Quantitative Trait Loci Alleles Research Articles

Quantitative trait loci in Drosophila.

Phenotypic variation for quantitative traits results from the simultaneous segregation of alleles at multiple quantitative trait loci. Understanding the genetic architecture of quantitative traits begins with mapping quantitative trait loci to broad genomic regions and ends with the molecular definition of quantitative trait loci alleles. This has been accomplished for some quantitative trait loci in Drosophila. Drosophila quantitative trait loci have sex-, environment- and genotype-specific effects, and are often associated with molecular polymorphisms in non-coding regions of candidate genes. These observations offer valuable lessons to those seeking to understand quantitative traits in other organisms, including humans.

Mapping QTLs controlling grain yield and its components on chromosome 5A of wheat

Chromosome 5A of wheat is known to carry a number of genes affecting adaptability and productivity. To localize quantitative trait loci (QTLs) controlling grain yield and its components, an RFLP map was constructed from 118 single-chromosome recombinant lines derived from the F1 between Chinese Spring (Cappelle-Desprez 5A) and Chinese Spring (Triticum spelta 5A). The map was combined with the field-trial data scored over 3 years. A total of five regions in chromosome 5A contributed effects on yield traits. Increases in grain yield, 50-grain weight and spikelet number/ear were determined by complementary QTL alleles from both parents. The effects associated with the vernalization requirement gene Vrn-A1 or a closely linked QTL were significant only in the favorable growing season where the later-flowering vrn-A1 allele from Cappelle-Desprez 5A produced a higher tiller number/plant and spikelet number/ear. The effects of the ear morphology gene q or closely linked QTL(s) were detected for grain yield and ear grain weight. Three other QTLs with minor effects were dispersed along chromosome 5A. These QTLs had large interactions with years due to changes in the magnitude of the significant response. The alleles from T. spelta, however, conferred a higher yield performance.

Deficiency mapping of quantitative trait loci affecting longevity in Drosophila melanogaster.

In a previous study, sex-specific quantitative trait loci (QTL) affecting adult longevity were mapped by linkage to polymorphic roo transposable element markers, in a population of recombinant inbred lines derived from the Oregon and 2b strains of Drosophila melanogaster. Two life span QTL were each located on chromosomes 2 and 3, within sections 33E-46C and 65D-85F on the cytological map, respectively. We used quantitative deficiency complementation mapping to further resolve the locations of life span QTL within these regions. The Oregon and 2b strains were each crossed to 47 deficiencies spanning cytological regions 32F-44E and 64C-76B, and quantitative failure of the QTL alleles to complement the deficiencies was assessed. We initially detected a minimum of five and four QTL in the chromosome 2 and 3 regions, respectively, illustrating that multiple linked factors contribute to each QTL detected by recombination mapping. The QTL locations inferred from deficiency mapping did not generally correspond to those of candidate genes affecting oxidative and thermal stress or glucose metabolism. The chromosome 2 QTL in the 35B-E region was further resolved to a minimum of three tightly linked QTL, containing six genetically defined loci, 24 genes, and predicted genes that are positional candidates corresponding to life span QTL. This region was also associated with quantitative variation in life span in a sample of 10 genotypes collected from nature. Quantitative deficiency complementation is an efficient method for fine-scale QTL mapping in Drosophila and can be further improved by controlling the background genotype of the strains to be tested.

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.

