Evidence map›Paper›PMID 27379164›Full record

ArticleFrontiers in genetics2016

Deriving Gene Networks from SNP Associated with Triacylglycerol and Phospholipid Fatty Acid Fractions from Ribeyes of Angus Cattle.

Justin W Buchanan, James M Reecy, Dorian J Garrick, Qing Duan, Don C Beitz, James E Koltes, Mahdi Saatchi, Lars Koesterke, Raluca G Mateescu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 19% 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

7 citing papers in PubMed, 11 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

9 authors at 4 institutions in 1 country.

Justin W BuchananDepartment of Animal Science, University of California, Davis, Davis CA, USA.
James M ReecyDepartment of Animal Science, Iowa State University, Ames IA, USA.
Dorian J GarrickDepartment of Animal Science, Iowa State University, Ames IA, USA.
Qing DuanDepartment of Animal Science, Iowa State University, Ames IA, USA.
Don C BeitzDepartment of Animal Science, Iowa State University, Ames IA, USA.
James E KoltesDepartment of Animal Science, University of Arkansas, Fayetteville AR, USA.
Mahdi SaatchiDepartment of Animal Science, Iowa State University, Ames IA, USA.
Lars KoesterkeTexas Advanced Computing Center, University of Texas at Austin Austin, TX, USA.
Raluca G MateescuDepartment of Animal Sciences, University of Florida, Gainesville FL, USA.
Iowa State University · USUniversity of Arkansas at Fayetteville · USUniversity of California, Davis · USUniversity of Florida · US

Funding

HSRD VA CDP 12-186
6 · The paper itself

Abstract

The fatty acid profile of beef is a complex trait that can benefit from gene-interaction network analysis to understand relationships among loci that contribute to phenotypic variation. Phenotypic measures of fatty acid profile from triacylglycerol and phospholipid fractions of longissimus muscle, pedigree information, and Illumina 54 k bovine SNP genotypes were utilized to derive an annotated gene network associated with fatty acid composition in 1,833 Angus beef cattle. The Bayes-B statistical model was utilized to perform a genome wide association study to estimate associations between 54 k SNP genotypes and 39 individual fatty acid phenotypes within each fraction. Posterior means of the effects were estimated for each of the 54 k SNP and for the collective effects of all the SNP in every 1-Mb genomic window in terms of the proportion of genetic variance explained by the window. Windows that explained the largest proportions of genetic variance for individual lipids were found in the triacylglycerol fraction. There was almost no overlap in the genomic regions explaining variance between the triacylglycerol and phospholipid fractions. Partial correlations were used to identify correlated regions of the genome for the set of largest 1 Mb windows that explained up to 35% genetic variation in either fatty acid fraction. SNP were allocated to windows based on the bovine UMD3.1 assembly. Gene network clusters were generated utilizing a partial correlation and information theory algorithm. Results were used in conjunction with network scoring and visualization software to analyze correlated SNP across 39 fatty acid phenotypes to identify SNP of significance. Significant pathways implicated in fatty acid metabolism through GO term enrichment analysis included homeostasis of number of cells, homeostatic process, coenzyme/cofactor activity, and immunoglobulin. These results suggest different metabolic pathways regulate the development of different types of lipids found in bovine muscle tissues. Network analysis using partial correlations and annotation of significant SNPs can yield information about the genetic architecture of complex traits.

Indexed as

beeffatty acidsgene networksGWASphospholipidSNPtriacylglycerol

Identifiers

PMID27379164
PMCPMC4913692
OpenAlexW2472742223

What OpenQuestion holds

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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 OpenQuestion graph.