Mouse models and quantitative trait loci of susceptibility to bleomycin- and radiation-induced pulmonary fibrosis

Radiotherapy involving the thoracic cavity and chemotherapy with the drug bleomycin are both dose limited by the development of pulmonary fibrosis. From evidence that there is variation in the population in susceptibility to pulmonary fibrosis, and animal data, it was hypothesized that individual variation in susceptibility to bleomycin-induced, or radiation-induced, pulmonary fibrosis is, in part, genetically controlled. In this thesis a three generation mouse genetic model of C57BL/6J (fibrosis prone) and C3Hf/Kam (fibrosis resistant) mouse strains and F1 and F2 (F1 intercross) progeny derived from the parental strains was developed to investigate the genetic basis of susceptibility to fibrosis. In the bleomycin studies the mice received 100 mg/kg (125 for females) of bleomycin, via mini osmotic pump. The animals were sacrificed at eight weeks following treatment or when their breathing rate indicated respiratory distress. In the radiation studies the mice were given a single dose of 14 or 16 Gy (Co$\sp{60})$ to the whole thorax and were sacrificed when moribund. The phenotype was defined as the percent of fibrosis area in the left lung as quantified with image analysis of histological sections. Quantitative trait loci (QTL) mapping was used to identify the chromosomal location of genes which contribute to susceptibility to bleomycin-induced pulmonary fibrosis in C57BL/6J mice compared to C3Hf/Kam mice and to determine if the QTL's which influence susceptibility to bleomycin-induced lung fibrosis in these progenitor strains could be implicated in susceptibility to radiation-induced lung fibrosis. For bleomycin, a genome wide scan revealed QTL's on chromosome 17, at the MHC, (LOD = 11.7 for males and 7.2 for females) accounting for approximately 21% of the phenotypic variance, and on chromosome 11 (LOD = 4.9), in male mice only, adding 8% of phenotypic variance. The bleomycin QTL on chromosome 17 was also implicated for susceptibility to radiation-induced fibrosis (LOD = 5.0) and contributes 7% of the phenotypic variance in the radiation study. In conclusion, susceptibility to both bleomycin-induced and radiation-induced pulmonary fibrosis are heritable traits, and are influenced by a genetic factor which maps to a genomic region containing the MHC. ^

Genome wide scan for quantitative trait loci affecting tick resistance in cattle (Bos taurus x Bos indicus)

Background : In tropical countries, losses caused by bovine tick Rhipicephalus (Boophilus) microplus infestation have a tremendous economic impact on cattle production systems. Genetic variation between Bos taurus and Bos indicus to tick resistance and molecular biology tools might allow for the identification of molecular markers linked to resistance traits that could be used as an auxiliary tool in selection programs. The objective of this work was to identify QTL associated with tick resistance/susceptibility in a bovine F2 population derived from the Gyr (Bos indicus) x Holstein (Bos taurus) cross. Results: Through a whole genome scan with microsatellite markers, we were able to map six genomic regions associated with bovine tick resistance. For most QTL, we have found that depending on the tick evaluation season (dry and rainy) different sets of genes could be involved in the resistance mechanism. We identified dry season specific QTL on BTA 2 and 10, rainy season specific QTL on BTA 5, 11 and 27. We also found a highly significant genome wide QTL for both dry and rainy seasons in the central region of BTA 23. Conclusions: The experimental F2 population derived from Gyr x Holstein cross successfully allowed the identification of six highly significant QTL associated with tick resistance in cattle. QTL located on BTA 23 might be related with the bovine histocompatibility complex. Further investigation of these QTL will help to isolate candidate genes involved with tick resistance in cattle.

Quantitative Trait Loci Mapping and The Genetic Basis of Heterosis in Maize and Rice

Despite its importance to agriculture, the genetic basis of heterosis is still not well understood. The main competing hypotheses include dominance, overdominance, and epistasis. NC design III is an experimental design that. has been used for estimating the average degree of dominance of quantitative trait 106 (QTL) and also for studying heterosis. In this study, we first develop a multiple-interval mapping (MIM) model for design III that provides a platform to estimate the number, genomic positions, augmented additive and dominance effects, and epistatic interactions of QTL. The model can be used for parents with any generation of selling. We apply the method to two data sets, one for maize and one for rice. Our results show that heterosis in maize is mainly due to dominant gene action, although overdominance of individual QTL could not completely be ruled out due to the mapping resolution and limitations of NC design III. For rice, the estimated QTL dominant effects could not explain the observed heterosis. There is evidence that additive X additive epistatic effects of QTL could be the main cause for the heterosis in rice. The difference in the genetic basis of heterosis seems to be related to open or self pollination of the two species. The MIM model for NC design III is implemented in Windows QTL Cartographer, a freely distributed software.

