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Identification and characterization of long intergenic noncoding RNAs in bovine mammary glands

Overview of attention for article published in BMC Genomics, June 2017
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Title
Identification and characterization of long intergenic noncoding RNAs in bovine mammary glands
Published in
BMC Genomics, June 2017
DOI 10.1186/s12864-017-3858-4
Pubmed ID
Authors

Chao Tong, Qiaoling Chen, Lili Zhao, Junfei Ma, Eveline M. Ibeagha-Awemu, Xin Zhao

Abstract

Mammary glands of dairy cattle produce milk for the newborn offspring and for human consumption. Long intergenic noncoding RNAs (lincRNAs) play various functions in eukaryotic cells. However, types and roles of lincRNAs in bovine mammary glands are still poorly understood. Using computational methods, 886 unknown intergenic transcripts (UITs) were identified from five RNA-seq datasets from bovine mammary glands. Their non-coding potentials were predicted by using the combination of four software programs (CPAT, CNCI, CPC and hmmscan), with 184 lincRNAs identified. By comparison to the NONCODE2016 database and a domestic-animal long noncoding RNA database (ALDB), 112 novel lincRNAs were revealed in bovine mammary glands. Many lincRNAs were found to be located in quantitative trait loci (QTL). In particular, 36 lincRNAs were found in 172 milk related QTLs, whereas one lincRNA was within clinical mastitis QTL region. In addition, targeted genes for 10 lincRNAs with the highest fragments per kilobase of transcript per million fragments mapped (FPKM) were predicted by LncTar for forecasting potential biological functions of these lincRNAs. Further analyses indicate involvement of lincRNAs in several biological functions and different pathways. Our study has provided a panoramic view of lincRNAs in bovine mammary glands and suggested their involvement in many biological functions including susceptibility to clinical mastitis as well as milk quality and production. This integrative annotation of mammary gland lincRNAs broadens and deepens our understanding of bovine mammary gland biology.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 22%
Student > Master 6 17%
Student > Ph. D. Student 4 11%
Student > Doctoral Student 2 6%
Student > Bachelor 2 6%
Other 2 6%
Unknown 12 33%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 25%
Biochemistry, Genetics and Molecular Biology 6 17%
Veterinary Science and Veterinary Medicine 3 8%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Computer Science 1 3%
Other 2 6%
Unknown 14 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 June 2017.
All research outputs
#20,428,633
of 22,982,639 outputs
Outputs from BMC Genomics
#9,316
of 10,687 outputs
Outputs of similar age
#275,646
of 316,590 outputs
Outputs of similar age from BMC Genomics
#177
of 205 outputs
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