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505 results for “genome-wide association”
Competitiveness prediction for nodule colonization in Sinorhizobium meliloti through combined in vitro tagged strain characterization and genome-wide association analysis
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Genome-wide association study in quinoa reveals selection pattern typical for crops with a short breeding history
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Genome-wide DDR protein Association Score (DAS) network
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Combining genome-wide studies of breast, prostate, ovarian and endometrial cancers maps cross-cancer susceptibility loci and identifies new genetic associations
<p>Data set linked to the paper, "Combining genome-wide studies of breast, prostate, ovarian and endometrial cancers maps cross-cancer susceptibility loci and identifies new genetic associations". Pre-print of the paper is here: <a href="https://doi.org/10.1101/2020.06.16.146803">https://doi.org/10.1101/2020.06.16.146803</a>.</p> <p> </p> <p>cross_cancer_sum_stats.txt.gz contains summary genome-wide association statistics for susceptibility to single cancers (breast (BR), prostate (PR), ovarian (OV), endometrial (EN), estrogen receptor (ER)-positive breast (POS), ER-negative breast (NEG), and high-grade serous ovarian (HGS) cancers) and from the cross-cancer meta-analysis (main [main] and subtype-focused [sub]). EA in the header refers to the effect allele, OA is the other allele, EAF is the effect allele frequency in the largest of the single cancer data sets (BR), IMPR2 is the imputation quality in the largest of the single cancer data sets (BR), SE is the standard error, PVAL is the P-value, RE2Cs1 is the RE2C statistic mean effect part, RE2Cs2 is the RE2C statistic heterogeneity part, RE2Cp* is the RE2C* P-value. More on RE2Cp* can be found here: <a href="http://software.buhmhan.com/RE2C/index.php?mid=contact&act=dispBoardWrite">http://software.buhmhan.com/RE2C/index.php?mid=contact&act=dispBoardWrite</a> and in <a href="https://academic.oup.com/bioinformatics/article/33/14/i379/3953957">https://academic.oup.com/bioinformatics/article/33/14/i379/3953957</a> SNP names in cross_cancer_sum_stats.txt.gz include the chromosome and build 37 position.</p> <p> </p> <p>main_tetrachoric_corr_matrix.txt and subtype_tetrachoric_corr_matrix.txt provide the tetrachoric correlation matrices used in the main and subtype-focused meta-analyses. These were also used to specify the cryptic.cor argument of the exh.abf function of MetABF. More on MetABF can be found here: <a href="https://github.com/trochet/metabf">https://github.com/trochet/metabf</a> and in <a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/gepi.22202">https://onlinelibrary.wiley.com/doi/abs/10.1002/gepi.22202</a></p> <p> </p> <p>prior_sigmas_for_metabf.txt contains the values used to specify the prior.sigma argument of the exh.abf function in MetABF.</p> <p> </p> <p>The breast cancer data used are described in <a href="https://pubmed.ncbi.nlm.nih.gov/29059683/"><strong>PMID 29059683</strong></a> and can be downloaded from <a href="http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/oncoarray-and-combined-summary-result/gwas- summary-results-breast-cancer-risk-2017/">http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/oncoarray-and-combined-summary-result/gwas- summary-results-breast-cancer-risk-2017/</a> (this link also includes acknowledgements). The prostate cancer data are described in <a href="https://pubmed.ncbi.nlm.nih.gov/29892016/"><strong>PMID 29892016</strong></a> and can be downloaded from: <a href="http://practical.icr.ac.uk/blog/?page_id=8164">http://practical.icr.ac.uk/blog/?page_id=8164</a> (this link also includes acknowledgements). The ovarian cancer data used are described in <a href="https://pubmed.ncbi.nlm.nih.gov/28346442/"><strong>PMID 28346442</strong></a> and can be downloaded from <a href="https://www.ebi.ac.uk/gwas/studies/GCST004415">https://www.ebi.ac.uk/gwas/studies/GCST004415</a>. The endometrial cancer data are described in <a href="https://pubmed.ncbi.nlm.nih.gov/30093612/"><strong>PMID 30093612</strong></a> and can be downloaded from <a href="https://www.ebi.ac.uk/gwas/studies/GCST006464">https://www.ebi.ac.uk/gwas/studies/GCST006464</a>. These links point to the same data that form the basis of the cross_cancer_sum_stats.txt.gz file.</p> <p> </p> <p><strong>The sample size and precision of the data presented should preclude identification of any individual study participant. However, in downloading these data, you undertake not to attempt to identify individual study participant and not to re-post these data to a third-party website. Please cite the PMIDs highlighted above along with the appropriate acknowledements if you use the cross_cancer_sum_stats.txt.gz file.</strong></p> <p> </p> <p>If you have any questions about this repository, please email Siddhartha Kar at siddhartha dot kar at bristol dot ac dot uk</p>
