Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
242
datasets available to search
ShareScore release 0.9.0
Dataset results
242 results for “Genetic mapping”
Data from: Association mapping of genetic risk factors for chronic wasting disease in wild deer
Open the record for dataset details and reuse information.
Data from: Ecological speciation in sympatric palms: 3. genetic map reveals genomic islands underlying species divergence in Howea
Open the record for dataset details and reuse information.
Data from: Genetic basis of octanoic acid resistance in Drosophila sechellia: functional analysis of a fine-mapped region
Open the record for dataset details and reuse information.
Data from: Adaptation via pleiotropy and linkage: association mapping reveals a complex genetic architecture within the stickleback Eda locus
Genomic mapping of the loci associated with phenotypic evolution has revealed genomic "hotspots", or regions of the genome that control multiple phenotypic traits. This clustering of loci has important implications for the speed and maintenance of adaptation and could be due to pleiotropic effects of a single mutation or tight genetic linkage of multiple causative mutations affecting different traits. The threespine stickleback (<i>Gasterosteus aculeatus</i>) is a powerful model for the study of adaptive evolution because the marine ecotype has repeatedly adapted to freshwater environments across the northern hemisphere in the last 12,000 years. Freshwater ecotypes have repeatedly fixed a 16 kilobase haplotype on chromosome IV that contains Ectodysplasin (<i>Eda</i>), a gene known to affect multiple traits, including defensive armor plates, lateral line sensory hair cells, and schooling behavior. Many additional traits have previously been mapped to a larger region of chromosome IV that encompasses the <i>Eda</i> freshwater haplotype. To identify which of these traits specifically map to this adaptive haplotype, we made crosses of rare marine fish heterozygous for the freshwater haplotype in an otherwise marine genetic background. Further, we performed fine-scale association mapping in a fully interbreeding, polymorphic population of freshwater stickleback to disentangle the effects of pleiotropy and linkage on the phenotypes affected by this haplotype. Although we find evidence that linked mutations have small effects on a few phenotypes, a small 1.4 kb region within the first intron of <i>Eda</i> has large effects on three phenotypic traits: lateral plate count, and both the number and patterning of the posterior lateral line neuromasts. Thus, the <i>Eda</i> haplotype is a hotspot of adaptation in stickleback due to both a small, pleiotropic region affecting multiple traits as well as multiple linked mutations affecting additional traits.
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>
Surveying the genome and constructing a high-density genetic map of napiergrass (Cenchrus purpureus Schumach)
<p>Napiergrass (Cenchrus purpureus Schumach) is a tropical forage grass and a promising lignocellulosic biofuel feedstock due to its high biomass yield, persistence, and nutritive value. However, its utilization for breeding has lagged behind other crops due to limited genetic and genomic resources. In this study, next-generation sequencing was frst used to survey the genome of napiergrass. Napiergrass sequences displayed high synteny to the pearl millet genome and showed expansions in the pearl millet genome along with genomic rearrangements between the two genomes. An average repeat content of 27.5% was observed in napiergrass including 5,339 simple sequence repeats (SSRs). Furthermore, to construct a high-density genetic map of napiergrass, genotyping-by-sequencing (GBS) was employed in a bi-parental population of 185 F1 hybrids. A total of 512 million high quality reads were generated and 287,093 SNPs were called by using multiple de-novo and reference-based SNP callers. Single dose SNPs were used to construct the frst high-density linkage map that resulted in 1,913 SNPs mapped to 14 linkage groups, spanning a length of 1,410cM and a density of 1 marker per 0.73cM. This map can be used for many further genetic and genomic studies in napiergrass and related species.