &#8220;Number of alleles&#8221;.
</div></li><li data-sub-note-item="1-11"><div class="lab-step">Add code to cells H31 and J31 to obtain the total number of alleles in the simulated generation, which is two times the frequency of the respective homozygous genotype, plus the frequency of the heterozygous genotype.
</div></li><li data-sub-note-item="1-12"><div class="lab-step">Then, label cell E32 &#8220;Next gen allele frequency&#8221; and add code to cells H32 and J32 to obtain the ratio of alleles in the next generation.
</div></li><li data-sub-note-item="1-13"><div class="lab-step">Using the gene frequencies generated in the mathematical model you just built, adjust the gene pool values in cells C2 and C3 to those from H32 and J32, and run 10 more generations, updating the gene pool with the resulting allele frequency each time.
</div></li><li data-sub-note-item="1-14"><div class="lab-step">Record the ratio of the two variables at each time point in the spreadsheet on the table, and create a line graph to see how a small population changes over time. Hypotheses: The experimental hypothesis in this study is that smaller populations will deviate more from the Hardy-Weinberg expected frequencies of the alleles than will larger populations, because smaller populations are more susceptible to genetic drift. The null hypothesis is that the allele frequencies within the populations will not differ from the Hardy-Weinberg equilibrium equation expected frequencies, meaning that the allele frequencies will be the same from generation to generation.
</div></li><li data-sub-note-item="1-15"><div class="lab-step">Set the frequency of gene A to 0.3 and gene B to 0.7, and run the model 10 more times, recording the ratio of the genes in the next generation in the table after each run.
</div></li><li data-sub-note-item="1-16"><div class="lab-step">Then, drag the formulas for the cells further down to alter the model to include 100 zygotes and run the model another 10 times.
</div></li><li data-sub-note-item="1-17"><div class="lab-step">After the last run, save all of the working data to a personal storage device and exit the spreadsheet program.
</div></li></ul></li><li data-note-item="2" data-parent-collapse="">Simulation for Hardy-Weinberg and Genetic Drift
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="2-1"><div class="lab-step">To begin, find a partner and then collect one bag from the instructor.
</div></li><li data-sub-note-item="2-2"><div class="lab-step">Verify that the bag contains beads of two different colors and an even number of each color. 
</div></li><li data-sub-note-item="2-3"><div class="lab-step">Designate one color as allele capital A and the other as small a. Hypotheses: The experimental hypothesis for this simulation is that allele frequencies will not change over the 10 generations of the experiment, and Hardy-Weinberg equilibrium will be observed. The null hypothesis is that equilibrium will not be seen in the population.
</div></li><li data-sub-note-item="2-4"><div class="lab-step">Note the initial frequency in Table 1 next to generation zero. Using the Hardy-Weinberg equation, calculate the initial genotype frequencies of the population and note this in Table 1. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/4/Lab_4_Table_A.xlsx" target="__blank" style="display:block;margin:20px;">Click Here to download Table A</a>
</div></li><li data-sub-note-item="2-5"><div class="lab-step">Then, discuss with your partner about the expected final allele and genotype frequencies after 10 generations of Hardy-Weinberg equilibrium. Note this next to prediction in Table 1.
</div></li><li data-sub-note-item="2-6"><div class="lab-step">Draw a pair of beads from the bag. This represents the genotype of one individual in the next generation.
</div></li><li data-sub-note-item="2-7"><div class="lab-step">Place a tally mark in the appropriate column next to Generation 1.
</div></li><li data-sub-note-item="2-8"><div class="lab-step">Now, keeping each pair of beads out of the bag every time, repeat the drawing 20 times to fill out the generation one row of Table 1.
</div></li><li data-sub-note-item="2-9"><div class="lab-step">Using the tallies, calculate the allele frequency for that generation, remembering to count both alleles in each genotype. Make a note of the new allele frequency, and then adjust the 100 beads to reflect the population after Generation 1 by adding and removing beads as necessary.
</div></li><li data-sub-note-item="2-10"><div class="lab-step">Repeat the drawing of pairs from this adjusted population for another generation of 20 picks, recording all of the observations in Table 1.
</div></li><li data-sub-note-item="2-11"><div class="lab-step">After calculating the allele frequency for this generation, adjust the population again to set up a third generation draw.
</div></li><li data-sub-note-item="2-12"><div class="lab-step">Keep drawing, calculating allele frequencies, and adjusting the starting population until 10 generations have been recorded in total.
</div></li></ul></li><li data-note-item="3" data-parent-collapse="">Violations of Hardy-Weinberg 
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="3-1"><div class="lab-step">To test the effect of different physical and ecological scenarios on the Hardy-Weinberg equilibrium, first draw a slip of paper to determine which Hardy-Weinberg assumption you will be testing.
</div></li><li data-sub-note-item="3-2"><div class="lab-step">Make a prediction of what you think might happen in your selected scenario before beginning the experiment, and record this on the board.
</div></li><li data-sub-note-item="3-3"><div class="lab-step">If you selected the mutation scenario, select 5 alleles at random from the set and replace them with 5 of a third color, allele capital B.
</div></li><li data-sub-note-item="3-4"><div class="lab-step">As before, perform the simulation by pulling pairs of beads from the bag for a generation of 20 picks, recording the results.  <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/4/Lab_4_Table_B.xlsx" style="display:block;margin:20px;" target="__blank">Click Here to download Table B</a>
</div></li><li data-sub-note-item="3-5"><div class="lab-step">After each generation, make adjustments to have the starting population match the new allele frequency as before.
</div></li><li data-sub-note-item="3-6"><div class="lab-step">Then, replace 5 random alleles again with the new color, and simulate the new generation for 20 picks.
</div></li><li data-sub-note-item="3-7"><div class="lab-step">If you picked the non-random mating test, draw 1 allele at a time instead of 2 and then pair it with another of the same color pulled from the bag.
