Biology subjects

Korobeynikov, A.

Publications and source records attributed to Korobeynikov, A..

13 recordsLinked to original sources

bioRxiv2026

Petabase-scale Papillomavirus Discovery

Freely available nucleic acid sequencing databases have accumulated to a vast archive of genetic diversity, in excess of 50 petabase-pairs from tens of millions of experiments. Together, these data constitute a digital survey of Earths genome. However, the richness of biological information contained within these repositories remains largely unexplored, in large part owing to the technical challenges of analyzing petabytes of data. Recently, Logan completed the sequence-assembly and compression of 27 million sequencing libraries from the Sequence Read Archive (SRA), and here, we systematically search Logan-SRA to reveal the global diversity of the DNA-based Papillomaviruses (PVs). In a single [~]10-hour alignment-based search against the Logan assemblage, we independently re-identified 65% of the 992 PVs recorded within the NCBI Virus database, a body of work representing over five decades of PV characterization. We further expand the diversity of PVs by 34%, identifying 383 novel PV types spanning 105 associated host species, including taxa with no previously associated PVs, such as rhinoceros, voles, and grey foxes. Through integration of virus phylogeny, sample geography, and ecological metadata, we show that novel PV discovery is not directly proportional to sampling effort, and there are significant hotspots of PV biodiversity in East Africa and South America, and that undersampled biomes can yield disproportionately more novel PVs. Public sequencing repositories contain vast, unrealized biological information that is now accessible through advanced computational infrastructure. Here we lay the foundations for the efficient analysis of petabase-scale datasets for DNA virus discovery, with applications to uncovering all genetic diversity.

bioinformatics↗

bioRxiv2024

Blackbird: structural variant detection using synthetic and low-coverage long-reads

MotivationRecent benchmarks of structural variant (SV) detection tools revealed that the majority of human genome structural variations (SVs), especially the medium-range (50-10,000 bp) SVs cannot be re-solved with short-read sequencing, but long-read SV callers achieve great results on the same datasets. While improvements have been made, high-coverage long-read sequencing is associated with higher costs and input DNA requirements. To decrease the cost one can lower the sequence coverage, but the current long-read SV callers perform poorly with coverage below 10x. Synthetic long-read (SLR) technologies hold great potential for structural variant (SV) detection, although utilizing their long-range information for events smaller than 50 kbp has been challenging. ResultsIn this work, we propose a hybrid novel integrated alignment- and local-assembly-based algorithm, Blackbird, that uses SLR together with low-coverage long reads to improve SV detection and assembly. Without the need for a computationally expensive whole genome assembly, Blackbird uses a sliding window approach and barcode information encoded in SLR to accurately assemble small segments and use long reads for an improved gap closing and contig assembly. We evaluated Blackbird on simulated and real human genome datasets. Using the HG002 GIAB benchmark set, we demonstrated that in hybrid mode, Blackbird demonstrated results comparable to state-of-the-art long-read tools, while using less long-read coverage. Blackbird requires only 5x coverage to achieve F1 scores (0.835 and 0.808 for deletions and insertions) similar to PBSV (0.856 and 0.812) and Sniffles2 (0.839 and 0.804) using 10x Pacbio Hi-Fi long-read coverage.

