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研究分野生物学的科学遺伝学エピジェネティクス (ゲノムメチレーションとエピジェノミクスを含む)
候補 cis 規制要素の拡張登録

候補 cis 規制要素の拡張登録

Jill E Moore ¹, Henry E Pratt ², Kaili Fan ², Nishigandha Phalke ², Jonathan Fisher ², Shaimae I Elhajjajy ², Gregory Andrews ², Mingshi Gao ², Nicole Shedd ², Yu Fu ², Matthew C Lacadie ², Jair Meza ², Mansi Khandpekar ², Mohit Ganna ², Eva Choudhury ², Ross Swofford ², Huong Phan ², Christian C Ramirez ², Maxwell Campbell ², Mary Likhite ², Nina P Farrell ³, Annika K Weimer ⁴, Anusri Pampari ⁵, Vivekanandan Ramalingam ⁴, Fairlie Reese ⁶, Beatrice Borsari ^7,8, Xuezhu Yu ^7,8, Eve Wattenberg ^7,8, Marina Ruiz-Romero ⁹, Milad Razavi-Mohseni ¹⁰, Jinrui Xu ¹¹, Timur Galeev ^7,8, Andres Colubri ^2,3, Michael A Beer ¹⁰, Roderic Guigó ^9,12, Mark B Gerstein ^{7,8,13,14,15,16}, Jesse M Engreitz ^4,17,18,19, Mats Ljungman ²⁰, Timothy E Reddy ^21,22,23, Michael P Snyder ⁴, Charles B Epstein ³, Elizabeth Gaskell ³, Bradley E Bernstein ³, Diane E Dickel ²⁴, Axel Visel ^24,25,26, Len A Pennacchio ²⁴, Ali Mortazavi ^6,27, Anshul Kundaje ^4,5, Zhiping Weng ²⁸

Jill E Moore ¹, Henry E Pratt ², Kaili Fan ²

¹Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, USA. Jill.Moore@umassmed.edu.
²Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, USA.
³Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁴Department of Genetics, Stanford University, Stanford, CA, USA.
⁵Department of Computer Science, Stanford University, Stanford, CA, USA.
⁶Developmental and Cell Biology, University of California Irvine, Irvine, CA, USA.
⁷Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA.
⁸Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
⁹Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.
¹⁰Department of Biomedical Engineering and McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA.
¹¹Department of Biology and Center for Applied Data Science and Analytics, Howard University, Washington, DC, USA.
¹²Universitat Pompeu Fabra (UPF), Barcelona, Spain.
¹³Program in Computational Biology and Biomedical Informatics, Yale University, New Haven, CT, USA.
¹⁴Department of Computer Science, Yale University, New Haven, CT, USA.
¹⁵Department of Statistics and Data Science, Yale University, New Haven, CT, USA.
¹⁶Department of Biomedical Informatics and Data Science, Yale University, New Haven, CT, USA.
¹⁷Basic Sciences and Engineering Initiative, Betty Irene Moore Children's Heart Center, Lucile Packard Children's Hospital, Stanford, CA, USA.
¹⁸Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute, Cambridge, MA, USA.
¹⁹Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA.
²⁰Departments of Radiation Oncology and Environmental Health Sciences, University of Michigan, Ann Arbor, MI, USA.
²¹Duke Center for Statistical Genetics and Genomics, Duke University, Durham, NC, USA.
²²Division of Integrative Genomics, Department of Biostatistics Bioinformatics, Duke University Medical School, Durham, NC, USA.
²³Center for Genomic and Computational Biology, Duke University Medical School, Durham, NC, USA.
²⁴Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
²⁵US Department of Energy Joint Genome Institute, Berkeley, CA, USA.
²⁶School of Natural Sciences, University of California, Merced, Merced, CA, USA.
²⁷Center for Complex Biological Systems, University of California Irvine, Irvine, CA, USA.
²⁸Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, USA. zhiping.weng@umassmed.edu.

⁰Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, USA. Jill.Moore@umassmed.edu.

Nature +

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2026年1月7日

関連する実験動画

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Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

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HOX Loci Focused CRISPR/sgRNA Library Screening Identifying Critical CTCF Boundaries

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Quantitative Comparison of cis-Regulatory Element (CRE) Activities in Transgenic Drosophila melanogaster

Published on: December 19, 2011

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PubMedで要約を見る

まとめ

この要約は機械生成です。

ENCODEコンソーシアムは,候補のシス調節要素 (cCREs) のレジストリを2,300万以上のヒトと90万個のマウス要素に拡張しました. この包括的なリソースは遺伝子調節を理解し,特徴や病気に関連した遺伝子を特定するのに役立ちます.

科学分野

ゲノミクス
規制生物学
バイオ情報学

背景

哺乳類のゲノムには遺伝子発現を制御する何百万もの規制要素があります
ENCODEコンソーシアムは以前,ヒトの0.9百万とマウスの30万の候補シス調節要素 (cCREs) をカタログ化しました.

研究の目的

新しいデータセットと計算方法を使用して,cCREsのENCODEレジストリを拡張する.
多様な細胞と組織の遺伝子調節を理解するための包括的なリソースを提供する.

主な方法

新しいENCODEデータセットと強化された計算手法を利用した.
STARR-seq,MPRA,CRISPR,およびトランスジェニックマウスモデルのようなアッセイからの統合機能的特徴化データ.
ヒトのcCREは237万個,マウスのcCREは967000個に拡大した.

主要な成果

拡張されたレジストリには何百もの細胞と組織が含まれていて遺伝子調節の理解が深まっています
人間のcCREsの90%以上は機能的にプロファイリングされ,複雑な調節作用が明らかになった.
何千もの新型サイレンスcCREsが特定され,そのうちのいくつかはダブルエンサナー/サイレンス機能を備えたものであった.
KLF1は,赤血球特性の新しい因果遺伝子として特定されました.

結論

拡張されたENCODE cCREレジストリーは,規制ゲノミクス研究のための貴重なリソースです.
他のENCODEデータとの統合は,遺伝的多様性を解釈し,特質に関連した遺伝子を特定するのに役立ちます.
このリソースは,健康と病気における規制ゲノムの役割の研究を進めています.

関連する実験動画

自動的に一致したビデオです Contact us もしそれらが関連していない場合

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Published on: May 31, 2011

<em>HOX</em> Loci Focused CRISPR/sgRNA Library Screening Identifying Critical CTCF Boundaries

HOX Loci Focused CRISPR/sgRNA Library Screening Identifying Critical CTCF Boundaries

Published on: March 31, 2019

Quantitative Comparison of <em>cis</em>-Regulatory Element (CRE) Activities in Transgenic <em>Drosophila melanogaster</em>

Quantitative Comparison of cis-Regulatory Element (CRE) Activities in Transgenic Drosophila melanogaster

Published on: December 19, 2011

See all related videos

関連する概念動画

Cis-regulatory Sequences

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...

Cis-regulatory Sequences

Cis-regulatory Sequences

Cooperative Binding of Transcription Regulators

Cooperative Binding of Transcription Regulators

Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome. Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form...

Cooperative Binding of Transcription Regulators

Cooperative Binding of Transcription Regulators

Master Transcription Regulators

Master Transcription Regulators

Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...

Master Transcription Regulators

Master Transcription Regulators

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