HapTWAS: a haplotype-resolved transcriptome-wide association study framework

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ID: 329365
2026
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Abstract
Abstract Transcriptome-wide association studies (TWAS) link genetic loci to gene regulation, yet traditional SNP-based models overlook the concerted action of inter-variants and fragment cis-regulatory signals. We present HapTWAS, a haplotype-resolved transcriptome-wide association study framework, that models genetically regulated expression employing haplotypes and supports both individual-level and summary-statistic inputs. Leveraging multi-species FarmGTEx resources, HapTWAS constructs tissue-specific haplotype prediction models and provides a user-friendly server, achieving superior gene expression prediction and gene-trait association with fine-mapping. In balanced simulations, HapTWAS improved expression prediction accuracy by 17.50% (from 0.080 to 0.094) and gene-identified F1-score by 9.02% (from 0.399 to 0.435) while maintaining lower false discovery rate. Applied to six complex traits across four species, HapTWAS detected 20.64% additional genes and prioritized biologically meaningful candidates missed by SNP-based approaches. Our perturbation experiment confirmed MRPL45 as a regulator of porcine skeletal muscle cell proliferation. HapTWAS provides a scalable haplotype‑based strategy that directly encodes linkage phase and local LD into the predictor space, accelerating candidate gene discovery and delivering insights into human health and animal production.
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Authors Cheng Liu, Zitao Chen, Zhenyang Zhang, He Han, Zhan Wang, Yiting Wang, Qinqin Xie, Jiamin Gu, Wei Li, Zhe Zhang, Zhen Wang, Yuchun Pan, Lingzhao Fang, Qishan Wang
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Journal national science review
Year 2026
DOI
10.1093/nsr/nwag605
URL
https://doi.org/10.1093/nsr/nwag605
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