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Research: Global identification of mammalian host and nested gene pairs reveal tissue-specific transcriptional interplay
- Bertille Montibus,
- James A. Cain,
- Rocio T. Martinez-Nunez,
- and Rebecca J. Oakey
Genome Res. December 2024 34: 2163-2175; Published in Advance November 22, 2024, doi:10.1101/gr.279430.124
...a filter of a minimum of 1% of the cells of the data set which had to have robust expression for both the host and the nested gene, selecting 34 pairs. Finally, expression above the threshold for both the host and the nested gene allows the identification of cells which coexpress the pair. Expression above...
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Method: Accurate fusion transcript identification from long- and short-read isoform sequencing at bulk or single-cell resolution
- Qian Qin,
- Victoria Popic,
- Kirsty Wienand,
- Houlin Yu,
- Emily White,
- Akanksha Khorgade,
- Asa Shin,
- Christophe Georgescu,
- Catarina D. Campbell,
- Arthur Dondi,
- Niko Beerenwinkel,
- Francisca Vazquez,
- Aziz M. Al'Khafaji,
- and Brian J. Haas
Genome Res. April 2025 35: 967-986; Published in Advance March 14, 2025, doi:10.1101/gr.279200.124
...and gene expression regulatory elements of the 5′ gene, or encoding fusion proteins with altered molecular functions, all leading to alterations in the cellular circuitry that ultimately drive uncontrolled cellular proliferation.Identification of gene fusions has been an essential part of charting...
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Method: Scalable cell-specific coexpression networks for granular regulatory pattern discovery with NeighbourNet
- Yidi Deng,
- Jiadong Mao,
- Jarny Choi,
- and Kim-Anh Lê Cao
Genome Res. April 2026 36: 785-801; Published in Advance March 5, 2026, doi:10.1101/gr.281171.125
...on the identification of key meta-TFs and their regulons associated with MP differentiation, a process distinct from erythropoiesis. Each meta-TF represents a TF module (i.e., a soft cluster) defined by a set of TF weights. Although analyzing a single TF’s coexpression often provides only a partial view of its function...
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Method: Identifying gene function and module connections by the integration of multispecies expression compendia
- Hao Li,
- Daria Rukina,
- Fabrice P.A. David,
- Terytty Yang Li,
- Chang-Myung Oh,
- Arwen W. Gao,
- Elena Katsyuba,
- Maroun Bou Sleiman,
- Andrea Komljenovic,
- Qingyao Huang,
- Robert W. Williams,
- Marc Robinson-Rechavi,
- Kristina Schoonjans,
- Stephan Morgenthaler,
- and Johan Auwerx
Genome Res. December 2019 29: 2034-2045; Published in Advance November 21, 2019, doi:10.1101/gr.251983.119
...with the expression compendia are available as an open resource, which will facilitate the identification of connections linking genes, modules, phenotypes, and diseases.The identification of gene function and the integrated understanding of their roles in physiology are core aims of many biological and biomedical...
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Resource: Interspecies systems biology links bacterial metabolic pathways to nematode gene expression, chemotaxis behavior, and survival
- Marina Athanasouli,
- Tobias Loschko,
- and Christian Rödelsperger
Genome Res. October 2025 35: 2363-2374; Published in Advance August 5, 2025, doi:10.1101/gr.280848.125
...coexpression modules with differential responses to environmental microbiota. Third, we link the microbial and host transcriptome data by predicting a global map of more than 2800 metabolic interactions. These interactions represent statistical associations between variation in bacterial metabolic potential...
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Method: Incorporating valuable prior knowledge to improve deep learning prediction of genetic perturbation responses
- Xiuhao Fu,
- Chao Yang,
- Chunyan Cui,
- Aoyun Geng,
- Yidi Sun,
- Chao Zha,
- Feifei Cui,
- Leyi Wei,
- Quan Zou,
- Xin Gao,
- and Zilong Zhang
Genome Res. March 26, 2026 gr.281523.125; Published in Advance March 26, 2026, doi:10.1101/gr.281523.125
...perturbed genes. In parallel, 88 we incorporate a gene co-expression network to encode genes, allowing PRIM to 89 capture regulatory and expression-coupled relationships. Furthermore, by introducing 90 a cell encoding module based on control-cell expression profiles, PRIM learns 91 heterogeneous cellular...
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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
...analysis confirmed the enrichment of RT switching in novel splice junctions (FET P < 2.2 × 10−16) (Fig. 3D) and in NNC compared to NIC transcripts (7.24% versus 1.98%; FET P < 2.2 × 10−16). Described RT switching events affect minor isoforms of genes co-expressed with a major isoform that serves...
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Research: Dynamic metabolic and molecular changes during seasonal shrinking in Sorex araneus
- William R. Thomas,
- Cecilia Baldoni,
- Yuanyuan Zeng,
- David Carlson,
- Julie Holm-Jacobsen,
- Marion Muturi,
- Dominik von Elverfeldt,
- Tue B. Bennike,
- Dina K.N. Dechmann,
- John Nieland,
- Angelique P. Corthals,
- and Liliana M. Dávalos
Genome Res. January 2026 36: 61-70; Published in Advance November 4, 2025, doi:10.1101/gr.280639.125
...two size extremes, but large modules comprising genes of small effect could also play pivotal roles in regulating metabolic changes across all seasons. We characterized interactions in expression among genes and identified modules of coexpressed liver genes correlated with body size using a weighted...
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Research: Mapping multitissue regulatory variants reveals a liver-centric coexpression network associated with duck egg-laying performance
- Yang Xi,
- Jingjing Qi,
- Zhao Yang,
- Yutian Zeng,
- Huicong Zhang,
- Qiuyu Tao,
- Mengru Xu,
- Anqi Huang,
- Shenqiang Hu,
- Chunchun Han,
- Lili Bai,
- Jiwei Hu,
- Jiwen Wang,
- Liang Li,
- Lingzhao Fang,
- and Hehe Liu
Genome Res. October 2025 35: 2211-2225; Published in Advance September 10, 2025, doi:10.1101/gr.280345.124
..., we performed weighted gene coexpression network analysis (WGCNA) across four tissues (Supplemental Fig. S8A). The analysis revealed that LOC101800576 and LOC101790890 were assigned to the shell gland ME3 module, GLP2R to the spleen ME7 module, and LOC119713219 to the ovary ME6 module (Supplemental...
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Method: Cancer driver topologically associated domains identify oncogenic and tumor-suppressive lncRNAs
- Ziyan Rao,
- Min Zhang,
- Shaodong Huang,
- Chenyang Wu,
- Yuheng Zhou,
- Weijie Zhang,
- Xia Lin,
- and Dongyu Zhao
Genome Res. August 2025 35: 1842-1858; Published in Advance May 27, 2025, doi:10.1101/gr.280235.124
...enable the effective identification of cancer driver lncRNAs, which are defined as those directly modulating the expression of cancer driver PCGs. They can be divided into oncogenic lncRNAs and tumor-suppressive lncRNAs according to their association with cancer driver PCGs.In this study, we first...

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