</div></li><li data-sub-note-item="3-8"><div class="lab-step">As with the previous simulation, adjust the population to match the new allele frequencies at the end of the previous generation, and carry out the simulation for 10 generations in total.
</div></li><li data-sub-note-item="3-9"><div class="lab-step">For the gene flow condition, begin by removing 10 alleles from the population and replacing them with 10 randomly selected alleles from another set of 100 beads.
</div></li><li data-sub-note-item="3-10"><div class="lab-step">Adjust the allele frequency and repeat the gene flow of removing 10 beads and adding 10 beads from another bag at the beginning of each generation.
</div></li><li data-sub-note-item="3-11"><div class="lab-step">If you drew small population size, simply start each generation with 60 alleles instead of 100.
</div></li><li data-sub-note-item="3-12"><div class="lab-step">As usual, adjust allele frequencies each generation and record 10 generations. In the selection condition, draw from the original bag of beads but do not count any homozygous recessive pairs that are drawn when calculating the allele frequency at the end of each generation.
</div></li></ul></li><li data-note-item="4" data-parent-collapse="">Simulation of Genetic Drift
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="4-1"><div class="lab-step">Make your predictions before running the simulations and record them on the board.
</div></li><li data-sub-note-item="4-2"><div class="lab-step">If you have the small population size test, run the standard Hardy-Weinberg simulation as before, but instead start each generation with 30 alleles and not 100.
</div></li><li data-sub-note-item="4-3"><div class="lab-step">If you drew the founder effect with two alleles test, start generation 1 by drawing only 5 pairs of beads from the bag.
</div></li><li data-sub-note-item="4-4"><div class="lab-step">Then, creating the gene pool for generation 2, include only 50 beads at the allele frequency determined in generation 1. When you create the gene pool for generation 3 and all subsequent generations, include 100 beads.
</div></li><li data-sub-note-item="4-5"><div class="lab-step">For a founder effect with 10 alleles, you will need to collect a bag containing random amounts of 10 different colored beads.
</div></li><li data-sub-note-item="4-6"><div class="lab-step">Designate an allele name for each of the new alleles, and then calculate their initial allele frequency.
</div></li><li data-sub-note-item="4-7"><div class="lab-step">Now, run the experiment in the same way as the founder effect with two alleles, by drawing just 5 pairs randomly for generation 1 and then creating the second generation with 50 alleles, and third and subsequent generations with 100. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/4/Lab_4_Table_C.xlsx" style="display:block;margin:20px;" target="__blank">Click Here to download Table C</a>
</div></li><li data-sub-note-item="4-8"><div class="lab-step">If you have the natural disaster with 2 alleles, you will need to collect a paper plate from your instructor.
</div></li><li data-sub-note-item="4-9"><div class="lab-step">Draw a line down the middle of the plate. Before generation 1, pour out all of the beads from a standard 100 bead setup onto the plate, and mix them randomly, spreading them evenly.
</div></li><li data-sub-note-item="4-10"><div class="lab-step">Choose one side of the plate and take all of the beads from that side. You should draw from these to create generation 1.
</div></li><li data-sub-note-item="4-11"><div class="lab-step">For generation 2 and beyond, adjust the population and use a total of 100 beads.
</div></li><li data-sub-note-item="4-12"><div class="lab-step">Finally, if you selected the natural disaster with 10 alleles test, you will need to collect a bag containing 10 different colored beads.
</div></li><li data-sub-note-item="4-13"><div class="lab-step">Assign a name to each new allele, and then place them on the plate and select half. Draw from these 50 beads for generation 1, and then calculate the allele frequencies to make a population of 100 in each subsequent round.
</div></li></ul></li><li data-note-item="5" data-parent-collapse="">Results
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="5-1"><div class="lab-step">Using the entered functions, calculate the number of each allele by multiplying the number of the homozygous genotypes by 2 and adding the number of the heterozygous genotypes.
</div></li><li data-sub-note-item="5-2"><div class="lab-step">The frequency can then be calculated by dividing the number of the allele in question by the total number of alleles. Enter the results into the table.
</div></li><li data-sub-note-item="5-3"><div class="lab-step">Next, use the Hardy-Weinberg equation to calculate the expected genotype frequency of the next generation, and compare the results of the simulation with the expected frequency, using the table as a guide.
</div></li><li data-sub-note-item="5-4"><div class="lab-step">Plot the changes of the population gene frequencies over time that you recorded in the table. Note any changes in allele frequencies over time and if any alleles decrease in frequency to the point that they disappear from the population. 
</div></li><li data-sub-note-item="5-5"><div class="lab-step">Plot the changes in the populations of the 25 and 100 zygotes with initial gene frequencies of 0.5 for each allele. Compare the results of the smaller population and the larger populations.  NOTE: The observed allele frequencies are expected to differ slightly from the Hardy-Weinberg expected values as a result of chance from the RAND function.
</div></li><li data-sub-note-item="5-6"><div class="lab-step">Using separate lines for each allele, graph the allele frequencies found for the original Hardy-Weinberg experiment over 10 generations.
</div></li><li data-sub-note-item="5-7"><div class="lab-step">Compare the results across the class, and see if your results agree.
</div></li><li data-sub-note-item="5-8"><div class="lab-step">Next, again using one line per allele, graph the results of your second experiment testing violations of the Hardy-Weinberg equilibrium, and share your finding with the class. Compare your actual results with your prediction. 
</div></li><li data-sub-note-item="5-9"><div class="lab-step">Finally, graph the results of your genetic drift simulation scenario in the same manner.
</div></li><li data-sub-note-item="5-10"><div class="lab-step">Again, present your results to the group and hypothesize why your results did or did not match your prediction. Compare your results to those of your classmates&#8217;. 
</div></li></ul></li></ol>

