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.     

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.     

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.     

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.     

Polymorphisms on SSC15q21-q26 Containing QTL for reproduction in Swine and its association with litter size

Several quantitative trait loci (QTL) for important reproductive traits (ovulation rate) have been identified on the porcine chromosome 15 (SSC15). To assist in the selection of positional candidate swine genes for these QTL on SSC15, twenty-one genes had already been assigned to SSC15 in a previous study in our lab, by using the radiation hybrid panel IMpRH. Further polymorphism studies were carried out on these positional candidate genes with four breeds of pigs (Duroc, Erhualian, Dahuabai and Landrace) harboring significant differences in reproduction traits. A total of nineteen polymorphisms were found in 21 genes. Among these, seven in six genes were used for association studies, whereby NRP2 polymorphism was found to be significantly (p < 0.05) associated with litter-size traits. NRP2 might be a candidate gene for pig-litter size based on its chromosome location (Du et al., 2006), significant association with litter-size traits and relationships with Sema and the VEGF super families.     

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.     

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.     

A QTL affecting daily feed intake maps to Chromosome 2 in pigs

Our understanding of the molecular genetic basis of several key performance traits in pigs has been significantly advanced through the quantitative trait loci (QTL) mapping approach. However, in contrast to growth and fatness traits, the genetic basis of feed intake traits has rarely been investigated through QTL mapping. Since feed intake is an important component of efficient pig production, the identification of QTL affecting feed intake may lead to the identification of genetic markers that can be used in selection programs. In this study a QTL analysis for feed intake, feeding behavior, and growth traits was performed in an F₂ population derived from a cross between Chinese Meishan and European Large White pigs. A QTL with a significant effect on daily feed intake (DFI) was identified on Sus scrofa Chromosome 2 (SSC2). A number of suggestive QTL with effects on daily gain, feed conversion, and feeding behavior traits were also located. The significant QTL lies close to a previously identified mutation in the insulin-like growth factor 2 gene (IGF2) that affects carcass composition traits, although the IGF2 mutation is not segregating in the populations analyzed in the current study. Therefore, a distinct causal variant may exist on the P arm of SSC2 with an effect on feed intake.     

On growth, fatness, and form: A further look at porcine Chromosome 4 in an Iberian × Landrace cross

A crossed population between Iberian × Landrace pigs consisting of 321 F₂, 87 F₃, and 85 backcross individuals has been analyzed to refine the number and positions of quantitative trait loci (QTL) affecting shape, growth, fatness, and meat quality traits in SSC4. A multitrait multi-QTL approach has been used. Our results suggest that carcass length and shoulder weight are affected by two loci. The first one, close to the AFABP gene, has a very strong pleiotropic effect on fatness, whereas the second one, in the interval between S0073 and S0214, also affects live weight, although to a lesser extent. This latter QTL would correspond to the FAT1 locus described initially in pigs. It seems that SSC4’s loci play an important role in redistributing total weight, and the Landrace allele increases shoulder weight and carcass length much more than ham or total weight. Furthermore, there is also strong evidence of additional loci influencing pH and color in more distant, telomeric positions.     

QTL analysis of clinical-chemical traits in an F₂ intercross between Landrace and Korean native pigs

Clinical-chemical traits are essential when examining the health status of individuals. The aim of this study was to identify quantitative trait loci (QTL) and the associated positional candidate genes affecting clinical-chemical traits in a reciprocal F(2) intercross between Landrace and Korean native pigs. Following an overnight fast, 25 serum phenotypes related to clinical-chemical traits (e.g., hepatic function parameters, renal function parameters, electrolyte, lipids) were measured in >970 F(2) progeny. All experimental samples were subjected to genotyping analysis using 165 microsatellite markers located across the genome. We identified eleven genome-wide significant QTL in six chromosomal regions (SSC 2, 7, 8, 13, 14, and 15) and 59 suggestive QTL in 17 chromosomal regions (SSC 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, and 18). We also observed significant effects of reciprocal crosses on some of the traits, which would seem to result from maternal effect, QTL on sex chromosomes, imprinted genes, or genetic difference in mitochondrial DNA. The role of genomic imprinting in clinical-chemical traits also was investigated. Genome-wide analysis revealed a significant evidence for an imprinted QTL in SSC4 affecting serum amylase levels. Additionally, a series of bivariate linkage analysis provided strong evidence that QTL in SSC 2, 13, 15, and 18 have a pleiotropic effect on clinical-chemical traits. In conclusion, our study detected both novel and previously reported QTL influencing clinical-chemical traits in pigs. The identified QTL together with the positional candidate genes identified here could play an important role in elucidating the genetic structure of clinical-chemical phenotype variation in humans and swine.     

