Three novel quantitative trait loci for skin thickness in swine identified by linkage and genome‐wide association studies

Skin is the largest organ in the pig body and plays a key role in protecting the body against pathogens and excessive water loss. Deciphering the genetic basis of swine skin thickness would enrich our knowledge about the skin. To identify the loci for porcine skin thickness, we first performed a genome scan with 194 microsatellite markers in a White Duroc × Erhualian F₂ intercross. We identified three genome‐wide significant QTL on pig chromosomes (SSC) 4, 7 and 15 using linkage analysis. The most significant QTL was found on SSC7 with a small confidence interval of ~5 cM, explaining 23.9 percent of phenotypic variance. Further, we conducted a genome‐wide association study (GWAS) using Illumina PorcineSNP60 Beadchips for the F₂ pedigree and a population of Chinese Sutai pigs. We confirmed significant QTL in the F₂ pedigree and replicated QTL on SSC15 in Chinese Sutai pigs. A meta‐analysis of GWASs on both populations detected a genomic region associated with skin thickness on SSC4. GWAS results were generally consistent with QTL mapping. Identical‐by‐descent analysis defined QTL on SSC7 in a 683‐kb region harboring an interesting candidate gene: HMGA1. On SSC15, the linkage disequilibrium analysis showed a haplotype block of 2.20 Mb that likely harbors the gene responsible for skin thickness. Our findings provide novel insights into the genetic basis of swine skin thickness, which would benefit further understanding of porcine skin function.     

Genome-wide association study using deregressed breeding values for cryptorchidism and scrotal/inguinal hernia in two pig lines

Background

Cryptorchidism and scrotal/inguinal hernia are the most frequent congenital defects in pigs. Identification of genomic regions that control these congenital defects is of great interest to breeding programs, both from an animal welfare point of view as well as for economic reasons. The aim of this genome-wide association study (GWAS) was to identify single nucleotide polymorphisms (SNPs) that are strongly associated with these congenital defects. Genotypes were available for 2570 Large White (LW) and 2272 Landrace (LR) pigs. Breeding values were estimated based on 1 359 765 purebred and crossbred male offspring, using a binary trait animal model. Estimated breeding values were deregressed (DEBV) and taken as the response variable in the GWAS.

Results

Heritability estimates were equal to 0.26 ± 0.02 for cryptorchidism and to 0.31 ± 0.01 for scrotal/inguinal hernia. Seven and 31 distinct QTL regions were associated with cryptorchidism in the LW and LR datasets, respectively. The top SNP per region explained between 0.96% and 1.10% and between 0.48% and 2.77% of the total variance of cryptorchidism incidence in the LW and LR populations, respectively. Five distinct QTL regions associated with scrotal/inguinal hernia were detected in both LW and LR datasets. The top SNP per region explained between 1.22% and 1.60% and between 1.15% and 1.46% of the total variance of scrotal/inguinal hernia incidence in the LW and LR populations, respectively. For each trait, we identified one overlapping region between the LW and LR datasets, i.e. a region on SSC8 (Sus scrofa chromosome) between 65 and 73 Mb for cryptorchidism and a region on SSC13 between 34 and 37 Mb for scrotal/inguinal hernia.

Conclusions

The use of DEBV in combination with a binary trait model was a powerful approach to detect regions associated with difficult traits such as cryptorchidism and scrotal/inguinal hernia that have a low incidence and for which affected animals are generally not available for genotyping. Several novel QTL regions were detected for cryptorchidism and scrotal/inguinal hernia, and for several previously known QTL regions, the confidence interval was narrowed down.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0096-6) contains supplementary material, which is available to authorized users.     

