Performed Genome Wide Association Research Articles

Genome wide association studies on seven yield-related traits of 183 rice varieties in Bangladesh.

Rice genetic diversity is regulated by multiple genes and is largely dependent on various environmental factors. Uncovering the genetic variations associated with the diversity in rice populations is the key to breed stable and high yielding rice varieties. We performed genome wide association studies (GWASs) on seven rice yielding traits (grain length, grain width, grain weight, panicle length, leaf length, leaf width, and leaf angle) based on a population of 183 rice landraces of Bangladesh. Our GWASs reveal various chromosomal regions and candidate genes that are associated with different traits in Bangladeshi rice varieties. Noteworthy was the recurrent implication of chromosome 10 in all three grain-shape-related traits (grain length, grain width, and grain weight), indicating its pivotal role in shaping rice grain morphology. Our study also underscores the involvement of transposon gene families across these three traits. For leaf related traits, chromosome 10 was found to harbor regions that are significantly associated with leaf length and leaf width. The results of these association studies support previous findings as well as provide additional insights into the genetic diversity of rice. This is the first known GWAS study on various yield-related traits in the varieties of Oryza sativa available in Bangladesh-the fourth largest rice-producing country. We believe this study will accelerate rice genetics research and breeding stable high-yielding rice in Bangladesh.

A genome‐wide association study in Puerto Ricans suggests new risk loci for Alzheimer disease

AbstractBackgroundAlzheimer disease (AD) is the fourth leading cause of death in Puerto Rico. The Puerto Rican (PR) population has a high proportion of older adults (18%, over > 65), with 12.5% of them suffering from ADThese statistics highlight the need to investigate the genetic risk factors underlying AD in the PR population, as it could lead to the development of targeted treatments and therapies. Moreover, the ancestrally admixed makeup of the PR population provides an opportunity to assess the role of the European (∼67%), African (∼20%) and Amerindian (∼13%) ancestry in AD risk. We performed genome wide association analysis (GWAS) using whole genome sequence data to identify genetic risk/protective factors associated with AD in the PR population.MethodThe PR dataset includes WGS and phenotype data from 640 individuals, comprising 335 AD and 305 cognitively unimpaired (CU) controls. To account for the population substructure, we calculated the global ancestry (principal components) using EIGENSTRAT. We performed GWAS analyses with a generalized linear mixed‐model using the SAIGE software. The model included genotype, sex, age, and principal components (population substructure) as fixed effects and genetic relationship matrix as a random effect. The genetic relationship matrix was calculated based on genomic data and accounted for the relatedness among the individuals in the dataset.ResultWe identified four suggestive significant loci (P<1×10−6) associated with the risk of AD in PRs: NACC2 (pv = 4.8×10−7) on chromosome 9, SCN8A (pv = 9.3×10−7) on chromosome 12, FOXK2 (pv = 9.9×10−7) on chromosome 17, and APOEe4 (pv = 6.8×10−8) on chromosome 19. Eight additional AD loci with the same lead marker from European GWAS study (Bellenquez et al.) showed nominal significance: FERMT2 (pv = 6.2×10−3), TREM2 (pv = 8.0×10−3), CLU (pv = 1.8×10−2), RASGEF1C (pv = 2.4×10−2), ADAM17 (pv = 3.5×10−2), DOC2A (pv = 4.3×10−2), GRN (pv = 4.4×10−2) and SORL1 (pv = 5.1×10−2).ConclusionThis study identified three suggestive novel significant loci (NACC2, SCN8A, and FOXK2) associated with AD risk in PRs. In addition, GWAS study on PRs with a high proportion of European ancestry was able to replicate nine AD loci previously identified in European studies. These findings provide new insights into the genetic architecture of AD in the PR population.