</p> <p><strong>Genetic map files for Elephant grass genetic map.</strong><br> Surveying the genome and constructing a high-density genetic map of napiergrass (Cenchrus purpureus Schumach)</p> <p><strong># Marker files:</strong><br> Sex averaged map: map_NG_final_geneticmap_1913.txt<br> Female map: map_female_selected899_lm.txt<br> Male map: map_male_selected1073_nn.txt </p> <p><strong># Sequence and locus information.</strong><br> All reference based pipelines used the pearl millet genome v1 as explained in the manuscript. Sequences for the reference pipelines can be extracted based on the location of the SNPs. For denovo based pipelines, either the sequences or the locus and denovo map are included.</p> <p><br> Freebayes (F)<br> - 1_freebayes_48.vcf.gz</p> <p>GATK (G)<br> - 2_gatk_48.vcf.gz</p> <p>Samtools (St)<br> - 3_samtools_48.vcf.gz</p> <p>GBS-SNP-CROP (C)<br> - 4_snpcrop.hmp.txt</p> <p>TASSEL (T)<br> - 5_tassel.hmp.txt.gz</p> <p>Stacks (St)<br> - 6a_stacks_loc.gz<br> - 6b_stacks_snp.vcf.gz</p> <p>denovo GBS-SNP-CROP (dC)<br> - 7a_denovo_SNP_CROP.hmp.txt<br> - 7b_snpcrop_MockRef2PP.MockRef_Genome.fasta</p> <p>denovo Stacks (dS)<br> - 8a_denovo_stacks.loc<br> - 8b_denovo_stacks_sequences.tsv</p> <p>denovo TASSEL (dT)<br> - 9_denovo_tassel_uneak.fas</p> <p><br> <strong># Comparison between elephant grass and pearl millet genome:</strong><br> - Filterdp20_Elephantgrass.vcf.gz</p>
Data from: Genetic variation and association mapping for 12 agronomic traits in indica rice
Background: Increasing rice (Oryza sativa L.) yield is a crucial challenge for modern agriculture. The ideal plant architecture is considered to be critical to enhance rice yield. Elite plant morphological traits should include compact plant type, short stature, few unproductive tillers, thick and sturdy stems and erect leaves. To reveal the genetic variations of important morphological traits, 523 germplasm accessions were genotyped using the Illumina custom-designed array containing 5,291 single nucleotide polymorphisms (SNPs) and phenotyped in two independent environments. Genome-wide association studies were performed to uncover the genotypic and phenotypic variations using a mixed linear model. Results: In total, 126 and 172 significant loci were identified and these loci explained an average of 34.45 % and 39.09 % of the phenotypic variance in two environments, respectively, and 16 of 298 (~5.37 %) loci were detected across the two environments. For the 16 loci, 423 candidate genes were predicted in a 200-kb region (±100 kb of the peak SNP). Expression-level analyses identified four candidate genes as the most promising regulators of tiller angle. Known (NAL1 and Rc) and new significant loci showed pleiotropy and gene linkage. In addition, a long genome region covering ~1.6 Mb on chromosome 11 was identified, which may be critical for rice leaf architecture because of a high association with flag leaf length and the ratio of flag leaf length and width. The pyramid effect of the elite alleles indicated that these significant loci could be beneficial for rice plant architecture improvements in the future. Finally, 37 elite varieties were chosen as breeding donors for further rice plant architectural modifications. Conclusions: This study detected multiple novel loci and candidate genes related to rice morphological traits, and the work demonstrated that genome-wide association studies are powerful strategies for uncovering the genetic variations of complex traits and identifying candidate genes in rice, even though the linkage disequilibrium decayed slowly in self-pollinating species. Future research will focus on the biological validation of the candidate genes, and elite varieties will also be of interest in genome selection and breeding by design.
