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Data from: Genome-wide association study for body weight in cattle populations from Siberia
Body weight is a complex trait in cattle associated with commonly used commercial breeding measurements related to growth. Although many quantitative trait loci (QTL) for body weight have been identified in cattle so far, searching for genetic determinants in different breeds or environments is promising. Therefore, we carried out a genome‐wide association study (GWAS) in two cattle populations from the Russian Federation (Siberian region) using the GGP HD150K array containing 139 376 single nucleotide polymorphism (SNP) markers. Association tests for 107 550 SNPs left after filtering revealed five statistically significant SNPs on BTA5, considering a false discovery rate of less than 0.05. The chromosomal region containing these five SNPs contains the CCND2 gene, which was previously associated with average daily weight gain and body mass index in US beef cattle populations and in humans respectively. Our study is the first GWAS for body weight in beef cattle populations from the Russian Federation. The results provided here suggest that, despite the existence of breed‐ and species‐specific QTL, the genetic architecture of body weight could be evolutionarily conserved in mammals.
Data from: A genome-wide association study identifies a region strongly associated with symmetrical onychomadesis on chromosome 12 in dogs
Symmetrical onychomadesis causes periodic loss of claws in otherwise healthy dogs. Genome-wide association analysis in 225 Gordon Setters identified a single region associated with symmetrical onychomadesis on chromosome 12 (spanning about 3.3 mb). A meta-analysis including also English Setters indicated that this genomic region predisposes for symmetrical onychomadesis in English Setters as well. The associated region spans most of the major histocompatibility complex and nearly 1 Mb downstream. Like many other autoimmune diseases, associations of symmetrical onychomadesis with DLA class II alleles have been reported. In this study, no associated markers were revealed within any of the DLA-DRB1, -DQA1 or -DQB1 genes, and the odds for symmetrical onychomadesis in the Gordon Setters were much higher, carrying significant single nucleotide polymorphisms compared to the odds of any of the recorded DLA-DRB1/DQA1/DQB1 haplotypes. We noticed that some of the associated DLA haplotypes were different between the English Setters and the Gordon Setters. Interestingly, associated SNP chip markers showed a more consistent pattern of allelic variants related to cases or controls regardless of breed. In conclusion, the associated genetic markers identified in this study hold the potential to aid in selection of breeding animals to reduce the frequency of symmetrical onychomadesis in the dog.
Integrative genome-wide analyses identify novel loci associated with kidney stones and provide insights into its genetic architecture
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Phenotypic variation and genome-wide association studies of main culm panicle node number, maximum node production rate, and degree-days to heading in rice
<p>To understand the genetic basis of main culm panicle node number, maximum node production rate, and degree-days to heading in rice (Oryza sativa), we conducted genome-wide association studies using a diversity panel of 220 rice accessions and 854,832 SNP markers generated using genotyping-by-sequencing (GBS), with 1X coverage. The raw genotype data was filtered, selecting single nucleotide polymorphisms (SNPs) having less than 50% missing data and minimum allele frequency (MAF) >5%. After initial filtering, imputation was conducted using BEAGLE V4.0 in 1,075,302 SNP markers. After imputation, the dataset was filtered a second time by removing SNPs with less than 5% MAF and more than 5% missing data. A total of 854,832 SNPs were used in the genome-wide association analyses. The dataset representing the genotype data of 854,832 SNP markers by 220 rice accessions is presented here.</p>
Data from: Genetic dissection of grain iron and zinc, and thousand kernel weight in wheat (Triticum aestivum L.) using genome-wide association study