Association of common genetic variants with brain microbleeds: A genome-wide association study
<p><strong>Objective:</strong> To identify common genetic variants associated with the presence of brain microbleeds (BMB).</p> <p><strong>Methods:</strong> We performed genome-wide association studies in 11 population-based cohort studies and 3 case-control or case-only stroke cohorts. Genotypes were imputed to the Haplotype Reference Consortium or 1000 Genomes reference panel. BMB were rated on susceptibility-weighted or T2*-weighted gradient echo magnetic resonance imaging sequences, and further classified as lobar, or mixed (including strictly deep and infratentorial, possibly with lobar BMB). In a subset, we assessed the effects of <em>APOE</em> ε2 and ε4 alleles on BMB counts. We also related previously identified cerebral small vessel disease variants to BMB.</p> <p><strong>Results: </strong>BMB were detected in 3,556 of the 25,862 participants, of which 2,179 were strictly lobar and 1,293 mixed. One locus in the <em>APOE</em> region reached genome-wide significance for its association with BMB (lead SNP rs769449; OR<sub>any BMB</sub> (95% CI)=1.33 (1.21-1.45); p=2.5x10-10). <em>APOE</em> ε4 alleles were associated with strictly lobar (OR (95% CI)=1.34 (1.19- 1.50); p=1.0x10-6) but not with mixed BMB counts (OR (95% CI)=1.04 (0.86-1.25); p=0.68). <em>APOE</em> ε2 alleles did not show associations with BMB counts. Variants previously related to deep intracerebral hemorrhage and lacunar stroke, and a risk score of cerebral white matter hyperintensity variants, were associated with BMB.</p> <p><strong>Conclusions: </strong>Genetic variants in the <em>APOE</em> region are associated with the presence of BMB, most likely due to the <em>APOE</em> ε4 allele count related to a higher number of strictly lobar BMB. Genetic predisposition to small vessel disease confers risk of BMB, indicating genetic overlap with other cerebral small vessel disease markers.</p>
Data from: Candidate variants for additive and interactive effects on bioenergy traits in switchgrass (Panicum virgatum L.) identified by genome-wide association analyses
Switchgrass is a promising herbaceous energy crop, but further gains in biomass yield and quality must be achieved to enable a viable bioenergy industry. Developing DNA markers can contribute to such progress, but depiction of genetic bases should be reliable, involving not only simple additive marker effects but also interactions with genetic backgrounds, e.g., ecotypes, or synergies with other markers. We analyzed plant height, carbon content, nitrogen content, and mineral concentration in a diverse panel consisting of 512 genotypes of upland and lowland ecotype. We performed association analyses based on exome capture sequencing and tested 439,170 markers for marginal effects, but also 83,290 markers for marker-by-ecotype interactions and up to 311,445 marker pairs for pairwise interactions. Analyses of pairwise interactions focused on subsets of marker pairs preselected based on marginal marker effects, gene ontology annotation, and pairwise marker associations. Our tests identified 12 significant effects. Homology and gene expression information corroborated seven effects and indicated plausible causal pathways: flowering time and lignin synthesis for plant height; plant growth and senescence for carbon content and mineral concentration. Four pairwise interactions were detected, including three interactions preselected based on pairwise marker correlations. Furthermore, one marker-by-ecotype interaction and one pairwise interaction were confirmed in an independent switchgrass panel. Our analyses identified reliable candidate variants for important bioenergy traits in switchgrass. Moreover, they exemplified the importance of interactive effects for the depiction of genetic bases, and illustrated the usefulness of preselection of marker pairs for identifying pairwise marker interactions in association testing.
