Genome-wide association with residual body weight gain in Bos indicus cattle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A mixed model QTL analysis for sugarcane multiple-harvest-location trial data

Sugarcane-breeding programs take at least 12 years to develop new commercial cultivars. Molecular markers offer a possibility to study the genetic architecture of quantitative traits in sugarcane, and they may be used in marker-assisted selection to speed up artificial selection. Although the performance of sugarcane progenies in breeding programs are commonly evaluated across a range of locations and harvest years, many of the QTL detection methods ignore two- and three-way interactions between QTL, harvest, and location. In this work, a strategy for QTL detection in multi-harvest-location trial data, based on interval mapping and mixed models, is proposed and applied to map QTL effects on a segregating progeny from a biparental cross of pre-commercial Brazilian cultivars, evaluated at two locations and three consecutive harvest years for cane yield (tonnes per hectare), sugar yield (tonnes per hectare), fiber percent, and sucrose content. In the mixed model, we have included appropriate (co)variance structures for modeling heterogeneity and correlation of genetic effects and non-genetic residual effects. Forty-six QTLs were found: 13 QTLs for cane yield, 14 for sugar yield, 11 for fiber percent, and 8 for sucrose content. In addition, QTL by harvest, QTL by location, and QTL by harvest by location interaction effects were significant for all evaluated traits (30 QTLs showed some interaction, and 16 none). Our results contribute to a better understanding of the genetic architecture of complex traits related to biomass production and sucrose content in sugarcane.

Mapping of angular leaf spot resistance QTL in common bean (Phaseolus vulgaris L.) under different environments

Background: Common bean (Phaseolus vulgaris L.) is the most important grain legume for human diet worldwide and the angular leaf spot (ALS) is one of the most devastating diseases of this crop, leading to yield losses as high as 80%. In an attempt to breed resistant cultivars, it is important to first understand the inheritance mode of resistance and to develop tools that could be used in assisted breeding. Therefore, the aim of this study was to identify quantitative trait loci (QTL) controlling resistance to ALS under natural infection conditions in the field and under inoculated conditions in the greenhouse. Results: QTL analyses were made using phenotypic data from 346 recombinant inbreed lines from the IAC-UNA x CAL 143 cross, gathered in three experiments, two of which were conducted in the field in different seasons and one in the greenhouse. Joint composite interval mapping analysis of QTL x environment interaction was performed. In all, seven QTLs were mapped on five linkage groups. Most of them, with the exception of two, were significant in all experiments. Among these, ALS10.1(DG,UC) presented major effects (R-2 between 16% - 22%). This QTL was found linked to the GATS11b marker of linkage group B10, which was consistently amplified across a set of common bean lines and was associated with the resistance. Four new QTLs were identified. Between them the ALS5.2 showed an important effect (9.4%) under inoculated conditions in the greenhouse. ALS4.2 was another major QTL, under natural infection in the field, explaining 10.8% of the variability for resistance reaction. The other QTLs showed minor effects on resistance. Conclusions: The results indicated a quantitative inheritance pattern of ALS resistance in the common bean line CAL 143. QTL x environment interactions were observed. Moreover, the major QTL identified on linkage group B10 could be important for bean breeding, as it was stable in all the environments. Thereby, the GATS11b marker is a potential tool for marker assisted selection for ALS resistance.

Studying the genetic basis of drought tolerance in sorghum by managed stress trials and adjustments for phenological and plant height differences

