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PubMed2006

Power of QTL mapping experiments in commercial Atlantic salmon populations, exploiting linkage and linkage disequilibrium and effect of limited recombination in males.

Whereas detection and positioning of genes that affect quantitative traits (quantitative trait loci (QTL)) using linkage mapping uses only information from recombinants in the genotyped generations, linkage disequilibrium (LD) mapping uses historical recombinants. Thus, whereas linkage mapping requires large family sizes to detect and accurately position QTL, LD mapping is more dependent on the number of families sampled from the population. In commercial Atlantic salmon breeding programmes, only a small number of individuals per family are routinely phenotyped for traits such as disease resistance and meat colour. In this paper, we assess the power and accuracy of combined linkage disequilibrium linkage analysis (LDLA) to detect QTL in the commercial population using simulation. When 15 half-sib sire families (each sire mated to 30 dams, each dam with 10 progeny) were sampled from the population for genotyping, we were able to detect a QTL explaining 10% of the phenotypic variance in 85% of replicates and position this QTL within 3 cM of the true position in 70% of replicates. When recombination was absent in males, a feature of the salmon genome, power to detect QTL increased; however, the accuracy of positioning the QTL was decreased. By increasing the number of sire families sampled from the population to be genotyped to 30, we were able to increase both the proportion of QTL detected and correctly positioned (even with no recombination in males). QTL with much smaller effect could also be detected. The results suggest that even with the existing recording structure in commercial salmon breeding programmes, there is considerable power to detect and accurately position QTL using LDLA.

Animals↗

PubMed1998

QTL analysis in plants; where are we now?

We have briefly reviewed the methods currently available for QTL analysis in segregating populations and summarized some of the conclusions arising from such analyses in plant populations. We show that the analytical methods locate QTL with poor precision (10-30 cM), unless the heritability of an individual QTL is high. Also the estimates of the QTL effects, particularly the dominance effects tend to be inflated because only large estimates are significant. Estimates of numbers of QTL per trait are generally low (< 8) for individual trials. This may suggest that there are few QTL but probably reflects the power of the methods. There is no large correlation between the numbers of QTL found and the amount of the variation explained. Of those cases where dominance is measurable, dominance ratios are often > 1, but seldom significantly greater. These latter cases need further analysis. Many QTL map close to candidate genes, and there is growing evidence from synteny studies of corresponding chromosome regions carrying similar QTL in different species. However, unreliability of QTL location may suggest false candidates.

Chromosome Mapping↗

PubMed2005

A comparison of interval mapping procedures including the QTL-cluster mapping.

Using the deterministic sampling, patterns of the log-likelihood surfaces expected in some interval mapping procedures for estimating the position of, and the effect for, QTL(s) were investigated for the situations where a single QTL or closely linked QTLs are contained in a chromosome segment bracketed with two markers. The mapping procedures compared were the conventional, likelihood-based interval mapping (IM), the regression interval mapping (RIM), and the QTL-cluster mapping (CM) in which the conditional probabilities of transmission of the whole segment marked by the flanking markers were taken into consideration. The half-sib design was used here, and several cases of the true genetic model were considered, differing in the number of QTLs contained in the marker interval, the linkage phase for the sire, and the magnitude of the QTL(s) effect. For the true genetic models where a single QTL or closely linked QTLs being in coupling phase are contained in the interval, with (R)IM, clear global maxima of the log-likelihood were observed within the range of the marker interval. It was shown that the estimates of the QTL(s) effect at the marked segment level are expected to be unbiased. On the other hand, in a setting where the linkage phase for the linked QTLs located in the interval was different from coupling and repulsion, there was found a ridge along the interval for the log-likelihood surface with (R)IM, indicating the dependency between the estimates of the position of, and the effect for, the putative QTL. For this case, it was found that the position of the putative QTL could be estimated as that of one of the flanking markers, and the estimate of the QTL effect be biased. In contrast, it was revealed that CM is expected to provide the unbiased estimate of the QTL(s)-effect at the segment level for any case of the true genetic models considered here. If the aim is for marker-assisted selection rather than mapping closely linked QTLs individually, then the CM approach is considered to be useful.

Chromosome Mapping↗

PubMed2002

[Molecular mapping of quantitative trait loci (QTL) for characters of vascular bundles in peduncle related to indica-japonica differentiation in rice (Oryza sativa L.)].

