우리는 미국 농무부 농업 연구청과 국립 과학 재단 (IOS 1025881 및 IOS 1361554)으로부터 자금을 지원하고 싶습니다. 우리는 R. Caspers에게 온실 유지 관리 및 식물 관리에 감사드립니다. 우리는 Illumina 라이브러리 준비 및 시퀀싱이 수행 된 Minnesota Genomics Center 대학에도 감사드립니다. 저널 편집자와 4 명의 익명의 평론가가 우리 원고를 더욱 강화시킨 것에 대해 감사드립니다. 우리는 또한 OECD가 일본의 동료들과 협력 프로젝트를 위해 이러한 프로토콜을 통합하는 SK와의 협력에 감사한다.

<ol>
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저자는 경쟁적 이익이 없다고 선언합니다. 이 간행물의 상호 또는 상업 제품에 대한 언급은 특정 정보를 제공하기위한 목적 일 뿐이며 미 농무부 (US Department of Agriculture)의 추천이나 보증을 의미하지는 않습니다. USDA는 기회 균등 제공자이자 고용주입니다.

지금까지 대부분의 organellar sequencing 연구는 특정 DC를 풍부하게하는 전통적인 DC 방법에 초점을두고 있습니다. 모스 ( 40)를 포함하여 다양한 식물로부터 세포 소기관을 분리하는 방법이 설명되었다. 밀 15 및 귀리 11 과 같은 단핵구; 아라비돕시스 11 , 해바라기 17 , 유채 14 등의 족자입니다. ?...

<html> 게놈 시퀀싱은 중요한 식물 형질의 기본 유전 적 기초를 분석하는 강력한 도구입니다. 대부분의 게놈 시퀀싱 연구는 대부분의 유전자가 핵에 위치하므로 핵 게놈 내용에 초점을 맞 춥니 다. 그러나, (진핵 생물에서) 미토콘드리아와 색소체 포함 organellar 게놈 (식물, 전문화 된 형태로, 엽록체, 광합성에서 작동)는 생명체의 개발, 스트레스 반응 및 전반적인 체력 1에 필수적인 중요한 유전 정보를 기여한다. Organellar 게놈은 일반적으로 핵 게놈 시퀀싱을위한 총 DNA 추출에 포함되지만 DNA 추출 이전에 세포 소기관 수를 줄이는 방법도 사용됩니다 2 . 많은 연구에서 전체 gDNA 추출물의 sequencing 결과를 사용하여 organellar 게놈 3 , 4 , 5 ,xref &quot;&gt; 6 , 7. 그러나 연구 대상이 세포 소기관 게놈에 초점을 맞추고있을 때 많은 gDNA가 핵산 염기 서열에&quot;손실 &quot;되어 있기 때문에 전체 핵산을 사용하면 시퀀싱 비용이 증가합니다. 적당한 게놈, bioinformatically 8 도전 2에 관한 것이다. 또한, 염기 서열의 정확한지도 위치를 해결 중복 핵 게놈 내로 소기관 사이 organellar 서열의 전사에 의한 읽기. 핵 게놈 organellar 게놈의 정제 하나이다 전략을 사용하여 미토콘드리아와 엽록체 사이의 상 동성 영역으로 매핑되는 판독을 분리 할 수 ​​있습니다. 많은 식물 종의 세포 소기관 게놈이 서열화되어 있지만, 소기관 게놈 다양성의 폭은 거의 알려져 있지 않습니다야생 개체군 또는 경작 된 육종 풀에서 이용 가능하다. Organellar 게놈은 또한 반복 서열 9 사이의 재조합으로 인해 중요한 구조적 재 배열을 거친 동적 분자로 알려져있다. 