<p>The study material in GWAS panel with 280 common bread wheat genotypes was selected from All India Coordinated Research Project on Wheat and Barley to map the genomic regions responsible for enhanced Grain Zinc Content (GZnC), Grain Iron Content (GZnC) and Thousand Kernel weight (TKW).</p> <p><strong>Phenotypic data:</strong></p> <p>The GWAS panel was evaluated at five different environments: E1-University of Agricultural Sciences, research farm, Dharwad (15°29'20.71"N, 74°59'3.35"E, 750m AMSL), E2-ICAR- Indian Agricultural Research Institute, New Delhi (28°38′30.5″N, 77°09′58.2″E, 228 m AMSL), E3-Indian Agricultural Research Institute, Jharkhand (24°16'58.4"N, 85°21'16.1"E, 651m AMSL), E4-ICAR-Indian Institute of Wheat and Barley, Karnal (29°41'8.2644''N, 76°59'25.9692''E, 250m AMSL), and E5-Punjab Agricultural University, Ludhiana (30o54' N, 75o48'E, 247m AMSL). Around 20 g of grain sample from each genotype were used for phenotyping GFeC and GZnC through high-throughput Energy Dispersive X-ray Fluorescence (ED-XRF) machine (model X-Supreme 8000; Oxford Instruments plc, Abingdon, United Kingdom) calibrated with glass beads-based values. To record TKW, the Numigral grain counter was used to count the grain number, the reading was set at 1000 grains and the weight of the grains was recorded in grams with an electronic balance. The GFeC, GZnC were expressed as milligram per kilogram (mg/kg), GPC in percentage (%), TKW in grams (gms).</p> <p><strong>Genotypic data:</strong></p> <p>Genomic DNA of the GWAS panel was extracted from the leaves of 21 days-old seedlings by Cetyl Trimethyl Ammonium Bromide (CTAB) method. The panel was genotyped using Axiom Wheat Breeder's Genotyping Array (Affymetrix, Santa Clara, CA, United States) having 35,143 genome-wide SNPs. The monomorphic, markers with minor allele frequency (MAF) of <5%, missing data of >20%, and heterozygote frequency >25% were removed from the analysis. The remaining set of 14,790 high-quality SNPs was used in GWAS analysis. The detailed information of the methods and software used, data analysis and GWAS is available at DOI: 10.1038/s41598-022-15992-z.</p>
Data from: Genome-wide association study for grain yield and component traits in wheat (Triticum aestivum L.)
<p>The study material in GWAS panel with 280 common bread wheat genotypes was selected from All India Coordinated Research Project on Wheat and Barley to map the genomic regions governing days to heading (DH), grain filling duration (GFD), grain number per spike (GNPS), grain weight per spike (GWPS), plant height (PH), and grain yield (GY).</p> <p><strong>Phenotypic data:</strong></p> <p>The GWAS panel was evaluated at five different environments during the 2020-21 <em>Rabi</em> (winter) season: E1-University of Agricultural Sciences, research farm, Dharwad (15°29'20.71"N, 74°59'3.35"E, 750m AMSL), E2-ICAR-Indian Agricultural Research Institute, New Delhi (28°38′30.5″N, 77°09′58.2″E, 228 m AMSL), E3-Indian Agricultural Research Institute, Jharkhand (24°16'58.4"N, 85°21'16.1"E, 651m AMSL), E4-ICAR-Indian Institute of Wheat and Barley, Karnal (29°41'8.2644''N, 76°59'25.9692''E, 250m AMSL), and E5-Punjab Agricultural University, Ludhiana (30o54' N, 75o48'E, 247m AMSL). The genotypes were planted in an augmented block design along with repeated checks (DBW187, MACS6222, WH1124, and WH1142). All the genotypes of a GWAS panel were phenotyped for six quantitative traits i.e. GWPS (gm), GY (gm), PH (cm) at five locations, GFD (days), DH (days) at four locations and GNPS (number) at two locations. Phenotypic data were analyzed using the R package 'augmentedRCBD'</p> <p><strong>Genotypic data:</strong></p> <p>Genomic DNA of the GWAS panel was extracted from the leaves of 21 days-old seedlings by Cetyl Trimethyl Ammonium Bromide (CTAB) method. The panel was genotyped using Axiom Wheat Breeder's Genotyping Array (Affymetrix, Santa Clara, CA, United States) having 35,143 genome-wide SNPs. The monomorphic, markers with minor allele frequency (MAF) of <5%, missing data of >20%, and heterozygote frequency >25% were removed from the analysis. The remaining set of 14,790 high-quality SNPs was used in GWAS analysis. </p>
Genome-wide association mapping for component traits of drought and heat tolerance in wheat
