Evidence map›Paper›PMID 30105049›Full record

ArticleFrontiers in genetics2018

Genome Wide Identification of Novel Long Non-coding RNAs and Their Potential Associations With Milk Proteins in Chinese Holstein Cows.

Wentao Cai, Cong Li, Shuli Liu, Chenghao Zhou, Hongwei Yin, Jiuzhou Song, Qin Zhang, Shengli Zhang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
1.4field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 36 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 2 countries.

Wentao CaiKey Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China.
Cong LiShaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A&F University, Yangling, China.
Shuli LiuKey Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China.
Chenghao ZhouKey Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China.
Hongwei YinKey Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China.
Jiuzhou SongDepartment of Animal and Avian Science, University of Maryland, College Park, MD, United States.
Qin ZhangKey Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China.
Shengli ZhangKey Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China.
China Agricultural University · CNNorthwest A&F University · CNUniversity of Maryland, College Park · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long non-coding RNAs (lncRNAs) have emerged as a novel class of regulatory molecules involved in various biological processes. However, their role in milk performance is unknown. Here, whole transcriptome RNA sequencing was used to generate the lncRNA transcriptome profiles in mammary tissue samples from 6 Chinese Holstein cows with 3 extremely high and 3 low milk protein percentage phenotypes. In this study, 6,450 lncRNA transcripts were identified through 5 stringent steps and filtration by coding potential. In total, 31 lncRNAs and 18 novel genes were identified to be differentially expressed in high milk protein samples (HP) relative to low milk protein samples (LP), respectively. Differentially expressed lncRNAs were selected to predict target genes through bioinformatics analysis, followed by the integration of differentially expressed mRNA data, gene function, gene ontology (GO) and pathway, genome wide association study (GWAS) and quantitative trait locus (QTL) information, as well as network analysis to further characterize potential interactions. Several lncRNAs were found (such as XLOC_059976) that could be used as candidate markers for milk protein content prediction. This is the first study to perform global expression profiling of lncRNAs and mRNAs related to milk protein traits in dairy cows. These results provide important information and insights into the synthesis of milk proteins, and potential targets for the future improvement of milk quality.

Indexed as

integrate studylong non-coding RNAmammary glandmilk proteinstranscriptome

Identifiers

PMID30105049
PMCPMC6077245
OpenAlexW2883632220

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.