Identification of the genetic basis of the duck growth rate in multiple growth stages using genome-wide association analysis

BackgroundThe genetic locus responsible for duck body size has been fully explained before, but the growth trait-related genetic basis is still waiting to be explored. For example, the genetic site related to growth rate, an important economic trait affecting marketing weight and feeding cost, is still unclear. Here, we performed genome wide association study (GWAS) to identify growth rate-associated genes and mutations.ResultIn the current study, the body weight data of 358 ducks were recorded every 10 days from hatching to 120 days of age. According to the growth curve, we evaluated the relative and absolute growth rates (RGR and AGR) of 5 stages during the early rapid growth period. GWAS results for RGRs identified 31 significant SNPs on autosomes, and these SNPs were annotated by 24 protein-coding genes. Fourteen autosomal SNPs were significantly associated with AGRs. In addition, 4 shared significant SNPs were identified as having an association with both AGR and RGR, which were Chr2: 11483045 C>T, Chr2: 13750217 G>A, Chr2: 42508231 G>A and Chr2: 43644612 C>T. Among them, Chr2: 11483045 C>T, Chr2: 42508231 G>A, and Chr2: 43644612 C>T were annotated by ASAP1, LYN and CABYR, respectively. ASAP1 and LYN have already been proven to play roles in the growth and development of other species. In addition, we genotyped every duck using the most significant SNP (Chr2: 42508231 G>A) and compared the growth rate difference among each genotype population. The results showed that the growth rates of individuals carrying the Chr2: 42508231 A allele were significantly lower than those without this allele. Moreover, the results of the Mendelian randomization (MR) analysis supported the idea that the growth rate and birth weight had a causal effect on the adult body weight, with the growth rate having a greater effect size.ConclusionIn this study, 41 SNPs significantly related to growth rate were identified. In addition, we considered that the ASAP1 and LYN genes are essential candidate genes affecting the duck growth rate. The growth rate also showed the potential to be used as a reliable predictor of adult weight, providing a theoretical reference for preselection.

Novel SNP Markers and Their Application in Low-Cyanide Cassava (Manihot esculenta crantz) Breeding Program

The major flaw of cassava is its indigenous cyanide. Traditional breeding program for diminishing cyanide in cassava take a long waiting time for harvesting cassava tubers to assess cyanide content. Genetic markers are useful for selection of good agricultural traits, which also applied in low-cyanide cassava breeding programs by detecting gene associate with cyanide content in cassava. Therefore, the objective of this study was to develop SNP markers to detect low cyanide trait in cassava. Genotype analysis was carried out using Genotyping by Sequencing (GBS) technology assembling with phenotype analysis. Then, the SNP markers associated with cyanide content were found. Afterward, the primers of SNP marker associated with cyanide content 2 positions were developed using tetra-primer ARMS-PCR techniques. S16_640082 and S16_735381 SNP markers on chromosome 16 showed potential ability of the selection of cassava varieties with cyanide content less than 250 mg HCN/kg fresh weight. The selection accuracy of S16_640082 and S16_735381 SNP markers was 73.33 and 76.64 %, respectively. These markers could be used in marker assisted selection (MAS) in cassava seedling. It substantially reduces cassava breeding programs cost and time. HIGHLIGHTS The major flaw of cassava is its indigenous cyanide. Up to our knowledge, there is rarely report on SNP marker related to cyanide content in Thai cassava population By performing genome wide association mapping (GWAS) to characterize the genome position related to HCN, 2 novel SNP markers associated with cyanide content were found The primers to detect the SNP markers were developed using tetra-primer ARMS-PCR techniques The markers showed ability of the selection of cassava varieties with cyanide content less than 250 mg HCN/kg fresh weight GRAPHICAL ABSTRACT