Hardy-Weinberg Equilibrium Principle and Genetic Drift - Procedure

Hardy-Weinberg i dryf genetyczny

Class Simulation
ExpandBegin by opening a new spreadsheet file. Following the Hardy-Weinberg equation where p is the frequency of a dominant allele A in a ...

Genetics of Organisms

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">REF and WEF Fly Genetics
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">NOTE: At your station, you should have four vials of flies. They will be labeled as male or female. They will also be labeled with the notation REF for red-eyed flies or WEF for white-eyed flies. The female vial should also be labeled virgin as these flies should be unmated for the purpose of this experiment.
</div></li><li data-sub-note-item="1-2"><div class="lab-step">Make sure you have around five flies in each vial. NOTE: You will perform crosses using these flies to determine if red or white eyes is dominant and if the trait is sex-linked. You should also have two fly anesthesia wands, a paint brush, magnifying glass, fly anesthetic, some empty fly vials, and a sheet of white paper.
</div></li><li data-sub-note-item="1-3"><div class="lab-step">Draw a line in the middle of the paper to make a male side and a female side.
</div></li><li data-sub-note-item="1-4"><div class="lab-step">Dip the fly anesthesia wand into the solution and insert it into the red-eyed female vial until the flies stop moving.
</div></li><li data-sub-note-item="1-5"><div class="lab-step">Then, dip the same wand into the white-eyed male vial until these flies are also anesthetized.
</div></li><li data-sub-note-item="1-6"><div class="lab-step">Tap the flies from the two vials onto the sheet - Females on one side and males on the other.
</div></li><li data-sub-note-item="1-7"><div class="lab-step">Check to make sure that all the flies from the female vial are female and likewise, confirm that the male flies are male.  NOTE: Males are slightly smaller and have a darker solid pigment on the end of their abdomen. Females are larger and have stripes rather than a solid spot.
</div></li><li data-sub-note-item="1-8"><div class="lab-step">If there are any male flies in the female vial, obtain a new vial as these females likely have sperm from males from their own strain and are unusable.
</div></li><li data-sub-note-item="1-9"><div class="lab-step">Now, move the five red-eyed females and five white-eyed males into a new vial using the paintbrush.
</div></li><li data-sub-note-item="1-10"><div class="lab-step">Label this vial to indicate that this is a cross between red-eyed females and white-eyed males. HYPOTHESES: Use Punnett squares to formulate hypotheses for this experiment. Consider what you will see in a few days if the white allele is dominant and there is no effect of parental sex. What if red is dominant? Under the potential offspring genotype in each box, write the expected phenotype.
</div></li><li data-sub-note-item="1-11"><div class="lab-step">To set up the reverse cross, again dip the fly anesthesia wand into the solution and insert it this time into the white-eyed female vial and then the red-eyed male vial until all the flies have stopped moving.
</div></li><li data-sub-note-item="1-12"><div class="lab-step">Tap the flies onto a sheet of white paper and check to make sure that all the flies from the female vial are female and likewise with the male flies.
</div></li><li data-sub-note-item="1-13"><div class="lab-step">Now, move the five white-eyed females and five red-eyed males into a new vial using the paintbrush.
</div></li><li data-sub-note-item="1-14"><div class="lab-step">Label this vial to indicate that this is a cross between white-eyed females and red-eyed males.
</div></li><li data-sub-note-item="1-15"><div class="lab-step">Finally, place the two tubes containing the new crosses into a rack for incubation at room temperature. NOTE: After about three days, larvae should be moving around in the vial.
</div></li><li data-sub-note-item="1-16"><div class="lab-step">Remove the 10 adult flies and dispose of them into the morgue tube containing 70% ethanol.
</div></li><li data-sub-note-item="1-17"><div class="lab-step">Now, put the tubes back in the rack and let the larvae mature until they reach the adult stage in up to two weeks.
</div></li><li data-sub-note-item="1-18"><div class="lab-step">Once all of the larvae from these crosses have matured to adulthood, anesthetize the flies in one of the tubes using the wand.
</div></li><li data-sub-note-item="1-19"><div class="lab-step">Then, on a piece of white paper, sort the flies by sex and phenotype and then record these data.
</div></li><li data-sub-note-item="1-20"><div class="lab-step">Now, repeat this process and tally the sexes and phenotypes for the second cross (steps 1 &#8211; 18).
</div></li><li data-sub-note-item="1-21"><div class="lab-step">Finally, once you have counted all of your flies, dispose of them in the morgue vial.
</div></li></ul></li><li data-note-item="2" data-parent-collapse="">Results
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="2-1"><div class="lab-step">To begin investigating your results, first compare the data you collected with the hypothesis you made using the Punnett squares.
</div></li><li data-sub-note-item="2-2"><div class="lab-step">Did your data match the simple Punnett square hypothesis where red or white is dominant and there is no effect of sex? Compare your data with other lab groups.
</div></li><li data-sub-note-item="2-3"><div class="lab-step">If your data does not match what your Punnett squares predicted, does this indicate that the gene may be sex-linked?
</div></li><li data-sub-note-item="2-4"><div class="lab-step">If the red gene were dominant and sex-linked, when we cross red-eyed females with white-eyed males, all of the offspring would have red eyes. Assuming all of the females were homozygous for the color allele, does this match your data for the first cross?
</div></li><li data-sub-note-item="2-5"><div class="lab-step">If white were dominant and the gene were sex-linked, we would see the exact opposite. So all of the flies would have white eyes. From your data, can you conclude from your first cross whether red or white is dominant?
</div></li><li data-sub-note-item="2-6"><div class="lab-step">When the reciprocal cross of white-eyed females and red-eyed males is performed, if the red phenotype is dominant, all of the females would be red and all of the males would be white. This would also confirm that the gene is specifically x-linked because white-eyed females could then only be produced in crosses with white-eyed males. Did your second cross produce any white-eyed females?
</div></li><li data-sub-note-item="2-7"><div class="lab-step">Finally, if the gene were x-linked and white was dominant, crossing white-eyed females with red-eyed males would result in all of the offspring having white eyes. Does this hypothesis fit with your second cross?
</div></li><li data-sub-note-item="2-8"><div class="lab-step">Look over your data and conclude which of the hypotheses best fits the patterns you found in your crosses. If your data does not fit with any of these, hypothesize why this might be the case.
</div></li></ul></li></ol>

Genetics of Organisms: REF and WEF Fly Genetics - Procedure

Genetyka organizmów

REF and WEF Fly Genetics
ExpandNOTE: At your station, you should have four vials of flies. They will be labeled as male or female. They will also be ...

