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Recent advancements in long-read sequencing have enabled the telomere-to-telomere (complete) assembly of a human genome and are now contributing to the haplotype-resolved complete assemblies of multiple human genomes. Because the accuracy of read mapping tools deteriorates in highly repetitive regions, there is a need to develop accurate,error-exposing(detecting potential assembly errors), anddiploid-aware (distinguishing different haplotypes) tools for read mapping in complete assemblies. We describe the first accurate, error-exposing, and partially diploid-aware VerityMap tool for long-read mapping to complete assemblies.

Single-nuclei RNA sequencing characterizes cell types at the gene level. However, compared to single-cell approaches, many single-nuclei cDNAs are purely intronic, lack barcodes and hinder the study of isoforms. Here we present single-nuclei isoform RNA sequencing (SnISOr-Seq). Using microfluidics, PCR-based artifact removal, target enrichment and long-read sequencing, SnISOr-Seq increased barcoded, exon-spanning long reads 7.5-fold compared to naive long-read single-nuclei sequencing. We applied SnISOr-Seq to adult human frontal cortex and found that exons associated with autism exhibit coordinated and highly cell-type-specific inclusion. We found two distinct combination patterns: those distinguishing neural cell types, enriched in TSS-exon, exon-polyadenylation-site and non-adjacent exon pairs, and those with multiple configurations within one cell type, enriched in adjacent exon pairs. Finally, we observed that human-specific exons are almost as tightly coordinated as conserved exons, implying that coordination can be rapidly established during evolution. SnISOr-Seq enables cell-type-specific long-read isoform analysis in human brain and in any frozen or hard-to-dissociate sample.

Since its initial release in 2000, the human reference genome has covered only the euchromatic fraction of the genome, leaving important heterochromatic regions unfinished. Addressing the remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium presents a complete 3.055 billion–base pair sequence of a human genome, T2T-CHM13, that includes gapless assemblies for all chromosomes except Y, corrects errors in the prior references, and introduces nearly 200 million base pairs of sequence containing 1956 gene predictions, 99 of which are predicted to be protein coding. The completed regions include all centromeric satellite arrays, recent segmental duplications, and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies.

Advances in long-read sequencing technologies and genome assembly methods have enabled the recent completion of the first telomere-to-telomere human genome assembly, which resolves complex segmental duplications and large tandem repeats, including centromeric satellite arrays in a complete hydatidiform mole (CHM13). Although derived from highly accurate sequences, evaluation revealed evidence of small errors and structural misassemblies in the initial draft assembly. To correct these errors, we designed a new repeat-aware polishing strategy that made accurate assembly corrections in large repeats without overcorrection, ultimately fixing 51% of the existing errors and improving the assembly quality value from 70.2 to 73.9 measured from PacBio high-fidelity and Illumina k-mers. By comparing our results to standard automated polishing tools, we outline common polishing errors and offer practical suggestions for genome projects with limited resources. We also show how sequencing biases in both high-fidelity and Oxford Nanopore Technologies reads cause signature assembly errors that can be corrected with a diverse panel of sequencing technologies.

Annotating newly sequenced genomes and determining alternative isoforms from long-read RNA data are complex and incompletely solved problems. Here we present IsoQuant—a computational tool using intron graphs that accurately reconstructs transcripts both with and without reference genome annotation. For novel transcript discovery, IsoQuant reduces the false-positive rate fivefold and 2.5-fold for Oxford Nanopore reference-based or reference-free mode, respectively. IsoQuant also improves performance for Pacific Biosciences data.

The human Y chromosome has been notoriously difficult to sequence and assemble because of its complex repeat structure including long palindromes, tandem repeats, and segmental duplications. As a result, more than half of the Y chromosome is missing from the GRCh38 reference sequence and it remains the last human chromosome to be finished. Here, the Telomere-to-Telomere (T2T) consortium presents the complete 62,460,029 base pair sequence of a human Y chromosome from the HG002 genome (T2T-Y) that corrects multiple errors in GRCh38-Y and adds over 30 million base pairs of sequence to the reference, revealing the complete ampliconic structures ofTSPY, DAZ, andRBMY; 42 additional protein-coding genes, mostly from theTSPYgene family; and an alternating pattern of human satellite 1 and 3 blocks in the heterochromatic Yq12 region. We have combined T2T-Y with a prior assembly of the CHM13 genome and mapped available population variation, clinical variants, and functional genomics data to produce a complete and comprehensive reference sequence for all 24 human chromosomes.

