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PubMed2006

Quantitative trait analysis of seed yield and other complex traits in hybrid spring rapeseed (Brassica napus L.): 1. Identification of genomic regions from winter germplasm.

The introgression of winter germplasm into spring canola (Brassica napus L.) represents a novel approach to improve seed yield of hybrid spring canola. In this study, quantitative trait loci (QTL) for seed yield and other traits were genetically mapped to determine the effects of genomic regions introgressed from winter germplasm into spring canola. Plant materials used comprised of two populations of doubled haploid (DH) lines having winter germplasm introgression from two related French winter cultivars and their testcrosses with a spring line used in commercial hybrids. These populations were evaluated for 2 years at two locations (Wisconsin, USA and Saskatchewan, Canada). Genetic linkage maps based on RFLP loci were constructed for each DH population. Six QTL were detected in the testcross populations for which the winter alleles increased seed yield. One of these QTL explained 11 and 19% of the phenotypic variation in the two Canadian environments. The winter allele for another QTL that increased seed yield was linked in coupling to a QTL allele for high glucosinolate content, suggesting that the transition of rapeseed into canola could have resulted in the loss of favorable seed yield alleles. Most QTL for which the introgressed allele decreased seed yield of hybrids mapped to genomic regions having homoeologous non-reciprocal transpositions. This suggests that allelic configurations created by these rearrangements might make an important contribution to genetic variation for complex traits in oilseed B. napus and could account for a portion of the heterotic effects in hybrids.

Alleles↗
PubMed2006

Quantitative trait analysis of seed yield and other complex traits in hybrid spring rapeseed (Brassica napus L.): 2. Identification of alleles from unadapted germplasm.

Unadapted germplasm may contain alleles that could improve hybrid cultivars of spring oilseed Brassica napus. Quantitative trait loci (QTL) mapping was used to identify potentially useful alleles from two unadapted germplasm sources, a Chinese winter cultivar and a re-synthesized B. napus, that increase seed yield when introgressed into a B. napus spring hybrid combination. Two populations of 160 doubled haploid (DH) lines were created from crosses between the unadapted germplasm source and a genetically engineered male-fertility restorer line (P1804). A genetically engineered male-sterile tester line was used to create hybrids with each DH line (testcrosses). The two DH line populations were evaluated in two environments and the two testcross populations were evaluated in three or four environments for seed yield and other agronomic traits. Several genomic regions were found in the two testcross populations which contained QTL for seed yield. The map positions of QTL for days to flowering and resistance to a bacterial leaf blight disease coincided with QTL for seed yield and other agronomic traits, suggesting the occurrence of pleiotropic or linked effects. For two hybrid seed yield QTL, the favorable alleles increasing seed yield originated from the unadapted parents, and one of these QTL was detected in multiple environments and in both populations. In this QTL region, a chromosome rearrangement was identified in P1804, which may have affected seed yield.

Alleles↗
PubMed2006

Identification of quantitative trait loci (QTL) for oil and protein contents and their relationships with other seed quality traits in Brassica juncea.

A detailed RFLP-genomic map was used to study the genetics of oil, seed and meal protein and sum of oil and seed/meal protein contents in a recombinant doubled-haploid population developed by crossing black- and yellow-seeded Brassica juncea lines. Two yellow seed color genes (SC-B4, SC-A6) and one QTL for erucic acid content (E(1b)) showed pleiotropic effect for oil, protein and sum of oil and seed/meal protein contents. Six (O-A1, O-A6, O-A9, O-B3, O-B4, O-B5) and five (SP-A1, SP-A9, SP-B4, SP-B6, SP-C) QTLs were significant for oil and seed protein contents, respectively. Tight linkage of three of these QTLs (SP-A1, SP-A9, SP-B4, O-A1, O-A9, O-B4), with opposite effects, poses challenge to the plant breeders for simultaneous improvement of negatively correlated (r = -0.7**) oil and seed protein contents. However, one QTL for oil content (O-B3) and two for seed protein content (SP-B6, SP-C) were found to be unlinked, which offer the possibility for simultaneous improvement of these two traits. QTLs significant for meal protein (MP-A1, MP-A6, MP-A9, MP-B5, MP-B6) were significant at least for oil, seed protein or sum of oil and seed/meal protein contents (T-A6, T-A7, T-B4, T-B5). Sum of oil and seed protein contents and sum of oil and meal protein contents had a perfect correlation, as well as same epistatic interactions and QTLs with similar additive effect. This indicates that protein in seed or meal has practically the same meaning for breeding purposes. Epistatic interactions were significant for the quality traits, and their linkage reflected association among the traits.