Managed environments in the form of well watered and water stressed trials were performed to study the genetic basis of grain yield and stay green in sorghum with the objective of validating previously detected QTL. As variations in phenology and plant height may influence QTL detection for the target traits, QTL for flowering time and plant height were introduced as cofactors in QTL analyses for yield and stay green. All but one of the flowering time QTL were detected near yield and stay green QTL. Similar co-localization was observed for two plant height QTL. QTL analysis for yield, using flowering time/plant height cofactors, led to yield QTL on chromosomes 2, 3, 6, 8 and 10. For stay green, QTL on chromosomes 3, 4, 8 and 10 were not related to differences in flowering time/plant height. The physical positions for markers in QTL regions projected on the sorghum genome suggest that the previously detected plant height QTL, Sb-HT9-1, and Dw2, in addition to the maturity gene, Ma5, had a major confounding impact on the expression of yield and stay green QTL. Co-localization between an apparently novel stay green QTL and a yield QTL on chromosome 3 suggests there is potential for indirect selection based on stay green to improve drought tolerance in sorghum. Our QTL study was carried out with a moderately sized population and spanned a limited geographic range, but still the results strongly emphasize the necessity of corrections for phenology in QTL mapping for drought tolerance traits in sorghum.

Gene by environment QTL mapping through multiple trait analyses in blood pressure salt-sensitivity: identification of a novel QTL in rat chromosome 5

Background The genetic mechanisms underlying interindividual blood pressure variation reflect the complex interplay of both genetic and environmental variables. The current standard statistical methods for detecting genes involved in the regulation mechanisms of complex traits are based on univariate analysis. Few studies have focused on the search for and understanding of quantitative trait loci responsible for gene × environmental interactions or multiple trait analysis. Composite interval mapping has been extended to multiple traits and may be an interesting approach to such a problem. Methods We used multiple-trait analysis for quantitative trait locus mapping of loci having different effects on systolic blood pressure with NaCl exposure. Animals studied were 188 rats, the progenies of an F2 rat intercross between the hypertensive and normotensive strain, genotyped in 179 polymorphic markers across the rat genome. To accommodate the correlational structure from measurements taken in the same animals, we applied univariate and multivariate strategies for analyzing the data. Results We detected a new quantitative train locus on a region close to marker R589 in chromosome 5 of the rat genome, not previously identified through serial analysis of individual traits. In addition, we were able to justify analytically the parametric restrictions in terms of regression coefficients responsible for the gain in precision with the adopted analytical approach. Conclusion Future work should focus on fine mapping and the identification of the causative variant responsible for this quantitative trait locus signal. The multivariable strategy might be valuable in the study of genetic determinants of interindividual variation of antihypertensive drug effectiveness.

Meta-analysis identifies 29 additional ulcerative colitis risk loci, increasing the number of confirmed associations to 47

Genome-wide association studies and candidate gene studies in ulcerative colitis have identified 18 susceptibility loci. We conducted a meta-analysis of six ulcerative colitis genome-wide association study datasets, comprising 6,687 cases and 19,718 controls, and followed up the top association signals in 9,628 cases and 12,917 controls. We identified 29 additional risk loci (P < 5 × 10(-8)), increasing the number of ulcerative colitis-associated loci to 47. After annotating associated regions using GRAIL, expression quantitative trait loci data and correlations with non-synonymous SNPs, we identified many candidate genes that provide potentially important insights into disease pathogenesis, including IL1R2, IL8RA-IL8RB, IL7R, IL12B, DAP, PRDM1, JAK2, IRF5, GNA12 and LSP1. The total number of confirmed inflammatory bowel disease risk loci is now 99, including a minimum of 28 shared association signals between Crohn's disease and ulcerative colitis.

IgE, IgGa, IgGb and IgG(T) serum antibody levels in offspring of two sires affected with equine recurrent airway obstruction