Analysis of a Quantitative Trait Locus Allele from Wild Soybean That Increases Seed Protein Concentration in Soybean

Increases in the seed protein concentration of soybean [Glycine max (L.) Merr.] would improve the value of the crop. Two major quantitative trait locus (QTL) alleles from Glycine soja Sieb. and Zucc. that increased seed protein concentration were identified previously. The first objective of our study was to test the two G. soja QTL alleles in a population developed through backcrossing the alleles into a soybean background. The second objective was to evaluate the effect of one of the G. soja QTL alleles in three genetic backgrounds. A backcross three (BC3) population was developed and evaluated in the field across two locations over 2 yr. To test the allele in different backgrounds, a line from the backcross population was crossed to three soybean genotypes. Populations developed from these crosses were then evaluated in three field environments. In the backcross population, genetic marker alleles linked to the QTL allele from G. soja on linkage group (LG) I were significantly (P < 0.05) associated with greater protein and less oil concentration, reduced yield, smaller seeds, taller plants, and earlier maturity than the G. max alleles. Markers linked to the second G. soja QTL allele on LG E were not significantly associated with seed or agronomic traits. In the genetic background tests, markers linked to the G. soja QTL allele on LG I were associated with an increase in protein concentration in two of the three crosses. These results show that seed component traits can be successfully modified through genetic mapping coupled with marker assisted selection.

Fine-mapping of quantitative trait loci in half-sib families using current recombinations.

Two groups of methods are being developed to fine-map quantitative trait loci (QTLs): identity-by-descent methods or methods using historical recombinations, and genetic chromosome dissection methods or methods utilizing current recombinations. Here we propose two methods that fall into the second group: contrast mapping and substitution mapping. A QTL has previously been detected via linkage mapping in a half-sib design (granddaughter or daughter design), and sires (grandsires) likely to be heterozygous at the QTL have been identified. A sire (grandsire) and its recombinant offspring are then genotyped for a series of ordered markers spanning the initial marker interval. Offspring are grouped by paternal multi-marker haplotype with haplotypes differing in the location of the recombination event. In the contrast method, contrasts between the phenotypic averages of haplotypes or offspring groups are calculated which correspond to marker intervals within the original interval. The expected value of the contrast for the true QTL interval is always maximum, hence the interval with maximum observed contrast is assumed to contain the QTL. Alternative statistics for determining the interval most likely to contain a QTL are presented for contrast mapping, as well as a bootstrap estimation of the probability of having identified the correct interval. For an initial marker bracket of 20 cM and 10 additional equidistant markers, the probability of assigning the QTL to the correct 2 cM marker interval or to a combined 4 cM interval was calculated. For substitution effects of 0.093, 0.232, 0.464, 0.696 and 0.928 (in additive genetic SD), power values near 0.14, 0.26, 0.48, 0.67 and 0.80 (0.25, 0.53, 0.86, 0.97 and 0.99) are achieved for a family of 200 (1000) sons, respectively. In substitution mapping, QTL segregation status of recombinant sons must be determined using daughter genotyping. Combinations of two haplotypes with their segregation status are required to assign the QTL to an interval. Probabilities of correct QTL assignment were calculated assuming absence of the mutant QTL allele in dams of sons. For a 2 cM interval and a QTL at the midpoint of an interval, power near 0.95 (0.90) is reached when the number of recombinant sons is 70 (60), or total number of sons is 424 (363). For QTL positions away from the midpoint, power decreases but can be improved by combining marker intervals. For a QTL located halfway to the midpoint, and 182 sons in a family resulting in 30 recombinant sons, probability is 0.94 for assignment to either a 2 cM or a combined 4 cM interval. Effect of type I and type II errors in segregation status determination on power of QTL assignment was found to be small. Errors in segregation status due to QTL segregation in dams have an impact if the frequency of the mutant QTL allele is intermediate to high.

Efficient marker-based recurrent selection for multiple quantitative trait loci

We studied the efficiency of recurrent selection based solely on marker genotypes (marker-based selection), in order to increase favourable allele frequency at 50 previously detected quantitative trait loci (QTLs). Two selection procedures were investigated, using computer simulations: (1) Truncation Selection (MTS), in which individuals are ranked based on marker score, and best individuals are selected for recombination; and (2) QTL Complementation Selection (QCS), in which individuals are selected such that their QTL composition complements those individuals already selected. Provided QTL locations are accurate, marker-based selection with a population size of 200 was very effective in rapidly increasing frequencies of favourable QTL alleles. QCS methods were more effective than MTS for improving the mean frequency and fixation of favourable QTL alleles. Marker-based selection was not very sensitive to a reduction in population size, and appears valuable to optimize the use of molecular markers in recurrent selection programmes.