Evaluation of the causality of the low‐density lipoprotein receptor gene (LDLR) for serum lipids in pigs

A significant quantitative trait locus (QTL) for low‐density lipoprotein cholesterol (LDL‐C) and total cholesterol (TC) was identified around the LDLR gene on chromosome 2 (SSC2) in a White Duroc × Erhualian F₂ resource population and Sutai pigs in our previous study. However, in previous reports, the causality of LDLR with serum lipids is controversial in pigs. To systematically assess the causality of LDLR with serum lipids, association analyses were successively performed in three populations: Sutai pigs, a White Duroc × Erhualian F₂ resource population and a Duroc × (Landrace × Large White) population. We first performed a haplotype‐based association study with 60K SNP genotyping data and evidenced the significant association with LDL‐C and TC around the LDLR gene region. We also found that there is more than one QTL for LDL‐C and TC on SSC2. Then, we evaluated the causalities of two missense mutations, c.1812C>T and c.1520A>G, with LDL‐C and TC. We revealed that the c.1812C>T SNP showed the strongest association with LDL‐C (P = 5.40 × 10^?11) and TC (P = 3.64 × 10^?8) and explained all the QTL effect in Sutai pigs. Haplotype analysis found that two missense SNPs locate within a 1.93‐Mb haplotype block. One major haplotype showed the strongest significant association with LDL‐C (P = 4.62 × 10^?18) and TC (P = 1.06 × 10^?9). However, the c.1812C>T SNP was not identified in the White Duroc × Erhualian intercross, and the association of c.1520A>G with both LDL‐C and TC did not achieve significance in this F₂ population, suggesting population heterogeneity. Both missense mutations were identified in the Duroc × (Landrace × Large White) population and showed significant associations with LDL‐C and TC. Our data give evidence that the LDLR gene should be a candidate causative gene for LDL‐C and TC in pigs, but heterogeneity exists in different populations.     

Genome-wide association analyses reveal significant loci and strong candidate genes for growth and fatness traits in two pig populations

Background

Recently, genome-wide association studies (GWAS) have been reported on various pig traits. We performed a GWAS to analyze 22 traits related to growth and fatness on two pig populations: a White Duroc × Erhualian F₂ intercross population and a Chinese Sutai half-sib population.

Results

We identified 14 and 39 loci that displayed significant associations with growth and fatness traits at the genome-wide level and chromosome-wide level, respectively. The strongest association was between a 750 kb region on SSC7 (SSC for Sus scrofa) and backfat thickness at the first rib. This region had pleiotropic effects on both fatness and growth traits in F₂ animals and contained a promising candidate gene HMGA1 (high mobility group AT-hook 1). Unexpectedly, population genetic analysis revealed that the allele at this locus that reduces fatness and increases growth is derived from Chinese indigenous pigs and segregates in multiple Chinese breeds. The second strongest association was between the region around 82.85 Mb on SSC4 and average backfat thickness. PLAG1 (pleiomorphic adenoma gene 1), a gene under strong selection in European domestic pigs, is proximal to the top SNP and stands out as a strong candidate gene. On SSC2, a locus that significantly affects fatness traits mapped to the region around the IGF2 (insulin-like growth factor 2) gene but its non-imprinting inheritance excluded IGF2 as a candidate gene. A significant locus was also detected within a recombination cold spot that spans more than 30 Mb on SSCX, which hampered the identification of plausible candidate genes. Notably, no genome-wide significant locus was shared by the two experimental populations; different loci were observed that had both constant and time-specific effects on growth traits at different stages, which illustrates the complex genetic architecture of these traits.

