A genome scan for quantitative trait loci associated with body weight at different developmental stages in chickens

A genome scan to detect quantitative trait loci (QTL) affecting body weight in chickens was conducted on 238 F(2) chickens from a reciprocal cross of Silky Fowl and White Plymouth Rock using 125 microsatellite markers covering 23 autosomes and the Z chromosome. Two types of QTL were considered: static QTL (SQ) and developmental QTL (DQ). Static QTL affected the body weight from hatch to time t, and DQ affected the body weight from time t-1 to time t. Six SQ and nine DQ were detected. Of these QTL, four reached a genome-wide significance of 5% or better, with SQ1 and DQ1 being the most significant QTL. Static QTL1 was on chromosome 1 between GCT0006 and MCW0106 and explained 4.05-9.80% of the phenotypic variation in body weights from 3 to 12 weeks of age. At 9, 10 and 11 weeks, the genome-wide significance thresholds of SQ1 were <1%. Developmental QTL1 was located on chromosome 1 between MCW0168 and GCT0006, and explained 2.75% of the phenotypic variation for body weight from week 7 to 8 with a genome-wide significance level <1%. The results suggest that body weight from hatch to time t and developmental growth from time t-1 to time t may involve two different sets of genes or gene actions.     

Mapping quantitative trait loci regulating chicken body composition traits

Genome scans were conducted on an F₂ resource population derived from intercross of the White Plymouth Rock with the Silkies Fowl to detect QTL affecting chicken body composition traits. The population was genotyped with 129 microsatellite markers and phenotyped for 12 body composition traits on 238 F₂ individuals from 15 full-sib families. In total, 21 genome-wide QTL were found to be responsible for 11 traits, including two newly studied traits of proventriculus weight and shank girth. Three QTL were genome-wide significant: at 499 c m on GGA1 (explained 3.6% of phenotypic variance, P  < 0.01) and 51 c m on GGA5 (explained 3.3% of phenotypic variance, P  < 0.05) for the shank & claw weight and 502 c m on GGA1 (explained 1.4% of phenotypic variance, P  < 0.05) for wing weight. The QTL on GGA1 seemed to have pleiotropic effects, also affecting gizzard weight at 490 c m , shank girth at 489 c m and intestine length at 481 c m . It is suggested that further efforts be made to understand the possible pleiotropic effects of the QTL on GGA1 and that on GGA5 for two shank-related traits.     

A genome scan for quantitative trait loci affecting three ear traits in a White Duroc × Chinese Erhualian resource population

Chinese Erhualian pigs have larger and floppier ears compared with White Duroc pigs (small, half- or fully-pricked ears). To identify quantitative trait loci (QTL) for ear weight and area as well as erectness, a genome-wide scan with 194 microsatellites was performed in a White Duroc × Chinese Erhualian resource population (>1000 F₂ animals). Twenty-three genome-wide significant QTL and 12 suggestive QTL were identified. All QTL for ear erectness and size detected in two previous studies, bar two on SSC6 and 9, were confirmed here. The 1% genome-wide significant QTL at 70 cM on SSC5 and at 58 cM on SSC7 have profound and pleiotropic effects on the three ear traits, with Erhualian alleles increasing weight and area but decreasing erectness. Notably, the 95% confidence interval of the QTL for weight and area on SSC7 spanned only 3 cM. New QTL reaching 1% genome-wide significance were found on SSC8 (at 37 cM) for all three ear traits, on SSC4 and 16 for weight and area, and on SSCX for area. Unexpectedly, Erhualian alleles at these loci were associated with lighter and smaller or erect ear. Some new suggestive QTL were also found on other chromosome regions. Almost all the QTL for weight and area had essentially additive effects, while the QTL for erectness on SSC2, 5 and 7 showed not only additive effects but also partial dominance effects of Erhualian alleles. The two most significant QTL on SSC7 and SSC5 could be promising targets for fine mapping and identification of the causative mutations.     

