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PubMed2003

Detection of QTL affecting fatty acid composition in the pig.

We present a QTL genome scan for fatty acid composition in pigs. An F2 cross between Iberian x Landrace pigs and a regression approach fitting the carcass weight as a covariate for QTL identification was used. Chromosomes (Chrs) 4, 6, 8, 10, and 12 showed highly significant effects. The Chr 4 QTL influenced the linoleic content and both the fatty acid double-bond index and peroxidability index. In Chr 6 we found significant associations with the double-bond index and the unsaturated index of fatty acids. Chr 8 showed clear effects on the percentages of palmitic and palmitoleic fatty acids as well as the average chain length of fatty acids. In Chr 10 we detected a significant QTL for the percentage of myristic fatty acid, with an F value that was slightly above the genomewide threshold. The percentage of linolenic fatty acid was affected by a region on Chr 12. A nearly significant QTL for the content of gadoleic fatty acid was also detected in Chr 12. We also analyzed the genomic QTL distribution by a regression model that fits the backfat thickness as a covariate. Some of the QTL that were detected in our analysis could not be detected when the data were corrected by backfat thickness. This work shows how critical the selection of a covariate can be in the interpretation of results. This is the first report of a genome scan detection of QTL directly affecting fatty acid composition in pigs.

Animals↗

PubMed2003

Characterization of a QTL affecting skeletal size in mice.

Previous work identified a tail length QTL on Chromosome (Chr) 1 in an F(2) population of C57BL/6J x DBA/2J mice. The goals of the present study were to (1) refine the position of this QTL by additional genotyping of samples from the original study; (2) confirm the effect of this QTL by producing a partially congenic strain carrying the C57BL/6J allele against the DBA/2J background; and (3) examine the effect of the QTL on skeletal dimensions. The presence of the QTL was confirmed in a new F(2) population (N = 431) derived from the partially congenic strain, and estimates of its additive effects were similar to those from the original F(2) population (N = 901) in both sexes, i.e., the C57BL/6J chromosomal segment increased tail length, the additive effect (half the difference between homozygotes) being 0.5-0.8 standard deviations. The QTL region was more than halved, relative to that in the previous study, to an 8-cM region between D1Mit30 and D1Mit57. Among a subsample of individuals (N = 30) from the new F(2) population that were not recombinant within the QTL region, there was a significant additive effect of the QTL on the length of the humerus, femur, tibia, mandible, scapula, pelvic girdle, and a tail bone; the direction of the effect was the same as for tail length. No significant effect was found on the number of bones in the tail or on the dimensions of the ulna, skull, or first vertebra.

Animals↗

PubMed2004

New retinal light damage QTL in mice with the light-sensitive RPE65 LEU variant.

The purpose of this study was to determine the QTL that influence acute, light-induced retinal degeneration differences between the BALB/cByJ and 129S1/SvImJ mouse strains. Five- to 6-week-old F(2) progeny of an intercross between the two strains were exposed to 15,000 LUX of white light for 1 h after their pupils were dilated, placed in the dark for 16 h, and kept for 10-12 days in dim cyclic light before retinal rhodopsin was measured spectrophotometrically. This was used as the quantitative trait for retinal degeneration. Neither gender nor pigmentation had a significant influence on the amount of rhodopsin after light exposure in the F(2) progeny. For genetic study, DNAs of the 27-36 F(2) progeny with the highest and 27-36 F(2) with the lowest levels of rhodopsin after light exposure were genotyped with 71 dinucleotide repeat markers spanning the genome. Any marker with a 95% probability of being associated with phenotype was tested in all 289 F(2) progeny. Data were analyzed with Map Manager QTX. Significant QTL were found on mouse Chrs 1 and 4, and suggestive QTL on Chrs 6 and 2. The four QTL together equal an estimated 78% of the total genetic effect, and each of the QTL represents a gene with BALB/c susceptible alleles. The Chr 6 QTL is in the same region as a highly significant age-related retinal degeneration QTL found previously. Identification of these QTL is a first step toward identifying the modifier genes/alleles they represent, and identification of the modifiers may provide important information for human retinal diseases that are accelerated by light exposure.

