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.
5
datasets available to search
ShareScore release 0.9.0
Dataset results
5 results for “pearl millet genome”
Chromosome-level assembly of two pearl millet (Cenchrus americanus) genomes, functional annotation and transcriptomes
Open the record for dataset details and reuse information.
Data from: Genome scan reveals selection acting on genes linked to stress response in wild pearl millet
Uncovering genomic regions involved in adaption is a major goal in evolutionary biology. High-throughput sequencing now makes it possible to tackle this challenge in nonmodel species. Yet, despite the increasing number of methods targeted to specifically detect genomic footprints of selection, the complex demography of natural populations often causes high rates of false positive in gene discoveries. The aim of this study was to identify climate adaptations in wild pearl millet populations, Cenchrus americanus ssp. monodii. We focused on two climate gradients, one in Mali and one in Niger. We used a two-step strategy to limit false-positive outliers. First, we considered gradients as biological replicates and performed RNA sequencing of four populations at the extremities. We combined four methods—three based on differentiation among populations and one based on diversity patterns within populations—to identify outlier SNPs from a set of 87 218 high-quality SNPs. Among 11 155 contigs of pearl millet reference transcriptome, 540 exhibited selection signals as evidenced by at least one of the four methods. In a second step, we genotyped 762 samples in 11 additional populations distributed along the gradients using SNPs from the detected contigs and random SNPs as control. We further assessed selection on this large data set using a differentiation-based method and a method based on correlations with environmental variables based. Four contigs displayed consistent signatures between the four extreme and 11 additional populations, two of which were linked to abiotic and biotic stress responses.
Data from: Population genomics of pearl millet (Pennisetum glaucum (L.) R. Br.): comparative analysis of global accessions and Senegalese landraces
Background: Pearl millet is a staple food for people in arid and semi-arid regions of Africa and South Asia due to its high drought tolerance and nutritional qualities. A better understanding of the genomic diversity and population structure of pearl millet germplasm is needed to support germplasm conservation and genetic improvement of this crop. Here we characterized two pearl millet diversity panels, (i) a set of global accessions from Africa, Asia, and the America, and (ii) a collection of landraces from multiple agro-ecological zones in Senegal. Results: We identified 83,875 single nucleotide polymorphisms (SNPs) in 500 pearl millet accessions, comprised of 252 global accessions and 248 Senegalese landraces, using genotyping by sequencing (GBS) of PstI-MspI reduced representation libraries. We used these SNPs to characterize genomic diversity and population structure among the accessions. The Senegalese landraces had the highest levels of genetic diversity (π), while accessions from southern Africa and Asia showed lower diversity levels. Principal component analyses and ancestry estimation indicated clear population structure between the Senegalese landraces and the global accessions, and among countries in the global accessions. In contrast, little population structure was observed across in the Senegalese landraces collections. We ordered SNPs on the pearl millet genetic map and observed much faster linkage disequilibrium (LD) decay in Senegalese landraces compared to global accessions. A comparison of pearl millet GBS linkage map with the foxtail millet (Setaria italica) and sorghum (Sorghum bicolor) genomes indicated extensive regions of synteny, as well as some large-scale rearrangements in the pearl millet lineage. Conclusions: We identified 83,875 SNPs as a genomic resource for pearl millet improvement. The high genetic diversity in Senegal relative to other regions of Africa and Asia supports a West African origin of this crop, followed by wide diffusion. The rapid LD decay and lack of confounding population structure along agro-ecological zones in Senegalese pearl millet will facilitate future association mapping studies. Comparative population genomics will provide insights into panicoid crop evolution and support improvement of these climate-resilient crops.
Data from: Genome scan reveals selection acting on genes linked to stress response in wild pearl millet
Open the record for dataset details and reuse information.
Data from: Population genomics of pearl millet (Pennisetum glaucum (L.) R. Br.): comparative analysis of global accessions and Senegalese landraces
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.