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PubMed2000

The use of a genetic algorithm for simultaneous mapping of multiple interacting quantitative trait loci.

Here we describe a general method for improving computational efficiency in simultaneous mapping of multiple interacting quantitative trait loci (QTL). The method uses a genetic algorithm to search for QTL in the genome instead of an exhaustive enumerative ("step-by-step") search. It can be used together with any method of QTL mapping based on a genomic search, since it only provides a more efficient way to search the genome for QTL. The computational demand decreases by a factor of approximately 130 when using genetic algorithm-based mapping instead of an exhaustive enumerative search for two QTL in a genome size of 2000 cM using a resolution of 1 cM. The advantage of using a genetic algorithm increases further for larger genomes, higher resolutions, and searches for more QTL. We show that a genetic algorithm-based search has efficiency higher than or equal to a search method conditioned on previously identified QTL for all epistatic models tested and that this efficiency is comparable to that of an exhaustive search for multiple QTL. The genetic algorithm is thus a powerful and computationally tractable alternative to the exhaustive enumerative search for simultaneous mapping of multiple interacting QTL. The use of genetic algorithms for simultaneous mapping of more than two QTL and for determining empirical significance thresholds using permutation tests is also discussed.

Algorithms↗
PubMed2003

Efficiency robust tests for mapping quantitative trait loci using extremely discordant sib pairs.

In 1972, Haseman and Elston proposed a pioneering regression method for mapping quantitative trait loci using randomly selected sib pairs. Recently, the statistical power of their method was shown to be increased when extremely discordant sib pairs are ascertained. While the precise genetic model may not be known, prior information that constrains IBD probabilities is often available. We investigate properties of tests that are robust against model uncertainty and show that the power gain from further constraining IBD probabilities is marginal. The additional linkage information contained in the trait values can be incorporated by combining the Haseman-Elston regression method and a robust allele sharing test.

Chromosome Mapping↗
PubMed2001

Genetic architecture of mandible shape in mice: effects of quantitative trait loci analyzed by geometric morphometrics.

This study introduces a new multivariate approach for analyzing the effects of quantitative trait loci (QTL) on shape and demonstrates this method for the mouse mandible. We quantified size and shape with the methods of geometric morphometrics, based on Procrustes superimposition of five morphological landmarks recorded on each mandible. Interval mapping for F(2) mice originating from an intercross of the LG/J and SM/J inbred strains revealed 12 QTL for size, 25 QTL for shape, and 5 QTL for left-right asymmetry. Multivariate ordination of QTL effects by principal component analysis identified two recurrent features of shape variation, which involved the positions of the coronoid and angular processes relative to each other and to the rest of the mandible. These patterns are reminiscent of the knockout phenotypes of a number of genes involved in mandible development, although only a few of these are possible candidates for QTL in our study. The variation of shape effects among the QTL showed no evidence of clustering into distinct groups, as would be expected from theories of morphological integration. Further, for most QTL, additive and dominance effects on shape were markedly different, implying overdominance for specific features of shape. We conclude that geometric morphometrics offers a promising new approach to address problems at the interface of evolutionary and developmental genetics.

Animals↗
PubMed1999

Quantitative trait loci that regulate plasma lipid concentration in hereditary obese KK and KK-Ay mice.

To identify quantitative trait loci (QTLs) responsible for regulating plasma lipid concentration associated with obesity, linkage analysis was carried out on the 190 F2 progeny of a cross between C57BL/6J female and KK-Ay (Ay allele at the agouti locus congenic) male. In F2 a/a (agouti locus genotype) mice, two QTLs were identified on chromosome 1 and a QTL on chromosome 3 for total-cholesterol. A QTL for HDL-cholesterol was identified on chromosome 1 and a QTL for NEFA on chromosome 9. In F2 Ay/a mice, two QTLs for HDL-cholesterol were found on chromosome 1. Loci for other lipids with suggestive linkage were also identified. In both F2 mice, one QTL on chromosome 1 for total- and HDL-cholesterol was mapped near D1Mit150, in the vicinity of the apolipoprotein A-II (Apoa2) locus. Seven nucleotide substitutions out of 309 nucleotide apolipoprotein A-II cDNA sequences were identified between KK and C57BL/6J. The Ay allele may be an indication of the plasma lipid levels, but its influence was less apparent than in the case of weight control. The loci for lipids were not on identical chromosomes with those previously identified for obesity, suggesting that hyperlipidemia in KK does not coincidentally occur with obesity.

