High-resolution association mapping of number of teats in pigs reveals regions controlling vertebral development

Background

Selection pressure on the number of teats has been applied to be able to provide enough teats for the increase in litter size in pigs. Although many QTL were reported, they cover large chromosomal regions and the functional mutations and their underlying biological mechanisms have not yet been identified. To gain a better insight in the genetic architecture of the trait number of teats, we performed a genome-wide association study by genotyping 936 Large White pigs using the Illumina PorcineSNP60 Beadchip. The analysis is based on deregressed breeding values to account for the dense family structure and a Bayesian approach for estimation of the SNP effects.

Results

The genome-wide association study resulted in 212 significant SNPs. In total, 39 QTL regions were defined including 170 SNPs on 13 Sus scrofa chromosomes (SSC) of which 5 regions on SSC7, 9, 10, 12 and 14 were highly significant. All significantly associated regions together explain 9.5% of the genetic variance where a QTL on SSC7 explains the most genetic variance (2.5%). For the five highly significant QTL regions, a search for candidate genes was performed. The most convincing candidate genes were VRTN and Prox2 on SSC7, MPP7, ARMC4, and MKX on SSC10, and vertebrae δ-EF1 on SSC12. All three QTL contain candidate genes which are known to be associated with vertebral development. In the new QTL regions on SSC9 and SSC14, no obvious candidate genes were identified.

Conclusions

Five major QTL were found at high resolution on SSC7, 9, 10, 12, and 14 of which the QTL on SSC9 and SSC14 are the first ones to be reported on these chromosomes. The significant SNPs found in this study could be used in selection to increase number of teats in pigs, so that the increasing number of live-born piglets can be nursed by the sow. This study points to common genetic mechanisms regulating number of vertebrae and number of teats.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-542) contains supplementary material, which is available to authorized users.     

SNPs associated with body weight and backfat thickness in two pig breeds identified by a genome-wide association study

Growth and fat deposition are important economic traits due to the influence on production in pigs. In this study, a dataset of 1200 pigs with 345,570 SNPs genotyped by sequencing (GBS) was used to conduct a GWAS with single-marker regression method to identify SNPs associated with body weight and backfat thickness (BFT) and to search for candidate genes in Landrace and Yorkshire pigs. A total of 27 and 13 significant SNPs were associated with body weight and BFT, respectively. In the region of 149.85–149.89 Mb on SSC6, the SNP (SSC6: 149876737) for body weight and the SNP (SSC6: 149876507) for BFT were in the same locus region (a gap of 230 bp). Two SNPs were located in the DOCK7 gene, which is a protein-coding gene that plays an important role in pigmentation. Two SNPs located on SSC8: 54567459 and SSC11: 33043081 were found to overlap weight and BFT; however, no candidate gene was found in these regions. In addition, based on other significant SNPs, two positional candidate genes, NSRP1 and CADPS, were proposed to influence weight. In conclusion, this is the first study report using GBS data to identify the significant SNPs for weight and BFT. A total of four particularly interesting SNPs and one potential candidate genes (DOCK7) were found for these traits in domestic pigs. This study improves our knowledge to better understand the complex genetic architecture of weight and BFT, but further validation studies of these candidate loci and genes are recommended in pigs     

A genome-wide association study for feed efficiency-related traits in a crossbred pig population