MotivationExtra-long tandem repeats (ETRs) are widespread in eukaryotic genomes and play an important role in fundamental cellular processes, such as chromosome segregation. Although emerging long-read technologies have enabled ETR assemblies, the accuracy of such assemblies is difficult to evaluate since there are no tools for their quality assessment. Moreover, since the mapping of error-prone reads to ETRs remains an open problem, it is not clear how to polish draft ETR assemblies.ResultsTo address these problems, we developed the TandemTools software that includes the TandemMapper tool for mapping reads to ETRs and the TandemQUAST tool for polishing ETR assemblies and their quality assessment. We demonstrate that TandemTools not only reveals errors in ETR assemblies but also improves the recently generated assemblies of human centromeres.Availability and implementationhttps://github.com/ablab/TandemTools.Supplementary informationSupplementary data are available at Bioinformatics online.

Long reads are reshaping RNA biology. However, determining alternative isoforms from long-read RNA data is a complex and incompletely solved problem even when the reference genome is known. Here we present IsoQuant - a reference-based tool that accurately discovers novel transcripts with at least 3-fold lower false positive rate and 1.8-fold increase in F1-score compared to other tools for Oxford Nanopore data. IsoQuant also increases performance for Pacific Biosciences data.

Annotating newly sequenced genomes and determining alternative isoforms from long-read RNA data are complex and incompletely solved problems. Here we present IsoQuant-a computational tool using intron graphs that accurately reconstructs transcripts both with and without reference genome annotation. For novel transcript discovery, IsoQuant reduces the false-positive rate fivefold and 2.5-fold for Oxford Nanopore reference-based or reference-free mode, respectively. IsoQuant also improves performance for Pacific Biosciences data.

Recent advancements in long-read sequencing have enabled the telomere-to-telomere (T2T) assembly of a human genome and are now contributing to the haplotype-resolved T2T assemblies of multiple human genomes. Since the accuracy of read mapping tools deteriorates in highly-repetitive regions, there is a need to develop accurate, error-exposing (detecting potential assembly errors), and diploid-aware (distinguishing different haplotypes) tools for read mapping in T2T assemblies. Although TandemMapper and Winnowmap2 tools made the first steps toward this goal, they have limitations. We describe the first accurate, error-exposing, and (to a limited extent) diploid-aware VerityMap tool for long-read mapping to T2T assemblies. Github: https://github.com/ablab/VerityMap

Long-read transcriptomics requires understanding error sources inherent to technologies. Current approaches cannot compare methods for an individual RNA molecule. Here, we present a novel platform comparison method that combined barcoding strategies and long-read sequencing to sequence cDNA copies representing an individual RNA molecule on both Pacific Biosciences and Oxford Nanopore. We compared these long reads pairs in terms of sequence content and splicing structure. Although individual read pairs show high similarity, we found differences in (i) aligned length, (ii) TSS and (iii) polyA-site assignment, and (iv) exon-intron structures. Overall 25% of read pairs disagreed on either TSS, polyA-site, or a splice site. Intron-chain disagreement typically arises from alignment errors of microexons and complicated splice sites. Our single-molecule technology comparison revealed that inconsistencies are often caused by sequencing-error induced inaccurate ONT alignments, especially to downstream GTNNGT donor motifs. However, annotation-disagreeing upstream shifts in NAGNAG acceptors in ONT are often confirmed by PacBio and thus likely real. In both barcoded and non-barcoded ONT reads, we found that intron number and proximity of other GT/AGs better predict inconsistency with the annotation than read quality alone. We summarized these findings in an annotation-based algorithm for spliced alignment correction that improves subsequent transcript construction with ONT reads.

Single-nuclei RNA-Seq is being widely employed to investigate cell types, especially of human brain and other frozen samples. In contrast to single-cell approaches, however, the majority of single-nuclei RNA counts originate from partially processed RNA leading to intronic cDNAs, thus hindering the investigation of complete isoforms. Here, using microfluidics, PCR-based artifact removal, target enrichment, and long-read sequencing, we developed single-nuclei isoform RNA-sequencing (‘SnISOr-Seq’), and applied it to the analysis of human adult frontal cortex samples. We found that exons associated with autism exhibit coordinated and more cell-type specific inclusion than exons associated with schizophrenia or ALS. We discovered two distinct modes of combination patterns: first, those distinguishing cell types in the human brain. These are enriched in combinations of TSS-exon, exon-polyA site, and distant (non-adjacent) exon pairs. Second, those with all isoform combinations found within one neural cell type, which are enriched in adjacent exon pairs. Furthermore, adjacent exon pairs are predominantly mutually associated, while distant pairs are frequently mutually exclusive. Finally, we observed that human-specific exons are as tightly coordinated as conserved exons, pointing to an efficient evolutionary mechanism underpinning coordination. SnISOr-Seq opens the door to single-nuclei long-read isoform analysis in the human brain, and in any frozen, archived or hard-to-dissociate sample.