A doubled-haploid population, consisting of 81 DH lines derived from the F1 hybrid of a cross between an indica cultivar and a japonica cultivar, was used to map quantitative trait loci (QTL) controlling numbers of vascular bundles in peduncle, primary rachis branches and the ratio of vascular bundles to primary rachis branches (V/R ratio). For vascular bundles, three QTL were detected. Among them, the QTL qVB-8 with the largest effect individually accounted for 31.1% of the total variation. Two QTL controlling primary rachis branches were identified and they were co-located with 2 of the 3 QTL for vascular bundles respectively. Three QTL for the V/R ratio were mapped on chromosome 1, 2 and 8, respectively. Of the three QTL, the QTL qV/R-1 with the largest additive effect, explained 25.3% of the total variation, was located on chromosome 1 and found to be closely linked to the gene sh-2, a major gene underlying grain-shattering ability. In addition, four and two pairs of significant epistatic QTL were detected for vascular bundles and the V/R ratio, respectively, but none for rachis branches. Our results suggested that the numbers of vascular bundles and primary rachis branches were independently controlled by different polygenic systems, but the two polygenic systems shared a fraction of quantitative trait loci. It was also shown that the chromosome region carrying the QTL qV/R-1 on chromosome 1 might play an important role in the processes of indica-japonica differentiation in rice.

Chromosome Mapping↗

PubMed2003

QTL x environment interactions in rice. I. heading date and plant height.

One hundred twenty six doubled-haploid (DH) rice lines were evaluated in nine diverse Asian environments to reveal the genetic basis of genotype x environment interactions (GEI) for plant height (PH) and heading date (HD). A subset of lines was also evaluated in four water-limited environments, where the environmental basis of G x E could be more precisely defined. Responses to the environments were resolved into individual QTL x environment interactions using replicated phenotyping and the mixed linear-model approach. A total of 37 main-effect QTLs and 29 epistatic QTLs were identified. On average, these QTLs were detectable in 56% of the environments. When detected in multiple environments, the main effects of most QTLs were consistent in direction but varied considerably in magnitude across environments. Some QTLs had opposite effects in different environments, particularly in water-limited environments, indicating that they responded to the environments differently. Inconsistent QTL detection across environments was due primarily to non- or weak-expression of the QTL, and in part to significant QTL x environment interaction effects in the opposite direction to QTL main effects, and to pronounced epistasis. QTL x environment interactions were trait- and gene-specific. The greater GEI for HD than for PH in rice were reflected by more environment-specific QTLs, greater frequency and magnitude of QTL x environment interaction effects, and more pronounced epistasis for HD than for PH. Our results demonstrated that QTL x environment interaction is an important property of many QTLs, even for highly heritable traits such as height and maturity. Information about QTL x environment interaction is essential if marker-assisted selection is to be applied to the manipulation of quantitative traits.

Chromosome Mapping↗

PubMed2004

Detection and mapping of QTL for earliness components in a bread wheat recombinant inbred lines population.

Earliness, an adaptative trait and factor of variation for agronomic characters, is a major trait in plant breeding. Its constituent traits, photoperiod sensitivity (PS), vernalization requirement (VR) and intrinsic earliness (IE), are largely under independent genetic controls. Mapping of major genes and quantitative trait loci (QTL) controlling these components is in progress. Most of the studies focusing on earliness considered it as a whole or through one (or two) of its components. The purpose of this study was to detect and map QTL for the three traits together through an experimental design combining field trials and controlled growth conditions. QTL were mapped in a population of F(7) recombinant inbred lines derived by single-seed descent from a cross between two French varieties, 'Renan' and 'Recital'. A map was previously constructed, based on 194 lines and 254 markers, covering about 77% of the genome. Globally, 13 QTL with a LOD>2.5 were detected, of which four control PS, five control VR and four control IE. Two major photoperiod sensitive QTL, together explaining more than 31% of the phenotypic variation, were mapped on chromosomes 2B and 2D, at the same position as the two major genes Ppd-B1 and Ppd-D1. One major VR QTL explaining (depending on the year) 21.8-39.6% of the phenotypic variation was mapped on 5A. Among the other QTL, two QTL of PS and VR not referenced so far were detected on 5A and 6D, respectively. A VR QTL already detected on 2B in a connected population was confirmed.

Bread↗

PubMed2004

QTL analyses of drought tolerance and growth for a Salix dasyclados x Salix viminalis hybrid in contrasting water regimes.