Feed efficiency (FE) is one of the most important traits in pig production. However, it is difficult and costly to measure it, limiting the collection of large amount of data for an accurate selection for better FE. Therefore, the identification of single-nucleotide polymorphisms (SNPs) associated with FE-related traits to be used in the genetic evaluation is of great interest of pig breeding programs for increasing the prediction accuracy and the genetic progress of these traits. The objective of this study was to identify SNPs significantly associated with FE-related traits: average daily gain (ADG), average daily feed intake (ADFI) and feed conversion ratio (FCR). We also aimed to identify potential candidate genes for these traits. Phenotypic information recorded on a population of 2386 three-way crossbreed pigs that were genotyped for 51 468 SNPs was used. We identified three loci of quantitative trait (QTL) regions associated with ADG and three QTL regions associated with ADFI; however, no significant association was found for FCR. A false discovery rate (FDR) ≤ 0.005 was used as the threshold for declaring an association as significant. The QTL regions associated with ADG on Sus scrofa chromosome (SSC) 1 were located between 177.01 and 185.47 Mb, which overlaps with the QTL regions for ADFI on SSC1 (173.26 and 185.47 Mb). The other QTL region for ADG was located on SSC12 (2.87 and 3.22 Mb). The most significant SNPs in these QTL regions explained up to 3.26% of the phenotypic variance of these traits. The non-identification of genomic regions associated with FCR can be explained by the complexity of this trait, which is a ratio between ADG and ADFI. Finally, the genes CDH19, CDH7, RNF152, MC4R, PMAIP1, FEM1B and GAA were the candidate genes found in the 1 Mb window around the QTL regions identified in this study. Among them, the MC4R gene (SSC1) has a well-known function related to ADG and ADFI. In this study, we identified three QTL regions for ADG (SSC1 and SSC12) and three for ADFI (SSC1). These regions were previously described in purebred pig populations; however, to our knowledge, this is the first study to confirm the relevance of these QTL regions in a crossbred pig population. The potential use of the SNPs and genes identified in this study in prediction models that combine genomic selection and marker-assisted selection should be evaluated for increasing the prediction accuracy of these traits in this population.     

Single step genome-wide association studies based on genotyping by sequence data reveals novel loci for the litter traits of domestic pigs

In this study, data genotyping by sequence (GBS) was used to perform single step GWAS (ssGWAS) to identify SNPs associated with the litter traits in domestic pigs and search for candidate genes in the region of significant SNPs. After quality control, 167,355 high-quality SNPs from 532 pigs were obtained. Phenotypic traits on 2112 gilt litters from 532 pigs were recorded including total number born (TNB), number born alive (NBA), and litter weight born alive (LWB). A single-step genomic BLUP approach (ssGBLUP) was used to implement the genome-wide association analysis at a 5% genome-wide significance level. A total of 8, 23 and 20 significant SNPs were associated with TNB, NBA, and LWB, respectively, and these significant SNPs accounted for 62.78%, 79.75%, and 58.79% of genetic variance. Furthermore, 1 (SSC14: 16314857), 4 (SSC1: 81986236, SSC1: 66599775, SSC1: 161999013, and SSC1: 267883107), and 5 (SSC9: 29030061, SSC2: 32368561, SSC5: 110375350, SSC13: 45619882 and SSC13: 45647829) significant SNPs for TNB, NBA, and LWB were inferred to be novel loci. At SSC1, the AIM1 and FOXO3 genes were found to be associated with NBA; these genes increase ovarian reproductive capacity and follicle number and decrease gonadotropin levels. The genes SLC36A4 and INTU are involved in cell growth, cytogenesis and development were found to be associated with LWB. These significant SNPs can be used as an indication for regions in the Sus scrofa genome for variability in litter traits, but further studies are expected to confirm causative mutations.     

A genome‐wide association study for a proxy of intermuscular fat level in the Italian Large White breed identifies genomic regions affecting an important quality parameter for dry‐cured hams

Intermuscular fat content in protected designations of origin dry‐cured hams is a very important meat quality trait that affects the acceptability of the product by the consumers. An excess in intermuscular fat (defined as the level of fat deposition between leg muscles) is a defect that depreciates the final product. In this study we carried out a genome‐wide association study for visible intermuscular fat (VIF) of hams in the Italian Large White pig breed. This trait was evaluated on the exposed muscles of green legs in 1122 performance‐tested gilts by trained personnel, according to a classification scale useful for routine and cheap evaluation. All animals were genotyped with the Illumina PorcineSNP60 BeadChip. The genome‐wide association study identified three QTL regions on porcine chromosome 1 (SSC1; accounting for ~79% of the SNPs below the 5.0E?04 threshold) and SSC2, two on SSC7 and one each on SSC3, SSC6, SSC9, SSC11, SSC13, SSC15, SSC16 and SSC17. The most significant SNP (ALGA0004143 on SSC1 at 77.3 Mb; P_FDR < 0.05), included in the largest QTL region which spanned about 6.8 Mb on SSC1, is located within the glutamate ionotropic receptor kainate type subunit 2 (GRIK2) gene. Functional annotation of all genes included in QTL regions for VIF suggested that intermuscular fat in the Italian Large White breed is a complex trait apparently influenced by complex biological mechanisms also involving obesity‐related processes. These QTL target mainly chromosome regions different from those affecting subcutaneous and intramuscular fat deposition.     