Genetic Insights from the ADSP into Drug Discovery In Alzheimer’s Disease

AbstractBackgroundA major goal of the NAPA plan initiated in 2013 is the development of novel drugs for the treatment and prevention of Alzheimer’s disease (AD). It is widely recognized that drug targets with genetic support are more likely to successfully make it through the drug development pipeline than those without genetic support. The target may be a genetic risk factor for AD or within a genetically regulated network implicated by an AD genetic risk factor. Thus, one of the primary goals of the Alzheimer’s disease sequencing project (ADSP) is to identify and validate putative novel drug targets and to work with the community to advance testing of these candidates.MethodsSince 2013 the ADSP has performed genome wide association studies of both common and rare variants to identify novel AD risk genes in diverse human populations.ResultsGenomic analyses have demonstrated that these AD risk alleles are enriched with regulatory regions, in microglial enhancers and the PU.1 regulatory network. The ADSP has also made a major effort in including different ancestries into AD research and utilized the differences in AD risk between ancestries for major genetic risk factors (like ApoE) to identified potential therapeutic targets. A key challenge for common variants associated with AD is to link them to specific genes, and to understand the subsequent biological processes that lead to AD. This is a major focus of the Functional Genetics Consortium within the ADSP. Rare coding variants have directly implicated specific genes, which also provide support for the central role of microglial function in AD risk, e.g. Trem2, ABI3, PLCg2. The genetics of endophenotypes (e.g. sTrem2) and of protein quantitative trait loci offer alternative approaches to link genetics to biology.ConclusionsTogether, common and rare variants identify myeloid cell efferocytosis as a key disease risk hub. An alternative approach to drug discovery is the use of in silico approaches to match disease relevant signatures to existing drugs to enable drug repurposing. To date this approach has focused on transcriptomic signatures and implicates several biological pathways including the integrated stress response.

Vulnerability for alcohol use disorder after adverse childhood experiences (AUDACE): protocol for a longitudinal fMRI study assessing neuropsychobiological risk factors for relapse

BackgroundAdverse childhood experiences (ACE) are common and may predispose affected individuals to various health problems, including alcohol use disorder (AUD). Although a relationship between ACE and AUD has been well-established,...

Linkage and association analysis define novel regions for the risk of adenomas and colorectal cancer

Colorectal cancer (CRC) is a multifactorial disease, where both the environment and genetics play a role. It is estimated that approximately 35% of CRCs have a potentially identifiable genetic cause. Well-known and highly penetrant genetic causes make up less than 5% of all CRC, and leave many families not explained by known predisposing genes/mutations. Low penetrant alleles have also been thought to modify the risk of CRC. Linkage studies have been successful in discovering and localizing highly penetrant genes in CRC and risk loci has become possible to discover performing genome wide association studies (GWAS). In this study we have analyzed families with CRC where individuals with CRC as well as individuals with premalignant lesions, adenomas, were codes as affected. In total 600 individuals in 121 families were included in the study. In total three genomic regions were found with suggestive linkage located at 4p16.3, 6p24.3 and 10p14. These regions were further studied using sequencing analysis and association studies using haplotypes.

The genetic basis of adaptation in phenology in an introduced population of Black Cottonwood (Populus trichocarpa, Torr. & Gray)

BackgroundEntering and exiting winter dormancy present important trade-offs between growth and survival at northern latitudes. Many forest trees display local adaptation across latitude in traits associated with these phenology transitions. Transfers of a species outside its native range introduce the species to novel combinations of environmental conditions potentially requiring different combinations of alleles to optimize growth and survival. In this study, we performed genome wide association analyses and a selection scan in a P. trichocarpa mapping population derived from crossings between clones collected across the native range and introduced into Sweden. GWAS analyses were performed using phenotypic data collected across two field seasons and in a controlled phytotron experiment.ResultsWe uncovered 584 putative candidate genes associated with spring and autumn phenology traits as well as with growth. Many regions harboring variation significantly associated with the initiation of leaf shed and leaf autumn coloring appeared to have been evolving under positive selection in the native environments of P. trichocarpa. A comparison between the candidate genes identified with results from earlier GWAS analyses performed in the native environment found a smaller overlap for spring phenology traits than for autumn phenology traits, aligning well with earlier observations that spring phenology transitions have a more complex genetic basis than autumn phenology transitions.ConclusionsIn a small and structured introduced population of P. trichocarpa, we find complex genetic architectures underlying all phenology and growth traits, and identify multiple putative candidate genes despite the limitations of the study population.