Alleles↗
PubMed2005

A wheat intervarietal genetic linkage map based on microsatellite and target region amplified polymorphism markers and its utility for detecting quantitative trait loci.

Efficient user-friendly methods for mapping plant genomes are highly desirable for the identification of quantitative trait loci (QTLs), genotypic profiling, genomic studies, and marker-assisted selection. SSR (microsatellite) markers are user-friendly and efficient in detecting polymorphism, but they detect few loci. Target region amplification polymorphism (TRAP) is a relatively new PCR-based technique that detects a large number of loci from a single reaction without extensive pre-PCR processing of samples. In the investigation reported here, we used both SSRs and TRAPs to generate over 700 markers for the construction of a genetic linkage map in a hard red spring wheat intervarietal recombinant inbred population. A framework map consisting of 352 markers accounted for 3,045 cM with an average density of one marker per 8.7 cM. On average, SSRs detected 1.9 polymorphic loci per reaction, while TRAPs detected 24. Both marker systems were suitable for assigning linkage groups to chromosomes using wheat aneuploid stocks. We demonstrated the utility of the maps by identifying major QTLs for days to heading and reduced plant height on chromosomes 5A and 4B, respectively. Our results indicate that TRAPs are highly efficient for genetic mapping in wheat. The maps developed will be useful for the identification of quality and disease resistance QTLs that segregate in this population.

Chromosome Mapping↗
PubMed2002

Quantitative trait locus mapping of genes that regulate HDL cholesterol in SM/J and NZB/B1NJ inbred mice.

To investigate the quantitative trait loci (QTL) regulating plasma cholesterol, the female progeny of an (SMxNZB/ B1NJ)xNZB/B1NJ backcross were fed an atherogenic diet. After 18 wk, plasma total cholesterol and high-density lipoprotein cholesterol (HDL-C) was measured. HDL-C concentrations were greater in NZB than in SM mice. For standard chow-fed mice, QTL were found near D5Mit370 and D18Mit34. For mice fed an atherogenic diet, a QTL was found near D5Mit239. The QTL for chow-fed and atherogenic-fed mice on chromosome 5 seem to be two different loci. We used a multitrait analysis to rule out pleiotropy in favor of a two-QTL hypothesis. Furthermore, the HDL-C in these strains was induced by the high-fat diet. For inducible HDL-C, one significant locus was found near D15Mit39. The gene for an HDL receptor, Srb1, maps close to the HDL-C QTL at D5Mit370, but the concentrations of Srb1 mRNA and SR-B1 protein and the gene sequence of NZB/B1NJ and SM/J did not support Srb1 as a candidate gene. With these QTL, we have identified chromosomal regions that affect lipoprotein profiles in these strains.

Animals↗
PubMed2006

Confirmation and fine mapping of ethanol sensitivity quantitative trait loci, and candidate gene testing in the LXS recombinant inbred mice.

In previous studies, we have mapped quantitative trait loci (QTLs) for hypnotic sensitivity to ethanol using a small recombinant inbred (RI) panel and a large F(2) backcross. Alcohol sensitivity is a major predictor of long-term risk for alcoholism. We remapped hypnotic sensitivity using a new set of 75 RI strains, the LXS, derived from Inbred Long Sleep and Inbred Short Sleep strains. We expected to improve mapping resolution in the QTL regions and to identify novel QTLs for loss of the righting reflex due to ethanol. We used three common mapping algorithms (R/qtl, QTL Cartographer, and WebQTL) to map QTLs in the LXS, and we compared the results. Most mapping studies use only a single algorithm, an approach that may result in failure to identify minor QTLs. We confirmed most of our previously reported QTLs, although one major QTL from earlier work (Lore2) failed to replicate, possibly because it represented multiple linked genes separated by recombination in the RI strains. We also report narrowed confidence intervals, based on mapping with a new genetic resource of more than 4000 polymorphic single-nucleotide polymorphism markers. These narrowed confidence intervals will facilitate candidate gene identification and assessment of overlap with human regions specifying risk for alcoholism. Finally, we present an approach for using these RI strains to assess evidence for candidate genes in the narrowed intervals, and we apply this method to a strong candidate, the serotonin transporter.