Quantitative trait loci (QTL) for growth traits and water-use efficiency have been identified in two water regimes (normal and drought-treated) and for a treatment index. A tetraploid hybrid F2 population originating from a cross between a Salix dasyclados clone (SW901290) and a Salix viminalis clone ('Jorunn') was used in the study. The growth response of each individual including both above and below ground dry-matter production (i.e. shoot length, shoot diameter, aboveground and root dry weight, internode length, root dry weight/total dry weight, relative growth rate and leaf nitrogen content) was analysed in a replicated block experiment with two water treatments. A composite interval mapping approach was used to estimate number of QTL, the magnitude of the QTL and their position on genetic linkage maps. QTL specific for each treatment and for the treatment index were found, but QTL common across the treatments and the treatment index were also detected. Each QTL explained from 8% to 29% of the phenotypic variation, depending on trait and treatment. Clusters of QTL for different traits were mapped close to each other at several linkage groups, indicating either a common genetic base or tightly linked QTL. Common QTL identified between treatments and treatment index in the complex trait dry weight can be useful tools in the breeding and selection for drought stress tolerance in Salix.

Biomass↗

PubMed2005

Mapping of QTL associated with chilling tolerance during reproductive growth in soybean.

Low temperatures in summer bring about drastic reduction in seed yield of soybean [Glycine max (L.) Merr.]. To identify quantitative trait loci (QTL) associated with chilling tolerance during the reproductive growth in soybean, a recombinant inbred line (RIL) population consisting of 104 F(6)-derived lines was created from a cross between two cultivars, chilling-tolerant Hayahikari and chilling-sensitive Toyomusume. The RIL were genotyped with 181 molecular and phenotypic markers and were scored with regard to chilling tolerance, which was evaluated by comparison of seed-yielding abilities in two artificial climatic environments at chilling and usual temperatures. Three QTL were detected for chilling tolerance in seed-yielding ability. Two of them, qCTTSW 1 and qCTTSW 2, were mapped near QTL for flowering time, and the latter had an epistatic interaction with a marker locus located near another QTL for flowering time, where no significant QTL for chilling tolerance was detected. The analysis of an F(2) population derived from the cross between Hayahikari and an RIL of the Hayahikari genotype at all QTL for flowering time confirmed the effect of the third QTL, qCTTSW 3, on chilling tolerance and suggested that qCTTSW 1 was basically independent of the QTL for flowering time. The findings and QTL found in this study may provide useful information for marker-assisted selection (MAS) and further genetic studies on soybean chilling tolerance.

Acclimatization↗

PubMed2005

Novel quantitative trait loci (QTL) for Fusarium head blight resistance in wheat cultivar Chokwang.

Fusarium head blight (FHB) is one of the most destructive diseases in wheat. This study was to identify new quantitative trait loci (QTL) for FHB resistance and the molecular markers closely linked to the QTL in wheat cultivar Chokwang. The primers of 612 simple sequence repeats (SSRs) and 12 target-region-amplified polymorphism (TRAP) marker were analyzed between resistant (Chokwang) and susceptible (Clark) parents. One hundred and seventy-two polymorphic markers were used to screen a population of 79 recombinant inbred lines (RILs) derived from the cross of Chokwang and Clark. One major QTL, Qfhb.ksu-5DL1, was identified on chromosome 5DL. The SSR marker Xbarc 239 was mapped in the QTL region, and also physically located to the bin of 5DL1-0.60-0.74 by using Chinese Spring deletion lines. Another QTL Qfhb.ksu-4BL1was linked to SSR Xbarc 1096 and tentatively mapped on 4BL. A QTL on 3BS, Qfhb.ksu-3BS1, was also detected with marginal significance in this population. Different marker alleles for these QTL were detected between Chokwang and Sumai 3 and its derivatives. These results suggested that Chokwang contains new QTL for FHB resistance that are different from those in Sumai 3. Pyramiding resistance QTL from various sources may enhance FHB resistance in wheat cultivars.

Crosses, Genetic↗

PubMed2006

Mapping QTLs and QTL x environment interaction for CIMMYT maize drought stress program using factorial regression and partial least squares methods.

