Literature DB >> 34022808

A comparative analysis of the intrauterine transcriptome in fertile and subfertile mares using cytobrush sampling.

Stefan Bauersachs1, Heinrich Bollwein2, Katharina S Weber2, Karen Wagener2,3, Miguel Blanco4.   

Abstract

BACKGROUND: Subfertility is a major problem in modern horse breeding. Especially, mares without clinical signs of reproductive diseases, without known uterine pathogens and no evidence of inflammation but not becoming pregnant after several breeding attempts are challenging for veterinarians. To obtain new insights into the cause of these fertility problems and aiming at improving diagnosis of subfertile mares, a comparative analysis of the intrauterine transcriptome in subfertile and fertile mares was performed. Uterine cytobrush samples were collected during estrus from 57 mares without clinical signs of uterine diseases. RNA was extracted from the cytobrush samples and samples from 11 selected subfertile and 11 fertile mares were used for Illumina RNA-sequencing.
RESULTS: The cytobrush sampling was a suitable technique to isolate enough RNA of high quality for transcriptome analysis. Comparing subfertile and fertile mares, 114 differentially expressed genes (FDR = 10%) were identified. Metascape enrichment analysis revealed that genes with lower mRNA levels in subfertile mares were related to 'extracellular matrix (ECM)', 'ECM-receptor interaction', 'focal adhesion', 'immune response' and 'cytosolic calcium ion concentration', while DEGs with higher levels in subfertile mares were enriched for 'monocarboxyl acid transmembrane transport activity' and 'protein targeting'.
CONCLUSION: Our study revealed significant differences in the uterine transcriptome between fertile and subfertile mares and provides leads for potential uterine molecular biomarkers of subfertility in the mare.

Entities:  

Keywords:  Biomarker; Cytobrush; Mare; RNA-seq; Subfertility; Uterine transcriptome

Year:  2021        PMID: 34022808     DOI: 10.1186/s12864-021-07701-3

Source DB:  PubMed          Journal:  BMC Genomics        ISSN: 1471-2164            Impact factor:   3.969


  91 in total

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