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Functional & Integrative Genomics

, Volume 12, Issue 4, pp 717–723 | Cite as

Analysis of copy number variations in Holstein cows identify potential mechanisms contributing to differences in residual feed intake

  • Yali Hou
  • Derek M. Bickhart
  • Hoyoung Chung
  • Jana L. Hutchison
  • H. Duane Norman
  • Erin E. ConnorEmail author
  • George E. LiuEmail author
Short Communication

Abstract

Genomic structural variation is an important and abundant source of genetic and phenotypic variation. In this study, we performed an initial analysis of copy number variations (CNVs) using BovineHD SNP genotyping data from 147 Holstein cows identified as having high or low feed efficiency as estimated by residual feed intake (RFI). We detected 443 candidate CNV regions (CNVRs) that represent 18.4 Mb (0.6 %) of the genome. To investigate the functional impacts of CNVs, we created two groups of 30 individual animals with extremely low or high estimated breeding values (EBVs) for RFI, and referred to these groups as low intake (LI; more efficient) or high intake (HI; less efficient), respectively. We identified 240 (~9.0 Mb) and 274 (~10.2 Mb) CNVRs from LI and HI groups, respectively. Approximately 30–40 % of the CNVRs were specific to the LI group or HI group of animals. The 240 LI CNVRs overlapped with 137 Ensembl genes. Network analyses indicated that the LI-specific genes were predominantly enriched for those functioning in the inflammatory response and immunity. By contrast, the 274 HI CNVRs contained 177 Ensembl genes. Network analyses indicated that the HI-specific genes were particularly involved in the cell cycle, and organ and bone development. These results relate CNVs to two key variables, namely immune response and organ and bone development. The data indicate that greater feed efficiency relates more closely to immune response, whereas cattle with reduced feed efficiency may have a greater capacity for organ and bone development.

Keywords

Cattle genome Copy number variation (CNV) Feed efficiency Residual feed intake (RFI) Single nucleotide polymorphism (SNP) 

Notes

Acknowledgments

GEL and EEC conceived and designed the experiments. EEC collected samples, RFI data, and generated the SNP genotyping data. HDN and JLH performed statistical analyses to estimate RFI. YH and GEL performed in silico prediction and computational analyses. DMB and HC conducted qPCR validations. GEL, EEC, and DMB wrote the manuscript. GEL was supported by NRI/AFRI grants no. 2007-35205-17869 and 2011-67015-30183 from the USDA CSREES (now NIFA) and Projects 1265-31000-098 and 1265-31000-097 from USDA-ARS. Mention of trade names or commercial products in this article is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. The USDA is an equal opportunity provider and employer.

Supplementary material

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Copyright information

© Springer-Verlag (outside the USA) 2012

Authors and Affiliations

  • Yali Hou
    • 1
    • 2
  • Derek M. Bickhart
    • 1
  • Hoyoung Chung
    • 1
    • 3
  • Jana L. Hutchison
    • 4
  • H. Duane Norman
    • 4
  • Erin E. Connor
    • 1
    Email author
  • George E. Liu
    • 1
    Email author
  1. 1.Bovine Functional Genomics LaboratoryANRI, USDA-ARSBeltsvilleUSA
  2. 2.Laboratory of Disease Genomics and Individualized Medicine, Beijing Institute of GenomicsChinese Academy of SciencesBeijingChina
  3. 3.Rural Development AdministrationNational Institute of Animal ScienceSuwonSouth Korea
  4. 4.Animal Improvement Programs LaboratoryANRI, USDA-ARSBeltsvilleUSA

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