The study of QTL x environment interaction (QEI) is important for understanding genotype x environment interaction (GEI) in many quantitative traits. For modeling GEI and QEI, factorial regression (FR) models form a powerful class of models. In FR models, covariables (contrasts) defined on the levels of the genotypic and/or environmental factor(s) are used to describe main effects and interactions. In FR models for QTL expression, considerable numbers of genotypic covariables can occur as for each putative QTL an additional covariable needs to be introduced. For large numbers of genotypic and/or environmental covariables, least square estimation breaks down and partial least squares (PLS) estimation procedures become an attractive alternative. In this paper we develop methodology for analyzing QEI by FR for estimating effects and locations of QTLs and QEI and interpreting QEI in terms of environmental variables. A randomization test for the main effects of QTLs and QEI is presented. A population of F2 derived F3 families was evaluated in eight environments differing in drought stress and soil nitrogen content and the traits yield and anthesis silking interval (ASI) were measured. For grain yield, chromosomes 1 and 10 showed significant QEI, whereas in chromosomes 3 and 8 only main effect QTLs were observed. For ASI, QTL main effects were observed on chromosomes 1, 2, 6, 8, and 10, whereas QEI was observed only on chromosome 8. The assessment of the QEI at chromosome 1 for grain yield showed that the QTL main effect explained 35.8% of the QTL + QEI variability, while QEI explained 64.2%. Minimum temperature during flowering time explained 77.6% of the QEI. The QEI analysis at chromosome 10 showed that the QTL main effect explained 59.8% of the QTL + QEI variability, while QEI explained 40.2%. Maximum temperature during flowering time explained 23.8% of the QEI. Results of this study show the possibilities of using FR for mapping QTL and for dissecting QEI in terms of environmental variables. PLS regression is efficient in accounting for background noise produced by other QTLs.

Chromosome Mapping↗

PubMed2005

Identification and validation of QTL for Sclerotinia midstalk rot resistance in sunflower by selective genotyping.

Midstalk rot, caused by Sclerotinia sclerotiorum (Lib.) de Bary, is an important cause of yield loss in sunflower (Helianthus annuus L.). Objectives of this study were to: (1) estimate the number, genomic positions and genetic effects of quantitative trait loci (QTL) for resistance to midstalk rot in line TUB-5-3234, derived from an interspecific cross; (2) determine congruency of QTL between this line and other sources of resistance; and (3) make inferences about the efficiency of selective genotyping (SG) in detecting QTL conferring midstalk rot resistance in sunflower. Phenotypic data for three resistance (stem lesion, leaf lesion and speed of fungal growth) and two morphological (leaf length and leaf length with petiole) traits were obtained from 434 F3 families from cross CM625 (susceptible) x TUB-5-3234 (resistant) under artificial infection in field experiments across two environments. The SG was applied by choosing the 60 most resistant and the 60 most susceptible F3 families for stem lesion. For genotyping of the respective F2 plants, 78 simple sequence repeat markers were used. Genotypic variances were highly significant for all traits. Heritabilities and genotypic correlations between reMidstalk rot, caused by Sclerotinia sclerotiorum (Lib.) de Bary, is an important cause of yield loss in sunflower (Helianthus annuus L.). Objectives of this study were to: (1) estimate the number, genomic positions and genetic effects of quantitative trait loci (QTL) for resistance to midstalk rot in line TUB-5-3234, derived from an interspecific cross; (2) determine congruency of QTL between this line and other sources of resistance; and (3) make inferences about the efficiency of selective genotyping (SG) in detecting QTL conferring midstalk rot resistance in sunflower. Phenotypic data for three resistance (stem lesion, leaf lesion and speed of fungal growth) and two morphological (leaf length and leaf length with petiole) traits were obtained from 434 F3 families from cross CM625 (susceptible) x TUB-5-3234 (resistant) under artificial infection in field experiments across two environments. The SG was applied by choosing the 60 most resistant and the 60 most susceptible F3 families for stem lesion. For genotyping of the respective F2 plants, 78 simple sequence repeat markers were used. Genotypic variances were highly significant for all traits. Heritabilities and genotypic correlations between resistance traits were moderate to high. Three to four putative QTL were detected for each resistance trait explaining between 40.8% and 72.7% of the genotypic variance (PTS). Two QTL for stem lesion showed large genetic effects and corroborated earlier findings from the cross NDBLOSsel (resistant) x CM625 (susceptible). Our results suggest that SG can be efficiently used for QTL detection and the analysis of congruency for resistance genes across populations.

