Sequencing & Pangenomes

A Chicken Graph Pangenome Integrating T2T Assemblies Illuminates Causal Structural Variants for Growth Traits

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Abstract

Chickens were the first agricultural animals with a reference genome, yet any single chicken reference cannot capture species-wide diversity. Advances in sequencing technology now enable construction of graph pangenomes based telomere-to-telomere (T2T) assemblies. However, deciphering the genetic regulation of complex traits in biota by structural variations within the pangenome remains a significant challenge to date.We generated Illumina paired-end 150 bp short-read data and de novo assembled six chicken breeds including HQLA (Lingnan Yellow Chicken Line A03), which was one parent strain of our Advanced Intercross Lines (AIL, a population developed by serial passage from HQLA chickens and Huxu Beard chickens to date, featuring abundant quantitative, qualitative, and molecular phenotypes). We generated ~7à— resequencing data for the F16 generation population (1,186 individuals) and recorded 75 phenotypes, including growth and development, tissue and carcass traits, feed intake and feed conversion ratio, blood biochemical indicators, and feather characteristics. For the F18 generation (305 individuals), we obtained ~15à— resequencing data; additionally, transcriptome data from multiple tissues were generated for this population, with phenotypes mainly focusing on body weight and shank circumference. De novo assemblies together with public genomes were integrated using Minigraph-Cactus to build a graph pangenome. Population-scale genotyping on the graph was performed with PanGenie. Subsequently, integrative analysis of SVs and eQTLs was used to assess the probability of shared causal variants, leveraging PP4 (posterior probability of colocalization, i.e., both traits share a single causal variant) to elucidate the functional relevance of structural variations in modulating gene expression traits.We produced six high-quality genomes (1.0-1.1 Gb). The HQLA assembly is gap-free (T2T), with 16.21% repeats and >97% BUSCO completeness. Using GRCg7b as the coordinate backbone for compatibility, the graph pangenome added 149 Mb of novel sequence and comprised 70,238,857 nodes and 89,684,682 edges. Deconstruction of snarls yielded a comprehensive variant map: 15.3M SNPs, 2.4M indels, and ~68k structural variants. Next, we integrated this pangenome with our AIL: F18 resequencing data were aligned to the graph to call variants, which were then imputed into F16; imputation accuracy was assessed by within-F18 mask-and-impute cross-validation and concordance checks. SV-based GWAS for body weight and shank circumference was conducted using a linear mixed model controlling for relatedness (genomic relationship matrix) and key covariates, with genome-wide significance controlled by Bonferroni correction (and FDR for suggestive signals). Colocalization with eQTL/sQTL implicated shared causal variants, and regulatory annotation showed overlaps with tissue-relevant enhancers, promoters, and CTCF/TAD features.Taken together, our study demonstrates that integrating T2T assemblies, a graph pangenome, and population-scale SV genotyping enables precise dissection of the regulatory architecture underlying key growth traits in chickens. These results highlight the value of graph-based genomic references for revealing causal structural variants and accelerating trait-improvement strategies in breeding programs.

Keywords: 2026

How to Cite:

Yu, D., Qu, H., Luo, C., Wang, Y. & Hu, X., (2026) “A Chicken Graph Pangenome Integrating T2T Assemblies Illuminates Causal Structural Variants for Growth Traits”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2285523. doi: https://doi.org/10.31274/wcgalp.23731

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