A genome scan for loci affecting pork quality in a Duroc-Landrace F population

A genome scan was conducted on 370 F2 Duroc-Landrace pigs. Microsatellite markers (n = 182) were genotyped across the entire F2 population, all F1 parents and the paternal grandparents. Breed of origin of all chromosomal segments inherited in F2 progeny were predicted using GenoProb, where genotypic data, genetic maps and extended pedigrees were used as inputs. Statistical tests for quantitative trait loci (QTL) associations were conducted on 41 phenotypes with SAS using output from GenoProb for genotypic data. Fixed effects included sex and age at slaughter. For certain analyses carcass weight, RYR1 genotype and/or PRKAG3 genotype were also included as covariates. Subjective and objective measures of pork colour, marbling and tenderness were recorded, as well as measures of carcass fatness and muscularity. Test results were adjusted to a genome-wide level of significance. Five genomic regions presented significant evidence for QTL at chromosome 1 positions 6 cM (intramuscular fat) and 67 cM (Hunter L*), chromosome 2 position 62 cM (taste panel tenderness), chromosome 17 position 50 (loineye area and image analysis estimated loineye area) and X position 87 cM (carcass weight). Sixty-six suggestive associations were detected. Fourteen of these associations were within the regions with significant QTL on chromosomes 2, 17 and X, and the remaining 52 associations resided in 29 other regions on 13 different chromosomes of the porcine genome. The chromosome 2 region of 60-66 cM was associated with all measures of pork tenderness and the region on chromosome 17 (32-39 cM) was associated with both measures of intramuscular fat and loineye area. After verification, the QTL for marbling and tenderness should be useful in commercial production to improve pork quality as the population was developed from two of the three most utilized breeds of swine in the USA.     

Correcting for bias in estimation of quantitative trait loci effects

Estimates of quantitative trait loci (QTL) effects derived from complete genome scans are biased, if no assumptions are made about the distribution of QTL effects. Bias should be reduced if estimates are derived by maximum likelihood, with the QTL effects sampled from a known distribution. The parameters of the distributions of QTL effects for nine economic traits in dairy cattle were estimated from a daughter design analysis of the Israeli Holstein population including 490 marker-by-sire contrasts. A separate gamma distribution was derived for each trait. Estimates for both the α and β parameters and their SE decreased as a function of heritability. The maximum likelihood estimates derived for the individual QTL effects using the gamma distributions for each trait were regressed relative to the least squares estimates, but the regression factor decreased as a function of the least squares estimate. On simulated data, the mean of least squares estimates for effects with nominal 1% significance was more than twice the simulated values, while the mean of the maximum likelihood estimates was slightly lower than the mean of the simulated values. The coefficient of determination for the maximum likelihood estimates was five-fold the corresponding value for the least squares estimates.     

Revisiting the quantitative trait loci for milk production traits on BTA6

A parallel association study was performed in two independent cattle populations based on 41 validated, targeted single nucleotide polymorphisms (SNPs) and four microsatellite markers to re-evaluate the multiple quantitative trait loci (QTL) architecture for milk performance on bovine chromosome 6 (BTA6). Two distinct QTL located in the vicinity of the middle region of BTA6, but differing unambiguously regarding their effects on milk composition and yield traits were validated in the German Holstein population. A highly significant association of the protein variant ABCG2 p.Tyr581Ser with milk composition traits reconfirmed the causative molecular relevance of the ABCG2 gene in QTL region 1, whereas in QTL region 2, significant and tentative associations between gene variants RW070 and RW023 (located in the promoter region and exon 9 of the PPARGC1A gene for milk yield traits) were detected. For the German Fleckvieh population, only RW023 showed a tentative association with milk yield traits, whereas those loci with significant effects in German Holsteins (ABCG2 p.Tyr581Ser, RW070) showed fixed alleles. Even though our new data highlight two variants in the PPARGC1A gene (RW023, RW070) in QTL region 2, based on the results of our study, currently no unequivocal conclusion about the causal background of this QTL affecting milk yield traits can be drawn. Notably, the German Holstein and Fleckvieh populations, known for their divergent degree of dairy type, differ substantially in their allele frequencies for the growth-associated NCAPG p.Ile442Met locus.     

