Analysis of runs of homozygosity from next generation sequence data in Canadian dairy cattle

加拿大奶牛下一代序列数据纯合性分析

• 批准号: 494693-2016
• 负责人: Baes, Christine
• 金额: $ 2.16万
• 依托单位: University of Guelph
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=644440
• 关键词: Analysis; runs; homozygosity; next; generation

Cattle breeders commonly estimate inbreeding coefficients by calculating the degree of parental relatedness using pedigree information, and, more recently, SNP data. The rate of inbreeding in dairy cattle populations has increased in recent years, and will likely continue to increase steadily as genomic selection intensifies. In Canada, Stachowicz et al. (2011) found that both Jersey and Holstein populations have very limited gene pools and already suffer from negative effects of accumulation of inbreeding and genetic diversity loss. The authors suggest that the rapid decrease in generation interval through genomic selection will cause an even faster accumulation of inbreeding over time. They concluded that a need exists for managing selection and mating decisions to control future inbreeding. Using current genomic information, we propose the use of new genomic tools to better understand the mechanisms of inbreeding in Canadian dairy populations and to re-evaluate appropriate rates of inbreeding. This research project involves 3 stages: (1) analysis of genomic inbreeding in Canadian dairy breeds using both array and sequence information, and characterisation of regions of homozygous loci, including rate and functional severity of deleterious and neutral variants within runs of homozygosity, (2) understanding the consequences of genomic inbreeding through genome-wide association analyses using the regions of homozygosity identified, (3) integration of new knowledge into selection strategies to help manage genomic inbreeding based on simulation results. We propose that the currently available genomic information provides new possibilities for monitoring and controlling the frequency of deleterious recessive alleles and haplotypes. **

牛育种者通常通过使用系谱信息和最近的SNP数据计算亲本相关程度来估计近交系数。近年来，奶牛群体中的近亲繁殖率有所增加，并且随着基因组选择的加强，可能会继续稳步增加。在加拿大，Stachowicz等人（2011年）发现泽西岛和荷斯坦牛种群的基因库非常有限，已经受到近亲繁殖和遗传多样性丧失的负面影响。作者认为，通过基因组选择快速缩短世代间隔将导致近亲繁殖随着时间的推移更快地积累。他们的结论是，需要管理选择和交配的决定，以控制未来的近亲繁殖。利用目前的基因组信息，我们建议使用新的基因组工具，以更好地了解在加拿大的奶牛种群近亲繁殖的机制，并重新评估适当的近亲繁殖率。本研究项目包括三个阶段：（1）使用阵列和序列信息分析加拿大奶牛品种中的基因组近亲繁殖，以及纯合基因座区域的表征，包括纯合性运行内有害和中性变体的比率和功能严重性，（2）通过使用鉴定的纯合性区域的全基因组关联分析理解基因组近亲繁殖的后果，（3）将新知识整合到选择策略中，以帮助基于模拟结果管理基因组近交。 我们建议，目前可用的基因组信息提供了新的可能性，监测和控制有害的隐性等位基因和单倍型的频率。**