共 50 条
Long noncoding RNA repertoire in chicken liver and adipose tissue
被引:62
|作者:
Muret, Kevin
[1
,2
]
Klopp, Christophe
[3
]
Wucher, Valentin
[4
]
Esquerre, Diane
[5
,6
]
Legeai, Fabrice
[7
,8
]
Lecerf, Frederic
[1
,2
]
Desert, Colette
[1
,2
]
Boutin, Morgane
[1
,2
]
Jehl, Frederic
[1
,2
]
Acloque, Herve
[6
]
Giuffra, Elisabetta
[9
]
Djebali, Sarah
[6
]
Foissac, Sylvain
[6
]
Derrien, Thomas
[4
]
Lagarrigue, Sandrine
[1
,2
]
机构:
[1] INRA, UMR PEGASE, F-35042 Rennes, France
[2] AGROCAMPUS OUEST, UMR PEGASE, F-35042 Rennes, France
[3] INRA, SIGENAE, F-31326 Castanet Tolosan, France
[4] Univ Rennes 1, CNRS, IGDR UMR6290, F-35000 Rennes, France
[5] INRA, Plateforme GENOTOUL, F-31326 Castanet Tolosan, France
[6] Univ Toulouse, INRA, ENVT, GenPhySE,INPT, F-31326 Castanet Tolosan, France
[7] INRA, UMR IGEPP, F-35042 Rennes, France
[8] AGROCAMPUS OUEST, UMR IGEPP, F-35042 Rennes, France
[9] Univ Paris Saclay, INRA, AgroParisTech, GABI, F-78350 Jouy En Josas, France
基金:
欧盟地平线“2020”;
关键词:
DIFFERENTIAL EXPRESSION;
LIPID-METABOLISM;
ANTISENSE RNA;
SEQUENCE;
ANNOTATION;
EVOLUTION;
REVEALS;
LANDSCAPE;
LNCRNA;
IDENTIFICATION;
D O I:
10.1186/s12711-016-0275-0
中图分类号:
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号:
0905 ;
摘要:
Background: Improving functional annotation of the chicken genome is a key challenge in bridging the gap between genotype and phenotype. Among all transcribed regions, long noncoding RNAs (lncRNAs) are a major component of the transcriptome and its regulation, and whole-transcriptome sequencing (RNA-Seq) has greatly improved their identification and characterization. We performed an extensive profiling of the lncRNA transcriptome in the chicken liver and adipose tissue by RNA-Seq. We focused on these two tissues because of their importance in various economical traits for which energy storage and mobilization play key roles and also because of their high cell homogeneity. To predict lncRNAs, we used a recently developed tool called FEELnc, which also classifies them with respect to their distance and strand orientation to the closest protein-coding genes. Moreover, to confidently identify the genes/transcripts expressed in each tissue (a complex task for weakly expressed molecules such as lncRNAs), we probed a particularly large number of biological replicates (16 per tissue) compared to common multi-tissue studies with a larger set of tissues but less sampling. Results: We predicted 2193 lncRNA genes, among which 1670 were robustly expressed across replicates in the liver and/or adipose tissue and which were classified into 1493 intergenic and 177 intragenic lncRNAs located between and within protein-coding genes, respectively. We observed similar structural features between chickens and mammals, with strong synteny conservation but without sequence conservation. As previously reported, we confirm that lncRNAs have a lower and more tissue-specific expression than mRNAs. Finally, we showed that adjacent lncRNA-mRNA genes in divergent orientation have a higher co-expression level when separated by less than 1 kb compared to more distant divergent pairs. Among these, we highlighted for the first time a novel lncRNA candidate involved in lipid metabolism, lnc_DHCR24, which is highly correlated with the DHCR24 gene that encodes a key enzyme of cholesterol biosynthesis. Conclusions: We provide a comprehensive lncRNA repertoire in the chicken liver and adipose tissue, which shows interesting patterns of co-expression between mRNAs and lncRNAs. It contributes to improving the structural and functional annotation of the chicken genome and provides a basis for further studies on energy storage and mobilization traits in the chicken.
引用
收藏
页码:1 / 17
页数:17
相关论文