Equine recurrent airway obstruction (RAO) is a chronic lower airway disease of the horse caused by hypersensitivity reactions to inhaled stable dust, including mould spores such as Aspergillus fumigatus. The goals of this study were to investigate whether total serum IgE levels and allergen-specific IgE and IgG subclasses are influenced by genetic factors and/or RAO and whether quantitative trait loci (QTL) could be identified for these parameters. The offspring of two RAO-affected sires (S1: n=56 and S2: n=65) were grouped by stallion and disease status, and total serum IgE levels and specific IgE, IgGa, IgGb and IgG(T) levels against recombinant Aspergillus fumigatus 7 (rAspf7) were measured by ELISA. A panel of 315 microsatellite markers covering the 31 equine autosomes were used to genotype the stallions and their offspring. A whole-genome scan using half-sib regression interval mapping was performed for each of the IgG and IgE subclasses. There was no significant effect of disease status or sire on total IgE levels, but there was a significant effect of gender and age. rAspf7-specific IgGa levels were significantly higher in RAO-affected than in healthy horses. The offspring of S1 had significantly higher rAspf7-specific IgGa and IgE levels than those of S2. Five QTLs were significant chromosome-wide (P<0.01). QTLs for rAspf7-specific IgGa and IgE were identified on ECA 1, for rAspf7-specific IgGa and IgGb on ECA 24 and for rAspf7 IgGa on ECA 26. These results provide evidence for effects of disease status and genetics on allergen-specific IgGa and IgE.

Simulating the evolution of a clonal trait in plants with sexual and vegetative reproduction

Aims Phenotypic optimality models neglect genetics. However, especially when heterozygous genotypes ire fittest, evolving allele, genotype and phenotype frequencies may not correspond to predicted optima. This was not previously addressed for organisms with complex life histories. Methods Therefore, we modelled the evolution of a fitness-relevant trait of clonal plants, stolon internode length. We explored the likely case of air asymmetric unimodal fitness profile with three model types. In constant selection models (CSMs), which are gametic, but not spatially explicit, evolving allele frequencies in the one-locus and five-loci cases did not correspond to optimum stolon internode length predicted by the spatially explicit, but not gametic, phenotypic model. This deviation was due to the asymmetry of the fitness profile. Gametic, spatially explicit individual-based (SEIB) modeling allowed us relaxing the CSM assumptions of constant selection with exclusively sexual reproduction. Important findings For entirely vegetative or sexual reproduction, predictions. of the gametic SEIB model were close to the ones of spatially explicit CSMs gametic phenotypic models, hut for mixed modes of reproduction they appoximated those of gametic, not spatially explicit CSMs. Thus, in contrast to gametic SEIB models, phenotypic models and, especially for few loci, also CSMs can be very misleading. We conclude that the evolution of trails governed by few quantitative trait loci appears hardly predictable by simple models, that genetic algorithms aiming at technical optimization may actually, miss the optimum and that selection may lead to loci with smaller effects, in derived compared with ancestral lines.

Genetic Distance between Species Predicts Novel Trait Expression in Their Hybrids

Interspecific hybridization can generate transgressive hybrid phenotypes with extreme trait values exceeding the combined range of the parental species. Such variation can enlarge the working surface for natural selection, and may facilitate the evolution of novel adaptations where ecological opportunity exists. The number of quantitative trait loci fixed for different alleles in different species should increase with time since speciation. If transgression is caused by complementary gene action or epistasis, hybrids between more distant species should be more likely to display transgressive phenotypes. To test this prediction we collected data on transgression frequency from the literature, estimated genetic distances between the hybridizing species from gene sequences, and calculated the relationship between the two using phylogenetically controlled methods. We also tested if parental phenotypic divergence affected the occurrence of transgression. We found a highly significant positive correlation between transgression frequency and genetic distance in eudicot plants explaining 43% of the variance in transgression frequency. In total, 36% of the measured traits were transgressive. The predicted effect of time since speciation on transgressive segregation was unconfounded by the potentially conflicting effects of phenotypic differentiation between species. Our analysis demonstrates that the potential impact hybridization may have on phenotypic evolution is predictable from the genetic distance between species.

Accumulating mutations in series of haplotypes at the KIT and MITF loci are major determinants of white markings in Franches-Montagnes horses.

