Name: identification of circular rnas using rna sequencing
Uploaded: 2019-11-14T11:00:00
Description: Watch this Scientific Journal Video about Identification of Circular RNAs using RNA Sequencing at JoVE.com

우리는 인간의 뇌 조직의 제공에 대한 선 시의 배너 태양 건강 연구소 뇌와 신체 기증 프로그램 (BBDP)에 감사드립니다. BBDP는 국립 신경 장애 및 뇌졸중 연구소 (U24 NS072026 파킨슨 병 및 관련 장애에 대한 국가 뇌 및 조직 자원), 노화에 대한 국립 연구소 (P30AG19610 애리조나 알츠하이머 병 핵심 센터), 건강 서비스의 애리조나 부서 (계약 211002, 애리조나 알츠하이머 연구 센터), 애리조나 생물 의학 연구위원회 (계약 4001, 0011, 05-901 및 1001 애리조나 파킨슨 병 컨소시엄) 및 마이클 J. 파 킨 슨 병의 연구에 대 한 폭스 재단27. 이 연구는 또한 DHS와 애리조나 주 (ADHS 교부금 # ADHS14-052688)에 의해 지원되었다. 우리는 또한 안드레아 슈미트 (배너 연구)와 신시아 레슈가 (TGen) 행정 지원을 주셔서 감사합니다.

이 연구는 인간의 복지에 대한 모든 제도적, 국가적, 국제적 지침을 준수하여 수행되었습니다. 뇌 조직은 애리조나 주 선시티에 있는 배너 선 건강 연구소 뇌 및 신체 기증 프로그램에서 얻어졌습니다. 두뇌와 바디 기증 프로그램의 운영은 서부 기관 검토 위원회 (WIRB 프로토콜 #20120821)에 의해 승인됩니다. 모든 주체 또는 법정 대리인은 통보된 동의서에 서명했습니다. 상업적(비뇌) 생물표본은 프?...

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본 연구에서, 시판되는 2개의 라이브러리 준비 키트, 전처리 옵션 및 입력 RNA 양은 circRNA 염기서열 분석 라이브러리의 시공을 위한 circRNA 농축 프로토콜을 최적화하기 위해 시험되었다. 이 연구의 평가에 기초하여, circRNA 염기서열 분석 라이브러리를 만드는 중요한 단계및 중요한 단계의 숫자는 명백하다. 우리의 평가는 검출된 circRNAs의 증가수에 의해 반영되는 RNase R 전처리의 유용성을 확인합니?...

원형 RNA(CircRNAs)는 진핵 전사체1,2,3에서그들의 만연한 발현을 감안할 때 주목을 받고 있는 내인성, 비코딩 RNA이다. 그(것)들은 exons가 서로 에 다시 접합할 때 형성되고, 그러므로 처음에 접합유물4,5로여겨졌습니다 . 그러나, 최근 연구에 따르면 circRNAs는 세포 유형, 조직 및 발달 단계 특이적 발현3,6을 나타내고 진화적으로 보존되는2,3. 더욱이, 이들은 단백질-단백질 상호작용7,마이크로RNA(miRNA) 결합3,8,9,10,및 부모 유전자전사(11)의조절에 관여한다.
고전적인 RNA 염기서열 분석(RNA-seq)에서, circRNAs는 mRNA를 위한 폴리-A 선택의 결과로 라이브러리 시공 도중 완전히 손실될 수 있거나 그들의 낮은 풍부도를 감안할 때 격리하기 어려울 수 있습니다. 그러나, 최근 circRNA 특성화 연구는 CircRNAs2,12,13을풍부하게 하기 위해 RNase R을 이용한 전처리 단계를 통합했다. RNase R은 선형 RNA를 소화하는 외분비증으로, 원형 RNA 구조를 남깁니다. CircRNA 농축 프로토콜은 RNase R 전처리 단계의 유무에 관계없이 시판되는 두 개의 전체 전사체 라이브러리 구성 키트에서 데이터를 생성 및 비교하고 다양한 양의 총 RNA 입력(1 ~ 4 μg)을 사용하여 최적화되었습니다. 최적화된 프로토콜은 5개의 상이한 뇌 영역(소뇌 [BC], 열등한 정수리 엽 [IP], 중간 측두엽 [MG], 후두 피질 [OC] 및 우수한 전두엽 자이러스 [SF]) 및 4개의 다른 조직 유형(간[LV], 폐[LU]] 및 파프린스 [LN]에 걸쳐 circRNAs의 풍부를 평가하는 데 사용되었다. RNA-seq 라이브러리는 짝을 이루고 데이터를 6개의 상이한 circRNA 예측 알고리즘을 사용하여 분석했다: find_circ3,CIRI14,Mapsplice15,나이프16,DCC17,및 CIRCexplorer18. 우리의 분석에 기초하여, RNase R 전처리 및 4 μg 총 입력 RNA를 가진 좌초된 총 RNA 라이브러리 준비 키트를 사용할 때 가장 많은 고유 circRNAs가 검출되었다. 최적화된 프로토콜은 여기에 설명되어 있습니다. 이전에 보고 된 바와 같이19,20,circRNAs의 가장 높은 농축은 다른 조직 유형에 비해 뇌에서 관찰되었다.