<p>The study material in GWAS panel with 282 advanced breeding line of bread wheat genotypes from IARI stress breeding program was selected to map the genomic regions responsible for Drought and heat tolerance component traits.</p> <p>Phenotypic data:</p> <p>The GWAS panel was evaluated at multiple locations namely, IARI, New Delhi - DL (28.6550° N, 77.1888° E, MSL 228.61 m), ARI, Pune - PUNE (18.5204° N, 73.8567° E, MSL 560m), IIWBR, Karnal - IIWBR (29.6857° N, 76.9905°E, MSL 243m), IARI, Jharkhand - JR (24.1929° N, 85.3756° E, MSL 580m) and IARI RS, Indore - IND (22.7196° N, 75.8577° E, MSL 553 m) with augmented RCBD design. Three tratments viz, IR (Irrigated), RI (Restricted irrigated) and LS (Late sown) were imposed for control, drought and heat stress, respectively. Data was collected on traits like Days to heading (DH), Days to maturity (DM), Normalized Difference Vegetation Index (NDVI) at anthesis and grain filling stage, chlorophyll content (SPAD) of flag leaf at post anthesis stage, Plant height (PH), Canopy temperature (CT), Grain weight per spike (GWPS), Thousand Grain weight (TGW), Plot Yield (PLTY) and Biomass.</p> <p>Genotypic data:</p> <p>Genomic DNA of the GWAS panel was extracted from the leaves of seedlings by Cetyl Trimethyl Ammonium Bromide (CTAB) method. The panel was genotyped using Axiom Wheat Breeder's Genotyping Array (Affymetrix, Santa Clara, CA, United States) having 35,143 genome-wide SNPs. The monomorphic, markers with minor allele frequency (MAF) of <5%, missing data of >20%, and heterozygote frequency >25% were removed from the analysis. The remaining set of 10546 high-quality SNPs was used in GWAS analysis.</p> <p>The detailed information of the methods and software used, data analysis and GWAS is provided at doi: 10.3389/fpls.2022.943033</p>
Data from: Genome-wide analysis reveals demographic and life history patterns associated with habitat modification in land-locked, deep-spawning sockeye salmon (Oncorhynchus nerka)
<p>Human-mediated habitat fragmentation in freshwater ecosystems can negatively impact genetic diversity, demography and life history of native biota, while disrupting the behaviour of species that are dependent on spatial connectivity to complete their life cycles. In the Alouette River system (British Columbia, Canada), dam construction in 1928 impacted passage of anadromous sockeye salmon (<i>Oncorhynchus nerka</i>), with the last records of migrants occurring in the 1930's. Since that time, <i>O. nerka</i> persisted as a resident population in Alouette Reservoir until experimental water releases beginning in 2005 created conditions for migration; two years later, returning migrants were observed for the first time in ~70 years, raising important basic and applied questions regarding life history variation and population structure in this system. Here, we investigated the genetic distinctiveness and population history of Alouette Reservoir <i>O. nerka</i> using genome-wide SNP data (n=7,709 loci) collected for resident and migrant individuals, as well as for neighbouring anadromous sockeye salmon and resident kokanee populations within the Fraser River drainage (n=312 individuals). Bayesian clustering and principal components analyses based on neutral loci revealed five distinct clusters, largely associated with geography, and clearly demonstrated that Alouette Reservoir resident and migrant individuals are genetically distinct from other <i>O. nerka</i> populations in the Fraser River drainage. At a finer-level, there was no clear evidence for differentiation between Alouette Reservoir residents and migrants; although we detected eight high-confidence outlier loci, they all mapped to sex chromosomes suggesting that differences were likely due to uneven sex ratios rather than life history. Taken together, these data suggest that contemporary Alouette Reservoir <i>O. nerka</i> represents a landlocked sockeye salmon population, constituting the first reported instance of deep-water spawning behaviour associated with this life history form. This finding punctuates the need for re-assessment of conservation status and supports on-going fisheries management activities in Alouette Reservoir. </p>
Data from: Genome-wide association and genome partitioning reveal novel genomic regions underlying variation in gastrointestinal nematode burden in a wild bird
