Integrating Genetic and Genomic Analyses of Combined Health Data Across Ecotypes to Improve Disease Resistance in Indigenous African Chickens.
Integrating Genetic and Genomic Analyses of Combined Health Data Across Ecotypes to Improve Disease Resistance in Indigenous African Chickens.
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DOI：
10.3389/fgene.2020.543890
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发表时间：
2020
影响因子：
3.7
通讯作者：
Psifidi A
中科院分区：
文献类型：
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作者：
Banos G;Lindsay V;Desta TT;Bettridge J;Sanchez-Molano E;Vallejo-Trujillo A;Matika O;Dessie T;Wigley P;Christley RM;Kaiser P;Hanotte O;Psifidi A
家禽在许多非洲国家的农业中发挥着重要作用。撒哈拉以南非洲的大多数鸡都是本地的，在半食腐条件下在村庄里饲养。疫苗接种和生物安全措施很少适用，传染病仍然是导致死亡和生产力下降的一个主要原因。抗病的基因组选择提供了一个潜在的可持续解决方案，但这需要足够数量的具有基因组和表型数据的个体鸟，而在本地鸡生态型的小种群中收集这些数据往往是一个挑战。跨生态型信息的使用为增加基因组选择的相关数量和准确性提供了一个有吸引力的可能性。在这项研究中，我们对两种不同的埃塞俄比亚土鸡生态型进行了联合分析，以研究重要健康和生产力性状的基因组结构，并探索跨生态型进行基因组选择的可行性。考虑的表型性状包括对传染性法氏囊病（IBDV）、马立克病（MDV）、禽霍乱（PM）和禽伤寒（SG）的抗体应答，对艾美耳球虫和绦虫寄生的抗性，以及生产力[体重和体况评分（BCS）]。结合霍罗（n = 384）和雅索（n = 376）两个生态型的数据，对遗传参数估计、全基因组关联研究（GWAS）、基因组育种值（GEBVs）计算、基因组预测、全基因组测序（WGS）和途径分析进行联合分析。除SG和BCS外，其余性状的跨生态型遗传力均为显著且中等水平（0.22 ~ 0.47）。GWAS确定了几个与健康和生产力特征相关的重要基因组。WGS分析揭示了IBDV （TOLLIP、ANGPTL5、BCL9、THEMIS2）、MDV （GRM7）、SG （MAP3K21）、艾美耳球虫（TOM1L1）和cestdes （TNFAIP1、ATG9A、NOS2）寄生的候选基因和突变，值得进一步研究。与生态型内计算相比，gebv的可靠性提高了，但基因组预测的准确性却没有提高，这可能是因为两种生态型之间的遗传距离抵消了样本量增加带来的好处。然而，对某些性状的基因组预测只能通过跨生态型分析来实现。我们的研究结果普遍支持基因组选择的潜力，以提高跨生态型的健康和生产力。未来的研究应确定所需的最小样本量和生态型之间的遗传相似性，以确保准确的联合基因组选择。
Poultry play an important role in the agriculture of many African countries. The majority of chickens in sub-Saharan Africa are indigenous, raised in villages under semi-scavenging conditions. Vaccinations and biosecurity measures rarely apply, and infectious diseases remain a major cause of mortality and reduced productivity. Genomic selection for disease resistance offers a potentially sustainable solution but this requires sufficient numbers of individual birds with genomic and phenotypic data, which is often a challenge to collect in the small populations of indigenous chicken ecotypes. The use of information across-ecotypes presents an attractive possibility to increase the relevant numbers and the accuracy of genomic selection. In this study, we performed a joint analysis of two distinct Ethiopian indigenous chicken ecotypes to investigate the genomic architecture of important health and productivity traits and explore the feasibility of conducting genomic selection across-ecotype. Phenotypic traits considered were antibody response to Infectious Bursal Disease (IBDV), Marek’s Disease (MDV), Fowl Cholera (PM) and Fowl Typhoid (SG), resistance to Eimeria and cestode parasitism, and productivity [body weight and body condition score (BCS)]. Combined data from the two chicken ecotypes, Horro (n = 384) and Jarso (n = 376), were jointly analyzed for genetic parameter estimation, genome-wide association studies (GWAS), genomic breeding value (GEBVs) calculation, genomic predictions, whole-genome sequencing (WGS), and pathways analyses. Estimates of across-ecotype heritability were significant and moderate in magnitude (0.22–0.47) for all traits except for SG and BCS. GWAS identified several significant genomic associations with health and productivity traits. The WGS analysis revealed putative candidate genes and mutations for IBDV (TOLLIP, ANGPTL5, BCL9, THEMIS2), MDV (GRM7), SG (MAP3K21), Eimeria (TOM1L1) and cestodes (TNFAIP1, ATG9A, NOS2) parasitism, which warrant further investigation. Reliability of GEBVs increased compared to within-ecotype calculations but accuracy of genomic prediction did not, probably because the genetic distance between the two ecotypes offset the benefit from increased sample size. However, for some traits genomic prediction was only feasible in across-ecotype analysis. Our results generally underpin the potential of genomic selection to enhance health and productivity across-ecotypes. Future studies should establish the required minimum sample size and genetic similarity between ecotypes to ensure accurate joint genomic selection.