Characterization of the Genetic Architecture for Fusarium Head Blight Resistance in Durum Wheat: The Complex Association of Resistance, Flowering Time, and Height Genes.

Durum wheat is an economically important crop for Canadian farmers. Fusarium head blight (FHB) is one of the most destructive diseases that threatens durum production in Canada. FHB reduces yield and end-use quality and most commonly contaminates the grain with the fungal mycotoxin deoxynivalenol, also known as DON. Serious outbreaks of FHB can occur in durum wheat in Canada, and combining genetic resistance with fungicide application is a cost effective approach to control this disease. However, there is limited variation for genetic resistance to FHB in elite Canadian durum cultivars. To explore and identify useful genetic FHB resistance variation for the improvement of Canadian durum wheat, we assembled an association mapping (AM) panel of diverse durum germplasms and performed genome wide association analysis (GWAS). Thirty-one quantitative trait loci (QTL) across all 14 chromosomes were significantly associated with FHB resistance. On 3BS, a stable QTL with a larger effect for resistance was located close to the centromere of 3BS. Three haplotypes of Fhb1 QTL were identified, with an emmer wheat haplotype contributing to disease susceptibility. The large number of QTL identified here can provide a rich resource to improve FHB resistance in commercially grown durum wheat. Among the 31 QTL most were associated with plant height and/or flower time. QTL 1A.1, 1A.2, 3B.2, 5A.1, 6A.1, 7A.3 were associated with FHB resistance and not associated or only weakly associated with flowering time nor plant height. These QTL have features that would make them good targets for FHB resistance breeding.

Comparison of GWA statistical methods for traits under different genetic structures: A simulation study

Several methods have been used to perform genome wide association (GWA) studies, aiming to map quantitative trait loci (QTL) and candidate variants. The single-step genomic best linear unbiased prediction (ssGBLUP) method is one alternative to perform GWA, which allows the simultaneous use of genotypic, pedigree and phenotypic information. Bayesian multiple regression models have also been used to perform GWA, allowing specifying different priori distribution for the molecular marker effects. The aim of the present study was to evaluate, through simulation, the performance of different methods in the identification of QTLs for polygenic and major gene traits, under different heritabilities when only relatively few animals were genotyped. We also investigated the consequence of considering the agreement among results from different methods as a strategy to decrease errors associated with false positives in QTL mapping. For polygenic scenarios, results showed low power to detect QTL, irrespective of the method, and the use of phenotypes from non-genotyped animals slightly helped QTL detection of ssGBLUP and weighted ssGBLUP (wssGBLUP). For scenarios with major gene effects, there was greater power in QTL detection, with a slight superiority of Bayes C over the other methods. The inclusion of additional phenotypic information (from non-genotyped animals) harmed the performance of wssGBLUP in the presence of major QTL. When only consensus regions identified by different methods were considered as evidence of QTL, the percentage of top windows containing a true QTL tended to increase with the number of methods that identified a top window, for all scenarios. However, an important proportion of true QTL were identified only by a single or few methods. Despite the small differences among methods in the QTL detection, for polygenic traits, the ssGBLUP and wssGBLUP methods seemed to show better results in comparison to the other methods mainly in the low heritability scenario. For traits with major gene effects, the Bayes C method is expected to present better results, compared to the other methods evaluated, given a limited number of genotyped animals. The strategy to use agreement of GWA results among methods to map QTL helps to reduce false positives but comes at a cost of missing important QTL, irrespective of the genetic structure of the trait.