또한, 세포 소기관 게놈의 여러 사본이 각 세포 소기관에 포함되어 있으며, 여러 세포 소기관이 각 세포 내에 포함되어 있습니다. 이 게놈의 모든 사본이 동일하다는 것은 이질균이라고 알려져 있습니다. &quot;마스터 서클&quot;의 정경과는 달리 하위 게놈 서클, 선형 염색체, 선형 concatamers 및 가지 형 구조 10을 포함하여 organellar 게놈 구조의 더 복잡한 그림에 대한 증거가 증가하고 있습니다. 식물 세포 소기관 게놈의 조립은 상대적으로 큰 크기와 상당한 거꾸로 된 직접 반복에 의해 더욱 복잡해진다. 세포 기관 분리, DNA 정제 및 후속 유전체에 대한 기존의 프로토콜<html> 전자 시퀀싱은 종종 성가 시며 많은 양의 조직을 필요로하며 수백 g의 어린 잎 조직을 출발점 11 , 12 , 13 , 14 , 15 , 16 , 17로 필요로 합니다. 이렇게하면 조직이 제한되어있을 때 세포 내 게놈 시퀀싱을 사용할 수 없게됩니다. 어떤 상황에서는, 세대 간 (through generational basis) 또는 교차점을 통해 유지되어야하는 수컷 멸균 계통에서 필요할 때와 같이, 종자의 양은 제한적이다. 이러한 상황에서 세포 내 소기관 DNA를 정제 한 다음 전체 게놈 증폭을 수행 할 수 있습니다. 그러나 전체 게놈 증폭은 구조적 변이, 하위 게놈 구조 및 이종성 수준을 평가할 때 특히 중요한 문제인 시퀀싱 바이어스를 도입 할 수 있습니다&gt; 18. 짧은 읽기 시퀀싱 기술에 대한 라이브러리 준비의 최근 발전은 전체 게놈 증폭을 피하기 위해 낮은 입력 장벽을 극복했습니다. 예를 들어, Illumina Nextera XT 라이브러리 준비 키트는 1 ng의 적은 DNA를 입력으로 사용할 수 있습니다 19 . 그러나 PacBio 또는 Oxford Nanopore 시퀀싱 기술과 같은 장시간 시퀀싱 응용 프로그램을위한 표준 라이브러리 준비에는 여전히 많은 양의 입력 DNA가 필요하며 이는 세포 내 게놈 시퀀싱에 대한 도전이 될 수 있습니다. 최근에, 입력량을 줄이고 마이크로 그램 - 양의 DNA를 얻기가 어려운 시료에서 게놈 시퀀싱을 용이하게하기 위해 사용자가 작성한 긴 판독 시퀀싱 프로토콜이 개발되었습니다 20 , 21 . 그러나, 고 분자량의 순수한 세포 내 소 분획을 이들 라이브러리 제제에 공급하는 것은 여전히 ​​어려운 과제이다. 우리는o 전체 게놈 증폭없이 NGS에 적합한 세포 내 DNA 농축 및 분리 방법을 비교 및 ​​최적화합니다. 구체적으로, 우리의 목표는 잎의 하위 샘플과 같이 제한된 출발 물질로부터 고 분자량 세포 기관 DNA를 풍부하게하는 우수 사례를 결정하는 것이 었습니다. 이 연구는 organellar DNA를 풍부하게하는 방법의 비교 분석을 제시한다 : (1) 상업적으로 이용 가능한 DNA CpG- 메틸 결합 도메인 단백질 풀다운 접근의 사용에 기초한 DNA 분획 프로토콜 (2) 수정 된 전통적인 분별 원심 분리 프로토콜 22 식물 조직에 적용 23 . 우리는 다른 식물 및 조직 유형으로 쉽게 확장 될 수있는 밀엽 조직으로부터 세포 기관 DNA를 분리하는 최상의 방법을 권장합니다.