Strategies for genetic mapping of categorical traits.

The search for efficient and powerful statistical methods and optimal mapping strategies for categorical traits under various experimental designs continues to be one of the main tasks in genetic mapping studies. Methodologies for genetic mapping of categorical traits can generally be classified into two groups, linear and non-linear models. We develop a method based on a threshold model, termed mixture threshold model to handle ordinal (or binary) data from multiple families. Monte Carlo simulations are done to compare its statistical efficiencies and properties of the proposed non-linear model with a linear model for genetic mapping of categorical traits using multiple families. The mixture threshold model has notably higher statistical power than linear models. There may be an optimal sampling strategy (family size vs number of families) in which genetic mapping reaches its maximal power and minimal estimation errors. A single large-sibship family does not necessarily produce the maximal power for detection of quantitative trait loci (QTL) due to genetic sampling of QTL alleles. The QTL allelic model has a marked impact on efficiency of genetic mapping of categorical traits in terms of statistical power and QTL parameter estimation. Compared with a fixed number of QTL alleles (two or four), the model with an infinite number of QTL alleles and normally distributed allelic effects results in loss of statistical power. The results imply that inbred designs (e.g. F2 or four-way crosses) with a few QTL alleles segregating or reducing number of QTL alleles (e.g. by selection) in outbred populations are desirable in genetic mapping of categorical traits using data from multiple families.

Fine-mapping of quantitative trait loci by identity by descent in outbred populations: application to milk production in dairy cattle.

We previously mapped a quantitative trait locus (QTL) affecting milk production to bovine chromosome 14. To refine the map position of this QTL, we have increased the density of the genetic map of BTA14q11-16 by addition of nine microsatellites and three single nucleotide polymorphisms. Fine-mapping of the QTL was accomplished by a two-tiered approach. In the first phase, we identified seven sires heterozygous "Qq" for the QTL by marker-assisted segregation analysis in a Holstein-Friesian pedigree comprising 1,158 individuals. In a second phase, we genotyped the seven selected sires for the newly developed high-density marker map and searched for a shared haplotype flanking an hypothetical, identical-by-descent QTL allele with large substitution effect. The seven chromosomes increasing milk fat percentage were indeed shown to carry a common chromosome segment with an estimated size of 5 cM predicted to contain the studied QTL. The same haplotype was shown to be associated with increased fat percentage in the general population as well, providing additional support in favor of the location of the QTL within the corresponding interval.

QTLs for resistance to Setosphaeria turcica in an early maturing Dent×Flint maize population

Quantitative trait loci (QTLs) for resistance to the fungal pathogen Setosphaeria turcica, the cause of northern corn leaf blight (NCLB), were mapped in a population of 220 F(3) families derived from a cross between two moderately resistant European inbred lines, D32 (dent) and D145 (flint). The population was genotyped with 87 RFLP and 7 SSR markers. Trials were conducted in the field in Switzerland, and in the greenhouse with selected F(3) families in Germany. The F(3) population segregated widely for resistance with transgression of the parents. By composite interval mapping, a total of 13 QTLs were detected with two disease ratings (0 and 3 weeks after flowering). Together these QTLs explained 48% and 62% of the phenotypic variation. Gene action at most QTLs was partially dominant. Eight out of the 13 QTL alleles for resistance were contributed by the more-resistant parent, D145. On chromosomes 3, 5 and 8, QTLs were located in the same chromosomal regions as QTLs in tropical and U.S. Corn Belt germplasm. Some QTLs affected NCLB, head smut and common rust at the same time, with alleles at these loci acting isodirectionally.

