Genomic Analysis of Wild Tomato Introgressions Determining Metabolism- and Yield-Associated Traits

With the aim of determining the genetic basis of metabolic regulation in tomato fruit, we constructed a detailed physical map of genomic regions spanning previously described metabolic quantitative trait loci of a Solanum pennellii introgression line population. Two genomic libraries from S. pennellii were screened with 104 colocated markers from five selected genomic regions, and a total of 614 bacterial artificial chromosome (BAC)/cosmids were identified as seed clones. Integration of sequence data with the genetic and physical maps of Solanum lycopersicum facilitated the anchoring of 374 of these BAC/cosmid clones. The analysis of this information resulted in a genome-wide map of a nondomesticated plant species and covers 10% of the physical distance of the selected regions corresponding to approximately 1% of the wild tomato genome. Comparative analyses revealed that S. pennellii and domesticated tomato genomes can be considered as largely colinear. A total of 1,238,705 bp from both BAC/cosmid ends and nine large insert clones were sequenced, annotated, and functionally categorized. The sequence data allowed the evaluation of the level of polymorphism between the wild and cultivated tomato species. An exhaustive microsynteny analysis allowed us to estimate the divergence date of S. pennellii and S. lycopersicum at 2.7 million years ago. The combined results serve as a reference for comparative studies both at the macrosyntenic and microsyntenic levels. They also provide a valuable tool for fine-mapping of quantitative trait loci in tomato. Furthermore, they will contribute to a deeper understanding of the regulatory factors underpinning metabolism and hence defining crop chemical composition.

Detecting Major Genes Controlling Robustness of Chicken Body Weight Using Double Generalized Linear Models

Detecting both the majors genes that control the phenotypic mean and those controlling phenotypic variance has been raised in quantitative trait loci analysis. In order to mapping both kinds of genes, we applied the idea of the classic Haley-Knott regression to double generalized linear models. We performed both kinds of quantitative trait loci detection for a Red Jungle Fowl x White Leghorn F2 intercross using double generalized linear models. It is shown that double generalized linear model is a proper and efficient approach for localizing variance-controlling genes. We compared two models with or without fixed sex effect and prefer including the sex effect in order to reduce the residual variances. We found that different genes might take effect on the body weight at different time as the chicken grows.

Physical mapping of the Nile tilapia (Oreochromis niloticus) genome by fluorescent in situ hybridization of repetitive DNAs to metaphase chromosomes - a review

The Nile tilapia (Oreochromis niloticus) has received increasing scientific interest over the past few decades for two reasons: first, tilapia is an enormously important species in aquaculture worldwide, especially in regions where there is a chronic shortage of animal protein; and second, this teleost fish belongs to the fascinating group of cichlid fishes that have undergone a rapid and extensive radiation of much interest to evolutionary biologists. Currently, studies based on physical and genetic mapping of the Nile tilapia genome offer the best opportunities for applying genomics to such diverse questions and issues as phylogeography, isolation of quantitative trait loci involved in behaviour, morphology, and disease, and overall improvement of aquacultural stocks. In this review, we have integrated molecular cytogenetic data for the Nile tilapia describing the chromosomal location of the repetitive DNA sequences, satellite DNAs, telomeres, 45S and 5S rDNAs, and the short and long interspersed nucleotide elements [short interspersed nuclear elements (SINEs) and long interspersed nuclear elements (LINEs)], and provide the beginnings of a physical genome map for this important teleost fish. (C) 2004 Elsevier B.V. All rights reserved.

Mapping QTLs on chicken chromosome 1 for performance and carcass traits in a broiler x layer cross

With the objective of mapping quantitative trait loci (QTLs) for performance and carcass traits, an F-2 chicken population was developed by crossing broiler and layer lines. A total of 2063 F-2 chicks in 21 full-sib families were reared as broilers and slaughtered at 42 days of age. Seventeen performance and carcass traits were measured. Parental (F-0) and F-1 individuals were genotyped with 80 microsatellites from chicken chromosome 1 to select informative markers. Thirty-three informative markers were used for selective genotyping of F-2 individuals with extreme phenotypes for body weight at 42 days of age (BW42). Based on the regions identified by selective genotyping, seven full-sib families (649 F-2 chicks) were genotyped with 26 markers. Quantitative trait loci affecting body weight, feed intake, carcass weight, drums and thighs weight and abdominal fat weight were mapped to regions already identified in other populations. Quantitative trait loci for weights of gizzard, liver, lungs, heart and feet, as well as length of intestine, not previously described in the literature were mapped on chromosome 1. This F-2 population can be used to identify novel QTLs and constitutes a new resource for studies of genes related to growth and carcass traits in poultry.