<table border="0" cellpadding="0" cellspacing="0" width="685">
	<tbody>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">2-mercaptoethanol (beta-mercaptoethanol; BME)</td>
			<td style="width:183px;">Sigma Aldrich</td>
			<td style="width:119px;">M3148-100ml</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">2-propanol (Isopropyl alcohol/isopropanol), bioreagent</td>
			<td>Sigma Aldrich</td>
			<td>I9516</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">agarose, Bio-Rad Cetified Megabase agarose</td>
			<td>Bio-Rad</td>
			<td>1613108</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">analytical balance</td>
			<td>Mettler Toledo</td>
			<td>AB54-S</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">balance</td>
			<td>Mettler Toledo</td>
			<td>PB1502-S</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">bovine serum albumin (BSA)</td>
			<td>Sigma Aldrich</td>
			<td>B4287-25G</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Ceramic grinding cylinders, 3/8in x 7/8in</td>
			<td>SPEX SamplePrep</td>
			<td>2183</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:216px;">Cryogenic Blocks compatible with tissue homogenizer for holding 50 ml tubes</td>
			<td>SPEX SamplePrep</td>
			<td>2664</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">DNaseI</td>
			<td>Sigma</td>
			<td>DN25</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">ethanol, absolute</td>
			<td>Decon Laboratories</td>
			<td>2716</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Ethylenediamine Tetraacetic Acid (EDTA), 0.5M Solution, pH8.0</td>
			<td>Fisher</td>
			<td>BP2482-500</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">gel imaging system</td>
			<td></td>
			<td></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;width:216px;">gel stain</td>
			<td></td>
			<td></td>
			<td style="width:167px;">Such as GelRed or Ethidium Bromide</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">grinding pestle, wide tip for 2 ml conical tubes</td>
			<td></td>
			<td></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Guanidine-HCl, 8M solution</td>
			<td>ThermoFisher</td>
			<td>24115</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">LightCycler 480 SYBR Green I Master</td>
			<td>Roche</td>
			<td>4707516001</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">liquid nitrogen</td>
			<td></td>
			<td></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Lysing enzymes from Trichoderma harzianum</td>
			<td>Sigma</td>
			<td>L1412</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Magnesium Chloride</td>
			<td>G Bioscience</td>
			<td>24115</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">magnetic rack</td>
			<td>ThermoFisher</td>
			<td>A13346</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">microcentrifuge tubes, LoBind 1.5 ml&#160;</td>
			<td>Eppendorf</td>
			<td>22431021</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">microcentrifuge tubes, standard nuclease-free 1.5 ml</td>
			<td>Eppendorf</td>
			<td></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="120">
			<td height="120" style="height:120px;width:216px;">microcentrifuge, refrigerated</td>
			<td>Sorvall&#160;</td>
			<td>Legend X1R</td>
			<td style="width:167px;">Or equivalent product, must be capable of reaching at least 18,000 x g with rotors for 50 ml tubes, Oak Ridge tubes, and 1.5 ml tubes</td>
		</tr>
		<tr height="120">
			<td height="120" style="height:120px;width:216px;">microcentrifuge, room temperature</td>
			<td>Eppendorf</td>
			<td>5424</td>
			<td style="width:167px;">Or equivalent product, must be capable of reaching at least 18,000 x g with rotor for 1.5 ml and 2 ml microcentrifuge tubes</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Microcon DNA Fast Flow Centrifugal Filter Units</td>
			<td>EMD Millipore</td>
			<td>MRCFOR100</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Miracloth, 1 square per sample cut to fit funnel</td>
			<td>EMD Millipore</td>
			<td>475855</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">NEBNext Microbiome DNA Enrichment Kit</td>
			<td>New England Biolabs</td>
			<td>E2612L</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">parafilm</td>
			<td>Parafilm M</td>
			<td>PM992</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">plastic pots and trays</td>
			<td></td>
			<td></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">polyvinylpyrrolidone (PVP)</td>
			<td>Fisher</td>
			<td>BP431-100</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Proteinase K</td>
			<td>Qiagen</td>
			<td>19131</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Pulsed-Field Gel Electrophoresis rig (e.g. CHEF DR III)</td>
			<td>Bio-Rad</td>
			<td>1703697</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">purification beads, Agencourt AMpureXP beads</td>
			<td>Beckman Coulter</td>
			<td>A63881</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">QIAamp DNA Mini Kit</td>
			<td>Qiagen</td>
			<td>51304</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Qiagen 20/g Genomic Tip DNA Extraction Kit</td>
			<td>Qiagen</td>
			<td>10223</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Qiagen Buffer EB (elution buffer)</td>
			<td>Qiagen</td>
			<td>19086</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Qiagen DNA Extraction Buffer Set</td>
			<td>Qiagen</td>
			<td>19060</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">QiaRack</td>
			<td>Qiagen</td>
			<td>19015</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">qPCR machine (e.g. Roche Light Cycler 480)</td>
			<td>Roche</td>
			<td></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">qPCR plate sealing film</td>
			<td>Roche</td>
			<td>4729757001</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">qPCR plate, 96 well plate</td>
			<td>Roche</td>
			<td>4729692001</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Qubit&#160;assay tubes</td>
			<td>Life Technologies</td>
			<td>Q32856</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Qubit Broad Spectrum assay kit</td>
			<td>Life Technologies</td>
			<td>Q32850</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Qubit High Sensitivity assay kit</td>
			<td>Life Technologies</td>
			<td>Q32851</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">RNaseA</td>
			<td>Qiagen</td>
			<td>19101</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Serological pipettes (20 ml) and pipet-aid</td>
			<td>Fisher</td>
			<td>13-678-11</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Small funnels, 1 per sample</td>
			<td></td>
			<td></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Sodium Chloride</td>
			<td>Ambion</td>
			<td>AM9759</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Soft paintbrush, 2 per sample</td>
			<td></td>
			<td></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="260">
			<td height="260" style="height:260px;width:216px;">SPEX SamplePrep 2010 Geno/Grinder or another type of tissue homogenizer</td>
			<td>SPEX SamplePrep</td>
			<td></td>
			<td style="width:167px;">Or another comparable tissue homogenizer. If you do not have access to a tissue homogenizer, then grinding in a pre-chilled mortar and pestle will suffice (see protocol for details). However, a homogenizer will give more consistent results and total homogenization time is reduced.</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Sucrose</td>
			<td>Omnipure</td>
			<td>8550</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">TBE</td>
			<td></td>
			<td></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">thermomixer</td>
			<td></td>
			<td></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Tris</td>
			<td>Sigma</td>
			<td>T2819-100ml</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Triton X-100</td>
			<td>Promega</td>
			<td>H5142</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">tube rotater</td>
			<td></td>
			<td></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">tubes, 50 mL conical polypropylene</td>
			<td>Corning</td>
			<td>352070</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">tubes, 50 ml high-speed polypropylene&#160;</td>
			<td>ThermoScientific/Nalgene</td>
			<td>3119-0050</td>
			<td style="width:167px;">e.g. Nalgene Oakridge tubes or equivalent</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">vermiculite</td>
			<td></td>
			<td></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">water bath</td>
			<td></td>
			<td></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">water, sterile and certified Nuclease-free&#160;</td>
			<td>Fisher</td>
			<td>1481</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">water, sterile milliQ</td>
			<td></td>
			<td></td>
			<td style="width:167px;"></td>
		</tr>
	</tbody>
</table>