Mapping and fine mapping of quantitative trait loci for the number of vertebrae in a White Duroc × Chinese Erhualian intercross resource population

The number of vertebrae is associated with body size and meat production in pigs. To identify quantitative trait loci (QTL) for the number of vertebrae, phenotypic values were measured in 1029 individuals from a White Duroc × Chinese Erhualian intercross F₂ population. A whole genome scan was performed with 194 microsatellite markers in the F₂ population. Four genome‐wide significant QTL and eight chromosome‐wide significant QTL for the number of vertebrae were identified on pig chromosomes (SSC) 1, 2, 6, 7, 10 and 12. The most significant QTL was detected on SSC7 with a confidence interval of 1 cM, explaining 42.32% of the phenotypic variance in the thoracic vertebral number. The significant QTL on SSC1, 2 and 7 confirmed previous reports. A panel of 276 animals representing seven Western and Chinese breeds was genotyped with 34 microsatellite markers in the SSC7 QTL region. No obvious selective sweep effect was observed in the tested breeds, indicating that intensive selection for enlarged body size in Western commercial breeds did not wipe out the genetic variability in the QTL region. The Q alleles for increased vertebral number originated from both Chinese Erhualian and White Duroc founder animals. A haplotype block of approximately 900 kb was found to be shared by all Q‐bearing chromosomes of F₁ sires except for one distinct Q chromosome. The critical region harbours the newly reported VRTN gene associated with vertebral number. Further investigations are required to confirm whether VRTN or two other positional candidate genes, PROX2 and FOS, cause the QTL effect.     

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.     

Detection of quantitative trait loci for teat number and female reproductive traits in Meishan × Large White F2 pigs

A quantitative trait locus (QTL) analysis of female reproductive data from a three-generation experimental cross between Meishan (MS) and Large White (LW) pig breeds is presented. Six F1 boars and 23 F1 sows, progeny of six LW boars and six MS sows, produced 573 F2 females and 530 F2 males. Six traits, i.e. teat number (TN), age at puberty (AP), ovulation rate (OR), weight at mating (WTM), number of viable embryos (NVE) and embryo survival (ES) at 30 days of gestation were analysed. Animals were genotyped for a total of 137 markers covering the entire porcine genome. Analyses were carried out based on interval mapping methods, using a line-cross (LC) regression and a half-full sib (HFS) maximum likelihood test. Genome-wide (GW) highly significant (P < 0.001) QTL were detected for WTM on SSC 7 and for AP on SSC 13. They explained, respectively, 14.5% and 8.9% of the trait phenotypic variance. Other GW significant (P < 0.05) QTL were detected for TN on SSC 3, 7, 8, 16 and 17, for OR on SSC 4 and 5, and for ES on SSC 9. Two additional chromosome-wide significant (P < 0.05) QTL were detected for TN, three for WTM, four for AP, three for OR, three for NVE and two for ES. With the exception of the two above-mentioned loci, the QTL explained from 1.2% to 4.6% of trait phenotypic variance. QTL alleles were in most cases not fixed in the grand-parental populations and Meishan alleles were not systematically associated with higher reproductive performance.     

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 association study identifies quantitative trait loci affecting hematological traits in an F2 intercross between Landrace and Korean native pigs

Changes affecting the status of health and robustness can bring about physiological alterations including hematological parameters in swine. To identify quantitative trait loci (QTL) associated with eight hematological traits (one leukocyte trait, six erythrocyte traits and one platelet trait), we conducted a genome‐wide association study using the PorcineSNP60K BeadChip in a resource population derived from an intercross between Landrace and Korean native pigs. A total of 36 740 SNPs from 816 F₂ progeny were analyzed for each blood‐related trait after filtering for quality control. Data were analyzed by the genome‐wide rapid association using mixed model and regression (GRAMMAR) approach. A total of 257 significant SNPs (P < 1.36 × 10^?6) on SSC3, 6, 8, 13 and 17 were identified for blood‐related traits in this study. Interestingly, the genomic region between 17.9 and 130 Mb on SSC8 was found to be significantly associated with red blood cell, mean corpuscular volume and mean corpuscular hemoglobin. Our results include the identification of five significant SNPs within five candidate genes (KIT, IL15, TXK, ARAP2 and ERG) for hematopoiesis. Further validation of these identified SNPs could give valuable information for understanding the variation of hematological traits in pigs.     