Alleles↗

PubMed2004

Genetic complexity of an obesity QTL ( Fob3) revealed by detailed genetic mapping.

Obesity is proving to be a serious health concern in the developed world as well as an unwanted component of growth in livestock production. While recent advances in genetics have identified a number of monogenic causes of obesity, these are responsible for only a small proportion of human cases of obesity. By divergent selection for high and low fat content over 60 generations, we have created Fat (F) and Lean (L) lines of mice that represent a model of polygenic obesity similar to the situation in human populations. From previous crosses of these lines, four body fat quantitative trait loci (QTL) were identified. We have created congenic lines (F(chr15L)), by recurrent marker-assisted backcrossing, to introgress the QTL region with the highest LOD score, Fob3 on Chr 15, from the L-Iine into the F-line background. We have further mapped this QTL by progeny testing of recombinants, produced from crosses between the F-line and congenic F(chrl5L) mice, showing that the Fob3 QTL region is a composite of at least two smaller effect QTL-the proximal QTL Fob3a is a late-onset obesity QTL, whereas the distal Fob3b is an early-onset obesity QTL.

Analysis of Variance↗

PubMed2004

Fine mapping of a murine growth locus to a 1.4-cM region and resolution of linked QTL.

Previous work identified a QTL affecting murine size (particularly tail length) in a cross between C57BL/6J and DBA/2J mice and refined its location to an 8-cM region between D1Mit30 and D1Mit57. The present study used recombinant progeny testing to fine map this QTL. Individuals from a partially congenic strain carrying chromosomes recombinant between D1Mit30 and D1Mit57 were mated to DBA/2J, generating 942 progeny. Two QTL affecting 10-week tail length were identified in this population: one at 9.7 cM distal to D1Mit30 (the position estimated in previous work), and another of smaller effect near D1Mit30. A second population ( n = 787) was generated by mating siblings from the progeny test population that were heterozygous for the same segment of chromosome, including only recombinants between D1Mit265 and D1Mit57. In the latter population, two QTL were also identified: one at 10.2 cM distal to D1Mit30, and another of smaller effect at the distal end of the mapped region (at D1Mit150). When the two populations were analyzed together, the estimated location of the central QTL was 10.2 cM distal to D1Mit30 and there was marginally significant evidence of the distal QTL. The central QTL explained approximately 7% of the phenotypic variance, and the 95% confidence interval for its position (determined by bootstrapping) was a 1.4-cM region, approximately the region from D1Mit451 to D1Mit219. The central QTL also affected tail length and body mass at 3 and 6 weeks of age, but to a lesser degree than 10-week tail length.

Animals↗

PubMed2005

A QTL resource and comparison tool for pigs: PigQTLDB.

During the past decade, efforts to map quantitative trait loci (QTL) in pigs have resulted in hundreds of QTL being reported for growth, meat quality, reproduction, disease resistance, and other traits. It is a challenge to locate, interpret, and compare QTL results from different studies. We have developed a pig QTL database (PigQTLdb) that integrates available pig QTL data in the public domain, thus, facilitating the use of this QTL data in future studies. We also developed a pig trait classification system to standardize names of traits and to simplify organization and searching of the trait data. These steps made it possible to compare primary data from diverse sources and methods. We used existing pig map databases and other publicly available data resources (such as PubMed) to avoid redundant developmental work. The PigQTLdb was also designed to include data representing major genes and markers associated with a large effect on economically important traits. To date, over 790 QTL from 73 publications have been curated into the database. Those QTL cover more than 300 different traits. The data have been submitted to the Entrez Gene and the Map Viewer resources at NCBI, where the information about markers was matched to marker records in NCBI's UniSTS database. Having these data in a public resource like NCBI allows regularly updated automatic matching of markers to public sequence data by e-PCR. The submitted data, and the results of these calculations, are retrievable from NCBI via Entrez Gene, Map Viewer, and UniSTS. Efforts were undertaken to improve the integrated functional genomics resources for pigs.

Animals↗

PubMed1995

Marker assisted selection for genetic improvement of animal populations when a single QTL is marked.