Conclusions

We confirm several previously reported QTL and provide a list of novel loci for porcine growth and fatness traits in two experimental populations with Chinese Taihu and Western pigs as common founders. We showed that distinct loci exist for these traits in the two populations and identified HMGA1 and PLAG1 as strong candidate genes on SSC7 and SSC4, respectively.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0089-5) contains supplementary material, which is available to authorized users.     

A two‐step approach to map quantitative trait loci for meat quality in connected porcine F2 crosses considering main and epistatic effects

The aim of this study was to map QTL for meat quality traits in three connected porcine F₂ crosses comprising around 1000 individuals. The three crosses were derived from the founder breeds Chinese Meishan, European Wild Boar and Pietrain. The animals were genotyped genomewide for approximately 250 genetic markers, mostly microsatellites. They were phenotyped for seven meat quality traits (pH at 45 min and 24 h after slaughter, conductivity at 45 min and 24 h after slaughter, meat colour, drip loss and rigour). QTL mapping was conducted using a two‐step procedure. In the first step, the QTL were mapped using a multi‐QTL multi‐allele model that was tailored to analyse multiple connected F₂ crosses. It considered additive, dominance and imprinting effects. The major gene RYR1:g.1843C>T affecting the meat quality on SSC6 was included as a cofactor in the model. The mapped QTL were tested for pairwise epistatic effects in the second step. All possible epistatic effects between additive, dominant and imprinting effects were considered, leading to nine orthogonal forms of epistasis. Numerous QTL were found. The most interesting chromosome was SSC6. Not all genetic variance of meat quality was explained by RYR1:g.1843C>T. A small confidence interval was obtained, which facilitated the identification of candidate genes underlying the QTL. Epistasis was significant for the pairwise QTL on SSC12 and SSC14 for pH24 and for the QTL on SSC2 and SSC5 for rigour. Some evidence for additional pairwise epistatic effects was found, although not significant. Imprinting was involved in epistasis.     

QTL analysis of back fat thickness and carcass pH in an F2 intercross between Landrace and Korean native pigs

In this study, we conducted a genome-wide linkage analysis to identify the quantitative trait loci (QTL) that influence back fat thickness and carcass pH in an F(2) intercross between Landrace and Korean native pigs. Eight phenotypes related with back fat thickness and carcass pH were measured in more than 960 F(2) progeny. All experimental animals were subjected to genotypic analysis using 173 microsatellite markers located throughout the pig genome. The GridQTL program, based on the least squares regression model, was used to perform the QTL analysis. We identified 22 genome-wide significant QTL in 9 chromosomal regions (SSC1, 2, 5, 6, 7, 8, 12, 15, and 16) and 29 suggestive QTL in 16 chromosomal regions (SSC2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 14, 15, 16, 17, 18, and X). On SSC5, we detected a QTL affecting back fat thickness that accounted for 4.8 % of the phenotypic variance, which was the highest test statistic (F-ratio = 50.3 under the additive model, nominal P value = 2.5 × 10(-12)) observed in this study. Additionally, we showed that there were significant QTL on SSC16 affecting carcass pH traits. In conclusion, the QTL identified in this study together with associated positional candidate genes could play an important role in determining the genetic structure underlying the variation of back fat thickness and carcass pH in pigs.     

Quantitative trait loci and candidate genes associated with starch pasting viscosity characteristics in cassava (Manihot esculenta Crantz)