Genome-wide association study for birth weight in Nellore cattle points to previously described orthologous genes affecting human and bovine height

Background: Birth weight (BW) is an economically important trait in beef cattle, and is associated with growth- and stature-related traits and calving difficulty. One region of the cattle genome, located on Bos primigenius taurus chromosome 14 (BTA14), has been previously shown to be associated with stature by multiple independent studies, and contains orthologous genes affecting human height. A genome-wide association study (GWAS) for BW in Brazilian Nellore cattle (Bos primigenius indicus) was performed using estimated breeding values (EBVs) of 654 progeny-tested bulls genotyped for over 777,000 single nucleotide polymorphisms (SNPs).Results: The most significant SNP (rs133012258, PGC = 1.34 × 10-9), located at BTA14:25376827, explained 4.62% of the variance in BW EBVs. The surrounding 1 Mb region presented high identity with human, pig and mouse autosomes 8, 4 and 4, respectively, and contains the orthologous height genes PLAG1, CHCHD7, MOS, RPS20, LYN, RDHE2 (SDR16C5) and PENK. The region also overlapped 28 quantitative trait loci (QTLs) previously reported in literature by linkage mapping studies in cattle, including QTLs for birth weight, mature height, carcass weight, stature, pre-weaning average daily gain, calving ease, and gestation length.Conclusions: This study presents the first GWAS applying a high-density SNP panel to identify putative chromosome regions affecting birth weight in Nellore cattle. These results suggest that the QTLs on BTA14 associated with body size in taurine cattle (Bos primigenius taurus) also affect birth weight and size in zebu cattle (Bos primigenius indicus). © 2013 Utsunomiya et al.; licensee BioMed Central Ltd.

A genome-wide scan for selection signatures in Nellore cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Effect of IGF1, GH, and PIT1 markers on the genetic parameters of growth and reproduction traits in Canchim cattle

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

Comparative analysis of the river buffalo somatostatin gene

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

DEPTOR Cell-Autonomously Promotes Adipogenesis, and Its Expression Is Associated with Obesity

DEP domain-containing mTOR-interacting protein (DEPTOR) inhibits the mechanistic target of rapamycin (mTOR), but its in vivo functions are unknown. Previous work indicates that Deptor is part of the Fob3a quantitative trait locus (QTL) linked to obesity/leanness in mice, with Deptor expression being elevated in white adipose tissue (WAT) of obese animals. This relation is unexpected, considering the positive role of mTOR in adipogenesis. Here, we dissected the Fob3a QTL and show that Deptor is the highest-priority candidate promoting WAT expansion in this model. Consistently, transgenic mice overexpressing DEPTOR accumulate more WAT. Furthermore, in humans, DEPTOR expression in WAT correlates with the degree of obesity. We show that DEPTOR is induced by glucocorticoids during adipogenesis and that its overexpression promotes, while its suppression blocks, adipogenesis. DEPTOR activates the proadipogenic Akt/PKB-PPAR-gamma axis by dampening mTORC1-mediated feedback inhibition of insulin signaling. These results establish DEPTOR as a new regulator of adipogenesis.