Genetic mapping of quantitative trait loci affecting susceptibility in chicken to develop pulmonary hypertension syndrome

Pulmonary hypertension syndrome (PHS), also referred to as ascites syndrome, is a growth-related disorder of chickens frequently observed in fast-growing broilers with insufficient pulmonary vascular capacity at low temperature and/or at high altitude. A cross between two genetically different broiler dam lines that originated from the White Plymouth Rock breed was used to produce a three-generation population. This population was used for the detection and localization of quantitative trait loci (QTL) affecting PHS-related traits. Ten full-sib families consisting of 456 G2 birds were typed with 420 microsatellite markers covering 24 autosomal chromosomes. Phenotypic observations were collected on 4202 G3 birds and a full-sib across family regression interval mapping approach was used to identify QTL. There was statistical evidence for QTL on chicken chromosome 2 (GGA2), GGA4 and GGA6. Suggestive QTL were found on chromosomes 5, 8, 10, 27 and 28. The most significant QTL were located on GGA2 for right and total ventricular weight as percentage of body weight (%RV and %TV respectively). A related trait, the ratio of right ventricular weight as percentage to total ventricular weight (RATIO), reached the suggestive threshold on this chromosome. All three QTL effects identified on GGA2 had their maximum test statistic in the region flanked by markers MCW0185 and MCW0245 (335-421 cM).     

Identification of quantitative trait loci for growth and carcass composition in cattle

A genomic screening to detect quantitative trait loci (QTL) affecting growth, carcass composition and meat quality traits was pursued. Two hundred nineteen microsatellite markers were genotyped on 176 of 620 (28%) progeny from a Brahman x Angus sire mated to mostly MARC III dams. Selective genotyping, based on retail product yield (%) and fat yield (%), was used to select individuals to be genotyped. Traits included in the study were birth weight (kg), hot carcass weight (kg), retail product yield, fat yield, marbling score (400 = slight00 and 500 = small00), USDA yield grade, and estimated kidney, heart and pelvic fat (%). The QTL were classified as significant when the expected number of false positives (ENFP) was less than 0.05 (F-statistic greater than 17.3), and suggestive when the ENFP was <1 (F-statistic between 10.2 and 17.3). A significant QTL (F = 19; ENFP = 0.02) was detected for marbling score at centimorgan (cM) 54 on chromosome 2. Suggestive QTL were detected for fat yield at 50 cM, for retail product yield at 53 cM, and for USDA yield grade at 63 cM on chromosome 1, for marbling score at 56 cM, for retail product yield at 70 cM, and for estimated kidney, heart and pelvic fat at 79 cM on chromosome 3, for marbling score at 44 cM, for hot carcass weight at 49 cM, and for estimated kidney, heart and pelvic fat at 62 cM on chromosome 16, and for fat yield at 35 cM on chromosome 17. Two suggestive QTL for birth weight were identified, one at 12 cM on chromosome 20 and the other at 56 cM on chromosome 21. An additional suggestive QTL was detected for retail product yield, for fat yield, and for USDA yield grade at 26 cM on chromosome 26. Results presented here represent the initial search for quantitative trait loci in this family. Validation of detected QTL in other populations will be necessary.     

Genetic mapping of quantitative trait loci for resistance to Haemonchus contortus in sheep