Long-read transcriptomics require understanding error sources inherent to technologies. Current approaches cannot compare methods for an individual RNA molecule. Here, we present a novel platform-comparison method that combines barcoding strategies and long-read sequencing to sequence cDNA copies representing an individual RNA molecule on both Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT). We compare these long-read pairs in terms of sequence content and isoform patterns. Although individual read pairs show high similarity, we find differences in (1) aligned length, (2) transcription start site (TSS), (3) polyadenylation site (poly(A)-site) assignment, and (4) exon–intron structures. Overall, 25% of read pairs disagree on either TSS, poly(A)-site, or splice site. Intron-chain disagreement typically arises from alignment errors of microexons and complicated splice sites. Our single-molecule technology comparison reveals that inconsistencies are often caused by sequencing error–induced inaccurate ONT alignments, especially to downstream GUNNGU donor motifs. However, annotation-disagreeing upstream shifts in NAGNAG acceptors in ONT are often confirmed by PacBio and are thus likely real. In both barcoded and nonbarcoded ONT reads, we find that intron number and proximity of GU/AGs better predict inconsistencies with the annotation than read quality alone. We summarize these findings in an annotation-based algorithm for spliced alignment correction that improves subsequent transcript construction with ONT reads.

INTRODUCTION: To faithfully distribute genetic material to daughter cells during cell division, spindle fibers must couple to DNA by means of a structure called the kinetochore, which assembles at each chromosome’s centromere. Human centromeres are located within large arrays of tandemly repeated DNA sequences known as alpha satellite (αSat), which often span millions of base pairs on each chromosome. Arrays of αSat are frequently surrounded by other types of tandem satellite repeats, which have poorly understood functions, along with nonrepetitive sequences, including transcribed genes. Previous genome sequencing efforts have been unable to generate complete assemblies of satellite-rich regions because of their scale and repetitive nature, limiting the ability to study their organization, variation, and function. RATIONALE: Pericentromeric and centromeric (peri/centromeric) satellite DNA sequences have remained almost entirely missing from the assembled human reference genome for the past 20 years. Using a complete, telomere-to-telomere (T2T) assembly of a human genome, we developed and deployed tailored computational approaches to reveal the organization and evolutionary patterns of these satellite arrays at both large and small length scales. We also performed experiments to map precisely which αSat repeats interact with kinetochore proteins. Last, we compared peri/centromeric regions among multiple individuals to understand how these sequences vary across diverse genetic backgrounds. RESULTS: Satellite repeats constitute 6.2% of the T2T-CHM13 genome assembly, with αSat representing the single largest component (2.8% of the genome). By studying the sequence relationships of αSat repeats in detail across each centromere, we found genome-wide evidence that human centromeres evolve through “layered expansions.” Specifically, distinct repetitive variants arise within each centromeric region and expand through mechanisms that resemble successive tandem duplications, whereas older flanking sequences shrink and diverge over time. We also revealed that the most recently expanded repeats within each αSat array are more likely to interact with the inner kinetochore protein Centromere Protein A (CENP-A), which coincides with regions of reduced CpG methylation. This suggests a strong relationship between local satellite repeat expansion, kinetochore positioning, and DNA hypomethylation. Furthermore, we uncovered large and unexpected structural rearrangements that affect multiple satellite repeat types, including active centromeric αSat arrays. Last, by comparing sequence information from nearly 1600 individuals’ Xchromosomes, we observed that individuals with recent African ancestry possess the greatest genetic diversity in the region surrounding the centromere, which sometimes contains a predominantly African αSat sequence variant. CONCLUSION: The genetic and epigenetic properties of centromeres are closely interwoven through evolution. These findings raise important questions about the specific molecular mechanisms responsible for the relationship between inner kinetochore proteins, DNA hypomethylation, and layered αSat expansions. Even more questions remain about the function and evolution of non-αSat repeats. To begin answering these questions, we have produced a comprehensive encyclopedia of peri/centromeric sequences in a human genome, and we demonstrated how these regions can be studied with modern genomic tools. Our work also illuminates the rich genetic variation hidden within these formerly missing regions of the genome, which may contribute to health and disease. This unexplored variation underlines the need for more T2T human genome assemblies from genetically diverse individuals.