Data from: Genome-wide association reveals the locus responsible for four-horned ruminant
Phenotypic variability in horn characteristics, such as their size, number and shape, offers the opportunity to elucidate the molecular basis of horn development. The objective of this study was to map the genetic determinant controlling the production of four horns in two breeds, Jacob sheep and Navajo-Churro, and examine whether an eyelid abnormality occurring in the same populations is related. Genome-wide association mapping was performed using 125 animals from the two breeds that contain two- and four-horned individuals. A case–control design analysis of 570 712 SNPs genotyped with the ovine HD SNP Beadchip revealed a strong association signal on sheep chromosome 2. The 10 most strongly associated SNPs were all located in a region spanning Mb positions 131.9–132.6, indicating the genetic architecture underpinning the production of four horns is likely to involve a single gene. The closest genes to the most strongly associated marker (OAR2_132568092) were MTX2 and the HOXD cluster, located approximately 93 Kb and 251 Kb upstream respectively. The occurrence of an eyelid malformation across both breeds was restricted to polled animals and those carrying more than two horns. This suggests the eyelid abnormality may be associated with departures from the normal developmental production of two-horned animals and that the two conditions are developmentally linked. This study demonstrated the presence of separate loci responsible for the polled and four-horned phenotypes in sheep and advanced our understanding of the complexity that underpins horn morphology in ruminants.
Data from: Combining high-throughput micro-CT-RGB phenotyping and genome-wide association study to dissect the genetic architecture of tiller growth in rice
Manual phenotyping of rice tillers is time consuming and labor intensive and lags behind the rapid development of rice functional genomics. Thus, automated, non-destructive phenotyping of rice tiller traits at a high spatial resolution and high-throughput for large-scale assessment of rice accessions is urgently needed. In this study, we developed a high-throughput micro-CT-RGB (HCR) imaging system to non-destructively extract 730 traits from 234 rice accessions at 9 time points. We could explain 30% of the grain yield variance from 2 tiller traits assessed in the early growth stages. A total of 402 significantly associated loci were identified by GWAS, and dynamic and static genetic components were found across the nine time points. A major locus associated with tiller angle was detected at nine time points, which contained a major gene TAC1. Significant variants associated with tiller angle were enriched in the 3'-UTR of TAC1. Three haplotypes for the gene were found and rice accessions containing haplotype H3 displayed much smaller tiller angles. Further, we found two loci contained associations with both vigor-related HCR traits and yield. The superior alleles would be beneficial for breeding of high yield and dense planting.
Data from: Genome-wide association study in Arabidopsis thaliana of natural variation in seed oil melting point, a widespread adaptive trait in plants
Seed oil melting point is an adaptive, quantitative trait determined by the relative proportions of the fatty acids that compose the oil. Micro- and macro-evolutionary evidence suggests selection has changed the melting point of seed oils to covary with germination temperatures because of a trade-off between total energy stores and the rate of energy acquisition during germination under competition. The seed oil compositions of 391 natural accessions of Arabidopsis thaliana, grown under common-garden conditions, were used to assess whether seed oil melting point within a species varied with germination temperature. In support of the adaptive explanation, long-term monthly spring and fall field temperatures of the accession collection sites significantly predicted their seed oil melting points. In addition, a genome-wide association study (GWAS) was performed to determine which genes were most likely responsible for the natural variation in seed oil melting point. The GWAS found a single highly significant association within the coding region of FAD2, which encodes a fatty acid desaturase central to the oil biosynthesis pathway. In a separate analysis of fifteen a priori oil synthesis candidate genes, two (FAD2 and FATB) were located near significant SNPs associated with seed oil melting point. These results comport with others' molecular work showing that lines with alterations in these genes affect seed oil melting point as expected. Our results suggest natural selection has acted on a small number of loci to alter a quantitative trait in response to local environmental conditions.