Coat color and pattern variations in domestic animals are frequently inherited as simple monogenic traits, but a number are known to have a complex genetic basis. While the analysis of complex trait data remains a challenge in all species, we can use the reduced haplotypic diversity in domestic animal populations to gain insight into the genomic interactions underlying complex phenotypes. White face and leg markings are examples of complex traits in horses where little is known of the underlying genetics. In this study, Franches-Montagnes (FM) horses were scored for the occurrence of white facial and leg markings using a standardized scoring system. A genome-wide association study (GWAS) was performed for several white patterning traits in 1,077 FM horses. Seven quantitative trait loci (QTL) affecting the white marking score with p-values p≤10(-4) were identified. Three loci, MC1R and the known white spotting genes, KIT and MITF, were identified as the major loci underlying the extent of white patterning in this breed. Together, the seven loci explain 54% of the genetic variance in total white marking score, while MITF and KIT alone account for 26%. Although MITF and KIT are the major loci controlling white patterning, their influence varies according to the basic coat color of the horse and the specific body location of the white patterning. Fine mapping across the MITF and KIT loci was used to characterize haplotypes present. Phylogenetic relationships among haplotypes were calculated to assess their selective and evolutionary influences on the extent of white patterning. This novel approach shows that KIT and MITF act in an additive manner and that accumulating mutations at these loci progressively increase the extent of white markings.

Hd6, a rice quantitative trait locus involved in photoperiod sensitivity, encodes the α subunit of protein kinase CK2

Hd6 is a quantitative trait locus involved in rice photoperiod sensitivity. It was detected in backcross progeny derived from a cross between the japonica variety Nipponbare and the indica variety Kasalath. To isolate a gene at Hd6, we used a large segregating population for the high-resolution and fine-scale mapping of Hd6 and constructed genomic clone contigs around the Hd6 region. Linkage analysis with P1-derived artificial chromosome clone-derived DNA markers delimited Hd6 to a 26.4-kb genomic region. We identified a gene encoding the α subunit of protein kinase CK2 (CK2α) in this region. The Nipponbare allele of CK2α contains a premature stop codon, and the resulting truncated product is undoubtedly nonfunctional. Genetic complementation analysis revealed that the Kasalath allele of CK2α increases days-to-heading. Map-based cloning with advanced backcross progeny enabled us to identify a gene underlying a quantitative trait locus even though it exhibited a relatively small effect on the phenotype.

Localization of atherosclerosis susceptibility loci to chromosomes 4 and 6 using the Ldlr knockout mouse model

Atherosclerosis is a complex disease resulting from the interaction of multiple genes. We have used the Ldlr knockout mouse model in an interspecific genetic cross to map atherosclerosis susceptibility loci. A total of 174 (MOLF/Ei × B6.129S7-Ldlrtm1Her) × C57BL/6J-Ldlrtm1Her backcross mice, homozygous for the Ldlr null allele, were fed a Western-type diet for 3 months and then killed for quantification of aortic lesions. A genome scan was carried out by using DNA pools and microsatellite markers spaced at ≈18-centimorgan intervals. Quantitative trait locus analysis of individual backcross mice confirmed linkages to chromosomes 4 (Athsq1, logarithm of odds = 6.2) and 6 (Athsq2, logarithm of odds = 6.7). Athsq1 affected lesions in females only whereas Athsq2 affected both sexes. Among females, the loci accounted for ≈50% of the total variance of lesion area. The susceptible allele at Athsq1 was derived from the MOLF/Ei genome whereas the susceptible allele at Athsq2 was derived from C57BL/6J. Inheritance of susceptible alleles at both loci conferred a 2-fold difference in lesion area, suggesting an additive effect of Athsq1 and Athsq2. No associations were observed between the quantitative trait loci and levels of plasma total cholesterol, high density lipoprotein cholesterol, non-high density lipoprotein cholesterol, insulin, or body weight. We provide strong evidence for complex inheritance of atherosclerosis in mice with elevated plasma low density lipoprotein cholesterol and show a major influence of nonlipoprotein-related factors on disease susceptibility. Athsq1 and Athsq2 represent candidate susceptibility loci for human atherosclerosis, most likely residing on chromosomes 1p36–32 and 12p13–12, respectively.