Genome-Wide Scan Reveals LEMD3 and WIF1 on SSC5 as the Candidates for Porcine Ear Size

The quantitative trait loci (QTL) for porcine ear size was previously reported to mainly focus on SSC5 and SSC7. Recently, a missense mutation, G32E, in PPARD in the QTL interval on SSC7 was identified as the causative mutation for ear size. However, on account of the large interval of QTL, the responsible gene on SSC5 has not been identified. In this study, an intercross population was constructed from the large-eared Minzhu, an indigenous Chinese pig breed, and the Western commercial Large White pig to examine the genetic basis of ear size diversity. A GWAS was performed to detect SNPs significantly associated with ear size. Thirty-five significant SNPs defined a 10.78-Mb (30.14–40.92 Mb) region on SSC5. Further, combining linkage disequilibrium and haplotype sharing analysis, a reduced region of 3.07-Mb was obtained. Finally, by using a selective sweep analysis, a critical region of about 450-kb interval containing two annotated genes LEMD3 and WIF1 was refined in this work. Functional analysis indicated that both represent biological candidates for porcine ear size, with potential application in breeding programs. The two genes could also be used as novel references for further study of the mechanism underlying human microtia.     

Genome-Wide Association Study Reveals Genetic Architecture of Eating Behavior in Pigs and Its Implications for Humans Obesity by Comparative Mapping

This study was aimed at identifying genomic regions controlling feeding behavior in Danish Duroc boars and its potential implications for eating behavior in humans. Data regarding individual daily feed intake (DFI), total daily time spent in feeder (TPD), number of daily visits to feeder (NVD), average duration of each visit (TPV), mean feed intake per visit (FPV) and mean feed intake rate (FR) were available for 1130 boars. All boars were genotyped using the Illumina Porcine SNP60 BeadChip. The association analyses were performed using the GenABEL package in the R program. Sixteen SNPs were found to have moderate genome-wide significance (p<5E-05) and 76 SNPs had suggestive (p<5E-04) association with feeding behavior traits. MSI2 gene on chromosome (SSC) 14 was very strongly associated with NVD. Thirty-six SNPs were located in genome regions where QTLs have previously been reported for behavior and/or feed intake traits in pigs. The regions: 64–65 Mb on SSC 1, 124–130 Mb on SSC 8, 63–68 Mb on SSC 11, 32–39 Mb and 59–60 Mb on SSC 12 harbored several signifcant SNPs. Synapse genes (GABRR2, PPP1R9B, SYT1, GABRR1, CADPS2, DLGAP2 and GOPC), dephosphorylation genes (PPM1E, DAPP1, PTPN18, PTPRZ1, PTPN4, MTMR4 and RNGTT) and positive regulation of peptide secretion genes (GHRH, NNAT and TCF7L2) were highly significantly associated with feeding behavior traits. This is the first GWAS to identify genetic variants and biological mechanisms for eating behavior in pigs and these results are important for genetic improvement of pig feed efficiency. We have also conducted pig-human comparative gene mapping to reveal key genomic regions and/or genes on the human genome that may influence eating behavior in human beings and consequently affect the development of obesity and metabolic syndrome. This is the first translational genomics study of its kind to report potential candidate genes for eating behavior in humans.     

