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PubMed2003

Bayesian model choice and search strategies for mapping interacting quantitative trait Loci.

Most complex traits of animals, plants, and humans are influenced by multiple genetic and environmental factors. Interactions among multiple genes play fundamental roles in the genetic control and evolution of complex traits. Statistical modeling of interaction effects in quantitative trait loci (QTL) analysis must accommodate a very large number of potential genetic effects, which presents a major challenge to determining the genetic model with respect to the number of QTL, their positions, and their genetic effects. In this study, we use the methodology of Bayesian model and variable selection to develop strategies for identifying multiple QTL with complex epistatic patterns in experimental designs with two segregating genotypes. Specifically, we develop a reversible jump Markov chain Monte Carlo algorithm to determine the number of QTL and to select main and epistatic effects. With the proposed method, we can jointly infer the genetic model of a complex trait and the associated genetic parameters, including the number, positions, and main and epistatic effects of the identified QTL. Our method can map a large number of QTL with any combination of main and epistatic effects. Utility and flexibility of the method are demonstrated using both simulated data and a real data set. Sensitivity of posterior inference to prior specifications of the number and genetic effects of QTL is investigated.

Bayes Theorem↗
PubMed1999

Bivariate familial correlation analysis of quantitative traits by use of estimating equations: application to a familial analysis of the insulin resistance syndrome.

Familial correlation analysis involving two traits may give a better insight into the etiology of multifactorial syndromes than familial analysis focused on single traits. Significant cross-trait correlations between biological relatives but not between spouses suggest that the two traits share common transmissible factors whereas correlations between spouses additionally suggest the influence of shared lifestyle factors. We apply the Estimating Equations (EE) technique to the estimation of intra-trait and cross-trait familial correlations on two quantitative traits. Unlike maximum likelihood methods, the EE method does not require one to specify the joint distribution of the traits. Estimation of correlations and of their variance involves an iterative three-stage algorithm which converges rapidly. The generalized Wald test can be used to test any specific hypothesis of familial resemblance. This method has great flexibility for handling covariates and incomplete family data. A simulation study indicated that the EE technique performed well in large samples (100 families), both in terms of type I error and coverage probability . However, in small samples (50 families), an increase of the type I error and a decrease of the coverage probability was observed. As an illustration, we applied this technique to a family study of metabolic factors involved in the Insulin Resistance Syndrome (body mass index, insulin, triglycerides, HDL-cholesterol, and diastolic blood pressure). The study was carried out in a sample of 216 healthy nuclear families with > or =2 offspring. The results suggested the existence of a common transmissible (genetic or cultural) factor influencing both body mass index and insulin, whereas the weak clustering of triglycerides and HDL-cholesterol would be more compatible with the influence of shared lifestyle factors.

Algorithms↗
PubMed1995

Interactions between quantitative trait loci in soybean in which trait variation at one locus is conditional upon a specific allele at another.

A large recombinant inbred population of soybean has been characterized for 220 restriction fragment-length polymorphism (RFLP) markers. Values for agronomic traits also have been measured. Quantitative trait loci (QTL) for height, yield, and maturity were located by their linkage to RFLP markers. QTL controlling large amounts of trait variation were analyzed for the dependence of trait variation on particular alleles at a second locus by comparing cumulative distributions of the trait for each genotype (four genotypes per pair of loci). Interesting pairs of loci were analyzed statistically with maximum likelihood and Monte Carlo comparison of additive and epistatic models. For each locus affecting height, variation was conditional upon the presence of a particular allele at a second unlinked locus that itself explained little or no trait variation. The results show that interactions between QTL are frequent and control large effects. Interactions distinguished between different QTL in a single linkage group and between QTL that affect different traits closely linked to one RFLP marker--i.e., distinguished between pleiotropy and closely linked genes. The implications for the evolution of inbreeding plants and for the construction of agronomic breeding strategies are discussed.

Alleles↗
PubMed1999

Confirmed quantitative trait loci for fatness and growth on pig chromosome 4.