Data from: An SNP-based second-generation genetic map of Daphnia magna and its application to QTL analysis of phenotypic traits
Background: Although Daphnia is increasingly recognized as a model for ecological genomics and biomedical research, there is, as of yet, no high-resolution genetic map for the genus. Such a map would provide an important tool for mapping phenotypes and assembling the genome. Here we estimate the genome size of Daphnia magna and describe the construction of an SNP array based linkage map. We then test the suitability of the map for life history and behavioural trait mapping. The two parent genotypes used to produce the map derived from D. magna populations with and without fish predation, respectively and are therefore expected to show divergent behaviour and life-histories. Results: Using flow cytometry we estimated the genome size of D. magna to be about 238 mb. We developed an SNP array tailored to type SNPs in a D. magna F2 panel and used it to construct a D. magna linkage map, which included 1,324 informative markers. The map produced ten linkage groups ranging from 108.9 to 203.6 cM, with an average distance between markers of 1.13 cM and a total map length of 1,483.6 cM (Kosambi corrected). The physical length per cM is estimated to be 160 kb. Mapping infertility genes, life history traits and behavioural traits on this map revealed several significant QTL peaks and showed a complex pattern of underlying genetics, with different traits showing strongly different genetic architectures. Conclusions: The new linkage map of D. magna constructed here allowed us to characterize genetic differences among parent genotypes from populations with ecological differences. The QTL effect plots are partially consistent with our expectation of local adaptation under contrasting predation regimes. Furthermore, the new genetic map will be an important tool for the Daphnia research community and will contribute to the physical map of the D. magna genome project and the further mapping of phenotypic traits. The clones used to produce the linkage map are maintained in a stock collection and can be used for mapping QTLs of traits that show variance among the F2 clones.
Data from: Application of a dense genetic map for assessment of genomic responses to selection and inbreeding in Heliothis virescens
Adaptation of pest species to laboratory conditions and selection for resistance to toxins in the laboratory are expected to cause inbreeding and genetic bottlenecks that reduce genetic variation. Heliothis virescens, a major cotton pest, has been colonized in the laboratory many times, and a few laboratory colonies have been selected for Bacillus thuringiensis (Bt) resistance. We developed 350-bp double-digest restriction-site associated DNA-sequencing (ddRAD-seq) molecular markers to examine and compare changes in genetic variation associated with laboratory adaptation, artificial selection and inbreeding in this nonmodel insect species. We found that allelic and nucleotide diversity declined dramatically in laboratory-reared H. virescens as compared with field-collected populations. The declines were primarily a result of the loss of low frequency alleles present in field-collected H. virescens. A further, albeit modest decline in genetic diversity was observed in a Bt-selected population. The greatest decline was seen in H. virescens that were sib-mated for 10 generations, in which more than 80% of loci were fixed for a single allele. To determine which regions of the genome were resistant to fixation in our sib-mated line, we generated a dense intraspecific linkage map containing three PCR-based and 659 ddRAD-seq markers. Markers that retained polymorphism were observed in small clusters spread over multiple linkage groups, but this clustering was not statistically significant. Overall, we have confirmed and extended the general expectations for reduced genetic diversity in laboratory colonies, provided tools for further genomic analyses and produced highly homozygous genomic DNA for future whole genome sequencing of H. virescens.
Data from: Mapping migration in a songbird using high-resolution genetic markers
Neotropical migratory birds are declining across the Western Hemisphere, but conservation efforts have been hampered by the inability to assess where migrants are most limited – the breeding grounds, migratory stopover sites, or wintering areas. A major challenge has been the lack of an efficient, reliable, and broadly applicable method for measuring the strength of migratory connections between populations across the annual cycle. Here we show how high-resolution genetic markers can be used to identify genetically distinct groups of a migratory bird, the Wilson's warbler (Cardellina pusilla), at fine enough spatial scales to facilitate assessing regional drivers of demographic trends. By screening 1626 samples using 96 highly divergent single nucleotide polymorphisms (SNPs) selected from a large pool of candidates (~450,000), we identify novel region-specific migratory routes and timetables of migration along the Pacific Flyway. Our results illustrate that high-resolution genetic markers are more reliable, precise, and amenable to high throughput screening than previously described intrinsic marking techniques, making them broadly applicable to large-scale monitoring and conservation of migratory organisms.
