4.7 Article

Detection of copy number variants in African goats using whole genome sequence data

期刊

BMC GENOMICS
卷 22, 期 1, 页码 -

出版社

BMC
DOI: 10.1186/s12864-021-07703-1

关键词

African goats; Copy number variations; Whole genome sequence

资金

  1. Feed the Future project: Improving Livestock Productivity through Enhanced Breeding Programs (Agricultural Research Service/USDA) [8042-31000-001-02S]
  2. SCINet project of the USDA Agricultural Research Service [0500-00093-001-00-D]

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This study focused on African goats and developed a detailed copy number variation map, identifying a large number of CNVs with substantial differentiation between populations and population-specific selective pressures. A total of 6231 global CNV regions were identified across all animals, containing genes enriched in important biological functions and cellular components.
Background Copy number variations (CNV) are a significant source of variation in the genome and are therefore essential to the understanding of genetic characterization. The aim of this study was to develop a fine-scaled copy number variation map for African goats. We used sequence data from multiple breeds and from multiple African countries. Results A total of 253,553 CNV (244,876 deletions and 8677 duplications) were identified, corresponding to an overall average of 1393 CNV per animal. The mean CNV length was 3.3 kb, with a median of 1.3 kb. There was substantial differentiation between the populations for some CNV, suggestive of the effect of population-specific selective pressures. A total of 6231 global CNV regions (CNVR) were found across all animals, representing 59.2 Mb (2.4%) of the goat genome. About 1.6% of the CNVR were present in all 34 breeds and 28.7% were present in all 5 geographical areas across Africa, where animals had been sampled. The CNVR had genes that were highly enriched in important biological functions, molecular functions, and cellular components including retrograde endocannabinoid signaling, glutamatergic synapse and circadian entrainment. Conclusions This study presents the first fine CNV map of African goat based on WGS data and adds to the growing body of knowledge on the genetic characterization of goats.

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