optimization and comparative analysis of plant organellar dna enrichment methods suitable for next-generation sequencing

식물 세포 소기관 게놈은 복잡한 구조 및 / 또는 서브 게놈 조각을 형성하기 위해 페어링 또는 재조합을 거칠 수있는 크고 반복적 인 요소를 포함합니다. Organellar 게놈은 또한 주어진 세포 또는 조직 유형 (heteroplasmy) 내의 혼합물에 존재하며, 아형의 다량은 발육 기간 동안 또는 스트레스하에있을 때 (부분 화학량 론적 이동) 변화 할 수있다. 세포 기관 게놈 구조와 기능에 대한 더 깊은 이해를 위해서는 차세대 시퀀싱 (NGS) 기술이 필요합니다. 전통적인 sequencing 연구는 organellar DNA를 얻기 위해 몇 가지 방법을 사용합니다 : (1) 대량의 시작 조직이 사용되면 균질화되고 차등 원심 분리 및 / 또는 기울기 정화가 이루어집니다. (종자, 재료 또는 공간이 한정되어있는 경우, 즉) (2) 조직의 작은 양이 사용된다면, 동일한 프로세스는 (1) 충분한 DNA를 얻기 위해 전체 게놈 증폭 다음과 같이 수행된다. (3) 생물 정보학 분석은 seq전체 게놈 DNA를 분석하고 세포 기관 판독을 분석합니다. 이러한 모든 방법에는 고유 한 문제점과 단점이 있습니다. (1)에서 이와 같이 많은 양의 시작 조직을 얻는 것이 어려울 수 있습니다. (2)에서, 전체 게놈 증폭은 시퀀싱 바이어스를 도입 할 수있다; (3)에서 핵과 세포 내 게놈 간의 상동 성은 집합과 분석을 방해 할 수있다. 거대한 핵 게놈을 가진 식물에서, organellar DNA를 풍부하게하여 생물 정보학 분석을위한 서열화 비용 및 서열 복잡성을 줄이는 것이 유리하다. 여기에서 전통적인 차동 원심 분리 방법과 네 번째 방법 인 CpG- 메틸 풀다운 방식을 비교하여 총 게놈 DNA를 핵 및 세포 내 분획으로 분리합니다. 두 가지 방법 모두 미토콘드리아와 엽록체의 비율이 다르긴하지만 세포 내 소기관 서열에 대해 고도로 농축 된 DNA 인 NGS에 충분한 양의 DNA를 생산합니다. 우리는 밀 잎 조직을위한 이러한 방법의 최적화를 제시하고 주요 이점과 d샘플 입력, 프로토콜 용이성 및 다운 스트림 응용 프로그램의 맥락에서 각 접근법의 단점.

이 원고에 제시된 프로토콜은 식물 조직에서 세포 기관 DNA를 풍부하게하는 두 가지 방법을 설명합니다. 여기에 제시된 조건은 밀의 조직 최적화를 반영합니다. 프로토콜의 주요 단계, 필요한 조직 입력 및 DNA 출력의 비교는 그림 1에 설명되어 있습니다. 우리가 테스트 한 DC 프로토콜의 단계는 이전에 설명한 것과 비슷한 조건을 따른다 ( <strong class="x...