Quantitative trait loci (QTLs) with large effects on fatness and growth have been identified previously on pig chromosome 4 in an intercross between the European wild pig and Large White domestic pigs. Two F2 sows, heterozygous for the actual chromosome region, were backcrossed to a Large White boar, and two backcross (BC1) boars were in turn backcrossed to Large White/Landrace sows. One of the boars was heterozygous for an intact wild pig-derived QTL region, whereas the other carried a recombinant haplotype. A total of 85 BC2 animals were produced. Phenotypical measurements included daily weight gain, ultrasonic measurements of fat depth at 70 and 90 kg and several carcass traits. QTL segregation was deduced using 15 markers previously assigned to chromosome 4. Highly significant QTL effects were observed on all fatness traits and on the length of the carcass. A small but significant effect on growth was also observed. The results confirm the presence of one or more QTLs on chromosome 4 affecting fatness and growth. There was a good agreement between the estimates of QTL effects in the F2 and BC2 generations. The results from the recombinant sire family allowed us to map the major QTL effect distal to the recombination breakpoint. We propose that this confirmed QTL with a major effect on fatness is designated FAT1.

Adipose Tissue↗
PubMed2006

Quantitative trait loci analysis of primary cell wall composition in Arabidopsis.

Quantitative trait loci (QTL) analysis was used to identify genes underlying natural variation in primary cell wall composition in Arabidopsis (Arabidopsis thaliana). The cell walls of dark-grown seedlings of a Bay-0 x Shahdara recombinant inbred line population were analyzed using three miniaturized global cell wall fingerprinting techniques: monosaccharide composition analysis by gas chromatography, xyloglucan oligosaccharide mass profiling, and whole-wall Fourier-transform infrared microspectroscopy. Heritable variation and transgression were observed for the arabinose-rhamnose ratio, xyloglucan side-chain composition (including O-acetylation levels), and absorbance for a subset of Fourier-transform infrared wavenumbers. In total, 33 QTL, corresponding to at least 11 different loci controlling dark-grown hypocotyl length, pectin composition, and levels of xyloglucan fucosylation and O-acetylation, were identified. One major QTL, accounting for 51% of the variation in the arabinose-rhamnose ratio, affected the number of arabinan side chains presumably attached to the pectic polysaccharide rhamnogalacturonan I, paving the way to positional cloning of the first gene underlying natural variation in pectin structure. Several QTL were found to be colocalized, which may have implications for the regulation of xyloglucan metabolism. These results demonstrate the feasibility of combining fingerprinting techniques, natural variation, and quantitative genetics to gain original insight into the molecular mechanisms underlying the structure and metabolism of cell wall polysaccharides.

Arabidopsis↗
PubMed2006

Connected populations for detecting quantitative trait loci and testing for epistasis: an application in maize.

Quantitative trait loci (QTL) detection experiments have often been restricted to large biallelic populations. Use of connected multiparental crosses has been proposed to increase the genetic variability addressed and to test for epistatic interactions between QTL and the genetic background. We present here the results of a QTL detection performed on six connected F(2) populations of 150 F(2:3) families each, derived from four maize inbreds and evaluated for three traits of agronomic interest. The QTL detection was carried out by composite interval mapping on each population separately, then on the global design either by taking into account the connections between populations or not. Epistatic interactions between loci and with the genetic background were tested. Taking into account the connections between populations increased the number of QTL detected and the accuracy of QTL position estimates. We detected many epistatic interactions, particularly for grain yield QTL (R(2) increase of 9.6%). Use of connections for the QTL detection also allowed a global ranking of alleles at each QTL. Allelic relationships and epistasis both contribute to the lack of consistency for QTL positions observed among populations, in addition to the limited power of the tests. The potential benefit of assembling favorable alleles by marker-assisted selection are discussed.

Epistasis, Genetic↗
PubMed2000

A primary screen of the bovine genome for quantitative trait loci affecting twinning rate.

An autosomal genome scan for quantitative trait loci (QTL) affecting twinning rate was carried out in the Norwegian Cattle population. Suggestive QTL were detected on Chromosomes (Chr) 5, 7, 12, and 23. Among these, the QTL positions on both Chr 5 and Chr 23 are strongly supported by literature in the field. Our results also confirm previous mapping of a QTL for twinning to Chr 7, but definitely suggest a different location of the QTL on this chromosome. The most convincing QTL peak was observed for a region in the middle part of Chr 5 close to the insulin-like growth factor 1 (IGF1) gene. Since IGF1 plays an important role in the regulation of folliculogenesis, a mutation search was performed by sequencing more than 3.5 kb of the gene in actual families. The sequencing revealed three polymorphisms in noncoding regions of the gene that will be important in fine structure mapping and characterization of the QTL.

Animals↗
PubMed2001

Fine mapping of Ath6, a quantitative trait locus for atherosclerosis in mice.