Phylogeny of Dissimilatory Sulfite Reductases Supports an Early Origin of Sulfate Respiration

Microorganisms that use sulfate as a terminal electron acceptor for anaerobic respiration play a central role in the global sulfur cycle. Here, we report the results of comparative sequence analysis of dissimilatory sulfite reductase (DSR) genes from closely and distantly related sulfate-reducing organisms to infer the evolutionary history of DSR. A 1.9-kb DNA region encoding most of the α and β subunits of DSR could be recovered only from organisms capable of dissimilatory sulfate reduction with a PCR primer set targeting highly conserved regions in these genes. All DNA sequences obtained were highly similar to one another (49 to 89% identity), and their inferred evolutionary relationships were nearly identical to those inferred on the basis of 16S rRNA. We conclude that the high similarity of bacterial and archaeal DSRs reflects their common origin from a conserved DSR. This ancestral DSR was either present before the split between the domains Bacteria, Archaea, and Eucarya or laterally transferred between Bacteria and Archaea soon after domain divergence. Thus, if the physiological role of the DSR was constant over time, then early ancestors of Bacteria and Archaea already possessed a key enzyme of sulfate and sulfite respiration.     

Disentangling Two QTL on Porcine Chromosome 12 for Backfat Fatty Acid Composition

A previous study allowed the identification of two QTL regions at positions 11–34 cM (QTL1) and 68–76 cM (QTL2) on porcine chromosome SSC12 affecting several backfat fatty acids in an Iberian x Landrace F2 intercross. In the current study, different approaches were performed in order to better delimit the quoted QTL regions and analyze candidate genes. A new chromosome scan, using 81 SNPs selected from the Porcine 60KBeadChip and six previously genotyped microsatellites have refined the QTL positions. Three new functional candidate genes (ACOX1, ACLY, and SREBF1) have been characterized. Moreover, two putative promoters of porcine ACACA gene have also been investigated. New isoforms and 24 SNPs were detected in the four candidate genes, 19 of which were genotyped in the population. ACOX1 and ACLY SNPs failed to explain the effects of QTL1 on palmitic and gadoleic fatty acids. QTL2, affecting palmitoleic, stearic, and vaccenic fatty acids, maps close to the ACACA gene location. The most significant associations have been detected between one intronic (g.53840T > C) and one synonymous (c.5634T > C) ACACA SNPs and these fatty acids. Complementary analyses including ACACA gene expression quantification and association studies in other porcine genetic types do not support the expected causal effect of ACACA SNPs.     

Genome-Wide Association Studies Identify the Loci for 5 Exterior Traits in a Large White × Minzhu Pig Population

As one of the main breeding selection criteria, external appearance has special economic importance in the hog industry. In this study, an Illumina Porcine SNP60 BeadChip was used to conduct a genome-wide association study (GWAS) in 605 pigs of the F₂ generation derived from a Large White × Minzhu intercross. Traits under study were abdominal circumference (AC), body height (BH), body length (BL), cannon bone circumference (CBC), chest depth (CD), chest width (CW), rump circumference (RC), rump width (RW), scapula width (SW), and waist width (WW). A total of 138 SNPs (the most significant being MARC0033464) on chromosome 7 were found to be associated with BH, BL, CBC, and RC (P-value  = 4.15E-6). One SNP on chromosome 1 was found to be associated with CD at genome-wide significance levels. The percentage phenotypic variance of these significant SNPs ranged from 0.1–25.48%. Moreover, a conditional analysis revealed that the significant SNPs were derived from a single quantitative trait locus (QTL) and indicated additional chromosome-wide significant association for 25 SNPs on SSC4 (BL, CBC) and 9 SNPs on SSC7 (RC). Linkage analysis revealed two complete linkage disequilibrium haplotype blocks that contained seven and four SNPs, respectively. In block 1, the most significant SNP, MARC0033464, was present. Annotations from pig reference genome suggested six genes (GRM4, HMGA1, NUDT3, RPS10, SPDEF and PACSIN1) in block 1 (495 kb), and one gene (SCUBE3) in block 3 (124 kb). Functional analysis indicated that HMGA1 and SCUBE3 genes are the potential genes controlling BH, BL, and RC in pigs, with an application in breeding programs. We screened several candidate intervals and genes based on SNP location and gene function, and predicted their function using bioinformatics analyses.     