Quantitative trait loci for agronomic and seed quality traits in an F-2 and F-4 : 6 soybean population

Molecular breeding is becoming more practical as better technology emerges. The use of molecular markers in plant breeding for indirect selection of important traits can favorably impact breeding efficiency. The purpose of this research is to identify quantitative trait loci (QTL) on molecular linkage groups (MLG) which are associated with seed protein concentration, seed oil concentration, seed size, plant height, lodging, and maturity, in a population from a cross between the soybean cultivars 'Essex' and 'Williams.' DNA was extracted from F-2 generation soybean leaves and amplified via polymerase chain reaction (PCR) using simple sequence repeat (SSR) markers. Markers that were polymorphic between the parents were analyzed against phenotypic trait data from the F-2 and F-4:6 generation. For the F-2 population, significant additive QTL were Satt540 (MLG M, maturity, r(2)=0.11; height, r(2)=0.04, seed size, r(2)=0.061, Satt373 (MLG L, seed size, r(2)=0.04; height, r(2)=0.14), Satt50 (MLG A1, maturity r(2)=0.07), Satt14 (MLG D2, oil, r(2)=0.05), and Satt251 (protein r(2)=0.03, oil, r(2)=0.04). Significant dominant QTL for the F-2 population were Satt540 (MLG M, height, r(2)=0.04; seed size, r(2)=0.06) and Satt14 (MLG D2, oil, r(2)=0.05). In the F-4:6 generation significant additive QTL were Satt239 (MLG I, height, r(2)=0.02 at Knoxville, TN and r(2)=0.03 at Springfield, TN), Satt14 (MLG D2, seed size, r(2)=0.14 at Knoxville, TN), Satt373 (MLG L, protein, r(2)=0.04 at Knoxville, TN) and Satt251 (MLG B I, lodging r(2)=0.04 at Springfield, TN). Averaged over both environments in the F-4:6 generation, significant additive QTL were identified as Satt251 (MLG B 1, protein, r(2)=0.03), and Satt239 (MLG 1, height, r(2)=0.03). The results found in this study indicate that selections based solely on these QTL would produce limited gains (based on low r(2) values). Few QTL were detected to be stable across environments. Further research to identify stable QTL over environments is needed to make marker-assisted approaches more widely adopted by soybean breeders.

Two-locus Linkage Analysis Applied to Putative Quantitative Trait Loci for Lipoprotein(a) Levels

Plasma levels of lipoprotein(a) _ Lp(a) _ are associated with cardiovascular risk (Danesh et al., 2000) and were long believed to be influenced by the LPA locus on chromosome 6q27 only. However, a recent report of Broeckel et al. (2002) suggested the presence of a second quantitative trait locus on chromosome 1 influencing Lp(a) levels. Using a two-locus model, we found no evidence for an additional Lp(a) locus on chromosome 1 in a linkage study among 483 dizygotic twin pairs.

Genetic parameters and mapping quantitative trait loci associated with tibia traits in broilers.

Abstract: Selection among broilers for performance traits is resulting in locomotion problems and bone disorders, once skeletal structure is not strong enough to support body weight in broilers with high growth rates. In this study, genetic parameters were estimated for body weight at 42 days of age (BW42), and tibia traits (length, width, and weight) in a population of broiler chickens. Quantitative trait loci (QTL) were identified for tibia traits to expand our knowledge of the genetic architecture of the broiler population. Genetic correlations ranged from 0.56 +/- 0.18 (between tibia length and BW42) to 0.89 +/- 0.06 (between tibia width and weight), suggesting that these traits are either controlled by pleiotropic genes or by genes that are in linkage disequilibrium. For QTL mapping, the genome was scanned with 127 microsatellites, representing a coverage of 2630 cM. Eight QTL were mapped on Gallus gallus chromosomes (GGA): GGA1, GGA4, GGA6, GGA13, and GGA24. The QTL regions for tibia length and weight were mapped on GGA1, between LEI0079 and MCW145 markers. The gene DACH1 is located in this region; this gene acts to form the apical ectodermal ridge, responsible for limb development. Body weight at 42 days of age was included in the model as a covariate for selection effect of bone traits. Two QTL were found for tibia weight on GGA2 and GGA4, and one for tibia width on GGA3. Information originating from these QTL will assist in the search for candidate genes for these bone traits in future studies.

