Literature DB >> 30837362

Identification of the miRNA-mRNA regulatory network of antler growth centers.

Baojin Yao1, Mei Zhang, Meixin Liu, Bocheng Lu, Xiangyang Leng, Yaozhong Hu, Daqing Zhao, Y U Zhao.   

Abstract

Antler growth is a unique event compared to other growth and development processes in mammals. Antlers grow extremely fast during the rapid growth stage when growth rate peaks at 2 cm per day. Antler growth is driven by a specific endochondral ossification process in the growth center that is in the distal region of the antler tip. In this study, we used state-of-art RNA-seq technology to analyze the expression profiles of mRNAs and miRNAs during antler growth. Our results indicated that the expression levels of multiple genes involved in chondrogenesis and endochondral ossification, including Fn1, Sox9, Col2a1, Acan, Col9a1, Col11a1, Hapln1, Wwp2, Fgfr3, Comp, Sp7 and Ihh, were significantly increased at the rapid growth stage. Our results also indicated that there were multiple differentially expressed miRNAs interacting with differentially expressed genes with opposite expression patterns. Furthermore, some of the miRNAs, including miR-3072-5p, miR-1600, miR-34-5p, miR-6889-5p and miR-6729-5p, simultaneously interacted with and controlled multiple genes involved in the process of chondrogenesis and endochondral ossification. Therefore, we established a miRNA-mRNA regulatory network by identifying miRNAs and their target genes that were differentially expressed in the antler growth centers by comparing the rapid growth stage and the initial growth stage.

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Year:  2019        PMID: 30837362

Source DB:  PubMed          Journal:  J Biosci        ISSN: 0250-5991            Impact factor:   1.826


  27 in total

1.  Sampling technique to discriminate the different tissue layers of growing antler tips for gene discovery.

Authors:  Chunyi Li; Dawn E Clark; Eric A Lord; Jo-Anne L Stanton; James M Suttie
Journal:  Anat Rec       Date:  2002-10-01

2.  Analyzing real-time PCR data by the comparative C(T) method.

Authors:  Thomas D Schmittgen; Kenneth J Livak
Journal:  Nat Protoc       Date:  2008       Impact factor: 13.491

3.  DEGseq: an R package for identifying differentially expressed genes from RNA-seq data.

Authors:  Likun Wang; Zhixing Feng; Xi Wang; Xiaowo Wang; Xuegong Zhang
Journal:  Bioinformatics       Date:  2009-10-24       Impact factor: 6.937

4.  Identification of differentially expressed genes in the developing antler of red deer Cervus elaphus.

Authors:  Andrea Molnár; István Gyurján; Eva Korpos; Adrienn Borsy; Viktor Stéger; Zsuzsanna Buzás; Ibolya Kiss; Zoltán Zomborszky; Péter Papp; Ferenc Deák; László Orosz
Journal:  Mol Genet Genomics       Date:  2006-11-28       Impact factor: 3.291

5.  Most mammalian mRNAs are conserved targets of microRNAs.

Authors:  Robin C Friedman; Kyle Kai-How Farh; Christopher B Burge; David P Bartel
Journal:  Genome Res       Date:  2008-10-27       Impact factor: 9.043

Review 6.  Exploring the mechanisms regulating regeneration of deer antlers.

Authors:  J Price; S Allen
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2004-05-29       Impact factor: 6.237

7.  Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation.

Authors:  Cole Trapnell; Brian A Williams; Geo Pertea; Ali Mortazavi; Gordon Kwan; Marijke J van Baren; Steven L Salzberg; Barbara J Wold; Lior Pachter
Journal:  Nat Biotechnol       Date:  2010-05-02       Impact factor: 54.908

8.  Real-time quantification of microRNAs by stem-loop RT-PCR.

Authors:  Caifu Chen; Dana A Ridzon; Adam J Broomer; Zhaohui Zhou; Danny H Lee; Julie T Nguyen; Maura Barbisin; Nan Lan Xu; Vikram R Mahuvakar; Mark R Andersen; Kai Qin Lao; Kenneth J Livak; Karl J Guegler
Journal:  Nucleic Acids Res       Date:  2005-11-27       Impact factor: 16.971

9.  Human MicroRNA targets.

Authors:  Bino John; Anton J Enright; Alexei Aravin; Thomas Tuschl; Chris Sander; Debora S Marks
Journal:  PLoS Biol       Date:  2004-10-05       Impact factor: 8.029

10.  Full-length transcriptome assembly from RNA-Seq data without a reference genome.

Authors:  Manfred G Grabherr; Brian J Haas; Moran Yassour; Joshua Z Levin; Dawn A Thompson; Ido Amit; Xian Adiconis; Lin Fan; Raktima Raychowdhury; Qiandong Zeng; Zehua Chen; Evan Mauceli; Nir Hacohen; Andreas Gnirke; Nicholas Rhind; Federica di Palma; Bruce W Birren; Chad Nusbaum; Kerstin Lindblad-Toh; Nir Friedman; Aviv Regev
Journal:  Nat Biotechnol       Date:  2011-05-15       Impact factor: 54.908

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  2 in total

1.  Functional properties and antioxidant activity of gelatine and hydrolysate from deer antler base.

Authors:  Chang Liu; Yunshi Xia; Mei Hua; Zhiman Li; Lei Zhang; Shanshan Li; Ruize Gong; Songxin Liu; Zeshuai Wang; Yinshi Sun
Journal:  Food Sci Nutr       Date:  2020-05-10       Impact factor: 2.863

2.  Identification and Characterization of Alternative Splicing Variants and Positive Selection Genes Related to Distinct Growth Rates of Antlers Using Comparative Transcriptome Sequencing.

Authors:  Pengfei Hu; Zhen Wang; Jiping Li; Dongxu Wang; Yusu Wang; Quanmin Zhao; Chunyi Li
Journal:  Animals (Basel)       Date:  2022-08-26       Impact factor: 3.231

  2 in total

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