Genome wide association and gene enrichment analysis reveal membrane anchoring and structural proteins associated with meat quality in beef

BackgroundMeat quality related phenotypes are difficult and expensive to measure and predict but are ideal candidates for genomic selection if genetic markers that account for a worthwhile proportion of the phenotypic variation can be identified. The objectives of this study were: 1) to perform genome wide association analyses for Warner-Bratzler Shear Force (WBSF), marbling, cooking loss, tenderness, juiciness, connective tissue and flavor; 2) to determine enriched pathways present in each genome wide association analysis; and 3) to identify potential candidate genes with multiple quantitative trait loci (QTL) associated with meat quality.ResultsThe WBSF, marbling and cooking loss traits were measured in longissimus dorsi muscle from 672 steers. Out of these, 495 animals were used to measure tenderness, juiciness, connective tissue and flavor by a sensory panel. All animals were genotyped for 221,077 markers and included in a genome wide association analysis. A total number of 68 genomic regions covering 52 genes were identified using the whole genome association approach; 48% of these genes encode transmembrane proteins or membrane associated molecules. Two enrichment analysis were performed: a tissue restricted gene enrichment applying a correlation analysis between raw associated single nucleotide polymorphisms (SNPs) by trait, and a functional classification analysis performed using the DAVID Bioinformatic Resources 6.8 server. The tissue restricted gene enrichment approach identified eleven pathways including “Endoplasmic reticulum membrane” that influenced multiple traits simultaneously. The DAVID functional classification analysis uncovered eleven clusters related to transmembrane or structural proteins. A gene network was constructed where the number of raw associated uncorrelated SNPs for each gene across all traits was used as a weight. A multiple SNP association analysis was performed for the top five most connected genes in the gene-trait network. The gene network identified the EVC2, ANXA10 and PKHD1 genes as potentially harboring multiple QTLs. Polymorphisms identified in structural proteins can modulate two different processes with direct effect on meat quality: in vivo myocyte cytoskeletal organization and postmortem proteolysis.ConclusionThe main result from the present analysis is the uncovering of several candidate genes associated with meat quality that have structural function in the skeletal muscle.

Genomic Predictions and Genome-Wide Association Study of Resistance Against Piscirickettsia salmonis in Coho Salmon (Oncorhynchus kisutch) Using ddRAD Sequencing.

Piscirickettsia salmonis is one of the main infectious diseases affecting coho salmon (Oncorhynchus kisutch) farming, and current treatments have been ineffective for the control of this disease. Genetic improvement for P. salmonis resistance has been proposed as a feasible alternative for the control of this infectious disease in farmed fish. Genotyping by sequencing (GBS) strategies allow genotyping of hundreds of individuals with thousands of single nucleotide polymorphisms (SNPs), which can be used to perform genome wide association studies (GWAS) and predict genetic values using genome-wide information. We used double-digest restriction-site associated DNA (ddRAD) sequencing to dissect the genetic architecture of resistance against P. salmonis in a farmed coho salmon population and to identify molecular markers associated with the trait. We also evaluated genomic selection (GS) models in order to determine the potential to accelerate the genetic improvement of this trait by means of using genome-wide molecular information. A total of 764 individuals from 33 full-sib families (17 highly resistant and 16 highly susceptible) were experimentally challenged against P. salmonis and their genotypes were assayed using ddRAD sequencing. A total of 9,389 SNPs markers were identified in the population. These markers were used to test genomic selection models and compare different GWAS methodologies for resistance measured as day of death (DD) and binary survival (BIN). Genomic selection models showed higher accuracies than the traditional pedigree-based best linear unbiased prediction (PBLUP) method, for both DD and BIN. The models showed an improvement of up to 95% and 155% respectively over PBLUP. One SNP related with B-cell development was identified as a potential functional candidate associated with resistance to P. salmonis defined as DD.

Genetic Diversity and Population Structure of F3:6 Nebraska Winter Wheat Genotypes Using Genotyping-By-Sequencing.

