ArticleISME communications2025
Uneven sequencing (coverage) depth can bias microbial intraspecies diversity estimates and how to account for it.
Article in ISME communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Shotgun metagenome sequencing and informatics can accurately form a metagenome-assembled genome (MAG) of the bacterial tier 1 select agentMicrobiology spectrum · 2026Article
- Dispersal pathways and infection strategies within the Global Halophilic Virome.ISME communications · 2026Article
- An ANIr-based methodology to determine if two sequence-discrete populations are identical and identify cosmopolitan prokaryotic populations.ISME communications · 2026Article
- Genomic characterization and phylogenetic placement of Matryoshka RNA virus 1 associated with Plasmodium vivax malaria in Africa.Access microbiology · 2026Article
- Global dominance of Haloquadratum walsbyi by a single genomovar with distinct gene content and viral cohorts from close relatives.The ISME journal · 2025Article
- Differences in metagenome coverage may confound abundance-based and diversity conclusions and how to deal with them.ISME communications · 2025Article
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Authors and funding
8 authors.
Funding
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Abstract
An unbiased and accurate estimation of intraspecies diversity, i.e. the extent of genetic diversity within species (or microdiversity), is crucial for clinical and environmental microbiome studies. Although it is well appreciated that sequencing depth (or coverage depth) below 10X can provide biased estimates of microdiversity, typically underestimating diversity due to the random sampling of alleles, there is a widely accepted convention that microdiversity estimates tend to be relatively stable at sequencing depth exceeding 10X. Therefore, discarding species with <10X or rarefying to 10-20X sequencing depth are generally used to compare microdiversity among taxa and samples. Our findings showed that these biases may persist even at depth levels above 50-200X for all popular sequencing platforms, including Illumina, PacBio, and Oxford Nanopore. The biases mostly, but not always, represent an underestimation of diversity and were attributable to the incomplete recovery of Single Nucleotide Variants (SNVs) at lower sequencing depth levels. To address this issue, we recommend using rarefaction-based approaches to standardize data at least 50X, and ideally at 200X sequencing depth, which reduces differences between observed and expected microdiversity values to <0.5%. Furthermore, the Average Nucleotide Identity of reads (ANIr) metric is significantly less sensitive to sequencing depth variability than nucleotide diversity (
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