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Transcriptome variation in human tissues revealed by long-read sequencing

Author

Listed:
  • Dafni A. Glinos

    (New York Genome Center
    Columbia University)

  • Garrett Garborcauskas

    (The Broad Institute of MIT and Harvard)

  • Paul Hoffman

    (New York Genome Center)

  • Nava Ehsan

    (The Scripps Research Institute)

  • Lihua Jiang

    (Stanford University)

  • Alper Gokden

    (New York Genome Center)

  • Xiaoguang Dai

    (Oxford Nanopore Technology)

  • François Aguet

    (Broad Institute of MIT and Harvard)

  • Kathleen L. Brown

    (New York Genome Center
    Columbia University)

  • Kiran Garimella

    (Broad Institute of MIT and Harvard)

  • Tera Bowers

    (Broad Institute of MIT and Harvard)

  • Maura Costello

    (Broad Institute of MIT and Harvard)

  • Kristin Ardlie

    (Broad Institute of MIT and Harvard)

  • Ruiqi Jian

    (Stanford University)

  • Nathan R. Tucker

    (Masonic Medical Research Institute
    The Broad Institute of Harvard and MIT)

  • Patrick T. Ellinor

    (The Broad Institute of Harvard and MIT)

  • Eoghan D. Harrington

    (Oxford Nanopore Technology)

  • Hua Tang

    (Stanford University)

  • Michael Snyder

    (Stanford University)

  • Sissel Juul

    (Oxford Nanopore Technology)

  • Pejman Mohammadi

    (The Scripps Research Institute
    Scripps Research Translational Institute)

  • Daniel G. MacArthur

    (The Broad Institute of MIT and Harvard
    Garvan Institute of Medical Research, and UNSW Sydney
    Murdoch Children’s Research Institute)

  • Tuuli Lappalainen

    (New York Genome Center
    Columbia University
    KTH Royal Institute of Technology)

  • Beryl B. Cummings

    (The Broad Institute of MIT and Harvard)

Abstract

Regulation of transcript structure generates transcript diversity and plays an important role in human disease1–7. The advent of long-read sequencing technologies offers the opportunity to study the role of genetic variation in transcript structure8–16. In this Article, we present a large human long-read RNA-seq dataset using the Oxford Nanopore Technologies platform from 88 samples from Genotype-Tissue Expression (GTEx) tissues and cell lines, complementing the GTEx resource. We identified just over 70,000 novel transcripts for annotated genes, and validated the protein expression of 10% of novel transcripts. We developed a new computational package, LORALS, to analyse the genetic effects of rare and common variants on the transcriptome by allele-specific analysis of long reads. We characterized allele-specific expression and transcript structure events, providing new insights into the specific transcript alterations caused by common and rare genetic variants and highlighting the resolution gained from long-read data. We were able to perturb the transcript structure upon knockdown of PTBP1, an RNA binding protein that mediates splicing, thereby finding genetic regulatory effects that are modified by the cellular environment. Finally, we used this dataset to enhance variant interpretation and study rare variants leading to aberrant splicing patterns.

Suggested Citation

  • Dafni A. Glinos & Garrett Garborcauskas & Paul Hoffman & Nava Ehsan & Lihua Jiang & Alper Gokden & Xiaoguang Dai & François Aguet & Kathleen L. Brown & Kiran Garimella & Tera Bowers & Maura Costello &, 2022. "Transcriptome variation in human tissues revealed by long-read sequencing," Nature, Nature, vol. 608(7922), pages 353-359, August.
  • Handle: RePEc:nat:nature:v:608:y:2022:i:7922:d:10.1038_s41586-022-05035-y
    DOI: 10.1038/s41586-022-05035-y
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    Cited by:

    1. Kensuke Yamaguchi & Kazuyoshi Ishigaki & Akari Suzuki & Yumi Tsuchida & Haruka Tsuchiya & Shuji Sumitomo & Yasuo Nagafuchi & Fuyuki Miya & Tatsuhiko Tsunoda & Hirofumi Shoda & Keishi Fujio & Kazuhiko , 2022. "Splicing QTL analysis focusing on coding sequences reveals mechanisms for disease susceptibility loci," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    2. Xian Sun & Dongshuo Yin & Fei Qin & Hongfeng Yu & Wanxuan Lu & Fanglong Yao & Qibin He & Xingliang Huang & Zhiyuan Yan & Peijin Wang & Chubo Deng & Nayu Liu & Yiran Yang & Wei Liang & Ruiping Wang & C, 2023. "Revealing influencing factors on global waste distribution via deep-learning based dumpsite detection from satellite imagery," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    3. Arthur Dondi & Ulrike Lischetti & Francis Jacob & Franziska Singer & Nico Borgsmüller & Ricardo Coelho & Viola Heinzelmann-Schwarz & Christian Beisel & Niko Beerenwinkel, 2023. "Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer," Nature Communications, Nature, vol. 14(1), pages 1-19, December.

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