Evidence map›Paper›PMID 34705124›Full record

ArticleTropical animal health and production2021

Identification and in silico characterization of structural and functional impacts of genetic variants in milk protein genes in the Zebu breeds Guzerat and Gyr.

Carolina Guimarães Ramos Matosinho, Izinara Cruz Rosse, Pablo Augusto Souza Fonseca, Francislon Silva de Oliveira, Fausto Gonçalves Dos Santos, Flávio Marcos Gomes Araújo, Anna Christina de Matos Salim, Beatriz Cordenonsi Lopes, Wagner Antonio Arbex, Marco Antônio Machado and 7 more

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Article in Tropical animal health and production, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 27% 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

3 citing papers in PubMed, 5 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

17 authors at 5 institutions in 2 countries.

Carolina Guimarães Ramos MatosinhoPrograma de Pós-Graduação Em GenéticaDepartamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, 31901-207, Brazil.
Izinara Cruz RossePrograma de Pós-Graduação Em GenéticaDepartamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, 31901-207, Brazil.
Pablo Augusto Souza FonsecaPrograma de Pós-Graduação Em GenéticaDepartamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, 31901-207, Brazil. pfonseca@uoguelph.ca.
Francislon Silva de OliveiraPrograma de Pós-Graduação Em GenéticaDepartamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, 31901-207, Brazil.
Fausto Gonçalves Dos SantosGrupo de Genômica E Biologia Computacional, Centro de Pesquisas René Rachou - Fiocruz Minas, Belo Horizonte, MG, 30190-00, Brazil.
Flávio Marcos Gomes AraújoGrupo de Genômica E Biologia Computacional, Centro de Pesquisas René Rachou - Fiocruz Minas, Belo Horizonte, MG, 30190-00, Brazil.
Anna Christina de Matos SalimGrupo de Genômica E Biologia Computacional, Centro de Pesquisas René Rachou - Fiocruz Minas, Belo Horizonte, MG, 30190-00, Brazil.
Beatriz Cordenonsi LopesEPAMIG, Belo Horizonte, MG, 31170-495, Brazil.
Wagner Antonio ArbexEmbrapa Gado de Leite, Juiz de Fora, MG, 36038-330, Brazil.
Marco Antônio MachadoEmbrapa Gado de Leite, Juiz de Fora, MG, 36038-330, Brazil.
Maria Gabriela Campolina Diniz PeixotoEmbrapa Gado de Leite, Juiz de Fora, MG, 36038-330, Brazil.
Rui da Silva VernequeEPAMIG, Belo Horizonte, MG, 31170-495, Brazil.
Marta Fonseca MartinsEmbrapa Gado de Leite, Juiz de Fora, MG, 36038-330, Brazil.
Marcos Vinicius Gualberto Barbosa da SilvaEmbrapa Gado de Leite, Juiz de Fora, MG, 36038-330, Brazil.
Guilherme OliveiraGrupo de Genômica E Biologia Computacional, Centro de Pesquisas René Rachou - Fiocruz Minas, Belo Horizonte, MG, 30190-00, Brazil.
Douglas Eduardo Valente PiresSchool of Computing and Information Systems, University of Melbourne, Parkville, VIC, 3052, Australia.
Maria Raquel Santos CarvalhoPrograma de Pós-Graduação Em GenéticaDepartamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, 31901-207, Brazil.
Universidade Federal de Minas Gerais · BREmpresa de Pesquisa Agropecuária de Minas Gerais · BRUniversidade Federal de Ouro Preto · BRUniversity of Melbourne · AUVale Technological Institute · BR

Funding

Biotechnology and Biological Sciences Research Council BB/P027849/1Conselho Nacional de Desenvolvimento Científico e Tecnológico 307479/2016-1Conselho Nacional de Desenvolvimento Científico e Tecnológico 312068/2015-8Conselho Nacional de Desenvolvimento Científico e Tecnológico 312405/2018-9Fundação de Amparo à Pesquisa do Estado de Minas Gerais APQ-01377-17Fundação de Amparo à Pesquisa do Estado de Minas Gerais CBB-1181/0Fundação de Amparo à Pesquisa do Estado de Minas Gerais (BR) APQ-01093-15Fundação de Amparo à Pesquisa do Estado de Minas Gerais (BR) APQ-02003-15Fundação de Amparo à Pesquisa do Estado do Rio de Janeir 12.093/10Fundação de Amparo à Pesquisa do Estado do Rio de Janeir 17003/2011Research Councils UK BB/P027849/1
6 · The paper itself

Abstract

Whole genome sequencing of bovine breeds has allowed identification of genetic variants in milk protein genes. However, functional repercussion of such variants at a molecular level has seldom been investigated. Here, the results of a multistep Bioinformatic analysis for functional characterization of recently identified genetic variants in Brazilian Gyr and Guzerat breeds is described, including predicted effects on the following: (i) evolutionary conserved nucleotide positions/regions; (ii) protein function, stability, and interactions; (iii) splicing, branching, and miRNA binding sites; (iv) promoters and transcription factor binding sites; and (v) collocation with QTL. Seventy-one genetic variants were identified in the caseins (CSN1S1, CSN2, CSN1S2, and CSN3), LALBA, LGB, and LTF genes. Eleven potentially regulatory variants and two missense mutations were identified. LALBA Ile60Val was predicted to affect protein stability and flexibility, by reducing the number the disulfide bonds established. LTF Thr546Asn is predicted to generate steric clashes, which could mildly affect iron coordination. In addition, LALBA Ile60Val and LTF Thr546Asn affect exonic splicing enhancers and silencers. Consequently, both mutations have the potential of affecting immune response at individual level, not only in the mammary gland. Although laborious, this multistep procedure for classifying variants allowed the identification of potentially functional variants for milk protein genes.

Indexed as

CaseinsMilk ProteinsAnimalsCattleComputer SimulationMutationPromoter Regions, GeneticCaseinsMilk ProteinsCarolina Guimarães Ramos Matosinho and Izinara Cruz Rosse contributed equally for this workCaseinCattleIn silico variant analysisLactoferrinMilk proteinα-Lactalbumin

Identifiers

PMID34705124
OpenAlexW3209886006

What OpenQuestion holds

Textmetadata
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.