Transcriptomics

Dataset Information

0

A global view of the transcriptional profiling of adipose tissue in Chinese Qinchuan cattle using RNA sequencing


ABSTRACT: We constructed a transcriptional profiling of adipose tissue by RNA sequencing. Samples were collected from Chinese Qinchuan fetal bovine, heifers, bulls, and steers. We unambiguously detected a substantial number of differently expressed genes (DEGs), novel transcript units (NTUs), and splicing variants.The expressional profile of adipose tissue changed considerably from fetuses to adults, whereas smaller differences were detected between the adipose tissues of adult cows (ATACs). As an endocrine organ, DEGs related to inflammatory and immune process were significantly enriched in the ATACs. These genes may play some roles in different regulation mechanisms of adipose tissue in different genders. In addition, adipose tissue abundantly expressed genes concerning the functions of the mitochondria and the ribosomes. These support the adipose tissue as an extremely active tissue for energy and protein metabolism besides the storage of surplus fuel. In this study, about two-thirds of the NTUs did not have coding ability. Both the NTUs with and without coding ability were enriched from 300bp to 1,500bp. The main difference in the number of the two types of NTUs was also concentrated in this range. In total, about 18.2% of the genes in adipose tissues were alternatively spliced, and half of them were specially expressed in different patterns. Combined with previous studies, we concluded that alternatively splicing events occur variously in different tissues or different patterns of adipose tissue. Taken together, our study provided complete datasets involving the spatial and temporal transcriptome of adipose tissue which suggested the complexity of adipose tissue and our study will provide essential information for further research.

ORGANISM(S): Bos taurus

PROVIDER: GSE47653 | GEO | 2016/06/05

SECONDARY ACCESSION(S): PRJNA207067

REPOSITORIES: GEO

Similar Datasets

2009-12-23 | GSE19586 | GEO
| PRJNA552355 | ENA
2013-07-25 | E-GEOD-39618 | biostudies-arrayexpress
2017-06-15 | GSE100038 | GEO
2008-04-29 | GSE11295 | GEO
2013-07-25 | GSE39618 | GEO
2018-02-13 | GSE75063 | GEO
2008-04-29 | E-GEOD-11295 | biostudies-arrayexpress
| phs001048 | dbGaP
2015-11-30 | GSE74274 | GEO