<table>
	<tbody>
		<tr>
			<td>1000 &#181;L pipette tips</td>
			<td>Rainin</td>
			<td>GP-L1000F</td>
			<td></td>
		</tr>
		<tr>
			<td>20 &#181;L pipette tips</td>
			<td>Rainin</td>
			<td>SR L 10F</td>
			<td></td>
		</tr>
		<tr>
			<td>200 &#181;L pipette tips</td>
			<td>Rainin</td>
			<td>SR L 200F</td>
			<td></td>
		</tr>
		<tr>
			<td>2200 TapeStation Accessories (foil covers)</td>
			<td>Agilent Technologies</td>
			<td>5067-5154</td>
			<td></td>
		</tr>
		<tr>
			<td>2200 TapeStation Accessories (tips)</td>
			<td>Agilent Technologies</td>
			<td>5067-5153</td>
			<td></td>
		</tr>
		<tr>
			<td>Adhesive Film for Microplates</td>
			<td>VWR</td>
			<td>60941-064</td>
			<td></td>
		</tr>
		<tr>
			<td>AMPure XP Beads 450 mL</td>
			<td>Beckman Coulter</td>
			<td>A63882</td>
			<td>PCR purification</td>
		</tr>
		<tr>
			<td>Eppendorf twin.tec 96-Well PCR Plates</td>
			<td>VWR</td>
			<td>951020401</td>
			<td></td>
		</tr>
		<tr>
			<td>High Sensitivity D1000 reagents</td>
			<td>Agilent Technologies</td>
			<td>5067-5585</td>
			<td></td>
		</tr>
		<tr>
			<td>High Sensitivity D1000 ScreenTape</td>
			<td>Agilent Technologies</td>
			<td>5067-5584</td>
			<td></td>
		</tr>
		<tr>
			<td>HiSeq 2500 Sequencing System</td>
			<td>Illumina</td>
			<td>SY-401-2501</td>
			<td></td>
		</tr>
		<tr>
			<td>HiSeq 3000/4000 PE Cluster Kit</td>
			<td>Illumina</td>
			<td>PE-410-1001</td>
			<td></td>
		</tr>
		<tr>
			<td>HiSeq 3000/4000 SBS Kit (150 cycles)</td>
			<td>Illumina</td>
			<td>FC-410-1002</td>
			<td></td>
		</tr>
		<tr>
			<td>HiSeq 4000 Sequencing System</td>
			<td>Illumina</td>
			<td>SY-401-4001</td>
			<td></td>
		</tr>
		<tr>
			<td>HiSeq PE PE Rapid Cluster Kit v2</td>
			<td>Illumina</td>
			<td>PE-402-4002</td>
			<td></td>
		</tr>
		<tr>
			<td>HiSeq Rapid SBS Kit v2 (50 cycle)</td>
			<td>Illumina</td>
			<td>FC-402-4022</td>
			<td></td>
		</tr>
		<tr>
			<td>Kapa Total RNA Kit</td>
			<td>Roche</td>
			<td>KK8400</td>
			<td></td>
		</tr>
		<tr>
			<td>Molecular biology grade ethanol</td>
			<td>Fisher Scientific</td>
			<td>BP28184</td>
			<td></td>
		</tr>
		<tr>
			<td>Qubit Assay Tubes</td>
			<td>Supply Center by Thermo Fischer</td>
			<td>Q32856</td>
			<td></td>
		</tr>
		<tr>
			<td>Qubit dsDNA High Sense Assay Kit</td>
			<td>Supply Center by Thermo Fischer</td>
			<td>Q32854</td>
			<td></td>
		</tr>
		<tr>
			<td>RNA cleanup and concentrator - 5</td>
			<td>Zymo</td>
			<td>RCC-100</td>
			<td>Contains purification columns, collection tubes</td>
		</tr>
		<tr>
			<td>RNAClean XP beads</td>
			<td>Beckman Coulter Genomics</td>
			<td></td>
			<td>RNA Cleanup beads</td>
		</tr>
		<tr>
			<td>Rnase R</td>
			<td>Lucigen</td>
			<td>RNR07250</td>
			<td></td>
		</tr>
		<tr>
			<td>SuperScript II Reverse Transcriptase 10,000 units</td>
			<td>ThermoFisher (LifeTech)</td>
			<td>18064014</td>
			<td></td>
		</tr>
		<tr>
			<td>TapeStation 2200</td>
			<td>Agilent Technologies</td>
			<td></td>
			<td>Nucleic Acid analyzer</td>
		</tr>
		<tr>
			<td>TElowE</td>
			<td>VWR</td>
			<td>10128-588</td>
			<td></td>
		</tr>
		<tr>
			<td>TruSeq Stranded Total RNA Library Prep Kit</td>
			<td>Illumina</td>
			<td>20020596</td>
			<td>Kit used in section 3</td>
		</tr>
		<tr>
			<td>Two-Compartment Divided Tray</td>
			<td>VWR</td>
			<td>3054-1004</td>
			<td></td>
		</tr>
		<tr>
			<td>UltraPure Water</td>
			<td>Supply Center by Thermo Fischer</td>
			<td>10977-015</td>
			<td></td>
		</tr>
		<tr>
			<td>Universal control RNA</td>
			<td>Agilent</td>
			<td>740000</td>
			<td></td>
		</tr>
	</tbody>
</table>

