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Review: A systematic guide for identifying transcription factors that directly regulate the expression of a gene of interest
- Andrew D. Bates,
- Dawid Grzela,
- Maciej Studzian,
- Louise Brennan,
- Moli Williams,
- Conor Fawcett,
- Beth Hammond,
- Manreen Grewal,
- Marcin Ratajewski,
- Lukasz Pulaski,
- and Urszula L. McClurg
Genome Res. March 2026 36: 433-459; Published in Advance February 17, 2026, doi:10.1101/gr.281154.125
...beads. To focus on individual candidate genes predicted to be bound by the protein of interest, precipitated DNA can be analyzed using qPCR with primers designed specifically against the regulatory sequences of the GOIs. Alternatively, in ChIP-seq following precipitation, cross-links are reversed...
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Research: A gene regulatory element modulates myosin expression and controls cardiomyocyte response to stress
- Taylor Anglen,
- Irene M. Kaplow,
- Baekgyu Choi,
- Enya Dewars,
- Robin M. Perelli,
- Kevin T. Hagy,
- Duc Tran,
- Megan E. Ramaker,
- Svati H. Shah,
- Inkyung Jung,
- Andrew P. Landstrom,
- Ravi Karra,
- Yarui Diao,
- and Charles A. Gersbach
Genome Res. November 2025 35: 2418-2432; Published in Advance October 22, 2025, doi:10.1101/gr.280825.125
..., USA ↵10 Present address: Department of Biological Sciences and Ray and Stephanie Lane Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA Corresponding author: charles.gersbach@duke.eduAbstractA hallmark of heart disease is gene dysregulation and reactivation...
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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
...within different cell types (e.g., increases in gene expression in one cell type, whereas chromatin accessibility increases in a different cell type). The use of integrated same-cell multiome assays and new bioinformatic techniques allows the more accurate inference of the entire gene regulatory circuit...
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Research: Analysis of canine gene constraint identifies new variants for orofacial clefts and stature
- Reuben M. Buckley,
- Nüket Bilgen,
- Alexander C. Harris,
- Peter Savolainen,
- Cafer Tepeli,
- Metin Erdoğan,
- Aitor Serres Armero,
- Dayna L. Dreger,
- Frank G. van Steenbeek,
- Marjo K. Hytönen,
- Heidi G. Parker,
- Jessica Hale,
- Hannes Lohi,
- Bengi Çınar Kul,
- Adam R. Boyko,
- and Elaine A. Ostrander
Genome Res. May 2025 35: 1080-1093; Published in Advance March 24, 2025, doi:10.1101/gr.280092.124
...metrics (Gough et al. 2018; Plassais et al. 2019; Dutrow et al. 2022; Morrill et al. 2022).In humans, candidate trait and disease variants are generally identified using a combination of strategies, including multiple species alignment, protein structure predictions, gene mutation tolerance, and machine...
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Method: Reference-informed prediction of alternative splicing and splicing-altering mutations from sequences
- Chencheng Xu,
- Suying Bao,
- Ye Wang,
- Wenxing Li,
- Hao Chen,
- Yufeng Shen,
- Tao Jiang,
- and Chaolin Zhang
Genome Res. July 2024 34: 1052-1065; Published in Advance July 26, 2024, doi:10.1101/gr.279044.124
...of modulating gene expression using therapeutically compatible approaches (El Marabti and Abdel-Wahab 2021).A longstanding question in the splicing field is the possibility to derive a “splicing code,” which can accurately predict splice sites and their quantitative usage from pre-mRNA sequences, including...
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Method: A best-match approach for gene set analyses in embedding spaces
- Lechuan Li,
- Ruth Dannenfelser,
- Charlie Cruz,
- and Vicky Yao
Genome Res. September 2024 34: 1421-1433; Published in Advance September 4, 2024, doi:10.1101/gr.279141.124
...provide, there is an implicit assumption that a quality embedding amplifies the important signal in the data while reducing noise. In the biomedical realm, gene embeddings are gaining traction as a valuable approach for predicting function (Kulmanov et al. 2018; Kulmanov and Hoehndorf 2020; Gligorijević...