The availability of information on the genetic diversity and population structure in wheat (Triticum aestivum L.) breeding lines will help wheat breeders to better use their genetic resources and manage genetic variation in their breeding program. The recent advances in sequencing technology provide the opportunity to identify tens or hundreds of thousands of single nucleotide polymorphism (SNPs) in large genome species (e.g., wheat). These SNPs can be utilized for understanding genetic diversity and performing genome wide association studies (GWAS) for complex traits. In this study, the genetic diversity and population structure were investigated in a set of 230 genotypes (F3:6) derived from various crosses as a prerequisite for GWAS and genomic selection. Genotyping-by-sequencing provided 25,566 high-quality SNPs. The polymorphism information content (PIC) across chromosomes ranged from 0.09 to 0.37 with an average of 0.23. The distribution of SNPs markers on the 21 chromosomes ranged from 319 on chromosome 3D to 2,370 on chromosome 3B. The analysis of population structure revealed three subpopulations (G1, G2, and G3). Analysis of molecular variance identified 8% variance among and 92% within subpopulations. Of the three subpopulations, G2 had the highest level of genetic diversity based on three genetic diversity indices: Shannon’s information index (I) = 0.494, diversity index (h) = 0.328 and unbiased diversity index (uh) = 0.331, while G3 had lowest level of genetic diversity (I = 0.348, h = 0.226 and uh = 0.236). This high genetic diversity identified among the subpopulations can be used to develop new wheat cultivars.

Use of genotyping-by-sequencing to determine the genetic structure in the medicinal plant chamomile, and to identify flowering time and alpha-bisabolol associated SNP-loci by genome-wide association mapping

BackgroundChamomile (Matricaria recutita L.) has a long history of use in herbal medicine with various applications, and the flower heads contain numerous secondary metabolites which are medicinally active.In the major crop plants, next generation sequencing (NGS) approaches are intensely applied to exploit genetic resources, to develop genomic resources and to enhance breeding. Here, genotyping-by-sequencing (GBS) has been used in the non-model medicinal plant chamomile to evaluate the genetic structure of the cultivated varieties/populations, and to perform genome wide association study (GWAS) focusing on genes with large effect on flowering time and the medicinally important alpha-bisabolol content.ResultsGBS analysis allowed the identification of 6495 high-quality SNP-markers in our panel of 91 M. recutita plants from 33 origins (2–4 genotypes each) and 4 M. discoidea plants as outgroup, grown in the greenhouse in Gatersleben, Germany. M. recutita proved to be clearly distinct from the outgroup, as was demonstrated by different cluster and principal coordinate analyses using the SNP-markers. Chamomile genotypes from the same origin were mostly genetically similar. Model-based cluster analysis revealed one large group of tetraploid genotypes with low genetic differentiation including 39 plants from 14 origins. Tetraploids tended to display lower genetic diversity than diploids, probably reflecting their origin by artificial polyploidisation from only a limited set of genetic backgrounds.Analyses of flowering time demonstrated that diploids generally flowered earlier than tetraploids, and the analysis of alpha-bisabolol identified several tetraploid genotypes with a high content. GWAS identified highly significant (P < 0.01) SNPs for flowering time (9) and alpha-bisabolol (71). One sequence harbouring SNPs associated with flowering time was described to play a role in self-pollination in Arabidopsis thaliana, whereas four sequences harbouring SNPs associated with alpha-bisabolol were identified to be involved in plant biotic and abiotic stress response in various plants species.ConclusionsThe first genomic resource for future applications to enhance breeding in chamomile was created, andanalyses of diversity will facilitate the exploitation of these genetic resources. The GWAS data pave the way for future research towards the genetics underlying important traits in chamomile, the identification of marker-trait associations, and development of reliable markers for practical breeding.

Haplotypes on pig chromosome 3 distinguish metabolically healthy from unhealthy obese individuals.

