Literature DB >> 30539301

Full-length transcriptome and microRNA sequencing reveal the specific gene-regulation network of velvet antler in sika deer with extremely different velvet antler weight.

Pengfei Hu1, Tianjiao Wang1, Huamiao Liu1, Jiaping Xu1, Lei Wang1, Pei Zhao1, Xiumei Xing2.   

Abstract

Velvet antler displays the fastest and most robust tissue proliferation in the animal world, it is a model for a complete organ development/regeneration, and alternative medicine, tonic made from velvet antler, was beneficial for human. The weight of velvet antler had high biomedical and economic value, but the related regulation mechanisms controlling velvet antler weight remain unclear. In this study, extremely heavy and light velvet antler groups were selected from a sika deer population of 100 individuals with extreme velvet antler weight. A combination of full-length transcriptome sequencing and microRNA sequencing to the proliferation zone in the tip of velvet antler was applied. A total of 55306 transcripts and 1082 microRNAs were identified. Some highly expressed genes (COL1A1, COL1A2, COL3A1, FN1, and ATP6) and microRNAs (miR-21, let-7i, and miR-27b) were highly correlated with the physiological and growth characteristics of velvet antlers. Among the 334 differentially expressed genes, we found that most of the genes were located in the developmental process, especially animal organ development process. It is exciting to see that more blood vessels were found in the growing tip of heavy velvet antler through histological observation, and GO term of blood vessel development was also significant different between two groups. The combination analysis with mRNA and microRNA data in velvet antler showed a specific regulation network involved in the development of bone, mesenchyme, cartilage, and blood vessel, and helped us clearly find out the candidate 14 genes and 6 microRNAs, which could be used for selecting significant DNA markers of velvet antler weight.

Entities:  

Keywords:  Differential expression genes; MicroRNAs; Sika deer; Single-molecule real-time sequencing; Velvet antler weight

Mesh:

Substances:

Year:  2018        PMID: 30539301     DOI: 10.1007/s00438-018-1520-8

Source DB:  PubMed          Journal:  Mol Genet Genomics        ISSN: 1617-4623            Impact factor:   3.291


  11 in total

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2.  Development of novel EST microsatellite markers for genetic diversity analysis and correlation analysis of velvet antler growth characteristics in Sika deer.

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3.  Comprehensive transcriptome characterization of Grus japonensis using PacBio SMRT and Illumina sequencing.

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4.  Dynamic mRNA and miRNA expression of the head during early development in bighead carp (Hypophthalmichthys nobilis).

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Journal:  BMC Genomics       Date:  2022-03-01       Impact factor: 3.969

5.  Development of 16 novel EST-SSR markers for species identification and cross-genus amplification in sambar, sika, and red deer.

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Journal:  PLoS One       Date:  2022-04-01       Impact factor: 3.240

6.  Integrative Analyses of Antler Cartilage Transcriptome and Proteome of Gansu Red Deer (Cervus elaphus kansuensis) at Different Growth Stages.

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Journal:  Animals (Basel)       Date:  2022-04-06       Impact factor: 2.752

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

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Journal:  Animals (Basel)       Date:  2022-08-26       Impact factor: 3.231

8.  Peptide Biomarkers Discovery for Seven Species of Deer Antler Using LC-MS/MS and Label-Free Approach.

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9.  Comprehensive transcriptome analysis of sika deer antler using PacBio and Illumina sequencing.

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Journal:  Sci Rep       Date:  2022-09-28       Impact factor: 4.996

10.  Full-length transcriptome sequences of Agropyron cristatum facilitate the prediction of putative genes for thousand-grain weight in a wheat-A. cristatum translocation line.

Authors:  Shenghui Zhou; Jinpeng Zhang; Haiming Han; Jing Zhang; Huihui Ma; Zhi Zhang; Yuqing Lu; Weihua Liu; Xinming Yang; Xiuquan Li; Lihui Li
Journal:  BMC Genomics       Date:  2019-12-27       Impact factor: 3.969

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