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Research: Reconstructed cell fate–regulatory programs in stem cells reveal hierarchies and key factors of neurogenesis
- Marco-Antonio Mendoza-Parra,
- Valeriya Malysheva,
- Mohamed Ashick Mohamed Saleem,
- Michele Lieb,
- Aurelie Godel,
- and Hinrich Gronemeyer
Genome Res. November 2016 26: 1505-1519; Published in Advance September 20, 2016, doi:10.1101/gr.208926.116
...dissected the GRNs involved in the RA-induced neuronal or endodermal cell fate specification by integrating dynamic RXRA binding, chromatin accessibility, epigenetic promoter epigenetic status, and the transcriptional activity inferred from RNA polymerase II mapping and transcription profiling. Our data...
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Perspective: Applications of single-cell genomics and computational strategies to study common disease and population-level variation
- Benjamin J. Auerbach,
- Jian Hu,
- Muredach P. Reilly,
- and Mingyao Li
Genome Res. October 2021 31: 1728-1741; doi:10.1101/gr.275430.121
...-cell study in T2D at that time. Using the Smart-seq2 protocol, they generated transcriptional profiles of individual pancreatic endocrine and exocrine cells of healthy and T2D donors and simultaneously defined the transcriptional signatures of both abundant and rare cell types in the pancreas, including...
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Resource: Dynamic transcriptional and chromatin accessibility landscape of medaka embryogenesis
- Yingshu Li,
- Yongjie Liu,
- Hang Yang,
- Ting Zhang,
- Kiyoshi Naruse,
- and Qiang Tu
Genome Res. June 2020 30: 924-937; Published in Advance June 26, 2020, doi:10.1101/gr.258871.119
...-quality sequence and a variety of genetic tools are available for this model organism. However, existing annotation is still rudimentary, as it was mainly based on computational prediction and short-read RNA-seq data. Here we report a dynamic transcriptome landscape of medaka embryogenesis profiled by long...
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LETTER: In Vivo Regulation of Human Skeletal Muscle Gene Expression by Thyroid Hormone
- Karine Clément,
- Nathalie Viguerie,
- Maximilian Diehn,
- Ash Alizadeh,
- Pierre Barbe,
- Claire Thalamas,
- John D. Storey,
- Patrick O. Brown,
- Greg S. Barsh,
- and Dominique Langin
Genome Res. February 1, 2002 12: 281-291; doi:10.1101/gr.207702
...-PCR confirmed the array data (Table 2 ). View this table: In this window In a new window Table 2. Fold Change of Human Skeletal Muscle mRNA Levels during Triiodothyronine Treatment Reconstruction of the human skeletal muscle transcriptional profile has revealed a set of ∼400 genes highly expressed or specific...
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Resource: Integrated single-cell multiome analysis reveals muscle fiber-type gene regulatory circuitry modulated by endurance exercise
- Aliza B. Rubenstein,
- Gregory R. Smith,
- Zidong Zhang,
- Xi Chen,
- Toby L. Chambers,
- Frederique Ruf-Zamojski,
- Natalia Mendelev,
- Wan Sze Cheng,
- Michel Zamojski,
- Mary Anne S. Amper,
- Venugopalan D. Nair,
- Andrew R. Marderstein,
- Stephen B. Montgomery,
- Olga G. Troyanskaya,
- Elena Zaslavsky,
- Todd Trappe,
- Scott Trappe,
- and Stuart C. Sealfon
Genome Res. July 2025 35: 1664-1677; Published in Advance May 20, 2025, doi:10.1101/gr.280051.124
...)-expressing fibro-adipogenic progenitor cells. Single-cell regulatory circuit triad reconstruction (transcription factor, chromatin interaction site, regulated gene) also identifies largely distinct gene regulatory circuits modulated by exercise in the three muscle fiber types and LUM-expressing fibro...
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Research: Epigenetic maintenance of topological domains in the highly rearranged gibbon genome
- Nathan H. Lazar,
- Kimberly A. Nevonen,
- Brendan O'Connell,
- Christine McCann,
- Rachel J. O'Neill,
- Richard E. Green,
- Thomas J. Meyer,
- Mariam Okhovat,
- and Lucia Carbone
Genome Res. July 2018 28: 983-997; Published in Advance June 18, 2018, doi:10.1101/gr.233874.117
...Epigenetic maintenance of topological domains in the highly rearranged gibbon Nathan H. Lazar1, Kimberly A. Nevonen2, Brendan O'Connell3, Christine McCann4,5, Rachel J. O'Neill4,5, Richard E. Green3, Thomas J. Meyer1, Mariam Okhovat2 and Lucia Carbone1,2,6,7 1Bioinformatics and Computational...
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Method: Co-expression networks reveal the tissue-specific regulation of transcription and splicing
- Ashis Saha,
- Yungil Kim,
- Ariel D.H. Gewirtz,
- Brian Jo,
- Chuan Gao,
- Ian C. McDowell,
- The GTEx Consortium,
- Barbara E. Engelhardt,
- and Alexis Battle
Genome Res. November 2017 27: 1843-1858; Published in Advance October 11, 2017, doi:10.1101/gr.216721.116
..., we reconstruct co-expression networks from the Genotype Tissue Expression (GTEx) v6 RNA-seq data (The GTEx Consortium 2015, 2017), including 449 human donors with genotype information and 7310 RNA-seq samples across 50 tissues. We apply computational methods designed to reveal novel relationships...
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Perspective: Half dozen of one, six billion of the other: What can small- and large-scale molecular systems biology learn from one another?
- Ian A. Mellis and
- Arjun Raj
Genome Res. October 2015 25: 1466-1472; doi:10.1101/gr.190579.115
...by a bunchof irrelevant noise. We arenot so sure, however, that this view is completely supported by the evidence. We offer another recent example, CellNet, a computational framework developed for using -wide expression profiles analysis to help understand and manipulate cell types (Cahan et al. 2014; Morris...
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Method: Single-cell-level spatial gene expression in the embryonic neural differentiation niche
- Yi Huang,
- Xiaoming Yu,
- Na Sun,
- Nan Qiao,
- Yaqiang Cao,
- Jerome D. Boyd-Kirkup,
- Qin Shen,
- and Jing-Dong J. Han
Genome Res. April 2015 25: 570-581; Published in Advance January 9, 2015, doi:10.1101/gr.181966.114
...morphogenesis, BMP signaling pathway, transcription factor complex, zinc ion binding, embryonic skeletal system morphogenesis GSEA was used for the enrichment test, and NOM P-value < 0.01 was used to define significant enrichment. Single-cell-level gene expression of neurogenesis Genome Research 577 www...
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Methods: Targeted discovery of novel human exons by comparative genomics
- Adam Siepel,
- Mark Diekhans,
- Broňa Brejová,
- Laura Langton,
- Michael Stevens,
- Charles L.G. Comstock,
- Colleen Davis,
- Brent Ewing,
- Shelly Oommen,
- Christopher Lau,
- Hung-Chun Yu,
- Jianfeng Li,
- Bruce A. Roe,
- Phil Green,
- Daniela S. Gerhard,
- Gary Temple,
- David Haussler,
- and Michael R. Brent
Genome Res. December 2007 17: 1763-1773; Published in Advance November 7, 2007, doi:10.1101/gr.7128207
.... In addition, misses may arise for reasons other than false-positive predictions, such as failures of reverse transcription, PCR amplification, or sequencing, or incomplete sampling of tissues in the mRNA pool. View this table: In this window In a new window Table 1. Computational gene finders used...

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