This paper presents results from a mapping experiment to detect quantitative trait loci (QTL) for resistance to Haemonchus contortus infestation in merino sheep. The primary trait analysed was faecal worm egg count in response to artificial challenge at 6 months of age. In the first stage of the experiment, whole genome linkage analysis was used for broad-scale mapping. The animal resource used was a designed flock comprising 571 individuals from four half-sib families. The average marker spacing was about 20 cM. For the primary trait, 11 QTL (as chromosomal/family combinations) were significant at the 5% chromosome-wide level, with allelic substitution effects of between 0.19 and 0.38 phenotypic standard deviation units. In general, these QTL did not have a significant effect on faecal worm egg count recorded at 13 months of age. In the second stage of the experiment, three promising regions (located on chromosomes 1, 3 and 4) were fine-mapped. This involved typing more closely spaced markers on individuals from the designed flock as well as an additional 495 individuals selected from a related population with a deeper pedigree. Analysis was performed using a linkage disequilibrium–linkage approach, under additive, dominant and multiple QTL models. Of these, the multiple QTL model resulted in the most refined QTL positions, with resolutions of <10 cM achieved for two regions. Because of the moderate size of effect of the QTL, and the apparent age and/or immune status specificity of the QTL, it is suggested that a panel of QTL will be required for significant genetic gains to be achieved within industry via marker-assisted selection.     

Evidence for quantitative trait loci affecting twinning rate in North American Holstein cattle

Twinning in dairy cattle has been associated with many negative health and reproductive events that cause economic loss to the producer. Reports have suggested that twinning rates are increasing and that there may be a positive relationship between milk production and twinning frequency. Putative quantitative trait loci (QTL) for twinning and ovulation rate on bovine chromosomes 5, 7, 19 and 23 have been previously identified in other populations. The objective of this study was to detect and possibly confirm the existence and effects of these QTL in the North American Holstein population. Half-sib families of 20 North American Holstein sires with above average twinning rate predicted transmitting abilities (PTA) comprised the sample population under investigation. Twinning rate PTA values had been estimated from calving data. DNA extracted from semen samples was analysed using 45-61 microsatellite markers across the four chromosomes. Marker heterozygosity of the patriarchs averaged 62%. Evidence of twinning QTL was found in multiple families on chromosomes 5, 7 and 23 and in one family on chromosome 19. Four of the sires formed one three-generation family: one sire and three half-sib sons with sons of their own. This extended family was analysed with additional markers confirming a twinning QTL of significant size on chromosome 5.     

Joint tests for quantitative trait loci in experimental crosses

Selective genotyping is common because it can increase the expected correlation between QTL genotype and phenotype and thus increase the statistical power of linkage tests (i.e., regression-based tests). Linkage can also be tested by assessing whether the marginal genotypic distribution conforms to its expectation, a marginal-based test. We developed a class of joint tests that, by constraining intercepts in regression-based analyses, capitalize on the information available in both regression-based and marginal-based tests. We simulated data corresponding to the null hypothesis of no QTL effect and the alternative of some QTL effect at the locus for a backcross and an F2 intercross between inbred strains. Regression-based and marginal-based tests were compared to corresponding joint tests. We studied the effects of random sampling, selective sampling from a single tail of the phenotypic distribution, and selective sampling from both tails of the phenotypic distribution. Joint tests were nearly as powerful as all competing alternatives for random sampling and two-tailed selection under both backcross and F2 intercross situations. Joint tests were generally more powerful for one-tailed selection under both backcross and F2 intercross situations. However, joint tests cannot be recommended for one-tailed selective genotyping if segregation distortion is suspected.     

Whole-genome scan for quantitative trait loci associated with birth weight, gestation length and passive immune transfer in a Holstein × Jersey crossbred population

We herein report results from a daughter design genome-scan study aiming to identify quantitative trait loci (QTL) associated with birth weight, direct gestation length and passive immune transfer in a backcross (Holstein × Jersey) × Holstein population. Two-hundred and seventy-six calves, offspring of seven crossbred sires, were genotyped for 161 microsatellite markers distributed along the 29 bovine autosomes. The genome scan was performed through interval mapping using an animal model in order to identify QTL accounting for phenotypic differences between individual animals. Based on significant chi-squared values, we identified putative QTL on BTA7 and BTA14 for gestation length, on BTA2, BTA6 and BTA14 for birth weight and on BTA20 for passive immune transfer. In total, these QTL accounted for 12%, 18% and 1% of the phenotypic variance in gestation length, birth weight and passive immune transfer respectively. We also report results from a supplementary and independent influential grand-daughter Holstein family. In this family, findings on BTA7 and BTA14 for direct gestation length were in agreement with results in the crossbred population. Two other regions on BTA6 and BTA21 putatively underlying QTL for direct gestation length variability were discovered with this analysis.     

