AUTHOR=Bhatia Vishesh , Stevens Tomas , Derks Martijn F. L. , Dunkelberger Jenelle , Knol Egbert F. , Ross Jason W. , Dekkers Jack C. M. 

TITLE=Identification of the genetic basis of sow pelvic organ prolapse

JOURNAL=Frontiers in Genetics

VOLUME=14

YEAR=2023

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2023.1154713

DOI=10.3389/fgene.2023.1154713

ISSN=1664-8021

ABSTRACT=<p><bold>Introduction:</bold> Pelvic organ prolapse (POP) is one contributor to recent increases in sow mortality that have been observed in some populations and environments, leading to financial losses and welfare concerns.</p><p><bold>Methods:</bold> With inconsistent previous reports, the objective here was to investigate the role of genetics on susceptibility to POP, using data on 30,429 purebred sows, of which 14,186 were genotyped (25K), collected from 2012 to 2022 in two US multiplier farms with a high POP incidence of 7.1% among culled and dead sows and ranging from 2% to 4% of all sows present by parity. Given the low incidence of POP for parities 1 and &gt;6, only data from parities 2 to 6 were retained for analyses. Genetic analyses were conducted both across parities, using cull data (culled for POP versus another reason), and by parity, using farrowing data. (culled for POP versus culled for another reason or not culled).</p><p><bold>Results and Discussion:</bold> Estimates of heritability from univariate logit models on the underlying scale were 0.35 <inline-formula id="inf1"><mml:math id="m1" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mo>±</mml:mo></mml:mrow></mml:math></inline-formula> 0.02 for the across-parity analysis and ranged from 0.41 <inline-formula id="inf2"><mml:math id="m2" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mo>±</mml:mo></mml:mrow></mml:math></inline-formula> 0.03 in parity 2 to 0.15 <inline-formula id="inf3"><mml:math id="m3" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mo>±</mml:mo></mml:mrow></mml:math></inline-formula> 0.07 in parity 6 for the by-parity analyses. Estimates of genetic correlations of POP between parities based on bivariate linear models indicated a similar genetic basis of POP across parities but less similar with increasing distance between parities. Genome wide association analyses revealed six 1 Mb windows that explained more than 1% of the genetic variance in the across-parity data. Most regions were confirmed in several by-parity analyses. Functional analyses of the identified genomic regions showed a potential role of several genes on chromosomes 1, 3, 7, 10, 12, and 14 in susceptibility to POP, including the Estrogen Receptor gene. Gene set enrichment analyses showed that genomic regions that explained more variation for POP were enriched for several terms from custom transcriptome and gene ontology libraries.</p><p><bold>Conclusion:</bold> The influence of genetics on susceptibility to POP in this population and environment was confirmed and several candidate genes and biological processes were identified that can be targeted to better understand and mitigate the incidence of POP.</p>