Approaches to interval mapping of QTL in a multigeneration pedigree: the example of porcine chromosome 4

Quantitative trait loci (QTLs) have been mapped in many studies of F2 populations derived from crosses between diverse lines. One approach to confirming these effects and improving the mapping resolution is genetic chromosome dissection through a backcrossing programme. Analysis by interval mapping of the data generated is likely to provide additional power and resolution compared with treating data marker by marker. However, interval mapping approaches for such a programme are not well developed, especially where the founder lines were outbred. We explore alternative approaches to analysis using, as an example, data from chromosome 4 in an intercross between wild boar and Large White pigs where QTLs have been previously identified. A least squares interval mapping procedure was used to study growth rate and carcass traits in a subsequent second backcross generation (BC2). This procedure requires the probability of inheriting a wild boar allele for each BC2 animal for locations throughout the chromosome. Two methods for obtaining these probabilities were compared: stochastic or deterministic. The two methods gave similar probabilities for inheriting wild boar alleles and, hence, gave very similar results from the QTL analysis. The deterministic approach has the advantage of being much faster to run but requires specialized software. A QTL for fatness and for growth were confirmed and, in addition, a QTL for piglet growth from weaning at 5 weeks up to 7 weeks of age and another for carcass length were detected.     

Whole-genome scan to detect QTL for milk production, conformation, fertility and functional traits in two US Holstein families

A genome scan was conducted in two US Holstein half-sib families to identify quantitative trait loci (QTL) affecting milk production and conformation traits using the granddaughter design. The sires of the two studied families were related as sire and son and had 96 and 212 sons respectively. A total of 221 microsatellite loci were scored in both families. Statistical analysis was performed using two different analytical methods; half-sib least squares regression and Bayesian Monte Carlo Markov Chain. Traits analysed included five traditional milk production traits, somatic cell count, daughter pregnancy rate, male fertility and 20 conformation traits. A total of 47 tests achieved at least genome-wise significance. However, results from the two methods of analysis were only concordant for QTL location and level of significance in eight instances.     

Identification of a QTL on BTA20 affecting susceptibility to Mycobacterium avium ssp. paratuberculosis infection in US Holsteins

The objective of this study was to identify QTL affecting susceptibility to Mycobacterium paratuberculosis infection in US Holsteins. Twelve paternal half-sib families were selected for the study based on large numbers of daughters in production and limited relationships among sires. Serum and faecal samples from 4350 daughters of these 12 sires were obtained for disease testing. Case definition for an infected cow was an ELISA sample-to-positive ratio >/=0.25, a positive faecal culture or both. Three families were selected for genotyping based on a high apparent prevalence (6.8-10.4% infected cows), high faecal culture prevalence (46.2-52.9% positive faecal cultures) and large numbers of daughters tested for disease (264-585). DNA pooling was used to genotype cows, with an average of 159 microsatellites within each sire family. Infected cows (the positive pool) were matched with two of their non-infected herdmates in the same lactation (the negative pool) to control for herd and age effects. Eight chromosomal regions putatively linked with susceptibility to M. paratuberculosis infection were identified using a Z-test (P < 0.01). Significant results were more rigorously tested by individually genotyping cows with three to five informative microsatellites within 15 cM of the significant markers identified with the DNA pools. Probability of infection based on both diagnostic tests was estimated for each individual and used as the dependent variable for interval mapping. Based on this analysis, evidence for the presence of a QTL segregating within families on BTA20 was found (chromosome-wide P-value = 0.0319).     

Detection of loci affecting milk production and health traits in an elite US Holstein population using microsatellite markers

Quantitative trait loci (QTL) affecting health and milk production traits were studied in seven large half-sib US Holstein families by using the granddaughter design. Genotyping for 16 markers was completed and marker allele differences within and pooled-across families were analysed. Potential QTL were identified for somatic cell score (SCS), fat yield, fat percentage, protein yield and protein percentage. Three markers (BM203, BM4505 and BM2078) were associated with significant effects for different traits and, after further analysis, may be useful in marker-assisted selection in specific families. Comparisons between these data and previously identified QTL support the location of a QTL for milk yield and protein yield on chromosome 21.     

Testing for the presence of previously identified QTL for milk production traits in new populations

Five chromosomal regions previously associated with milk production traits were tested in 16 families of Black and White cattle from the UK. The traits were also linearly transformed into genetically and phenotypically independent variables normalized by phenotypic variances ('canonical traits'). Significant associations with the untransformed and canonical traits were found for bovine chromosome 6. There was also evidence that chromosome 9 influenced these traits. The linear transformation clarified the effects of chromosomal regions; regions with effects on all three untransformed traits (milk, fat and protein yields) were generally condensed into an effect on a single canonical trait. Comparison of our results with those reported previously for American Holstein cattle suggested that the QTL may not be the same.     