Genome‐wide association study for body weight in cattle populations from Siberia

Body weight is a complex trait in cattle associated with commonly used commercial breeding measurements related to growth. Although many quantitative trait loci (QTL) for body weight have been identified in cattle so far, searching for genetic determinants in different breeds or environments is promising. Therefore, we carried out a genome‐wide association study (GWAS) in two cattle populations from the Russian Federation (Siberian region) using the GGP HD150K array containing 139 376 single nucleotide polymorphism (SNP) markers. Association tests for 107 550 SNPs left after filtering revealed five statistically significant SNPs on BTA5, considering a false discovery rate of less than 0.05. The chromosomal region containing these five SNPs contains the CCND2 gene, which was previously associated with average daily weight gain and body mass index in US beef cattle populations and in humans respectively. Our study is the first GWAS for body weight in beef cattle populations from the Russian Federation. The results provided here suggest that, despite the existence of breed‐ and species‐specific QTL, the genetic architecture of body weight could be evolutionarily conserved in mammals.     

Genomic regions affecting backfat thickness and cannon bone circumference identified by genome‐wide association study in a Duroc pig population

We performed a genome‐wide association study using the porcine 60K SNP array to detect QTL regions for nine traits in a three‐generational Duroc samples (n = 651), viz. generations 1, 2 and 3 from a population selected over five generations using a closed nucleus breeding scheme. We applied a linear mixed model for association mapping to detect SNP effects, adjusting for fixed effects (sex and season) and random polygenic effects (reflecting genetic relatedness), and derived a likelihood ratio statistic for each SNP using the efficient mixed‐model association method. We detected a region on SSC6 for backfat thickness (BFT) and on SSC7 for cannon bone circumference (CANNON), with a genome‐wide significance of P < 0.01 after Bonferroni correction. These regions had been detected previously in other pig populations. Six genes are located in the BFT‐associated region, while the CANNON‐associated region includes 66 genes. In the future, significantly associated SNPs, derived by sequencing the coding regions of the six genes in the BFT region, can be used in marker‐assisted selection of BFT, whereas haplotypes constructed from the SSC7 region with strong LD can be used to select for the CANNON trait in our resource family.     

Identification of genes related to intramuscular fat independent of backfat thickness in Duroc pigs using single‐step genome‐wide association

Intramuscular fat (IMF) is an important meat‐quality trait of pigs, which influences pork’s shearing force, hydraulics, tenderness and juicy flavor. However, to achieve a higher percentage of lean meat, pigs with lower backfat thickness (BF) are intensively selected for, which may lead to a reduction in pork quality. Therefore, the objective of this study was to locate loci that affect IMF without changing BF. A single‐step GWAS was performed on 950 Duroc pigs genotyped by a 50K SNP chip in order to detect genomic variants relevant to IMF and BF. The significant SNPs detected were afterwards divided into a BF subset (seven SNPs), an IMF subset (11 SNPs) and a subset of both traits (12 SNPs), according to their P‐value and LD. After SNP and QTL annotation, our results indicated that SSC1: 167938652, 166363826, 164829874 and 167171587 might be associated with IMF without changing BF. In the subset of both traits, we found that the combined effect of ALGA0006602 (SSC1: 159538854) and 12784636 (SSC1: 160773437) might improve the IMF without changing BF. Our gene annotation result showed that TLE3, ITGA11, SMAD6, PAQR5 and [RNF152^A/G × MC4R^A/A] genes might affect IMF independently of BF. We believe that the SNPs and genes identified in this study will be valuable for the future molecular breeding of IMF in Duroc pigs.     

SNPs in the porcine GOT1 gene improve a QTL for serum aspartate aminotransferase activity on SSC14

Clinical–chemical traits are essential parameters to quantify the health status of individuals and herds, but the knowledge about their genetic architecture is sparse, especially in swine. We have recently described three QTL for serum aspartate aminotransferase activity (sAST), and one of these maps to a region on SSC14 where the aspartate aminotransferase coding gene GOT1 is located. This QTL was only apparent under the acute burden of a model disease. The aim of the present study was to characterize GOT1 as a candidate gene and to test the effects of different GOT1 SNPs as potential quantitative trait nucleotides (QTNs) for sAST. Nine SNPs within GOT1 were identified, and SNP c.‐793C>G significantly increased the QTL effects and narrowed the confidence interval from 90 to 15 cM. Additionally, we found a significant association of SNP c.‐793C>G in a commercial outbred line, but with reversed phase. We conclude that GOT1 is a putative candidate gene for the sAST QTL on SSC14, and that SNP c.‐793C>G is close to the responsible QTN.     

