Evidence map›Paper›PMID 31359622›Full record

ArticleMolecular ecology resources2019

An evaluation of sequencing coverage and genotyping strategies to assess neutral and adaptive diversity.

Badr Benjelloun, Frédéric Boyer, Ian Streeter, Wahid Zamani, Stefan Engelen, Adriana Alberti, Florian J Alberto, Mohamed BenBati, Mustapha Ibnelbachyr, Mouad Chentouf and 10 more

Abstract read
In one paragraph

Article in Molecular ecology resources, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

36 citing papers in PubMed.

  1. Article
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  6. Article
  7. Review
  8. Local Climate Adaptation in Chinese Indigenous Pig Genomes.Animals : an open access journal from MDPI · 2025
    Article
  9. Review
  10. Article
  11. Article
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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

20 authors.

Badr BenjellounUniversity of Grenoble-Alpes, University of Savoy Mont Blanc, CNRS, LECA, Grenoble, France.ORCID https://orcid.org/0000-0003-4310-7281
Frédéric BoyerUniversity of Grenoble-Alpes, University of Savoy Mont Blanc, CNRS, LECA, Grenoble, France.
Ian StreeterEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK.
Wahid ZamaniUniversity of Grenoble-Alpes, University of Savoy Mont Blanc, CNRS, LECA, Grenoble, France.
Stefan EngelenGenoscope, Institut François Jacob, CEA, CNRS, Université Paris-Saclay, Université Evry Val-d'Essonne, Evry, France.
Adriana AlbertiGenoscope, Institut François Jacob, CEA, CNRS, Université Paris-Saclay, Université Evry Val-d'Essonne, Evry, France.
Florian J AlbertoUniversity of Grenoble-Alpes, University of Savoy Mont Blanc, CNRS, LECA, Grenoble, France.
Mohamed BenBatiNational Institute of Agronomic Research (INRA Maroc), Regional Centre of Agronomic Research, Beni-Mellal, Morocco.
Mustapha IbnelbachyrNational Institute of Agronomic Research (INRA Maroc), CRRA Errachidia, Errachidia, Morocco.
Mouad ChentoufNational Institute of Agronomic Research (INRA Maroc), CRRA Tangier, Tangier, Morocco.
Abdelmajid BechchariNational Institute of Agronomic Research (INRA Maroc), CRRA Oujda, Oujda, Morocco.
Hamid R RezaeiDepartment of Environmental Sciences, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran.
Saeid NaderiEnvironmental Sciences Department, Natural Resources Faculty, University of Guilan, Guilan, Iran.
Alessandra StellaBioinformatics Unit, PTP Science Park, Lodi, Italy.
Abdelkader ChikhiNational Institute of Agronomic Research (INRA Maroc), CRRA Errachidia, Errachidia, Morocco.
Laura ClarkeEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK.
James KijasCommonwealth Scientific and Industrial Research Organisation Animal Food and Health Sciences, St Lucia, QLD, Australia.
Paul FlicekEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK.ORCID https://orcid.org/0000-0002-3897-7955
Pierre TaberletUniversity of Grenoble-Alpes, University of Savoy Mont Blanc, CNRS, LECA, Grenoble, France.ORCID https://orcid.org/0000-0002-3554-5954
François PompanonUniversity of Grenoble-Alpes, University of Savoy Mont Blanc, CNRS, LECA, Grenoble, France.ORCID https://orcid.org/0000-0003-4600-0172

Funding

EU Seventh Framework Programme 244356
6 · The paper itself

Abstract

Whole genome sequences (WGS) greatly increase our ability to precisely infer population genetic parameters, demographic processes, and selection signatures. However, WGS may still be not affordable for a representative number of individuals/populations. In this context, our goal was to assess the efficiency of several SNP genotyping strategies by testing their ability to accurately estimate parameters describing neutral diversity and to detect signatures of selection. We analysed 110 WGS at 12× coverage for four different species, i.e., sheep, goats and their wild counterparts. From these data we generated 946 data sets corresponding to random panels of 1K to 5M variants, commercial SNP chips and exome capture, for sample sizes of five to 48 individuals. We also extracted low-coverage genome resequencing of 1×, 2× and 5× by randomly subsampling reads from the 12× resequencing data. Globally, 5K to 10K random variants were enough for an accurate estimation of genome diversity. Conversely, commercial panels and exome capture displayed strong ascertainment biases. Besides the characterization of neutral diversity, the detection of the signature of selection and the accurate estimation of linkage disequilibrium (LD) required high-density panels of at least 1M variants. Finally, genotype likelihoods increased the quality of variant calling from low coverage resequencing but proportions of incorrect genotypes remained substantial, especially for heterozygote sites. Whole genome resequencing coverage of at least 5× appeared to be necessary for accurate assessment of genomic variations. These results have implications for studies seeking to deploy low-density SNP collections or genome scans across genetically diverse populations/species showing similar genetic characteristics and patterns of LD decay for a wide variety of purposes.

Indexed as

AnimalsExomeGene FrequencyGenetics, PopulationGenomeGenomicsGenotypeGenotyping TechniquesGoatsHeterozygoteHigh-Throughput Nucleotide SequencingLinkage DisequilibriumPolymorphism, Single NucleotideSequence Analysis, DNASheepWhole Genome Sequencingdepth of coveragegenotyping-by-sequencingmammalspopulation genomicsSNP chipwhole genome sequencing

Identifiers

PMID31359622
PMCPMC7115901

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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.