Evidence map›Paper›PMID 24673797›Full record

ArticleBMC genomics2014

Deleted copy number variation of Hanwoo and Holstein using next generation sequencing at the population level.

Dong-Hyun Shin, Hyun-Jeong Lee, Seoae Cho, Hyeon Jeong Kim, Jae Yeon Hwang, Chang-Kyu Lee, Jinyoung Jeong, Duhak Yoon, Heebal Kim

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
3.3field-weighted citation impact, top 8% 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

30 citing papers in PubMed, 55 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 3 institutions in 1 country.

Dong-Hyun Shin
Hyun-Jeong Lee
Seoae Cho
Hyeon Jeong Kim
Jae Yeon Hwang
Chang-Kyu Lee
Jinyoung Jeong
Duhak YoonDepartment of Agricultural Biotechnology, Animal Biotechnology Major, and Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul 151-921, Korea. dhyoon@knu.ac.kr.
Heebal Kim
Seoul National University · KRRural Development Administration · KRKyungpook National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCopy number variation (CNV), a source of genetic diversity in mammals, has been shown to underlie biological functions related to production traits. Notwithstanding, there have been few studies conducted on CNVs using next generation sequencing at the population level.

resultsIllumina NGS data was obtained for ten Holsteins, a dairy cattle, and 22 Hanwoo, a beef cattle. The sequence data for each of the 32 animals varied from 13.58-fold to almost 20-fold coverage. We detected a total of 6,811 deleted CNVs across the analyzed individuals (average length = 2732.2 bp) corresponding to 0.74% of the cattle genome (18.6 Mbp of variable sequence). By examining the overlap between CNV deletion regions and genes, we selected 30 genes with the highest deletion scores. These genes were found to be related to the nervous system, more specifically with nervous transmission, neuron motion, and neurogenesis. We regarded these genes as having been effected by the domestication process. Further analysis of the CNV genotyping information revealed 94 putative selected CNVs and 954 breed-specific CNVs.

conclusionsThis study provides useful information for assessing the impact of CNVs on cattle traits using NGS at the population level.

Indexed as

DNA Copy Number VariationsGenomeAnimalsCattleChromosome MappingGene DeletionGenotypeHigh-Throughput Nucleotide SequencingMetagenomicsQuantitative Trait LociSequence Analysis, DNA

Identifiers

PMID24673797
PMCPMC4051123
OpenAlexW2015286367

What OpenQuestion 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 OpenQuestion graph.