identification of circular rnas using rna sequencing

원형 RNA (circRNAs)는 마이크로 RNA (miRNA) 규정, 단백질 상호 작용의 중재 및 부모 유전자 전사의 조절을 포함하는 기능에 관여하는 비 코딩 RNA의 부류입니다. 고전적인 차세대 RNA 염기서열 분석(RNA-seq)에서 circRNAs는 전형적으로 mRNA 라이브러리의 시공 동안 폴리-A 선택의 결과로 간과되거나 매우 낮은 풍부함에서 발견되며, 따라서 분리 및 검출하기 가 어렵습니다. 여기서, circRNA 라이브러리 시공 프로토콜은 라이브러리 제제 키트, 전처리 옵션 및 다양한 총 RNA 입력 량을 비교하여 최적화되었다. RNase R 전처리 및 가변 적인 양의 총 RNA 입력(1~ 4 μg)을 사용 하 여 2 개의 시판 된 전체 전사체 라이브러리 준비 키트를 테스트 했습니다. 마지막으로, 여러 조직 유형; 간을 포함 하 여, 폐, 림프절, 그리고 췌 장; 뿐만 아니라 여러 뇌 영역; 소뇌, 열등한 정수리 엽, 중간 측두엽, 후두 피질 및 우수한 전두엽 자이러스를 포함; 조직 모형에 걸쳐 circRNA 풍부를 평가하기 위하여 비교되었습니다. 6개의 서로 다른 circRNA 검출 도구(find_circ, CIRI, Mapsplice, KNIFE, DCC 및 CIRCexplorer)를 사용하여 생성된 RNA-seq 데이터를 분석한 결과 RNase R 전처리 및 4 μg RNA 입력을 사용한 총 RNA 라이브러리 준비 키트가 최적임을 밝혀냈습니다. circRNAs의 가장 높은 상대 수를 식별하는 방법. 이전 사실 인정과 일치, circRNAs의 가장 높은 농축 다른 조직 유형에 비해 뇌 조직에서 관찰 되었다.

시판되는 범용 제어 RNA(UC)를 사용하여 생성된 데이터와 두 개의 라이브러리 준비 키트를 사용하여 생성된 데이터는 둘 다 프로토콜에서 리보 고갈 단계를 포함하고, 먼저 평가되었다. 분석 워크플로우(데이터 분석 워크플로우, 섹션 4)를 사용하여 전체적으로 Kapa 데이터 집합에 비해 TruSeq 데이터 집합에서 더 많은 수의 circRNAs가 검출되었습니다(그림1). 리보소말 RNA(rRNA) 백분?...

Watch this Scientific Journal Video about Identification of Circular RNAs using RNA Sequencing at JoVE.com

Identification of Circular RNAs using RNA Sequencing

원형 RNA (circRNAs)는 단백질 사이 전사 규칙 그리고 중재 상호 작용에 있는 역할을 할 수 있는 비 코딩 RNA입니다. circRNA 염기서열 분석 라이브러리의 구성을 위한 상이한 파라미터의 평가에 이어, RNase R 전처리와 함께 좌초된 총 RNA 라이브러리 제제를 활용한 프로토콜이 컴파일되고 여기에 제시된다.

