Evidence map›Paper›PMID 24386182›Full record

ArticlePloS one2013

High-throughput sequencing of a South American Amerindian.

André M Ribeiro-dos-Santos, Jorge Estefano Santana de Souza, Renan Almeida, Dayse O Alencar, Maria Silvanira Barbosa, Leonor Gusmão, Wilson A Silva, Sandro J de Souza, Artur Silva, Ândrea Ribeiro-dos-Santos and 2 more

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Characterization ofGenes · 2022
    Article
  4. Article
  5. Article
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.

André M Ribeiro-dos-SantosInstituto de Ciências Biológicas, Universidade Federal do Pará, Belém, Pará, Brazil.
Jorge Estefano Santana de SouzaCentro Regional de Hemoterapia, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, São Paulo, Brazil ; Institute of Bioinformatics and Biotechnology, São Paulo, São Paulo, Brazil.
Renan AlmeidaInstitute of Bioinformatics and Biotechnology, São Paulo, São Paulo, Brazil.
Dayse O AlencarInstituto de Ciências Biológicas, Universidade Federal do Pará, Belém, Pará, Brazil.
Maria Silvanira BarbosaInstituto de Ciências Biológicas, Universidade Federal do Pará, Belém, Pará, Brazil.
Leonor GusmãoInstituto de Ciências Biológicas, Universidade Federal do Pará, Belém, Pará, Brazil ; Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal.
Wilson A SilvaCentro Regional de Hemoterapia, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, São Paulo, Brazil ; Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, São Paulo, Brazil.
Sandro J de SouzaInstitute of Bioinformatics and Biotechnology, São Paulo, São Paulo, Brazil ; Brain Institute, Universidade Federal do Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil.
Artur SilvaInstituto de Ciências Biológicas, Universidade Federal do Pará, Belém, Pará, Brazil.
Ândrea Ribeiro-dos-SantosInstituto de Ciências Biológicas, Universidade Federal do Pará, Belém, Pará, Brazil.
Sylvain DarnetInstituto de Ciências Biológicas, Universidade Federal do Pará, Belém, Pará, Brazil.
Sidney SantosInstituto de Ciências Biológicas, Universidade Federal do Pará, Belém, Pará, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The emergence of next-generation sequencing technologies allowed access to the vast amounts of information that are contained in the human genome. This information has contributed to the understanding of individual and population-based variability and improved the understanding of the evolutionary history of different human groups. However, the genome of a representative of the Amerindian populations had not been previously sequenced. Thus, the genome of an individual from a South American tribe was completely sequenced to further the understanding of the genetic variability of Amerindians. A total of 36.8 giga base pairs (Gbp) were sequenced and aligned with the human genome. These Gbp corresponded to 95.92% of the human genome with an estimated miscall rate of 0.0035 per sequenced bp. The data obtained from the alignment were used for SNP (single-nucleotide) and INDEL (insertion-deletion) calling, which resulted in the identification of 502,017 polymorphisms, of which 32,275 were potentially new high-confidence SNPs and 33,795 new INDELs, specific of South Native American populations. The authenticity of the sample as a member of the South Native American populations was confirmed through the analysis of the uniparental (maternal and paternal) lineages. The autosomal comparison distinguished the investigated sample from others continental populations and revealed a close relation to the Eastern Asian populations and Aboriginal Australian. Although, the findings did not discard the classical model of America settlement; it brought new insides to the understanding of the human population history. The present study indicates a remarkable genetic variability in human populations that must still be identified and contributes to the understanding of the genetic variability of South Native American populations and of the human populations history.

Indexed as

Genome, HumanHigh-Throughput Nucleotide SequencingCluster AnalysisDNA, MitochondrialGenetic LinkageGenetics, PopulationHumansINDEL MutationIndians, South AmericanMolecular Sequence AnnotationPolymorphism, Single NucleotidePopulation GroupsDNA, Mitochondrial

Identifiers

PMID24386182
PMCPMC3875439

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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.