Agriculture↗
PubMed2000

Power of quantitative trait locus mapping for polygenic binary traits using generalized and regression interval mapping in multi-family half-sib designs.

A generalized interval mapping (GIM) method to map quantitative trait loci (QTL) for binary polygenic traits in a multi-family half-sib design is developed based on threshold theory and implemented using a Newton-Raphson algorithm. Statistical power and bias of QTL mapping for binary traits by GIM is compared with linear regression interval mapping (RIM) using simulation. Data on 20 paternal half-sib families were simulated with two genetic markers that bracketed an additive QTL. Data simulated and analysed were: (1) data on the underlying normally distributed liability (NDL) scale, (2) binary data created by truncating NDL data based on three thresholds yielding data sets with three different incidences, and (3) NDL data with polygenic and QTL effects reduced by a proportion equal to the ratio of the heritabilities on the binary versus NDL scale (reduced-NDL). Binary data were simulated with and without systematic environmental (herd) effects in an unbalanced design. GIM and RIM gave similar power to detect the QTL and similar estimates of QTL location, effects and variances. Presence of fixed effects caused differences in bias between RIM and GIM, where GIM showed smaller bias which was affected less by incidence. The original NDL data had higher power and lower bias in QTL parameter estimates than binary and reduced-NDL data. RIM for reduced-NDL and binary data gave similar power and estimates of QTL parameters, indicating that the impact of the binary nature of data on QTL analysis is equivalent to its impact on heritability.

Algorithms↗
PubMed1999

A search for quantitative trait loci for milk production traits on chromosome 6 in Finnish Ayrshire cattle.

Cattle chromosome 6 was scanned with 11 markers, ten microsatellites and the casein haplotype, to identify quantitative trait loci (QTLs) affecting the following milk production traits: milk yield, fat percentage, fat yield, protein percentage and protein yield. Twelve Finnish Ayrshire half-sib families with a total of 480 sons were genotyped and used in a grand-daughter design. Interval mapping was performed with a multiple-marker regression approach with a one-QTL and a two-QTL model, and the significance threshold values were determined empirically using a permutation test. Across-family analysis with the one-QTL model revealed an effect on protein percentage (P < 0.05) and on milk yield (P < 0.05). The analysis with the two-QTL model identified significant effects (P < 0.05) on protein percentage, milk yield, and fat yield. Comparing these two cases, the results suggest the existence of two QTLs on chromosome 6 with an effect on milk production traits. One of the QTLs was located around the casein genes. As the other QTL was similar in location and effect to a QTL found previously in Holstein-Friesians, an identity-by-descent approach could be applied to fine map this region.

Animals↗
PubMed2003

Linkage analysis of extremely discordant and concordant sibling pairs identifies quantitative-trait loci that influence variation in the human personality trait neuroticism.