Ascomycota↗

PubMed2006

QTL analysis of yield traits in an advanced backcross population derived from a cultivated Andean x wild common bean (Phaseolus vulgaris L.) cross.

Advanced backcross QTL analysis was used to identify quantitative trait loci (QTL) for agronomic performance in a population of BC2F(3:5) introgression lines created from the cross of a Colombian large red-seeded commercial cultivar, ICA Cerinza, and a wild common bean accession, G24404. A total of 157 lines were evaluated for phenological traits, plant architecture, seed weight, yield and yield components in replicated trials in three environments in Colombia and genotyped with microsatellite, SCAR, and phaseolin markers that were used to create a genetic map that covered all 11 linkage groups of the common bean genome with markers spaced at an average distance of every 10.4 cM. Segregation distortion was most significant in regions orthologous for a seed coat color locus (R-C) on linkage group b08 and two domestication syndrome genes, one on linkage group b01 at the determinacy (fin) locus and the other on linkage group b02 at the seed-shattering (st) locus. Composite interval mapping analysis identified a total of 41 significant QTL for the eight traits measured of which five for seed weight, two for days to flowering, and one for yield were consistent across two or more environments. QTL were located on every linkage group with b06 showing the greatest number of independent loci. A total of 13 QTL for plant height, yield and yield components along with a single QTL for seed size showed positive alleles from the wild parent while the remaining QTL showed positive alleles from the cultivated parent. Some QTL co-localized with regions that had previously been described to be important for these traits. Compensation was observed between greater pod and seed production and smaller seed size and may have resulted from QTL for these traits being linked or pleiotropic. Although wild beans have been used before to transfer biotic stress resistance traits, this study is the first to attempt to simultaneously obtain a higher yield potential from wild beans and to analyze this trait with single-copy markers. The wild accession was notable for being from a unique center of diversity and for contributing positive alleles for yield and other traits to the introgression lines showing the potential that advanced backcrossing has in common bean improvement.

Chromosome Mapping↗

PubMed2006

Conditional QTL mapping of oil content in rapeseed with respect to protein content and traits related to plant development and grain yield.

Oil content in rapeseed (Brassica napus L.) is generally regarded as a character with high heritability that is negatively correlated with protein content and influenced by plant developmental and yield related traits. To evaluate possible genetic interrelationships between these traits and oil content, QTL for oil content were mapped using data on oil content and on oil content conditioned on the putatively interrelated traits. Phenotypic data were evaluated in a segregating doubled haploid population of 282 lines derived from the F(1) of a cross between the old German cultivar Sollux and the Chinese cultivar Gaoyou. The material was tested at four locations, two each in Germany and in China. QTLMapper version 1.0 was used for mapping unconditional and conditional QTL with additive (a) and locus pairs with additive x additive epistatic (aa) effects. Clear evidence was found for a strong genetic relationship between oil and protein content. Six QTL and nine epistatic locus pairs were found, which had pleiotropic effects on both traits. Nevertheless, two QTL were also identified, which control oil content independent from protein content and which could be used in practical breeding programs to increase oil content without affecting seed protein content. In addition, six additional QTL with small effects were only identified in the conditional mapping. Some evidence was apparent for a genetic interrelationship between oil content and the number of seeds per silique but no evidence was found for a genetic relationship between oil content and flowering time, grain filling period or single seed weight. The results indicate that for closely correlated traits conditional QTL mapping can be used to dissect the genetic interrelationship between two traits at the level of individual QTL. Furthermore, conditional QTL mapping can reveal additional QTL with small effects that are undetectable in unconditional mapping.

Brassica rapa↗

PubMed2006

Pyramiding and dissecting disease resistance QTL to barley stripe rust.

Quantitative resistance (QR) to disease is usually more durable than qualitative resistance, but its genetic basis is not well understood. We used the barley/barley stripe rust pathosystem as a model for the characterization of the QR phenotype and associated genomic regions. As an intermediate step in the preparation of near-isogenic lines representing individual QTL alleles and combinations of QTL alleles in a homogeneous genetic background, we developed a set of QTL introgression lines in a susceptible background. These intermediate barley near-isogenic (i-BISON) lines represent disease resistance QTL combined in one-, two-, and three-way combinations in a susceptible background. We measured four components of disease resistance on the i-BISON lines: latent period, infection efficiency, lesion size, and pustule density. The greatest differences between the target QTL introgressions and the susceptible controls were for the latter three traits. On average, however, the QTL introgressions also had longer latent periods than the susceptible parent (Baronesse). There were significant differences in the magnitudes of effects of different QTL alleles. The 4H QTL allele had the largest effect, followed by the alleles on 1H and 5H. Pyramiding multiple QTL alleles led to higher levels of resistance in terms of all components of QR except latent period.