Genetics

Plant Diversity

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">Viewing Prepared Slides
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">To start the exercise, first split up into groups and find a station with a compound microscope, dissecting microscope and one prepared slide.
</div></li><li data-sub-note-item="1-2"><div class="lab-step">HYPOTHESES: The alternative hypothesis for this experiment might be that plants have specific adaptations that allow them to survive and reproduce in their own individual terrestrial environments. The null hypothesis for this experiment is that all plants have the same adaptations to live in terrestrial habitats.
</div></li><li data-sub-note-item="1-3"><div class="lab-step">Find the prepared slide at your station and place it on the stage of the compound microscope. Then, secure it between the stage clips.
</div></li><li data-sub-note-item="1-4"><div class="lab-step">Next, find the light switch on the side or back of the microscope and turn it on to illuminate the slide from below.
</div></li><li data-sub-note-item="1-5"><div class="lab-step">Adjust the lenses until the 10X lens is positioned above the slide.
</div></li><li data-sub-note-item="1-6"><div class="lab-step">Now, look through the eye piece of the microscope and turn the large course adjustment knob on the side of the microscope to bring the slide into focus.
</div></li><li data-sub-note-item="1-7"><div class="lab-step">After course adjustment, the smaller fine adjustment knob can be used to further refine the focus. Do this until the material on the slide becomes clear.
</div></li><li data-sub-note-item="1-8"><div class="lab-step">For each slide there are several key structures that you will need to sketch in Table 1. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/26/Table_1_Plant_diversity_and_evolution.xlsx" style="display:block;margin:20px;" target="__blank">Click Here to download Table 1</a>
</div></li><li data-sub-note-item="1-9"><div class="lab-step">For moss antheridium, identify the areas where sperm are formed. These areas should be darker than surrounding regions and oblong in shape. Sperm are released from these structures and swim to the archegonia.
</div></li><li data-sub-note-item="1-10"><div class="lab-step">For moss archegonia, identify the eggs. These are circular in shape and are located at the bottom of a long dark tube called the vent. Once fertilized, the new embryo will be retained within the structures surrounding the egg for protection.
</div></li><li data-sub-note-item="1-11"><div class="lab-step">Then, for the onion stomata, identify the stomata. These are the circular structures with two dark spots on either side. These dark spots are the nuclei of the guard cells that surround the pore and control its opening and closing.
</div></li><li data-sub-note-item="1-12"><div class="lab-step">For conifer pollen grains, notice the two wings on either side of each pollen grain. These allow the pollen to be blown by the wind to the female ovule. Also, notice the dark spots within the pollen grain. These are the nuclei.
</div></li></ul></li><li data-note-item="2" data-parent-collapse="">Observing Adaptations and Collecting Samples
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="2-1"><div class="lab-step">NOTE: For this experiment, you&#39;ll be testing the same hypotheses, but you will leave the lab behind and venture outside to explore plant adaptations in the local environment. For safety, make sure to wear proper clothing and sun protection if needed.
</div></li><li data-sub-note-item="2-2"><div class="lab-step">Once your instructor has taken you to the designated outdoor location, try to identify plants in each of the three major groups: non-vascular, seedless vascular, and seeded vascular.
</div></li><li data-sub-note-item="2-3"><div class="lab-step">Using Table 2, fill out information for at least 10 plants listing the major group, specific adaptations and a brief sketch for each. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/26/Table_2_Plant_diversity_and_evolution.xlsx" style="display:block;margin:20px;" target="__blank">Click Here to download Table 2</a>
</div></li><li data-sub-note-item="2-4"><div class="lab-step">Where possible, try to identify different adaptations than the ones we&#39;ve discussed so far. These include traits such as leaf size and shape, plant height, or flowers. To find plants of all three major groups, you may need to look in more than one location or habitat.
</div></li><li data-sub-note-item="2-5"><div class="lab-step">Before returning to the lab, each group member should collect a leaf, flower or other structure from a plant of their choosing for further analysis.
</div></li><li data-sub-note-item="2-6"><div class="lab-step">Back in the lab, place the one group member&#8217;s specimen on the stage of the dissecting microscope.
</div></li><li data-sub-note-item="2-7"><div class="lab-step">Next, find the light switch and turn it on to illuminate the sample.
</div></li><li data-sub-note-item="2-8"><div class="lab-step">Similar to the compound microscope, you will next need to adjust the fine focus knobs to bring the sample into view.
</div></li><li data-sub-note-item="2-9"><div class="lab-step">For leaves, view the stomata under maximum magnification. These will look like very small dots on the surface of the leaf.
</div></li><li data-sub-note-item="2-10"><div class="lab-step">Next, tear the leaf in half and see if you can find the clear cuticle that covers the surface of the leaf.
</div></li><li data-sub-note-item="2-11"><div class="lab-step">Examine the venation of the leaf, which allows for transport of resources.
</div></li><li data-sub-note-item="2-12"><div class="lab-step">When observing flowers, look for pollen, which will appear as yellow dust on the anthers of the flower.
</div></li><li data-sub-note-item="2-13"><div class="lab-step">Next, identify the stigma, a long structure protruding from the flower and ending with a round sticky tip. This is where pollen would land allowing sperm to travel down to the ovule at the base of the flower to form a seed.
</div></li><li data-sub-note-item="2-14"><div class="lab-step">Notice whether or not there is evidence of a fruit or seed in the base of the flower.
</div></li><li data-sub-note-item="2-15"><div class="lab-step">Make a sketch of each of the samples within your group.
</div></li><li data-sub-note-item="2-16"><div class="lab-step">When the exercise is complete, turn off the light on both microscopes. Remove the prepared slide from the stage of the compound microscope and return it to the instructor.
</div></li><li data-sub-note-item="2-17"><div class="lab-step">Finally, remove the samples you collected from the dissected microscope and discard them into the trash and clean the microscope stages, if necessary.
</div></li></ul></li><li data-note-item="3" data-parent-collapse="">Results
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="3-1"><div class="lab-step">Compare the adaptations you observed for the plants you examined outdoors with the adaptations other student groups noticed.
</div></li><li data-sub-note-item="3-2"><div class="lab-step">Take note of any similar adaptations across the different plant species.
</div></li></ul></li></ol>

Plant Diversity: Plant Adaptations across Different Species - Procedure

Różnorodność roślin

Viewing Prepared Slides
ExpandTo start the exercise, first split up into groups and find a station with a compound microscope, dissecting microscope and ...