A Monte Carlo simulation study to evaluate the benefits of marker assisted selection (MAS) in small populations with one marked bi-allelic quantitative trait locus (QTL) is described. In the base generation, linkage phase equilibrium between the markers, QTL and polygenes was assumed and frequencies of 0.5 for the two QTL alleles were used. Six discrete generations of selection for a single character measured on both sexes followed. An additive genetic model was used with the QTL positioned midway between two highly polymorphic markers. Schemes were simulated with a distance of 10 cM between the QTL and either of the two markers and with the QTL explaining 1/8 of the total genetic variance in the base generation. Values of 0.5, 0.25 or 0.1 were assumed for the heritability. Eight males and 16, 32 or 64 females were selected each generation with each dam producing four sons and four daughters as candidates for the next generation. Animals were evaluated with a conventional BLUP animal model or with a model using marker information. MAS resulted in substantially higher QTL responses (4-54%), especially with low heritabilities, than conventional BLUP but lower polygenic responses (up to 4%) so that the overall effect on the total genetic response, although in the majority of cases favourable, was relatively small. With QTLs of larger size (explaining 25% of the genetic variance) comparable results were found. When the distance between the QTL and the markers was reduced to 2 cM, genetic responses were increased very slightly with a heritability of 0.5 whereas with a heritability of 0.1 responses were increased by up to 10%, compared with conventional BLUP. Results emphasize that MAS should be most useful for lowly heritable traits and that once QTLs for such traits have been identified the search for closely linked polymorphic markers should be intensified.

Alleles↗

PubMed2001

Selection and subsequent analysis of sib pair data for QTL detection.

Haseman and Elston (1972) developed a robust regression method for the detection of linkage between a marker and a quantitative trait locus (QTL) using sib pair data. The principle underlying this method is that the difference in phenotypes between pairs of sibs becomes larger as they share a decreasing number of alleles at a particular QTL identical by descent (IBD) from their parents. In this case, phenotypically very different sibs will also on average share a proportion of alleles IBD at any marker linked to the QTL that is lower than the expected value of 0.5. Thus, the deviation of the proportion of marker alleles IBD from the expected value in pairs of sibs selected to be phenotypically different (i.e. discordant) can provide a test for the presence of a QTL. A simple regression method for QTL detection in sib pairs selected for high phenotypic differences is presented here. The power of the analytical method was found to be greater than the power obtained using the standard analysis when samples of sib pairs with high phenotypic differences were used. However, the use of discordant sib pairs was found to be less powerful for QTL detection than alternative selective genotyping schemes based on the phenotypic values of the sibs except with intense selection, when its advantage was only marginal. The most effective selection scheme overall was the use of sib pairs from entire families selected on the basis of high within-family variance for the trait in question. There is little effect of selection on QTL position estimates, which are in good agreement with the simulated values. However, QTL variance estimates are biased to a greater or lesser degree, depending on the selection method.

Biological Evolution↗

PubMed2003

Haplotypic QTL mapping in an outbred pedigree.

An offspring genome can be viewed as a mosaic of chromosomal segments or haplotypes contributed by multiple founders in any quantitative trait locus (QTL) detection study but tracing these is especially complex to achieve for outbred pedigrees. QTL haplotypes can be traced from offspring back to individual founders in outbred pedigrees by combining founder-origin probabilities with fully informative flanking markers. This haplotypic method was illustrated for QTL detection using a three-generation pedigree for a woody perennial plant, Pinus taeda L. Growth rate was estimated using height measurements from ages 2 to 10 years. Using simulated and actual datasets, power of the experimental design was shown to be efficient for detecting QTLs of large effect. Using interval mapping and fully informative markers, a large QTL accounting for 11.3% of the phenotypic variance in the growth rate was detected. This same QTL was expressed at all ages for height, accounting for 7.9-12.2% of the phenotypic variance. A mixed-model inheritance was more appropriate for describing genetic architecture of growth curves in P. taeda than a strictly polygenic model. The positive QTL haplotype was traced from the offspring to its contributing founder, GP3, then the haplotypic phase for GP3 was determined by assaying haploid megagametophytes. The positive QTL haplotype was a recombinant haplotype contributed by GP3. This study illustrates the combined power of fully informative flanking markers and founder origin probabilities for (1) estimating QTL haplotype magnitude, (2) tracing founder origin and (3) determining haplotypic transmission frequency.