RFLP mapping of QTLs conferring salt tolerance during the vegetative stage in tomato

Quantitative trait loci (QTLs) contributing to salt tolerance during the vegetative stage in tomato were investigated using an interspecific backcross between a salt-sensitive Lycopersicon esculentum breeding line (NC84173, maternal and recurrent parent) and a salt-tolerant Lycopersicon pimpinellifolium accession (LA722). One hundred and nineteen BC1 individuals were genotyped for 151 RFLP markers and a linkage map was constructed. The parental lines and 119 BC1S1 families (self-pollinated progeny of the BC1 individuals) were evaluated for salt tolerance in aerated saline-solution cultures with the salt concentration gradually raised to 700 mM NaCl+70 mM CaCl2 (equivalent to an electrical conductivity of approximately 64 dS/m and a water potential of approximately −35.2 bars). The two parental lines were distinctly different in salt tolerance: 80% of the LA722 plants versus 25% of the NC84173 plants survived for at least 2 weeks after the final salt concentration was reached. The BC1S1 population exhibited a continuous variation, typical of quantitative traits, with the survival rate of the BC1S1 families ranging from 9% to 94% with a mean of 51%. Two QTL mapping techniques, interval mapping (using MAPMAKER/QTL) and single-marker analysis (using QGENE), were used to identify QTLs. The results of both methods were similar and five QTLs were identified on chromosomes 1 (two QTLs), 3, 5 and 9. Each QTL accounted for between 5.7% and 17.7%, with the combined effects (of all five QTLs) exceeding 46%, of the total phenotypic variation. All QTLs had the positive QTL alleles from the salt-tolerant parent. Across QTLs, the effects were mainly additive in nature. Digenic epistatic interactions were evident among several QTL-linked and QTL-unlinked markers. The overall results indicate that tomato salt tolerance during the vegetative stage could be improved by marker-assisted selection using interspecific variation.

Dynamic gene action at QTLs for resistance to Setosphaeria turcica in maize

Cultivars with quantitative resistance are widely used to control Setosphaeria turcica (Luttrell) Leonard & Suggs, the causal organism of northern corn leaf blight (NCLB). Here the effectiveness of quantitative trait loci (QTLs) for NCLB resistance was investigated over the course of host plant development in inoculated field trials. A population of 194–256 F2:3 lines derived from a cross between a susceptible Italian (Lo951) and a highly resistant African inbred line (CML202) was tested in three environments in Kenya. The traits assessed were the incubation period (IP), the percentage disease severity (DS 1 to 5, taken biweekly), and the area under the disease progress curve (AUDPC). Considering all resistance traits and environments, a total of 19 putative QTLs were detected by composite interval mapping using a linkage map with 110 RFLP markers. In the combined analysis across environments, nine QTLs were significant (LOD >3.0) for DS 3, recorded around flowering time, explaining 71% of the genotypic variance. Four of these nine QTLs displayed significant (P<0.05) QTL×environment (QTL×E) interaction. Most QTLs were already significant in the juvenile stage (IP) and became less effective after flowering. Across environments, three QTLs conditioned adult-plant resistance, in the sense that they were only significant after flowering. Six QTL alleles on chromosomes 2, 4, 5, 8, and 9 of CML202 should be useful for marker-assisted backcrossing.

Linkage disequilibrium in two‐stage marker‐assisted selection

Linkage disequilibrium in two‐stage marker‐assisted selection

Casein polymorphism and relation between milk production traits

Casein polymorphism and relation between milk production traits

Association of growth hormone loci with milk yield traits in Holstein bulls.

