Differential Effects of Litter Size and Within-Litter Birthweight on Postnatal Traits of Fatty Pigs

MiR-29a Family as a Key Regulator of Skeletal Muscle Dysplasia in a Porcine Model of Intrauterine Growth Retardation

MicroRNAs (miRNAs) play an essential role in many biological processes. In this study, miRNAs in the skeletal muscle of normal and intrauterine growth retardation (IUGR) neonatal piglets were identified by sequencing, and canonical miRNAs were functionally validated in vitro. A total of 403 miRNAs were identified in neonatal piglet skeletal muscle, among them 30 and 46 miRNAs were upregulated and downregulated in IUGR pigs, respectively. Upregulated miRNAs were mainly enriched in propanoate metabolism, endocytosis, beta-Alanine metabolism, gap junction, and tumor necrosis factor signaling pathway. Down-regulated miRNAs were mainly enriched in chemical carcinogenesis—receptor activation, endocytosis, MAPK signaling pathway, insulin resistance, and EGFR tyrosine kinase inhibitor resistance. Co-expression network analysis of umbilical cord blood and skeletal muscle miRNAs showed that the miR-29 family is an essential regulator of IUGR pigs. The dual-luciferase reporter system showed that IGF1 and CCND1 were target genes of the miR-29 family. Transfection of IUGR pig umbilical cord blood exosomes and miR-29a mimic significantly inhibited cell proliferation and promoted the expression of cellular protein degradation marker genes Fbxo32 and Trim63. In summary, these results enrich the regulatory network of miRNAs involved in skeletal muscle development in IUGR animals.

Estimation of Variance Components and Genomic Prediction for Individual Birth Weight Using Three Different Genome-Wide SNP Platforms in Yorkshire Pigs

Simple Summary

The individual birth weight (IBW) of pigs is an important trait regarding its relevance to mortality at weaning, sow prolificacy, and growth performance. This study investigates the variance component estimation, informative window regions, and the efficiency of genomic predictions associated with IBW traits in Yorkshire pigs. The low heritability (0.13) is estimated on the basis of a full model including individual genetic, sow genetic, and common environmental effects. Two common window regions of the genome are identified under three different genotyping platforms found within the ARAP2 and TSN genes concerning the IBW trait. The genomic prediction ability is improved using deregressed estimated breeding values including parental information as a response variable despite Bayesian methods and genotyping platforms for the IBW trait in Korean Yorkshire pigs.

Abstract

This study estimates the individual birth weight (IBW) trait heritability and investigates the genomic prediction efficiency using three types of high-density single nucleotide polymorphism (SNP) genotyping panels in Korean Yorkshire pigs. We use 38,864 IBW phenotypic records to identify a suitable model for statistical genetics, where 698 genotypes match our phenotypic records. During our genomic analysis, the deregressed estimated breeding values (DEBVs) and their reliabilities are used as derived response variables from the estimated breeding values (EBVs). Bayesian methods identify the informative regions and perform the genomic prediction using the IBW trait, in which two common significant window regions (SSC8 27 Mb and SSC15 29 Mb) are identified using the three genotyping platforms. Higher prediction ability is observed using the DEBV-including parent average as a response variable, regardless of the SNP genotyping panels and the Bayesian methods, relative to the DEBV-excluding parent average. Hence, we suggest that fine-mapping studies targeting the identified informative regions in this study are necessary to find the causal mutations to improve the IBW trait’s prediction ability. Furthermore, studying the IBW trait using a genomic prediction model with a larger genomic dataset may improve the genomic prediction accuracy in Korean Yorkshire pigs.