Data structures based on <i>k</i>-mers for querying large collections of sequencing data sets

Marchet, Camille; Boucher, Christina; Puglisi, Simon J.; Medvedev, Paul; Salson, Mikaël; Chikhi, Rayan

doi:10.1101/gr.260604.119

Cited by 83 publications

(89 citation statements)

References 69 publications

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“…The lesser detrimental effects of the maize B suggests that it is generally devoid of dosage-sensitive genes. In vertebrates, three different homologous chromosome pairs have evolved into heteromorphic sex chromosomes with the loss of many genes ( 56 ). However, dosage-sensitive genes are retained between the chromosome pair, illustrating selection against a two-fold change in dosage.…”

Section: Discussionmentioning

confidence: 99%

Sequence of the supernumerary B chromosome of maize provides insight into its drive mechanism and evolution

Blavet

Yang

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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B chromosomes are enigmatic elements in thousands of plant and animal genomes that persist in populations despite being nonessential. They circumvent the laws of Mendelian inheritance but the molecular mechanisms underlying this behavior remain unknown. Here we present the sequence, annotation, and analysis of the maize B chromosome providing insight into its drive mechanism. The sequence assembly reveals detailed locations of the elements involved with the cis and trans functions of its drive mechanism, consisting of nondisjunction at the second pollen mitosis and preferential fertilization of the egg by the B-containing sperm. We identified 758 protein-coding genes in 125.9 Mb of B chromosome sequence, of which at least 88 are expressed. Our results demonstrate that transposable elements in the B chromosome are shared with the standard A chromosome set but multiple lines of evidence fail to detect a syntenic genic region in the A chromosomes, suggesting a distant origin. The current gene content is a result of continuous transfer from the A chromosomal complement over an extended evolutionary time with subsequent degradation but with selection for maintenance of this nonvital chromosome.

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Section: Discussionmentioning

confidence: 99%

Sequence of the supernumerary B chromosome of maize provides insight into its drive mechanism and evolution

Blavet

Yang

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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“…Moreover, many other requests could be easily considered for annotated gene exploration like gene co-expression, or to compensate the lack of completeness in genomic or transcriptomic references to cover unreferenced RNA diversity and search for new spliced events, intron retention or new transcript categories including circular RNAs. In order to increase the potential of the k -mer approach, access to very large-scale datasets like SRA level (164 000 human samples) could be considered with efficient indexing structure development ( 43 ).…”

Section: Discussionmentioning

confidence: 99%

Kmerator Suite: design of specific k-mer signatures and automatic metadata discovery in large RNA-seq datasets

Riquier

Bessière

Guibert

et al. 2021

NAR Genomics and Bioinformatics

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The huge body of publicly available RNA-sequencing (RNA-seq) libraries is a treasure of functional information allowing to quantify the expression of known or novel transcripts in tissues. However, transcript quantification commonly relies on alignment methods requiring a lot of computational resources and processing time, which does not scale easily to large datasets. K-mer decomposition constitutes a new way to process RNA-seq data for the identification of transcriptional signatures, as k-mers can be used to quantify accurately gene expression in a less resource-consuming way. We present the Kmerator Suite, a set of three tools designed to extract specific k-mer signatures, quantify these k-mers into RNA-seq datasets and quickly visualize large dataset characteristics. The core tool, Kmerator, produces specific k-mers for 97% of human genes, enabling the measure of gene expression with high accuracy in simulated datasets. KmerExploR, a direct application of Kmerator, uses a set of predictor gene-specific k-mers to infer metadata including library protocol, sample features or contaminations from RNA-seq datasets. KmerExploR results are visualized through a user-friendly interface. Moreover, we demonstrate that the Kmerator Suite can be used for advanced queries targeting known or new biomarkers such as mutations, gene fusions or long non-coding RNAs for human health applications.

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“…K-mer-based methods have been applied for sequence comparison for error correction (1), genome assembly (2,3), metagenomic (4) and chromosome (5) sequence classification, sequence clustering (6), database search (7,8), structural variation detection (9,10), transcriptome analysis (11,12), and many other applications. Because of this widespread use, many data structures and techniques for efficiently storing, querying, and counting k-mers have been proposed (see (13) for a review). While k-mers has proven to be practical in several sequence comparison problems, they are sensitive to mutations.…”

Section: Introductionmentioning

confidence: 99%

“…K-mer-based methods have been applied for sequence comparison for error correction (1), genome assembly (2, 3), metagenomic (4) and chromosome (5) sequence classification, sequence clustering (6), database search (7, 8), structural variation detection (9–11), transcriptome analysis (12, 13), DNA barcoding of species (14), estimation of genome size (15), identification of biomarkers (16), and many other applications. Because of the widespread use of k-mers, many data structures and techniques for efficiently storing and querying k-mers have been proposed (see (17) for a review).…”

Section: Introductionmentioning

confidence: 99%

Strobemers: an alternative to k-mers for sequence comparison

Sahlin

2021

Preprint

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K-mer-based methods are widely used in bioinformatics for various types of sequence comparison. However, a single mutation will mutate k consecutive k-mers and makes most k-mer based applications for sequence comparison sensitive to variable mutation rates. Many techniques have been studied to overcome this sensitivity, e.g., spaced k-mers and k-mer permutation techniques, but these techniques do not handle indels well. For indels, pairs or groups of small k-mers are commonly used, but these methods first produce k-mer matches, and only in a second step, a pairing or grouping of k-mers is performed. Such techniques produce many redundant k-mer matches due to the size of k. Here, we propose strobemers as an alternative to k-mers for sequence comparison. Intuitively, strobemers consists of linked minimizers. We show that under a certain minimizer selection technique, strobemers provide more evenly distributed sequence matches than k-mers and are less sensitive to different mutation rates and distributions. Strobemers also produce a higher total match coverage across sequences. Strobemers are a useful alternative to k-mers for performing sequence comparisons as commonly used in sequence alignment, clustering, classification, and error-correction. A reference implementation with code for analyses is available at https://github.com/ksahlin/strobemers.

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Data structures based on k-mers for querying large collections of sequencing data sets

Cited by 83 publications

References 69 publications

Sequence of the supernumerary B chromosome of maize provides insight into its drive mechanism and evolution

Sequence of the supernumerary B chromosome of maize provides insight into its drive mechanism and evolution

Kmerator Suite: design of specific k-mer signatures and automatic metadata discovery in large RNA-seq datasets

Strobemers: an alternative to k-mers for sequence comparison

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