Polymorphisms of the porcine dopaminebeta-hydroxylase gene and their relation to reproduction and piglet survivability in an Iberian x Meishan F2 intercross

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.

Genome-Wide Association Study and Fine Mapping Reveals Candidate Genes for Birth Weight of Yorkshire and Landrace Pigs

Birth weight of pigs is an important economic factor in the livestock industry. The identification of the genes and variants that underlie birth weight is of great importance. In this study, we integrated two genotyping methods, single nucleotide polymorphism (SNP) chip analysis and restriction site associated DNA sequencing (RAD-seq) to genotype genome-wide SNPs. In total, 45,175 and 139,634 SNPs were detected with the SNP chip and RAD-seq, respectively. The genome-wide association study (GWAS) of the combined SNP panels identified two significant loci located at chr1: 97,745,041 and chr4: 112,031,589, that explained 6.36% and 4.25% of the phenotypic variance respectively. To reduce interval containing causal variants, we imputed sequence-level SNPs in the GWAS identified regions and fine-mapped the causative variants into two narrower genomic intervals: a ∼100 kb interval containing 71 SNPs and a broader ∼870 kb interval with 432 SNPs. This fine-mapping highlighted four promising candidate genes, SKOR2, SMAD2, VAV3, and NTNG1. Additionally, the functional genes, SLC25A24, PRMT6 and STXBP3, are also located near the fine-mapping region. These results suggest that these candidate genes may have contribute substantially to the birth weight of pigs.

The dopamine β-hydroxylase gene in Chinese goose (Anas cygnoides): cloning, characterization, and expression during the reproductive cycle

BACKGROUND

Dopamine β-hydroxylase (DBH) is a critical enzyme in the biosynthesis of catecholamines. This enzyme's role in neuroendocrine regulation is well known, but there are some indications that it may also modulate reproduction and endocrine in mammals and birds. We selected goose (Anas cygnoides) as an ideal model species for investigating the role of DBH in avian reproduction.

RESULTS

Full-length cDNA encoding DBH was cloned from Zhedong goose using reverse transcription PCR and rapid amplification of cDNA ends. The cDNA consisted of a 126-base pair (bp) 5'-untranslated region (UTR), a 379-bp 3'-UTR, and an 1896-bp open reading frame encoding a polypeptide of 631 amino acids. The deduced amino acid sequence of gDBH shared high homology with an analogue from other birds and contained three conserved domains from a mono-oxygenase family including a DOMON domain and two Cu2_mono-oxygen domains. Real-time quantitative PCR analysis showed that gDBH mRNA was expressed in both reproductive and endocrine tissues of Zhedong goose, specifically in the hypothalamus, pituitary, ovary, and oviduct. More DBH mRNA of reproductive and endocrine tissues was detected at ovulation than at oviposition in Zhedong goose. Evidence of opposite trend of gDBH expression was found between the hypothalamus-pituitary and oviduct during the ovulation phase and the broody phase. In addition, we assessed DBH mRNA expression during ovulation in two breeds of geese that differ in egg production. The reproductive and endocrine tissues of Yangzhou geese with higher egg production had more gDBH expression than Zhedong geese. Finally, the five non-synonymous SNP(c.1739 C > T, c.1760G > T, c.1765A > G, c.1792 T > C and c.1861G > C) were identified in the coding region of DBH gene between Zhedong goose and Yangzhou goose.

CONCLUSIONS

We conclude that goose DBH mRNA show obvious periodically variation in reproductive and endocrine tissues during the reproductive cycle in geese.

Genome wide screening of candidate genes for improving piglet birth weight using high and low estimated breeding value populations

