Biology subjects

Kaplinski, L.

Publications and source records attributed to Kaplinski, L..

4 recordsLinked to original sources

bioRxiv2026

DIPLER: rapid k-mer-based locus identification

Here, we present Dipler, a two-step strategy that combines the identification of group-specific k-mers from whole-genome sequencing data with de novo assembly of PacBio reads enriched for those k-mers. Using a Gg/gg presence/absence-like model in Juglans hindsii, we recovered the structurally distinct "G" allele from PacBio reads at coverage as low as 9x. Using the exceptional GG genotype of J. regia "Sharkey" as a complementary diploid model, we further show that two divergent "G" alleles of the same locus can be resolved and assembled separately from 13x coverage. Dipler therefore provides a rapid, reference-independent framework for identifying structurally complex loci, with potential applicability across eukaryotic species.

bioinformatics↗

bioRxiv2020

KATK: fast genotyping of rare variants directly from unmapped sequencing reads

MotivationKATK is a fast and accurate software tool for calling variants directly from raw NGS reads. It uses predefined k-mers to retrieve only the reads of interest from the FASTQ file and calls genotypes by aligning retrieved reads locally. KATK does not use data about known polymorphisms and has NC (No Call) as default genotype. The reference or variant allele is called only if there is sufficient evidence for their presence in data. Thus it is not biased against rare variants or de novo mutations. ResultsWith simulated datasets, we achieved a false negative rate of 0.23% (sensitivity 99.77%) and a false discovery rate of 0.19%. Calling all human exonic regions with KATK requires 1-2 h, depending on sequencing coverage. AvailabilityKATK is distributed under the terms of GNU GPL v3. The k-mer databases are distributed under the Creative Commons CC BY-NC-SA license. The source code is available at GitHub as part of Genometester4 package (https://github.com/bioinfo-ut/GenomeTester4/). The binaries of KATK package and k-mer databases described in the current paper are available on http://bioinfo.ut.ee/KATK/.

bioinformatics↗

bioRxiv2019

Gene content of the fish-hunting cone snail Conus consors

BackgroundConus consors is a fish-hunting cone snail that lives in the tropical waters of the Indo-Pacific region. Cone snails have attracted scientific interest for the amazing potency of their venom, which consists of a complex mixture of small proteins known as conopeptides, many of which act as ion channel and receptor modulators with high selectivity.\n\nResultsWe have analysed publicly available transcriptomic sequences from 8 tissues of Conus consors and complemented the transcriptome data with the data from genomic DNA reads. We identified 17,715 full-length protein sequences from the transcriptome. In addition, we predicted 168 full-length or partial conopeptide sequences and characterized gene structures of several conopeptide superfamilies.

genomics↗

bioRxiv2018

Creating basis for introducing NIPT in the Estonian public health setting

ObjectiveThe study aimed to validate a whole-genome sequencing-based NIPT method and our newly developed NIPTmer analysis software with the potential to integrate the pipeline into prenatal clinical care in Estonia.\n\nMethodIn total, 447 maternal blood samples were included to the study. Analysis pipeline involved whole-genome library preparation and massively parallel sequencing on Illumina NextSeq 500. Aneuploidy status was determined with NIPTmer software, which is based on counting pre-defined per-chromosome sets of unique k-mers from raw sequencing data. To estimate fetal fraction (FF) from total cell-free DNA SeqFF was implemented.\n\nResultsNIPTmer software allowed to identify correctly all samples of non-mosaic T21 (15/15), T18 (9/9) and T13 (4/4) cases. However, one mosaic T18 remained undetected. Six false positive results were observed, including three for T18 (specificity 99.3%) and three for T13 (specificity 99.3%). FF < 4% (2.8-3.99%) was estimated in eight samples, including two samples with T13 and T18. Despite low FF, these two samples were determined as aneuploid with NIPTmer software.\n\nConclusionOur NIPT analysis pipeline proved to perform efficiently in detecting common fetal aneuploidies T21, T18 and T13 and is feasible for implementation into clinical service in Estonia.

genetics↗