Exploring differentially expressed genes in the ovaries of uniparous and multiparous goats using the RNA-Seq (Quantification) method

Ling, Yinghui; Xiang, Hao; Li, Yunsheng; Liu, Ya; Zhang, Yunhai; Zhang, Zi-Juan; Ding, Jianping; Zhang, Xiaorong

doi:10.1016/j.gene.2014.08.008

Cited by 29 publications

(30 citation statements)

References 39 publications

(38 reference statements)

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“…Focal adhesion and actin cytoskeleton regulation pathways were also enriched in the ovary transcriptomes of other goat breeds 57, 58 . Focal adhesion plays essential roles in important biological processes, including cell motility, cell proliferation, cell differentiation, regulation of gene expression and cell survival 59 .…”

Section: Discussionmentioning

confidence: 97%

Identification and comparative analysis of the ovarian microRNAs of prolific and non-prolific goats during the follicular phase using high-throughput sequencing

Lü

2017

Sci Rep

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The kidding rate is one of the most important economic traits for goat production, but the genetic mechanism that is associated with ovulation rate is poorly understood. Recently, increasing evidence has suggested that microRNAs (miRNAs) influence ovarian biological processes. The present study provides the first comparison of the ovarian miRNAs of prolific Jintang black goats (JTGs) and non-prolific Tibetan goats (TBGs) during the follicular phase using RNA-Seq technology. We generated 11.19 million (M) and 11.34 M clean reads from the TBG and JTG libraries, respectively, from which a total of 389 known miRNAs were identified and 142 novel miRNAs were predicted. A total of 191 miRNAs were differentially expressed between the two breeds. Among the 10 most abundant miRNAs, miR-21-5p was defined as differentially expressed miRNA with a higher level in the JTG library than in the TBG library, but the other miRNAs were not different between the breeds. The predicted miRNA-targeted genes were further analyzed by Gene Ontology and KEGG pathway analyses. The results revealed that miR-21, miR-99a, miRNA-143, let-7f, miR-493 and miR-200b may affect follicular development. These findings will increase the current understanding of the role of ovarian miRNAs in the regulation of ovulation rate in goats.

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Section: Discussionmentioning

confidence: 97%

Identification and comparative analysis of the ovarian microRNAs of prolific and non-prolific goats during the follicular phase using high-throughput sequencing

Lü

2017

Sci Rep

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“…Among these signaling pathways, ECM-receptor interaction and olfactory transduction had significant difference in three of four comparison groups. The extracellular matrix (ECM) consists of a complex mixture of structural and functional macromolecules, and plays an important role in tissue and organ morphogenesis 63 . Specific interaction between cells and the ECM leads to the direct or indirect control of cellular activities, such as adhesion, migration, differentiation, proliferation, and apoptosis 64 .…”

Section: Discussionmentioning

confidence: 99%

Genome-wide differential mRNA expression profiles in follicles of two breeds and at two stages of estrus cycle of gilts

Chu

Zhou

et al. 2017

Sci Rep

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Estrus expression by gilts and sows is hereditable and important for heat detection. To better understand the molecular biological mechanisms of estrus expression in gilts, the mRNA expression profiles of follicular tissue from Large White gilts in diestrus (LD, n = 3) and estrus (LE, n = 3), and Chinese indigenous Mi gilts in diestrus (MD, n = 2) and estrus (ME, n = 3) were investigated using RNA sequencing. We detected 122,804-335,295 SNPs, 6,140-14,947 InDel and 12 types of AS events (39.57% TSS, 34.90% TTS) in 11 samples. A total of 2,838 differentially expressed genes (DEGs) were found in LD vs MD, LE vs ME, LE vs LD, or ME vs MD comparisons. Two DEGs (ACP5 and PIGS) were observed in all comparisons. Two new genes (ENSSSCG00000028235 and ENSSSCG00000021903) were exclusively expressed in Mi and Large White gilts, respectively. Bioinformatics analyses indicate that these DEGs are involved in single-organism process, catalytic activity, cell adhesion and enriched in ECM-receptor interaction, olfactory transduction, ovarian steroidogenesis, steroid biosynthesis and CAMs signaling pathways. These results of RNA-Seq have provided important information for screening the key functional genes or molecular markers of estrus expression in gilts.