Birth weight is an economically important trait in pig production because it directly impacts piglet growth and survival rate. In the present study, we performed a genome wide survey of candidate genes and pathways associated with individual birth weight (IBW) using the Illumina PorcineSNP60 BeadChip on 24 high (HEBV) and 24 low estimated breeding value (LEBV) animals. These animals were selected from a reference population of 522 individuals produced by three sires and six dam lines, which were crossbreds with multiple breeds. After quality-control, 43,257 SNPs (single nucleotide polymorphisms), including 42,243 autosomal SNPs and 1,014 SNPs on chromosome X, were used in the data analysis. A total of 27 differentially selected regions (DSRs), including 1 on Sus scrofa chromosome 1 (SSC1), 1 on SSC4, 2 on SSC5, 4 on SSC6, 2 on SSC7, 5 on SSC8, 3 on SSC9, 1 on SSC14, 3 on SSC18, and 5 on SSCX, were identified to show the genome wide separations between the HEBV and LEBV groups for IBW in piglets. A DSR with the most number of significant SNPs (including 7 top 0.1% and 31 top 5% SNPs) was located on SSC6, while another DSR with the largest genetic differences in F_ST was found on SSC18. These regions harbor known functionally important genes involved in growth and development, such as TNFRSF9 (tumor necrosis factor receptor superfamily member 9), CA6 (carbonic anhydrase VI) and MDFIC (MyoD family inhibitor domain containing). A DSR rich in imprinting genes appeared on SSC9, which included PEG10 (paternally expressed 10), SGCE (sarcoglycan, epsilon), PPP1R9A (protein phosphatase 1, regulatory subunit 9A) and ASB4 (ankyrin repeat and SOCS box containing 4). More importantly, our present study provided evidence to support six quantitative trait loci (QTL) regions for pig birth weight, six QTL regions for average birth weight (ABW) and three QTL regions for litter birth weight (LBW) reported previously by other groups. Furthermore, gene ontology analysis with 183 genes harbored in these 27 DSRs suggested that protein, metal, ion and ATP binding, viral process and innate immune response present important pathways for deciphering their roles in fetal growth or development. Overall, our study provides useful information on candidate genes and pathways for regulating birth weight in piglets, thus improving our understanding of the genetic mechanisms involved in porcine embryonic or fetal development.

Transcriptome profiling of the goose (Anser cygnoides) ovaries identify laying and broodiness phenotypes

Background

The geese have strong broodiness and poor egg performance. These characteristics are the key issues that hinder the goose industry development. Yet little is known about the mechanisms responsible for follicle development due to lack of genomic resources. Hence, studies based on high-throughput sequencing technologies are needed to produce a comprehensive and integrated genomic resource and to better understand the biological mechanisms of goose follicle development.

Methodology/Principal Findings

In this study, we performed de novo transcriptome assembly and gene expression analysis using short-read sequencing technology (Illumina). We obtained 67,315,996 short reads of 100 bp, which were assembled into 130,514 unique sequences by Trinity strategy (mean size = 753bp). Based on BLAST results with known proteins, these analyses identified 52,642 sequences with a cut-off E-value above 10⁻⁵. Assembled sequences were annotated with gene descriptions, gene ontology and clusters of orthologous group terms. In addition, we investigated the transcription changes during the goose laying/broodiness period using a tag-based digital gene expression (DGE) system. We obtained a sequencing depth of over 4.2 million tags per sample and identified a large number of genes associated with follicle development and reproductive biology including cholesterol side-chain cleavage enzyme gene and dopamine beta-hydroxylas gene. We confirm the altered expression levels of the two genes using quantitative real-time PCR (qRT-PCR).

Conclusions/Significance

The obtained goose transcriptome and DGE profiling data provide comprehensive gene expression information at the transcriptional level that could promote better understanding of the molecular mechanisms underlying follicle development and productivity.

Empirical Bayes factor analyses of quantitative trait loci for gestation length in Iberian × Meishan F2 sows

The aim of this study was to investigate chromosomal regions affecting gestation length in sows. An experimental F2 cross between Iberian and Meishan pig breeds was used for this purpose and we genotyped 119 markers covering the 18 porcine autosomal chromosomes. Within this context, we have developed a new empirical Bayes factor (BF) approach to compare between nested models, with and without the quantitative trait loci (QTL) effect, and after including the location of the QTL as an unknown parameter in the model. This empirical BF can be easily calculated from the output of a Markov chain Monte Carlo sampling by averaging conditional densities at the null QTL effects. Linkage analyses were performed in each chromosome using an animal model to account for infinitesimal genetic effects. Initially, three QTL were detected at chromosomes 6, 8 and 11 although, after correcting for multiple testing, only the additive QTL located in cM 110 of chromosome 8 remained. For this QTL, the allelic effect of substitution of the Iberian allele increased gestation length in 0.521 days, with a highest posterior density region at 95% ranged between 0.121 and 0.972 days. Although future studies are necessary to confirm if detected QTL is relevant and segregating in commercial pig populations, a hot-spot on the genetic regulation of gestation length in pigs seems to be located in chromosome 8.