Genome-Wide Association for Growth Traits in Canchim Beef Cattle

Studies are being conducted on the applicability of genomic data to improve the accuracy of the selection process in livestock, and genome-wide association studies (GWAS) provide valuable information to enhance the understanding on the genetics of complex traits. The aim of this study was to identify genomic regions and genes that play roles in birth weight (BW), weaning weight adjusted for 210 days of age (WW), and long-yearling weight adjusted for 420 days of age (LYW) in Canchim cattle. GWAS were performed by means of the Generalized Quasi-Likelihood Score (GQLS) method using genotypes from the BovineHD BeadChip and estimated breeding values for BW, WW, and LYW. Data consisted of 285 animals from the Canchim breed and 114 from the MA genetic group (derived from crossings between Charolais sires and ½ Canchim + ½ Zebu dams). After applying a false discovery rate correction at a 10% significance level, a total of 4, 12, and 10 SNPs were significantly associated with BW, WW, and LYW, respectively. These SNPs were surveyed to their corresponding genes or to surrounding genes within a distance of 250 kb. The genes DPP6 (dipeptidyl-peptidase 6) and CLEC3B (C-type lectin domain family 3 member B) were highlighted, considering its functions on the development of the brain and skeletal system, respectively. The GQLS method identified regions on chromosome associated with birth weight, weaning weight, and long-yearling weight in Canchim and MA animals. New candidate regions for body weight traits were detected and some of them have interesting biological functions, of which most have not been previously reported. The observation of QTL reports for body weight traits, covering areas surrounding the genes (SNPs) herein identified provides more evidence for these associations. Future studies targeting these areas could provide further knowledge to uncover the genetic architecture underlying growth traits in Canchim cattle.     

Genes with expression levels correlating to drip loss prove association of their polymorphism with water holding capacity of pork

Six genes that were known to exhibit expression levels that are correlated to drip loss BVES, SLC3A2, ZDHHC5, CS, COQ9, and EGFR have been for candidate gene analysis. Based on in silico analysis SNPs were detected, confirmed by sequencing, and used for genotyping. The SNPs were genotyped in about 1,800 animals from six pig populations including commercial herds of Pietrain (PI) and German Landrace (DL), different commercial herds of Pietrain × (German Large White × German Landrace) (PIF1(a/b/c)), and one experimental F₂-population Duroc × Pietrain (DUPI). Comparative and genetic mapping established the location of BVES on SSC1, of SLC3A2 and ZDHHC5 on SSC2, of CS on SSC5, of COQ9 on SSC6 and of EGFR on SSC9, respectively, coinciding with QTL regions for carcass and meat quality traits. BVES, SLC3A2, and CS revealed association at least with drip loss and with several other measures of water holding capacity (WHC). Moreover, COQ9 and EGFR were associated with several meat quality traits such as meat color and/or thawing loss. This study reveals statistic evidence in addition to the functional relationship of these genes to WHC previously evidenced by expression analysis. This study reveals positional and genetic statistical evidence for a link of genetic variation at these loci or close to them and promotes those six candidate genes as functional and/or positional candidate genes for meat quality traits.     

Analysis of candidate genes underlying two epistatic quantitative trait loci on SSC12 affecting litter size in pig

The previous results from a genome scan for total number of piglets born and number of piglets born alive in a F₂ Iberian by Meishan intercross showed several single and epistatic QTL. One of the most interesting results was obtained for SSC12, where two QTL affecting both traits showed epistatic interaction. In this study, we proposed two genes ( SLC9A3R1 and NOS2 ) as biological and potentially positional candidates underlying these QTL. Both cDNAs were characterized and 23 polymorphisms were detected. A chromosome scan was conducted with 12 markers, plus one SNP in SLC9A3R1 and one in NOS2, covering 110 cM of SSC12. The epistatic QTL (QTL1 at 15 cM and QTL2 at 97 cM) were confirmed, and SLC9A3R1 and NOS2 were mapped around the QTL1 and QTL2 regions respectively. Several SNPs in both genes were tested with standard animal model and marker assisted association tests. The most significant results were obtained with the NOS2 haplotype defined by one missense SNP c.2192C > T (Val to Ala) and a 15 bp duplication at the 3'UTR. This duplication seems to include AU-rich elements, and could be a target site for miRNA, therefore there are statistical and biological indications to consider this haplotype as the potential causal mutation underlying QTL2. SLC9A3R1 results were not conclusive. Although the interaction between the SNPs was not significant, we cannot reject the possibility of interaction of the NOS2 haplotype with other polymorphisms closely linked to the SL9A3R1 SNPs analysed.     