Alcoholism↗
PubMed2003

New quantitative trait loci for the genetic variance in circadian period of locomotor activity between inbred strains of mice.

Provisional quantitative trait loci (QTL) for circadian locomotor period and wheel-running period have been identified in recombinant inbred (RI) mouse strains. To confirm those QTL and identify new ones, the genetic component of variance of the circadian period was partitioned among an F2 intercross of RI mouse strains (BXD19 and CXB07). First, a genomic survey using 108 SSLP markers with an average spacing of 15 cM was carried out in a population of 259 (BXD19 x CXB07)F2 animals. The genome-wide survey identified two significant QTL for period of locomotor activity measured by infrared photobeam crossings on mouse chromosomes 1 (lod score 5.66) and 14 (lod score 4.33). The QTL on distal chromosome 1 confirmed a previous report based on congenic B6.D2-Mtv7a/Ty mice. Lod scores greater than 2.0 were found on chromosomes 1, 2, 6, 12, 13, and 14. In a targeted extension study, additional genotyping was performed on these chromosomes in the full sample of 341 F2 progeny. The 6 chromosome-wide surveys identified 3 additional QTL on mouse chromosomes 6, 12, and 13. The QTL on chromosome 12 overlaps with circadian period QTL identified in several prior studies. For wheel-running period, the chromosome-wide surveys identified QTL on chromosomes 2 and 13 and one highly suggestive QTL on proximal chromosome 1. The results are compared to other published studies of QTL of circadian period.

Animals↗
PubMed2006

Identification of two novel quantitative trait loci for pre-eclampsia susceptibility on chromosomes 5q and 13q using a variance components-based linkage approach.

Pre-eclampsia/eclampsia (PE/E) is a common and serious disorder of human pregnancy that is associated with substantial maternal and perinatal morbidity and mortality. The suspected aetiology of PE/E is complex, with susceptibility being attributable to multiple environmental factors and a large genetic component. By assuming that the underlying liability towards PE/E susceptibility is inherently quantitative, any PE/E susceptibility gene would represent a quantitative trait locus (QTL). This assumption enables a more refined and powerful variance components procedure using a threshold model for our PE/E statistical analysis. Using this more efficient linkage approach, we have now re-analysed our previously completed Australian/New Zealand genome scan data to identify two novel PE/E susceptibility QTLs on chromosomes 5q and 13q. We have obtained strong evidence of linkage on 5q with a peak logarithm-of-odds (LOD) score of 3.12 between D5S644 and D5S433 [at approximately 121 centimorgan (cM)] and strong evidence of linkage on 13q with a peak LOD score of 3.10 between D13S1265 and D13S173 (at approximately 123 cM). Objective identification and prioritization of positional candidate genes using the quantitative bioinformatics program GeneSniffer revealed highly plausible PE/E candidate genes encoding aminopeptidase enzymes and a placental peptide hormone on the 5q QTL and two type IV collagens on the 13q QTL regions, respectively.

Analysis of Variance↗
PubMed2005

qUVR-10, a major quantitative trait locus for ultraviolet-B resistance in rice, encodes cyclobutane pyrimidine dimer photolyase.