RNA 시퀀싱을 사용하는 원형 RNA 식별

Circular RNAs (circRNAs) are a class of non-coding RNAs involved in functions including micro-RNA (miRNA) regulation, mediation of protein-protein ...

이 프로토콜은 키트 유형, RNase R 처리, 입력 금액 및 circRNA 검출에 미치는 영향과 같은 circRNA 라이브러리 준비의 주요 측면을 평가한 결과입니다. 최적의 circRNA 검출을 가능하게 하고 사용자의 요구에 따라 조정 가능한 매개 변수에 대한 데이터를 제공합니다. 다른 견본 모형에 있는 circRNAs를 확인하는 것은 우리가 그들의 표현의 분포를 더 잘 이해하고 이 분자의 기능적인 역할을 delineating를 위한 무대를 설정하는 것을 도울 것입니다.이 방법은 모든 총 RNA 샘플에 적용될 수 있다. 프로토콜을 시작하기 전에 RNA 샘플을 얼음 위에 유지하는 것이 중요합니다. 준비 전에 Agilent Bio analyzer 또는 TapeStation에서 RIN 및 DV200 값을 평가하고 RNA로 작업할 때 적절한 절차를 따릅니다.RNase 가 없는 물의 39 마이크로리터에 총 RNA를 4 마이크로그램으로 희석하고 혼합하기 위해 위아래로 파이프팅하는 것으로 시작합니다. 별도의 튜브에서 1x RNase R 버퍼를 사용하여 RNase R을 마이크로리터 당 2 단위의 작동 농도로 희석하십시오. 파이펫 39 마이크로리터의 총 RNA및 10x RNase R 반응 버퍼의 5개의 마이크로리터를 1.5 마이크로리터 반응 튜브로 혼합하고 혼합한다.희석 된 RNase R.의 6 마이크로 리터를 추가 한 다음 파이펫을 전체 반응 볼륨으로 조정하고 10 배 위아래로 파이펫을 사용하여 용액을 혼합합니다. 튜브를 섭씨 37도 의 수조에 10 분 동안 놓고 전체 반응 량이 수조에 침지되도록하십시오. 그런 다음 튜브를 얼음 위에 놓고 RNA 정화 및 농도를 즉시 진행합니다.시작하기 전에, 100% 에탄올의 48 밀리리터와 농축물을 혼합하여 RNA 세척 버퍼를 준비하고, 정화 컬럼을 수집 튜브에 배치한다. 준비가 되면, RNase R 처리 된 샘플에 RNA 결합 버퍼의 두 볼륨을 추가하고 잘 혼합. 총 300 마이크로리터를 혼합물에 100% 에탄올150 마이크로리터를 추가하고 전체 부피를 기둥으로 옮기고 원심분리기를 30초 간 전달합니다.흐름을 제거하고 400 마이크로리터의 RNA 준비 버퍼를 컬럼에 직접 추가합니다. 30초 동안 원심분리기를 제거하고 흐름을 폐기합니다. 그런 다음 700 마이크로리터의 RNA 워시 버퍼를 컬럼에 넣고 30초 동안 원심분리기를 넣고 흐름을 폐기합니다.워시 버퍼의 400 마이크로리터를 추가하면 원심분리기를 2분 간 추가하고 컬럼을 신선한 RNase 가 없는 1.5밀리리터 튜브로 옮겨 넣습니다. 기둥 필터 바로 위에 파이펫 팁을 붙이면 RNase가 없는 물 11마이크로리터를 기둥에 직접 추가하십시오. 샘플이 실온에서 1 분 동안 앉아서 원심 분리하여 1 분 동안 앉게하십시오.1.5 밀리리터 튜브에 흐름이 있는지 확인하고 컬럼을 폐기하십시오. 정제 된 RNA 샘플은 영하 80도에서 저장하거나 도서관 준비를 위해 즉시 사용할 수 있습니다. 정제된 총 RNA의 10마이크로리터를 96웰 PCR 플레이트에서 깨끗한 우물로 옮는다.rRNA 바인딩 버퍼의 5 마이크로 리터를 추가 한 다음 rRNA 제거 믹스의 5 마이크로 리터다음 부드럽게 시약을 혼합하기 위해 위아래로 파이펫. 