Identifying the genetic architecture underlying complex phenotypes is a notoriously difficult problem that often impedes progress in understanding adaptive eco-evolutionary processes in natural populations. Host–parasite interactions are fundamentally important drivers of evolutionary processes, but a lack of understanding of the genes involved in the host's response to chronic parasite insult makes it particularly difficult to understand the mechanisms of host life history trade-offs and the adaptive dynamics involved. Here, we examine the genetic basis of gastrointestinal nematode (Trichostrongylus tenuis) burden in 695 red grouse (Lagopus lagopus scotica) individuals genotyped at 384 genome-wide SNPs. We first use genome-wide association to identify individual SNPs associated with nematode burden. We then partition genome-wide heritability to identify chromosomes with greater heritability than expected from gene content, due to harbouring a multitude of additive SNPs with individually undetectable effects. We identified five SNPs on five chromosomes that accounted for differences of up to 556 worms per bird, but together explained at best 4.9% of the phenotypic variance. These SNPs were closely linked to genes representing a range of physiological processes including the immune system, protein degradation and energy metabolism. Genome partitioning indicated genome-wide heritability of up to 29% and three chromosomes with excess heritability of up to 4.3% (total 8.9%). These results implicate SNPs and novel genomic regions underlying nematode burden in this system and suggest that this phenotype is somewhere between being based on few large-effect genes (oligogenic) and based on a large number of genes with small individual but large combined effects (polygenic).
Data from: Genome-wide association mapping of date palm fruit traits
Date palms (Phoenix dactylifera) are an important fruit crop of arid regions of the Middle East and North Africa. Despite its importance, few genomic resources exist for date palms, hampering evolutionary genomic studies of this perennial crop species. Here we report an improved long-read genome assembly for P. dactylifera that is 772.3 Mb in length, with contig N50 of 897.2 Kb, and use this to perform GWAS mapping of the sex determining region and 21 fruit traits. We find a fruit color GWAS at the R2R3-MYB transcription factor (VIRESCENS) gene and identify functional alleles that include a retrotransposon insertion and start codon mutation. We also find a GWAS peak for sugar composition spanning deletion polymorphisms in multiple linked invertase genes. MYB transcription factors and invertase are implicated in fruit color and sugar composition in other crop species, demonstrating the importance of parallel evolution in the evolutionary diversification of domesticated species.
Data from: Linking genotype to phenotype in a changing ocean: inferring the genomic architecture of a blue mussel stress response with genome-wide association
A key component to understanding the evolutionary response to a changing climate is linking underlying genetic variation to phenotypic variation in stress response. Here we use a genome-wide association approach (GWAS) to understand the genetic architecture of calcification rates under simulated climate stress. We take advantage of the genomic gradient across the blue mussel hybrid zone (Mytilus edulis and Mytilus trossulus) in the Gulf of Maine (GOM) to link genetic variation with variance in calcification rates in response to simulated climate change. Falling calcium carbonate saturation states are predicted to negatively impact many marine organisms that build calcium carbonate shells - like blue mussels. We sampled wild mussels and measured net calcification phenotypes after exposing mussels to a "climate change" common garden, where we raised temperature 3°C, decreased pH by 0.2 units, and limited food supply by filtering out planktonic particles > 5 μm, compared to ambient GOM conditions in the summer. This climate change exposure greatly increased phenotypic variation in net calcification rates compared to ambient conditions. We then used regression models to link the phenotypic variation with over 170,000 single nucleotide polymorphism loci (SNPs) generated by genotype by sequencing to identify genomic locations associated with calcification phenotype, and estimate heritability and architecture of the trait. We identified at least one of potentially 2-10 genomic regions responsible for 30% of the phenotypic variation in calcification rates that are potential targets of natural selection by climate change. Our simulations suggest a power of 13.7% with our study's average effective sample size of 118 individuals and rare alleles, but a power of > 90% when effective sample size is 900.