Rice qUVR-10, a quantitative trait locus (QTL) for ultraviolet-B (UVB) resistance on chromosome 10, was cloned by map-based strategy. It was detected in backcross inbred lines (BILs) derived from a cross between the japonica variety Nipponbare (UV resistant) and the indica variety Kasalath (UV sensitive). Plants homozygous for the Nipponbare allele at the qUVR-10 locus were more resistant to UVB compared with the Kasalath allele. High-resolution mapping using 1850 F(2) plants enabled us to delimit qUVR-10 to a <27-kb genomic region. We identified a gene encoding the cyclobutane pyrimidine dimer (CPD) photolyase in this region. Activity of CPD photorepair in Nipponbare was higher than that of Kasalath and nearly isogenic with qUVR-10 [NIL(qUVR-10)], suggesting that the CPD photolyase of Kasalath was defective. We introduced a genomic fragment containing the CPD photolyase gene of Nipponbare to NIL(qUVR-10). Transgenic plants showed the same level of resistance as Nipponbare did, indicating that the qUVR-10 encoded the CPD photolyase. Comparison of the qUVR-10 sequence in the Nipponbare and Kasalath alleles revealed one probable candidate for the functional nucleotide polymorphism. It was indicated that single-base substitution in the CPD photolyase gene caused the alteration of activity of CPD photorepair and UVB resistance. Furthermore, we were able to develop a UV-hyperresistant plant by overexpression of the photolyase gene.

Base Sequence↗
PubMed2005

Fine-mapping milk production quantitative trait loci on BTA6: analysis of the bovine osteopontin gene.

Bovine chromosome six (BTA6) harbors up to six quantitative trait loci (QTL) influencing the milk production of dairy cattle. In stark contrast to human, there is long-range linkage disequilibrium in dairy cattle, which has previously made it difficult to identify the mutations underlying these QTL. Using 38 microsatellite markers in a pedigree of 3,147 Holstein bulls, we fine mapped regions of BTA6 that had previously been shown to harbor QTL. Next, we sequenced a 12.3-kb region harboring Osteopontin, a positional candidate for the statistically most significant of the identified QTL. Nine mutations were identified, and only genotypes for the OPN3907 indel were concordant with the QTL genotypes of eight bulls that were established by segregation analysis. Four of these mutations were genotyped, and a joint linkage/linkage disequilibrium mapping analysis was used to demonstrate the existence of only two functionally distinct clusters of haplotypes within the QTL region, which were uniquely defined by OPN3907 alleles. We estimate a probability of 0.40 that no other mutation within this region is concordant with the QTL genotypes of these eight bulls. Finally, we demonstrate that the motif harboring OPN3907, which is upstream of the promoter and within a region known to harbor tissue-specific osteopontin regulatory elements, is moderately conserved among mammals. The motif was not retrieved from database queries and may be a novel regulatory element.

Alleles↗
PubMed2000

Detection of quantitative trait loci for body weight at 10 weeks from Philippine wild mice.

A genome-wide scan for quantitative trait loci (QTLs) controlling body weight at 10 weeks after birth was carried out in a population of 387 intersubspecific backcross mice derived from a cross between C57BL/6J inbred mice (Mus musculus domesticus) and wild mice (M. m. castaneus) captured in the Philippines, in order to discover novel QTLs from the wild mice that have about 60% lower body weight than C57BL/6J. By interval mapping, we detected four QTLs: a highly significant QTL on Chromosome (Chr) 2, which was common in both sexes; two significant QTLs on Chr 13, one male-specific and the other female-specific; and a suggestive male-specific QTL on X Chr. By composite interval mapping, we confirmed the presence of the three QTLs on Chrs 2 and 13, but not of the male-specific X-linked QTL. The composite interval mapping analysis newly identified three QTLs: a significant male-specific QTL on Chr 11 and two highly significant female-specific QTLs on Chrs 9 and X. Individual QTLs explained 3.8-11.6% of the phenotypic variance, and all the QTL alleles derived from the wild mice decreased body weight. A two-way analysis of variance revealed a significant epistatic interaction between the Chr 2 QTL and the background marker locus D12Mit4 on Chr 12 only in males. The interaction effect unexpectedly increased body weight. The chromosomal region containing the Chr 2 QTL did not coincide with those of growth or fatness QTLs mapped in previous studies. These results suggest that a population of wild mice may play an important role as new sources of valuable QTLs.

Animals↗
PubMed2000

On the differences between maximum likelihood and regression interval mapping in the analysis of quantitative trait loci.