Ath6 is a novel quantitative trait locus associated with differences in susceptibility to atherosclerosis between C57BL/6J (B6) and C57BLKS/J (BKS) inbred mouse strains. Combining data from an intercross and a backcross (1593 meioses) between mice from B6 and BKS strains and from The Jackson Laboratory interspecific backcross panels, (C57BL/6J x Mus spretus) F1 x C57BL/6J and (C57BL/6J x SPRET/Ei) F1 x SPRET/Ei, we constructed a consensus genetic map and narrowed Ath6 to a 1.07 +/- 0.26 cM interval between the anonymous DNA marker D12Pgn4 and the gene Nmyc1. This region is near the proximal end of murine Chromosome (Chr) 12, which is homologous to the human chromosomal region 2p24-p25. Marker order in the Ath6 region was concordant among the two crosses and The Jackson Laboratory interspecific backcross panels. This high resolution map rules out candidate genes encoding apolipoprotein B, syndecan 1, and Adam17. The two Ath6 crosses have a combined potential resolution of 0.06 cM.

Alleles↗
PubMed2006

Mapping of quantitative trait loci for carcass traits in a Japanese Black (Wagyu) cattle population.

To detect quantitative trait loci (QTL) that influence economically important traits in a purebred Japanese Black cattle population, we performed a preliminary genome-wide scan using 187 microsatellite markers across a paternal half-sib family composed of 258 offspring. We located six QTL at the 1% chromosome-wise level on bovine chromosomes (BTA) 4, 6, 13, 14 and 21. A second screen of these six QTL regions using 138 additional paternal offspring half-sib from the same sire, provided further support for five QTL: carcass weight on BTA14 (22-39 cM), one for rib thickness on BTA6 (27-58 cM) and three for beef marbling score (BMS) on BTA4 (59-67 cM), BTA6 (68-89 cM) and BTA21 (75-84 cM). The location of QTL for subcutaneous fat thickness on BTA13 was not supported by the second screen (P > 0.05). We determined that the combined contribution of the three QTLs for BMS was 10.1% of the total variance. The combined phenotypic average of these three Q was significantly different (P < 0.001) from those of other allele combinations. Analysis of additional half-sib families will be necessary to confirm these QTL.

Animals↗
PubMed2003

Use of a panel of congenic strains to evaluate differentially expressed genes as candidate genes for blood pressure quantitative trait loci.

Candidate gene(s) for multiple blood pressure (BP) quantitative trait loci (QTL) were sought by analysis of differential gene expression patterns in the kidneys of a panel of eight congenic strains, each of which carries a different low-BP QTL allele with a genetic composition that is otherwise similar to that of the hypertensive Dahl salt-sensitive (S) rat strain. First, genes differentially expressed in the kidneys of one-month-old Dahl S and salt-resistant (R) rats were identified. Then, Northern filter hybridization was used to examine the expression patterns of these genes in a panel of congenic strains. Finally, their chromosomal location was determined by radiation hybrid (RH) mapping. Seven out of 37 differentially expressed genes were mapped to congenic regions carrying BP QTLs, but only one of these genes, L-2 hydroxy acid oxidase (Hao2), showed the congenic strain-specific pattern of differential kidney gene expression predicted by its chromosomal location. This data suggests that Hao2 should be examined as a candidate gene for the rat chromosome 2 (RNO2) BP QTL.

Alcohol Oxidoreductases↗
PubMed2026

Identifying Single-Cell Expression Quantitative Trait Loci Using a Bootstrap Penalized Hurdle Model.

BACKGROUND: Expression quantitative trait loci (eQTL) analysis links genetic variants to gene expression levels, helping to uncover how genetic variation contributes to gene regulation. While traditional eQTL analyses rely on bulk RNA-seq data, recent advances in single-cell RNA sequencing (scRNA-seq) have made it possible to detect cell-type-specific eQTLs. However, the inherent sparsity and heterogeneity of scRNA-seq data present major challenges for standard modeling approaches. METHODS: In this paper, we propose a novel statistical framework, Bootstrap Penalized Hurdle regression model (BPHurdle), designed specifically for scRNA-seq data. BPHurdle employs a hurdle modeling framework, where a logistic component accounts for the excess zeros in single-cell expression data, and a Poisson component jointly evaluates the effects of multiple SNPs on positive gene expression levels. RESULTS: Through simulation studies, we show that BPHurdle achieves high accuracy and robustness in identifying regulatory variants. We further demonstrate its utility on a real dataset through a case study focusing on a subset of differentially expressed genes, where it successfully identifies reliable cell-type-specific eQTLs. CONCLUSIONS: Overall, BPHurdle offers an advanced and flexible approach for single-cell eQTL mapping, providing deeper insight into the genetic regulation of gene expression at cellular resolution.