Haplotypes↗

PubMed2004

Segregation of QTL for production traits in commercial meat-type chickens.

This study investigated whether quantitative trait loci (QTL) identified in experimental crosses of chickens provide a short cut to the identification of QTL in commercial populations. A commercial population of broilers was targeted for chromosomal regions in which QTL for traits associated with meat production have previously been detected in extreme crosses. A three-generation design, consisting of 15 grandsires, 608 half-sib hens and over 15 000 third-generation offspring, was implemented within the existing breeding scheme of a broiler breeding company. The first two generations were typed for 52 microsatellite markers spanning regions of nine chicken chromosomes and covering a total of 730 cM, approximately one-fifth of the chicken genome. Using half-sib analyses with a multiple QTL model, linkage was studied between these regions and 17 growth and carcass traits. Out of 153 trait x region comparisons, 53 QTL exceeded the threshold for genome-wide significance while an additional 23 QTL were significant at the nominal 1% level. Many of the QTL affect the carcass proportions and feed intake, for which there are few published studies. Given intensive selection for efficient growth in broilers for more than 50 generations it is surprising that many QTL affecting these traits are still segregating. Future fine-mapping efforts could elucidate whether ancestral mutations are still segregating as a result of pleiotropic effects on fitness traits or whether this variation is due to new mutations.

Analysis of Variance↗

PubMed2004

The IGF2-intron3-G3072A substitution explains a major imprinted QTL effect on backfat thickness in a Meishan x European white pig intercross.

A paternally expressed QTL for muscle growth and backfat thickness (BFT) has previously been identified near the IGF2 locus on the distal tip of pig chromosome 2 (SSC2p) in three experimental F2 populations. Recently, a mutation in a regulatory element of the IGF2 gene was identified as the quantitative trait nucleotide (QTN) underlying the major QTL effect on muscle growth and BFT in crosses between Large White and Wild Boar or Pietrain. This study demonstrates that the IGF2 mutation also controls the paternally expressed QTL for backfat thickness in a cross between Meishan and European Whites. In addition, a comparison of QTL of backfat thickness measured by Hennessy grading probe (HGP) and by ultrasound measurement (USM) was made. In the USM analyses, the IFG2 mutation explains the entire QTL effect on SSC2p, whereas in the HGP analysis the presence of a second minor QTL can not be excluded. Finally, this study shows that this particular IGF2 mutation does not cause the paternally expressed QTL for teat number mapping to the same region of SSC2p as the BFT QTL.

Animals↗

PubMed2004

QTL analysis of multiple behavioral measures of anxiety in mice.

In a test battery consisting of an open-field arena, a light-dark box, a mirror-chamber box, an elevated plus maze, and an elevated square maze, 1,671 mice were tested, generating over 100 putative measures of anxiety in rodents. Quantitative trait loci (QTL) analysis was carried out on all measures, plus composite measures and phenotypic factor scores. Significant LOD scores were found for QTL on 17 chromosomes, with large and consistent QTL behavioral effects on chromosomes 1, 4, 7, 8, 14, 15, l8, and X. QTL on chromosomes 4 and 8 largely influence locomotor activity in both home cages and novel environments, whereas QTL on chromosomes 1, 15, and 18 influence anxiety-related behaviors. Five genetically separable, cross-test dimensions of anxiety could be identified: (i) the suppression of locomotor activity in low to moderately anxiogenic regions of the tests; (ii) a shift toward proportionally less time and activity spent in high-anxiogenic test areas; (iii) the suppression of rearing behavior; (iv) increased latency to enter novel areas; (v) increased autonomic responses, as assessed by defecation and urination. Patterns of QTL influence on cross-test composite scores were distinctive. For example, the QTL on chromosome 1 strongly influenced safe-area locomotor activity (LOD = 35) and autonomic responses (LOD = 16), whereas the QTL on chromosome 15 influenced the proportion of activity in high-anxiogenic areas (LOD = 16), latency to enter novel areas (LOD = 36) and rearing behavior (LOD = 57). Phenotypic factor analysis identified factors heavily loaded on single tests, rather than cross-test factors. The use of factor analysis or within-test principal components for data reduction before genetic analysis was less satisfactory than using genetic dissection methods on the original measures and logically derived composites.