플레이트를 밀봉하고 사전 프로그래밍되고 예열된 열순환기 블록에서 섭씨 68도에서 5분간 인큐베이션하십시오. 인큐베이션 후, 접시가 실온에 1 분 동안 앉게하십시오.플레이트에서 씰을 제거하고, 샘플에 소용돌이 실온 rRNA 제거 구슬의 35 마이크로 리터를 추가합니다. 파이펫을 45마이크로리터로 조정하고 파이펫을 10~20회 위아래로 조정하여 철저히 섞습니다. 접시가 실온에 1 분 동안 앉게하십시오.플레이트를 마그네틱 스탠드로 옮기고 1분 동안 또는 용액이 지워지도록 배양합니다. 상체를 플레이트의 새로운 우물로 옮기. 그런 다음 마그네틱 스탠드에서 플레이트 스탠드로 플레이트를 옮기합니다.소용돌이 RNA 정화 구슬은 잘 분산 될 때까지 구슬을 청소하고 샘플에 구슬 99 마이크로 리터를 추가합니다. 파이펫을 위아래로 섞고 실온에서 10분 동안 플레이트를 배양합니다. 접시를 자기 스탠드로 옮기고 5분 동안 또는 용액이 지워질 때까지 그대로 두고 우물에서 모든 상퍼를 제거하고 폐기합니다.플레이트가 마그네틱 스탠드에 남아 있는 동안, 비드를 방해하지 않고 신선하게 준비된 80%에탄올 200마이크로리터를 우물에 넣습니다. 에탄올을 30초 동안 우물에 두고 제거하여 버립니다. 11 마이크로리터의 용출 버퍼를 웰에 넣고 파이펫을 위아래로 섞어 넣습니다.플레이트를 실온에서 2분간 배양한 다음 다시 마그네틱 스탠드로 옮기고 용액이 지울 때까지 보관하십시오. 동일한 플레이트에 있는 새로운 우물에 수퍼티의 8.5 마이크로리터를 옮기고, 샘플을 포함하는 각 웰에 Elute, 프라이머, 단편 높은 믹스의 8.5 마이크로리터를 추가합니다. 파이펫을 10회 위아래로 위아래로 섞어 플레이트를 밀봉하고, 섭씨 94도로 예열된 열순환기에서 8분간 배양합니다.샘플을 섭씨 4도로 냉각하고, 열순환기에서 플레이트를 제거하고, 원심분리기를 간단히 제거합니다. 두 개의 라이브러리 준비 키트, TruSeq와 KAPA, 이 프로토콜에 대 한 평가 되었다. 전반적으로, TruSeq 키트를 사용할 때 원형 RNA의 더 높은 수와 리보소말 RNA의 낮은 백분율이 검출되었기 때문에 TruSeq는 추가 실험을 위해 선택되었습니다.RNase R 전처리의 중요성은 전처리 및 비처리 라이브러리에서 생성된 데이터를 비교하여 평가하였다. 예상대로, 비처리 된 라이브러리에 비해 전처리 된 라이브러리에서 더 많은 수의 원형 RNA가 일관되게 확인되었습니다. 입력 RNA의 양은 원형 RNA의 더 높은 다양성을 검출하기 위해 최적화되었다.라이브러리는 1, 2, 4 마이크로그램의 입력 RNA를 사용하여 제조되었고, 총 RNA의 4마이크로그램을 사용할 때 원형 RNA 종의 가장 높은 다양성을 관찰하였다. 최적화된 프로토콜은 4명의 건강한 기증자에서 5개의 두뇌 지구에 있는 원형 RNA 풍부를 비교하고 6명의 건강한 기증자에게서 그밖 조직 모형을 위해 이용되었습니다. 전반적으로, 원형 RNase의 높은 풍부는 다른 조직 모형에 비해 두뇌에서 관찰되었습니다.장갑착용, RNase 와이프 또는 스프레이로 벤치 및 파이펫을 철저히 청소하고 프로토콜을 시작하기 전에 건조시 와 파이펫을 철저히 청소하고, RNA를 사전에 얼음에 보관하는 등 RNA와 함께 작업할 때 적절한 절차를 따르는 것이 중요합니다. 이 절차에 따라 확인된 circRNA 접합의 Sanger 시퀀싱과 같은 직교 유효성 검사를 수행할 수 있습니다. 새로운 circRNAs의 발견과 그들의 존재의 추가 증거는 그들의 생물학 기능을 탐구하기 위한 연구의 새로운 지역을 개척합니다.