Detection of quantitative trait loci for carcass composition traits in pigs

A quantitative trait locus (QTL) analysis of carcass composition data from a three-generation experimental cross between Meishan (MS) and Large White (LW) pig breeds is presented. A total of 488 F2 males issued from six F1 boars and 23 F1 sows, the progeny of six LW boars and six MS sows, were slaughtered at approximately 80 kg live weight and were submitted to a standardised cutting of the carcass. Fifteen traits, i.e. dressing percentage, loin, ham, shoulder, belly, backfat, leaf fat, feet and head weights, two backfat thickness and one muscle depth measurements, ham + loin and back + leaf fat percentages and estimated carcass lean content were analysed. Animals were typed for a total of 137 markers covering the entire porcine genome. Analyses were performed using a line-cross (LC) regression method where founder lines were assumed to be fixed for different QTL alleles and a half/full sib (HFS) maximum likelihood method where allele substitution effects were estimated within each half-/full-sib family. Additional analyses were performed to search for multiple linked QTL and imprinting effects. Significant gene effects were evidenced for both leanness and fatness traits in the telomeric regions of SSC 1q and SSC 2p, on SSC 4, SSC 7 and SSC X. Additional significant QTL were identified for ham weight on SSC 5, for head weight on SSC 1 and SSC 7, for feet weight on SSC 7 and for dressing percentage on SSC X. LW alleles were associated with a higher lean content and a lower fat content of the carcass, except for the fatness trait on SSC 7. Suggestive evidence of linked QTL on SSC 7 and of imprinting effects on SSC 6, SSC 7, SSC 9 and SSC 17 were also obtained.     

Genome-wide association analyses for meat quality traits in Chinese Erhualian pigs and a Western Duroc?×?(Landrace × Yorkshire) commercial population

Background

Understanding the genetic mechanisms that underlie meat quality traits is essential to improve pork quality. To date, most quantitative trait loci (QTL) analyses have been performed on F₂ crosses between outbred pig strains and have led to the identification of numerous QTL. However, because linkage disequilibrium is high in such crosses, QTL mapping precision is unsatisfactory and only a few QTL have been found to segregate within outbred strains, which limits their use to improve animal performance. To detect QTL in outbred pig populations of Chinese and Western origins, we performed genome-wide association studies (GWAS) for meat quality traits in Chinese purebred Erhualian pigs and a Western Duroc × (Landrace × Yorkshire) (DLY) commercial population.

Methods

Three hundred and thirty six Chinese Erhualian and 610 DLY pigs were genotyped using the Illumina PorcineSNP60K Beadchip and evaluated for 20 meat quality traits. After quality control, 35 985 and 56 216 single nucleotide polymorphisms (SNPs) were available for the Chinese Erhualian and DLY datasets, respectively, and were used to perform two separate GWAS. We also performed a meta-analysis that combined P-values and effects of 29 516 SNPs that were common to Erhualian, DLY, F₂ and Sutai pig populations.

Results

We detected 28 and nine suggestive SNPs that surpassed the significance level for meat quality in Erhualian and DLY pigs, respectively. Among these SNPs, ss131261254 on pig chromosome 4 (SSC4) was the most significant (P = 7.97E-09) and was associated with drip loss in Erhualian pigs. Our results suggested that at least two QTL on SSC12 and on SSC15 may have pleiotropic effects on several related traits. All the QTL that were detected by GWAS were population-specific, including 12 novel regions. However, the meta-analysis revealed seven novel QTL for meat characteristics, which suggests the existence of common underlying variants that may differ in frequency across populations. These QTL regions contain several relevant candidate genes.

Conclusions

These findings provide valuable insights into the molecular basis of convergent evolution of meat quality traits in Chinese and Western breeds that show divergent phenotypes. They may contribute to genetic improvement of purebreds for crossbred performance.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0120-x) contains supplementary material, which is available to authorized users.     

