Degree Type

Dissertation

Date of Award

2014

Degree Name

Doctor of Philosophy

Department

Animal Science

First Advisor

Jack C. M. Dekkers

Abstract

Increased milk production due to high litter size, coupled with low feed intake, results in excessive mobilization of sow body reserves during lactation, and this can have detrimental effects on future reproductive performance. A strategy to prevent this is to genetically improve sow lactation performance along with other traits of interest. Hence, the objectives of this thesis were to estimate breed specific genetic parameters and identify genomic regions associated with lactation performance, and to evaluate the accuracy of genomic prediction for traits associated with lactation and lactation efficiency in different breeds of pigs. Breed specific genetic parameters (by parity, between parities, and across parities) were estimated for traits associated with lactation, lactation efficiency, and reproduction, in Yorkshire and Landrace sows from a commercial breeding program. Performance data were available for 2107 sows with 1 to 3 parities (3424 records). Among the traits that measured energy efficiency of sows during lactation, sow lactation efficiency showed a low heritability (nearly 0 in Yorkshire and 0.05 in Landrace sows), but residual feed intake and net energy balance during lactation showed moderate heritabilities in both breeds. Estimates of genetic correlations between traits associated with lactation indicated that feed intake of a sow during lactation has a strong negative genetic correlation with body resource mobilization traits (-0.35 to -0.70), while body resource mobilization traits in turn have a strong positive genetic correlation with litter weight gain (+0.24 to +0.54) (P<0.05). At the same time, feed intake did not exhibit a significant genetic correlation with litter weight gain in either breed. These results suggest that, genetically, increases in feed intake during lactation are predominantly used to reduce sow body tissue losses, rather than for increasing milk production. Genetic correlations between the same traits measured in parity 1 and 2 ranged from +0.64 to +0.98, which implies that for some traits associated with lactation and reproduction, first and second parities should be treated as genetically different. Genetic correlations between parity 1 lactation traits and parity 2 reproductive performance traits were not significantly different from zero in both breeds.

To understand the genetic architecture of traits associated with lactation and lactation efficiency, a genome wide association study (GWAS) using genotypes from the 60k single nucleotide polymorphism (SNP) chip was conducted in three populations (Yorkshire n = 821, Landrace n = 711, Yorkshire lines divergently selected for RFI n = 525). A Bayesian variable selection regression model B (BayesB) was used to estimate the effects of genomic regions on a trait. Separate GWAS were conducted for parity 1 and 2 phenotypes using the software GenSel. Except for one trait in one breed, for all traits studied more than 90% of the genetic variance came from a large number of genomic regions with small effects. The results suggest that these traits are polygenic in nature, without regions or quantitative trait loci (QTL) with big effects. A 1 Mb region on chromosome 2 (at 44 Mb) explained 43% of the genetic variance for litter weight gain (LWG), an indicator trait for milk production potential, in parity 2 Yorkshire sows. Genomic estimated breeding values of Yorkshire sows for this window suggested the presence of a bi-allelic QTL, and one SNP in this window captured all variation for LWG. Fitting the genotype for this SNP as a fixed class effect in a mixed linear animal model, resulted in highly significant P values (P < 0.001) for the effect of genotype at this SNP on litter weight gain, loin depth loss, body weight loss, energy balance, and residual feed intake during lactation for parity 2 Yorkshire sows. Similar results were also observed for these traits for parity 3 sows but with lower P values (P < 0.05). No effects were detected for this region in Landrace sows and in the divergently selected lines of Yorkshire sows.

Most traits associated with lactation exhibited reasonable genetic variation and hence can be improved by selection. However, the economical and practical challenges associated with measuring some of these traits hinder their routine implementation. Recent technological advancements in molecular genetics, especially the high density porcine SNP chip, have improved the ability to used genetic markers in the selection process. To evaluate the potential benefits of using marker information, accuracies of estimated breeding values (EBV) obtained using this marker information were compared with accuracies of pedigree-based EBV. Using a validation set of animals that consisted of individuals from a younger generation, accuracies of four Bayesian regression methods (BayesB, BayesC, BayesCπ and BayesC0) and a pedigree based model (PBLUP) were compared, by correlating the resulting EBV with phenotypes corrected for fixed effects. For most traits, accuracies obtained for Bayesian regression methods were higher than the pedigree based estimates, and among the Bayesian regression methods, BayesB performed better than other models.

In conclusion, traits associated with lactation in sows have a sizable genetic component and there is potential for genetic improvement. Including lactation feed intake and energy balance traits in a maternal selection index, should allow concurrent improvement of sow lactation performance along with grow finish performance. Also, for traits associated with lactation, using genomic information provides more accurate estimates of breeding values than pedigree based methods and hence can provide a better response to selection.

DOI

https://doi.org/10.31274/etd-180810-3768

Copyright Owner

Dinesh Moorkattukara Thekkoot

Language

en

File Format

application/pdf

File Size

267 pages

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