Watch this Scientific Journal Video about Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing at JoVE.com

Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing

2 가지 plant organellar DNA 농축 방법의 비교 및 ​​최적화가 제시됩니다 : 전통적인 차동 원심 분리 및 메틸화 상태에 기초한 총 gDNA 분획. 우리는 결과로 나오는 DNA 양과 품질을 평가하고, 짧은 읽기 차세대 시퀀싱에서의 성능을 시연하며, 장시간 읽기 단일 분자 시퀀싱에서의 사용 가능성에 대해 논의합니다.

차세대 시퀀싱에 적합한 식물성 세포질 DNA 농축 방법의 최적화 및 비교 분석

Plant organellar genomes contain large, repetitive elements that may undergo pairing or recombination to form complex structures and/or sub-genomic ...

optimization-comparative-analysis-plant-organellar-dna-enrichment

Research

JoVE Journal

Genetics

12.8K 조회수.  United States Department of Agriculture-Agricultural Research Service.  2 가지 plant organellar DNA 농축 방법의 비교 및 ​​최적화가 제시됩니다 : 전통적인 차동 원심 분리 및 메틸화 상태에 기초한 총 gDNA 분획. 우리는 결과로 나오는 DNA 양과 품질을 평가하고, 짧은 읽기 차세대 시퀀싱에서의 성능을 시연하며, 장시간 읽기 단일 분자 시퀀싱에서의 사용 가능성에 대해 논의합니다. 

비디오: Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing

Methyl-binding DNA capture Sequencing for Patient Tissues

Methylation is one of the essential epigenetic modifications to the DNA, which is responsible for the precise regulation of genes required for stable development and differentiation of different tissue types. Dysregulation of this process is often the hallmark of various diseases like cancer. Here, we outline one of the recent sequencing techniques, Methyl-Binding DNA Capture sequencing (MBDCap-seq), used to quantify methylation in various normal and disease tissues for large patient cohorts. We describe a detailed protocol of this affinity enrichment approach along with a bioinformatics pipeline to achieve optimal quantification. This technique has been used to sequence hundreds of patients across various cancer types as a part of the 1,000 methylome project (Cancer Methylome System).

Here we present a protocol to investigate genome wide DNA methylation in large scale clinical patient screening studies using the Methyl-Binding DNA Capture sequencing (MBDCap-seq or MBD-seq) technology and the subsequent bioinformatics analysis pipeline.

환자 조직에 대한 메틸 결합 DNA 캡처 시퀀싱

Methylation is one of the essential epigenetic modifications to the DNA, which is responsible for the precise regulation of genes required for stable ...

연구

유전학

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

This workflow allows novice researchers to leverage advanced computational resources such as cloud computing to carry out pairwise comparative transcriptomics. It also serves as a primer for biologists to develop data scientist computational skills, e.g. executing bash commands, visualization and management of large data sets. All command line code and further explanations of each command or step can be found on the wiki (<a href="https://wiki.cyverse.org/wiki/x/dgGtAQ">https://wiki.cyverse.org/wiki/x/dgGtAQ</a>). The Discovery Environment and Atmosphere platforms are connected together through the CyVerse Data Store. As such, once the initial raw sequencing data has been uploaded there is no more need to transfer large data files over an Internet connection, minimizing the amount of time needed to conduct analyses. This protocol is designed to analyze only two experimental treatments or conditions. Differential gene expression analysis is conducted through pairwise comparisons, and will not be suitable to test multiple factors. This workflow is also designed to be manual rather than automated. Each step must be executed and investigated by the user, yielding a better understanding of data and analytical outputs, and therefore better results for the user. Once complete, this protocol will yield de novo assembled transcriptome(s) for underserved (non-model) organisms without the need to map to previously assembled reference genomes (which are usually not available in underserved organism). These de novo transcriptomes are further used in pairwise differential gene expression analysis to investigate genes differing between two experimental conditions. Differentially expressed genes are then functionally annotated to understand the genetic response organisms have to experimental conditions. In total, the data derived from this protocol is used to test hypotheses about biological responses of underserved organisms.

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms

This protocol outlines a comparative de novo transcriptome assembly and annotation workflow for novice bioinformaticians. The workflow is available for free entirely through CyVerse and connected by the Data Store. Command line and graphical user interfaces are used, but all code needed is available to copy and paste.

CyVerse 리소스 활용<em&gt; 드 노보</em&gt; 비포장 (비 모델) 생물의 비교 전이학

This workflow allows novice researchers to leverage advanced computational resources such as cloud computing to carry out pairwise comparative ...

