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      Transcriptome Analysis of Ovarian Follicles Reveals Potential Pivotal Genes Associated With Increased and Decreased Rates of Chicken Egg Production

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          Abstract

          Egg production is an important economic trait in the commercial poultry industry. Ovarian follicle development plays a pivotal role in regulation of laying hen performance and reproductive physiology. However, the key genes and signaling pathways involved in the various-stages of laying hen follicular development remain poorly understood. In this study, transcriptomes of ovarian follicles at three developmental stages, the large white follicle (LWF), small yellow follicle (SYF), and large yellow follicle (LYF), were comparatively analyzed in hens with high (HR) and low (LR) egg-laying rates by RNA-sequencing. Eighteen cDNA libraries were constructed and a total of 236, 544, and 386 unigenes were significantly differentially expressed in the LWF, SYF, and LYF follicles of HR and LR hens, respectively. Among them, 47 co-transcribed differentially expressed genes (DEGs) in LWF and SYF, 68 co-expressed DEGs in SYF and LYF, and 54 co-expressed DEGs in LWF and LYF were mined. Thirteen co-expressed DEGs were found in LWF, SYF, and LYF follicles. Eighteen candidate genes, including P2RX1, CAB39L, BLK, CSMD3, GPR65, ADRB2, CSMD1, PLPP4, ATF3, PRLL, STMN3, RORB, PIK3R1, PERP1, ACSBG1, MRTO4, CDKN1A, and EDA2R were identified to be potentially related to egg production. Furthermore, Kyoto Encyclopedia of Genes and Genomes analysis indicated neuroactive ligand-receptor interaction, cell adhesion molecules, peroxisome proliferator-activated receptor pathway, and cAMP signaling pathway might elicit an important role in formation of egg-laying traits by influencing ovarian follicle development. This study represents the first transcriptome analysis of various-sized follicles between HR and LR hens. These results provide useful molecular evidence for elucidating the genetic mechanism underlying ovarian follicle development associated with egg production in chicken.

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype

            Rapid advances in next-generation sequencing technologies have dramatically changed our ability to perform genome-scale analyses. The human reference genome used for most genomic analyses represents only a small number of individuals, limiting its usefulness for genotyping. We designed a novel method, HISAT2, for representing and searching an expanded model of the human reference genome, in which a large catalogue of known genomic variants and haplotypes is incorporated into the data structure used for searching and alignment. This strategy for representing a population of genomes, along with a fast and memory-efficient search algorithm, enables more detailed and accurate variant analyses than previous methods. We demonstrate two initial applications of HISAT2: HLA typing, a critical need in human organ transplantation, and DNA fingerprinting, widely used in forensics. These applications are part of HISAT-genotype, with performance not only surpassing earlier computational methods, but matching or exceeding the accuracy of laboratory-based assays.
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              Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown

              High-throughput sequencing of messenger RNA (RNA-seq) has become the standard method for measuring and comparing the levels of gene expression in a wide variety of species and conditions. RNA-seq experiments generate very large, complex data sets that demand fast, accurate, and flexible software to reduce the raw read data to comprehensible results. HISAT, StringTie, and Ballgown are free, open-source software tools for comprehensive analysis of RNA-seq experiments. Together, they allow scientists to align reads to a genome, assemble transcripts including novel splice variants, compute the abundance of these transcripts in each sample, and compare experiments to identify differentially expressed genes and transcripts. This protocol describes all the steps necessary to process a large set of raw sequencing reads and create lists of gene transcripts, expression levels, and differentially expressed genes and transcripts. The protocol’s execution time depends on the computing resources, but typically takes under 45 minutes of computer time. Pertea et al. describe a protocol to analyze RNA-seq data using HISAT, StringTie, and Ballgown (the “new Tuxedo” package). The protocol can be used for assembly of transcripts, quantification of gene expression levels and differential expression analysis.
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                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                10 March 2021
                2021
                : 12
                : 622751
                Affiliations
                [1] 1Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Jilin Agricultural University , Changchun, China
                [2] 2Joint Laboratory of Modern Agricultural Technology International Cooperation, Ministry of Education, Jilin Agricultural University , Changchun, China
                [3] 3College of Agricultural & Environmental Sciences, University of Georgia , Athens, GA, United States
                Author notes

                Edited by: Meng-Hua Li, Institute of Zoology, Chinese Academy of Sciences (CAS), China

                Reviewed by: Li Kang, Shandong Agricultural University, China; Huadong Yin, Sichuan Agricultural University, China

                *Correspondence: Rifu Xu, poultryxu@ 123456jlau.edu.cn
                John Michael Gonzalez, johngonz@ 123456uga.edu

                These authors have contributed equally to this work

                This article was submitted to Livestock Genomics, a section of the journal Frontiers in Genetics

                Article
                10.3389/fgene.2021.622751
                7987945
                33777097
                bba0b70d-56fa-4e9e-99a7-04ca1159545c
                Copyright © 2021 Chen, Sun, Chimbaka, Qin, Xu, Liswaniso, Xu and Gonzalez.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 29 October 2020
                : 08 February 2021
                Page count
                Figures: 7, Tables: 3, Equations: 0, References: 55, Pages: 16, Words: 0
                Funding
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Award ID: No. 31902145
                Award ID: No.31672407
                Funded by: Agriculture Research System of China 10.13039/501100010203
                Award ID: No. CARS-41-Z03
                Categories
                Genetics
                Original Research

                Genetics
                chicken,egg production,differentially expressed gene,ovarian follicle,transcriptome
                Genetics
                chicken, egg production, differentially expressed gene, ovarian follicle, transcriptome

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