Detection of genomic regions associated malformations in newborn piglets: a machine-learning approach

Siroj Bakoev; Aleksei Traspov; Lyubov Getmantseva; Anna Belous; Tatiana Karpushkina; Olga Kostyunina; Alexander Usatov; Tatiana V Tatarinova

doi:10.7717/peerj.11580

Detection of genomic regions associated malformations in newborn piglets: a machine-learning approach

PeerJ. 2021 Jul 22:9:e11580. doi: 10.7717/peerj.11580. eCollection 2021.

Authors

Siroj Bakoev^{1

2}, Aleksei Traspov^{1

2}, Lyubov Getmantseva¹, Anna Belous¹, Tatiana Karpushkina¹, Olga Kostyunina¹, Alexander Usatov³, Tatiana V Tatarinova^{4

5

6

7}

Affiliations

¹ Federal Research Center for Animal Husbandry named after Academy Member LK. Ernst, Dubrovitsy, Russia.
² Centre for Strategic Planning and Management of Biomedical Health Risks, Moscow, Russia.
³ South Federal University, Rostov-on-Don, Russia.
⁴ Department of Biology, University of La Verne, La Verne, CA, United States of America.
⁵ Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, Russia.
⁶ Vavilov Institute for General Genetics, Moscow, Russia.
⁷ School of Fundamental Biology and Biotechnology, Siberian Federal University, Krasnoyarsk, Russia.

Abstract

Background: A significant proportion of perinatal losses in pigs occurs due to congenital malformations. The purpose of this study is the identification of genomic loci associated with fetal malformations in piglets.

Methods: The malformations were divided into two groups: associated with limb defects (piglet splay leg) and associated with other congenital anomalies found in newborn piglets. 148 Landrace and 170 Large White piglets were selected for the study. A genome-wide association study based on the gradient boosting machine algorithm was performed to identify markers associated with congenital anomalies and piglet splay leg.

Results: Forty-nine SNPs (23 SNPs in Landrace pigs and 26 SNPs in Large White) were associated with congenital anomalies, 22 of which were localized in genes. A total of 156 SNPs (28 SNPs in Landrace; 128 in Large White) were identified for piglet splay leg, of which 79 SNPs were localized in genes. We have demonstrated that the gradient boosting machine algorithm can identify SNPs and their combinations associated with significant selection indicators of studied malformations and productive characteristics.

Data availability: Genotyping and phenotyping data are available at http://www.compubioverne.group/data-and-software/.

Keywords: Agriculture; Congenital malformations; GWAS; Machine learning; Pigs.

Grants and funding

This research was supported by the RSF Project No. 18-76-00034 (Identification of genome regions related to malformations in newborn piglets); the Russian Foundation for Basic Research 19-016-00068 A (Machine learning-methods for detection of genomic regions and genes affecting piglet splay leg); the State task of the Ministry of science and higher education 0445- 2021-0008 (Genotyping of piglets using GeneSeek Genomic Profiler (GGP) BeadChip for Porcine HD). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.