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.     

Identification of a 3.7-Mb region for a marbling QTL on bovine chromosome 4 by identical-by-descent and association analysis

QTL mapping for growth and carcass traits was performed using a paternal half-sib family composed of 325 Japanese Black cattle offspring. Nine QTL were detected at the 1% chromosome-wise significance level at a false discovery rate of less than 0.1. These included two QTL for marbling on BTA 4 and 18, two QTL for carcass weight on BTA 14 and 24, two QTL for longissimus muscle area on BTA 1 and 4, two QTL for subcutaneous fat thickness on BTA 1 and 15 and one QTL for rib thickness on BTA 6. Although the marbling QTL on BTA 4 has been replicated with significant linkages in two Japanese Black cattle sires, the three Q (more marbling) haplotypes, each inherited maternally, were apparently different. To compare the three Q haplotypes in more detail, high-density microsatellite markers for the overlapping regions were developed within the 95% CIs (65 markers in 44–78 cM). A detailed haplotype comparison indicated that a small region (<3.7 Mb) around 46 cM was shared between the Qs of the two sires, whose dams were related. An association of this region with marbling was shown by a regression analysis using the local population, in which the two sires were produced and this was confirmed by an association study using a population collected throughout Japan. These results strongly suggest that the marbling QTL on BTA 4 is located in the 3.7-Mb region at around 46 cM.     

Confirmation and refinement of a QTL on BTA5 affecting milk production traits in the Fleckvieh dual purpose cattle breed

We analysed a QTL affecting milk yield (MY), milk protein yield (PY) and milk fat yield (FY) in the dual purpose cattle breed Fleckvieh on BTA5. Twenty-six microsatellite markers covering 135 cM were selected to analyse nine half-sib families containing 605 sons in a granddaughter design. We thereby assigned two new markers to the public linkage map using the CRI-MAP program. Phenotypic records were daughter yield deviations (DYD) originating from the routinely performed genetic evaluations of breeding animals. To determine the position of the QTL, three different approaches were applied: interval mapping (IM), linkage analysis by variance component analysis (LAVC), and combined linkage disequilibrium (LD) and linkage (LDL) analysis. All three methods mapped the QTL in the same marker interval ( BM2830-ETH152 ) with the greatest test-statistic value at 118, 119.33 and 119.33 cM respectively. The positive QTL allele simultaneously increases DYD in the first lactation by 272 kg milk, 7.1 kg milk protein and 7.0 kg milk fat. Although the mapping accuracy and the significance of a QTL effect increased from IM over LAVC to LDL, the confidence interval was large (13, 20 and 24 cM for FY, MY and PY respectively) for the positional cloning of the causal gene. The estimated averages of pair wise marker LD with a distance <5 cM were low (0.107) and reflect the large effective population size of the Fleckvieh subpopulation analysed. This low level of LD suggests a need for increase in marker density in following fine mapping steps.     

Genome-wide scan for bovine twinning rate QTL using linkage disequilibrium

Twinning is a complex trait with negative impacts on health and reproduction, which cause economic loss in dairy production. Several twinning rate quantitative trait loci (QTL) have been detected in previous studies, but confidence intervals for QTL location are broad and many QTL are unreplicated. To identify genomic regions or genes associated with twinning rate, QTL analysis based on linkage combined with linkage disequilibrium (LLD) and individual marker associations was conducted across the genome using high-throughput single nucleotide polymorphism (SNP) genotypes. A total of 9919 SNP markers were genotyped with 200 sires and sons in 19 half-sib North American Holstein dairy cattle families. After SNPs were genotyped, informative markers were selected for genome-wide association tests and QTL searches. Evidence for twinning rate QTL was found throughout the genome. Thirteen markers significantly associated with twinning rate were detected on chromosomes 2, 5 and 14 ( P  < 2.3 × 10⁻⁵). Twenty-six regions on fourteen chromosomes were identified by LLD analysis at P  < 0.0007. Seven previously reported ovulation or twinning rate QTL were supported by results of single marker association or LLD analyses. Single marker association analysis and LLD mapping were complementary tools for the identification of putative QTL in this genome scan.     

