Evidence map›Paper›PMID 25077682›Full record

ArticleBMC genomics2014

Extraction and annotation of human mitochondrial genomes from 1000 Genomes Whole Exome Sequencing data.

Maria Angela Diroma, Claudia Calabrese, Domenico Simone, Mariangela Santorsola, Francesco Maria Calabrese, Giuseppe Gasparre, Marcella Attimonelli

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
4.0field-weighted citation impact, top 5% 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

39 citing papers in PubMed, 72 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 3 institutions in 2 countries.

Maria Angela Diroma
Claudia Calabrese
Domenico Simone
Mariangela Santorsola
Francesco Maria Calabrese
Giuseppe Gasparre
Marcella Attimonelli
University of Bari Aldo Moro · ITUniversity of Bologna · ITUniversity of Calgary · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWhole Exome Sequencing (WES) is one of the most used and cost-effective next generation technologies that allows sequencing of all nuclear exons. Off-target regions may be captured if they present high sequence similarity with baits. Bioinformatics tools have been optimized to retrieve a large amount of WES off-target mitochondrial DNA (mtDNA), by exploiting the aspecificity of probes, partially overlapping to Nuclear mitochondrial Sequences (NumtS). The 1000 Genomes project represents one of the widest resources to extract mtDNA sequences from WES data, considering the large effort the scientific community is undertaking to reconstruct human population history using mtDNA as marker, and the involvement of mtDNA in pathology.

resultsA previously published pipeline aimed at assembling mitochondrial genomes from off-target WES reads and further improved to detect insertions and deletions (indels) and heteroplasmy in a dataset of 1242 samples from the 1000 Genomes project, enabled to obtain a nearly complete mitochondrial genome from 943 samples (76% analyzed exomes). The robustness of our computational strategy was highlighted by the reduction of reads amount recognized as mitochondrial in the original annotation produced by the Consortium, due to NumtS filtering.

conclusionsTo the best of our knowledge, this is likely the most extended population-scale mitochondrial genotyping in humans enriched with the estimation of heteroplasmies.

Indexed as

Computational BiologyExomeGenome, MitochondrialGenomicsCell LineChromosome MappingCluster AnalysisDatasets as TopicFemaleGene FrequencyGenetic VariationHaplotypesHigh-Throughput Nucleotide SequencingHumansINDEL MutationMale

Identifiers

PMID25077682
PMCPMC4083402
OpenAlexW2134905460

What OpenQuestion holds

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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.