We have established a pig resource population specifically designed to elucidate the genetics involved in development of obesity and obesity related co-morbidities by crossing the obesity prone Göttingen Minipig breed with two lean production pig breeds. In this study we have performed genome wide association (GWA) to identify loci with effect on blood lipid levels. The most significantly associated single nucleotide polymorphisms (SNPs) were used for linkage disequilibrium (LD) and haplotype analyses. Three separate haploblocks which influence the ratio between high density lipoprotein cholesterol and total cholesterol (HDL-C/CT), triglycerides (TG) and low density lipoprotein cholesterol (LDL-C) levels respectively were identified on Sus Scrofa chromosome 3 (SSC3). Large additive genetic effects were found for the HDL-C/CT and LDL-C haplotypes. Haplotypes segregating from Göttingen Minipigs were shown to impose a positive effect on blood lipid levels. Thus, the genetic profile of the Göttingen Minipig breed seems to support a phenotype comparable to the metabolic healthy obese (MHO) phenotype in humans.

Genome-wide population structure and evolutionary history of the Frizarta dairy sheep

In the present study, we used genomic data, generated with a medium density single nucleotide polymorphisms (SNP) array, to acquire more information on the population structure and evolutionary history of the synthetic Frizarta dairy sheep. First, two typical measures of linkage disequilibrium (LD) were estimated at various physical distances that were then used to make inferences on the effective population size at key past time points. Population structure was also assessed by both multidimensional scaling analysis and k-means clustering on the distance matrix obtained from the animals’ genomic relationships. The Wright’s fixation FST index was also employed to assess herds’ genetic homogeneity and to indirectly estimate past migration rates. The Wright’s fixation FIS index and genomic inbreeding coefficients based on the genomic relationship matrix as well as on runs of homozygosity were also estimated. The Frizarta breed displays relatively low LD levels with r2 and |Dʹ| equal to 0.18 and 0.50, respectively, at an average inter-marker distance of 31 kb. Linkage disequilibrium decayed rapidly by distance and persisted over just a few thousand base pairs. Rate of LD decay (β) varied widely among the 26 autosomes with larger values estimated for shorter chromosomes (e.g. β=0.057, for OAR6) and smaller values for longer ones (e.g. β=0.022, for OAR2). The inferred effective population size at the beginning of the breed’s formation was as high as 549, was then reduced to 463 in 1981 (end of the breed’s formation) and further declined to 187, one generation ago. Multidimensional scaling analysis and k-means clustering suggested a genetically homogenous population, FST estimates indicated relatively low genetic differentiation between herds, whereas a heat map of the animals’ genomic kinship relationships revealed a stratified population, at a herd level. Estimates of genomic inbreeding coefficients suggested that most recent parental relatedness may have been a major determinant of the current effective population size. A denser than the 50k SNP panel may be more beneficial when performing genome wide association studies in the breed.

Variation in Arabidopsis flooding responses identifies numerous putative “tolerance genes”

ABSTRACTPlant survival in flooded environments requires a combinatory response to multiple stress conditions such as limited light availability, reduced gas exchange and nutrient uptake. The ability to fine-tune the molecular response at the transcriptional and/or post-transcriptional level that can eventually lead to metabolic and anatomical adjustments are the underlying requirements to confer tolerance. Previously, we compared the transcriptomic adjustment of submergence tolerant, intolerant accessions and identified a core conserved and genotype-specific response to flooding stress, identifying numerous ‘putative’ tolerance genes. Here, we performed genome wide association analyses on 81 natural Arabidopsis accessions that identified 30 additional SNP markers associated with flooding tolerance. We argue that, given the many genes associated with flooding tolerance in Arabidopsis, improving resistance to submergence requires numerous genetic changes.