Alleles↗

PubMed2003

Tests of candidate genes in breed cross populations for QTL mapping in livestock.

In recent years, several F(2) crosses between outbred lines of livestock have been developed to identify quantitative trait loci (QTL). These populations are valuable for further genetic analysis, including positional candidate gene loci (CGL). Analysis of CGL in F(2) populations is, however, hindered by extensive between-breed linkage disequilibrium (LD). The objectives here were to develop and evaluate three tests for CGL in simulated F(2) breed-cross populations. 1) A standard association test, based on the fixed effect of CGL genotype. This test was significant for CGL at considerable distances from the QTL. 2) A marker-assisted association test, based on a test at the CGL of the fixed effect of CGL genotype in a breed-cross QTL interval mapping model. This removed the impact of between-breed LD, but was not powerful in detecting CGL closely linked to the QTL, unless the CGL was the QTL. 3) An F-drop test, comparing F ratios for a QTL at the CGL with and without the CGL included as fixed effect. It had low power to distinguish close from distant CGL. Power to distinguish two CGL within 10 cM from the QTL was limited and little improved by including QTL effects associated with markers to remove between-breed LD, although the power was greater when one of the CGL was the causative mutation. Therefore, while we conclude that candidate gene tests in QTL mapping populations must be interpreted with caution, we now have a clearer picture of the value of candidate gene tests in these populations.

Animals↗

PubMed2005

Mapping the dominant wound healing and soft tissue regeneration QTL in MRL x CAST.

We have used a mouse ear punch model and the QTL (quantitative trait loci) mapping technique to identify genes that are responsible for soft tissue regeneration. In the early studies, we have identified several QTL and have shown that the inheritance of ear healing was additive in one cross (MRL x SJL), and recessive in another cross (DBA x 129). Because CAST mice are genetically distinct and have a different genetic background, CAST would facilitate the identification of common and novel QTL when crossed with common inbred lines. We made a cross between super healer MRL and poor healer CAST and collected ear punch phenotype and marker genotype data from F(2). Ear punch healing exhibited a dominant mode of inheritance in this cross. There were three main QTL on Chromosomes 4, 9, and 17, and two suggestive QTL on Chromosomes 1 (new) and 7. Taken together, these QTL accounted for about 29% of total F2 variance of MRL x CAST. Compared with another study using the same cross, we found a totally different set of QTL. Two QTL interactions were identified by a full QTL model: Chromosomes 4 x 17 and 9 x 17; the latter reached to a statistical level at p < 0.05. These interactions explained about 4% of the F2 phenotypic variance. We conclude that soft tissue regeneration is controlled by multiple genes and locus vs. locus interactions.

Animals↗

PubMed2006

Investigation of a QTL region for loin eye area and fatness on pig chromosome 1.

Previously, quantitative trait loci (QTL) for tenth-rib backfat (TENTHRIB) and loin eye area (LEA) were identified on pig Chromosome 1 (SSC 1) near microsatellite S0008 from a three-generation Berkshire x Yorkshire cross (BY). This work attempted to refine these QTL positions and identify genes associated with these QTL. Genotypes of BY (n = 555) were determined by PCR-RFLP or PCR tests for 13 polymorphisms identified in BY F(0) individuals for candidate genes, BAC end sequences, and genomic clones. Using least-squares regression interval mapping, the LEA QTL was estimated at S0008; the TENTHRIB QTL position was shifted approximately 1 cM downstream from S0008. Of the genes/sequences mapped in the QTL region, CL349415 was significantly associated with TENTHRIB (p = 0.02) and solute carrier family 2, member 12 (SLC2A12) was significantly associated with LEA (p = 0.02). These results suggest that the gene(s) responsible for the LEA and TENTHRIB QTL effects are tightly linked to S0008 or that the high informativeness of S0008 relative to surrounding markers is influencing the QTL position estimates. In addition, janus kinase 2 (JAK2) was mapped to a suggestive LEA QTL region and showed association with LEA (p = 0.009), fatness, color, and pH traits in BY.

Animals↗

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↗