Data from: Genetic mapping a meiotic driver that causes sex ratio distortion in the mosquito Aedes aegypti
An endogenous meiotic driver in the dengue and yellow fever vector mosquito Aedes aegypti can cause highly male-biased sex ratio distortion in crosses from suitable genetic backgrounds. We previously selected a strain that carries a strong meiotic drive gene (D) linked with the male-determining allele (M) on chromosome 1 in A. aegypti. Here we performed segregation analysis of the MD locus among backcross (BC1) progeny from a driver male and drive-sensitive females. Assessment of sex ratios among BC2 progeny showed ~5.2% recombination between the MD locus and the sex determination locus. Multipoint linkage mapping across this region revealed consistent marker orders and recombination frequencies with the existing reference linkage map and placed the MD locus within a 6.5 cM interval defined by the LF159 locus and microsatellite marker 446GAA, which should facilitate future positional cloning efforts.
Data from: Genetic mapping of MAPK-mediated complex traits across S. cerevisiae
Signaling pathways enable cells to sense and respond to their environment. Many cellular signaling strategies are conserved from fungi to humans, yet their activity and phenotypic consequences can vary extensively among individuals within a species. A systematic assessment of the impact of naturally occurring genetic variation on signaling pathways remains to be conducted. In S. cerevisiae, both response and resistance to stressors that activate signaling pathways differ between diverse isolates. Here, we present a quantitative trait locus (QTL) mapping approach that enables us to identify genetic variants underlying such phenotypic differences across the genetic and phenotypic diversity of S. cerevisiae. Using a Round-robin cross between twelve diverse strains, we identified QTL that influence phenotypes critically dependent on MAPK signaling cascades. Genetic variants under these QTL fall within MAPK signaling networks themselves as well as other interconnected signaling pathways. Finally, we demonstrate how the mapping results from multiple strain background can be leveraged to narrow the search space of causal genetic variants.
Data from: Mapping of genetic factors that elicit intermale aggressive behavior on mouse chromosome 15: intruder effects and the complex genetic basis
Despite high estimates of the heritability of aggressiveness, the genetic basis for individual differences in aggression remains unclear. Previously, we showed that the wild-derived mouse strain MSM/Ms (MSM) exhibits highly aggressive behaviors, and identified chromosome 15 (Chr 15) as the location of one of the genetic factors behind this escalated aggression by using a panel of consomic strains of MSM in a C57BL/6J (B6) background. To understand the genetic effect of Chr 15 derived from MSM in detail, this study examined the aggressive behavior of a Chr 15 consomic strain towards different types of opponent. Our results showed that both resident and intruder animals had to have the same MSM Chr 15 genotype in order for attack bites to increase and attack latency to be reduced, whereas there was an intruder effect of MSM Chr 15 on tail rattle behavior. To narrow down the region that contains the genetic loci involved in the aggression-eliciting effects on Chr 15, we established a panel of subconsomic strains of MSM Chr 15. Analysis of these strains suggested the existence of multiple genes that enhance and suppress aggressive behavior on Chr 15, and these loci interact in a complex way. Regression analysis successfully identified four genetic loci on Chr 15 that influence attack latency, and one genetic locus that partially elicits aggressive behaviors was narrowed down to a 4.1-Mbp region (from 68.40 Mb to 72.50 Mb) on Chr 15.
Genetic mapping of serum metabolome to chronic diseases among Han Chinese
Open the record for dataset details and reuse information.
