Biology subjects

Tolstoganov, I.

Publications and source records attributed to Tolstoganov, I..

6 recordsLinked to original sources

bioRxiv2026

Hybrid RY-mers increase aDNA alignment sensitivity

One of the key steps in ancient DNA data analysis is the accurate identification of endogenous short reads that originate from the ancient genome. Currently, this step is performed using general-purpose sequence aligners, such as BWA-aln, with parameter settings optimized for sensitivity. This approach results in increased runtime, even relative to standard DNA alignment workflows, and is not sufficient for aligning samples that are highly divergent from a reference database. We introduce hybrid RY-mers, a seed construct designed to incorporate aDNA-specific sequence damage. We adapt hybrid RY-mers to the existing concept of multi-context seeds and implement them in the read aligner strobealign. On simulated genomic and metagenomic datasets, we show that hybrid RY-mers result in higher mapping accuracy, while also reducing runtime by 4-6 times compared to the state-of-the-art aDNA alignment method BWA-aln. Furthermore, substituting aDNA aligner MALT in the metagenomic tool-suite aMeta with our new alignment approach demonstrated that aMeta gave a faster and less memory consuming detection of ancient taxa present in the samples.

bioinformatics↗

bioRxiv2025

AEMB: a computationally efficient abundance estimation method for metagenomic binning

Metagenomic binning is a crucial step in metagenomic analysis, namely grouping together contigs that are predicted to originate from the same genome to enable the recovery of metagenome-assembled genomes (MAGs). It has been shown that using information from multiple samples yields better results than binning each sample independently. However, for N metagenomic samples, using full multi-against-multi binning requires N2 alignments, making it computationally challenging to apply in large-scale metagenomic studies. Here, we propose AEMB (Abundance Estimation for Metagenomic Binning), a novel mapping mode implemented in strobealign. AEMB is a computationally efficient abundance estimation method that uses a prefix-lookup vector as an indexing structure to reduce memory usage and randstrobes to estimate the abundance of contigs without performing base-level alignment. Compared to the hash table used in the previous version of strobealign, the indexing structure reduces peak memory usage by 25.2% with almost the same runtime. Furthermore, we implemented a fast abundance estimation method that skips base-level alignment. Altogether, AEMB reduces the runtime for abundance estimation by 88% to 96% compared to commonly used alignment methods such as Bowtie2 and BWA, while achieving similar binning results. AEMB is available as a mapping mode in strobealign https://github.com/ksahlin/strobealign and SemiBin2 (v2.1 and later) accepts its inputs for binning.

bioinformatics↗

bioRxiv2024

Multi-context seeds enable fast and high-accuracy read mapping

A key step in sequence similarity search is to identify shared seeds between a query and a reference sequence. A well-known tradeoff is that longer seeds offer fast searches but reduce sensitivity in variable regions. We introduce multi-context seeds (MCS), which allow to store seeds with different lengths in the same index structure, thus retaining the advantages of both short and long seeds. We demonstrate the applicability of MCS by implementing them in strobealign. Strobealign with MCS substantially improves accuracy compared to the previous version with little cost in runtime and no memory overhead.

bioinformatics↗

bioRxiv2022

SpLitteR: Diploid genome assembly using linked TELL-Seq reads and assembly graphs

BackgroundRecent advances in long-read sequencing technologies enabled accurate and contiguous de novo assemblies of large genomes and metagenomes. However, even long and accurate high-fidelity (HiFi) reads do not resolve repeats that are longer than the read lengths. This limitation negatively affects the contiguity of diploid genome assemblies since two haplomes share many long identical regions. To generate the telomere-to-telomere assemblies of diploid genomes, biologists now construct their HiFi-based phased assemblies and use additional experimental technologies to transform them into more contiguous diploid assemblies. The barcoded linked-reads, generated using an inexpensive TELL-Seq technology, provide an attractive way to bridge unresolved repeats in phased assemblies of diploid genomes. ResultsWe developed SpLitteR tool for diploid genome assembly using linked-reads and assembly graphs and benchmarked it against state-of-the-art linked-read scaffolders ARKS and SLR-superscaffolder using human HG002 genome and sheep gut microbiome datasets. The benchmark showed that SpLitteR scaffolding results in 1.5-fold increase in NGA50 compared to baseline LJA assembly and other scaffolders while introducing no additional misassemblies on the human dataset. ConclusionWe developed the SpLitteR tool for haplotype phasing and scaffolding in an assembly graph using barcoded linked-reads. We benchmarked SpLitteR on assembly graphs produced by various long-read assemblers and have shown how TELL-Seq reads facilitate phasing and scaffolding in these graphs. This benchmarking demonstrates that SpLitteR improves upon the state-of-the-art linked-read scaffolders in the accuracy and contiguity metrics. SpLitteR is implemented in C++ as a part of the freely available SPAdes package and is available at https://github.com/ablab/spades/releases/tag/splitter-preprint.

bioinformatics↗

bioRxiv2022

BinSPreader: refine binning results for fuller MAG reconstruction

Despite the recent advances in high-throughput sequencing, analysis of the metagenome of the whole microbial population still remains a challenge. In particular, the metagenome-assembled genomes (MAGs) are often fragmented due to interspecies repeats, uneven coverage and vastly different strain abundance. MAGs are usually constructed via a dedicated binning process that uses different features of input data in order to cluster contigs that might belong to the same species. This process has some limitations and therefore binners usually discard input contigs that are shorter than several kilobases. Therefore, binning of even simple metagenome assemblies can miss a decent fraction of contigs and resulting MAGs oftentimes do not contain important conservative sequences that might be of great interest of researcher. In this work we present BO_SCPLOWINC_SCPLOWSPO_SCPLOWREADERC_SCPLOW -- a novel binning refiner tool that exploits the assembly graph topology and other connectivity information to refine the existing binning, correct binning errors, propagate binning from longer contigs to shorter contigs and infer contigs belonging to multiple bins. Furthermore, BO_SCPLOWINC_SCPLOWSPO_SCPLOWREADERC_SCPLOW can split input reads in accordance with the resulting binning, predicting reads potentially belonging to multiple MAGs. We show that BO_SCPLOWINC_SCPLOWSPO_SCPLOWREADERC_SCPLOW could effectively complete the binning, increasing the completeness of the bins without sacrificing the purity and could predict contigs belonging to several MAGs.

bioinformatics↗

bioRxiv2021

Generation of lineage-resolved complete metagenome-assembled genomes by precision phasing

Microbial communities in many environments include distinct lineages of closely related organisms which have proved challenging to separate in metagenomic assembly, preventing generation of complete metagenome-assembled genomes (MAGs). The advent of long and accurate HiFi reads presents a possible means to address this challenge by generating complete MAGs for nearly all sufficiently abundant bacterial genomes in a microbial community. We present a metagenomic HiFi assembly of a complex microbial community from sheep fecal material that resulted in 428 high-quality MAGs from a single sample, the highest resolution achieved with metagenomic deconvolution to date. We applied a computational approach to separate distinct haplotype lineages and identified haplotypes of hundreds of variants across hundreds of kilobases of genomic sequence. Analysis of these haplotypes revealed 220 lineage-resolved complete MAGs, including 44 in single circular contigs, and demonstrated improvement in overall assembly compared to error-prone long reads. We report the characterization of multiple, closely-related microbes within a sample with potential to improve precision in assigning mobile genetic elements to host genomes within complex microbial communities.

microbiology↗