Data from: Genome-wide association analysis for blood lipid traits measured in three pig populations revealed a substantial level of genetic heterogeneity
Serum lipids are associated with myocardial infarction and cardiovascular disease in humans. Here we dissected the genetic architecture of blood lipid traits by applying genome-wide association studies (GWAS) in 1,256 pigs from Laiwu, Erhualian and Duroc × (Landrace × Yorkshire) populations, and a meta-analysis of GWAS in more than 2,400 pigs from five diverse populations. A total of 22 genomic loci surpassing the suggestive significance level were detected on 11 pig chromosomes (SSC) for six blood lipid traits. Meta-analysis of GWAS identified 5 novel loci associated with blood lipid traits. Comparison of GWAS loci across the tested populations revealed a substantial level of genetic heterogeneity for porcine blood lipid levels. We further evaluated the causality of nine polymorphisms nearby or within the APOB gene on SSC3 for serum LDL-C and TC levels. Of the 9 polymorphisms, an indel showed the most significant association with LDL-C and TC in Laiwu pigs. But the significant association was not identified in the White Duroc × Erhualian F2 resource population, in which the QTL for LDL-C and TC was also detected on SSC3. This indicates that population-specific signals may exist for the SSC3 QTL. Further investigations are warranted to validate this assumption.
Data from: Penalized Multi-Marker versus Single-Marker Regression methods for genome-wide association studies of quantitative traits
The data from genome-wide association studies (GWAS) in humans are still predominantly analyzed using single marker association methods. As an alternative to Single Marker Analysis (SMA), all or subsets of markers can be tested simultaneously. This approach requires a form of Penalized Regression (PR) as the number of SNPs is much larger than the sample size. Here we review PR methods in the context of GWAS, extend them to perform penalty parameter and SNP selection by False Discovery Rate (FDR) control, and assess their performance in comparison with SMA. PR methods were compared with SMA using realistically simulated GWAS data with a continuous phenotype and real data. Based on these comparisons our analytic FDR criterion may currently be the best approach to SNP selection using PR for GWAS. We found that PR with FDR control provides substantially more power than SMA with genome-wide type-I error control but somewhat less power than SMA with Benjamini-Hochberg FDR control (SMA-BH). PR with FDR based penalty parameter selection controlled the FDR somewhat conservatively while SMA-BH may not achieve FDR control in all situations. Differences among PR methods seem quite small when the focus is on SNP selection with FDR control. Incorporating linkage disequilibrium into the penalization by adapting penalties developed for covariates measured on graphs can improve power but also generate more false positives or wider regions for follow-up. We recommend the Elastic Net with a mixing weight for the Lasso penalty near 0.5 as the best method.
Data from: Genome-wide association study identifies vitamin B5 biosynthesis as a host specificity factor in Campylobacter
Genome-wide association studies have the potential to identify causal genetic factors underlying important phenotypes but have rarely been performed in bacteria. We present an association mapping method that takes into account the clonal population structure of bacteria and is applicable to both core and accessory genome variation. Campylobacter is a common cause of human gastroenteritis as a consequence of its proliferation in multiple farm animal species and its transmission via contaminated meat and poultry. We applied our association mapping method to identify the factors responsible for adaptation to cattle and chickens among 192 Campylobacter isolates from these and other host sources. Phylogenetic analysis implied frequent host switching but also showed that some lineages were strongly associated with particular hosts. A seven-gene region with a host association signal was found. Genes in this region were almost universally present in cattle but were frequently absent in isolates from chickens and wild birds. Three of the seven genes encoded vitamin B5 biosynthesis. We found that isolates from cattle were better able to grow in vitamin B5-depleted media and propose that this difference may be an adaptation to host diet.
