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Method: Autoencoders for genomic variation analysis
- Margarita Geleta,
- Daniel Mas Montserrat,
- Xavier Giro-i-Nieto,
- and Alexander G. Ioannidis
Genome Res. February 2026 36: 348-360; Published in Advance January 20, 2026, doi:10.1101/gr.280086.124
...an overly large window size, which might lose fine-grained structure) and encoding efficiency (not using an excessively small window size, which would require a large bottleneck to capture all local information). In our analysis, w = 2500 results in a good compromise between capturing local genomic...
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Method: EnDeep4mC predicts DNA N⁴-methylcytosine sites using a dual-adaptive feature encoding framework in deep ensembles
- Shuyu Zhang,
- Quan Zou,
- Mengting Niu,
- Zhibin Lv,
- Antony Stalin,
- and Ximei Luo
Genome Res. March 2026 36: 589-599; Published in Advance February 17, 2026, doi:10.1101/gr.280977.125
...networks (CNN), for 4mC identification. Based on this, Liu et al. (2021a) proposed DeepTorrent by combining multiple feature encoding schemes with CNN and Bi-LSTM algorithms. Xu et al. (2021) proposed Deep4mC to further improve the model performance by building a stacked model based on the prediction...
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Method: Genotyping of selected germline adaptive immune system loci using short-read sequencing data
- Michael K.B. Ford,
- Ananth Hari,
- Meredith Yeager,
- Lisa Mirabello,
- Stephen Chanock,
- Ibrahim Numanagić,
- COVNET Consortium,
- and S. Cenk Sahinalp
Genome Res. September 2025 35: 2076-2086; Published in Advance August 5, 2025, doi:10.1101/gr.280314.124
...Mendelian concordance analysis in 590 trios from the 1000 Genomes Project, benchmarking 40 samples against HPRC assembly-derived genotypes, and assessing robustness through sequencing depth analysis and parameter sensitivity tests. We introduce allele call confidence metrics to help quantify reliability. We...
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Method: spRefine denoises and imputes spatial transcriptomic data with a reference-free framework powered by genomic language model
- Tianyu Liu,
- Tinglin Huang,
- Wengong Jin,
- Tinyi Chu,
- Rex Ying,
- and Hongyu Zhao
Genome Res. February 3, 2026 ; Published in Advance February 3, 2026, doi:10.1101/gr.281001.125
.... PLMs are foundationmodels trainedwith large-scale amino-acid sequences to model protein data as a language (Ofer et al. 2021; Zhang et al. 2024), and the success of applying PLMs to this task suggests the utility of PLMs to build expression Corresponding author: hongyu.zhao@yale.edu Article published...
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Method: Automated interpretable artificial intelligence genomic prediction with AlGP
- Lei Wei,
- Ziqin Jiang,
- Baoliang Fan,
- Yidan Yan,
- Zhenqiang Xu,
- Xiaoxiang Hu,
- and Yuzhe Wang
Genome Res. March 5, 2026 ; Published in Advance March 5, 2026, doi:10.1101/gr.281006.125
...approaches, integration of prior information, and parameter optimization. The AIGP toolkit enables automated model optimization and interpretability, making ML-driven genomic selection more accessible and providing new tools to support genomic research. [Supplemental material is available for this article...
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Method: Measuring X-Chromosome inactivation skew for X-linked diseases with adaptive nanopore sequencing
- Sena A. Gocuk,
- James Lancaster,
- Shian Su,
- Jasleen K. Jolly,
- Thomas L. Edwards,
- Doron G. Hickey,
- Matthew E. Ritchie,
- Marnie E. Blewitt,
- Lauren N. Ayton,
- and Quentin Gouil
Genome Res. November 2024 34: 1954-1965; Published in Advance September 16, 2024, doi:10.1101/gr.279396.124
....Compared with transcriptome-based estimates of skewed X inactivation (Werner et al. 2022), sequencing the native genomic DNA allows orientation of the skew even for genes that are not expressed in the sampled tissue. Other benefits include a simplified sample collection and preparation, as well as the identification of all...
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Research: Adaptation of centromeres to breakage through local genomic and epigenomic remodeling in wheat
- Jingwei Zhou,
- Yuhong Huang,
- Huan Ma,
- Yiqian Chen,
- Chuanye Chen,
- Fangpu Han,
- and Handong Su
Genome Res. November 2025 35: 2461-2471; Published in Advance September 30, 2025, doi:10.1101/gr.280913.125
...Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; 3State Key Laboratory of Seed Innovation, Institute of Genetics and Developmental Biology, Chinese Academy...
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Research: Genomic regulatory landscape underlying the antiviral response of Atlantic salmon
- Shahmir Naseer,
- Thomas C Clark,
- Bertrand Collet,
- Pooran Dewari,
- Damir Baranasic,
- Daniel J Macqueen,
- Pierre Boudinot,
- and Samuel A.M. Martin
Genome Res. October 22, 2025 gr.280579.125; Published in Advance October 22, 2025, doi:10.1101/gr.280579.125
...for downstream TFBS analysis, allowing the 142 identification of key regulatory motifs involved in the antiviral response. 143 To further characterise the genomic distribution of ATAC-seq and H3K27ac peaks, we 144 annotated consensus peaks relative to gene features and transcription start sites (TSS). The 145...
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Research: Pangenome analysis reveals families of ubiquitin-ligase adaptors as key genomic divergence drivers that lead to hybrid incompatibility
- Dongying Xie,
- Pohao Ye,
- Yiming Ma,
- and Zhongying Zhao
Genome Res. March 2026 36: 506-521; Published in Advance February 17, 2026, doi:10.1101/gr.280885.125
...). These findings suggest that C. nigoni populations may experience substantially higher selection pressure from pathogens in their native environments compared with C. briggsae populations.Genes encoding Cullin-E3 ubiquitin-ligase-adaptors are major contributors to both gene family and genomic sequence divergence...
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Resource: Comprehensive identification of genomic and environmental determinants of phenotypic plasticity in maize
- Laura E. Tibbs-Cortes,
- Tingting Guo,
- Carson M. Andorf,
- Xianran Li,
- and Jianming Yu
Genome Res. August 2024 34: 1253-1263; Published in Advance September 13, 2024, doi:10.1101/gr.279027.124
...) and genomic selection have been two main approaches for complex trait dissection, prediction, and selection (Crossa et al. 2017; Tibbs-Cortes et al. 2021). Recently, both approaches have been expanded to include the environmental dimension, enabling a more comprehensive understanding of phenotypic plasticity...
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