Evidence map›Paper›PMID 33420243›Full record

ArticleScientific reports2021

Analysis of human mitochondrial genome co-occurrence networks of Asian population at varying altitudes.

Rahul K Verma, Alena Kalyakulina, Cristina Giuliani, Pramod Shinde, Ajay Deep Kachhvah, Mikhail Ivanchenko, Sarika Jalan

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Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 13 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

7 authors at 5 institutions in 5 countries.

Rahul K VermaDepartment of Biosciences and Biomedical Engineering, Indian Institute of Technology Indore, Khandwa Road, Simrol, Indore, 453552, India.
Alena KalyakulinaDepartment of Applied Mathematics and Centre of Bioinformatics, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia.
Cristina GiulianiLaboratory of Molecular Anthropology & Center for Genome Biology, Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy.
Pramod ShindeDivision of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, CA, 92037, USA.
Ajay Deep KachhvahComplex Systems Lab, Department of Physics, Indian Institute of Technology Indore, Khandwa Road, Simrol, Indore, 453552, India.
Mikhail IvanchenkoDepartment of Applied Mathematics and Centre of Bioinformatics, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia.
Sarika JalanDepartment of Biosciences and Biomedical Engineering, Indian Institute of Technology Indore, Khandwa Road, Simrol, Indore, 453552, India. sarika@iiti.ac.in.
Indian Institute of Technology Indore · INN. I. Lobachevsky State University of Nizhny Novgorod · RUInstitute for Basic Science · KRLa Jolla Institute for Immunology · USUniversity of Bologna · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Networks have been established as an extremely powerful framework to understand and predict the behavior of many large-scale complex systems. We studied network motifs, the basic structural elements of networks, to describe the possible role of co-occurrence of genomic variations behind high altitude adaptation in the Asian human population. Mitochondrial DNA (mtDNA) variations have been acclaimed as one of the key players in understanding the biological mechanisms behind adaptation to extreme conditions. To explore the cumulative effects of variations in the mitochondrial genome with the variation in the altitude, we investigated human mt-DNA sequences from the NCBI database at different altitudes under the co-occurrence motifs framework. Analysis of the co-occurrence motifs using similarity clustering revealed a clear distinction between lower and higher altitude regions. In addition, the previously known high altitude markers 3394 and 7697 (which are definitive sites of haplogroup M9a1a1c1b) were found to co-occur within their own gene complexes indicating the impact of intra-genic constraint on co-evolution of nucleotides. Furthermore, an ancestral 'RSRS50' variant 10,398 was found to co-occur only at higher altitudes supporting the fact that a separate route of colonization at these altitudes might have taken place. Overall, our analysis revealed the presence of co-occurrence interactions specific to high altitude at a whole mitochondrial genome level. This study, combined with the classical haplogroups analysis is useful in understanding the role of co-occurrence of mitochondrial variations in high altitude adaptation.

Indexed as

AltitudeGenome, HumanGenome, MitochondrialAdaptation, PhysiologicalAsian PeopleDNA, MitochondrialHumansMutationDNA, Mitochondrial

Identifiers

PMID33420243
PMCPMC7794584
OpenAlexW3120200530

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