Several theoretical studies have suggested that large samples of randomly ascertained siblings can be used to ascertain phenotypically extreme individuals and thereby increase power to detect genetic linkage in complex traits. Here, we report a genetic linkage scan using extremely discordant and concordant sibling pairs, selected from 34,580 sibling pairs in the southwest of England who completed a personality questionnaire. We performed a genomewide scan for quantitative-trait loci (QTLs) that influence variation in the personality trait of neuroticism, or emotional stability, and we established genomewide empirical significance thresholds by simulation. The maximum pointwise P values, expressed as the negative logarithm (base 10), were found on 1q (3.95), 4q (3.84), 7p (3.90), 12q (4.74), and 13q (3.81). These five loci met or exceeded the 5% genomewide significance threshold of 3.8 (negative logarithm of the P value). QTLs on chromosomes 1, 12, and 13 are likely to be female specific. One locus, on chromosome 1, is syntenic with that reported from QTL mapping of rodent emotionality, an animal model of neuroticism, suggesting that some animal and human QTLs influencing emotional stability may be homologous.

Adult↗
PubMed1999

Identification of quantitative trait loci influencing traits related to energy balance in selection and inbred lines of mice.

Energy balance is a complex trait with relevance to the study of human obesity and maintenance energy requirements of livestock. The objective of this study was to identify, using unique mouse models, quantitative trait loci (QTL) influencing traits that contribute to variation in energy balance. Two F2 resource populations were created from lines of mice differing in heat loss measured by direct calorimetry as an indicator of energy expenditure. The HB F2 resource population originated from a cross between a noninbred line selected for high heat loss and an inbred line with low heat loss. Evidence for significant QTL influencing heat loss was found on chromosomes 1, 2, 3, and 7. Significant QTL influencing body weight and percentage gonadal fat, brown fat, liver, and heart were also identified. The LH F2 resource population originated from noninbred lines of mice that had undergone divergent selection for heat loss. Chromosomes 1 and 3 were evaluated. The QTL for heat loss identified on chromosome 1 in the HB population was confirmed in the LH population, although the effect was smaller. The presence of a QTL influencing 6-wk weight was also confirmed. Suggestive evidence for additional QTL influencing heat loss, percentage subcutaneous fat, and percentage heart was found for chromosome 1.

Adipose Tissue↗
PubMed2003

Quantitative trait loci responsible for variation in sexually dimorphic traits in Drosophila melanogaster.

To understand the mechanisms of morphological evolution and species divergence, it is essential to elucidate the genetic basis of variation in natural populations. Sexually dimorphic characters, which evolve rapidly both within and among species, present attractive models for addressing these questions. In this report, we map quantitative trait loci (QTL) responsible for variation in sexually dimorphic traits (abdominal pigmentation and the number of ventral abdominal bristles and sex comb teeth) in a natural population of Drosophila melanogaster. To capture the pattern of genetic variation present in the wild, a panel of recombinant inbred lines was created from two heterozygous flies taken directly from nature. High-resolution mapping was made possible by cytological markers at the average density of one per 2 cM. We have used a new Bayesian algorithm that allows QTL mapping based on all markers simultaneously. With this approach, we were able to detect small-effect QTL that were not evident in single-marker analyses. Our results show that at least for some sexually dimorphic traits, a small number of QTL account for the majority of genetic variation. The three strongest QTL account for >60% of variation in the number of ventral abdominal bristles. Strikingly, a single QTL accounts for almost 60% of variation in female abdominal pigmentation. This QTL maps to the chromosomal region that Robertson et al. have found to affect female abdominal pigmentation in other populations of D. melanogaster. Using quantitative complementation tests, we demonstrate that this QTL is allelic to the bric a brac gene, whose expression has previously been shown to correlate with interspecific differences in pigmentation. Multiple bab alleles that confer distinct phenotypes appear to segregate in natural populations at appreciable frequencies, suggesting that intraspecific and interspecific variation in abdominal pigmentation may share a similar genetic basis.

Animals↗
PubMed2003

Identification of quantitative trait loci for production traits in commercial pig populations.