Assessment of DNA Contamination in RNA Samples Based on Ribosomal DNA

One method extensively used for the quantification of gene expression changes and transcript abundances is reverse-transcription quantitative real-time PCR (RT-qPCR). It provides accurate, sensitive, reliable, and reproducible results. Several factors can affect the sensitivity and specificity of RT-qPCR. Residual genomic DNA (gDNA) contaminating RNA samples is one of them. In gene expression analysis, non-specific amplification due to gDNA contamination will overestimate the abundance of transcript levels and can affect the RT-qPCR results. Generally, gDNA is detected by qRT-PCR using primer pairs annealing to intergenic regions or an intron of the gene of interest. Unfortunately, intron/exon annotations are not yet known for all genes from vertebrate, bacteria, protist, fungi, plant, and invertebrate metazoan species.
Here we present a protocol for detection of gDNA contamination in RNA samples by using ribosomal DNA (rDNA)-based primers. The method is based on the unique features of rDNA: their multigene nature, highly conserved sequences, and high frequency in the genome. Also as a case study, a unique set of primers were designed based on the conserved region of ribosomal DNA (rDNA) in the Poaceae family. The universality of these primer pairs was tested by melt curve analysis and agarose gel electrophoresis. Although our method explains how rDNA-based primers can be applied for the gDNA contamination assay in the Poaceae family,&#160;it could be easily used to other prokaryote and eukaryote species

Here, we present a protocol for tracing genomic DNA (gDNA) contamination in RNA samples. The presented method utilizes primers specific for the internal transcribed spacer region (ITS) of ribosomal DNA (rDNA) genes. The method is suited for reliable and sensitive detection of DNA contamination in most eukaryotes and prokaryotes.

Ribosomal DNA에 따라 RNA 샘플에서 DNA 오염 평가

One method extensively used for the quantification of gene expression changes and transcript abundances is reverse-transcription quantitative real-time ...

Purification of High Molecular Weight Genomic DNA from Powdery Mildew for Long-Read Sequencing

The powdery mildew fungi are a group of economically important fungal plant pathogens. Relatively little is known about the molecular biology and genetics of these pathogens, in part due to a lack of well-developed genetic and genomic resources. These organisms have large, repetitive genomes, which have made genome sequencing and assembly prohibitively difficult. Here, we describe methods for the collection, extraction, purification and quality control assessment of high molecular weight genomic DNA from one powdery mildew species, Golovinomyces cichoracearum. The protocol described includes mechanical disruption of spores followed by an optimized phenol/chloroform genomic DNA extraction. A typical yield was 7 &#181;g DNA per 150 mg conidia. The genomic DNA that is isolated using this procedure is suitable for long-read sequencing (i.e., &#62; 48.5 kbp). Quality control measures to ensure the size, yield, and purity of the genomic DNA are also described in this method. Sequencing of the genomic DNA of the quality described here will allow for the assembly and comparison of multiple powdery mildew genomes, which in turn will lead to a better understanding and improved control of this agricultural pathogen.

Described here is a method for the extraction, purification, and quality control of genomic DNA from the obligate biotrophic fungal pathogen, powdery mildew, for use in long-read genome sequencing.

긴 읽기 시퀀싱에 대한 흰가루병에서 높은 분자량의 게놈의 DNA의 정제

The powdery mildew fungi are a group of economically important fungal plant pathogens. Relatively little is known about the molecular biology and genetics ...

Robust DNA Isolation and High-throughput Sequencing Library Construction for Herbarium Specimens

Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with a number of challenges including sample preservation quality, degraded DNA, and destructive sampling of rare specimens. In order to more effectively use herbarium material in large sequencing projects, a dependable and scalable method of DNA isolation and library preparation is needed. This paper demonstrates a robust, beginning-to-end protocol for DNA isolation and high-throughput library construction from herbarium specimens that does not require modification for individual samples. This protocol is tailored for low quality dried plant material and takes advantage of existing methods by optimizing tissue grinding, modifying library size selection, and introducing an optional reamplification step for low yield libraries. Reamplification of low yield DNA libraries can rescue samples derived from irreplaceable and potentially valuable herbarium specimens, negating the need for additional destructive sampling and without introducing discernible sequencing bias for common phylogenetic applications. The protocol has been tested on hundreds of grass species, but is expected to be adaptable for use in other plant lineages after verification. This protocol can be limited by extremely degraded DNA, where fragments do not exist in the desired size range, and by secondary metabolites present in some plant material that inhibit clean DNA isolation. Overall, this protocol introduces a fast and comprehensive method that allows for DNA isolation and library preparation of 24 samples in less than 13 h, with only 8 h of active hands-on time with minimal modifications.