Gene expression variation and expression quantitative trait mapping of human chromosome 21 genes.

Inter-individual differences in gene expression are likely to account for an important fraction of phenotypic differences, including susceptibility to common disorders. Recent studies have shown extensive variation in gene expression levels in humans and other organisms, and that a fraction of this variation is under genetic control. We investigated the patterns of gene expression variation in a 25 Mb region of human chromosome 21, which has been associated with many Down syndrome (DS) phenotypes. Taqman real-time PCR was used to measure expression variation of 41 genes in lymphoblastoid cells of 40 unrelated individuals. For 25 genes found to be differentially expressed, additional analysis was performed in 10 CEPH families to determine heritabilities and map loci harboring regulatory variation. Seventy-six percent of the differentially expressed genes had significant heritabilities, and genomewide linkage analysis led to the identification of significant eQTLs for nine genes. Most eQTLs were in trans, with the best result (P=7.46 x 10(-8)) obtained for TMEM1 on chromosome 12q24.33. A cis-eQTL identified for CCT8 was validated by performing an association study in 60 individuals from the HapMap project. SNP rs965951 located within CCT8 was found to be significantly associated with its expression levels (P=2.5 x 10(-5)) confirming cis-regulatory variation. The results of our study provide a representative view of expression variation of chromosome 21 genes, identify loci involved in their regulation and suggest that genes, for which expression differences are significantly larger than 1.5-fold in control samples, are unlikely to be involved in DS-phenotypes present in all affected individuals.

Methods for testing association between uncertain genotypes and quantitative traits.

Interpretability and power of genome-wide association studies can be increased by imputing unobserved genotypes, using a reference panel of individuals genotyped at higher marker density. For many markers, genotypes cannot be imputed with complete certainty, and the uncertainty needs to be taken into account when testing for association with a given phenotype. In this paper, we compare currently available methods for testing association between uncertain genotypes and quantitative traits. We show that some previously described methods offer poor control of the false-positive rate (FPR), and that satisfactory performance of these methods is obtained only by using ad hoc filtering rules or by using a harsh transformation of the trait under study. We propose new methods that are based on exact maximum likelihood estimation and use a mixture model to accommodate nonnormal trait distributions when necessary. The new methods adequately control the FPR and also have equal or better power compared to all previously described methods. We provide a fast software implementation of all the methods studied here; our new method requires computation time of less than one computer-day for a typical genome-wide scan, with 2.5 M single nucleotide polymorphisms and 5000 individuals.

The effects of dominance, regular inbreeding and sampling design on Q(ST), an estimator of population differentiation for quantitative traits.

To test whether quantitative traits are under directional or homogenizing selection, it is common practice to compare population differentiation estimates at molecular markers (F(ST)) and quantitative traits (Q(ST)). If the trait is neutral and its determinism is additive, then theory predicts that Q(ST) = F(ST), while Q(ST) > F(ST) is predicted under directional selection for different local optima, and Q(ST) < F(ST) is predicted under homogenizing selection. However, nonadditive effects can alter these predictions. Here, we investigate the influence of dominance on the relation between Q(ST) and F(ST) for neutral traits. Using analytical results and computer simulations, we show that dominance generally deflates Q(ST) relative to F(ST). Under inbreeding, the effect of dominance vanishes, and we show that for selfing species, a better estimate of Q(ST) is obtained from selfed families than from half-sib families. We also compare several sampling designs and find that it is always best to sample many populations (>20) with few families (five) rather than few populations with many families. Provided that estimates of Q(ST) are derived from individuals originating from many populations, we conclude that the pattern Q(ST) > F(ST), and hence the inference of directional selection for different local optima, is robust to the effect of nonadditive gene actions.

Expression quantitative trait locus mapping across water availability environments reveals contrasting associations with genomic features in Arabidopsis.

The regulation of gene expression is crucial for an organism's development and response to stress, and an understanding of the evolution of gene expression is of fundamental importance to basic and applied biology. To improve this understanding, we conducted expression quantitative trait locus (eQTL) mapping in the Tsu-1 (Tsushima, Japan) × Kas-1 (Kashmir, India) recombinant inbred line population of Arabidopsis thaliana across soil drying treatments. We then used genome resequencing data to evaluate whether genomic features (promoter polymorphism, recombination rate, gene length, and gene density) are associated with genes responding to the environment (E) or with genes with genetic variation (G) in gene expression in the form of eQTLs. We identified thousands of genes that responded to soil drying and hundreds of main-effect eQTLs. However, we identified very few statistically significant eQTLs that interacted with the soil drying treatment (GxE eQTL). Analysis of genome resequencing data revealed associations of several genomic features with G and E genes. In general, E genes had lower promoter diversity and local recombination rates. By contrast, genes with eQTLs (G) had significantly greater promoter diversity and were located in genomic regions with higher recombination. These results suggest that genomic architecture may play an important a role in the evolution of gene expression.

