What makes a bad egg? Egg transcriptome reveals dysregulation of translational machinery and novel fertility genes important for fertilization.


Journal

BMC genomics
ISSN: 1471-2164
Titre abrégé: BMC Genomics
Pays: England
ID NLM: 100965258

Informations de publication

Date de publication:
15 Jul 2019
Historique:
received: 18 02 2019
accepted: 24 06 2019
entrez: 17 7 2019
pubmed: 17 7 2019
medline: 18 12 2019
Statut: epublish

Résumé

Egg quality can be defined as the egg ability to be fertilized and subsequently develop into a normal embryo. Previous research has shed light on factors that can influence egg quality. Large gaps however remain including a comprehensive view of what makes a bad egg. Initial development of the embryo relies on maternally-inherited molecules, such as transcripts, deposited in the egg during its formation. Bad egg quality is therefore susceptible to be associated with alteration or dysregulation of maternally-inherited transcripts. We performed transcriptome analysis on a large number (N = 136) of zebrafish egg clutches, each clutch being split to monitor developmental success and perform transcriptome analysis in parallel. We aimed at drawing a molecular portrait of the egg in order to characterize the relation between egg transcriptome and developmental success and to subsequently identify new candidate genes involved in fertility. We identified 66 transcript that were differentially abundant in eggs of contrasted phenotype (low or high developmental success). Statistical modeling using partial least squares regression and genetics algorithm demonstrated that gene signatures from transcriptomic data can be used to predict developmental success. The identity and function of differentially expressed genes indicate a major dysregulation of genes of the translational machinery in poor quality eggs. Two genes, otulina and slc29a1a, predominantly expressed in the ovary and dysregulated in poor quality eggs were further investigated using CRISPR/Cas9 mediated genome editing. Mutants of each gene revealed remarkable subfertility whereby the majority of their eggs were unfertilizable. The Wnt pathway appeared to be dysregulated in the otulina mutant-derived eggs. Here we show that egg transcriptome contains molecular signatures, which can be used to predict developmental success. Our results also indicate that poor egg quality in zebrafish is associated with a dysregulation of (i) the translational machinery genes and (ii) novel fertility genes, otulina and slc29a1a, playing an important role for fertilization. Together, our observations highlight the diversity of the possible causes of egg quality defects and reveal mechanisms of maternal origin behind the lack of fertilization and early embryonic failures that can occur under normal reproduction conditions.

Sections du résumé

BACKGROUND BACKGROUND
Egg quality can be defined as the egg ability to be fertilized and subsequently develop into a normal embryo. Previous research has shed light on factors that can influence egg quality. Large gaps however remain including a comprehensive view of what makes a bad egg. Initial development of the embryo relies on maternally-inherited molecules, such as transcripts, deposited in the egg during its formation. Bad egg quality is therefore susceptible to be associated with alteration or dysregulation of maternally-inherited transcripts. We performed transcriptome analysis on a large number (N = 136) of zebrafish egg clutches, each clutch being split to monitor developmental success and perform transcriptome analysis in parallel. We aimed at drawing a molecular portrait of the egg in order to characterize the relation between egg transcriptome and developmental success and to subsequently identify new candidate genes involved in fertility.
RESULTS RESULTS
We identified 66 transcript that were differentially abundant in eggs of contrasted phenotype (low or high developmental success). Statistical modeling using partial least squares regression and genetics algorithm demonstrated that gene signatures from transcriptomic data can be used to predict developmental success. The identity and function of differentially expressed genes indicate a major dysregulation of genes of the translational machinery in poor quality eggs. Two genes, otulina and slc29a1a, predominantly expressed in the ovary and dysregulated in poor quality eggs were further investigated using CRISPR/Cas9 mediated genome editing. Mutants of each gene revealed remarkable subfertility whereby the majority of their eggs were unfertilizable. The Wnt pathway appeared to be dysregulated in the otulina mutant-derived eggs.
CONCLUSIONS CONCLUSIONS
Here we show that egg transcriptome contains molecular signatures, which can be used to predict developmental success. Our results also indicate that poor egg quality in zebrafish is associated with a dysregulation of (i) the translational machinery genes and (ii) novel fertility genes, otulina and slc29a1a, playing an important role for fertilization. Together, our observations highlight the diversity of the possible causes of egg quality defects and reveal mechanisms of maternal origin behind the lack of fertilization and early embryonic failures that can occur under normal reproduction conditions.

Identifiants

pubmed: 31307377
doi: 10.1186/s12864-019-5930-8
pii: 10.1186/s12864-019-5930-8
pmc: PMC6631549
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

584

Subventions

Organisme : Agence Nationale de la Recherche
ID : ANR-13-BSV7-0015-Maternal Legacy

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Auteurs

Caroline T Cheung (CT)

INRA, Laboratoire de Physiologie et Génomique des poissons, Campus de Beaulieu, F-35042, Rennes cedex, France.

Thao-Vi Nguyen (TV)

INRA, Laboratoire de Physiologie et Génomique des poissons, Campus de Beaulieu, F-35042, Rennes cedex, France.

Aurélie Le Cam (A)

INRA, Laboratoire de Physiologie et Génomique des poissons, Campus de Beaulieu, F-35042, Rennes cedex, France.

Amélie Patinote (A)

INRA, Laboratoire de Physiologie et Génomique des poissons, Campus de Beaulieu, F-35042, Rennes cedex, France.

Laurent Journot (L)

Institut de Génomique Fonctionnelle, IGF, Université de Montpellier, CNRS, INSERM, Montpellier, France.
Montpellier GenomiX, BioCampus Montpellier, MGX, Université de Montpellier, CNRS, INSERM, Montpellier, France.

Christelle Reynes (C)

Institut de Génomique Fonctionnelle, IGF, Université de Montpellier, CNRS, INSERM, Montpellier, France.

Julien Bobe (J)

INRA, Laboratoire de Physiologie et Génomique des poissons, Campus de Beaulieu, F-35042, Rennes cedex, France. julien.bobe@inra.fr.

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Classifications MeSH