In 2001, Celera Genomics and the International Human Genome Sequencing Consortium published their initial drafts of the human genome, which revolutionized the field of genomics. While these drafts and the updates that followed effectively covered the euchromatic fraction of the genome, the heterochromatin and many other complex regions were left unfinished or erroneous. Addressing this remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium has finished the first truly complete 3.055 billion base pair (bp) sequence of a human genome, representing the largest improvement to the human reference genome since its initial release. The new T2T-CHM13 reference includes gapless assemblies for all 22 autosomes plus Chromosome X, corrects numerous errors, and introduces nearly 200 million bp of novel sequence containing 2,226 paralogous gene copies, 115 of which are predicted to be protein coding. The newly completed regions include all centromeric satellite arrays and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies for the first time.

The complete assembly of each human chromosome is essential for understanding human biology and evolution1,2. Here we use complementary long-read sequencing technologies to complete the linear assembly of human chromosome 8. Our assembly resolves the sequence of five previously long-standing gaps, including a 2.08-Mb centromeric α-satellite array, a 644-kb copy number polymorphism in the β-defensin gene cluster that is important for disease risk, and an 863-kb variable number tandem repeat at chromosome 8q21.2 that can function as a neocentromere. We show that the centromeric α-satellite array is generally methylated except for a 73-kb hypomethylated region of diverse higher-order α-satellites enriched with CENP-A nucleosomes, consistent with the location of the kinetochore. In addition, we confirm the overall organization and methylation pattern of the centromere in a diploid human genome. Using a dual long-read sequencing approach, we complete high-quality draft assemblies of the orthologous centromere from chromosome 8 in chimpanzee, orangutan and macaque to reconstruct its evolutionary history. Comparative and phylogenetic analyses show that the higher-order α-satellite structure evolved in the great ape ancestor with a layered symmetry, in which more ancient higher-order repeats locate peripherally to monomeric α-satellites. We estimate that the mutation rate of centromeric satellite DNA is accelerated by more than 2.2-fold compared to the unique portions of the genome, and this acceleration extends into the flanking sequence., The complete assembly of human chromosome 8 resolves previous gaps and reveals hidden complex forms of genetic variation, enabling functional and evolutionary characterization of primate centromeres.

Natural products have traditionally been rich sources for drug discovery. In order to clear the road toward the discovery of unknown natural products, biologists need dereplication strategies that identify known ones. Here we report DEREPLICATOR+, an algorithm that improves on the previous approaches for identifying peptidic natural products, and extends them for identification of polyketides, terpenes, benzenoids, alkaloids, flavonoids, and other classes of natural products. We show that DEREPLICATOR+ can search all spectra in the recently launched Global Natural Products Social molecular network and identify an order of magnitude more natural products than previous dereplication efforts. We further demonstrate that DEREPLICATOR+ enables cross-validation of genome-mining and peptidogenomics/glycogenomics results., New natural products can be identified via mass spectrometry by excluding all known ones from the analysis, a process called dereplication. Here, the authors extend a previously published dereplication algorithm to different classes of secondary metabolites.

Peptidic natural products (PNPs) include many antibiotics and other bioactive compounds. While the recent launch of the Global Natural Products Social (GNPS) molecular networking infrastructure is transforming PNP discovery into a high-throughput technology, PNP identification algorithms are needed to realize the potential of the GNPS project. GNPS relies on the assumption that each connected component of a molecular network (representing related metabolites) illuminates the 'dark matter of metabolomics' as long as it contains a known metabolite present in a database. We reveal a surprising diversity of PNPs produced by related bacteria and show that, contrary to the 'comparative metabolomics' assumption, two related bacteria are unlikely to produce identical PNPs (even though they are likely to produce similar PNPs). Since this observation undermines the utility of GNPS, we developed a PNP identification tool, VarQuest, that illuminates the connected components in a molecular network even if they do not contain known PNPs and only contain their variants. VarQuest reveals an order of magnitude more PNP variants than all previous PNP discovery efforts and demonstrates that GNPS already contains spectra from 41% of the currently known PNP families. The enormous diversity of PNPs suggests that biosynthetic gene clusters in various microorganisms constantly evolve to generate a unique spectrum of PNP variants that differ from PNPs in other species.

