Fig. 1: Data summary of the chicken laying-stage GTEx data resource. | Nature Communications

Fig. 1: Data summary of the chicken laying-stage GTEx data resource.

From: Egg-laying ChickenGTEx resource deciphers context-specific regulatory effects on fertility traits

Fig. 1: Data summary of the chicken laying-stage GTEx data resource.The alternative text for this image may have been generated using AI.

A The overall workflow of the chicken laying-stage GTEx. All samples were collected from a single commercial chicken population. In total, 358 hens representing three distinct laying stages—pre-laying (20 weeks of age), peak-laying (30 weeks), and late-laying (58 weeks)—were selected. Four tissues (hypothalamus, pituitary, ovary, and liver) were collected from each individual, generating 1272 RNA-seq datasets. In parallel, genomic DNA was extracted from blood and subjected to whole-genome sequencing (WGS) with an average depth of 26×. Based on these multi-omics data, we performed molecular quantitative trait loci (molQTL) mapping for gene expression, exon expression, enhancer activity, alternative splicing, and tissue-specific expression ratios, and investigated the temporal and tissue-specific regulatory patterns of these molQTL. In addition, low-depth whole-genome sequencing followed by genotype imputation was conducted for 12,952 hens from the same population with recorded egg-production phenotypes. Genome-wide association studies (GWAS) were performed for six complex traits, and the identified QTL were integrated with molQTL to explore their regulatory relationships. Finally, cross-species comparative analyses were carried out to investigate the conservation of reproductive trait regulation among chickens, humans, pigs, and cattle. Illustrative images were created in BioRender. Wang, Y. (2025) https://BioRender.com/fydtay2. B Hierarchical clustering was performed using the expression levels (quantified as transcripts per million, TPM) of the 4000 genes showing the highest variance across all samples, together with the 4000 splicing events exhibiting the greatest variability. This analysis illustrates the overall similarity and tissue-specific clustering patterns among the 1272 RNA-seq datasets.

Back to article page