The aim of this study was to investigate methods for detecting QTL in outbred commercial pig populations. Several QTL for back fat and growth rate, previously detected in experimental resource populations, were examined for segregation in 10 different populations. Two hundred trait-by-population-by-chromosome tests were performed, resulting in 20 tests being significant at the 5% level. In addition, 53 QTL tests for 11 meat quality traits were declared significant, using a subset of the populations. These results show that a considerable amount of phenotypic variance observed in these populations can be explained by major alleles segregating at several of the loci described. Thus, despite a relatively strong selection pressure for growth and back fat traits in these populations, these alleles have not yet reached fixation. The approaches used here demonstrate that it is possible to verify segregation of QTL in commercial populations by limited genotyping of a selection of informative animals. Such verified QTL may be directly exploited in marker-assisted selection (MAS) programs in commercial populations and their molecular basis may be revealed by positional candidate cloning.

Adipose Tissue↗
PubMed2006

Identification of trait loci affecting white meat percentage and other growth and carcass traits in commercial broiler chickens.

White meat is the most economically valuable part of a broiler chicken. Increasing white meat relative to overall body size (white meat percentage, WM%) makes a broiler, gram for gram, a more valuable animal. However, accurately measuring WM% requires removing the bird from the breeding flock. Identification of markers for genomic regions associated with WM% would allow direct genetic selection on breeders. The objective of the current study was to identify genomic regions affecting WM% and other growth and carcass traits in an F2 cross between 2 commercial broiler lines that differed in WM%. Two commercial lines were crossed to generate 5 F1 half-sib families of each reciprocal cross type. One male from each family was crossed with 3 females from each of the other families within each reciprocal cross type. Seven F2 half-sib families, totaling 430 F2 individuals, were analyzed. Microsatellite markers (n = 73) on the 11 largest chromosomes were analyzed for associations with various growth and carcass traits by least squares interval mapping using line-cross, half-sib, combined, and parent of origin models. Sixty-eight QTL were identified at the 5% chromosome-wise level, including 6 QTL affecting WM%. Ten QTL reached 5% genome-wise significance, including 1 WM% QTL on Gga 2. The current study identified genomic regions harboring QTL affecting WM% and other carcass and growth traits, which may be useful for direct genetic selection, and also identified putative imprinted QTL in the chicken. The advantage of using multiple statistical models was evident because QTL were identified with the combined and parent of origin models that were not identified with the line-cross or half-sib models.

Animals↗
PubMed2006

Quantitative trait loci mapping for fatty acid composition traits in perirenal and back fat using a Japanese wild boar x Large White intercross.

Here, we analysed quantitative trait loci (QTL) for fatty acid composition, one of the factors affecting fat quality, in a Japanese wild boar x Large White cross. We found 25 significant effects for 17 traits at 13 positions at the 5% genome-wise level, of which 16 effects for 12 traits at 10 positions were significant at the 1% level. QTL for saturated fatty acids (SFA) in back fat were mapped to swine (Sus scrofa) chromosomes (SSC) 1p, 9 and 15. QTL for unsaturated fatty acids in back fat were mapped to SSC1p, 1q, 4, 5, 9, 15 and 17. Using a regression model that fits back fat thickness as a covariate, two of the QTL for linoleic acid content on SSC4 and SSC17 were not significant, but one QTL for total SFA composition was detected on SSC5 with correction for back fat thickness. Wild boar alleles at six of seven QTL tended to increase SFAs and to decrease unsaturated fatty acids. QTL for fatty acid composition in perirenal fat were mapped on SSC2, 3, 4, 5, 6, 14, 16 and X. QTL for melting point (in back fat samples) were mapped on SSC1, 2 and 15. Wild boar alleles in QTL on SSC1 and SSC15 were associated with elevated melting points whereas those on SSC2 were associated with lower melting point measurements.

Adipose Tissue↗
PubMed2006

Quantitative trait loci analysis of egg and meat production traits in a red junglefowlxWhite Leghorn cross.