Adaptation of tree growth to elevated CO2: quantitative trait loci for biomass in Populus

* Information on the genetic variation of plant response to elevated CO(2) (e[CO(2)]) is needed to understand plant adaptation and to pinpoint likely evolutionary response to future high atmospheric CO(2) concentrations. * Here, quantitative trait loci (QTL) for above- and below-ground tree growth were determined in a pedigree - an F(2) hybrid of poplar (Populus trichocarpa and Populus deltoides), following season-long exposure to either current day ambient CO(2) (a[CO(2)]) or e[CO(2)] at 600 microl l(-1), and genotype by environment interactions investigated. * In the F(2) generation, both above- and below-ground growth showed a significant increase in e[CO(2)]. Three areas of the genome on linkage groups I, IX and XII were identified as important in determining above-ground growth response to e[CO(2)], while an additional three areas of the genome on linkage groups IV, XVI and XIX appeared important in determining root growth response to e[CO(2)]. * These results quantify and identify genetic variation in response to e[CO(2)] and provide an insight into genomic response to the changing environment.     

A search for quantitative trait loci for milk production traits on chromosome 6 in Finnish Ayrshire cattle

Cattle chromosome 6 was scanned with 11 markers, ten microsatellites and the casein haplotype, to identify quantitative trait loci (QTLs) affecting the following milk production traits: milk yield, fat percentage, fat yield, protein percentage and protein yield. Twelve Finnish Ayrshire half-sib families with a total of 480 sons were genotyped and used in a grand-daughter design. Interval mapping was performed with a multiple-marker regression approach with a one-QTL and a two-QTL model, and the significance threshold values were determined empirically using a permutation test. Across-family analysis with the one-QTL model revealed an effect on protein percentage (P < 0.05) and on milk yield (P < 0.05). The analysis with the two-QTL model identified significant effects (P < 0.05) on protein percentage, milk yield, and fat yield. Comparing these two cases, the results suggest the existence of two QTLs on chromosome 6 with an effect on milk production traits. One of the QTLs was located around the casein genes. As the other QTL was similar in location and effect to a QTL found previously in Holstein-Friesians, an identity-by-descent approach could be applied to fine map this region.     

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 association study for quantitative trait loci of show-jumping in Hanoverian warmblood horses

Show-jumping is an economically important breeding goal in Hanoverian warmblood horses. The aim of this study was a genome-wide association study (GWAS) for quantitative trait loci (QTL) for show-jumping in Hanoverian warmblood horses, employing the Illumina equine SNP50 Beadchip. For our analyses, we genotyped 115 stallions of the National State stud of Lower Saxony. The show-jumping talent of a horse includes style and ability in free-jumping. To control spurious associations based on population stratification, two different mixed linear animal model (MLM) approaches were employed, besides linear models with fixed effects only and adaptive permutations for correcting multiple testing. Population stratification was explained best in the MLM considering Hanoverian, Thoroughbred, Trakehner and Holsteiner genes and the marker identity-by-state relationship matrix. We identified six QTL for show-jumping on horse chromosomes (ECA) 1, 8, 9 and 26 (-log(10) P-value >5) and further putative QTL with -log(10) P-values of 3-5 on ECA1, 3, 11, 17 and 21. Within six QTL regions, we identified human performance-related genes including PAPSS2 on ECA1, MYL2 on ECA8, TRHR on ECA9 and GABPA on ECA26 and within the putative QTL regions NRAP on ECA1, and TBX4 on ECA11. The results of our GWAS suggest that genes involved in muscle structure, development and metabolism are crucial for elite show-jumping performance. Further studies are required to validate these QTL in larger data sets and further horse populations.     