Data from: Genetic mapping of novel loci affecting canine blood phenotypes
Since the publication of the dog genome and the construction of high-quality genome- wide SNP arrays, thousands of dogs have been genotyped for disease studies. For many of these dogs, additional clinical phenotypes are available, such as hematological and clinical chemistry results collected during routine veterinary care. Little is known about the genetic basis of variation in blood phenotypes, but this variation may play an important role in the etiology and progression of many diseases. From a cohort of dogs that had been previously genotyped on a semi-custom Illumina CanineHD array for various genome-wide association studies (GWAS) at Cornell University Hospital for Animals, we chose 353 clinically healthy, adult dogs for our analysis of clinical pathologic test results (14 hematological tests and 25 clinical chemistry tests). After correcting for age, body weight and sex, genetic associations were identified for amylase, segmented neutrophils, urea nitrogen, glucose, and mean corpuscular hemoglobin. Additionally, a strong genetic association (P = 8.1×10-13) was evident between a region of canine chromosome 13 (CFA13) and alanine aminotransferase (ALT), explaining 23% of the variation in ALT levels. This region of CFA13 encompasses the GPT gene that encodes the transferase. Dogs homozygous for the derived allele exhibit lower ALT activity, making increased ALT activity a less useful marker of hepatic injury in these individuals. Overall, these associations provide a roadmap for identifying causal variants that could improve interpretation of clinical blood tests and understanding of genetic risk factors associated with diseases such as canine diabetes and anemia, and demonstrate the utility of holistic phenotyping of dogs genotyped for disease mapping studies.
Data from: Fast and cost-effective genetic mapping in apple using next-generation sequencing
Next-generation DNA sequencing (NGS) produces vast amounts of DNA sequence data, but it is not specifically designed to generate data suitable for genetic mapping. Recently developed DNA library preparation methods for NGS have helped solve this problem, however, by combining the use of reduced representation libraries with DNA sample barcoding to generate genome-wide genotype data from a common set of genetic markers across a large number of samples. Here we use such a method, called genotyping-by-sequencing (GBS), to produce a data set for genetic mapping in an F1 population of apples (Malus x domestica) segregating for skin color. We show that GBS produces a relatively large, but extremely sparse, genotype matrix: over 270,000 SNPs were discovered, but most SNPs have too much missing data across samples to be useful for genetic mapping. After filtering for genotype quality and missing data, only 6% of the 85 million DNA sequence reads contributed to useful genotype calls. Despite this limitation, using existing software and a set of simple heuristics, we generated a final genotype matrix containing 3967 SNPs from 89 DNA samples from a single lane of Illumina HiSeq and used it to create a saturated genetic linkage map and to identify a known QTL underlying apple skin color. We therefore demonstrate that GBS is a cost effective method for generating genome-wide SNP data suitable for genetic mapping in a highly diverse and heterozygous agricultural species. We anticipate future improvements to the GBS analysis pipeline presented here that will enhance the utility of next-generation DNA sequence data for the purposes of genetic mapping across diverse species.
Data from: Genetic mapping of molar size relations identifies inhibitory locus for third molars in mice
Molar size in Mammals shows considerable disparity and exhibits variation similar to that predicted by the Inhibitory Cascade model. The importance of such developmental systems in favoring evolutionary trajectories is also underlined by the fact that this model can predict macroevolutionary patterns. Using backcross mice, we mapped QTL for molar sizes controlling for their sequential development. Genetic controls for upper and lower molars appear somewhat similar, and regions containing genes implied in dental defects drive this variation. We mapped three relationship QTLs (rQTL) modifying the control of the mesial molars on the focal third molar. These regions overlap Shh, Sostdc1 and Fst genes, which have pervasive roles in development and should be buffered against new variation. It has theoretically been shown that rQTL produces new variation channeled in the direction of adaptive changes. Our results provide evidence that evolutionary/disease patterns of tooth size variation could result from such a non-random generating process.
Data from: Adaptation via pleiotropy and linkage: association mapping reveals a complex genetic architecture within the stickleback Eda locus
Open the record for dataset details and reuse information.
Data from: Genetic mapping of novel loci affecting canine blood phenotypes
Open the record for dataset details and reuse information.
Data from: Fast and cost-effective genetic mapping in apple using next-generation sequencing
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
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.