DNA Isolation and Restriction Enzyme Analysis

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">DNA Isolation
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">NOTE: In this experiment you will perform DNA isolation under two experimental conditions: one using a buffer containing the detergent SDS and one without detergent. Hypotheses: The alternate hypothesis for this experiment might be that the sample prepared without SDS, a strong anionic detergent that breaks apart cell membranes, will yield less DNA than the sample prepared with SDS. The null hypothesis for this experiment might be that both samples will yield an equal amount of DNA.
</div></li><li data-sub-note-item="1-2"><div class="lab-step">To begin collect a tissue sample for DNA isolation. Here you will be using your own cheek cells. Use a Popsicle stick to scrape the insides of your cheeks for approximately 30 s. IMPORTANT: Do not scrape hard enough to cause pain or draw blood.
</div></li><li data-sub-note-item="1-3"><div class="lab-step">Position a funnel in a 15-mL conical tube. 
</div></li><li data-sub-note-item="1-4"><div class="lab-step">Then take 10 mL of the 1% saline solution provided to you in a labeled cup and swish it around in your mouth without swallowing. 
</div></li><li data-sub-note-item="1-5"><div class="lab-step">Continue swishing for 90 s and then spit the saline solution containing your cheek cells into the funnel to collect in the conical tube.
</div></li><li data-sub-note-item="1-6"><div class="lab-step">Next, label two empty microcentrifuge tubes with your initials. 
</div></li><li data-sub-note-item="1-7"><div class="lab-step">Label one of the tubes as +SDS and the other as -SDS to differentiate the two treatments. 
</div></li><li data-sub-note-item="1-8"><div class="lab-step">Then add 1.5 to 2 mL of the saline solution containing the cheek cells to each tube.
</div></li><li data-sub-note-item="1-9"><div class="lab-step">Spin the tubes in a microcentrifuge for 30 s. 
</div></li><li data-sub-note-item="1-10"><div class="lab-step">Remove the tubes from the microcentrifuge and carefully pour off the supernatant without disturbing the cells collected at the bottom of each tube. 
</div></li><li data-sub-note-item="1-11"><div class="lab-step">Fill the tubes with more of the saline solution containing the cheek cells and repeat the centrifugation. 
</div></li><li data-sub-note-item="1-12"><div class="lab-step">Repeat this process taking care to evenly distribute cells between the +SDS and -SDS tubes until all of the cheek cells have been collected.
</div></li><li data-sub-note-item="1-13"><div class="lab-step">Next, add 1 mL of lysis buffer containing SDS to the tube marked as +SDS, and then resuspend the cell pellet by pipetting up and down. 
</div></li><li data-sub-note-item="1-14"><div class="lab-step">Then add 1 mL of lysis buffer without SDS to the tube marked with -SDS and resuspend the cell pellet by pipetting up and down.
</div></li><li data-sub-note-item="1-15"><div class="lab-step">After this add 10 &#181;L of proteinase K to each tube and then carefully place the tubes in the 56 &#186;C water bath for 10 min. 
</div></li><li data-sub-note-item="1-16"><div class="lab-step">After 10 minutes carefully remove the tubes from the water bath and add 100 &#181;L of 2.5 M NaCl to each tube. 
</div></li><li data-sub-note-item="1-17"><div class="lab-step">Close the tubes firmly and invert several times to mix.
</div></li><li data-sub-note-item="1-18"><div class="lab-step">Next, label one 15 mL conical tube as +SDS and another with -SDS. 
</div></li><li data-sub-note-item="1-19"><div class="lab-step">Pour the contents of each microcentrifuge tube into the corresponding 15 mL conical tube. 
</div></li><li data-sub-note-item="1-20"><div class="lab-step">Obtain one 10 mL aliquot of 100% ethanol from the freezer. 
</div></li><li data-sub-note-item="1-21"><div class="lab-step">Hold one of the conical tubes at an angle and slowly dispense 1 mL of 100% ethanol into the tube to form a layer on top of the liquid already in the tube.
</div></li><li data-sub-note-item="1-22"><div class="lab-step">Repeat this process for the second conical tube. 
</div></li><li data-sub-note-item="1-23"><div class="lab-step">Now look at both of your tubes. There should be a stringy precipitate present at the interface of the ethanol and the aqueous layer below it. This stringy material contains the isolated DNA. Take pictures of the DNA in the tube and make clear descriptive notes and drawings of your observations in your notebook. 
</div></li><li data-sub-note-item="1-24"><div class="lab-step">Using a glass stir rod, pick up the DNA from the +SDS tube and examine it. Repeat this for the -SDS tube, again recording your observations. Take note of whether one of the tubes appears to have more precipitate than the other, and why this might be.
</div></li><li data-sub-note-item="1-25"><div class="lab-step">Finally, discard all liquid waste into the appropriate waste container and return all tools to their proper locations in the lab.
</div></li></ul></li><li data-note-item="2" data-parent-collapse="">Restriction Enzyme Virtual Digest
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="2-1"><div class="lab-step">To study how restriction enzymes work, first navigate to the New England Biolabs website: <a href="https://www.neb.com/" target="__blank">https://www.neb.com/</a>
</div></li><li data-sub-note-item="2-2"><div class="lab-step">The resources available at this site allow researchers to run virtual experiments before they are performed in the lab. Click on &#8220;Tools and Resources&#8221; to find the NEBcutter tool and open the program.
</div></li><li data-sub-note-item="2-3"><div class="lab-step">To the right of the search box find the list that says &#8220;Viral + phage&#8221;. From that list select Lambda. This is the name of the DNA you will be digesting. Select the Linear option where the tool says &#8220;the sequence is&#8221; and the &#8220;NEB enzymes&#8221; option where the tool says, &#8220;Enzymes to use&#8221;. Then click Submit.
</div></li><li data-sub-note-item="2-4"><div class="lab-step">The next page will display a full restriction map of the lambda DNA. This restriction map can be used to predict what will happen if certain enzymes are used. Next, click on &#8220;Custom digest&#8221; under the &#8220;Main options&#8221; heading.
</div></li><li data-sub-note-item="2-5"><div class="lab-step">Search for the enzyme StuI and note that it works optimally in buffer 2.1 or CS buffer. Select the StuI enzyme and click digest.
</div></li><li data-sub-note-item="2-6"><div class="lab-step">In the next window click on &#8220;View gel&#8221; under the &#8220;Main options&#8221; header. Select the option to run a virtual 1% gel using a pBR322-BstN1 digest.
</div></li><li data-sub-note-item="2-7"><div class="lab-step">After the results appear, take a screenshot and paste it into a blank document.
</div></li><li data-sub-note-item="2-8"><div class="lab-step">After this, navigate back to the main page of the NEBcutter tool and select &#8220;New custom digest&#8221;.
