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基于年龄的比利时蓝牛个体基因组近交水平划分。

Age-based partitioning of individual genomic inbreeding levels in Belgian Blue cattle.

机构信息

Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, B34 (+1) Avenue de l'Hôpital 1, 4000, Liège, Belgium.

Awé Coopérative (Association Wallonne de l'Élevage) - Recherche et Développement, Rue des Champs Elysées 4, 5590, Ciney, Belgium.

出版信息

Genet Sel Evol. 2017 Dec 22;49(1):92. doi: 10.1186/s12711-017-0370-x.

Abstract

BACKGROUND

Inbreeding coefficients can be estimated either from pedigree data or from genomic data, and with genomic data, they are either global or local (when the linkage map is used). Recently, we developed a new hidden Markov model (HMM) that estimates probabilities of homozygosity-by-descent (HBD) at each marker position and automatically partitions autozygosity in multiple age-related classes (based on the length of HBD segments). Our objectives were to: (1) characterize inbreeding with our model in an intensively selected population such as the Belgian Blue Beef (BBB) cattle breed; (2) compare the properties of the model at different marker densities; and (3) compare our model with other methods.

RESULTS

When using 600 K single nucleotide polymorphisms (SNPs), the inbreeding coefficient (probability of sampling an HBD locus in an individual) was on average 0.303 (ranging from 0.258 to 0.375). HBD-classes associated to historical ancestors (with small segments ≤ 200 kb) accounted for 21.6% of the genome length (71.4% of the total length of the genome in HBD segments), whereas classes associated to more recent ancestors accounted for only 22.6% of the total length of the genome in HBD segments. However, these recent classes presented more individual variation than more ancient classes. Although inbreeding coefficients obtained with low SNP densities (7 and 32 K) were much lower (0.060 and 0.093), they were highly correlated with those obtained at higher density (r = 0.934 and 0.975, respectively), indicating that they captured most of the individual variation. At higher SNP density, smaller HBD segments are identified and, thus, more past generations can be explored. We observed very high correlations between our estimates and those based on homozygosity (r = 0.95) or on runs-of-homozygosity (r = 0.95). As expected, pedigree-based estimates were mainly correlated with recent HBD-classes (r = 0.56).

CONCLUSIONS

Although we observed high levels of autozygosity associated with small HBD segments in BBB cattle, recent inbreeding accounted for most of the individual variation. Recent autozygosity can be captured efficiently with low-density SNP arrays and relatively simple models (e.g., two HBD classes). The HMM framework provides local HBD probabilities that are still useful at lower SNP densities.

摘要

背景

亲缘系数可以从系谱数据或基因组数据中估计得到,而在使用基因组数据时,亲缘系数可以是全局的,也可以是局部的(当使用连锁图谱时)。最近,我们开发了一种新的隐马尔可夫模型(HMM),该模型可以估计每个标记位置的同源单倍型(HBD)的概率,并根据 HBD 片段的长度自动将多个人类相关年龄类别的自交自动划分(自交)。我们的目标是:(1)在比利时蓝牛(BBB)等高度选择的种群中,用我们的模型描述近交情况;(2)比较不同标记密度下模型的性质;(3)比较我们的模型与其他方法。

结果

使用 600 K 个单核苷酸多态性(SNP)时,近交系数(个体中采样 HBD 位点的概率)平均为 0.303(范围为 0.258 至 0.375)。与历史祖先(小片段≤200 kb)相关的 HBD 类占基因组长度的 21.6%(在 HBD 片段的总长度中占 71.4%),而与更近祖先相关的类仅占 HBD 片段的总长度的 22.6%。然而,这些较近的类表现出比更古老的类更多的个体变异。尽管使用低 SNP 密度(7 和 32 K)获得的近交系数低得多(0.060 和 0.093),但它们与较高密度时获得的近交系数高度相关(r = 0.934 和 0.975),这表明它们捕获了大部分个体变异。在更高的 SNP 密度下,识别到较小的 HBD 片段,因此可以探索更多的过去世代。我们观察到我们的估计值与基于同质性(r = 0.95)或基于 Runs-of-Homozygosity(r = 0.95)的估计值之间存在很高的相关性。正如预期的那样,基于系谱的估计值主要与最近的 HBD 类(r = 0.56)相关。

结论

尽管我们在 BBB 牛中观察到与小 HBD 片段相关的高水平自交,但近期的近交导致了大部分个体变异。利用低密度 SNP 阵列和相对简单的模型(例如,两个 HBD 类)可以有效地捕获近期的自交。HMM 框架提供了局部 HBD 概率,在较低的 SNP 密度下仍然有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/103a/5741860/f4c6bb24c04d/12711_2017_370_Fig1_HTML.jpg

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