Evidence map›Paper›PMID 33526009›Full record

ArticleBMC genomics2021

Identification and co-expression analysis of long noncoding RNAs and mRNAs involved in the deposition of intramuscular fat in Aohan fine-wool sheep.

Fuhui Han, Jing Li, Ranran Zhao, Lirong Liu, Lanlan Li, Qian Li, Jianning He, Nan Liu

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 20% 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Non-Coding RNAs in Regulating Fat Deposition in Farm Animals.Animals : an open access journal from MDPI · 2025
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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 1 country.

Fuhui HanCollege of Animal Science and Technology, Qingdao Agricultural University, Qingdao, 266109, China.
Jing LiQufu Animal Husbandry and Veterinary Technical Service Center, Qufu, 273100, China.
Ranran ZhaoCollege of Animal Science and Technology, Qingdao Agricultural University, Qingdao, 266109, China.
Lirong LiuChina Animal Health and Epidemiology Center, Qingdao, 266032, China.
Lanlan LiCollege of Animal Science and Technology, Qingdao Agricultural University, Qingdao, 266109, China.
Qian LiCollege of Animal Science and Technology, Qingdao Agricultural University, Qingdao, 266109, China.
Jianning HeCollege of Animal Science and Technology, Qingdao Agricultural University, Qingdao, 266109, China. hexingxing104@163.com.ORCID http://orcid.org/0000-0002-9657-9752
Nan LiuCollege of Animal Science and Technology, Qingdao Agricultural University, Qingdao, 266109, China. nanliu@sina.com.
Qingdao Agricultural University · CNChina Animal Health and Epidemiology Center · CNQingdao University · CN

Funding

A Project of Shandong Province Higher Educational Science and Technology Program J18KA136National Natural Science Foundation of China 31402047The Earmarked Fund for Modern China Wool & CashmereTechnology Research System CARS-39The Project of Shandong Province Agricultural Variety Program 2019LZGC012
6 · The paper itself

Abstract

backgroundIntramuscular fat (IMF) content has become one of the most important indicators for measuring meat quality, and levels of IMF are affected by various genes. Long non-coding RNAs (lncRNAs) are widely expressed non-coding RNAs that play an important regulatory role in a variety of biological processes; however, research on the lncRNAs involved in sheep IMF deposition is still in its infancy. Aohan fine-wool sheep (AFWS), one of China's most important meat-hair, dual-purpose sheep breed, provides a great model for studying the role of lncRNAs in the regulation of IMF deposition. We identified lncRNAs by RNA sequencing in Longissimus thoracis et lumborum (LTL) samples of sheep at two ages: 2 months (Mth-2) and 12 months (Mth-12).

resultsWe identified a total of 26,247 genes and 6935 novel lncRNAs in LTL samples of sheep. Among these, 199 mRNAs and 61 lncRNAs were differentially expressed. We then compared the structural characteristics of lncRNAs and mRNAs. We obtained target genes of differentially expressed lncRNAs (DELs) and performed enrichment analyses using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). We found that target mRNAs were enriched in metabolic processes and developmental pathways. One pathway was significantly enriched, namely tight junction. Based on the analysis of critical target genes, we obtained seven candidate lncRNAs that potentially regulated lipid deposition and constructed a lncRNA-mRNA co-expression network that included MSTRG.4051.3-FZD4, MSTRG.16157.3-ULK1, MSTRG.21053.3-PAQR3, MSTRG.19941.2-TPI1, MSTRG.12864.1-FHL1, MSTRG.2469.2-EXOC6 and MSTRG.21381.1-NCOA1. We speculated that these candidate lncRNAs might play a role by regulating the expression of target genes. We randomly selected five mRNAs and five lncRNAs to verify the accuracy of the sequencing data by qRT-PCR.

conclusionsOur study identified the differentially expressed mRNAs and lncRNAs during intramuscular lipid deposition in Aohan fine-wool sheep. The work may widen the knowledge about the annotation of the sheep genome and provide a working basis for investigating intramuscular fat deposition in sheep.

Indexed as

RNA, Long NoncodingAnimalsGene Expression ProfilingGene Regulatory NetworksRNA, MessengerSequence Analysis, RNASheepWoolRNA, Long NoncodingRNA, MessengerAohan fine-wool sheepCo-expression analysisIntramuscular fatLipid depositionLong non-coding RNAs

Identifiers

PMID33526009
PMCPMC7852088
OpenAlexW3113620453

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.