Evidence map›Paper›PMID 32415111›Full record

ArticleScientific reports2020

High confidence copy number variants identified in Holstein dairy cattle from whole genome sequence and genotype array data.

Adrien M Butty, Tatiane C S Chud, Filippo Miglior, Flavio S Schenkel, Arun Kommadath, Kirill Krivushin, Jason R Grant, Irene M Häfliger, Cord Drögemüller, Angela Cánovas and 2 more

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
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

15 citing papers in PubMed.

  1. Article
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  7. Molecular Cytogenetics in Domestic Bovids: A Review.Animals : an open access journal from MDPI · 2023
    Review
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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

12 authors.

Adrien M ButtyCentre for Genetic Improvement of Livestock, University of Guelph, Guelph, ON, Canada.ORCID http://orcid.org/0000-0003-2320-8405
Tatiane C S ChudCentre for Genetic Improvement of Livestock, University of Guelph, Guelph, ON, Canada.
Filippo MigliorCentre for Genetic Improvement of Livestock, University of Guelph, Guelph, ON, Canada.
Flavio S SchenkelCentre for Genetic Improvement of Livestock, University of Guelph, Guelph, ON, Canada.ORCID http://orcid.org/0000-0001-8700-0633
Arun KommadathDepartment of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada.ORCID http://orcid.org/0000-0003-3587-6670
Kirill KrivushinDepartment of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada.
Jason R GrantDepartment of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada.
Irene M HäfligerInstitute of Genetics, Vetsuisse Faculty, University of Bern, Bern, BE, Switzerland.ORCID http://orcid.org/0000-0002-5648-963X
Cord DrögemüllerInstitute of Genetics, Vetsuisse Faculty, University of Bern, Bern, BE, Switzerland.ORCID http://orcid.org/0000-0001-9773-522X
Angela CánovasCentre for Genetic Improvement of Livestock, University of Guelph, Guelph, ON, Canada.ORCID http://orcid.org/0000-0002-0036-0757
Paul StothardDepartment of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada.
Christine F BaesCentre for Genetic Improvement of Livestock, University of Guelph, Guelph, ON, Canada. cbaes@uoguelph.ca.ORCID http://orcid.org/0000-0001-6614-8890

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple methods to detect copy number variants (CNV) relying on different types of data have been developed and CNV have been shown to have an impact on phenotypes of numerous traits of economic importance in cattle, such as reproduction and immunity. Further improvements in CNV detection are still needed in regard to the trade-off between high-true and low-false positive variant identification rates. Instead of improving single CNV detection methods, variants can be identified in silico with high confidence when multiple methods and datasets are combined. Here, CNV were identified from whole-genome sequences (WGS) and genotype array (GEN) data on 96 Holstein animals. After CNV detection, two sets of high confidence CNV regions (CNVR) were created that contained variants found in both WGS and GEN data following an animal-based (n = 52) and a population-based (n = 36) pipeline. Furthermore, the change in false positive CNV identification rates using different GEN marker densities was evaluated. The population-based approach characterized CNVR, which were more often shared among animals (average 40% more samples per CNVR) and were more often linked to putative functions (48 vs 56% of CNVR) than CNV identified with the animal-based approach. Moreover, false positive identification rates up to 22% were estimated on GEN information. Further research using larger datasets should use a population-wide approach to identify high confidence CNVR.

Indexed as

DNA Copy Number VariationsGenomeGenotypeWhole Genome SequencingAnimalsBreedingCattleChromosome MappingComputational BiologyGenetic MarkersGenomicsGenetic Markers

Identifiers

PMID32415111
PMCPMC7229195

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Registered trials

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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.