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.

Analysis of key molecules of the innate immune system in mammary epithelial cells isolated from marker-assisted and conventionally selected cattle

Mastitis is the most prevalent infectious disease in dairy herds. Breeding programs considering mastitis susceptibility were adopted as approaches to improve udder health status. In recent decades, conventional selection criteria based on phenotypic characteristics such as somatic cell score in milk have been widely used to select animals. Recently, approaches to incorporate molecular information have become feasible because of the detection of quantitative trait loci (QTL) affecting mastitis resistance. The aims of the study were to explore molecular mechanisms underlying mastitis resistance and the genetic mechanisms underlying a QTL on Bos taurus chromosome 18 found to influence udder health. Primary cell cultures of mammary epithelial cells from heifers that were selected for high or low susceptibility to mastitis were established. Selection based on estimated pedigree breeding value or on the basis of marker-assisted selection using QTL information was implemented. The mRNA expression of 10 key molecules of the innate immune system was measured using quantitative real-time PCR after 1, 6, and 24 h of challenge with heat-inactivated mastitis pathogens (Escherichia coli and Staphylococcus aureus) and expression levels in the high and low susceptibility groups were compared according to selection criteria. In the marker-assisted selection groups, mRNA expression in cells isolated from less-susceptible animals was significantly elevated for toll-like receptor 2, tumor necrosis factor-alpha, IL-1beta, IL-6, IL-8, RANTES (regulated upon activation, normal t-cell expressed and secreted), complement factor C3, and lactoferrin. In the estimated pedigree breeding value groups, mRNA expression was significantly elevated only for V-rel reticuloendotheliosis viral oncogene homolog A, IL-1 beta, and RANTES. These observations provide first insights into genetically determined divergent reactions to pathogens in the bovine mammary gland and indicate that the application of QTL information could be a successful tool for the selection of animals resistant to mastitis.

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.

Dissection of floral pollination syndromes in petunia

Animal-mediated pollination is essential in the reproductive biology of many flowering plants and tends to be associated with pollination syndromes, sets of floral traits that are adapted to particular groups of pollinators. The complexity and functional convergence of various traits within pollination syndromes are outstanding examples of biological adaptation, raising questions about their mechanisms and origins. In the genus Petunia, complex pollination syndromes are found for nocturnal hawkmoths (P. axillaris) and diurnal bees (P. integrifolia), with characteristic differences in petal color, corolla shape, reproductive organ morphology, nectar quantity, nectar quality, and fragrance. We dissected the Petunia syndromes into their most important phenotypic and genetic components. They appear to include several distinct differences, such as cell-growth and cell-division patterns in the basal third of the petals, elongation of the ventral stamens, nectar secretion and nectar sugar metabolism, and enzymatic differentiation in the phenylpropanoid pathway. In backcross-inbred lines of species-derived chromosome segments in a transposon tagging strain of P. hybrida, one to five quantitative trait loci were identified for each syndrome component. Two loci for stamen elongation and nectar volume were confirmed in introgression lines and showed large allelic differences. The combined data provide a framework for a detailed understanding of floral syndromes from their developmental and molecular basis to their impact on animal behavior. With its molecular genetic tools, this Petunia system provides a novel venue for a pattern of adaptive radiation that is among the most characteristic of flowering plants.

A Non-Synonymous HMGA2 Variant Decreases Height in Shetland Ponies and Other Small Horses