Starch pasting viscosity is an important quality trait in cassava (Manihot esculenta Crantz) cultivars. The aim here was to identify loci and candidate genes associated with the starch pasting viscosity. Quantitative trait loci (QTL) mapping for seven pasting viscosity parameters was carried out using 100 lines of an F₁ mapping population from a cross between two cassava cultivars Huay Bong 60 and Hanatee. Starch samples were obtained from roots of cassava grown in 2008 and 2009 at Rayong, and in 2009 at Lop Buri province, Thailand. The traits showed continuous distribution among the F₁ progeny with transgressive variation. Fifteen QTL were identified from mean trait data, with Logarithm of Odds (LOD) values from 2.77–13.01 and phenotype variations explained (PVE) from10.0–48.4%. In addition, 48 QTL were identified in separate environments. The LOD values ranged from 2.55–8.68 and explained 6.6–43.7% of phenotype variation. The loci were located on 19 linkage groups. The most important QTL for pasting temperature (PT) (qPT.1LG1) from mean trait values showed largest effect with highest LOD value (13.01) and PVE (48.4%). The QTL co‐localised with PT and pasting time (PTi) loci that were identified in separate environments. Candidate genes were identified within the QTL peak regions. However, the major genes of interest, encoding the family of glycosyl or glucosyl transferases and hydrolases, were located at the periphery of QTL peaks. The loci identified could be effectively applied in breeding programmes to improve cassava starch quality. Alleles of candidate genes should be further studied in order to better understand their effects on starch quality traits.     

Heritabilities and quantitative trait loci for blood gases and blood pH in swine

Maintaining pH and blood gases in a narrow range is essential to sustain normal biochemical reactions. Decreased oxygenation, poor tissue perfusion, disturbance to CO₂ expiration, and shortage of HCO₃⁻ can lead to metabolic acidosis. This is a common situation in swine, and originates from a broad range of medical conditions. pH and blood gases appear to be under genetic control, and populations with physiological traits closer to the pathological thresholds may be more susceptible to developing pathological conditions. However, little is known about the genetic basis of such traits. We have therefore estimated phenotypic and genetic variability and identified quantitative trait loci (QTL) for pH and blood gases in blood samples from 139 F₂ pigs from the Meishan/Pietrain family. Samples were taken before and after challenge with Sarcocystis miescheriana , a protozoan parasite of muscle. Twenty-seven QTL influencing pH and blood gases were identified on nine chromosomes. Five of the QTL were significant on a genome-wide level; 22 QTL were significant on a chromosome-wide level. QTL for pH-associated traits have been mapped to SSC3, 18 and X. QTL associated with CO₂ have been detected on SSC6, 7, 8 and 9, and QTL associated with O₂ on SSC2 and SSC8. QTL showed specific health/disease patterns that were related to the physiological state of the pigs from day 0, to acute disease (day 14), convalescence (day 28) and chronic disease (day 42). The results demonstrate that pH and blood gases are influenced by multiple chromosomal areas, each with relatively small effects.     

Genome-Wide Association Analysis for Blood Lipid Traits Measured in Three Pig Populations Reveals a Substantial Level of Genetic Heterogeneity

Serum lipids are associated with myocardial infarction and cardiovascular disease in humans. Here we dissected the genetic architecture of blood lipid traits by applying genome-wide association studies (GWAS) in 1,256 pigs from Laiwu, Erhualian and Duroc × (Landrace × Yorkshire) populations, and a meta-analysis of GWAS in more than 2,400 pigs from five diverse populations. A total of 22 genomic loci surpassing the suggestive significance level were detected on 11 pig chromosomes (SSC) for six blood lipid traits. Meta-analysis of GWAS identified 5 novel loci associated with blood lipid traits. Comparison of GWAS loci across the tested populations revealed a substantial level of genetic heterogeneity for porcine blood lipid levels. We further evaluated the causality of nine polymorphisms nearby or within the APOB gene on SSC3 for serum LDL-C and TC levels. Of the 9 polymorphisms, an indel showed the most significant association with LDL-C and TC in Laiwu pigs. But the significant association was not identified in the White Duroc × Erhualian F₂ resource population, in which the QTL for LDL-C and TC was also detected on SSC3. This indicates that population-specific signals may exist for the SSC3 QTL. Further investigations are warranted to validate this assumption.     