A genome‐wide association study to detect genetic variation for postpartum dysgalactia syndrome in five commercial pig breeding lines

Postpartum dysgalactia syndrome (PDS) in sows is an important disease after parturition with a relevant economic impact, affecting the health and welfare of both sows and piglets. The genetic background of this disease has been discussed and its heritability estimated, but further genetic analyses are lacking in detail. The aim of the current study was to detect loci affecting the susceptibility to PDS through a genome‐wide association approach. The study was designed as a family‐based association study with matched sampling of affected sows and healthy half‐ or full‐sib control sows on six farms. For the study, 597 sows (322 affected vs. 275 healthy control sows) were genotyped on 62 163 single nucleotide polymorphisms (SNPs) using the Illumina PorcineSNP60 BeadChip. After quality control, 585 sows (314 affected vs. 271 healthy control sows) and 49 740 SNPs remained for further analysis. Statistics were performed mainly with the r package genabel and included a principal component analysis. A statistically significant genome‐wide associated SNP was identified on porcine chromosome (SSC) 17. Further promising results with moderate significance were detected on SSC 13 and on an unplaced scaffold with an older annotation on SSC 15. The PRICKLE2 and NRP2 genes were identified as candidate genes near associated SNPs. Several quantitative trait loci (QTL) have been previously described in these genomic regions, including QTL for mammary gland condition, as teat number and non‐functional nipples QTL, as well as QTL for body temperature and gestation length.     

Genetic Dissection of Photoperiod Response Based on GWAS of Pre-Anthesis Phase Duration in Spring Barley

Heading time is a complex trait, and natural variation in photoperiod responses is a major factor controlling time to heading, adaptation and grain yield. In barley, previous heading time studies have been mainly conducted under field conditions to measure total days to heading. We followed a novel approach and studied the natural variation of time to heading in a world-wide spring barley collection (218 accessions), comprising of 95 photoperiod-sensitive (Ppd-H1) and 123 accessions with reduced photoperiod sensitivity (ppd-H1) to long-day (LD) through dissecting pre-anthesis development into four major stages and sub-phases. The study was conducted under greenhouse (GH) conditions (LD; 16/8 h; ∼20/∼16°C day/night). Genotyping was performed using a genome-wide high density 9K single nucleotide polymorphisms (SNPs) chip which assayed 7842 SNPs. We used the barley physical map to identify candidate genes underlying genome-wide association scans (GWAS). GWAS for pre-anthesis stages/sub-phases in each photoperiod group provided great power for partitioning genetic effects on floral initiation and heading time. In addition to major genes known to regulate heading time under field conditions, several novel QTL with medium to high effects, including new QTL having major effects on developmental stages/sub-phases were found to be associated in this study. For example, highly associated SNPs tagged the physical regions around HvCO1 (barley CONSTANS1) and BFL (BARLEY FLORICAULA/LEAFY) genes. Based upon our GWAS analysis, we propose a new genetic network model for each photoperiod group, which includes several newly identified genes, such as several HvCO-like genes, belonging to different heading time pathways in barley.     

A genome‐wide association analysis for carcass traits in a commercial Duroc pig population

We performed a genome‐wide association study to map the genetic determinants of carcass traits in 350 Duroc pigs typed with the Porcine SNP60 BeadChip. Association analyses were carried out using the gemma software. The proportion of phenotypic variance explained by the SNPs ranged between negligible to moderate (= 0.01–0.30) depending on the trait under consideration. At the genome‐wide level, we detected one significant association between backfat thickness between the 3^rd and 4^th ribs and six SNPs mapping to SSC12 (37–40 Mb). We also identified several chromosome‐wide significant associations for ham weight (SSC11: 51–53 Mb, three SNPs; 67–68 Mb, two SNPs), carcass weight (SSC11: 66–68 Mb, two SNPs), backfat thickness between the 3^rd and 4^th ribs (SSC12: 21 Mb, one SNP; 33–40 Mb, 17 SNPs; 51–58 Mb, two SNPs), backfat thickness in the last rib (SSC12: 37 Mb, one SNP; 40–41 Mb, nine SNPs) and lean meat content (SSC13: 34 Mb, three SNPs and SSC16: 45.1 Mb, one SNP; 62–63 Mb, 10 SNPs; 71–75 Mb, nine SNPs). The ham weight trait‐associated region on SSC11 contains two genes (UCHL3 and LMO7) related to muscle development. In addition, the ACACA gene, which encodes an enzyme for the catalysis of fatty acid synthesis, maps to the SSC12 (37–41 Mb) region harbouring trait‐associated regions for backfat thickness traits. Sequencing of these candidate genes may help to uncover the causal mutations responsible for the associations found in the present study.     