identification-of-circular-rnas-using-rna-sequencing

Research

JoVE Journal

Genetics

Mapping RNA-RNA Interactions Globally Using Biotinylated Psoralen

Knowing how RNAs interact with themselves and with others is key to understanding RNA based gene regulation in the cell. While examples of RNA-RNA interactions such as microRNA-mRNA interactions have been shown to regulate gene expression, the full extent to which RNA interactions occur in the cell is still unknown. Previous methods to study RNA interactions have primarily focused on subsets of RNAs that are interacting with a particular protein or RNA species. Here, we detail a method named Sequencing of Psoralen crosslinked, Ligated, and Selected Hybrids (SPLASH) that allows genome-wide capture of RNA interactions in vivo in an unbiased manner. SPLASH utilizes in vivo crosslinking, proximity ligation, and high throughput sequencing to identify intramolecular and intermolecular RNA base-pairing partners globally. SPLASH can be applied to different organisms including bacteria, yeast and human cells, as well as diverse cellular conditions to facilitate the understanding of the dynamics of RNA organization under diverse cellular contexts. The entire experimental SPLASH protocol takes about 5 days to complete and the computational workflow takes about 7 days to complete.

Here, we detail the method of Sequencing of Psoralen crosslinked, Ligated, and Selected Hybrids (SPLASH), which enables genome-wide mapping of intramolecular and intermolecular RNA-RNA interactions in vivo. SPLASH can be applied to study RNA interactomes of organisms including yeast, bacteria and humans.

Biotinylated Psoralen을 사용하여 RNA-RNA 상호 작용을 세계적으로 매핑

Knowing how RNAs interact with themselves and with others is key to understanding RNA based gene regulation in the cell. While examples of RNA-RNA ...

연구

유전학

Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays

Transfer RNAs (tRNA) are abundant short non-coding RNA species that are typically 76 to 90 nucleotides in length. tRNAs are directly responsible for protein synthesis by translating codons in mRNA into amino acid sequences. tRNAs were long considered as house-keeping molecules that lacked regulatory functions. However, a growing body of evidence indicates that cellular tRNA levels fluctuate in correspondence to varying conditions such as cell type, environment, and stress. The fluctuation of tRNA expression directly influences gene translation, favoring or repressing the expression of particular proteins. Ultimately comprehending the dynamic of protein synthesis requires the development of methods able to deliver high-quality tRNA profiles. The method that we present here is named SPOt, which stands for Streamlined Platform for Observing tRNA. SPOt consists of three steps starting with metabolic labeling of cell cultures with radioactive orthophosphate, followed by guanidinium thiocyanate-phenol-chloroform extraction of radioactive total RNAs and finally hybridization on in-house printed macroarrays. tRNA levels are estimated by quantifying the radioactivity intensities at each probe spot. In the protocol presented here we profile tRNAs in Mycobacterium smegmatis mc2155, a nonpathogenic bacterium often used as a model organism to study tuberculosis.

We describe an original transfer RNA analysis platform named SPOt (Streamlined Platform for Observing tRNA). SPOt simultaneously measures cellular levels of all tRNAs in biological samples, in only three steps, and in less than 24 hours.

신진 대사 라벨 및 Macroarrays를 사용 하 여 전송 RNAs의 프로 파일링

Transfer RNAs (tRNA) are abundant short non-coding RNA species that are typically 76 to 90 nucleotides in length. tRNAs are directly responsible for ...

Retrospective MicroRNA Sequencing: Complementary DNA Library Preparation Protocol Using Formalin-fixed Paraffin-embedded RNA Specimens

&#8211;Archived, clinically classified formalin-fixed paraffin-embedded (FFPE) tissues can provide nucleic acids for retrospective molecular studies of cancer development. By using non-invasive or pre-malignant lesions from patients who later develop invasive disease, gene expression analyses may help identify early molecular alterations that predispose to cancer risk. It has been well described that nucleic acids recovered from FFPE tissues have undergone severe physical damage and chemical modifications, which make their analysis difficult and generally requires adapted assays. MicroRNAs (miRNAs), however, which represent a small class of RNA molecules spanning only up to ~18&#8211;24 nucleotides, have been shown to withstand long-term storage and have been successfully analyzed in FFPE samples. Here we present a 3&#39; barcoded complementary DNA (cDNA) library preparation protocol specifically optimized for the analysis of small RNAs extracted from archived tissues, which was recently demonstrated to be robust and highly reproducible when using archived clinical specimens stored for up to 35 years. This library preparation is well adapted to the multiplex analysis of compromised/degraded material where RNA samples (up to 18) are ligated with individual 3&#39; barcoded adapters and then pooled together for subsequent enzymatic and biochemical preparations prior to analysis. All purifications are performed by polyacrylamide gel electrophoresis (PAGE), which allows size-specific selections and enrichments of barcoded small RNA species. This cDNA library preparation is well adapted to minute RNA inputs, as a pilot polymerase chain reaction (PCR) allows determination of a specific amplification cycle to produce optimal amounts of material for next-generation sequencing (NGS). This approach was optimized for the use of degraded FFPE RNA from specimens archived for up to 35 years and provides highly reproducible NGS data.