Functional markers for gene mapping and genetic diversity studies in sugarcane

Abstract Background The database of sugarcane expressed sequence tags (EST) offers a great opportunity for developing molecular markers that are directly associated with important agronomic traits. The development of new EST-SSR markers represents an important tool for genetic analysis. In sugarcane breeding programs, functional markers can be used to accelerate the process and select important agronomic traits, especially in the mapping of quantitative traits loci (QTL) and plant resistant pathogens or qualitative resistance loci (QRL). The aim of this work was to develop new simple sequence repeat (SSR) markers in sugarcane using the sugarcane expressed sequence tag (SUCEST database). Findings A total of 365 EST-SSR molecular markers with trinucleotide motifs were developed and evaluated in a collection of 18 genotypes of sugarcane (15 varieties and 3 species). In total, 287 of the EST-SSRs markers amplified fragments of the expected size and were polymorphic in the analyzed sugarcane varieties. The number of alleles ranged from 2-18, with an average of 6 alleles per locus, while polymorphism information content values ranged from 0.21-0.92, with an average of 0.69. The discrimination power was high for the majority of the EST-SSRs, with an average value of 0.80. Among the markers characterized in this study some have particular interest, those that are related to bacterial defense responses, generation of precursor metabolites and energy and those involved in carbohydrate metabolic process. Conclusions These EST-SSR markers presented in this work can be efficiently used for genetic mapping studies of segregating sugarcane populations. The high Polymorphism Information Content (PIC) and Discriminant Power (DP) presented facilitate the QTL identification and marker-assisted selection due the association with functional regions of the genome became an important tool for the sugarcane breeding program.

Molecular characterization of five porcine candidate genes for drip loss in pork

Drip loss is the loss of fluid from a piece of meat without mechanical force and represents an important meat quality trait. Previous work revealed a quantitative trait locus (QTL) for drip loss in pork in an experimental Duroc x Pietrain (DUPI) F2 family on SSC 5. Based on functional data indicating their possible involvement in water holding capacity and their expression in skeletal muscle, we selected five positional candidates (ACO2, ADSL, CBY1, KCNJ4, PLA2AG6) out of 130 predicted genes in the QTL interval for further analysis. We performed a mutation analysis of all coding exons and discovered 204 polymorphisms. We genotyped 39 single nucleotide polymorphisms (SNPs) in 192 Pietrain pigs with extreme drip loss phenotypes and detected a possible association with drip loss for one non-coding SNP in the ADSL gene (ss107793818, p(raw) = 0.021). Correspondingly, ADSL diplotypes were associated with drip loss and pH1 of M. longissimus dorsi. However, after correction for multiple testing, none of the tested SNPs were significantly associated with drip loss. One possible explanation for these results is that one of the QTL-alleles from the experimental DUPI family may be fixed or nearly fixed in the tested Pietrain population.

A high-resolution comparative radiation hybrid map of equine chromosome 4q12-q22

In this study, we present a comprehensive 5000-rad radiation hybrid map of a 40-cM region on equine chromosome 4 (ECA4) that contains quantitative trait loci for equine osteochondrosis. We mapped 29 gene-associated sequence tagged site markers using primers designed from equine expressed sequence tags or BAC clones in the ECA4q12-q22 region. Three blocks of conserved synteny, showing two chromosomal breakpoints, were identified in the segment of ECA4q12-q22. Markers from other segments of HSA7q mapped to ECA13p and ECA4p, and a region of HSA7p was homologous to ECA13p. Therefore, we have improved the resolution of the human-equine comparative map, which allows the identification of candidate genes underlying traits of interest.

Genome-wide search for markers associated with osteochondrosis in Hanoverian warmblood horses

A genome-wide scan was performed to detect quantitative trait loci (QTLs) for osteochondrosis (OC) and osteochondrosis dissecans (OCD) in horses. The marker set comprised 260 microsatellites. We collected data from 211 Hanoverian warmblood horses consisting of 14 paternal half-sib families. Traits used were OC (fetlock and/or hock joints affected), OCD (fetlock and/or hock joints affected), fetlock OC, fetlock OCD, hock OC, and hock OCD. The first genome scan included 172 microsatellite markers. In a second step 88 additional markers were chosen to refine putative QTLs found in the first scan. Genome-wide significant QTLs were located on equine chromosomes 2, 4, 5, and 16. QTLs for fetlock OC and hock OC partly overlapped on the same chromosomes, indicating that these traits may be genetically related. QTLs reached the chromosome-wide significance level on eight different equine chromosomes: 2, 3, 4, 5, 15, 16, 19, and 21. This whole-genome scan was a first step toward the identification of candidate genome regions harboring genes responsible for equine OC. Further investigations are necessary to refine the map positions of the QTLs already identified for OC.