Animals↗

PubMed2004

Efficient method for analysis of QTL using F1 progenies in an outcrossing species.

In the present paper, we proposed a statistical procedure based on composite interval mapping for accurate analysis of quantitative trait loci (QTL) for individuals sampled from an outcrossing population with two-generation families consisting of the sampled individuals and F1 progenies obtained by crossing them as parental individuals. In the proposed procedure, haplotypes of markers of parental individuals were reconstructed based on the genotypes of F1 progenies and QTL analyses with composite interval mapping were conducted separately for each of parents as well as jointly for both parents. A least squares method was applied to the composite interval mapping, where some of markers were selected as cofactors to absorb the variation induced by QTL located elsewhere in the genome. The procedure was evaluated for the efficiency in detecting QTL and the precision of estimates of locations and effects of QTL using simulations. It was shown that QTL with interaction between paternal and maternal alleles was effectively detected by joint analysis of both parents, while a QTL segregating only in one parent, closely linked to a QTL segregating only in the other parent, was successfully detected by analyzing separately each of the parents with inclusion of markers of both parents. The proposed procedure can provide detailed genetic information useful for marker assisted breeding in an outcrossing species such as forest trees.

Chromosome Mapping↗

PubMed1999

High resolution mapping and identification of new quantitative trait loci (QTL) affecting susceptibility to Marek's disease.

Marek's disease (MD) is a lymphoproliferative disease of chickens that costs the poultry industry approximately $1 billion annually. Genetic resistance to MD is gaining increased attention to augment vaccinal control as disease outbreaks occur more frequently. Previously, analysis of a 272 F2 White Leghorn resource population measured for many MD traits and genotyped for 78 microsatellite markers revealed two and four quantitative trait loci (QTL) with significant and suggestive association, respectively, to one or more MD associated traits. Additional genetic markers have since been scored on the MD resource population to increase QTL resolution and genome coverage. Saturation of four of the QTL regions with 17 markers revealed five new QTL while 32 markers extended the genome coverage by 400 + CM and uncovered three more QTL. QTL analysis by single-point and interval mapping algorithms agreed well when marker saturation was approximately 20 CM or less. Currently 127 genetic markers cover approximately 68% of the genome that contain up to 14 MD QTL associated to one or more MD trait; seven at the significant level and seven at the suggestive level. Individually each QTL accounts for 2-10% of the variation and, in general, resistance was dominant although the resistant allele may come from either parental line. This study suggests that a limited number of genomic regions play a major role in the genetic control of MD resistance. Markers linked to these loci may be useful for selection of MD resistant stock by the poultry industry following verification of the association within their breeding populations.

Animals↗

PubMed2002

An improved genetic model generates high-resolution mapping of QTL for protein quality in maize endosperm.

The genetic mapping of polymorphic markers in a cross between two inbred plant lines has proven to be a powerful method for detecting quantitative trait loci (QTL) underlying complex traits. However, existing methods of QTL mapping were developed for disomic inheritance of both marker and QTL loci in a diploid population. To map QTL influencing traits expressed in the endosperm, a triploid embryo-nourishing tissue resulting from double fertilization, existing QTL mapping models require modification to consider the trisomic inheritance of the endosperm and the generation difference between the mapping population and the endosperm. Such a model requires simultaneous use of two successive generations, which theoretically can lead to an increase in resolution for QTL mapping compared with the use of a single backcross or F(2) generation. Using a newly developed model based on these considerations, we demonstrate the improved resolution of QTL, influencing protein quality traits in maize endosperm. The increased resolution made possible with this approach makes identified QTL accessible to positional cloning.