A pedigree analysis was used to investigate the association of bovine growth hormone loci with milk production traits of Holstein cattle. Holstein bulls were typed for three bovine growth hormone loci located in exon V, intron C, and the 3' region of the gene. Phenotypic data were daughter yield deviations for milk, fat, and protein yields and for fat and protein percentages. Analysis of linkage across families was applied to the data using one or two bovine growth hormone loci as markers linked to a putative biallelic quantitative trait locus. Estimated parameters were allele frequency, genotypic means, within-genotype standard deviation of a putative quantitative trait locus, and recombination fraction between the markers and the quantitative trait locus. Parameters were estimated by maximum likelihood techniques. The estimated frequency of the quantitative trait locus allele that decreased the value of the phenotype ranged from 0.1 for milk yield to 0.6 for protein yield. The estimated effect of an allele substitution at the quantitative trait locus, given in phenotypic standard deviation units, ranged from 0.75 for fat percentage to 1.6 for milk yield. The standard deviation within genotype ranged from 0.67 for fat yield to 0.87 for milk yield. The estimated recombination fraction was close to zero for protein percentage, indicating physical linkage between a quantitative trait locus affecting the trait and the bovine growth hormone loci.

The full-sib intercross line (FSIL): a QTL mapping design for outcrossing species

A full-sib intercross line (FSIL) is constructed in an outcrossing species by mating two parents and intercrossing their progeny to form a large intercross line. For given statistical power, a FSIL design requires only slightly more individuals than an F2 design derived from inbred line cross, but 6- to 10-fold fewer than a half-sib or full-sib design. Due to population-wide linkage disequilibrium, a FSIL is amenable to analysis by selective DNA pooling. In addition, a FSIL is maintained by continued intercrossing so that DNA samples and phenotypic information are accumulated across generations. Continued intercrossing also leads to map expansion and thus to increased mapping accuracy in the later generations. A FSIL can thus provide a bridge to positional cloning of quantitative trait loci (QTL) and marker-assisted selection in outcrossers; and is particularly effective in exploiting the QTL mapping potential of crosses between selection lines or phenotypically differentiated populations that differ in frequency, but are not at fixation, for alternative QTL alleles. In the course of the power analyses, it is shown that for F2 and FSIL designs, power is a function of Nd2 alone, where N is the total size of the mapping population and d is the standardized gene effect; while for half-sib and full-sib populations, power is a function of Nd2 and of the number of families included in the mapping population. This provides a convenient means of estimating power for a wide variety of mapping designs.

The importance of genetic diversity in livestock populations of the future.

Farm animal genetic diversity is required to meet current production needs in various environments, to allow sustained genetic improvement, and to facilitate rapid adaptation to changing breeding objectives. Production efficiency in pastoral species is closely tied to the use of diverse genetic types, but greater genetic uniformity has evolved in intensively raised species. In poultry, breeding decisions are directed by a few multinational companies and involve intense selection, the use of distinct production lines, and very large populations. In dairy cattle, the Holstein breed dominates production. Intensive sire selection is leading to relatively rapid inbreeding rates and raises questions about long-term effects of genetic drift. Key questions in management of farm animal genetic diversity involve the distribution of potentially useful quantitative trait locus alleles among global livestock breeds. Experiments with tomato, maize, and mice suggest that favorable alleles can exist in otherwise lowly productive stocks; this cryptic variation may potentially contribute to future selection response. Genetic improvement under relatively intense unidirectional selection may involve both increases in the frequency of favorable additive alleles as well as the progressive breakdown of homeostatic regulatory mechanisms established under the stabilizing selection that is characteristic of natural populations. Recombination among closely linked regulatory loci and new, potentially favorable mutations are possible sources of long-term genetic variation. A greater understanding of the potential that these alternative mechanisms have for supporting long-term genetic improvement and of genetic relationships among global livestock populations are priorities for managing farm animal genetic diversity.

A primary screen of the bovine genome for quantitative trait loci affecting carcass and growth traits.