Formalin-fixed paraffin-embedded specimens represent a valuable source of molecular biomarkers of human diseases. Here we present a laboratory-based cDNA library preparation protocol, initially designed with fresh frozen RNA, and optimized for the analysis of archived microRNAs from tissues stored up to 35 years.

회고전 예측에 관한 시퀀싱: 보완 DNA 도서관 준비 프로토콜 포 르 말린 고정 파라핀 포함 RNA 견본을 사용 하 여

&#8211;Archived, clinically classified formalin-fixed paraffin-embedded (FFPE) tissues can provide nucleic acids for retrospective molecular studies of ...

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 ...

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 ...

Overexpressing Long Noncoding RNAs Using Gene-activating CRISPR

Long noncoding RNA (lncRNA) biology is a new and exciting field of research, with the number of publications from this field growing exponentially since 2007. These studies have confirmed that lncRNAs are altered in almost all diseases. However, studying the functional roles for lncRNAs in the context of disease remains difficult due to the lack of protein products, tissue-specific expression, low expression levels, complexities in splice forms, and lack of conservation among species. Given the species-specific expression, lncRNA studies are often restricted to human research contexts when studying disease processes. Since lncRNAs function at the molecular level, one way to dissect lncRNA biology is to either remove the lncRNA or overexpress the lncRNA and measure cellular effects. In this article, a written and visualized protocol to overexpress lncRNAs in vitro is presented. As a representative experiment, an lncRNA associated with inflammatory bowel disease, Interferon Gamma Antisense 1 (IFNG-AS1), is shown to be overexpressed in a Jurkat T-cell model. To accomplish this, the activating clustered regularly interspaced short palindromic repeats (CRISPR) technique is used to enable overexpression at the endogenous genomic loci. The activating CRISPR technique targets a set of transcription factors to the transcriptional start site of a gene, enabling a robust overexpression of multiple lncRNA splice forms. This procedure will be broken down into three steps, namely (i) guide RNA (gRNA) design and vector construction, (ii) virus generation and transduction, and (iii) colony screening for overexpression. For this representative experiment, a greater than 20-fold enhancement in IFNG-AS1 in Jurkat T cells was observed.

Traditional cDNA-based overexpression techniques have a limited applicability for the overexpression of long noncoding RNAs due to their multiple splice forms with potential functionality. This review reports a protocol using CRISPR technology to overexpress multiple splice variants of a long noncoding RNA.

Overexpressing 긴 Noncoding RNAs 유전자 활성화 CRISPR를 사용 하 여

Long noncoding RNA (lncRNA) biology is a new and exciting field of research, with the number of publications from this field growing exponentially since ...

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Sequencing in remote locations and resource-poor settings presents unique challenges. Nanopore sequencing can be successfully used under such conditions, and was deployed to West Africa during the recent Ebola virus epidemic, highlighting this possibility. In addition to its practical advantages (low cost, ease of equipment transport and use), this technology also provides fundamental advantages over second-generation sequencing approaches, particularly the very long read length, ability to directly sequence RNA, and real-time availability of data. Raw read accuracy is lower than with other sequencing platforms, which represents the main limitation of this technology; however, this can be partially mitigated by the high read depth generated. Here, we present a field-compatible protocol for sequencing of the mRNAs encoding for Niemann-Pick C1, which is the cellular receptor for ebolaviruses. This protocol encompasses extraction of RNA from animal blood samples, followed by RT-PCR for target enrichment, barcoding, library preparation, and the sequencing run itself, and can be easily adapted for use with other DNA or RNA targets.

Nanopore sequencing is a novel technology that allows cost-effective sequencing in remote locations and resource-poor settings. Here, we present a protocol for sequencing of mRNAs from whole blood that is compatible with such conditions.

나노 포어 시퀀싱을 사용 하 여 전 혈에서 mRNA의 시퀀싱

Sequencing in remote locations and resource-poor settings presents unique challenges. Nanopore sequencing can be successfully used under such conditions, ...