Quantitative Trait Loci↗
PubMed2003

Quantitative trait loci and comparative genomics of cereal cell wall composition.

Quantitative trait loci (QTLs) affecting sugar composition of the cell walls of maize (Zea mays) pericarp were mapped as an approach to the identification of genes involved in cereal wall biosynthesis. Mapping was performed using the IBM (B73 x Mo17) recombinant inbred line population. There were statistically significant differences between B73 and Mo17 in content of xylose (Xyl), arabinose (Ara), galactose (Gal), and glucose. Thirteen QTLs were found, affecting the content of Xyl (two QTLs), Ara (two QTLs), Gal (five QTLs), Glc (two QTLs), Ara + Gal (one QTL), and Xyl + Glc (one QTL). The chromosomal regions corresponding to two of these, affecting Ara + Gal and Ara on maize chromosome 3, could be aligned with a syntenic region on rice (Oryza sativa) chromosome 1, which has been completely sequenced and annotated. The contiguous P1-derived artificial chromosome rice clones covering the QTLs were predicted to encode 117 and 125 proteins, respectively. Two of these genes encode putative glycosyltransferases, displaying similarity to carbohydrate-active enzyme database family GT4 (galactosyltransferases) or to family GT64 (C-terminal domain of animal heparan synthases). The results illustrate the potential of using natural variation, emerging genomic resources, and homeology within the Poaceae to identify candidate genes involved in the essential process of cell wall biosynthesis.

Carbohydrate Metabolism↗
PubMed2006

Further studies on using multiple-cross mapping (MCM) to map quantitative trait loci.

We have completed whole-genome scans for quantitative trait loci (QTLs) associated with acute ethanol-induced activation in the six F(2) intercrosses that can be formed from the C57BL/6J (B6), DBA/2J (D2) , BALB/cJ (C), and LP/J (LP) inbred strains. The goal was to test the hypothesis that given the relatively simple structure of the laboratory mouse genome, the same QTLs will be detected in multiple crosses which in turn will provide support for the strategy of multiple-cross mapping (MCM). QTLs with LOD scores greater than 4 were detected on Chrs 1, 2, 3, 8, 9, 13, 14, and 16. Only for the QTL on distal Chr 1 was there convincing evidence that the same or at least a very similar QTL was detected in multiple crosses. We also mapped the Chr 2 QTL directly in heterogeneous stock (HS) animals derived from the four inbred strains. At G(19) the QTL was mapped to an approximately 3-Mbp interval and this interval was associated with a haplotype block with a largely biallelic structure: B6-L:C-D2. We conclude that mapping in HS animals not only provides significantly greater QTL resolution, at least in some cases it provides significantly more information about the QTL haplotype structure.

Animals↗
PubMed2003

Fine linkage mapping enables dissection of closely linked quantitative trait loci for seed dormancy and heading in rice.

Two quantitative trait loci (QTLs) for seed dormancy (tentatively designated Sdr1) and heading date ( Hd8) have been mapped to approximately the same region on chromosome 3 by interval mapping of backcross inbred lines derived from crosses between the rice cultivars Nipponbare (japonica) and Kasalath (indica). To clarify whether Sdr1 and Hd8 could be dissected genetically, we carried out fine-scale mapping with an advanced backcross progeny. We selected a BC(4)F(1) plant, in which a small chromosomal region including Sdr1 and Hd8, on the short arm of chromosome 3, remained heterozygous, whereas all the other chromosomal regions were homozygous for Nipponbare. Days-to-heading and seed germination rate in the BC(4)F(2) plants showed continuous variation. Ten BC(4)F(2) plants with recombination in the vicinity of Sdr1 and Hd8 were selected on the basis of the genotypes of the restriction fragment length polymorphism (RFLP) markers flanking both QTLs. Genotypes of those plants for Sdr1 and Hd8 were determined by advanced progeny testing of BC(4)F(4) families. Sdr1 was mapped between the RFLP markers R10942 and C2045, and co-segregated with C1488. Hd8 was also mapped between C12534S and R10942. Six recombination events were detected between Sdr1 and Hd8. These results clearly demonstrate that Sdr1 and Hd8 were tightly linked. Nearly isogenic lines for Sdr1 and Hd8 were selected by marker-assisted selection.