</div></li><li data-sub-note-item="2-9"><div class="lab-step">This time search for the BsrGI enzyme and note that it performs optimally in buffer 2.1 or buffer 3.1. Select the enzyme and click digest.
</div></li><li data-sub-note-item="2-10"><div class="lab-step">Under the Main options header click on &#8220;View gel&#8221; and select the options to run a virtual 1% gel using a pBR322-BstN1 digest.
</div></li><li data-sub-note-item="2-11"><div class="lab-step">Take a screenshot of the results and save this in a text document.
</div></li><li data-sub-note-item="2-12"><div class="lab-step">Finally, repeat these steps using both StuI and BsrGI together in a single digest.
</div></li><li data-sub-note-item="2-13"><div class="lab-step">Again, take a screenshot and save the resulting gel.
</div></li></ul></li><li data-note-item="3" data-parent-collapse="">DNA Profiling
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="3-1"><div class="lab-step">Before starting the restriction enzyme digests first put your aliquots of lambda DNA, NEB buffer 2.1, StuI enzyme, and BsrGI enzyme into an ice bucket, and take this to your work area.
</div></li><li data-sub-note-item="3-2"><div class="lab-step">Label a tube as StuI &#8211; this will contain the StuI digest. 
</div></li><li data-sub-note-item="3-3"><div class="lab-step">Label a tube as BsrGI to contain the BsrGI digest. 
</div></li><li data-sub-note-item="3-4"><div class="lab-step">Then, label a tube S+B, to contain the digest with both of the enzymes.
</div></li><li data-sub-note-item="3-5"><div class="lab-step">Use the appropriate micropipetters to set up the reactions listed in the Table 1:<a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/12/Lab_12_Table_1.xlsx" style="display:block;margin:20px;" target="__blank">Click Here to download Table 1</a>
</div></li><li data-sub-note-item="3-6"><div class="lab-step">First, pipette the 40 &#181;L of water into each tube.
</div></li><li data-sub-note-item="3-7"><div class="lab-step">Then, using a fresh pipette tip each time, dispense 5 &#181;L of buffer 2.1 into each tube and pipette up and down to mix.
</div></li><li data-sub-note-item="3-8"><div class="lab-step">Next, add 4 &#181;L of lambda DNA to each tube, and then pipette 0.5 &#181;L of each enzyme into the appropriate tubes.
</div></li><li data-sub-note-item="3-9"><div class="lab-step">Finally, add a sufficient amount of water to each tube to bring the total volume up to 50 &#181;L.
</div></li><li data-sub-note-item="3-10"><div class="lab-step">Next, incubate the tubes at 37 &#186;C for 15 - 60 min in a water bath, and return the buffers and enzymes to the freezer.
</div></li><li data-sub-note-item="3-11"><div class="lab-step">To prepare an agarose gel to run the digest, in a 250 mL flask mix 1 g of agarose powder with 100 mL of TAE buffer.
</div></li><li data-sub-note-item="3-12"><div class="lab-step">Microwave the solution for approximately 90 s at full power, taking care to prevent the solution from boiling over.
</div></li><li data-sub-note-item="3-13"><div class="lab-step">Next, carefully remove the solution from the microwave using a glove or heat pad and place it to cool for about 15 min. 
</div></li><li data-sub-note-item="3-14"><div class="lab-step">While the agarose solution cools set up a casting tray. 
</div></li><li data-sub-note-item="3-15"><div class="lab-step">When the agarose solution is cool add 5 &#181;L of 10,000X SYBR Safe gel stain to the solution.
</div></li><li data-sub-note-item="3-16"><div class="lab-step">Add the comb which is used to make the wells of the gel to the casting tray of the gel electrophoresis apparatus.
</div></li><li data-sub-note-item="3-17"><div class="lab-step">Pour the agarose gel solution into the casting tray and allow it to solidify. 
</div></li><li data-sub-note-item="3-18"><div class="lab-step">Once the gel is solid, pull the comb straight up to remove it from the gel, and then remove the dams from the casting tray if appropriate.
</div></li><li data-sub-note-item="3-19"><div class="lab-step">Place the gel in the electrophoresis chamber with the wells positioned closest to the negative or black electrode and fill the chamber with 1x TAE buffer to completely cover the gel.
</div></li><li data-sub-note-item="3-20"><div class="lab-step">Remove your samples from the water bath.
</div></li><li data-sub-note-item="3-21"><div class="lab-step">Then add 8.3 &#181;L of 6X loading dye to each sample.
</div></li><li data-sub-note-item="3-22"><div class="lab-step">Dispense 10 &#181;L of the pBR322-BstN1 digest which contains DNA fragments of known size into the first well.
</div></li><li data-sub-note-item="3-23"><div class="lab-step">Then load 25 &#181;L of sample StuI into the second well.
</div></li><li data-sub-note-item="3-24"><div class="lab-step">Place 25 &#181;L of sample BsRGI into the third well.
</div></li><li data-sub-note-item="3-25"><div class="lab-step">Load 25 &#181;L of sample S+B into the fourth well.
</div></li><li data-sub-note-item="3-26"><div class="lab-step">To run the gel plug the leads into the electrophoresis chamber and then into the power supply. The red positive lead should be at the end farthest away from the wells and the black negative lead should be nearest to the wells. This is because the samples will run from negative to positive.
</div></li><li data-sub-note-item="3-27"><div class="lab-step">Turn on the power supply and set the gel box to run at 170 volts for approximately 60 minutes.
</div></li><li data-sub-note-item="3-28"><div class="lab-step">After the run is complete turn off the power to the gel box and disconnect the electrodes from the tank.
</div></li><li data-sub-note-item="3-29"><div class="lab-step">Then remove the gel from the electrophoresis chamber and observe it with a UV transilluminator.  CAUTION: Protect eyes from the UV by wearing goggles or using the provided shield.
</div></li><li data-sub-note-item="3-30"><div class="lab-step">Finally, use a cell phone camera to take a picture of the gel from directly above and parallel to the gel surface.
</div></li></ul></li><li data-note-item="4" data-parent-collapse="">Results
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="4-1"><div class="lab-step">Compare the gel you ran in the lab to your virtual enzymatic digest with StuI.
</div></li><li data-sub-note-item="4-2"><div class="lab-step">The virtual digest with StuI resulted in seven bands. Count the bands in the StuI lane of your gel and note whether this matched the virtual digest or appeared to show a similar pattern. NOTE: Small bands on agarose electrophoresis gels are often invisible.
</div></li><li data-sub-note-item="4-3"><div class="lab-step">Now look at the results for your BsrGI digest. The virtual digest with BsrGI resulted in six bands. Count the bands in the BsrGI lane. Again, note whether the virtual digest and lab digest showed the same or a similar pattern.
</div></li><li data-sub-note-item="4-4"><div class="lab-step">Finally, look at the virtual digest with StuI and BsrGI. The virtual digest with both enzymes resulted in 12 bands. Count the bands in the corresponding lane of your gel, and consider whether the DNA banding pattern looks similar to the virtual digest.
</div></li></ul></li></ol>