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“…On average, a total of 15,719 and 15,738 genes were expressed in each TBG and JTG ovary, respectively. Previous transcriptome studies of ovaries used samples from multiple pooled ovary RNA for analysis (Ling et al., ; Miao et al., ; Wang et al., ; Zhao et al., ). Pooling methods would possibly mask individual ovary variability and gene expression heterogeneity.…”

Section: Discussionmentioning

confidence: 99%

“…To develop a broader view of the gene expression in the pre-ovulatory ovary and identify the key genes involved in the regulation of goat ovulation rate, for the first time, the present study compared the (Ling et al, 2014;Miao et al, 2016;Wang et al, 2016;Zhao et al, 2015). Pooling methods would possibly mask individual ovary variability and gene expression heterogeneity.…”

Section: Discussionmentioning

confidence: 99%

“…The RNA‐Seq approach produces millions of short cDNA reads that are mapped to a reference genome to obtain a genome‐scale transcriptional map, which consists of the transcriptional structure and the expression level for each gene (Mortazavi, Williams, McCue, Schaeffer, & Wold, ). Transcriptomes of ovaries have been initially compared in some goats (Ling, Xiang, Li, Liu, & Zhang, ; Miao, Luo, & Qin, ; Wang et al., ; Zhao et al., ) and pigs (Zhang et al., ) with different prolificacy using RNA‐Seq technology, and a large number of differentially expressed genes (DEGs) have been identified, although the results are not consistent. The Jintang black goat (JTG) is an excellent local Chinese breed that has a high kidding rate (248% on average) and superior meat performance.…”

Section: Introductionmentioning

confidence: 99%

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Comparative analysis of ovarian transcriptomes between prolific and non‐prolific goat breeds via high‐throughput sequencing

Zhou

et al. 2017

Reprod Domestic Animals

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To increase the current understanding of the gene expression in the pre-ovulatory ovary and identify the key genes involved in the regulation of ovulation rate, we compared the transcriptomes of ovaries from the prolific Jintang black goat (JTG) and the non-prolific Tibetan goat (TBG) during the follicular phase using the Illumina RNA-Seq method. Three ovarian libraries were constructed for each breed. On average, we obtained approximately 49.2 and 45.9 million reads for each individual ovary of TBGs and JTGs, respectively, of which 79.76% and 78.67% reads were covered in the genome database. A total of 407 differentially expressed genes (DEG) were detected between these two breeds, in which 316 were upregulated, and 91 were downregulated in the ovaries of JTGs versus TBGs. Based on the results of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, some of these DEGs potentially play an important role in controlling the development of ovarian follicles. SRD5A2, MSMB, STAR and 3BHSD, etc. were the most significantly differentially expressed between these two distinct breeds. In addition, each ovary expressed 1,066 versus 989 novel transcripts, and 171,829 versus 140,529 putative SNPs in TBGs versus JTBs, respectively. All data sets (GEO and dbSNP) were available via public repositories. Our study provides insight into the transcriptional regulation of the ovaries of two distinct breeds of goats that might serve as a key resource for understanding goat fecundity. SRD5A2, MSMB, STAR and 3BHSD may be associated with the high fecundity of JTGs.

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Exploring differentially expressed genes in the ovaries of uniparous and multiparous goats using the RNA-Seq (Quantification) method

Cited by 29 publications

References 39 publications

Identification and comparative analysis of the ovarian microRNAs of prolific and non-prolific goats during the follicular phase using high-throughput sequencing

Identification and comparative analysis of the ovarian microRNAs of prolific and non-prolific goats during the follicular phase using high-throughput sequencing

Genome-wide differential mRNA expression profiles in follicles of two breeds and at two stages of estrus cycle of gilts

Comparative analysis of ovarian transcriptomes between prolific and non‐prolific goat breeds via high‐throughput sequencing

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