FastEpistasis: a high performance computing solution for quantitative trait epistasis.

Motivation: Genome-wide association studies have become widely used tools to study effects of genetic variants on complex diseases. While it is of great interest to extend existing analysis methods by considering interaction effects between pairs of loci, the large number of possible tests presents a significant computational challenge. The number of computations is further multiplied in the study of gene expression quantitative trait mapping, in which tests are performed for thousands of gene phenotypes simultaneously. Results: We present FastEpistasis, an efficient parallel solution extending the PLINK epistasis module, designed to test for epistasis effects when analyzing continuous phenotypes. Our results show that the algorithm scales with the number of processors and offers a reduction in computation time when several phenotypes are analyzed simultaneously. FastEpistasis is capable of testing the association of a continuous trait with all single nucleotide polymorphism ( SNP) pairs from 500 000 SNPs, totaling 125 billion tests, in a population of 5000 individuals in 29, 4 or 0.5 days using 8, 64 or 512 processors.

Mapping of quantitative trait loci for thermosensitive genic male sterility in indica rice

The objective of this work was to select and use microsatellite markers, to map genomic regions associated with the genetic control of thermosensitive genic male sterility (TGMS) in rice. An F2 population, derived from the cross between fertile and TGMS indica lines, was used to construct a microsatellite-based genetic map of rice. The TGMS phenotype showed a continuous variation in the segregant population. A low level of segregation distortion was detected in the F2 (14.65%), whose cause was found to be zygotic selection. There was no evidence suggesting a cause-effect relationship between zygotic selection and the control of TGMS in this cross. A linkage map comprising 1,213.3 cM was constructed based on the segregation data of the F2 population. Ninety-five out of 116 microsatellite polymorphic markers were assembled into 11 linkage groups, with an average of 12.77 cM between two adjacent marker loci. The phenotypic and genotypic data allowed for the identification of three new quantitative trait loci (QTL) for thermosensitive genic male sterility in indica rice. Two of the QTL were mapped on chromosomes that, so far, have not been associated with the genetic control of the TGMS trait (chromosomes 1 and 12). The third QTL was mapped on chromosome 7, where a TGMS locus (tms2) has recently been mapped. Allelic tests will have to be developed, in order to clarify if the two regions are the same or not.

A hyperactive quantitative trait locus allele of Arabidopsis BRX contributes to natural variation in root growth vigor.

Quantitative trait loci analysis of natural Arabidopsis thaliana accessions is increasingly exploited for gene isolation. However, to date this has mostly revealed deleterious mutations. Among them, a loss-of-function allele identified the root growth regulator BREVIS RADIX (BRX). Here we present evidence that BRX and the paralogous BRX-LIKE (BRXL) genes are under selective constraint in monocotyledons as well as dicotyledons. Unexpectedly, however, whereas none of the Arabidopsis orthologs except AtBRXL1 could complement brx null mutants when expressed constitutively, nearly all monocotyledon BRXLs tested could. Thus, BRXL proteins seem to be more diversified in dicotyledons than in monocotyledons. This functional diversification was correlated with accelerated rates of sequence divergence in the N-terminal regions. Population genetic analyses of 30 haplotypes are suggestive of an adaptive role of AtBRX and AtBRXL1. In two accessions, Lc-0 and Lov-5, seven amino acids are deleted in the variable region between the highly conserved C-terminal, so-called BRX domains. Genotyping of 42 additional accessions also found this deletion in Kz-1, Pu2-7, and Ws-0. In segregating recombinant inbred lines, the Lc-0 allele (AtBRX(Lc-0)) conferred significantly enhanced root growth. Moreover, when constitutively expressed in the same regulatory context, AtBRX(Lc-0) complemented brx mutants more efficiently than an allele without deletion. The same was observed for AtBRXL1, which compared with AtBRX carries a 13 amino acid deletion that encompasses the deletion found in AtBRX(Lc-0). Thus, the AtBRX(Lc-0) allele seems to contribute to natural variation in root growth vigor and provides a rare example of an experimentally confirmed, hyperactive allelic variant.