Single-cell RNA Sequencing and Analysis of Human Pancreatic Islets

Pancreatic islets comprise of endocrine cells with distinctive hormone expression patterns. The endocrine cells show functional differences in response to normal and pathological conditions. The goal of this protocol is to generate high-quality, large-scale transcriptome data of each endocrine cell type with the use of a droplet-based microfluidic single-cell RNA sequencing technology. Such data can be utilized to build the gene expression profile of each endocrine cell type in normal or specific conditions. The process requires careful handling, accurate measurement, and rigorous quality control. In this protocol, we describe detailed steps for human pancreatic islets dissociation, sequencing, and data analysis. The representative results of about 20,000 human single islet cells demonstrate the successful application of the protocol.

Here, we present a protocol to generate high-quality, large-scale transcriptome data of single cells from isolated human pancreatic islets using a droplet-based microfluidic single-cell RNA sequencing technology.

단세포 RNA 시퀀싱 및 인간 췌장 섬 분석

Pancreatic islets comprise of endocrine cells with distinctive hormone expression patterns. The endocrine cells show functional differences in response to ...

Identification of Footprints of RNA:Protein Complexes via RNA Immunoprecipitation in Tandem Followed by Sequencing (RIPiT-Seq)

RNA immunoprecipitation in tandem (RIPiT) is a method for enriching RNA footprints of a pair of proteins within an RNA:protein (RNP) complex. RIPiT employs two purification steps. First, immunoprecipitation of a tagged RNP subunit is followed by mild RNase digestion and subsequent non-denaturing affinity elution. A second immunoprecipitation of another RNP subunit allows for enrichment of a defined complex. Following a denaturing elution of RNAs and proteins, the RNA footprints are converted into high-throughput DNA sequencing libraries. Unlike the more popular ultraviolet (UV) crosslinking followed by immunoprecipitation (CLIP) approach to enrich RBP binding sites, RIPiT is UV-crosslinking independent. Hence RIPiT can be applied to numerous proteins present in the RNA interactome and beyond that are essential to RNA regulation but do not directly contact the RNA or UV-crosslink poorly to RNA. The two purification steps in RIPiT provide an additional advantage of identifying binding sites where a protein of interest acts in partnership with another cofactor. The double purification strategy also serves to enhance signal by limiting background. Here, we provide a step-wise procedure to perform RIPiT and to generate high-throughput sequencing libraries from isolated RNA footprints. We also outline RIPiT&#39;s advantages and applications and discuss some of its limitations.

Identification of Footprints of RNA:Protein Complexes via RNA Immunoprecipitation in Tandem Followed by Sequencing RIPiT-Seq

Here, we present a protocol to enrich endogenous RNA binding sites or &#34;footprints&#34;&#160;of RNA:protein (RNP) complexes from mammalian cells. This approach involves two immunoprecipitations of RNP subunits and is therefore dubbed RNA immunoprecipitation in tandem (RIPiT).

RNA의 발자국 의 식별:연속RNA 면역 침전을 통한 단백질 복합체 시퀀싱 (RIPiT-Seq)

RNA immunoprecipitation in tandem (RIPiT) is a method for enriching RNA footprints of a pair of proteins within an RNA:protein (RNP) complex. RIPiT ...

Improving Small RNA-seq: Less Bias and Better Detection of 2'-O-Methyl RNAs

The study of small RNAs (sRNAs) by next-generation sequencing (NGS) is challenged by bias issues during library preparation. Several types of sRNA such as plant microRNAs (miRNAs) carry a 2&#39;-O-methyl (2&#39;-OMe) modification at their 3&#39;&#160;terminal nucleotide. This modification adds another difficulty as it inhibits 3&#39;&#160;adapter ligation. We previously demonstrated that modified versions of the &#39;TruSeq (TS)&#39;&#160;protocol have less bias and an improved detection of 2&#39;-OMe RNAs. Here we describe in detail protocol &#39;TS5&#39;, which showed the best overall performance. TS5 can be followed either using homemade reagents or reagents from the TS kit, with equal performance.

Improving Small RNA-seq: Less Bias and Better Detection of 2&#039;-O-Methyl RNAs

We present a detailed small RNA library reparation protocol with less bias than standard methods and an increased sensitivity for 2&#39;-O-methyl RNAs. This protocol can be followed using homemade reagents to save cost or using kits for convenience.

작은 RNA-seq 개선: 2'-O-메틸 RNA의 더 적은 편견 및 더 나은 검출

The study of small RNAs (sRNAs) by next-generation sequencing (NGS) is challenged by bias issues during library preparation. Several types of sRNA such as ...