Multivariate QTL linkage analysis suggests a QTL for platelet count on chromosome 19q

Platelet count is a highly heritable trait with genetic factors responsible for around 80% of the phenotypic variance. We measured platelet count longitudinally in 327 monozygotic and 418 dizygotic twin pairs at 12, 14 and 16 years of age. We also performed a genome-wide linkage scan of these twins and their families in an attempt to localize QTLs that influenced variation in platelet concentrations. Suggestive linkage was observed on chromosome 19q13.13-19q13.31 at 12 (LOD=2.12, P=0.0009), 14 (LOD=2.23, P=0.0007) and 16 (LOD=1.01, P=0.016) years of age and multivariate analysis of counts at all three ages increased the LOD to 2.59 (P=0.0003). A possible candidate in this region is the gene for glycoprotein VI, a receptor involved in platelet aggregation. Smaller linkage peaks were also seen at 2p, 5p, 5q, 10p and 15q. There was little evidence for linkage to the chromosomal regions containing the genes for thrombopoietin (3q27) and the thrombopoietin receptor (1q34), suggesting that polymorphisms in these genes do not contribute substantially to variation in platelet count between healthy individuals.

Comparison of identity by descent and identity by state for detecting genetic regions under selection in a sorghum pedigree breeding program

Seventy sorghum inbred lines which formed part of the Queensland Department of Primary Industries (QDPI) sorghum breeding program were screened with 104 previously mapped RFLP markers. The lines were related by pedigree and consisted of ancestral source lines, intermediate lines and recent releases from the program. We compared the effect of defining marker alleles using either identity by state (IBS) or identity by descent (IBD) on our capacity to trace markers through the pedigree and detect evidence of selection for particular alleles. Allelic identities defined using IBD were much more sensitive for detecting non-Mendelian segregation in this pedigree. Only one marker allele showed significant evidence of selection when IBS was used compared with ten regions with particular allelic identities when IBD was used. Regions under selection were compared with the location of QTLs for agronomic traits known to be under selection in the breeding program. Only two of the ten regions were associated with known QTLs that matched with knowledge of the agronomic characteristics of the ancestral lines. Some of the other regions were hypothesised to be associated with genes for particular traits based on the properties of the ancestral source lines.

Genetic time-series analysis identifies a major QTL for in vivo alcohol metabolism not predicted by in vitro studies of structural protein polymorphism at the ADH1B or ADH1C loci

After ingestion of a standardized dose of ethanol, alcohol concentrations were assessed, over 3.5 hours from blood (six readings) and breath (10 readings) in a sample of 412 MZ and DZ twins who took part in an Alcohol Challenge Twin Study (ACTS). Nearly all participants were subsequently genotyped on two polymorphic SNPs in the ADH1B and ADH1C loci known to affect in vitro ADH activity. In the DZ pairs, 14 microsatellite markers covering a 20.5 cM region on chromosome 4 that includes the ADH gene family were assessed, Variation in the timed series of autocorrelated blood and breath alcohol readings was studied using a bivariate simplex design. The contribution of a quantitative trait locus (QTL) or QTL's linked to the ADH region was estimated via a mixture of likelihoods weighted by identity-by-descent probabilities. The effects of allelic substitution at the ADH1B and ADH1C loci were estimated in the means part of the model simultaneously with the effects sex and age. There was a major contribution to variance in alcohol metabolism due to a QTL which accounted for about 64% of the additive genetic covariation common to both blood and breath alcohol readings at the first time point. No effects of the ADH1B*47His or ADH1C*349Ile alleles on in vivo metabolism were observed, although these have been shown to have major effects in vitro. This implies that there is a major determinant of variation for in vivo alcohol metabolism in the ADH region that is not accounted for by these polymorphisms. Earlier analyses of these data suggested that alcohol metabolism is related to drinking behavior and imply that this QTL may be protective against alcohol dependence.