Fine-mapping of a marbling trait to a 2.9-cM region on bovine chromosome 7 in Japanese Black cattle

To locate quantitative trait loci (QTL) for intramuscular fat deposition (marbling) in a local population of Japanese Black cattle, we performed a genome scan using a paternal half-sib family of Bull A. A marbling QTL was mapped in the region flanked by DIK0079 (20.7 cM) and TGLA303 (39.3 cM) on bovine chromosome (BTA) 7, affecting 5.0% of the total family variance. Haplotype analysis of the QTL region revealed that the marbling-increasing Q allele was transmitted from the dam. On the other hand, Bull B, a maternal half-sib of Bull A, did not receive the Q allele from its dam, based on the following findings: (i) a marbling QTL on BTA7 was not detected in the Bull B paternal half-sib family; (ii) recombination between DIK0079 (20.7 cM) and RM006 (25.4 cM) in the QTL region was observed in the maternal chromosome of Bull B; and (iii) the Q -harbouring steers from Bull A exhibited significantly higher marbling than the steers from Bull B and the remaining steers from Bull A. To precisely compare the maternal chromosomes of both bulls, we constructed a bacterial artificial chromosome contig covering the region between DIK0079 and RM006 and developed DNA markers. The recombination occurred between DIK8042 and DIK8044 , indicating that the marbling QTL was in a 2.9-cM region flanked by DIK0079 and DIK8044 .     

Mapping QTL controlling yield and yield components in a spring barley (Hordeum vulgare L.) cross using marker regression

An RFLP map constructed from 99 doubled haploid lines of a cross between two spring barley varieties (Blenheim × Kym) was used to localize quantitative trait loci (QTL) controlling grain yield and yield components by marker regression and single-marker analysis. Trials were conducted over three years. Genotype-by-year interaction was detected for plant grain weight and ear grain weight so they were analysed separately for each year. None was detected for thousand-grain weight and ear grain number so data were pooled over years. A total of eleven QTL were detected for plant grain weight over two years and fourteen for ear grain weight over three years. Seven QTL were detected for plot yield. The locus with the largest effect was on chromosome 2(2H)L and accounted for 19% of the variation in the progeny. Eight QTL were detected for thousand-grain weight and five for ear grain number. Many of the QTL detected were in comparable positions in each year. Yield and yield components were only partly correlated. Comparisons based on common RFLP markers showed that some QTL were found in positions similar to those identified in other studies. For a number of QTL the identification of linked markers provided suitable opportunities for marker-assisted selection and improvement of barley and reference markers with which to analyse the homoeologous chromosome regions of wheat and other cereals.     

A QTL with major effect on milk yield and composition maps to bovine Chromosome 14

A whole genome scan was undertaken in a granddaughter design comprising 1158 progeny-tested bulls in order to map QTL influencing milk yield and composition. In this paper we report the identification of a locus on the centromeric end of bovine Chromosome (Chr) 14, with major effect on fat and protein percentage as well as milk yield. The genuine nature of this QTL was verified using the grand²-daughter design, that is, by tracing the segregating QTL alleles from heterozygous grandsires to their maternal grandsons and confirming the predicted QTL allele substitution effect. Received: 30 December 1997 / Accepted: 21 February 1998     

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.     

Identification and reciprocal introgression of a QTL affecting body mass in mice

The aim of this study was to examine the effects of a QTL in different genetic backgrounds. A QTL affecting body mass on chromosome 6 was identified in an F₂ cross between two lines of mice that have been divergently selected for this trait. The effect of the QTL on mass increased between 6 and 10 weeks of age and was not sex-specific. Body composition analysis showed effects on fat-free dry body mass and fat mass. To examine the effect of this QTL in different genetic backgrounds, the high body mass sixth chromosome was introgressed into the low body mass genetic background and vice versa by repeated marker-assisted backcrossing. After three generations of backcrossing, new F₂ populations were established within each of the introgression lines by crossing individuals that were heterozygous across the sixth chromosome. The estimated additive effect of the QTL on 10-week body mass was similar in both genetic backgrounds and in the original F₂ population (i.e., ~0.4 phenotypic standard deviations); no evidence of epistatic interaction with the genetic background was found. The 95% confidence interval for the location of the QTL was refined to a region of approximately 7 cM between D6Mit268 and D6Mit123.     

Fine mapping quantitative trait loci affecting milk production traits on bovine chromosome 6 in a Chinese Holstein population

To fine map the previously detected quantitative trait loci （QTLs） affecting milk production traits on bovine chromosome 6 （BTA6）, 15 microsatellite markers situated within an interval of 14.3 cM spanning from BMS690 to BM4528 were selected and 918 daughters of 8 sires were genotyped. Two mapping approaches, haplotype sharing based LD mapping and single marker regression mapping, were used to analyze the data. Both approaches revealed a quantitative trait locus （QTL） with significant effects on milk yield, fat yield and protein yield located in the segment flanked by markers BMS483 and MNB209, which spans a genetic distance of 0.6 cM and a physical distance of 1.5 Mb. In addition, the single marker regression mapping also revealed a QTL affecting fat percentage and protein percentage at marker DIK2291. Our fine mapping work will facilitate the cloning of candidate genes underlying the QTLs for milk production traits.     