Competitiveness prediction for nodule colonization in Sinorhizobium meliloti through combined in vitro tagged strain characterization and genome-wide association analysis
<p>Associations between leguminous plants and symbiotic nitrogen-fixing rhizobia are a classic example of mutualism between a eukaryotic host and a specific group of prokaryotic microbes. Although this symbiosis is in part species-specific, different rhizobial strains may colonise the same nodule. Some rhizobial strains are commonly known as better competitors than others, but detailed analyses that aim to predict rhizobial competitive abilities based on genomes are still scarce. Here, we performed a bacterial <em>genome-wide association (GWAS) analysis to define the </em>genomic determinants related to the competitive capabilities in the model rhizobial species <em>Sinorhizobium meliloti.</em> For this, 13 tester strains were GFP-tagged and assayed <i>vs.</i> 3 RFP-tagged reference competitor strains (<em>Rm1021, AK83, and BL225C) in a</em> <i>Medicago sativa</i> nodule occupancy test. Competition data and strain genomic sequences were employed to build a model for GWAS based on <i>k</i>-mers. Among the <i>k</i>-mers with the highest scores, 51 <i>k</i>-mers mapped on the genomes of four strains showing the highest competition phenotypes (> 60% single strain nodule occupancy; GR4, KH35c, KH46 and SM11) <i>vs.</i> BL225C. These <i>k</i>-mers were mainly located on the symbiosis-related megaplasmid pSymA, specifically on genes coding for transporters, proteins involved in the biosynthesis of cofactors and proteins related to metabolism (e.g., fatty acids). The same analysis was performed considering the sum of single and mixed nodules obtained in the competition assays <em>vs. </em>BL225C, retrieving <i>k</i>-mers mapped on the genes previously found and on <i>vir</i> genes. Therefore, the competition abilities seem to be linked to multiple genetic determinants and comprise several cellular components.</p>
Genome-wide association of the metabolic shifts underpinning dark-induced senescence in Arabidopsis
<p>This dataset contained the result of Fv-Fm, chlorophyll, primary and lipid metabolites of Arabidopsis thaliana accessions of the <em>HapMap</em> collection under 0d, 3d and 6d after darkness treatment.</p>
UK dogs data from: Genome-wide association studies for canine hip dysplasia in single and multiple populations – implications and potential novel risk loci
<p>Background: <span>Association mapping studies of quantitative trait loci (QTL) for canine hip dysplasia (CHD) </span><span>can contribute to the understanding of the genetic background of this common and debilitating disease and might contribute to its genetic improvement. The power of association studies for CHD is limited by relatively small sample numbers for CHD records within countries, suggesting potential benefits of joining data across countries. However, this is complicated due to the use of different scoring systems across countries. In this study, we incorporated routinely assessed CHD records and genotype data of German Shepherd dogs from </span><span><span>two</span></span><span> countries </span><span><span>(UK and Sweden)</span></span><span> to perform </span><span>genome-wide association stud</span><span>ies (GWAS) within populations using different variations of CHD phenotypes. As phenotypes, dogs were either classified into cases and controls based on the </span><i><span>Fédération Cynologique Internationale</span></i><span> (FCI) five-level grading of the worst hip or the FCI grade was treated as an ordinal trait. </span><span><span>In a subsequent meta-analysis, we added publicly available data from a Finnish population and performed the GWAS across all populations.</span></span><span> Genetic associations for the CHD phenotypes were evaluated in a linear mixed model using 62,089 SNPs.</span></p> <p>Results: <span><span>Multiple SNPs with genome-wide significant and suggestive</span></span><span><span> associations</span></span><span> </span><span><span>were detected in single-population GWAS and the meta-analysis.</span></span><span> Few of these SNPs overlapped between populations </span><span><span>or between single-population GWAS and the meta-analysis</span></span><span>, suggesting that many CHD-related QTL are population-specific. More significant or suggestive SNPs were identified when FCI grades were used as phenotypes in comparison to the case-control approach. </span><i><span>MED13</span></i><span> (Chr 9) and </span><i><span>PLEKHA7</span></i><span> (Chr 21) emerged as novel positional candidate genes associated with hip dysplasia.</span></p> <p>Conclusions: <span>Our findings confirm the complex genetic nature of hip dysplasia in dogs, with multiple loci associated with the trait, </span><span><span>most</span></span><span> of which are population-specific. Routinely assessed CHD information collected across countries provide an opportunity to increase sample sizes and statistical power for association studies. While the lack of standardisation of CHD assessment schemes across countries poses a challenge, we showed that conversion of traits can be utilised to overcome this obstacle.</span></p>