A genome‐wide scan for quantitative trait loci affecting respiratory disease and immune capacity in Landrace pigs

Respiratory disease is the most important health concern for the swine industry. Genetic improvement for disease resistance is challenging because of the difficulty in obtaining good phenotypes related with disease resistance; however, identification of genes or markers associated with disease resistance can help in the genetic improvement of pig health. The purpose of our study was to investigate whether quantitative trait loci (QTL) associated with disease resistance were segregated in a purebred population of Landrace pigs that had been selected for meat production traits and mycoplasmal pneumonia of swine (MPS) scores over five generations. We analysed 1395 pigs from the base to the fifth generation of this population. Two respiratory disease traits [MPS scores and atrophic rhinitis (AR) scores] and 11 immune‐capacity traits were measured in 630–1332 animals at 7 weeks of age and when the animal's body weight reached 105 kg. Each of the pigs, except sires in the base population, was genotyped using 109 microsatellite markers, and then, QTL analysis of the full‐sib family population with a multi‐generational pedigree structure was performed. Variance component analysis was used to detect QTL associated with MPS or AR scores, and the logarithm of odds (LOD) score and genotypic heritability of the QTL were estimated. Five significant (LOD > 2.51) and 18 suggestive (LOD > 1.35) QTL for respiratory disease traits and immune‐capacity traits were detected. The significant QTL for Log‐MPS score, located on S. scrofa chromosome 2, could explain 87% of the genetic variance of this score in this analysis. This is the first report of QTL associated with respiratory disease lesions.     

QTL‐seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations

The majority of agronomically important crop traits are quantitative, meaning that they are controlled by multiple genes each with a small effect (quantitative trait loci, QTLs). Mapping and isolation of QTLs is important for efficient crop breeding by marker‐assisted selection (MAS) and for a better understanding of the molecular mechanisms underlying the traits. However, since it requires the development and selection of DNA markers for linkage analysis, QTL analysis has been time‐consuming and labor‐intensive. Here we report the rapid identification of plant QTLs by whole‐genome resequencing of DNAs from two populations each composed of 20–50 individuals showing extreme opposite trait values for a given phenotype in a segregating progeny. We propose to name this approach QTL‐seq as applied to plant species. We applied QTL‐seq to rice recombinant inbred lines and F₂ populations and successfully identified QTLs for important agronomic traits, such as partial resistance to the fungal rice blast disease and seedling vigor. Simulation study showed that QTL‐seq is able to detect QTLs over wide ranges of experimental variables, and the method can be generally applied in population genomics studies to rapidly identify genomic regions that underwent artificial or natural selective sweeps.     

Genome-wide association mapping in Norwegian Red cattle identifies quantitative trait loci for fertility and milk production on BTA12

Reproductive performance is a critical trait in dairy cattle. Poor reproductive performance leads to prolonged calving intervals, higher culling rates and extra expenses related to multiple inseminations, veterinary treatments and replacements. Genetic gain for improved reproduction through traditional selection is often slow because of low heritability and negative correlations with production traits. Detection of DNA markers associated with improved reproductive performance through genome-wide association studies could lead to genetic gain that is more balanced between fertility and production. Norwegian Red cattle are well suited for such studies, as very large numbers of detailed reproduction records are available. We conducted a genome-wide association study for non-return rate, fertility treatments and retained placenta using almost 1 million records on these traits and 17 343 genome-wide single-nucleotide polymorphisms. Genotyping costs were minimized by genotyping the sires of the cows recorded and by using daughter averages as phenotypes. The genotyped sires were assigned to either a discovery or a validation population. Associations were only considered to be validated if they were significant in both groups. Strong associations were found and validated on chromosomes 1, 5, 8, 9, 11 and 12. Several of these were highly supported by findings in other studies. The most important result was an association for non-return rate in heifers in a region of BTA12 where several associations for milk production traits have previously been found. Subsequent fine-mapping verified the presence of a quantitative trait loci (QTL) having opposing effects on non-return rate and milk production at 18 Mb. The other reproduction QTL did not have pleiotropic effects on milk production, and these are therefore of considerable interest for use in marker-assisted selection.