Genome-wide QTL analysis of meat quality-related traits in a large F2 intercross between Landrace and Korean native pigs

Background

We conducted a genome-wide linkage analysis to identify quantitative trait loci (QTL) that influence meat quality-related traits in a large F₂ intercross between Landrace and Korean native pigs. Thirteen meat quality-related traits of the m. longissimus lumborum et thoracis were measured in more than 830 F₂ progeny. All these animals were genotyped with 173 microsatellite markers located throughout the pig genome, and the GridQTL program based on the least squares regression model was used to perform the QTL analysis.

Results

We identified 23 genome-wide significant QTL in eight chromosome regions (SSC1, 2, 6, 7, 9, 12, 13, and 16) (SSC for Sus Scrofa) and detected 51 suggestive QTL in the 17 chromosome regions. QTL that affect 10 meat quality traits were detected on SSC12 and were highly significant at the genome-wide level. In particular, the QTL with the largest effect affected crude fat percentage and explained 22.5% of the phenotypic variance (F-ratio = 278.0 under the additive model, nominal P = 5.5 × 10⁻⁵⁵). Interestingly, the QTL on SSC12 that influenced meat quality traits showed an obvious trend for co-localization.

Conclusions

Our results confirm several previously reported QTL. In addition, we identified novel QTL for meat quality traits, which together with the associated positional candidate genes improve the knowledge on the genetic structure that underlies genetic variation for meat quality traits in pigs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-014-0080-6) contains supplementary material, which is available to authorized users.     

Association analysis for udder health based on SNP-panel and sequence data in Danish Holsteins

Background

The sensitivity of genome-wide association studies for the detection of quantitative trait loci (QTL) depends on the density of markers examined and the statistical models used. This study compares the performance of three marker densities to refine six previously detected QTL regions for mastitis traits: 54 k markers of a medium-density SNP (single nucleotide polymorphism) chip (MD), imputed 777 k markers of a high-density SNP chip (HD), and imputed whole-genome sequencing data (SEQ). Each dataset contained data for 4496 Danish Holstein cattle. Comparisons were performed using a linear mixed model (LM) and a Bayesian variable selection model (BVS).

Results

After quality control, 587, 7825, and 78 856 SNPs in the six targeted regions remained for MD, HD, and SEQ data, respectively. In general, the association patterns between SNPs and traits were similar for the three marker densities when tested using the same statistical model. With the LM model, 120 (MD), 967 (HD), and 7209 (SEQ) SNPs were significantly associated with mastitis, whereas with the BVS model, 43 (MD), 131 (HD), and 1052 (SEQ) significant SNPs (Bayes factor > 3.2) were observed. A total of 26 (MD), 75 (HD), and 465 (SEQ) significant SNPs were identified by both models. In addition, one, 16, and 33 QTL peaks for MD, HD, and SEQ data were detected according to the QTL intensity profile of SNP bins by post-analysis of the BVS model.

Conclusions

The power to detect significant associations increased with increasing marker density. The BVS model resulted in clearer boundaries between linked QTL than the LM model. Using SEQ data, the six targeted regions were refined to 33 candidate QTL regions for udder health. The comparison between these candidate QTL regions and known genes suggested that NPFFR2, SLC4A4, DCK, LIFR, and EDN3 may be considered as candidate genes for mastitis susceptibility.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0129-1) contains supplementary material, which is available to authorized users.