家禽数量性状基因座定位的研究进展

近二十年来,各种DNA标记技术及相关生物技术的发展和完善为高密度、覆盖面广的连锁图谱的构建及QTL的定位奠定了基础,本就目前世界上建立的几个较有影响的资源家系、各种DNA标记技术、家禽中定位的QTL及存在问题等方面作一综述。     

A functional genomics approach to evaluate candidate genes located in a QTL interval for milk production traits on BTA6

The potential genetic and economic advantage of marker-assisted selection for enhanced production in dairy cattle has provided an impetus to conduct numerous genome scans in order to identify associations between DNA markers and future productive potential. One area of focus has been a quantitative trait locus on bovine chromosome 6 (BTA6) found to be associated with milk yield, milk protein and fat percentage, which has been subsequently fine-mapped to six positional candidate genes. Subsequent investigations have yet to resolve which of the potential positional candidate genes is responsible for the observed associations with productive performance. In this study, we analysed candidate gene expression and the effects of gene knockdown on expression of β- and κ-casein mRNA in a small interfering RNA transfected bovine in vitro mammosphere model. From our expression studies in vivo , we observed that four of the six candidates ( ABCG2 , SPP1 , PKD2 and LAP3 ) exhibited differential expression in bovine mammary tissue over the lactation cycle, but in vitro functional studies indicate that inhibition of only one gene, SPP1 , had a significant impact on milk protein gene expression. These data suggest that the gene product of SPP1 (also known as osteopontin) has a significant role in the modulation of milk protein gene expression. While these findings do not exclude other positional candidates from influencing lactation, they support the hypothesis that the gene product of SPP1 is a significant lactational regulatory molecule.     

数量性状基因座位及其在家禽中的定位

近年来随着现代分子生物学的发展 ,一些高效的分子遗传标记将各种畜禽的遗传图谱研究推向深入。为高密度、覆盖面广的连锁图谱的构建及QTL的定位奠定了基础。有关QTL的基本理论、QTL定位的步骤、QTL的检测方法以及家禽中定位的QTL已经展开了深入的研究 ,但目前QTL定位中存在诸多问题的问题     

A genome scan reveals QTL for growth, fatness, leanness and meat quality in a Duroc-Pietrain resource population

We performed a genome-wide QTL scan for production traits in a line cross between Duroc and Pietrain breeds of pigs, which included 585 F(2) progeny produced from 31 full-sib families genotyped with 106 informative microsatellites. A linkage map covering all 18 autosomes and spanning 1987 Kosambi cM was constructed. Thirty-five phenotypic traits including body weight, growth, carcass composition and meat quality traits were analysed using least square regression interval mapping. Twenty-four QTL exceeded the genome-wide significance threshold, while 47 QTL reached the suggestive threshold. These QTL were located at 28 genomic regions on 16 autosomal chromosomes and QTL in 11 regions were significant at the genome-wide level. A QTL affecting pH value in loin was detected on SSC1 between marker-interval S0312-S0113 with strong statistical support (P < 3.0 x 10(-14)); this QTL was also associated with meat colour and conductivity. QTL for carcass composition and average daily gain was also found on SSC1, suggesting multiple QTL. Seventeen genomic segments had only a single QTL that reached at least suggestive significance. Forty QTL exhibited additive inheritance whereas 31 QTL showed (over-) dominance effects. Two QTL for trait backfat thickness were detected on SSC2; a significant paternal effect was found for a QTL in the IGF2 region while another QTL in the middle of SSC2 showed Mendelian expression.     

QTL and QTL x environment effects on agronomic and nitrogen acquisition traits in rice

Agricultural environments deteriorate due to excess nitrogen application.Breeding for low nitrogen responsive genotypes can reduce soil nitrogen input.Rice genotypes respond variably to soil available nitrogen.The present study attempted quantification of genotype x nitrogen level interaction and mapping of quantitative trait loci (QTLs) associated with nitrogen use efficiency (NUE) and other associated agronomic traits.Twelve parameters were observed across a set of 82 double haploid (DH) lines derived from IR64/Azucena.Three nitrogen regimes namely,native (0 kg/ha; no nitrogen applied),optimum (100 kg/ha) and high (200 kg/ha) replicated thrice were the environments.The parents and DH lines were significantly varying for all traits under different nitrogen regimes.All traits except plant height recorded significant genotype x environment interaction.Individual plant yield was positively correlated with nitrogen use efficiency and nitrogen uptake.Sixteen QTLs were detected by composite interval mapping.Eleven QTLs showed significant QTL x environment interactions.On chromosome 3,seven QTLs were detected associated with nitrogen use,plant yield and associated traits.A QTL region between markers RZ678,RZ574 and RZ284 was associated with nitrogen use and yield.This chromosomal region was enriched with expressed gene sequences of known key nitrogen assimilation genes.