Ein genomweiter Ansatz bei Thrombozyten-und Gerinnungsstörungen

The sequencing of hundreds of thousands of human exomes and hundreds of thousands of whole genomes is providing a progressively accurate and complete catalogue of human genetic variation. The initial studies to use genome wide data to help understand platelet disorders performed genome wide association studies to identify loci linked to variations in blood cell parameters. These studies used normal variation to find corresponding genetic variation. We next wished to investigate the genetic basis of bleeding disorders which may also provide a key to novel genes regulating platelet and haemostatic functions. The BRIDGE consortium (www.bridgestudy.org) is funded by the NIHR and brings together 13 rare disease gene discovery projects. The aim of these projects is to investigate as yet undiagnosed rare inherited diseases and identify the underlying mutational basis. We have used a cluster analysis based on the Human Phenotype Ontology in combination with next generation sequencing techniques to help identify patients with similar phenotypes which we hypothesise will arise from defects in the same gene. Preliminary results validate the clustering approach and have also resulted in a number of novel genes important for normal and pathogenic platelet physiology.

The challenge of genetic selection for heat tolerance: the dairy cattle example

Exposure of livestock to high heat loads negatively affects animal’s productivity. Genetic selection for heat tolerance using quantitative approaches has been developed by making use of the milk recording information merged with the meteorological information in the test date. The main conclusions of the studies following this approach have been that there is genetic variability in the response to heat stress (HS), that a genotype by environment interaction between thermal comfort and HS conditions exists and that there is a genetic antagonism between HS tolerance and high milk production. This approach has the advantage of adding no extra costs to the existing milk recording schemes, but it has some disadvantages. Current milk recording information does not seem to fully capture the productive response to high heat loads. Moreover, the antagonism between heat tolerance and high milk production may offset the benefits of selection for this trait if heat-tolerant animals are less productive. The use of new tools from phenomics, genomics and transcriptomics can help in achieving an accurate selection of heat-tolerant animals without damaging progress in milk production. New phenotypes for this selection are measure of body temperature and respiration rates together with measures of indicators of heat tolerance in milk, through the use of mid IR spectroscopy. The use of commercial DNA chips to perform genome wide association studies or comparison of whole genome DNA sequence of animals of heat adapted and temperate climate breeds could also provide useful genomic information. Finally, RNA sequencing together with the recent discovery of the possibility to use the milk transcriptome instead of tissue biopsies could help to discover differentially expressed genes under HS and thermoneutrality. The existence of powerful tools to achieve better phenotypes to identify tolerantv. susceptible animals and to gain insights about the genetic mechanisms underlying HS response to be able to disentangle the genetic puzzle of heat tolerance may make possible the selection of heat-tolerant and still productive animals.

Polymorphisms in early neurodevelopmental genes affect natural variation in alcohol sensitivity in adult drosophila.

BackgroundAlcohol abuse and alcoholism are significant public health problems, but the genetic basis for individual variation in alcohol sensitivity remains poorly understood. Drosophila melanogaster presents a powerful model system for dissecting the genetic underpinnings that determine individual variation in alcohol-related phenotypes. We performed genome wide association analyses for alcohol sensitivity using the sequenced, inbred lines of the D. melanogaster Genetic Reference Panel (DGRP) together with extreme QTL mapping in an advanced intercross population derived from sensitive and resistant DGRP lines.ResultsThe DGRP harbors substantial genetic variation for alcohol sensitivity and tolerance. We identified 247 candidate genes affecting alcohol sensitivity in the DGRP or the DGRP-derived advanced intercross population, some of which met a Bonferroni-corrected significance threshold, while others occurred among the top candidate genes associated with variation in alcohol sensitivity in multiple analyses. Among these were candidate genes associated with development and function of the nervous system, including several genes in the Dopamine decarboxylase (Ddc) cluster involved in catecholamine synthesis. We found that 58 of these genes formed a genetic interaction network. We verified candidate genes using mutational analysis, targeted gene disruption through RNAi knock-down and transcriptional profiling. Two-thirds of the candidate genes have been implicated in previous Drosophila, mouse and human studies of alcohol-related phenotypes.ConclusionsIndividual variation in alcohol sensitivity in Drosophila is highly polygenic and in part determined by variation in evolutionarily conserved signaling pathways that are associated with catecholamine neurotransmitter biosynthesis and early development of the nervous system.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2064-5) contains supplementary material, which is available to authorized users.