Identification of new single nucleotide polymorphisms affecting total number born and candidate genes related to ovulation rate in Chinese Erhualian pigs

The Chinese Erhualian pig has the highest record for litter size in the world. However, the genetic mechanism of its high prolificacy remains poorly understood. In our study, large phenotypic variations in litter size were found among Erhualian sows. Significant differences in total number born (TNB) and corpora lutea numbers were observed between sows with high and low estimated breeding values (EBVs) for TNB. To identify single nucleotide polymorphisms (SNPs) associated with TNB, a selective genomic scan was conducted on 18 sows representing the top 10% and 18 sows representing the bottom 10% of EBVs of 177 sows using Illumina Porcine SNP60 genotype data. Genome‐wide fixation coefficient (F_ST) values were calculated for each SNP between the high‐ and low‐EBV groups. A total of 154 SNPs were significantly differentiated loci between the two groups. Of the top 10 highest F_ST SNPs, rs81399474, rs81400131 and rs81405013 on SSC8 and rs81434499 and rs81434489 on SSC 12 corresponded to previously reported QTL for litter size. The other five SNPs, rs81367039 on SSC2, rs80891106 on SSC7, rs81477883 on SSC12 and rs80938898 and rs80971725 on SSC14, appeared to be novel QTL for TNB. Significant associations between rs81399474 on SSC8 and TNB were confirmed in 313 Erhualian sows. Forty genes were identified around the top 10 highest F_ST SNPs, of which UCHL1, adjacent to rs81399474, and RPS6KB1 and CLTC, adjacent to rs81434499, have been reported to affect the ovulation rate in pig. The findings can advance understanding of the genetic variations in litter size of pigs.     

A genome‐wide linkage analysis for reproductive traits in F2 Large White × Meishan cross gilts

Female reproductive performance traits in pigs have low heritabilities thus limiting improvement through traditional selective breeding programmes. However, there is substantial genetic variation found between pig breeds with the Chinese Meishan being one of the most prolific pig breeds known. In this study, three cohorts of Large White × Meishan F₂ cross‐bred pigs were analysed to identify quantitative trait loci (QTL) with effects on reproductive traits, including ovulation rate, teat number, litter size, total born alive and prenatal survival. A total of 307 individuals were genotyped for 174 genetic markers across the genome. The genome‐wide analysis of the trait‐recorded F₂ gilts in their first parity/litter revealed one QTL for teat number significant at the genome level and a total of 12 QTL, which are significant at the chromosome‐wide level, for: litter size (three QTL), total born alive (two QTL), ovulation rate (four QTL), prenatal survival (one QTL) and teat number (two QTL). Further support for eight of these QTL is provided by results from other studies. Four of these 12 QTL were mapped for the first time in this study: on SSC15 for ovulation rate and on SSC18 for teat number, ovulation rate and litter size.     

QTL analysis of white blood cell, platelet and red blood cell-related traits in an F2 intercross between Landrace and Korean native pigs

Haematological traits play important roles in disease resistance and defence functions. The objective of this study was to locate quantitative trait loci (QTL) and the associated positional candidate genes influencing haematological traits in an F₂ intercross between Landrace and Korean native pigs. Eight blood‐related traits (six erythrocyte traits, one leucocyte trait and one platelet trait) were measured in 816 F₂ progeny. All experimental animals were genotyped with 173 informative microsatellite markers located throughout the pig genome. We report that nine chromosomes harboured QTL for the baseline blood parameters: genomic regions on SSC 1, 4, 5, 6, 8, 9, 11, 13 and 17. Eight of twenty identified QTL reached genome‐wide significance. In addition, we evaluated the KIT locus, an obvious candidate gene locus affecting variation in blood‐related traits. Using dense single nucleotide polymorphism marker data on SSC 8 and the marker‐assisted association test, the strong association of the KIT locus with blood phenotypes was confirmed. In conclusion, our study identified both previously reported and novel QTL affecting baseline haematological parameters in pigs. Additionally, the positional candidate genes identified here could play an important role in elucidating the genetic architecture of haematological phenotype variation in swine and in humans.     