Egg and production traits are of considerable economic importance in chickens. Using a White Leghorn x red junglefowl F(2) intercross, standard production measures of liver weight and colour, egg size, eggshell thickness, egg taste and meat quality were taken. A total of 160 markers covering 29 autosomes and the Z chromosome were genotyped on 175-243 individuals, depending on the trait under consideration. A total of nine significant quantitative trait loci (QTL) and three suggestive QTL were found on chicken chromosomes 1, 2, 4, 5, 7, 8, 10, 12, E47W24 and E22C19W28.

Animals↗
PubMed2005

An independent confirmation of a quantitative trait locus for milk yield and composition traits on bovine chromosome 26.

Several reports have demonstrated that bovine chromosome 26 (BTA26) harbours significant or suggestive quantitative trait loci (QTL) for milk production and composition traits in dairy cattle. Our previous study showed that a C/T substitution in the bovine TCF7L2 gene on BTA26 was significantly linked to QTL for protein yield (PY) in a Canadian dairy cattle population. Actually, this polymorphism was one of the markers derived from a genome-wide screening of QTL for milk PY using an amplified fragment length polymorphism technique combined with a DNA pooling strategy. In the present study, 990 Holstein bulls with complete genotype and phenotype data from 14 sire families were analysed to confirm, if the QTL effects exist in other populations. Statistical analysis revealed that this marker was significantly associated with PY, protein percentage, milk yield and fat yield (FY) (p < 0.001) in the US Holstein population. These results indicate that this QTL region has a pleiotrophic effecton different milk traits and is portable in different populations.

Analysis of Variance↗
PubMed2006

Investigation of two candidate genes for meat quality traits in a quantitative trait locus region on SSC6: the porcine short heterodimer partner and heart fatty acid binding protein genes.

A highly significant quantitative trait locus (QTL) on pig chromosome 6, affecting intramuscular fat (IMF), has previously been detected by our group and others. Two genes of positional and biological interest, the small heterodimer partner (SHP; NR0B2) and the heart fatty acid binding protein (FABP3; H-FABP), were investigated for meat quality traits and IMF respectively. SHP was partially sequenced (GenBank: DQ002896 and DQ002897) and mapped to the QTL region on porcine chromosome 6, affecting IMF. The map shows no recombination between SHP and FABP3, which was previously mapped to the same QTL region. Twelve single nucleotide polymorphisms were detected in the sequenced region of SHP gene. Haplotype information was used to investigate association between genetic variation and different meat quality traits. SHP haplotype combinations were found to have significant effect on connective tissue. However, further studies are needed to evaluate this possible association more effectively. The FABP3 is involved in fatty acid transport and has been studied as a candidate gene for IMF by several research groups. In our study, FABP3 genotypes were confirmed to be significantly associated with IMF in pigs. The average content of IMF in our population was 1.6%, which may indicate that the FABP3 polymorphism explains as much as 30-35% of the variation in IMF in our pig cross-population.

Animals↗
PubMedDate not supplied

Quantitative trait loci (QTLs) mapping for growth traits in the mouse: a review.

The attainment of a specific mature body size is one of the most fundamental differences among species of mammals. Moreover, body size seems to be the central factor underlying differences in traits such as growth rate, energy metabolism and body composition. An important proportion of this variability is of genetic origin. The goal of the genetic analysis of animal growth is to understand its "genetic architecture", that is the number and position of loci affecting the trait, the magnitude of their effects, allele frequencies and types of gene action. In this review, the different strategies developed to identify and characterize genes involved in the regulation of growth in the mouse are described, with emphasis on the methods developed to map loci contributing to the regulation of quantitative traits (QTLs).

Animals↗
PubMedDate not supplied

A generalized estimating equations approach to quantitative trait locus detection of non-normal traits.

