kWIP: The k-mer weighted inner product, a de novo estimator of genetic similarity

Murray, Kevin; Webers, Christfried; Ong, Cheng Soon; Borevitz, Justin O.; Warthmann, Norman

doi:10.1371/journal.pcbi.1005727

Cited by 45 publications

(42 citation statements)

References 51 publications

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“…We performed kmer‐based exploratory genetic analysis, to confirm sample identities and guide subsequent analyses. Genetic distances were estimated using kWIP, a kmer‐based estimator of genetic distance (Murray, Webers, Ong, Borevitz, & Warthmann, ). We first counted 21‐mers in unaligned, quality trimmed sequencing reads, after pooling all reads for each sample into one file.…”

Section: Methodsmentioning

confidence: 99%

Landscape drivers of genomic diversity and divergence in woodland Eucalyptus

et al. 2019

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Spatial genetic patterns are influenced by numerous factors, and they can vary even among coexisting, closely related species due to differences in dispersal and selection. Eucalyptus (L'Héritier 1789; the “eucalypts”) are foundation tree species that provide essential habitat and modulate ecosystem services throughout Australia. Here we present a study of landscape genomic variation in two woodland eucalypt species, using whole‐genome sequencing of 388 individuals of Eucalyptus albens and Eucalyptus sideroxylon. We found exceptionally high genetic diversity (π ≈ 0.05) and low genome‐wide, interspecific differentiation (FST = 0.15) and intraspecific differentiation between localities (FST ≈ 0.01–0.02). We found no support for strong, discrete population structure, but found substantial support for isolation by geographic distance (IBD) in both species. Using generalized dissimilarity modelling, we identified additional isolation by environment (IBE). Eucalyptus albens showed moderate IBD, and environmental variables have a small but significant amount of additional predictive power (i.e. IBE). Eucalyptus sideroxylon showed much stronger IBD and moderate IBE. These results highlight the vast adaptive potential of these species and set the stage for testing evolutionary hypotheses of interspecific adaptive differentiation across environments.

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Section: Methodsmentioning

confidence: 99%

Landscape drivers of genomic diversity and divergence in woodland Eucalyptus

et al. 2019

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“…We performed kmer-based exploratory genetic analysis, to confirm sample identities and guide subsequent analyses. Genetic distances were estimated using kWIP, a kmer-based estimator of genetic distance (Murray et al, 2017). We first counted 21-mers in unaligned, quality trimmed sequencing reads, after pooling all reads for each sample into one file.…”

Section: Population Genetic Analysismentioning

confidence: 99%

Landscape drivers of genomic diversity and divergence in woodland Eucalyptus

Murray

Janes

Bothwell

et al. 2019

Preprint

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Spatial genetic patterns are influenced by numerous factors, and they can vary even among coexisting, closely related species due to differences in dispersal and selection. Eucalyptus (L'Héritier 1789; the "eucalypts") are foundation tree species that provide essential habitat and modulate ecosystem services throughout Australia.Here we present a study of landscape genomic variation in two woodland eucalypt species, using whole-genome sequencing of 388 individuals of Eucalyptus albens and Eucalyptus sideroxylon. We found exceptionally high genetic diversity (π ≈ 0.05) and low genome-wide, interspecific differentiation (F ST = 0.15) and intraspecific differentiation between localities (F ST ≈ 0.01-0.02). We found no support for strong, discrete population structure, but found substantial support for isolation by geographic distance (IBD) in both species. Using generalized dissimilarity modelling, we identified additional isolation by environment (IBE). Eucalyptus albens showed moderate IBD, and environmental variables have a small but significant amount of additional predictive power (i.e. IBE). Eucalyptus sideroxylon showed much stronger IBD and moderate IBE. These results highlight the vast adaptive potential of these species and set the stage for testing evolutionary hypotheses of interspecific adaptive differentiation across environments. K E Y W O R D S adaptation, angiosperms, ecological genetics, landscape genetics, population geneticsempirical, speciation S U PP O RTI N G I N FO R M ATI O N Additional supporting information may be found online in the Supporting Information section.

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“…In general, the question of whether the percentage of matching k-mers is a good metric for comparing sequencing experiments is still open, and more investigation into how to best measure similarity is needed (e.g. see [27]). However, our large query algorithm opens the door for efficiently exploring the parameter space of k-mer-based approaches.…”

Section: Discussionmentioning

confidence: 99%

AllSome Sequence Bloom Trees

Sun

Harris

Chikhi

et al. 2018

Journal of Computational Biology

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The ubiquity of next-generation sequencing has transformed the size and nature of many databases, pushing the boundaries of current indexing and searching methods. One particular example is a database of 2652 human RNA-seq experiments uploaded to the Sequence Read Archive (SRA). Recently, Solomon and Kingsford proposed the Sequence Bloom Tree data structure and demonstrated how it can be used to accurately identify SRA samples that have a transcript of interest potentially expressed. In this article, we propose an improvement called the AllSome Sequence Bloom Tree. Results show that our new data structure significantly improves performance, reducing the tree construction time by 52.7% and query time by 39%-85%, with a price of upto 3 × memory consumption during queries. Notably, it can query a batch of 198,074 queries in <8 hours (compared with around 2 days previously) and a whole set of k-mers from a sequencing experiment (about 27 million k-mers) in <11 minutes.

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kWIP: The k-mer weighted inner product, a de novo estimator of genetic similarity

Cited by 45 publications

References 51 publications

Landscape drivers of genomic diversity and divergence in woodland Eucalyptus

Landscape drivers of genomic diversity and divergence in woodland Eucalyptus

Landscape drivers of genomic diversity and divergence in woodland Eucalyptus

AllSome Sequence Bloom Trees

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