Chromosome Mapping↗
PubMed2000

Applicability of a "speed" congenic strategy to dissect blood pressure quantitative trait loci on rat chromosome 2.

The identification of any quantitative trait locus (QTL) via a genome scan is only the first step toward the ultimate goal of gene identification. The next step is the production of congenic strains by which the existence of a QTL may be verified and the implicated chromosomal region be reduced to a size applicable to positional cloning of the causal gene. We used a speed congenic breeding protocol previously verified in mice for 2 blood pressure QTLs on rat chromosome 2. Four congenic strains were produced through introgression of various segments of chromosome 2 from Wistar-Kyoto rats from Glasgow colonies [WKY((Gla)) rats] into the recipient stroke-prone spontaneously hypertensive rats from Glasgow colonies [SHRSP((Gla))], and vice versa. The number of backcross generations required for each strain to achieve complete homozygosity at 83 background genetic markers in a "best" male varied between 3 and 4. Transfer of the region of rat chromosome 2 containing both QTLs from WKY((Gla)) into an SHRSP((Gla)) genetic background lowered both baseline and salt-loaded systolic blood pressure by approximately 20 and approximately 40 mm Hg in male congenic rats compared with the SHRSP parental strain (F=53.4, P<0.005; F=28.0, P< 0.0005, respectively). In contrast, control animals for stowaway heterozygosity presented no deviation from the blood pressure values recorded for the SHRSP((Gla)), indicating that if such heterozygosity exists, its effect on blood pressure is negligible. A reciprocal strategy in which 1 or both QTLs on rat chromosome 2 were transferred from SHRSP((Gla)) into a WKY((Gla)) genetic background resulted in statistically significant but smaller blood pressure increases for 1 of these QTLs. These results confirm the existence of blood pressure QTLs on rat chromosome 2 and demonstrate the applicability of a speed congenic strategy in the rat and emphasize the important role of the genetic background.

Animals↗
PubMed1997

Bivariate quantitative trait linkage analysis: pleiotropy versus co-incident linkages.

Power to detect linkage and localization of a major gene were compared in univariate and bivariate variance components linkage analysis of three related quantitative traits in general pedigrees. Although both methods demonstrated adequate power to detect loci of moderate effect, bivariate analysis improved both power and localization for correlated quantitative traits mapping to the same chromosomal region, regardless of whether co-localization was the result of pleiotropy. Additionally, a test of pleiotropy versus co-incident linkage was shown to have adequate power and a low error rate.

Chromosome Mapping↗
PubMed1996

A bayesian approach to detect quantitative trait loci using Markov chain Monte Carlo.

Markov chain Monte Carlo (MCMC) techniques are applied to simultaneously identify multiple quantitative trait loci (QTL) and the magnitude of their effects. Using a Bayesian approach a multi-locus model is fit to quantitative trait and molecular marker data, instead of fitting one locus at a time. The phenotypic trait is modeled as a linear function of the additive and dominance effects of the unknown QTL genotypes. Inference summaries for the locations of the QTL and their effects are derived from the corresponding marginal posterior densities obtained by integrating the likelihood, rather than by optimizing the joint likelihood surface. This is done using MCMC by treating the unknown QTL, genotypes, and any missing marker genotypes, as augmented data and then by including these unknowns in the Markov chain cycle alone with the unknown parameters. Parameter estimates are obtained as means of the corresponding marginal posterior densities. High posterior density regions of the marginal densities are obtained as confidence regions. We examine flowering time data from double haploid progeny of Brassica napus to illustrate the proposed method.

Bayes Theorem↗
PubMed2006

Sex-specific genetic architecture of asthma-associated quantitative trait loci in a founder population.

Identifying genes that influence susceptibility to asthma-related and atopy-related phenotypes has been challenging, owing to clinical heterogeneity and a complex underlying genetic architecture that includes both gene-gene and gene-environment interactions. In this article, we report the results of genome-wide linkage and association studies of eight asthma-associated quantitative traits in the Hutterites, a founder population of European descent. Our study revealed significant sex-specific genetic architecture for at least five of these traits, and identified 13 genome-wide significant quantitative trait loci (QTL) by linkage or association that are present in only one of the sexes (nine in males, four in females).

Asthma↗