To date, most statistical developments in QTL detection methodology have been directed at continuous traits with an underlying normal distribution. This paper presents a method for QTL analysis of non-normal traits using a generalized linear mixed model approach. Development of this method has been motivated by a backcross experiment involving two inbred lines of mice that was conducted in order to locate a QTL for litter size. A Poisson regression form is used to model litter size, with allowances made for under- as well as over-dispersion, as suggested by the experimental data. In addition to fixed parity effects, random animal effects have also been included in the model. However, the method is not fully parametric as the model is specified only in terms of means, variances and covariances, and not as a full probability model. Consequently, a generalized estimating equations (GEE) approach is used to fit the model. For statistical inferences, permutation tests and bootstrap procedures are used. This method is illustrated with simulated as well as experimental mouse data. Overall, the method is found to be quite reliable, and with modification, can be used for QTL detection for a range of other non-normally distributed traits.

Animals↗
PubMed1998

Identification of quantitative trait loci affecting carcass composition in swine: I. Fat deposition traits.

One of the major determining factors in the price of market hogs today is backfat depth. Therefore, identification of regions of the genome affecting this trait could be very useful to the swine industry. A large resource population (n = 540) was developed by backcrossing F1 Meishan-White composite females to either Meishan or White composite boars. A genomic scan was conducted by genotyping all animals with microsatellite markers spaced at approximately 20-cM intervals across the entire porcine genome. Breed of origin for all chromosomal segments was determined using multipoint linkage procedures, and a least squares regression analysis was conducted. Nominal P-values were converted to a genome-wide level of significance to adjust for the numerous tests conducted. Traits analyzed were backfat depths at the first rib (FRIB); 10th rib (10th); last rib (LRIB); last lumbar (LLUM) vertebra; the average of FRIB, LRIB, and LLUM (AVBF); and weight of leaf fat (LEAF). Significant quantitative trait loci (QTL) were detected on chromosomes 1, 7, and X. Suggestive evidence for QTL was present on chromosomes 5, 8, 9, 10, 13, and 14. Genotypic means for the loci detected indicated a predominantly additive mode of inheritance. Meishan alleles produced fatter pigs for all loci except those on chromosomes 7 and 10. Additional research should be conducted to refine the estimated position of each QTL and its effect and determine epistatic interactions. These loci should be evaluated in other germplasms to determine whether allelic variation at the QTL exists in other breeds.

Adipose Tissue↗
PubMed1998

Identification of quantitative trait loci affecting carcass composition in swine: II. Muscling and wholesale product yield traits.

A genomic scan was conducted on 540 reciprocal backcross Meishan x White composite pigs for hot carcass weight (HCWT); loin eye area (LOIN); carcass length (CRCL); belly weight (BELLY); and weight of trimmed ham, loin, picnic, and Boston butt adjusted to a constant live (TWPLWT) or carcass (TWPCWT) weight. Genetic markers spanned the entire porcine linkage map and were spaced at approximately 20-cM intervals. Grandparental breed of origin for all chromosomal segments was determined using multipoint linkage procedures, and a least squares regression analysis was conducted. Nominal P-values were converted to a genome-wide level of significance to adjust for the number of tests actually conducted. Seven associations were significant at the genome-wide level relating to chromosomes 1 (SSC 1), 7 (SSC 7), and X (SSC X). The SSC 1 region affected LOIN, TWPLWT, and TWPCWT; SSC 7 affected HWCT and CRCL; and SSC X affected TWPLWT and TWPCWT. Twelve associations relating to seven chromosomal regions (including SSC 1 and X) presented suggestive evidence for quantitative trait loci (QTL), and many of these regions are likely to contain QTL. Chromosomes 8 and 14 had two and three traits with suggestive evidence for QTL, respectively. Many pleiotropic effects were detected for regions on SSC 1, 7, 14, and X in this study and a companion study looking for fat deposition QTL in the same population. In addition, SSC 4 was nearly significant for CRCL in the same region identified as affecting backfat in a wild boar x Large White population. These results expand our knowledge of the inheritance of quantitative traits and are directly relevant to composite populations containing Meishan germplasm.

Alleles↗