Evidence map›Paper›PMID 40830176›Full record

ArticleScientific reports2025

Detection and functional assessment of structural variants using whole-genome re-sequencing data in Nellore cattle.

Natalia A Marín-Garzón, Lucio F M Mota, Giovana Vargas, Leonardo M Arikawa, Larissa F S Fonseca, Gerardo A Fernandes Júnior, Roberto Carvalheiro, Lucia G Albuquerque

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

2 citing papers in PubMed.

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4 · The record

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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.

Natalia A Marín-GarzónSchool of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castelane, Jaboticabal, 14884-900, SP, Brazil.
Lucio F M MotaSchool of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castelane, Jaboticabal, 14884-900, SP, Brazil. flaviommota.zoo@gmail.com.
Giovana VargasSchool of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castelane, Jaboticabal, 14884-900, SP, Brazil.
Leonardo M ArikawaSchool of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castelane, Jaboticabal, 14884-900, SP, Brazil.
Larissa F S FonsecaSchool of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castelane, Jaboticabal, 14884-900, SP, Brazil.
Gerardo A Fernandes JúniorSchool of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castelane, Jaboticabal, 14884-900, SP, Brazil.
Roberto CarvalheiroCSIRO Agriculture and Food, Hobart, TAS, 7000, Australia.
Lucia G AlbuquerqueSchool of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castelane, Jaboticabal, 14884-900, SP, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ongoing advances in genome sequencing technologies have enabled the identification of numerous structural variants (SVs) in livestock genomes, which are the main determinants of complex traits due to their impact on gene expression. Thus, this study aimed to detect structural variants using whole genome re-sequencing (WGS) data and identify positional candidate genes and quantitative trait loci (QTL) overlapping the most frequent SV regions in Nellore cattle. The WGS from 151 representative Nellore bulls were analyzed to conduct genome-wide structural variation calling and to identify common SV regions. Gene and QTL information surrounding the most frequent SV regions was identified using the Ensembl Genes and Cattle QTL database. The identified genes were functionally classified for biological mechanisms and pathways (Gene Ontology - GO) using the panther database. A total of 215,031 SVs were identified, with most of them being copy number variants (CNV) (183,032 deletions and 14,013 duplications) and 17,986 inversions (INV). These SVs cover, on average, 4.81% of the autosomal genome. Furthermore, we found 3,752 non-redundant SV regions that are frequent in at least 5% of the bulls. These SV regions mainly correspond to CNV regions (97%) and inversion regions (3%). In total, all SV regions cover 13.13% of the total autosomal genome, with 11.4% attributed to CNV regions and 1.7% to inversion regions. Moreover, we found that 532 SV regions were common in more than 50% of the bulls evaluated and overlapped 130 QTL previously associated with economically important traits related to exterior, health, meat and carcass, milk, production, and reproduction. A total of 1,164 positional candidate genes were identified, with 204 SVRs overlapping these genes. These genes are significantly overrepresented in GO terms related to biological processes (BP), molecular functions (MF), and biochemical pathways, playing an essential role in environmental adaptation mechanisms and feed efficiency indicator traits. Our results suggest that genes surrounding SV regions play key biological functions essential to thermotolerance, immunity, metabolism, tissue integrity, and environmental adaptation in tropical regions.

Indexed as

Genomic Structural VariationWhole Genome SequencingAnimalsCattleDNA Copy Number VariationsGenomeMaleQuantitative Trait LociCopy number variationGains and losses of DNA fragmentsMobile elementsNext-generation sequencingZebu cattle

Identifiers

PMID40830176
PMCPMC12365053

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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.