Genome‐wide association study for reproductive traits in a Large White pig population

Using the PorcineSNP80 BeadChip, we performed a genome‐wide association study for seven reproductive traits, including total number born, number born alive, litter birth weight, average birth weight, gestation length, age at first service and age at first farrowing, in a population of 1207 Large White pigs. In total, we detected 12 genome‐wide significant and 41 suggestive significant SNPs associated with six reproductive traits. The proportion of phenotypic variance explained by all significant SNPs for each trait ranged from 4.46% (number born alive) to 11.49% (gestation length). Among them, 29 significant SNPs were located within known QTL regions for swine reproductive traits, such as corpus luteum number, stillborn number and litter size, of which one QTL region associated with litter size contained the ALGA0098819 SNP for total number born. Subsequently, we found that 376 functional genes contained or were near these significant SNPs. Of these, 14 genes—BHLHA15, OCM2, IL1B2, GCK, SMAD2, HABP2, PAQR5, GRB10, PRELID2, DMKN, GPI, GPIHBP1, ADCY2 and ACVR2B—were considered important candidates for swine reproductive traits based on their critical roles in embryonic development, energy metabolism and growth development. Our findings contribute to the understanding of the genetic mechanisms for reproductive traits and could have a positive effect on pig breeding programs.     

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.     

Genome-wide association analysis of meat quality traits in a porcine Large White × Minzhu intercross population

Pork quality is an economically important trait and one of the main selection criteria for breeding in the swine industry. In this genome-wide association study (GWAS), 455 pigs from a porcine Large White × Minzhu intercross population were genotyped using the Illumina PorcineSNP60K Beadchip, and phenotyped for intramuscular fat content (IMF), marbling, moisture, color L*, color a*, color b* and color score in the longissimus muscle (LM). Association tests between each trait and the SNPs were performed via the Genome Wide Rapid Association using the Mixed Model and Regression-Genomic Control (GRAMMAR-GC) approach. From the Ensembl porcine database, SNP annotation was implemented using Sus scrofa Build 9. A total of 45 SNPs showed significant association with one or multiple meat quality traits. Of the 45 SNPs, 36 were located on SSC12. These significantly associated SNPs aligned to or were in close approximation to previously reported quantitative trait loci (QTL) and some were located within introns of previously reported candidate genes. Two haplotype blocks ASGA0100525-ASGA0055225-ALGA0067099-MARC0004712-DIAS0000861, and ASGA0085522-H3GA0056170 were detected in the significant region. The first block contained the genes MYH1, MYH2 and MYH4. A SNP (ASGA0094812) within an intron of the USP43 gene was significantly associated with five meat quality traits. The present results effectively narrowed down the associated regions compared to previous QTL studies and revealed haplotypes and candidate genes on SSC12 for meat quality traits in pigs.     

猪部分内脏器官性状和乳头数的QTL检测

对内脏器官重量性状的QTL定位研究,所见报道不多;对于猪的繁殖性状,尚需做进一步的探讨。本研究在总共214头(180头F2个体)组成的资源家系中,在猪的SSC4、SSC6、SSC7、SSC8 和 SSC13上共选取39个微卫星标记,检测了8种内脏器官的重量性状:心重 (HW)、肺重 (LW)、肝 胆重 (LGW)、脾重 (SPW)、胃重 (STW)、小肠重(SIW)、大肠重(LIW) 和肾重(KW);其他一些胴体性状:胴体长性状1(自第一颈椎,CL1)、胴体长性状2(自第一胸椎,CL2)、肋骨数(RNS)和繁殖性状乳头数(TNS)的QTL定位。结果表明,检测到3个染色体极显著水平的QTL(P≤0.01),它们是HW QTL定位在SSC6上30 cM处,RNS QTL定位在SSC7上115 cM处和TNS QTL定位在SSC7上 110 cM处;另外6个染色体显著水平的QTL(P≤0.05)是:LW(SSC13上119 cM处)、LGW(SSC6上94 cM处)、SPW(SSC8上106 cM处)、SIW(SSC 4上0 cM处)、LIW(SSC 4上170 cM 处)和TNS(SSC 6上95 cM处)。上述QTL解释的表型变异从 0.04% 到 14.06%,有些位点的 QTL 可以解释表型变异的 10%以上,如 HW 的 QTL 解释表型变异的9.52%、SIW的QTL解释表型变异的13.47%、定位在SSC6上的TNS QTL解释表型变异的14.06%,而定位在 SSC7上的TNS QTL解释表型变异的11.30%。多数内脏器官重量性状的QTL定位结果未见报道。胴体长未见显著水平的QTL,而在SSC7上定位染色体极显著水平的肋骨数QTL。     