The differences between maximum-likelihood (ML) and regression (REG) interval mapping in the analysis of quantitative trait loci (QTL) are investigated analytically and numerically by simulation. The analytical investigation is based on the comparison of the solution sets of the ML and REG methods in the estimation of QTL parameters. Their differences are found to relate to the similarity between the conditional posterior and conditional probabilities of QTL genotypes and depend on several factors, such as the proportion of variance explained by QTL, relative QTL position in an interval, interval size, difference between the sizes of QTL, epistasis, and linkage between QTL. The differences in mean squared error (MSE) of the estimates, likelihood-ratio test (LRT) statistics in testing parameters, and power of QTL detection between the two methods become larger as (1) the proportion of variance explained by QTL becomes higher, (2) the QTL locations are positioned toward the middle of intervals, (3) the QTL are located in wider marker intervals, (4) epistasis between QTL is stronger, (5) the difference between QTL effects becomes larger, and (6) the positions of QTL get closer in QTL mapping. The REG method is biased in the estimation of the proportion of variance explained by QTL, and it may have a serious problem in detecting closely linked QTL when compared to the ML method. In general, the differences between the two methods may be minor, but can be significant when QTL interact or are closely linked. The ML method tends to be more powerful and to give estimates with smaller MSEs and larger LRT statistics. This implies that ML interval mapping can be more accurate, precise, and powerful than REG interval mapping. The REG method is faster in computation, especially when the number of QTL considered in the model is large. Recognizing the factors affecting the differences between REG and ML interval mapping can help an efficient strategy, using both methods in QTL mapping to be outlined.

Chromosome Mapping↗
PubMed1997

Common quantitative trait loci for alcohol-related behaviors and central nervous system neurotensin measures: locomotor activation.

We have analyzed LSXSS recumbinant inbred for ethanol-induced activity using 2.0 g/kg ethanol and a new method we call ethanol activation slope. The ethanol activation slope provides a robust dose-response measure of ethanol activation, independent of both activity after saline and the inhibitory effects of ethanol on locomotor activity. These behavioral data were used in a quantitative trait locus analysis to map chromosomal loci involved in ethanol-induced locomotor activity. We tentatively identified seven loci that mediate the low-dose stimulatory effect of ethanol and six loci involved in locomotion after 2.0 g/kg ethanol. Only one of the loci are in common between the two behaviors. We also compared the behavioral quantitative trait locus to those previously identified that are involved in regulating central nervous system neurotensin levels and neurotensin receptor densities. Six chromosomal regions were identified that regulate at least one central nervous system neurotensin measure and an ethanol-induced locomotor behavior. The identification of loci controlling both central nervous system neurotensin levels or neurotensin receptor densities and ethanol-induced locomotor activity strengthens the proposal that neurotensin regulates, in part, ethanol-induced behaviors and central nervous system sensitivity to ethanol.

Alcoholism↗
PubMed2001

Mapping quantitative trait loci for milk production traits on ovine chromosome 6.

Spanish Churra sheep were studied in a daughter design for the presence on chromosome 6 of quantitative trait loci (QTL) influencing milk production traits. Eight half-sib families were genotyped for 11 microsatellites and marker-QTL effects analysed using yield deviations (YD) as quantitative measurements for the following traits: milk yield, protein yield, and protein percentage. QTL analysis was performed by interval mapping based on multimarker regression principles. Significance thresholds were estimated through a permutation test followed by a correction for multiple testing. The results suggest a region on ovine chromosome 6, close to the casein cluster, with an influence on milk traits and particularly on protein percentage. These results, the first ones reported for QTL affecting milk traits in sheep, are discussed in relation to data available for cattle, a closely related species.

Animals↗
PubMed2004

A quantitative trait locus influencing fasting plasma glucose in chromosome region 18q22-23.

Fasting plasma glucose is a multigenic trait related to both diabetes and obesity. We performed a genome scan for quantitative fasting plasma glucose levels in 320 families (1,514 subjects), segregating extreme obesity and normal weight using 382 autosomal microsatellite markers. We found significant linkages on 18q22-23 using family regression (logarithm of odds [LOD] 3.67, P = 0.00002, D18S1371 at 116 cM) and variance components (LOD 4.48, P < 0.00001) methods. Evidence for linkage remained strong when restricted to European Americans (260 families, 1,258 individuals). After an additional 60 families were added, the linkage signal strengthened (LOD 6.59). The result on 18q22-23 remained significant, even after controlling for both BMI and diabetes status. We also found suggestive linkages on chromosomes 2 (LOD 1.58, 216 cM) and 7 (LOD 1.78, 163 cM). Our results suggest that there is a quantitative trait locus in chromosome region 18q22-23 that influences fasting glucose levels and may play a role in the pathogenesis of type 2 diabetes. The strength of the serum glucose results after controlling for BMI suggests that this putative gene does not influence glucose levels merely through an effect on obesity.

