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Accession: PRJNA559681 ID: 559681

Single-cell RNA-seq (10x) of the goat ovarian granulosa cells samples from high fertility group (>three babys per birth) and low fertility group (< two babys per birth). (goat)

See Genome Information for Capra hircus
Single-cell RNA-seq (10x) of the goat ovarian granulosa cells samples from high fertility group (>three babys per birth) and low fertility group (< two babys per birth). The goal of this project is to explore the role of ovarian granulosa cells on the fertility of goat at single cell level. We would like to investigate the role of ovarian granulosa cells on the ovulation rate which indicates fertility. Therefore the ovarian granulosa cells from different population (hihg or low fertility groups animals) were analyzed. Overall design: We totally analyzed ~12,000 single cell transcriptome profile from goat ovarian granulosa cells from the two groups.
AccessionPRJNA559681; GEO: GSE135688
Data TypeTranscriptome or Gene expression
ScopeMultiisolate
OrganismCapra hircus[Taxonomy ID: 9925]
Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi; Mammalia; Eutheria; Laurasiatheria; Artiodactyla; Ruminantia; Pecora; Bovidae; Caprinae; Capra; Capra hircus
SubmissionRegistration date: 10-Aug-2019
B604, College of Life Sciences, Qingdao Agricultural University
RelevanceAgricultural
Project Data:
Resource NameNumber
of Links
Sequence data
SRA Experiments2
Other datasets
BioSample2
GEO DataSets1
GEO Data Details
ParameterValue
Data volume, Supplementary Mbytes2
SRA Data Details
ParameterValue
Data volume, Gbases408
Data volume, Tbytes0.16

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  • Single-cell RNA-seq (10x) of the goat ovarian granulosa cells samples from high ...
    Single-cell RNA-seq (10x) of the goat ovarian granulosa cells samples from high fertility group (>three babys per birth) and low fertility group (< two babys per birth).
    Single-cell RNA-seq (10x) of the goat ovarian granulosa cells samples from high fertility group (>three babys per birth) and low fertility group (< two babys per birth).
    BioProject

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