Novel classifier orthologs of bovine and human oocytes matured in different melatonin environments.

Classifier orthologs Cross-species RNA-Seq meta-analysis Melatonin Oocytes

Journal

Theriogenology
ISSN: 1879-3231
Titre abrégé: Theriogenology
Pays: United States
ID NLM: 0421510

Informations de publication

Date de publication:
15 Oct 2020
Historique:
received: 22 01 2020
revised: 25 06 2020
accepted: 25 06 2020
pubmed: 19 7 2020
medline: 22 6 2021
entrez: 19 7 2020
Statut: ppublish

Résumé

It has been demonstrated that melatonin influences the developmental competence of both in vivo and in vitro matured oocytes. It modulates oocyte-specific gene expression patterns among mammalian species. Due to differences among study systems, the identification of the classifier orthologs-the homologous genes related among mammals that could universally categorize oocytes matured in environments with varied melatonin levels is still limitedly studied. To gain insight into such orthologs, cross-species transcription profiling meta-analysis of in vitro matured bovine oocytes and in vivo matured human oocytes in low and high melatonin environments was demonstrated in the current study. RNA-Seq data of bovine and human oocytes were retrieved from the Sequence Read Archive database and pre-processed. The used datasets of bovine oocytes obtained from culturing in the absence of melatonin and human oocytes from old patients were regarded as oocytes in the low melatonin environment (Low). Datasets from bovine oocytes cultured in 10-9 M melatonin and human oocytes from young patients were considered as oocytes in the high melatonin environment (High). Candidate orthologs differentially expressed between Low and High melatonin environments were selected by a linear model, and were further verified by Zero-inflated regression analysis. Support Vector Machine (SVM) was applied to determine the potentials of the verified orthologs as classifiers of melatonin environments. According to the acquired results, linear model analysis identified 284 candidate orthologs differentially expressed between Low and High melatonin environments. Among them, only 15 candidate orthologs were verified by Zero-inflated regression analysis (FDR ≤ 0.05). Utilization of the verified orthologs as classifiers in SVM resulted in the precise classification of oocyte learning datasets according to their melatonin environments (Misclassification rates < 0.18, area under curves > 0.9). In conclusion, the cross-species RNA-Seq meta-analysis to identify novel classifier orthologs of matured oocytes under different melatonin environments was successfully demonstrated in this study-delivering candidate orthologs for future studies at biological levels. Such verified orthologs might provide valuable evidence about melatonin sufficiency in target oocytes-by which, the decision on melatonin supplementation could be implied.

Identifiants

pubmed: 32682179
pii: S0093-691X(20)30380-0
doi: 10.1016/j.theriogenology.2020.06.029
pii:
doi:

Substances chimiques

Melatonin JL5DK93RCL

Types de publication

Journal Article Meta-Analysis

Langues

eng

Sous-ensembles de citation

IM

Pagination

82-89

Informations de copyright

Copyright © 2020 Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest We certify that there is no conflict of interest with any financial organization regarding the material and methods discussed in the manuscript.

Auteurs

Thanida Sananmuang (T)

Rajamangala University of Technology Tawan-OK, Faculty of Veterinary Medicine, Chonburi, Thailand.

Denis Puthier (D)

Aix-Marseille Université, INSERM UMR 1090, TAGC, Marseille, France.

Catherine Nguyen (C)

Aix-Marseille Université, INSERM UMR 1090, TAGC, Marseille, France.

Kaj Chokeshaiusaha (K)

Rajamangala University of Technology Tawan-OK, Faculty of Veterinary Medicine, Chonburi, Thailand. Electronic address: kaj.chk@gmail.com.

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