A primary genomic screen for quantitative trait loci (QTL) affecting carcass and growth traits was performed by genotyping 238 microsatellite markers on 185 out of 300 total progeny from a Bos indicus x Bos taurus sire mated to Bos taurus cows. The following traits were analyzed for QTL effects: birth weight (BWT), weaning weight (WW), yearling weight (YW), hot carcass weight (HCW), dressing percentage (DP), fat thickness (FT), marbling score (MAR), longissimus muscle area (LMA), rib bone (RibB), rib fat (RibF), and rib muscle (RibM), and the predicted whole carcass traits, retail product yield (RPYD), fat trim yield (FATYD), bone yield (BOYD), retail product weight (RPWT), fat weight (FATWT), and bone weight (BOWT). Data were analyzed by generating an F-statistic profile computed at 1-cM intervals for each chromosome by the regression of phenotype on the conditional probability of receiving the Brahman allele from the sire. There was compelling evidence for a QTL allele of Brahman origin affecting an increase in RibB and a decrease in DP on chromosome 5 (BTA5). Putative QTL at or just below the threshold for genome-wide significance were as follows: an increase in RPYD and component traits on BTA2 and BTA13, an increase in LMA on BTA14, and an increase in BWT on BTA1. Results provided represent a portion of our efforts to identify and characterize QTL affecting carcass and growth traits.

Identification of trait-improving quantitative trait loci alleles from a wild rice relative, Oryza rufipogon.

Wild species are valued as a unique source of genetic variation, but they have rarely been used for the genetic improvement of quantitative traits. To identify trait-improving quantitative trait loci (QTL) alleles from exotic species, an accession of Oryza rufipogon, a relative of cultivated rice, was chosen on the basis of a genetic diversity study. An interspecific BC2 testcross population (V20A/O. rufipogon//V20B///V20B////Ce64) consisting of 300 families was evaluated for 12 agronomically important quantitative traits. The O. rufipogon accession was phenotypically inferior for all 12 traits. However, transgressive segregants that outperformed the original elite hybrid variety, V20A/Ce64, were observed for all traits examined. A set of 122 RFLP and microsatellite markers was used to identify QTL. A total of 68 significant QTL were identified, and of these, 35 (51%) had beneficial alleles derived from the phenotypically inferior O. rufipogon parent. Nineteen (54%) of these beneficial QTL alleles were free of deleterious effects on other characters. O. rufipogon alleles at two QTL on chromosomes 1 and 2 were associated with an 18 and 17% increase in grain yield per plant, respectively, without delaying maturity or increasing plant height. This discovery suggests that the innovative use of molecular maps and markers can alter the way geneticists utilize wild and exotic germplasm.

Molecular mapping of QTL for southwestern corn borer resistance, plant height and flowering in tropical maize

AbstractDevelopment of multiple insect resistance in tropical maize represents a major effort of the maize breeding programme at CIMMYT. Resistance to the southwestern corn borer (SWCB) is polygenically controlled with primarily additive gene action. Our main objective was to identify quantitative trait loci (QTL) involved in resistance to SWCB. Other objectives were to detect QTL in the same population for plant height, female flowering, and the anthesis‐silking interval (ASI). A population of 472 F2 individuals derived from a cross between the susceptible line Ki3 and the resistant inbred CML139, was restriction fragment length polymorphism (RFLP) genotyped using 110 maize probes. F3 families were rated for leaf‐feeding damage after artificial infestation at one location in three consecutive years. Height and flowering were measured in protected trials in two locations. QTL analyses were conducted using joint composite interval mapping. Seven QTL on chromosomes 3, 5, 6, 8, and 9 explained 30% of the phenotypic variance (σ2p) for SWCB damage. Most QTL alleles conferring resistance were contributed from CML139. QTL showed dominance, partial dominance and additive gene action. Eleven QTL dispersed across the genome were determined to affect plant height and explained 43% of σ2p. Four of these were in close proximity to loci with qualitative effects on plant height. Thirteen QTL (50% of sigma;2p) were identified for days to female flowering and nine (30% of σ2p) for ASI. Our results, along with those from other mapping studies at CIMMYT, are allowing us to formulate marker‐assisted selection schemes to complement the breeding efforts for such complex traits as borer resistance.