Genetic association studies under the population stratification, family pedigree and application to genome-wide association studies

This dissertation has three separate parts: the first part deals with the general pedigree association testing incorporating continuous covariates; the second part deals with the association tests under population stratification using the conditional likelihood tests; the third part deals with the genome-wide association studies based on the real rheumatoid arthritis (RA) disease data sets from Genetic Analysis Workshop 16 (GAW16) problem 1. Many statistical tests are developed to test the linkage and association using either case-control status or phenotype covariates for family data structure, separately. Those univariate analyses might not use all the information coming from the family members in practical studies. On the other hand, the human complex disease do not have a clear inheritance pattern, there might exist the gene interactions or act independently. In part I, the new proposed approach MPDT is focused on how to use both the case control information as well as the phenotype covariates. This approach can be applied to detect multiple marker effects. Based on the two existing popular statistics in family studies for case-control and quantitative traits respectively, the new approach could be used in the simple family structure data set as well as general pedigree structure. The combined statistics are calculated using the two statistics; A permutation procedure is applied for assessing the p-value with adjustment from the Bonferroni for the multiple markers. We use simulation studies to evaluate the type I error rates and the powers of the proposed approach. Our results show that the combined test using both case-control information and phenotype covariates not only has the correct type I error rates but also is more powerful than the other existing methods. For multiple marker interactions, our proposed method is also very powerful. Selective genotyping is an economical strategy in detecting and mapping quantitative trait loci in the genetic dissection of complex disease. When the samples arise from different ethnic groups or an admixture population, all the existing selective genotyping methods may result in spurious association due to different ancestry distributions. The problem can be more serious when the sample size is large, a general requirement to obtain sufficient power to detect modest genetic effects for most complex traits. In part II, I describe a useful strategy in selective genotyping while population stratification is present. Our procedure used a principal component based approach to eliminate any effect of population stratification. The paper evaluates the performance of our procedure using both simulated data from an early study data sets and also the HapMap data sets in a variety of population admixture models generated from empirical data. There are one binary trait and two continuous traits in the rheumatoid arthritis dataset of Problem 1 in the Genetic Analysis Workshop 16 (GAW16): RA status, AntiCCP and IgM. To allow multiple traits, we suggest a set of SNP-level F statistics by the concept of multiple-correlation to measure the genetic association between multiple trait values and SNP-specific genotypic scores and obtain their null distributions. Hereby, we perform 6 genome-wide association analyses using the novel one- and two-stage approaches which are based on single, double and triple traits. Incorporating all these 6 analyses, we successfully validate the SNPs which have been identified to be responsible for rheumatoid arthritis in the literature and detect more disease susceptibility SNPs for follow-up studies in the future. Except for chromosome 13 and 18, each of the others is found to harbour susceptible genetic regions for rheumatoid arthritis or related diseases, i.e., lupus erythematosus. This topic is discussed in part III.

Concept, design and implementation of a cardiovascular gene-centric 50 k SNP array for large-scale genomic association studies.

A wealth of genetic associations for cardiovascular and metabolic phenotypes in humans has been accumulating over the last decade, in particular a large number of loci derived from recent genome wide association studies (GWAS). True complex disease-associated loci often exert modest effects, so their delineation currently requires integration of diverse phenotypic data from large studies to ensure robust meta-analyses. We have designed a gene-centric 50 K single nucleotide polymorphism (SNP) array to assess potentially relevant loci across a range of cardiovascular, metabolic and inflammatory syndromes. The array utilizes a "cosmopolitan" tagging approach to capture the genetic diversity across approximately 2,000 loci in populations represented in the HapMap and SeattleSNPs projects. The array content is informed by GWAS of vascular and inflammatory disease, expression quantitative trait loci implicated in atherosclerosis, pathway based approaches and comprehensive literature searching. The custom flexibility of the array platform facilitated interrogation of loci at differing stringencies, according to a gene prioritization strategy that allows saturation of high priority loci with a greater density of markers than the existing GWAS tools, particularly in African HapMap samples. We also demonstrate that the IBC array can be used to complement GWAS, increasing coverage in high priority CVD-related loci across all major HapMap populations. DNA from over 200,000 extensively phenotyped individuals will be genotyped with this array with a significant portion of the generated data being released into the academic domain facilitating in silico replication attempts, analyses of rare variants and cross-cohort meta-analyses in diverse populations. These datasets will also facilitate more robust secondary analyses, such as explorations with alternative genetic models, epistasis and gene-environment interactions.