Analiza enzymów izolacyjnych i restrykcyjnych DNA

DNA Isolation
ExpandNOTE: In this experiment you will perform DNA isolation under two experimental conditions: one using a buffer containing the detergent ...

Macromolecules

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">Identifying Macromolecules with Indicator Solutions
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">HYPOTHESES: In this activity, the experimental hypothesis might be that the addition of an indicator dye to each test solution will result in a color change if the test solution contains the macromolecule of interest. The null hypothesis might be that the addition of an indicator dye will not result in a color change in any of the test solutions.
</div></li><li data-sub-note-item="1-2"><div class="lab-step">Place 16 clean test tubes in a tube rack in four rows of four tubes and label each row A through D and each column 1 - 4.
</div></li><li data-sub-note-item="1-3"><div class="lab-step">Label each test tube with its corresponding position in the test tube rack.
</div></li><li data-sub-note-item="1-4"><div class="lab-step">After this, stir solution A thoroughly and use a pipette to add 4 mL of solution A to each tube in Row A.
</div></li><li data-sub-note-item="1-5"><div class="lab-step">Next, stir solution B until it is well mixed and use a new pipette to add 4 mL of solution B to each tube in Row B.
</div></li><li data-sub-note-item="1-6"><div class="lab-step">After stirring solution C thoroughly, add 4 mL of solution C to each tube in Row C.
</div></li><li data-sub-note-item="1-7"><div class="lab-step">Then add 4 mL of soybean-derived vegetable oil to each tube in Row D.
</div></li><li data-sub-note-item="1-8"><div class="lab-step">When all of the tubes have been filled with their respective test solutions, add 200 mL of water to a 400 mL beaker on a hotplate and set the hotplate to high.
</div></li><li data-sub-note-item="1-9"><div class="lab-step">To perform the Benedict&#39;s Test, add 2 mL of Benedict&#39;s reagent to test tubes A1, B1, C1, and D1 while the water is warming.
</div></li><li data-sub-note-item="1-10"><div class="lab-step">Observe the initial color of the tubes.
</div></li><li data-sub-note-item="1-11"><div class="lab-step">When the water begins to boil, transfer each test tube to the beaker and heat the tubes in the boiling water bath for 3 - 5 minutes.
</div></li><li data-sub-note-item="1-12"><div class="lab-step">Then, record the final color of each of the tubes in the appropriate cells of the table and turn off the hotplate. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/22/Table_1_Macromolecules.xlsx" style="display:block;margin:20px;" target="__blank">Click Here to download Table 1</a>
</div></li><li data-sub-note-item="1-13"><div class="lab-step">To perform an Iodine-Potassium-Iodide Test, first observe the color of the solutions in the test tubes in column 2.
</div></li><li data-sub-note-item="1-14"><div class="lab-step">Then, add 1 mL of iodine potassium iodide reagent to tubes A2 to D2 and record the final color change in each of the tubes.
</div></li><li data-sub-note-item="1-15"><div class="lab-step">For the Sudan IV Test, observe and record the color of the solutions in the test tubes in column 3.
</div></li><li data-sub-note-item="1-16"><div class="lab-step">Then, add 2 - 3 drops of Sudan IV reagent to test tubes A3 through D3 and record the color change, if any, in each tube.
</div></li><li data-sub-note-item="1-17"><div class="lab-step">For the Biuret Test, observe the color of the solutions in the test tubes in column 4.
</div></li><li data-sub-note-item="1-18"><div class="lab-step">Then, add 1 mL of Biuret reagent to test tubes A4 through D4 and record the final color in each of the tubes.
</div></li></ul></li><li data-note-item="2" data-parent-collapse="">Results
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="2-1"><div class="lab-step">Using the results from the indicator tests, each of the four original solutions can be identified as a sugar, starch, lipid, or protein. Refer to the Concepts video to help you determine which tubes contain which macromolecules.
</div></li><li data-sub-note-item="2-2"><div class="lab-step">First, look at the results from the Benedict&#39;s Test. Determine which of the test solutions contain sugar based on your results.
</div></li><li data-sub-note-item="2-3"><div class="lab-step">Next, create a bar graph with your five plant species listed on the x-axis and the surface area in cm indicated on the y-axis.
</div></li><li data-sub-note-item="2-4"><div class="lab-step">Next, look at the results from the Iodine-Potassium-Iodide Test. Determine which of the test solutions contain starch.
</div></li><li data-sub-note-item="2-5"><div class="lab-step">Now, review the results from the Sudan IV Test. Using these observations, determine if any of the test solutions contain lipids.
</div></li><li data-sub-note-item="2-6"><div class="lab-step">Finally, look at the results from the Biuret Test. Determine if any of the test solutions contain proteins.
</div></li></ul></li></ol>

Macromolecules: Identification Using Indicator Solutions - Procedure

Makrocząsteczek

Identifying Macromolecules with Indicator Solutions
ExpandHYPOTHESES: In this activity, the experimental hypothesis might be that the addition of an ...