Data from: Genome-wide association analysis of stalk biomass and anatomical traits in maize
Background: Maize stover is an important source of crop residues and a promising sustainable energy source in the United States. Stalk is the main component of stover, representing about half of stover dry weight. Characterization of genetic determinants of stalk traits provide a foundation to optimize maize stover as a biofuel feedstock. We investigated maize natural genetic variation in genome-wide association studies (GWAS) to detect candidate genes associated with traits related to stalk biomass (stalk diameter and plant height) and stalk anatomy (rind thickness, vascular bundle density and area). Results: Using a panel of 942 diverse inbred lines, 899,784 RNA-Seq derived single nucleotide polymorphism (SNP) markers were identified. Stalk traits were measured on 800 members of the panel in replicated field trials across years. GWAS revealed 16 candidate genes associated with four stalk traits. Most of the detected candidate genes were involved in fundamental cellular functions, such as regulation of gene expression and cell cycle progression. Two of the regulatory genes (Zmm22 and an ortholog of Fpa) that were associated with plant height were previously shown to be involved in regulating the vegetative to floral transition. The association of Zmm22 with plant height was confirmed using a transgenic approach. Transgenic lines with increased expression of Zmm22 showed a significant decrease in plant height as well as tassel branch number, indicating a pleiotropic effect of Zmm22. Conclusion: Substantial heritable variation was observed in the association panel for stalk traits, indicating a large potential for improving useful stalk traits in breeding programs. Genome-wide association analyses detected several candidate genes associated with multiple traits, suggesting common regulatory elements underlie various stalk traits. Results of this study provide insights into the genetic control of maize stalk anatomy and biomass.
Data from: Genome-wide gene-associated microsatellite markers for the model invasive ascidian, Ciona intestinalis species complex
The vase tunicate, Ciona intestinalis species complex, has become a good model for ecological and evolutionary studies, especially those focusing on microevolution associated with rapidly changing environments. However, genome-wide genetic markers are still lacking. Here we characterized a large set of genome-wide gene-associated microsatellite markers for C. intestinalis spA (= C. robusta). Bioinformatic analysis identified 4654 microsatellites from expressed sequence tags (ESTs), 2126 of which successfully assigned to chromosomes were selected for further analysis. Based on the distribution evenness on chromosomes, function annotation and suitability for primer design, we chose 545 candidate microsatellites for further characterization. After amplification validation and variation assessment, 218 loci were polymorphic in at least one of the two populations collected from the coast of Arenys de Mar, Spain (N = 24 - 48) and Cape Town, South Africa (N = 24 - 33). The number of alleles, observed heterozygosity and expected heterozygosity ranged from two to 11, 0 to 0.833 and 0.021 to 0.818, and from two to 10, 0 to 0.879 and 0.031 to 0.845 for the Spanish and African populations, respectively. When all microsatellites were tested for cross-species utility, only 60 loci (25.8%) could be successfully amplified and all loci were polymorphic in C. intestinalis spB. A high level of genome-wide polymorphism is likely responsible for the low transferability. The large set of microsatellite markers characterized here is expected to provide a useful genome-wide resource for ecological and evolutionary studies using C. intestinalis as a model.
Data from: Genome-wide association study of a Varroa-specific defense behavior in honeybees (Apis mellifera)
Honey bees are exposed to many damaging pathogens and parasites. The most devastating is Varroa destructor, which mainly affects the brood. A promising approach for preventing its spread is to breed Varroa-resistant honey bees. One trait that has been shown to provide significant resistance against the Varroa mite is hygienic behavior, which is a behavioral response of honeybee workers to brood diseases in general. Here we report the use of an Affymetrix 44K SNP array to analyze SNPs associated with detection and uncapping of Varroa-parasitized brood by individual worker bees (Apis mellifera). For this study, 22,000 individually labeled bees were video-monitored and a sample of 122 cases and 122 controls was collected and analyzed to determine the dependence / independence of SNP genotypes from hygienic and non-hygienic behavior on a genome-wide scale. After false-discovery rate correction of the p-values, six SNP markers had highly significant associations with the trait investigated (alpha < 0.01). Inspection of the genomic regions around these SNPs led to the discovery of putative candidate genes.