Haplotype-based genome-wide association increases the predictability of leaf rust (Puccinia triticina) resistance in wheat
<p></p><p>Resistance breeding is crucial for a sustainable control of wheat leaf rust and SNP-based genome-wide association studies (GWAS) are widely used to dissect leaf rust resistance. Unfortunately, GWAS based on SNPs explained often only a small proportion of the genetic variation. We compared SNP-based GWAS with a method based on functional haplotypes (FH) considering epistasis in a comprehensive hybrid wheat mapping population composed of 133 parents plus their 1,574 hybrids and characterized with 626,245 high-quality SNPs. In total, 2,408 and 1,139,828 significant associations were detected in the mapping population by using SNP-based and FH-GWAS, respectively. These associations mapped to 25 and 69 candidate regions, correspondingly. SNP-based GWAS highlighted two already-known resistance genes, i.e. Lr22a and Lr34-B, while FH-GWAS not only detected associations on these genes but also on two additional genes, i.e. Lr10 and Lr1. As revealed by a second hybrid wheat population for independent validation, using detected associations from SNP-based and FH-GWAS reached predictabilities of 11.72% and 22.86%, respectively. Therefore, FH-GWAS is not only more powerful to detect associations, but also improves the accuracy of marker-assisted selection as compared to the SNP-based approach.</p><p></p>
Genome-wide association study of polygenic risk score-defined phenotype suffers from inflated test-statistics
<p>Simulation results from running the following script 100 times: https://github.com/euffelmann/paper-ad_prs_extremes/blob/main/scripts/ad_prs_extremes_simulation.R.</p> <p>These files can be used to reproduce tables and figures in: https://github.com/euffelmann/paper-ad_prs_extremes</p>
Summary statistics from a genome-wide association study of narcolepsy
<p>Type 1 narcolepsy (T1N) is a neurological condition, in which the death of hypocretin-producing neurons in the lateral hypothalamus leads to excessive daytime sleepiness and symptoms of abnormal Rapid Eye Movement (REM) sleep. Known triggers for narcolepsy are influenza-A infection and associated immunization during the 2009 H1N1 influenza pandemic. Here, we genotyped all remaining consented narcolepsy cases worldwide and assembled this with the existing genotyped individuals. We used this multi-ethnic sample in genome wide association study (GWAS) to dissect disease mechanisms and interactions with environmental triggers (5,339 cases and 20,518 controls). Overall, we found significant associations with HLA (2 GWA significant subloci) and 11 other loci. Six of these other loci have been previously reported (<em>TRA</em>, <em>TRB</em>, <em>CTSH</em>, <em>IFNAR1</em>, <em>ZNF365</em> and <em>P2RY11</em>) and five are new (<em>PRF1</em>, <em>CD207</em>, <em>SIRPG</em>, <em>IL27</em> and <em>ZFAND2A</em>). Strikingly, in vaccination-related cases, GWA significant effects were found in <em>HLA</em>, <em>TRA</em>, and in a novel variant near <em>SIRPB1</em>. Furthermore, <em>IFNAR1</em>-associated polymorphisms regulated dendritic cell response to influenza-A infection in vitro (p-value =1.92*10<sup>-25</sup>). A partitioned heritability analysis indicated specific enrichment of functional elements active in cytotoxic and helper T cells. Furthermore, functional analysis showed the genetic variants in <em>TRA</em> and <em>TRB</em> loci act as remarkably strong chain usage QTLs for <em>TRAJ*24</em> (p-value = 0.0017), <em>TRAJ*28</em> (p-value = 1.36*10<sup>-10</sup>) and <em>TRBV*4-2</em> (p-value = 3.71*10-<sup>117</sup>). This was further validated in TCR sequencing of 60 narcolepsy cases and 60 DQB1*06:02 positive controls, where chain usage effects were further accentuated. Together these findings show that the autoimmune component in narcolepsy is defined by antigen presentation, mediated through specific T cell receptor chains, and modulated by influenza-A as a critical trigger.</p>
Genome-wide association and genomic prediction for a reproductive index summarizing fertility outcomes in U.S. Holsteins