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Research: Motif conservation, stability, and host gene expression are the main drivers of snoRNA expression across vertebrates
- Étienne Fafard-Couture,
- Pierre-Étienne Jacques,
- and Michelle S. Scott
Genome Res. April 2023 33: 525-540; Published in Advance April 18, 2023, doi:10.1101/gr.277483.122
...are accurately predicted as expressed or not expressed by our classifiers (Supplemental Fig. S13). Out of the 79 host genes encoding multiple snoRNAs, 17 are in the situation in which their embedded snoRNAs vary in expression status, with expressed snoRNAs being always either equal in number or in majority...
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Method: Predicting transfer RNA gene activity from sequence and genome context
- Bryan P. Thornlow,
- Joel Armstrong,
- Andrew D. Holmes,
- Jonathan M. Howard,
- Russell B. Corbett-Detig,
- and Todd M. Lowe
Genome Res. January 2020 30: 85-94; Published in Advance December 19, 2019, doi:10.1101/gr.256164.119
...scores output by the classifier are shown on the x-axis, where tRNA genes further left are predicted inactive with greater probability, and tRNA genes further right are predicted active with greater probability: (A) mouse; (B) macaque; (C) rat; (D) dog. The y-axis shows Pol III ChIP-seq read counts from...
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Method: Integrating transcriptomic and proteomic data for accurate assembly and annotation of genomes
- T.S. Keshava Prasad,
- Ajeet Kumar Mohanty,
- Manish Kumar,
- Sreelakshmi K. Sreenivasamurthy,
- Gourav Dey,
- Raja Sekhar Nirujogi,
- Sneha M. Pinto,
- Anil K. Madugundu,
- Arun H. Patil,
- Jayshree Advani,
- Srikanth S. Manda,
- Manoj Kumar Gupta,
- Sutopa B. Dwivedi,
- Dhanashree S. Kelkar,
- Brantley Hall,
- Xiaofang Jiang,
- Ashley Peery,
- Pavithra Rajagopalan,
- Soujanya D. Yelamanchi,
- Hitendra S. Solanki,
- Remya Raja,
- Gajanan J. Sathe,
- Sandip Chavan,
- Renu Verma,
- Krishna M. Patel,
- Ankit P. Jain,
- Nazia Syed,
- Keshava K. Datta,
- Aafaque Ahmed Khan,
- Manjunath Dammalli,
- Savita Jayaram,
- Aneesha Radhakrishnan,
- Christopher J. Mitchell,
- Chan-Hyun Na,
- Nirbhay Kumar,
- Photini Sinnis,
- Igor V. Sharakhov,
- Charles Wang,
- Harsha Gowda,
- Zhijian Tu,
- Ashwani Kumar,
- and Akhilesh Pandey
Genome Res. January 2017 27: 133-144; Published in Advance November 15, 2016, doi:10.1101/gr.201368.115
...the same data sets were analyzed by different methodologies (Earl et al. 2011; Salzberg et al. 2012) demonstrating a critical need for developing protocols for accurate assembly of genomic sequences. Genome annotation, especially identification of protein-coding genes, is of high priority once...
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Method: SQANTI: extensive characterization of long-read transcript sequences for quality control in full-length transcriptome identification and quantification
- Manuel Tardaguila,
- Lorena de la Fuente,
- Cristina Marti,
- Cécile Pereira,
- Francisco Jose Pardo-Palacios,
- Hector del Risco,
- Marc Ferrell,
- Maravillas Mellado,
- Marissa Macchietto,
- Kenneth Verheggen,
- Mariola Edelmann,
- Iakes Ezkurdia,
- Jesus Vazquez,
- Michael Tress,
- Ali Mortazavi,
- Lennart Martens,
- Susana Rodriguez-Navarro,
- Victoria Moreno-Manzano,
- and Ana Conesa
Genome Res. March 2018 28: 396-411; Published in Advance February 9, 2018, doi:10.1101/gr.222976.117
...a window of nucleotides downstream from the genetic coordinates corresponding to transcripts’ 3′ ends.Finally, SQANTI implements the GeneMarkS-T (GMST) algorithm (Tang et al. 2015) to predict ORFs from transcript sequences (Supplemental Methods and Supplemental Fig. 1C–E).Diagnostic graphs...
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