Data from: Genome-wide association studies in apple reveal loci of large effect controlling apple polyphenols
Apples are a nutritious food source with significant amounts of polyphenols that contribute to human health and wellbeing, primarily as dietary antioxidants. Although numerous pre- and post-harvest factors can affect the composition of polyphenols in apples, genetics is presumed to play a major role because polyphenol concentration varies dramatically among apple cultivars. Here we investigated the genetic architecture of apple polyphenols by combining high performance liquid chromatography (HPLC) data with ~100,000 single nucleotide polymorphisms (SNPs) from two diverse apple populations. We found that polyphenols can vary in concentration by up to two orders of magnitude across cultivars, and that this dramatic variation was often predictable using genetic markers and frequently controlled by a small number of large effect genetic loci. Using GWAS, we identified candidate genes for the production of quercitrin, epicatechin, catechin, chlorogenic acid, 4-O-caffeoylquinic acid and procyanidins B1, B2, and C1. Our observation that a relatively simple genetic architecture underlies the dramatic variation of key polyphenols in apples suggests that breeders may be able to improve the nutritional value of apples through marker-assisted breeding or gene editing.
Data from: The evolutionary history of Xiphophorus fish and their sexually selected sword: a genome-wide approach using restriction site-associated DNA sequencing
Next-generation sequencing (NGS) techniques are now key tools in the detection of population genomic and gene expression differences in a large array of organisms. However, so far few studies have utilized such data for phylogenetic estimations. Here, we use NGS data obtained from genome-wide restriction site-associated DNA (RAD) (∼66000 SNPs) to estimate the phylogenetic relationships among all 26 species of swordtail and platyfish (genus Xiphophorus) from Central America. Past studies, both sequence and morphology-based, have differed in their inferences of the evolutionary relationships within this genus, particularly at the species-level and among monophyletic groupings. We show that using a large number of markers throughout the genome, we are able to infer the phylogenetic relationships with unparalleled resolution for this genus. The relationships among all three major clades and species within each of them are highly resolved and consistent under maximum likelihood, Bayesian inference and maximum parsimony. However, we also highlight the current cautions with this data type and analyses. This genus exhibits a particularly interesting evolutionary history where at least two species may have arisen through hybridization events. Here, we are able to infer the paternal lineages of these putative hybrid species. Using the RAD-marker-based tree we reconstruct the evolutionary history of the sexually selected sword trait and show that it may have been present in the common ancestor of the genus. Together our results highlight the outstanding capacity that RAD sequencing data has for resolving previously problematic phylogenetic relationships, particularly among relatively closely related species.
Data from: Genome-wide association study of insect bite hypersensitivity in Swedish-born Icelandic horses
Insect bite hypersensitivity (IBH) is the most common allergic skin disease in horses and is caused by biting midges, mainly of the genus Culicoides. The disease predominantly comprises a type I hypersensitivity reaction, causing severe itching and discomfort that reduce the welfare and commercial value of the horse. It is a multifactorial disorder influenced by both genetic and environmental factors, with heritability ranging from 0.16 to 0.27 in various horse breeds. The worldwide prevalence in different horse breeds ranges from 3% to 60%; it is more than 50% in Icelandic horses exported to the European continent and approximately 8% in Swedish-born Icelandic horses. To minimize the influence of environmental effects, we analyzed Swedish-born Icelandic horses to identify genomic regions that regulate susceptibility to IBH. We performed a genome-wide association (GWA) study on 104 affected and 105 unaffected Icelandic horses genotyped using Illumina® EquineSNP50 Genotyping BeadChip. Quality control and population stratification analyses were performed with the GenABEL package in R (λ = 0.81). The association analysis was performed using the Bayesian variable selection method, Bayes C, implemented in GenSel software. The highest percentage of genetic variance was explained by the windows on X chromosomes (0.51% and 0.36% by 73 and 74 mb), 17 (0.34% by 77 mb), and 18 (0.34% by 26 mb). Overlapping regions with previous GWA studies were observed on chromosomes 7, 9, and 17. The windows identified in our study on chromosomes 7, 10, and 17 harbored immune system genes and are priorities for further investigation.