Fundamentals

Natural Selection

<ol class="note-items"><li data-note-item="1" data-parent-collapse="">Simulating Natural Selection
<button class="expand">Expand</button><ul class="lab-items"><li data-sub-note-item="1-1"><div class="lab-step">To begin, cut the white, black, and gray pipe cleaners into quarters, which should produce a total of 100 pieces that are 3 inches long.
</div></li><li data-sub-note-item="1-2"><div class="lab-step">Then, cut the green pipe cleaners in the quantities and lengths specified in the video, taking care to minimize waste. This approximates a normal distribution of lengths and should result in an additional 100 pieces total. NOTE: One 12-inch pipe cleaner should yield multiple lengths, for example, a 5-inch piece and a 7-inch piece. Use this advantage to reduce waste.
</div></li><li data-sub-note-item="1-3"><div class="lab-step">Now, cut one sheet of black and one sheet of white construction paper into approximately 3-inch strips measured along the long edge of the paper.
</div></li><li data-sub-note-item="1-4"><div class="lab-step">Tape these strips down to cover the base of a dissecting tray to create an alternating pattern of black and white strips. NOTE: In the first simulation, you will use the white, gray, and black pipe cleaner segments against a black and white background to simulate different selection pressures due to predation on a population. You will select your prey using two different strategies, eyes-open and eyes-closed. For each of these strategies, you will perform four rounds consisting of 25 selections, alternating between two partners. After each round you will restore the population back to its original size using the proportions of phenotypes present after selection.
</div></li><li data-sub-note-item="1-5"><div class="lab-step">To begin the first scenario, count out 12 white, 12 black, and 26 gray pipe cleaner segments with your partner. Hypotheses: Here the experimental hypothesis might be that different predation strategies, such as having the eyes open or closed, will result in distinct selection pressures on the populations. Further, different phenotypes may be positively selected in the alternate scenarios. The null hypothesis might be that different predation strategies will have no effect on the populations or phenotypes.
</div></li><li data-sub-note-item="1-6"><div class="lab-step">Mix the pipe cleaner segments together as best as possible. Then, sprinkle them into the papered tray. NOTE: Ideally, the pipe cleaners will be spread out. However, this may not occur due to their self-adhering nature.
</div></li><li data-sub-note-item="1-7"><div class="lab-step">Once the segments are in the tray, separate them as best as possible without moving them too far from where they landed. As few segments as possible should be touching.
</div></li><li data-sub-note-item="1-8"><div class="lab-step">Have the first partner close their eyes. When given an audible signal by the second partner, the first should open their eyes and grab the first pipe cleaner they see from the tray as quickly as possible.
</div></li><li data-sub-note-item="1-9"><div class="lab-step">Set the removed pipe cleaner to the side.
</div></li><li data-sub-note-item="1-10"><div class="lab-step">Alternating partners, repeat this process a total of 25 times (steps 8 &#8211; 9).
</div></li><li data-sub-note-item="1-11"><div class="lab-step">Count the remaining pipe cleaners by color and record this in the data collection table for Scenario 1. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/23/Lab_23_Tables_1_and_2.xlsx" style="display:block;margin:20px;" target="__blank">Click Here to download Tables 1 and 2</a>
</div></li><li data-sub-note-item="1-12"><div class="lab-step">Then, restore the population to 50 by adding one pipe cleaner of the same color for each of the remaining pipe cleaners. Hold these to the side until they are all gathered.
</div></li><li data-sub-note-item="1-13"><div class="lab-step">Then, sprinkle the pipe cleaners into the tray as previously described (steps 6-7). Repeat this process for three more rounds consisting of 25 selections each and record the counts for each of the rounds in the data collection table for Scenario 1.
</div></li><li data-sub-note-item="1-14"><div class="lab-step">Remove all pipe cleaners from the tray after the fourth round.
</div></li><li data-sub-note-item="1-15"><div class="lab-step">For Scenario 2, again count out 12 white, 12 black, and 26 gray pipe cleaner segments and sprinkle them randomly into the tray.
</div></li><li data-sub-note-item="1-16"><div class="lab-step">Follow the same protocol as in Scenario 1. However, when given the signal, the grabbing partner should keep their eyes closed. To aid in accuracy, it may help to position the hand near to the tray before grabbing.
</div></li><li data-sub-note-item="1-17"><div class="lab-step">Repeat this process 25 times, switching partner roles, and record the remaining pipe cleaner amounts in the data collection table for Scenario 2.
</div></li><li data-sub-note-item="1-18"><div class="lab-step">Then, restore the population to 50 based on that count. Do this for all four rounds. NOTE: In the second simulation, you will be using the eyes-open and eyes-closed predation strategies as previously described to select pipe cleaners of various lengths.
</div></li><li data-sub-note-item="1-19"><div class="lab-step">For Scenario 3, gather all 100 of the pipe cleaners that have been cut to varying lengths to represent different phenotypes.
</div></li><li data-sub-note-item="1-20"><div class="lab-step">One partner should hold all the pipe cleaners upright and loosely in one hand resting on the tabletop, such that the bottom end of each pipe cleaner rests against the tabletop.
</div></li><li data-sub-note-item="1-21"><div class="lab-step">Now, the partner that is not holding the pipe cleaners should close their eyes. When given an audible signal, the partner should open their eyes and grab the first pipe cleaner they see from their partner&#39;s hand.
</div></li><li data-sub-note-item="1-22"><div class="lab-step">Repeat this process 50 times (step 21). However, the partners should not switch roles during the round this time. The partner holding the pipe cleaners should always be the one giving the signal and never grabbing from the bunch.
</div></li><li data-sub-note-item="1-23"><div class="lab-step">After the first round consisting of 50 selections, count the remaining pipe cleaners by length. Then, record this information in the data collection table for scenario three. <a href="https://www-jove-com.remotexs.ntu.edu.sg/CDNSource/lm/labs/23/Lab_23_Tables_3_and_4.xlsx" style="display:block;margin:20px;" target="__blank">Click Here to download Tables 3 and 4</a>
</div></li><li data-sub-note-item="1-24"><div class="lab-step">Add one pipe cleaner of the same length as each of the remaining ones to restore the population to 100. This will likely require more pipe cleaners than were originally cut. Try to use scraps from the class to reduce waste.
</div></li><li data-sub-note-item="1-25"><div class="lab-step">Repeat this for three more rounds, alternating which partner holds or grabs each round.
</div></li><li data-sub-note-item="1-26"><div class="lab-step">To perform Scenario 4, gather the varied-length pipe cleaners in their original proportions.
</div></li><li data-sub-note-item="1-27"><div class="lab-step">Now repeat the grabbing process, as described in Scenario 3. However, only remove 30 pipe cleaners instead of 50.
</div></li><li data-sub-note-item="1-28"><div class="lab-step">Divide the count at the end of each round by two for each phenotype 4 inches or below, rounding fractions down.
</div></li><li data-sub-note-item="1-29"><div class="lab-step">Then, record these values in the data recording table for Scenario 4.
</div></li><li data-sub-note-item="1-30"><div class="lab-step">Use the relative proportions of the phenotypes in the final population to restore the population to 100. When restoring the population to 100, it may be necessary to calculate relative proportions of phenotypes.
</div></li><li data-sub-note-item="1-31"><div class="lab-step">Repeat this for three more rounds, again alternating holding and grabbing the pipe cleaners.
</div></li><li data-sub-note-item="1-32"><div class="lab-step">For each scenario calculate the survival for each phenotype, that is the proportion of the phenotype surviving.
</div></li><li data-sub-note-item="1-33"><div class="lab-step">Then, calculate the relative fitness, or w, between each round. As reproductive rate does not vary in this simulation, this should always be considered equal, or 1.
</div></li><li data-sub-note-item="1-34"><div class="lab-step">Also, calculate the selection coefficients for each phenotype.
</div></li><li data-sub-note-item="1-35"><div class="lab-step">Now, use the relative frequencies of each phenotype to create histograms with appropriately labeled axes for each scenario showing the population before any selection took place and then alongside these in a different color after four rounds of selection.
</div></li><li data-sub-note-item="1-36"><div class="lab-step">Identify the type of selection taking place in each scenario and label the graphs. 
</div></li><li data-sub-note-item="1-37"><div class="lab-step">Develop a hypothesis to explain your observations. 
</div></li></ul></li></ol>

Natural Selection: Calculating Fitness and Selection - Procedure

Selekcja naturalna

Simulating Natural Selection
ExpandTo begin, cut the white, black, and gray pipe cleaners into quarters, which should produce a total of 100 pieces that ...