The identification of quantitative trait loci (QTL) such as height and their underlying causative variants is still challenging and often requires large sample sizes. In humans hundreds of loci with small effects control the heritable portion of height variability. In domestic animals, typically only a few loci with comparatively large effects explain a major fraction of the heritability. We investigated height at withers in Shetland ponies and mapped a QTL to ECA 6 by genome-wide association (GWAS) using a small cohort of only 48 animals and the Illumina equine SNP70 BeadChip. Fine-mapping revealed a shared haplotype block of 793 kb in small Shetland ponies. The HMGA2 gene, known to be associated with height in horses and many other species, was located in the associated haplotype. After closing a gap in the equine reference genome we identified a non-synonymous variant in the first exon of HMGA2 in small Shetland ponies. The variant was predicted to affect the functionally important first AT-hook DNA binding domain of the HMGA2 protein (c.83G>A; p.G28E). We assessed the functional impact and found impaired DNA binding of a peptide with the mutant sequence in an electrophoretic mobility shift assay. This suggests that the HMGA2 variant also affects DNA binding in vivo and thus leads to reduced growth and a smaller stature in Shetland ponies. The identified HMGA2 variant also segregates in several other pony breeds but was not found in regular-sized horse breeds. We therefore conclude that we identified a quantitative trait nucleotide for height in horses.

Genome-wide association studies based on sequence-derived genotypes reveal new QTL associated with conformation and performance traits in the Franches-Montagnes horse breed

To identify novel quantitative trait loci (QTL) within horses, we performed genome-wide association studies (GWAS) based on sequence-level genotypes for conformation and performance traits in the Franches-Montagnes (FM) horse breed. Sequence-level genotypes of FM horses were derived by re-sequencing 30 key founders and imputing 50K data of genotyped horses. In total, we included 1077 FM horses genotyped for ~4 million SNPs and their respective de-regressed breeding values of the traits in the analysis. Based on this dataset, we identified a total of 14 QTL associated with 18 conformation traits and one performance trait. Therefore, our results suggest that the application of sequence-derived genotypes increases the power to identify novel QTL which were not identified previously based on 50K SNP chip data.

Genomics of Rapid Incipient Speciation in Sympatric Threespine Stickleback

Ecological speciation is the process by which reproductively isolated populations emerge as a consequence of divergent natural or ecologically-mediated sexual selection. Most genomic studies of ecological speciation have investigated allopatric populations, making it difficult to infer reproductive isolation. The few studies on sympatric ecotypes have focused on advanced stages of the speciation process after thousands of generations of divergence. As a consequence, we still do not know what genomic signatures of the early onset of ecological speciation look like. Here, we examined genomic differentiation among migratory lake and resident stream ecotypes of threespine stickleback reproducing in sympatry in one stream, and in parapatry in another stream. Importantly, these ecotypes started diverging less than 150 years ago. We obtained 34,756 SNPs with restriction-site associated DNA sequencing and identified genomic islands of differentiation using a Hidden Markov Model approach. Consistent with incipient ecological speciation, we found significant genomic differentiation between ecotypes both in sympatry and parapatry. Of 19 islands of differentiation resisting gene flow in sympatry, all were also differentiated in parapatry and were thus likely driven by divergent selection among habitats. These islands clustered in quantitative trait loci controlling divergent traits among the ecotypes, many of them concentrated in one region with low to intermediate recombination. Our findings suggest that adaptive genomic differentiation at many genetic loci can arise and persist in sympatry at the very early stage of ecotype divergence, and that the genomic architecture of adaptation may facilitate this.

The genetic contribution of the major histocompatibility complex to bleomycin-induced lung injury

