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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
..., hinging on the precise binding of transcription factors (TFs) and cofactors to gene regulatory elements such as promoters and enhancers. Although it is relatively routine to profile -wide DNA binding landscapes of proteins, identifying the specific proteins that bind to, and regulate the transcription of...
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Method: Gene duplication is associated with gene diversification and potential neofunctionalization in lung cancer evolution
- Paul Ashford,
- Alexander M. Frankell,
- Zofia Piszka,
- Camilla S.M. Pang,
- Mahnaz Abbasian,
- Maise Al Bakir,
- Mariam Jamal-Hanjani,
- Nicholas McGranahan,
- Charles Swanton,
- and Christine A. Orengo
Genome Res. March 2026 36: 561-577; Published in Advance February 19, 2026, doi:10.1101/gr.278663.123
...functional diversification during evolution. In this study, we seek to identify the diversification and potential gene neofunctionalization of lung tumors in the TRACERx cohort. We develop a novel computational protocol to identify preduplication and postduplication mutations predicted to affect protein...
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Resource: Cell type–specific gene regulatory atlas prioritizes drug targets and repurposable medicines in Alzheimer's disease
- Yunxiao Ren,
- Ming Hu,
- Yang E. Li,
- Andrew A. Pieper,
- Jeffrey Cummings,
- and Feixiong Cheng
Genome Res. March 2026 36: 645-659; Published in Advance January 21, 2026, doi:10.1101/gr.280436.125
...–specific cis-regulatory DNA elements (CREs), we pinpoint 141 ADNC-associated genes. Using gene set enrichment analysis (GSEA) and network proximity analysis, we further identify nine candidate repurposable drugs that were associated with these ADNC-related genes. In summary, this cell type–specific multiomic...
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Method: Analysis of coding gene expression from small RNA sequencing
- Aygun Azadova,
- Anthonia Ekperuoh,
- Greg N. Brooke,
- and Antonio Marco
Genome Res. March 2026 36: 611-618; Published in Advance February 10, 2026, doi:10.1101/gr.281364.125
...on the estimated expression values from small RNA libraries, the size effect is negligible compared with the actual expression levels from total RNA libraries. Transcript half-life is therefore unlikely to impact/bias our analysis pipeline.The association between the differentially expressed genes identified using...
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Method: A scalable computational framework for predicting gene expression from candidate cis-regulatory elements
- Qinhu Zhang,
- Siguo Wang,
- Zhipeng Li,
- Wenzheng Bao,
- Wenjian Liu,
- and De-Shuang Huang
Genome Res. February 2026 36: 361-374; Published in Advance January 16, 2026, doi:10.1101/gr.281219.125
...neural networks with transformers. Compared with current state-of-the-art models, ScPGE exhibits superior performance in predicting gene expression and yields higher accuracy in identifying active enhancer–gene interactions through attention mechanisms. By comprehensively analyzing ScPGE's predictions...
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Resource: Single-nucleus multiomic profiling of the aging mouse substantia nigra reveals conserved gene alterations linked to Parkinson's disease
- Kangli Wang,
- Weikun Xia,
- Yingli Gu,
- Songpeng Zu,
- Qian Yang,
- Maria Luisa Amaral,
- Yaozhi Wang,
- Allen Wang,
- Xiang-Dong Fu,
- William C. Mobley,
- and Bing Ren
Genome Res. March 4, 2026 gr.281113.125; Published in Advance March 4, 2026, doi:10.1101/gr.281113.125
...samples highlighted 69 the utility of such analyses, identifying extensive changes not only in gene expression but also 70 4 in the connections between genes and chromatin regions in glia populations during aging and 71 PD(Adams et al. 2024). However, human samples often suffer from the inherent genetic...
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Method: Recovering gene regulatory networks in single-cell multi-omics data with PRISM-GRN
- Wenhao Zhang,
- Lan Cao,
- Xiaoxuan Gu,
- Yongyu Long,
- and Ying Wang
Genome Res. January 2026 36: 142-158; Published in Advance October 9, 2025, doi:10.1101/gr.280757.125
...data (Pratapa et al. 2020). Initial methods primarily rely on correlation or mutual information to infer regulatory interactions. For instance, weighted gene coexpression network analysis (WGCNA) (Langfelder and Horvath 2008) clusters coexpressed genes into modules to construct gene associations...
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Method: Kinetic measurement of gene-specific RNA polymerase II transcription elongation rates
- Haiyue Liu and
- Lea H. Gregersen
Genome Res. November 2025 35: 2550-2562; Published in Advance October 22, 2025, doi:10.1101/gr.280852.125
...RNP) complex involved in splicing and suppression of cryptic intronic polyadenylation similarly stimulates elongation and facilitates transcription of long genes (Mimoso and Adelman 2023). Furthermore, RNAPII elongation rates are modulated in response to certain stresses and stimuli such as heat shock and UV...
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Method: Chromosome engineering to correct a complex rearrangement on Chromosome 8 reveals the effects of 8p syndrome on gene expression and neural differentiation
- Sophia N. Lee,
- Erin C. Banda,
- Lu Qiao,
- Sarah L. Thompson,
- Karan Singh,
- Ryan A. Hagenson,
- Teresa Davoli,
- Stefan F. Pinter,
- and Jason M. Sheltzer
Genome Res. March 2026 36: 547-560; Published in Advance January 12, 2026, doi:10.1101/gr.280425.125
....05, (**) P ≤ 0.01, (***) P ≤ 0.001. (C) Representative genes that were identified as differentially expressed between the proband and revertant iPS lines. A complete list of differentially expressed genes is included in Supplemental Table S1. (D) RT-qPCR validation of differentially expressed genes between...
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Method: Robust and efficient annotation of cell states through gene signature scoring
- Laure Ciernik,
- Agnieszka Kraft,
- Florian Barkmann,
- Josephine Yates,
- and Valentina Boeva
Genome Res. March 2026 36: 630-644; Published in Advance February 18, 2026, doi:10.1101/gr.280926.125
...implementations. Discrepancies in Seurat scores between R (“AddModuleScore” of Seurat) and Python are attributed to randomization in the scoring method. (C) Control gene selection bias of the scoring methods for the top 8% of highly expressed genes in B memory kappa cells within the PBMC data set. The x...
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