Dataset Information

Transcriptome profiling of the goose (Anser cygnoides) ovaries identify laying and broodiness phenotypes.

ABSTRACT:

Background

The geese have strong broodiness and poor egg performance. These characteristics are the key issues that hinder the goose industry development. Yet little is known about the mechanisms responsible for follicle development due to lack of genomic resources. Hence, studies based on high-throughput sequencing technologies are needed to produce a comprehensive and integrated genomic resource and to better understand the biological mechanisms of goose follicle development.

Methodology/principal findings

In this study, we performed de novo transcriptome assembly and gene expression analysis using short-read sequencing technology (Illumina). We obtained 67,315,996 short reads of 100 bp, which were assembled into 130,514 unique sequences by Trinity strategy (mean size?=?753 bp). Based on BLAST results with known proteins, these analyses identified 52,642 sequences with a cut-off E-value above 10(-5). Assembled sequences were annotated with gene descriptions, gene ontology and clusters of orthologous group terms. In addition, we investigated the transcription changes during the goose laying/broodiness period using a tag-based digital gene expression (DGE) system. We obtained a sequencing depth of over 4.2 million tags per sample and identified a large number of genes associated with follicle development and reproductive biology including cholesterol side-chain cleavage enzyme gene and dopamine beta-hydroxylas gene. We confirm the altered expression levels of the two genes using quantitative real-time PCR (qRT-PCR).

Conclusions/significance

The obtained goose transcriptome and DGE profiling data provide comprehensive gene expression information at the transcriptional level that could promote better understanding of the molecular mechanisms underlying follicle development and productivity.

SUBMITTER: Xu Q

PROVIDER: S-EPMC3566205 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Publications

Transcriptome profiling of the goose (Anser cygnoides) ovaries identify laying and broodiness phenotypes.

Xu Qi Q Zhao WenMing W Chen Yang Y Tong YiYu Y Rong GuangHui G Huang ZhengYang Z Zhang Yang Y Chang GuoBing G Wu XinSheng X Chen GuoHong G

PloS one 20130206 2

<h4>Background</h4>The geese have strong broodiness and poor egg performance. These characteristics are the key issues that hinder the goose industry development. Yet little is known about the mechanisms responsible for follicle development due to lack of genomic resources. Hence, studies based on high-throughput sequencing technologies are needed to produce a comprehensive and integrated genomic resource and to better understand the biological mechanisms of goose follicle development.<h4>Method ...[more]

PMID: 23405160

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Project description:BackgroundRecent functional studies have demonstrated that the microRNAs (miRNAs) play critical roles in ovarian gonadal development, steroidogenesis, apoptosis, and ovulation in mammals. However, little is known about the involvement of miRNAs in the ovarian function of fowl. The goose (Anas cygnoides) is a commercially important food that is cultivated widely in China but the goose industry has been hampered by high broodiness and poor egg laying performance, which are influenced by ovarian function.Methodology/principal findingsIn this study, the miRNA transcriptomes of ovaries from laying and broody geese were profiled using Solexa deep sequencing and bioinformatics was used to determine differential expression of the miRNAs. As a result, 11,350,396 and 9,890,887 clean reads were obtained in laying and broodiness goose, respectively, and 1,328 conserved known miRNAs and 22 novel potential miRNA candidates were identified. A total of 353 conserved microRNAs were significantly differentially expressed between laying and broody ovaries. Compared with miRNA expression in the laying ovary, 127 miRNAs were up-regulated and 126 miRNAs were down-regulated in the ovary of broody birds. A subset of the differentially expressed miRNAs (G-miR-320, G-miR-202, G-miR-146, and G-miR-143*) were validated using real-time quantitative PCR. In addition, 130,458 annotated mRNA transcripts were identified as putative target genes. Gene ontology annotation and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis suggested that the differentially expressed miRNAs are involved in ovarian function, including hormone secretion, reproduction processes and so on.ConclusionsThe present study provides the first global miRNA transcriptome data in A. cygnoides and identifies novel and known miRNAs that are differentially expressed between the ovaries of laying and broody geese. These findings contribute to our understanding of the functional involvement of miRNAs in the broody period of goose.

Project description:BackgroundThe number of myofiber is determined during the embryonic stage and does not increase during the postnatal period for birds, including goose. Thus, muscle production of adult goose is pre-determined during embryogenesis. Previous studies show N6-methyladenosine (m6A) is an important regulator for skeletal muscle development of birds and miRNAs play as a co-regulator for the skeletal muscle development in birds. Herein, we sequenced m6A and miRNA transcriptomes to investigate the profiles of m6A and their potential mechanism of regulating breast muscle development in Dingan Goose.ResultsWe selected embryonic 21th day (E21) and embryonic 30th day (E30) to investigate the roles of transcriptome-wide m6A modification combining with mRNAs and miRNAs in goose breast muscle development. In this study, m6A peaks were mainly enriched in coding sequence (CDS) and start codon and397 genes were identified as differentially methylated genes (DMGs). GO and KEGG analysis showed that DMGs were highly related to cellular and metabolic process and that most DMGs were enriched in muscle-related pathways including Wnt signaling pathway, mTOR signaling and FoxO signaling pathway. Interestingly, a negative correlation between m6A methylation level and mRNA abundance was found through the analysis of m6A-RNA and RNA-seq data. Besides, we found 26 muscle-related genes in 397 DMGs. We also detected 228 differentially expressed miRNAs (DEMs), and further found 329 genes shared by the target genes of DEMs and DMGs (m6A-miRNA-genes), suggesting a tightly relationship between DEMs and DMGs. Among the m6A-miRNA-genes, we found 10 genes are related to breast muscle development. We further picked out an m6A-miRNA-gene, PDK3, from the 10 genes to visualize it and the result showed differentially methylated peaks on the mRNA transcript consistent with our m6A-seq results.ConclusionGO and KEGG of DMGs between E21 and E30 showed most DMGs were muscle-related. In total, 228 DEMs were found, and the majority of DMGs were overlapped with the targets of DEGs. The differentially methylated peaks along with an m6A-miRNA-gene, PDK3, showed the similar results with m6A-seq results. Taken together, the results presented here provide a reference for further investigation of embryonic skeletal muscle development mechanism in goose.

Dataset Information

Transcriptome profiling of the goose (Anser cygnoides) ovaries identify laying and broodiness phenotypes.

Background

Methodology/principal findings

Conclusions/significance

Publications

Transcriptome profiling of the goose (Anser cygnoides) ovaries identify laying and broodiness phenotypes.

Similar Datasets

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