QTL analysis of body weight and carcass body length traits in an F2 intercross between Landrace and Korean native pigs

Growth traits, such as body weight and carcass body length, directly affect productivity and economic efficiency in the livestock industry. We performed a genome‐wide linkage analysis to detect the quantitative trait loci (QTL) that affect body weight, growth curve parameters and carcass body length in an F₂ intercross between Landrace and Korean native pigs. Eight phenotypes related to growth were measured in approximately 1000 F₂ progeny. All experimental animals were subjected to genotypic analysis using 173 microsatellite markers located throughout the pig genome. The least squares regression approach was used to conduct the QTL analysis. For body weight traits, we mapped 16 genome‐wide significant QTL on SSC1, 3, 5, 6, 8, 9 and 12 as well as 22 suggestive QTL on SSC2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 16 and 17. On SSC12, we identified a major QTL affecting body weight at 140 days of age that accounted for 4.3% of the phenotypic variance, which was the highest test statistic (F‐ratio = 45.6 under the additive model, nominal P = 2.4 × 10^?11) observed in this study. We also showed that there were significant QTL on SSC2, 5, 7, 8, 9 and 12 affecting carcass body length and growth curve parameters. Interestingly, the QTL on SSC2, 3, 5, 6, 8, 9, 10, 12 and 17 influencing the growth‐related traits showed an obvious trend for co‐localization. In conclusion, the identified QTL may play an important role in investigating the genetic structure underlying the phenotypic variation of growth in pigs.     

Detecting QTL for feed intake traits and other performance traits in growing pigs in a Piétrain-Large White backcross

Knowing the large difference in daily feed intake (DFI) between Large White (LW) and Piétrain (PI) growing pigs, a backcross (BC) population has been set up to map QTL that could be used in marker assisted selection strategies. LW × PI boars were mated with sows from two LW lines to produce 16 sire families. A total of 717 BC progeny were fed ad libitum from 30 to 108 kg BW using single-place electronic feeders. A genome scan was conducted using genotypes for the halothane gene and 118 microsatellite markers spread on the 18 porcine autosomes. Interval mapping analyses were carried out, assuming different QTL alleles between sire families to account for within breed variability using the QTLMap software. The effects of the halothane genotype and of the dam line on the QTL effect estimates were tested. One QTL for DFI (P < 0.05 at the chromosome-wide (CW) level) and one QTL for feed conversion ratio (P < 0.01 at the CW level) were mapped to chromosomes SSC6 - probably due to the halothane alleles - and SSC7, respectively. Three putative QTL for feed intake traits were detected (P < 0.06 at the CW level) on SSC2, SSC7 and SSC9. QTL on feeding traits had effects in the range of 0.20 phenotypic s.d. The relatively low number of QTL detected for these traits suggests a large QTL allele variability within breeds and/or low effects of individual loci. Significant QTL were detected for traits related to carcass composition on chromosomes SSC6, SSC15 and SSC17, and to meat quality on chromosome SSC6 (P < 0.01 at the genome-wide level). QTL effects for body composition on SSC13 and SSC17 differed according to the LW dam line, which confirmed that QTL alleles were segregating in the LW breed. An epistatic effect involving the halothane locus and a QTL for loin weight on SSC7 was identified, the estimated substitution effects for the QTL differing by 200 g between Nn and NN individuals. The interactions between QTL alleles and genetic background or particular genes suggest further work to validate QTL segregations in the populations where marker assisted selection for the QTL would be applied.