bioinformatics↗

bioRxiv2024

Logan: Planetary-Scale Genome Assembly Surveys Life's Diversity

The breadth of lifes diversity is unfathomable, but public nucleic acid sequencing data offers a window into the dispersion and evolution of genetic diversity across Earth. However the rapid growth and accumulation of sequence data have outpaced efficient analysis capabilities. The largest collection of freely available sequencing data is the Sequence Read Archive (SRA), comprising 27.3 million datasets or 5 x 1016 basepairs. To realize the potential of the SRA, we constructed Logan, a massive sequence assembly transforming short reads into long contigs and compressing the data over 100-fold, enabling highly efficient petabase-scale analysis. We created Logan-Search, a k-mer index of Logan for free planetary-scale sequence search, returning matches in minutes. We used Logan contigs to identify >200 million plastic-degrading enzyme homologs, and validate novel enzymes with catalytic activities exceeding current reference standards. Further, we vastly expand the known diversity of proteins (30-fold over UniRef50), plasmids (22-fold over PLSDB), P4 satellites (4.5-fold), and the recently described Obelisk RNA elements (3.7-fold). Logan also enables ecological and biomedical data mining, such as global tracking of antimicrobial resistance genes and the characterization of viral reactivation across millions of human BioSamples. By transforming the SRA, Logan democratizes access to the worlds public genetic data and opens frontiers in biotechnology, molecular ecology, and global health.

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

wastewaterSPAdes: SARS-CoV-2 strain deconvolution using SPAdes toolkit

MotivationSARS-CoV-2 wastewater samples are extensively collected and studied because it allows quantitatively assess a viral load in surrounding populations. Additionally, SARS-CoV-2 strain deconvolution gives more insights into pandemic dynamics, and the uprising of new strains. Usually, the solution to the strain deconvolution problem starts with read alignment of wastewater short read sequencing data to the SARS-CoV-2 reference genome. After variants are called and their abundances are estimated, a reference database is used to assign variants to strains, select a subset of strains, and infer relative abundance of these strains based on some mathematical model. Assembly-based methods have its own strengths, but currently reside in the shadow of alignment-based methods. ResultsIn this paper we propose a new assembly-based approach based on SPAdes toolkit codebase --- wastewaterSPAdes, that is able to deconvolve wastewater without a need of read alignment. Our results show that watewaterSPAdes is able to accurately identify strains presented in a sample, and correctly estimate abundances for most of the samples. Availabilityhttps://cab.spbu.ru/software/wastewaterspades/ Contacta.korobeynikov@spbu.ru Supplementary informationSupplementary data are available at Bioinformatics

bioinformatics↗

bioRxiv2022

Benchmarking state-of-the-art approaches for norovirus genome assembly in metagenome sample

MotivationA recently published article in BMC Genomics by Fuentes-Trillo et al (2021) contains a comparison of assembly approaches of several Noroviral samples via different tools and preprocessing strategies. Unfortunately the study used outdated versions of tools as well as tools that were not designed for the viral assembly task. In order to improve the suboptimal assemblies the authors suggested different sophisticated preprocessing strategies that seem to make only minor contributions to the results. We redone the analysis using state-of-the art tools designed for viral assembly. ResultsHere we demonstrate that tools from the SPAdes toolkit (O_SCPLOWRNAVIRALC_SCPLOWSPAO_SCPLOWDESC_SCPLOW and O_SCPLOWCORONAC_SCPLOWSPAO_SCPLOWDESC_SCPLOW) allows one to assemble the samples from the original study into a single contig without any additional preprocessing.

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↗

bioRxiv2020

Petabase-scale sequence alignment catalyses viral discovery

Public databases contain a planetary collection of nucleic acid sequences, but their systematic exploration has been inhibited by a lack of efficient methods for searching this corpus, now exceeding multiple petabases and growing exponentially [1, 2]. We developed a cloud computing infrastructure, Serratus, to enable ultra-high throughput sequence alignment at the petabase scale. We searched 5.7 million biologically diverse samples (10.2 petabases) for the hallmark gene RNA dependent RNA polymerase, identifying well over 105 novel RNA viruses and thereby expanding the number of known species by roughly an order of magnitude. We characterised novel viruses related to coronaviruses and to hepatitis{delta} virus, respectively and explored their environmental reservoirs. To catalyse a new era of viral discovery, we established a free and comprehensive database of these data and tools. Expanding the known sequence diversity of viruses can reveal the evolutionary origins of emerging pathogens and improve pathogen surveillance for the anticipation and mitigation of future pandemics.

