Complex genetic architecture of the chicken Growth1 QTL region

Abstract

The genetic complexity of polygenic traits represents a captivating and intricate facet of biological inheritance. Unlike Mendelian traits controlled by a single gene, polygenic traits are influenced by multiple genetic loci, each exerting a modest effect on the trait. This cumulative impact of numerous genes, interactions among them, environmental factors, and epigenetic modifications results in a multifaceted architecture of genetic contributions to complex traits. Given the well-characterized genome, diverse traits, and range of genetic resources, chicken (Gallus gallus) was employed as a model organism to dissect the intricate genetic makeup of a previously identified major Quantitative Trait Loci (QTL) for body weight on chromosome 1. A multigenerational advanced intercross line (AIL) of 3215 chickens whose genomes had been sequenced to an average of 0.4x was analyzed using genome-wide association study (GWAS) and variance-heterogeneity GWAS (vGWAS) to identify markers associated with 8-week body weight. Additionally, epistatic interactions were studied using the natural and orthogonal interaction (NOIA) model. Six genetic modules, two from GWAS and four from vGWAS, were strongly associated with the studied trait. We found evidence of both additive- and non-additive interactions between these modules and constructed a putative local epistasis network for the region. Our screens for functional alleles revealed a missense variant in the gene ribonuclease H2 subunit B (RNASEH2B), which has previously been associated with growth-related traits in chickens and Darwin's finches. In addition, one of the most strongly associated SNPs identified is located in a non-coding region upstream of the long non-coding RNA, ENSGALG00000053256, previously suggested as a candidate gene for regulating chicken body weight. By studying large numbers of individuals from a family material using approaches to capture both additive and non-additive effects, this study advances our understanding of genetic complexities in a highly polygenic trait and has practical implications for poultry breeding and agriculture.

Fig 1. GWAS results on chromosome 1 150-180Mb region.

(a) Result of standard GWAS. Figures (b) and (c) show the result of adding the top SNP markers as covariates. The result shows that after adding the right peak as a covariate, the left peak signal remains moderate. This implies that both peaks could carry different effects. The QTL Growth1 region (chr1:165330388–176818938) is annotated with an orange translucent mask.

Fig 2. GWAS results and linkage disequilibrium (LD) on chromosome 1 150-180Mb region.

LD was painted related to the marker gga1_171m. Variants in the gga1_168m peak do not show high LD to marker in the gga1_171m.

Fig 3. Variance-heterogeneity GWAS result.

Red lines annotate the position of selected SNPs showing variance effects.

Fig 4. Distributions of normalized body weight stratified by genotype at marker gga1_178v.

Violin plots showing variance differences between genotype groups. The star signs show the pairwise significance of the variance effect.

Fig 5. Haplotype-based association study.

Haplotype-based association study results on chromosome 1 150-180Mb region. (a) General haplotype-based association study. A negative log of the P-value on the y-axis shows significant results. (b) Ancestry haplotype association study result. (c) Haplotype mosaic plot for F₀ generation of the population. Each row represents a sample. The color stands for different ancestry donors.

Fig 6. Significant interaction effect among selected markers.

A and D stand for additive effects and dominance effects. Line colors indicate the degree of statistical significance, with darker colors indicating lower P-values.

Fig 7. Epistasis effects conditioned on gga1_178v.

(a), samples were grouped by genotype of gga1_178v (red vertical line), in which 0, 1, and 2 represent the number of alternative alleles. The top SNP marker is annotated by the blue vertical line. (b) shows the normalized average and standard deviation body weight in different conditions.