Pulmonary fibrosis (PF) is the result of a variety of environmental and cancer treatment related insults and is characterized by excessive deposition of collagen. Gas exchange in the alveoli is impaired as the normal lung becomes dense and collapsed leading to a loss of lung volume. It is now accepted that lung injury and fibrosis are in part genetically regulated. ^ Bleomycin is a chemotherapeutic agent used for testicular cancer and lymphomas that induces significant pulmonary toxicity. We delivered bleomycin to mice subcutaneously via a miniosmotic pump in order to elicit lung injury (LI) and quantified the %LI morphometrically using video imaging software. We previously identified a quantitative trait loci, Blmpf-1(LOD=17.4), in the Major Histocompatibility Complex (MHC), but the exact genetic components involved have remained unknown. ^ In the current studies, Blmpf-1 was narrowed to an interval spanning 31.9-32.9Mb on Chromosome 17 using MHC Congenic mice. This region includes the MHC Class II and III genes, and is flanked by the TNF-alpha super locus and MHC Class I genes. Knockout mice of MHC Class I genes (B2mko), MHC Class II genes (Cl2ko), and TNF-alpha (TNF-/-) and its receptors (p55-/-, p75-/-, and p55/p75-/-) were treated with bleomycin in order to ascertain the role of these genes in the pathogenesis of lung injury. ^ Cl2ko mice had significantly better survival and %LI when compared to treated background BL/6 (B6, P<.05). In contrast, B2mko showed no differences in survival or %LI compared to B6. This suggests that the MHC Class II locus contains susceptibility genes for bleomycin-induced lung injury. ^ TNF-alpha, a Class III gene, was examined and it was found that TNF-/- and p55-/- mice had higher %LI and lower survival when compared to B6 (P<.05). In contrast, p75-/- mice had significantly reduced %LI when compared to TNF-/-, p55-/-, and B6 mice as well as higher survival (P<.01). These data contradict the current paradigm that TNF-alpha is a profibrotic mediator of lung injury and suggest a novel and distinct role for the p55 and p75 receptors in mediating lung injury. ^

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

Single nucleotide polymorphisms (SNPs) associated with TGF-beta pathway and their significance in systemic sclerosis - A multilevel analysis

Systemic sclerosis (SSc) or Scleroderma is a complex disease and its etiopathogenesis remains unelucidated. Fibrosis in multiple organs is a key feature of SSc and studies have shown that transforming growth factor-β (TGF-β) pathway has a crucial role in fibrotic responses. For a complex disease such as SSc, expression quantitative trait loci (eQTL) analysis is a powerful tool for identifying genetic variations that affect expression of genes involved in this disease. In this study, a multilevel model is described to perform a multivariate eQTL for identifying genetic variation (SNPs) specifically associated with the expression of three members of TGF-β pathway, CTGF, SPARC and COL3A1. The uniqueness of this model is that all three genes were included in one model, rather than one gene being examined at a time. A protein might contribute to multiple pathways and this approach allows the identification of important genetic variations linked to multiple genes belonging to the same pathway. In this study, 29 SNPs were identified and 16 of them located in known genes. Exploring the roles of these genes in TGF-β regulation will help elucidate the etiology of SSc, which will in turn help to better manage this complex disease. ^

Ligamiento genético entre variables asociadas a calidad del fruto de tomate y polipéptidos expresados en dos estados de madurez

Los perfiles de polipéptidos proveen información sobre la constitución genética de un individuo y su expresión, y son útiles como marcadores moleculares. El objetivo del trabajo fue detectar ligamiento entre los perfiles de polipéptidos del pericarpio en dos estados de madurez y caracteres cuantitativos y de calidad de los frutos, analizando 21 genotipos de tomate. Se obtuvieron los perfiles polipéptidos en los estados verde y rojo maduro de frutos de 18 líneas endocriadas recombinantes (RILs, recombinant inbred lines), derivadas de un cruzamiento interespecífico entre el cultivar Caimanta de S. lycopersicum y la entrada LA722 de S. pimpinellifolium, que se incluyeron como testigos experimentales junto a su F1. En estos 21 genotipos se evaluaron también vida poscosecha, peso, firmeza, porcentaje de reflectancia, índice cromático, forma, pH, acidez titulable, contenido de sólidos solubles, espesor de pericarpio y número de lóculos de los frutos. Los perfiles mostraron polimorfismo entre los estados de madurez dentro de un mismo genotipo y entre genotipos para un mismo estado de madurez. Algunos polipéptidos segregaron de forma mendeliana (1:1) y, por análisis de un único punto, mostraron ligamiento con caracteres de calidad del fruto. Se detectaron loci de caracteres cuantitativos (QTLs, quantitative trait loci) asociados a número de lóculos, peso, pH, firmeza y vida poscosecha de los frutos.