bioinformatics↗

bioRxiv2020

coronaSPAdes: from biosynthetic gene clusters to coronaviral assemblies

MotivationThe COVID-19 pandemic has ignited a broad scientific interest in viral research in general and coronavirus research in particular. The identification and characterization of viral species in natural reservoirs typically involves de novo assembly. However, existing genome, metagenome and transcriptome assemblers often are not able to assemble many viruses (including coronaviruses) into a single contig. Coverage variation between datasets and within dataset, presence of close strains, splice variants and contamination set a high bar for assemblers to process viral datasets with diverse properties. ResultsWe developed coronaSPAdes, a novel assembler for RNA viral species recovery in general and coronaviruses in particular. coronaSPAdes leverages the knowledge about viral genome structures to improve assembly extending ideas initially implemented in biosyntheticSPAdes. We have shown that coronaSPAdes outperforms existing SPAdes modes and other popular short-read metagenome and viral assemblers in the recovery of full-length RNA viral genomes. AvailabilitycoronaSPAdes version used in this article is a part of SPAdes 3.15 release and is freely available at http://cab.spbu.ru/software/spades. Contacta.korobeynikov@spbu.ru Supplementary informationSupplementary data are available at Bioinformatics

bioinformatics↗

bioRxiv2019

SPAligner: alignment of long diverged molecular sequences to assembly graphs

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSGraph-based representation of genome assemblies has been recently used in different applications -- from gene finding to haplotype separation. While most of these applications are based on the alignment of molecular sequences to assembly graphs, existing software tools for finding such alignments have important limitations.\n\nResultsWe present a novel SPAligner tool for aligning long diverged molecular sequences to assembly graphs and demonstrate that SPAligner is an efficient solution for mapping third generation sequencing data and can also facilitate the identification of known genes in complex metagenomic datasets.\n\nConclusionsOur work will facilitate accelerating the development of graph-based approaches in solving sequence to genome assembly alignment problem. SPAligner is implemented as a part of SPAdes tools library and is available on https://github.com/ablab/spades/archive/spaligner-paper.zip.

bioinformatics↗

bioRxiv2019

PathRacer: racing profile HMM paths on assembly graph

Recently large databases containing profile Hidden Markov Models (pHMMs) emerged. These pHMMs may represent the sequences of antibiotic resistance genes, or allelic variations amongst highly conserved housekeeping genes used for strain typing, etc. The typical application of such a database includes the alignment of contigs to pHMM hoping that the sequence of gene of interest is located within the single contig. Such a condition is often violated for metagenomes preventing the effective use of such databases. We present PO_SCPLOWATHC_SCPLOWRO_SCPLOWACERC_SCPLOW -- a novel standalone tool that aligns profile HMM directly to the assembly graph (performing the codon translation on fly for amino acid pHMMs). The tool provides the set of most probable paths traversed by a HMM through the whole assembly graph, regardless whether the sequence of interested is encoded on the single contig or scattered across the set of edges, therefore significantly improving the recovery of sequences of interest even from fragmented metagenome assemblies. Availabilityhttp://cab.spbu.ru/software/pathracer/

bioinformatics↗

bioRxiv2017

MetaRiPPquest: A Peptidogenomics Approach for the Discovery of Ribosomally Synthesized and Post-translationally Modified Peptides

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are an important class of natural products that include many antibiotics and a variety of other bioactive compounds. While recent breakthroughs in RiPP discovery raised the challenge of developing new algorithms for their analysis, peptidogenomic-based identification of RiPPs by combining genome/metagenome mining with analysis of tandem mass spectra remains an open problem. We present here MetaRiPPquest, a software tool for addressing this challenge that is compatible with large-scale screening platforms for natural product discovery. After searching millions of spectra in the Global Natural Products Social (GNPS) molecular networking infrastructure against just six genomic and metagenomic datasets, MetaRiPPquest identified 27 known and discovered 5 novel RiPP natural products.

bioinformatics↗