Blood Glucose↗
PubMed2026

X chromosome-wide association studies for quantitative trait loci based on the mixture of general pedigrees and additional unrelated individuals.

Genome-wide association studies have successfully identified many genetic variants associated with complex traits. However, most existing methods target autosomes rather than X chromosome, and several existing X chromosome-wide association studies (XWAS) at quantitative trait loci (QTL) largely focus on unrelated individuals, with limited attention to general pedigrees or mixture of general pedigrees and additional unrelated individuals (called the mixed data for brevity). In this study, we propose nine novel methods for XWAS at QTL in the mixed data (${\mathrm{MQX}}_{\mathrm{cat}}$, ${\mathrm{MQZ}}_{\mathrm{max}}$, ${\mathrm{MT}}_{\mathrm{plinkw}}$, ${\mathrm{MT}}_{\mathrm{chenw}}$, $\mathrm{MwM}3\mathrm{VNA}$, ${\mathrm{MQMVX}}_{\mathrm{cat}}$, ${\mathrm{MQMVZ}}_{\mathrm{max}}$, $\mathrm{MpMV}$, and $\mathrm{McMV}$), also applicable to general pedigrees alone. The first four methods test for mean differences across genotypes; the latter four test for differences in both means and variances; $\mathrm{MwM}3\mathrm{VNA}$ tests for variance differences only. All mean-based and mean-variance-based methods incorporate X chromosome inactivation information, and all nine methods consider genetic relatedness in pedigrees. Simulation studies confirm well-controlled type I error rates, and inclusion of pedigrees significantly improves statistical power. Note that there has been no study focusing on X chromosome for the mixed data or general pedigrees from UK Biobank database, so we apply our proposed methods to this dataset, which identify five total cholesterol (TC)-associated and 13 low-density lipoprotein cholesterol (LDL-C)-associated single nucleotide polymorphisms (SNPs). Linkage disequilibrium (LD) analysis reveals that these SNPs fall into three distinct LD blocks. Functional annotation and gene ontology enrichment analysis reveal 16 and 28 enriched pathways for TC-associated and LDL-C-associated genes, respectively. These methods provide robust and powerful tools for XWAS at QTL in both mixed data and general pedigrees.

Quantitative Trait Loci↗
PubMed2002

Quantitative trait loci (QTL) for lean body mass and body length in MRL/MPJ and SJL/J F(2) mice.

Studies on the genetic mechanisms involved in the regulation of lean body mass (LBM) in mammals are minimal, although LBM is associated with a competent immune system and an overall good (healthy) body functional status. In this study, we performed a high-density genome-wide scan using 633 (MRL/MPJ x SJL/J) F(2) intercross to identify the quantitative trait loci (QTL) involved in the regulation of LBM. We hypothesized that additional QTL can be identified using a different mouse cross (MRL/SJL cross). Ten QTL were identified for LBM on chromosomes (chrs) 2, 6, 7, 9,13 and 14. Of those ten, QTL on chrs 6, 7 and 14 were exclusive to LBM, while QTL on chrs 4 and 11 were exclusively body length. LBM QTL on chrs 2 and 9 overlap with those of size. Altogether, the ten LBM QTL explained 41.2% of phenotypic variance in F(2) mice. Five significantly interacting loci that may be involved in the regulation of LBM were identified and accounted for 24.4% of phenotypic variance explained by the QTL. Five epistatic interactions, contributing 22.9% of phenotypic variance, were identified for body length. Interacting loci on chr 2 may influence LBM by regulating body length. Therefore, epistatic interactions as well as single QTL effects play an important role in the regulation of LBM.

Alleles↗