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1.
PLoS One ; 19(5): e0295109, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38739572

RESUMO

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.


Assuntos
Galinhas , Estudo de Associação Genômica Ampla , Locos de Características Quantitativas , Animais , Galinhas/genética , Galinhas/crescimento & desenvolvimento , Peso Corporal/genética , Polimorfismo de Nucleotídeo Único , Epistasia Genética , Fenótipo , Feminino , Herança Multifatorial , Masculino
2.
J Anim Breed Genet ; 2018 Jun 21.
Artigo em Inglês | MEDLINE | ID: mdl-29926987

RESUMO

Growth is a complex and dynamic process that may be measured at a specific point or over a period of time. Compared was the growth of male and female chickens over a three-generation period. Involved were red junglefowl (RJF; Gallus gallus), a line of White Plymouth Rock chickens (LWS; Gallus gallus domesticus) selected for low body weight, and their reciprocal F1 and F2 crosses. In both sexes, Gompertz's description of growth showed that RJF had significantly lower asymptotes, earlier inflection points, and faster growth rates than LWS. Heterosis for these measures was positive for asymptote and negative for growth rate and inflection point. The RJF commenced egg production at a significantly younger age and lower body weight than LWS. Although F1 and F2 reciprocal crosses were similar for body weight and for age at first egg, the F1 reciprocal crosses began lay at significantly younger ages than the F2 crosses and parental lines. When viewed on a physiological basis where age and body weight were simultaneously standardized, both parental lines and reciprocal F1 and F2 crosses had differing rapid and lag growth phases. Overall, sexual dimorphism increased in all populations from hatch to sexual maturity. The LWS males had a longer growth period consistent with their female counterparts who became sexually mature at older ages. Comprehensively, these results indicate additive and nonadditive genetic variation for distinct growth patterns and changes in resource allocation strategies over time.

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