Haplotype analysis incorporating ancestral origins identified novel genetic loci associated with chicken body weight using an advanced intercross line

IF 3.6 1区农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE Genetics Selection Evolution Pub Date : 2024-12-20 DOI:10.1186/s12711-024-00946-y

Lina Bu, Yuzhe Wang, Lizhi Tan, Zilong Wen, Xiaoxiang Hu, Zhiwu Zhang, Yiqiang Zhao

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Abstract

The genome-wide association study (GWAS) is a powerful method for mapping quantitative trait loci (QTL). However, standard GWAS can detect only QTL that segregate in the mapping population. Crossing populations with different characteristics increases genetic variability but F2 or back-crosses lack mapping resolution due to the limited number of recombination events. This drawback can be overcome with advanced intercross line (AIL) populations, which increase the number recombination events and provide a more accurate mapping resolution. Recent studies in humans have revealed ancestry-dependent genetic architecture and shown the effectiveness of admixture mapping in admixed populations. Through the incorporation of line-of-origin effects and GWAS on an F9 AIL population, we identified genes that affect body weight at eight weeks of age (BW8) in chickens. The proposed ancestral-haplotype-based GWAS (testing only the origin regardless of the alleles) revealed three new QTLs on GGA12, GGA15, and GGA20. By using the concepts of ancestral homozygotes (individuals that carry two haplotypes of the same origin) and ancestral heterozygotes (carrying one haplotype of each origin), we identified 632 loci that exhibited high-parent (the heterozygote is better than both parents) and mid-parent (the heterozygote is better than the median of the parents) dominance across 12 chromosomes. Out of the 199 genes associated with BW8, EYA1, PDE1C, and MYC were identified as the best candidate genes for further validation. In addition to the candidate genes reported in this study, our research demonstrates the effectiveness of incorporating ancestral information in population genetic analyses, which can be broadly applicable for genetic mapping in populations generated by ancestors with distinct phenotypes and genetic backgrounds. Our methods can benefit both geneticists and biologists interested in the genetic determinism of complex traits.

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结合祖先起源的单倍型分析利用先进的杂交系发现了与鸡体重相关的新的遗传位点

全基因组关联研究（GWAS）是绘制数量性状位点（QTL）图的有力方法。然而，标准的全基因组关联研究只能检测在制图群体中分离的 QTL。具有不同特征的群体杂交可增加遗传变异性，但由于重组事件数量有限，F2 或回交缺乏制图分辨率。先进的杂交系（AIL）群体可以克服这一缺点，它们增加了重组事件的数量，提供了更精确的制图分辨率。最近对人类的研究揭示了依赖祖先的遗传结构，并显示了在混血人群中进行混血绘图的有效性。通过在一个 F9 AIL 群体中纳入原系效应和 GWAS，我们确定了影响鸡八周龄体重（BW8）的基因。所提出的基于祖先组型的 GWAS（只检测起源而不检测等位基因）揭示了 GGA12、GGA15 和 GGA20 上的三个新 QTL。通过使用祖先同源基因（携带两个同源单倍型的个体）和祖先杂合基因（各携带一个同源单倍型）的概念，我们在 12 条染色体上发现了 632 个表现出高亲本（杂合基因优于双亲）和中亲本（杂合基因优于亲本的中位数）显性的位点。在与 BW8 相关的 199 个基因中，EYA1、PDE1C 和 MYC 被确定为需要进一步验证的最佳候选基因。除了本研究中报告的候选基因外，我们的研究还证明了将祖先信息纳入群体遗传分析的有效性，这种方法可广泛应用于由具有不同表型和遗传背景的祖先所产生的群体的遗传图谱绘制。我们的方法可以使遗传学家和对复杂性状的遗传决定论感兴趣的生物学家受益。

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来源期刊

Genetics Selection Evolution 生物-奶制品与动物科学

CiteScore

6.50

自引率

9.80%

发文量

审稿时长

1 months

期刊介绍： Genetics Selection Evolution invites basic, applied and methodological content that will aid the current understanding and the utilization of genetic variability in domestic animal species. Although the focus is on domestic animal species, research on other species is invited if it contributes to the understanding of the use of genetic variability in domestic animals. Genetics Selection Evolution publishes results from all levels of study, from the gene to the quantitative trait, from the individual to the population, the breed or the species. Contributions concerning both the biological approach, from molecular genetics to quantitative genetics, as well as the mathematical approach, from population genetics to statistics, are welcome. Specific areas of interest include but are not limited to: gene and QTL identification, mapping and characterization, analysis of new phenotypes, high-throughput SNP data analysis, functional genomics, cytogenetics, genetic diversity of populations and breeds, genetic evaluation, applied and experimental selection, genomic selection, selection efficiency, and statistical methodology for the genetic analysis of phenotypes with quantitative and mixed inheritance.