This article demonstrates a detailed protocol for DNA isolation and high-throughput sequencing library construction from herbarium material including rescue of exceptionally poor-quality DNA.

강력한 DNA 고립과 표 본관 표본에 대 한 높은 처리량 시퀀싱 도서관 건축

Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with ...

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Next-generation sequencing (NGS) is quickly revolutionizing how research into the genetic determinants of constitutional disease is performed. The technique is highly efficient with millions of sequencing reads being produced in a short time span and at relatively low cost. Specifically, targeted NGS is able to focus investigations to genomic regions of particular interest based on the disease of study. Not only does this further reduce costs and increase the speed of the process, but it lessens the computational burden that often accompanies NGS. Although targeted NGS is restricted to certain regions of the genome, preventing identification of potential novel loci of interest, it can be an excellent technique when faced with a phenotypically and genetically heterogeneous disease, for which there are previously known genetic associations. Because of the complex nature of the sequencing technique, it is important to closely adhere to protocols and methodologies in order to achieve sequencing reads of high coverage and quality. Further, once sequencing reads are obtained, a sophisticated bioinformatics workflow is utilized to accurately map reads to a reference genome, to call variants, and to ensure the variants pass quality metrics. Variants must also be annotated and curated based on their clinical significance, which can be standardized by applying the American College of Medical Genetics and Genomics Pathogenicity Guidelines. The methods presented herein will display the steps involved in generating and analyzing NGS data from a targeted sequencing panel, using the ONDRISeq neurodegenerative disease panel as a model, to identify variants that may be of clinical significance.

Targeted next-generation sequencing is a time- and cost-efficient approach that is becoming increasingly popular in both disease research and clinical diagnostics. The protocol described here presents the complex workflow required for sequencing and the bioinformatics process used to identify genetic variants that contribute to disease.

다음-세대 시퀀싱과 생물 정보학 파이프라인 헌법 질병의 유전 결정 요인 평가 대상

Next-generation sequencing (NGS) is quickly revolutionizing how research into the genetic determinants of constitutional disease is performed. The ...

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Conventional next-generation sequencing techniques (NGS) have allowed for immense genomic characterization for over a decade. Specifically, NGS has been used to analyze the spectrum of clonal mutations in malignancy. Though far more efficient than traditional Sanger methods, NGS struggles with identifying rare clonal and subclonal mutations due to its high error rate of ~0.5&#8211;2.0%. Thus, standard NGS has a limit of detection for mutations that are &#62;0.02 variant allele fraction (VAF). While the clinical significance for mutations this rare in patients without known disease remains unclear, patients treated for leukemia have significantly improved outcomes when residual disease is &#60;0.0001 by flow cytometry. In order to mitigate this artefactual background of NGS, numerous methods have been developed. Here we describe a method for Error-corrected DNA and RNA Sequencing (ECS), which involves tagging individual molecules with both a 16 bp random index for error-correction and an 8 bp patient-specific index for multiplexing. Our method can detect and track clonal mutations at variant allele fractions (VAFs) two orders of magnitude lower than the detection limit of NGS and as rare as 0.0001 VAF.

Next-generation sequencing (NGS) is a powerful tool for genomic characterization that is limited by the high error rate of the platform (~0.5&#8211;2.0%). We describe our methods of error-corrected sequencing that allow us to obviate the NGS error rate and detect mutations at variant allele fractions as rare as 0.0001.

드문 이벤트 감지 오류 수정 DNA와 RNA 시퀀싱을 사용 하 여

Conventional next-generation sequencing techniques (NGS) have allowed for immense genomic characterization for over a decade. Specifically, NGS has been ...

Amplification of Near Full-length HIV-1 Proviruses for Next-Generation Sequencing

The Full-Length Individual Proviral Sequencing (FLIPS) assay is an efficient and high-throughput method designed to amplify and sequence single, near full-length (intact and defective), HIV-1 proviruses. FLIPS allows determination of the genetic composition of integrated HIV-1 within a cell population. Through identifying defects within HIV-1 proviral sequences that arise during reverse transcription, such as large internal deletions, deleterious stop codons/hypermutation, frameshift mutations, and mutations/deletions in cis acting elements required for virion maturation, FLIPS can identify integrated proviruses incapable of replication. The FLIPS assay can be utilized to identify HIV-1 proviruses that lack these defects and are&#160;therefore potentially replication-competent. The FLIPS protocol involves: lysis of HIV-1 infected cells, nested PCR of near full-length HIV-1 proviruses (using primers targeted to the HIV-1 5&#39; and 3&#39; LTR), DNA purification and quantification, library preparation for Next-generation Sequencing (NGS), NGS, de novo assembly of proviral contigs, and a simple process of elimination for identifying replication-competent proviruses. FLIPS provides advantages over traditional methods designed to sequence integrated HIV-1 proviruses, such as single-proviral sequencing. FLIPS amplifies and sequences near full-length proviruses enabling replication competency to be determined, and also uses fewer amplification primers, preventing the consequences of primer mismatches. FLIPS is a useful tool for understanding the genetic landscape of integrated HIV-1 proviruses, especially within the latent reservoir, however, its utilization can extend to any application in which the genetic composition of integrated HIV-1 is required.