Association of the porcine transforming growth factor beta type I receptor (TGFBR1) gene with growth and carcass traits

BACKGROUND

Growth and carcass traits are of great economic importance in livestock production. A large number of quantitative trait loci (QTL) have been identified for growth and carcass traits on porcine chromosome one (SSC1). A key positional candidate for this chromosomal region is TGFBR1 (transforming growth factor beta type I receptor). This gene plays a key role in inherited disorders at cardiovascular, craniofacial, neurocognitive, and skeletal development in mammals.

RESULTS

In this study, 27 polymorphic SNPs in the porcine TGFBR1 gene were identified on the University of Illinois Yorkshire × Meishan resource population. Three SNPs (SNP3, SNP43, SNP64) representing major polymorphic patterns of the 27 SNPs in F1 and F0 individuals of the Illinois population were selected for analyses of QTL association and genetic diversity. An association analysis for growth and carcass traits was completed using these three representative SNPs in the Illinois population with 298 F2 individuals and a large commercial population of 1008 animals. The results indicate that the TGFBR1 gene polymorphism (SNP64) is significantly associated (p < 0.05) with growth rates including average daily gains between birth and 56 kg (p = 0.049), between 5.5 and 56 kg (p = 0.024), between 35 and 56 kg (p = 0.021). Significant associations (p < 0.05) were also identified between TGFBR1 gene polymorphisms (SNP3/SNP43) and carcass traits including loin-eye-area (p = 0.022) in the Illinois population, and back-fat thickness (p = 0.0009), lean percentage (p = 0.0023) and muscle color (p = 0.021) in the commercial population. These three SNPs were also used to genotype a diverse panel of 130 animals representing 11 pig breeds. Alleles SNP3_T and SNP43_G were fixed in Pietrain and Sinclair pig breeds. SNP64_G allele was uniquely identified in Chinese Meishan pigs. Strong evidence of association (p < 0.01) between both SNP3 and SNP64 alleles and reproductive traits including gestation length and number of corpora lutea were also observed in the Illinois population.

CONCLUSION

This study gives the first evidence of association between the porcine TGFBR1 gene and traits of economic importance and provides support for using TGFBR1 markers for pig breeding and selection programs. The genetic diversities in different pig breeds would be helpful to understand the genetic background and migration of the porcine TGFBR1 gene.

A bi-dimensional genome scan for prolificacy traits in pigs shows the existence of multiple epistatic QTL

BACKGROUND

Prolificacy is the most important trait influencing the reproductive efficiency of pig production systems. The low heritability and sex-limited expression of prolificacy have hindered to some extent the improvement of this trait through artificial selection. Moreover, the relative contributions of additive, dominant and epistatic QTL to the genetic variance of pig prolificacy remain to be defined. In this work, we have undertaken this issue by performing one-dimensional and bi-dimensional genome scans for number of piglets born alive (NBA) and total number of piglets born (TNB) in a three generation Iberian by Meishan F(2) intercross.

RESULTS

The one-dimensional genome scan for NBA and TNB revealed the existence of two genome-wide highly significant QTL located on SSC13 (P < 0.001) and SSC17 (P < 0.01) with effects on both traits. This relative paucity of significant results contrasted very strongly with the wide array of highly significant epistatic QTL that emerged in the bi-dimensional genome-wide scan analysis. As much as 18 epistatic QTL were found for NBA (four at P < 0.01 and five at P < 0.05) and TNB (three at P < 0.01 and six at P < 0.05), respectively. These epistatic QTL were distributed in multiple genomic regions, which covered 13 of the 18 pig autosomes, and they had small individual effects that ranged between 3 to 4% of the phenotypic variance. Different patterns of interactions (a x a, a x d, d x a and d x d) were found amongst the epistatic QTL pairs identified in the current work.

CONCLUSIONS

The complex inheritance of prolificacy traits in pigs has been evidenced by identifying multiple additive (SSC13 and SSC17), dominant and epistatic QTL in an Iberian x Meishan F(2) intercross. Our results demonstrate that a significant fraction of the phenotypic variance of swine prolificacy traits can be attributed to first-order gene-by-gene interactions emphasizing that the phenotypic effects of alleles might be strongly modulated by the genetic background where they segregate.