Heat stress effects on crop performance and tools for tolerance breeding

Abiotic stress is one of the most common causes of crop deficit and loss and hence an important area of study. Moreover, concerns regarding global climate change over past decades mean the study of different abiotic stresses appears to be essential if its effects are to be mitigated. The current review covers the effects of heat stress on crop performance, the response crops make when subjected to this stress and the development of tools designed to breed for stress tolerant crops. Distinct levels of the problem are considered, from the morphological/anatomical, through the physiological and to the biochemical/molecular. The study of heat shock proteins (HSPs), quantitative trait loci (QTLs) identification and the relationship between metabolomics (OMICS) and heat stress are given special consideration.

Mapping and Introgression of QTL Involved in Fruit Shape Transgressive Segregation into 'Piel de Sapo' Melon (Cucumis melo L.)

A mapping F2 population from the cross ‘Piel de Sapo’ × PI124112 was selectively genotyped to study the genetic control of morphological fruit traits by QTL (Quantitative Trait Loci) analysis. Ten QTL were identified, five for FL (Fruit Length), two for FD (Fruit Diameter) and three for FS (Fruit Shape). At least one robust QTL per character was found, flqs8.1 (LOD = 16.85, R2 = 34%), fdqs12.1 (LOD = 3.47, R2 = 11%) and fsqs8.1 (LOD = 14.85, R2 = 41%). flqs2.1 and fsqs2.1 cosegregate with gene a (andromonoecious), responsible for flower sex determination and with pleiotropic effects on FS. They display a positive additive effect (a) value, so the PI124112 allele causes an increase in FL and FS, producing more elongated fruits. Conversely, the negative a value for flqs8.1 and fsqs8.1 indicates a decrease in FL and FS, what results in rounder fruits, even if PI124112 produces very elongated melons. This is explained by a significant epistatic interaction between fsqs2.1 and fsqs8.1, where the effects of the alleles at locus a are attenuated by the additive PI124112 allele at fsqs8.1. Roundest fruits are produced by homozygous for PI124112 at fsqs8.1 that do not carry any dominant A allele at locus a (PiPiaa). A significant interaction between fsqs8.1 and fsqs12.1 was also detected, with the alleles at fsqs12.1 producing more elongated fruits. fsqs8.1 seems to be allelic to QTL discovered in other populations where the exotic alleles produce elongated fruits. This model has been validated in assays with backcross lines along 3 years and ultimately obtaining a fsqs8.1-NIL (Near Isogenic Line) in ‘Piel de Sapo’ background which yields round melons.

Polyploid formation created unique avenues for response to selection in Gossypium (cotton)

A detailed restriction fragment length polymorphism map was used to determine the chromosomal locations and subgenomic distributions of quantitative trait loci (QTLs) segregating in a cross between cultivars of allotetraploid (AADD) Gossypium hirsutum (“Upland” cotton) and Gossypium barbadense (“Sea Island,” “Pima,” or “Egyptian” cotton) that differ markedly in the quality and quantity of seed epidermal fibers. Most QTLs influencing fiber quality and yield are located on the “D” subgenome, derived from an ancestor that does not produce spinnable fibers. D subgenome QTLs may partly account for the fact that domestication and breeding of tetraploid cottons has resulted in fiber yield and quality levels superior to those achieved by parallel improvement of “A” genome diploid cottons. The merger of two genomes with different evolutionary histories in a common nucleus appears to offer unique avenues for phenotypic response to selection. This may partly compensate for reduction in quantitative variation associated with polyploid formation and be one basis for the prominence of polyploids among extant angiosperms. These findings impel molecular dissection of the roles of divergent subgenomes in quantitative inheritance in many other polyploids and further exploration of both “synthetic” polyploids and exotic diploid genotypes for agriculturally useful variation.