Data from: Genome-wide association mapping of quantitative traits in a breeding population of sugarcane
Background: Molecular markers associated with relevant agronomic traits could significantly reduce the time and cost involved in developing new sugarcane varieties. Previous sugarcane genome-wide association analyses (GWAS) have found few molecular markers associated with relevant traits at plant-cane stage. The aim of this study was to establish an appropriate GWAS to find molecular markers associated with yield related traits consistent across harvesting seasons in a breeding population. Sugarcane clones were genotyped with DArT (Diversity Array Technology) and TRAP (Target Region Amplified Polymorphism) markers, and evaluated for cane yield (CY) and sugar content (SC) at two locations during three successive crop cycles. GWAS mapping was applied within a novel mixed-model framework accounting for population structure with Principal Component Analysis scores as random component. Results: A total of 43 markers significantly associated with CY in plant-cane, 42 in first ratoon, and 41 in second ratoon were detected. Out of these markers, 20 were associated with CY in 2 years. Additionally, 38 significant associations for SC were detected in plant-cane, 34 in first ratoon, and 47 in second ratoon. For SC, one marker-trait association was found significant for the 3 years of the study, while twelve markers presented association for 2 years. In the multi-QTL model several markers with large allelic substitution effect were found. Sequences of four DArT markers showed high similitude and e-value with coding sequences of Sorghum bicolor, confirming the high gene microlinearity between sorghum and sugarcane. Conclusions: In contrast with other sugarcane GWAS studies reported earlier, the novel methodology to analyze multi-QTLs through successive crop cycles used in the present study allowed us to find several markers associated with relevant traits. Combining existing phenotypic trial data and genotypic DArT and TRAP marker characterizations within a GWAS approach including population structure as random covariates may prove to be highly successful. Moreover, sequences of DArT marker associated with the traits of interest were aligned in chromosomal regions where sorghum QTLs has previously been reported. This approach could be a valuable tool to assist the improvement of sugarcane and better supply sugarcane demand that has been projected for the upcoming decades.
Petal size in rapeseed: novel QTL and candidate genes detected through genome-wide association study and transcriptome comparison
<p>Petal size determines the value of ornamental plants, and thus their economic worth. However, the molecular mechanisms controlling petal size remain unclear in most non-model species. To identify quantitative trait loci and candidate genes regulating petal size in rapeseed (<i>Brassica napus</i>), we performed a genome-wide association study (GWAS) using data from 588 accessions over three consecutive years. We detected 17 significant single nucleotide polymorphisms (SNPs) associated with petal size, with the most significant SNPs located on chromosomes A05 and C06. A combination of GWAS and transcriptomic sequencing based on two accessions with extreme differences in petal size identified 11 differentially expressed genes (DEGs) that may control petal size variation in rapeseed. In particular, <i>BnaA05</i><i>.</i><i>RAP2.2</i> homologous to <i>RAP2.2</i> in rapeseed may be a critical gene negatively influencing petal size through the ethylene signaling pathway. In addition, a comparison of petal epidermal cells indicated that petal size differences between the two extreme accessions were determined mainly by cell number differences. Finally, we propose a preliminary model for the control of petal size in rapeseed. Our results provide insights into the genetic mechanisms regulating petal size, and also lay the foundation for a better understanding of petal development in plants.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.