Quantitative trait loci analysis of phenotypic traits and principal components of maize tassel inflorescence architecture

Maize tassel inflorescence architecture is relevant to efficient production of F₁ seed and yield performance of F₁ hybrids. The objectives of this study were to identify genetic relationships among seven measured tassel inflorescence architecture traits and six calculated traits in a maize backcross population derived from two lines with differing tassel architectures, and identify Quantitative Trait Loci (QTL) involved in the inheritance of those tassel inflorescence architecture traits. A Principal Component (PC) analysis was performed to examine relationships among correlated traits. Traits with high loadings for PC1 were branch number and branch number density, for PC2 were spikelet density on central spike and primary branch, and for PC3 were lengths of tassel and central spike. We detected 45 QTL for individual architecture traits and eight QTL for the three PCs. For control of inflorescence architecture, important QTL were found in bins 7.02 and 9.02. The interval phi034—ramosa1 (ral) in bin 7.02 was associated with six individual architecture trait QTL and explained the largest amount of phenotypic variation (17.3%) for PC1. Interval bnlg344–phi027 in bin 9.02 explained the largest amount of phenotypic variation (14.6%) for PC2. Inflorescence architecture QTL were detected in regions with candidate genes fasciated ear2, thick tassel dwarf1, and ral. However, the vast majority of QTL mapped to regions without known candidate genes, indicating positional cloning efforts will be necessary to identify these genes.     

Quantitative trait loci for porcine white blood cells and platelet-related traits in a White Duroc × Erhualian F2 resource population

White blood cell count and platelets are implicated as risk factors for common complex diseases. Genetic factors substantially affect these traits in humans and mice. However, little is known about the genetic architecture of these traits in pigs. To identify quantitative trait loci (QTL) for leucocyte- and platelet-related traits in pigs, the total leucocyte number and differential leucocyte counts including the fraction of basophils, eosinophils, lymphocytes, monocytes, neutrophils, and a series of platelet parameters including platelet count, mean platelet volume, platelet distribution width and plateletcrit were measured in 1033 F₂ animals on 240 days from a White Duroc × Erhualian intercross resource population. A total of 183 informative microsatellites distributed across 19 pig chromosomes (SSC) were genotyped across the entire resource population. Thirty-three QTL were identified for the examined traits, including eight genome-wide significant QTL for white blood cells and differential leucocyte counts on SSC2, 7, 8, 12 and 15 and six significant QTL for platelet-related traits on SSC2, 8, 13 and X. Erhualian or White Duroc alleles were not systematically associated with increased phenotypic values. These results not only confirmed many QTL identified previously in the mouse and swine, but also revealed a number of novel QTL for the traits recorded. Moreover, it is the first time that QTL for platelet-related traits in pigs have been reported.     

A Further Look at Porcine Chromosome 7 Reveals VRTN Variants Associated with Vertebral Number in Chinese and Western Pigs

The number of vertebrae is an economically important trait that affects carcass length and meat production in pigs. A major quantitative trait locus (QTL) for thoracic vertebral number has been repeatedly identified on pig chromosome (SSC) 7. To dissect the genetic basis of the major locus, we herein genotyped a large sample of animals from 3 experimental populations of Chinese and Western origins using 60K DNA chips. Genome-wide association studies consistently identified the locus across the 3 populations and mapped the locus to a 947-Kb region on SSC7. An identical-by-descent sharing assay refined the locus to a 100-Kb segment that harbors only two genes including VRTN and SYNDIG1L. Of them, VRNT has been proposed as a strong candidate of the major locus in Western modern breeds. Further, we resequenced the VRTN gene using DNA samples of 35 parental animals with known QTL genotypes by progeny testing. Concordance tests revealed 4 candidate causal variants as their genotypes showed the perfect segregation with QTL genotypes of the tested animals. An integrative analysis of evolutional constraints and functional elements supported two VRTN variants in a complete linkage disequilibrium phase as the most likely causal mutations. The promising variants significantly affect the number of thoracic vertebrae (one vertebra) in large scale outbred animals, and are segregating at rather high frequencies in Western pigs and at relatively low frequencies in a number of Chinese breeds. Altogether, we show that VRTN variants are significantly associated with the number of thoracic vertebrae in both Chinese and Western pigs. The finding advances our understanding of the genetic architecture of the vertebral number in pigs. Furthermore, our finding is of economical importance as it provides a robust breeding tool for the improvement of vertebral number and meat production in both Chinese indigenous pigs and Western present-day commercial pigs.