The estrogen receptor locus is associated with a major gene influencing litter size in pigs.

Abstract

Identification of individual major genes affecting quantitative traits in livestock species has been limited to date. By using a candidate gene approach and a divergent breed cross involving the Chinese Meishan pig, we have shown that a specific allele of the estrogen receptor (ER) locus is associated with increased litter size. Female pigs from synthetic lines with a 50% Meishan background that were homozygous for this beneficial allele produced 2.3 more pigs in first parities and 1.5 more pigs averaged over all parities than females from the same synthetic lines and homozygous for the undesirable allele. This beneficial ER allele was also found in pigs with Large White breed ancestory. Analysis of females with Large White breed background showed an advantage for females homozygous for the beneficial allele as compared to females homozygous for the other allele of more than 1 total pig born. Analyses of growth performance test records detected no significant unfavorable associations of the beneficial allele with growth and developmental traits. Mapping of the ER gene demonstrated that the closest known genes or markers were 3 centimorgans from ER. To our knowledge, one of these, superoxide dismutase gene (SOD2), was mapped for the first time in the pig. Analysis of ER and these linked markers indicated that ER is the best predictor of litter size differences. Introgression of the beneficial allele into commercial pig breeding lines, in which the allele was not present, and marker-assisted selection for the beneficial allele in lines with Meishan and Large White background have begun.

Use of meta-analysis to combine candidate gene association studies: application to study the relationship between the ESR PvuII polymorphism and sow litter size

“…However, the sampling error is not the only cause that explains the diversity found in the results of the literature. While Rothschild et al [47] and Short et al [49] found differences for all traits, Southwood et al [52] did not find a significant effect of the B allele in NBA and TNB. This lack of significance was mainly due to a second parity drop, which had its largest effect impact in the more productive genotypes [52].…”

“…Standard errors originally not reported and computed in this work to make meta-analysis possible are over or underestimated. For example, for Korwin-Kossakowska et al [26], Rothschild et al [47], Short et al [49] and Southwood et al [52] standard errors were overestimated when the differences were significant, since they represent the maximum standard error inferred by the level of significance reported. And, oppositely, when differences were not significant, standard errors were underestimated, since they represent the minimum standard error inferred by the level of significance reported.…”

“…This hypothesis could be considered for several of the experiments reviewed but it could be rejected for the studies of Rothschild et al [47], Short et al [49] and Southwood et al [52] given the number of pigs involved. However, the sampling error is not the only cause that explains the diversity found in the results of the literature.…”

“…The criteria for excluding the identified studies and/or populations were the following: (1) Mean genotype values or differences for NBA1, TNB1, NBA or TNB were not estimated (i.e., only allele frequencies referred) [6,7,58] or reported [22,39]; (2) No sufficient information is provided in proceedings or English abstracts [24,36,50,51]; (3) Populations are monomorphic [12,13,30,53] or are analysed in other studies using a different number of data or methodology [34,44,45,48] (studies with more information or published in peer review journals were chosen).…”

“…Differences between genotype groups were estimated from published values of genotype or allele effect. The standard errors of differences were computed based on available information: (1) the standard errors of genotype effect estimates [11,14,21,30,32,33,57]; (2) the standard deviation and the number of records [25] or, when not available, the number of animals [5] of each genotype class; (3) the standard deviation estimated at the population level and the number of records [29]; (4) the P-values of t-test and the number of records of each genotype class [13]; (5) the level of significance of t-tests and the number of records of each genotype class [26,47,49,52]. When the number of records of each genotype class was not available, they were deducted from estimated allele frequencies assuming Hardy-Weinberg equilibrium.…”