Full-length individual proviral sequencing (FLIPS) provides an efficient and high-throughput method for the amplification and sequencing of single, near full-length (intact and defective) HIV-1 proviruses and allows for determination of their potential replication-competency. FLIPS overcomes limitations of previous assays designed to sequence the latent HIV-1 reservoir.

다음-세대 시퀀싱에 대 한 전체 길이 HIV-1 Proviruses 근처의 증폭

The Full-Length Individual Proviral Sequencing (FLIPS) assay is an efficient and high-throughput method designed to amplify and sequence single, near ...

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

The identification of regulatory elements for a given target gene poses a significant technical challenge owing to the variability in the positioning and effect sizes of regulatory elements to a target gene. Some progress has been made with the bioinformatic prediction of the existence and function of proximal epigenetic modifications associated with activated gene expression using conserved transcription factor binding sites. Chromatin conformation capture studies have revolutionized our ability to discover physical chromatin contacts between sequences and even within an entire genome. Circular chromatin conformation capture coupled with next-generation sequencing (4C-seq), in particular, is designed to discover all possible physical chromatin interactions for a given sequence of interest (viewpoint), such as a target gene or a regulatory enhancer. Current 4C-seq strategies directly sequence from within the viewpoint but require numerous and diverse viewpoints to be simultaneously sequenced to avoid the technical challenges of uniform base calling (imaging) with next generation sequencing platforms. This volume of experiments may not be practical for many laboratories. Here, we report a modified approach to the 4C-seq protocol that incorporates both an additional restriction enzyme digest and qPCR-based amplification steps that are designed to facilitate a greater capture of diverse sequence reads and mitigate the potential for PCR bias, respectively. Our modified 4C method is amenable to the standard molecular biology lab for assessing chromatin architecture.

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

The identification of physical interactions between genes and regulatory elements is challenging but has been facilitated by chromosome conformation capture methods. This modification to the 4C-seq protocol mitigates PCR bias by minimizing over-amplification of PCR templates and maximizes the mappability of reads by incorporating an addition restriction enzyme digest step.

차세대 시퀀싱의 원형 염색체 구조를 사용 하 여 유전자 규제 시퀀스의 높은 처리량 Id (4 C-seq)를 캡처

The identification of regulatory elements for a given target gene poses a significant technical challenge owing to the variability in the positioning and ...

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level

Long INterspersed Elements-1 (LINEs/L1s) are repetitive elements that can copy and randomly insert in the genome resulting in genomic instability and mutagenesis. Understanding the expression patterns of L1 loci at the individual level will lend to the understanding of the biology of this mutagenic element. This autonomous element makes up a significant portion of the human genome with over 500,000 copies, though 99% are truncated and defective. However, their abundance and dominant number of defective copies make it challenging to identify authentically expressed L1s from L1-related sequences expressed as part of other genes. It is also challenging to identify which specific L1 locus is expressed due to the repetitive nature of the elements. Overcoming these challenges, we present an RNA-Seq bioinformatic approach to identify L1 expression at the locus specific level. In summary, we collect cytoplasmic RNA, select for polyadenylated transcripts, and utilize strand-specific RNA-Seq analyses to uniquely map reads to L1 loci in the human reference genome. We visually curate each L1 locus with uniquely mapped reads to confirm transcription from its own promoter and adjust mapped transcript reads to account for mappability of each individual L1 locus. This approach was applied to a prostate tumor cell line, DU145, to demonstrate the ability of this protocol to detect expression from a small number of the full-length L1 elements.

Here, we present a bioinformatic approach and analyses to identify LINE-1 expression at the locus specific level.

RNA 차세대 염기 서 열 분석 및 생물 정보학 파이프라인은 궤적 특이 수준에서 발현 된 라인-1s를 식별 한다

Long INterspersed Elements-1 (LINEs/L1s) are repetitive elements that can copy and randomly insert in the genome resulting in genomic instability and ...