<p>Subfertility represents one major challenge to enhancing dairy production and efficiency. Herein, we use a reproductive index (RI) expressing the predicted probability of pregnancy following artificial insemination with Illumina 778K genotypes to perform single and multi-locus genome-wide association analyses (GWAA) on 2,448 geographically diverse U.S. Holstein cows and produce genomic heritability estimates. Moreover, we use genomic best linear unbiased prediction (GBLUP) to investigate the potential utility of the RI by performing genomic predictions with cross-validation. Notably, genomic heritability estimates for the U.S. Holstein RI were moderate ( 0.1654± 0.0317 – 0.2550 ± 0.0348), while single and multi-locus GWAA revealed overlapping quantitative trait loci (QTL) on BTA6 and BTA29, including known QTL for daughter pregnancy rate (DPR) and cow conception rate (CCR). Multi-locus GWAA revealed seven additional QTL, including one on BTA7 (60 Mb) which is adjacent to a known heifer conception rate (HCR) QTL (59 Mb). Positional candidate genes for the detected QTL included male and female fertility loci (i.e., spermatogenesis, oogenesis), meiotic and mitotic regulators, and genes associated with immune response, milk yield, enhanced pregnancy rates, and the reproductive-longevity pathway. Based on the proportion of phenotypic variance explained (PVE), all detected QTL (n = 13; P ≤ 5e<sup>-05</sup>) were estimated to have moderate (1.0% < PVE ≤ 2.0%) or small effects (PVE ≤ 1.0%) on the predicted probability of pregnancy. Genomic prediction using GBLUP with cross-validation (<em>k</em> = 3) produced mean predictive abilities (0.1692–0.2301) and mean genomic prediction accuracies (0.4119–0.4557) that were similar to bovine health and production traits previously investigated.</p>
Genome-Wide Association Studies meta-analysis uncovers NOJO and SGS3 novel genes involved in Arabidopsis thaliana primary root development and plasticity
<p>Postembryonic primary root growth relies on meristems that harbour multipotent stem cells that produce new cells that will duplicate and provide all the different root cell types. <em>Arabidopsis thaliana</em> primary root growth has become a model for evo-devo studies due to its simplicity and facility to record cell proliferation and differentiation. To identify new genetic components relevant to primary root growth, we used a Genome-Wide Association Studies (GWAS) meta-analysis approach using data published in the last decade. In this work, we performed intra and inter-studies analyses to discover new genetic components that could participate in primary root growth. We used 639 accessions from nine different studies and performed different GWAS tests ranging from single studies and pairwise analysis with high correlation associations, analyzing the same number of accessions in different studies to using the daily data of the root growth kinetic of the same research. We found that primary root growth changes were associated with 41 genomic loci, of which six (14.6%) have been previously described as inhibitors or promoters of primary root growth. The knockdown of genes associated with two of these loci: a gene that participates in Trans-acting siRNAs (tasiRNAs) processing <em>Suppressor of Gene Silencing</em> (<em>SGS3</em>) and a gene with a Sterile Alpha Motif (SAM) confirmed their participation as repressors of primary root growth. As none has been shown to participate in this developmental process before, our GWAS analysis identified new genes that participate in primary root growth. Overall, our findings provide novel insights into the genomic basis of root development and further demonstrate the usefulness of GWAS meta-analyses in non-human species.</p>
GWAS summary stats in "A web-based genome-wide association study reveals the susceptibility loci of common adverse events following COVID-19 vaccination in the Japanese population."
<p>Summary stats of the genome-wide meta-analysis with METAL software in the article "A web-based genome-wide association study reveals the susceptibility loci of common adverse events following COVID-19 vaccination in the Japanese population."</p><p>https://doi.org/10.1038/s41598-023-47632-5<br>Due to the absence of cases in either population, we were unable to perform GWAS for the following conditions.<br>constipation at BNT162b1 1st dose<br>dyspnea at BNT162b1 1st dose<br>eczema (long-term rash) at BNT162b1 1st dose<br>dyspnea at BNT162b1 2nd dose<br>sneeze at mRNA-1273 1st dose<br>dyspnea at mRNA-1273 1st dose</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.