Chromosome Mapping↗

PubMed1993

QTL analysis of transgressive segregation in an interspecific tomato cross.

Two accessions, representing the species Lycopersicon esculentum (cultivated tomato) and Lycopersicon pennellii (a wild relative), were evaluated for 11 quantitative traits and found to be significantly different for 10 of the traits. Transgressive segregation was observed for eight of the traits in a large interspecific F2 population. When restriction fragment length polymorphism markers were used as probes for the quantitative trait loci (QTL) underlying the traits, 74 significant QTL (LOD > 2) were detected. Thirty-six percent of those QTL had alleles with effects opposite to those predicted by the parental phenotypes. These QTL were directly related to the appearance of transgressive individuals in the F2 for those traits which showed transgressive segregation. However, the same types of QTL (with allelic effects opposite to those predicted by the parents) were also observed for traits that did not display transgressive segregation in the F2. One such trait was dry weight accumulation. When two overdominant QTL (detected in the F2) for this trait were backcrossed into the L. esculentum genetic background, transgressive individuals were recovered and their occurrence was associated with the two QTL demonstrating the potential for transgressive segregation for all characters and implicating overdominance as a second cause of transgressive segregation. Epistasis was not implicated in transgressive segregation in either the F2 or backcross generations. Results from this research not only reveal the basis of wide-cross transgressive segregation, but demonstrate that molecular markers can be used to identify QTL (from wild species) responsible for transgressive phenotypes and to selectively transfer them into crop species. This strategy might be used to improve many traits of economic importance including those for which wild species appear phenotypically inferior to their cultivated counterparts.

Alleles↗

PubMed2005

Fine mapping of a QTL region with large effects on growth and fatness on mouse chromosome 2.

We combined the use of a congenic line and recombinant progeny testing (RPT) to characterize and fine map a previously identified region of distal mouse chromosome 2 (MMU2) harboring quantitative trait loci (QTL) with large effects on growth and fatness. The congenic line [M16i.B6-(D2Mit306-D2Mit52); MB2] was created using an inbred line (M16i) derived from a line that had undergone long-term selection for rapid weight gain (M16) as the recipient for an approximately 38-cM region on MMU2 from the inbred line C57BL/6J. A large F2 cohort (1,200 mice) originating from a cross between MB2 and M16i was created, and 40 F2 males with defined recombinations within the QTL region were used to produce 665 segregating progeny. Linkage analysis of the F2 population detected QTL with very large effects on body weight, body fat, lean tissue mass, bone mineral density, and liver weight. Confidence intervals of the QTL were narrowed to regions of 1.5-4.5 cM. Analysis of progeny of the recombinant F2 males confirmed the existence of the QTL and further contributed to localization of their map positions. These efforts confirmed the presence of QTL with major effect on MMU2, narrowed the estimated region harboring the QTL from 38 to 12 cM, and further characterized phenotypic effects of the QTL, effectively culminating in a significantly decreased pool of positional candidate genes potentially representing these genes controlling predisposition to growth and fatness.

Animals↗

PubMedDate not supplied

Use of maternal information for QTL detection in a (grand)daughter design.

In a (grand)daughter design, maternal information is often neglected because the number of progeny per dam is limited. The number of dams per maternal grandsire (MGS), however, could be large enough to contribute to QTL detection. But dams and MGS usually are not genotyped, there are two recombination opportunities between the MGS and the progeny, and at a given location, only half the progeny receive a MGS chromosomal segment. A 3-step procedure was developed to estimate: (1) the marker phenotypes probabilities of the MGS; (2) the probability of each possible MGS haplotype; (3) the probabilities that the progeny receives either the first, or second MGS segment, or a maternal grandam segment. These probabilities were used for QTL detection in a linear model including the effects of sire, MGS, paternal QTL, MGS QTL and maternal grandam QTL. Including the grandam QTL effect makes it possible to detect QTL in the grandam population, even when MGS are not informative. The detection power, studied by simulation, was rather high, provided that MGS family size was greater than 50. Using maternal information in the French dairy cattle granddaughter design made it possible to detect 23 additional QTL genomewise significant.

Animals↗