Extra-long tandem repeats (ETRs) are widespread in eukaryotic genomes and play an important role in fundamental cellular processes, such as chromosome segregation. Although emerging long-read technologies have enabled ETR assemblies, the accuracy of such assemblies is difficult to evaluate since there is no standard tool for their quality assessment. Moreover, since the mapping of long error-prone reads to ETR remains an open problem, it is not clear how to polish draft ETR assemblies. To address these problems, we developed the tandemMapper tool for mapping reads to ETRs and the tandemQUAST tool for polishing ETR assemblies and their quality assessment. We demonstrate that tandemQUAST not only reveals errors in and evaluates ETR assemblies, but also improves them. To illustrate how tandemMapper and tandemQUAST work, we apply them to recently generated assemblies of human centromeres.

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are an important class of natural products that contain antibiotics and a variety of other bioactive compounds. The existing methods for discovery of RiPPs by combining genome mining and computational mass spectrometry are limited to discovering specific classes of RiPPs from small datasets, and these methods fail to handle unknown post-translational modifications. Here, we present MetaMiner, a software tool for addressing these challenges 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 eight genomic and metagenomic datasets, MetaMiner discovered 31 known and seven unknown RiPPs from diverse microbial communities, including human microbiome and lichen microbiome, and microorganisms isolated from the International Space Station.

Peptidic Natural Products (PNPs) are widely used compounds that include many antibiotics and a variety of other bioactive peptides. While recent breakthroughs in PNP discovery raised the challenge of developing new algorithms for their analysis, identification of PNPs via database search of tandem mass spectra remains an open problem. To address this problem, natural product researchers utilize dereplication strategies that identify known PNPs and lead to the discovery of new ones even in cases when the reference spectra are not present in existing spectral libraries. DEREPLICATOR is a new dereplication algorithm that enabled high-throughput PNP identification and that is compatible with large-scale mass spectrometry-based screening platforms for natural product discovery. After searching nearly one hundred million tandem mass spectra in the Global Natural Products Social (GNPS) molecular networking infrastructure, DEREPLICATOR identified an order of magnitude more PNPs (and their new variants) than any previous dereplication efforts.

Motivation The emergence of high-throughput sequencing technologies revolutionized genomics in early 2000s. The next revolution came with the era of long-read sequencing. These technological advances along with novel computational approaches became the next step towards the automatic pipelines capable to assemble nearly complete mammalian-size genomes. Results In this manuscript, we demonstrate performance of the state-of-the-art genome assembly software on six eukaryotic datasets sequenced using different technologies. To evaluate the results, we developed QUAST-LG—a tool that compares large genomic de novo assemblies against reference sequences and computes relevant quality metrics. Since genomes generally cannot be reconstructed completely due to complex repeat patterns and low coverage regions, we introduce a concept of upper bound assembly for a given genome and set of reads, and compute theoretical limits on assembly correctness and completeness. Using QUAST-LG, we show how close the assemblies are to the theoretical optimum, and how far this optimum is from the finished reference. Availability and implementation http://cab.spbu.ru/software/quast-lg Supplementary information Supplementary data are available at Bioinformatics online.

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.

Summary : Data visualization plays an increasingly important role in NGS data analysis. With advances in both sequencing and computational technologies, it has become a new bottleneck in genomics studies. Indeed, evaluation of de novo genome assemblies is one of the areas that can benefit from the visualization. However, even though multiple quality assessment methods are now available, existing visualization tools are hardly suitable for this purpose. Here, we present Icarus—a novel genome visualizer for accurate assessment and analysis of genomic draft assemblies, which is based on the tool QUAST. Icarus can be used in studies where a related reference genome is available, as well as for non-model organisms. The tool is available online and as a standalone application. Availability and Implementation: http://cab.spbu.ru/software/icarus Contact: aleksey.gurevich@spbu.ru Supplementary information: Supplementary data are available at Bioinformatics online.

Background: The aim of the study was to elaborate a method of specific diagnostics of progressive ovarian cancer. Methods and Findings: We observed 21 parameters in plasma of 300 primary ovarian cancer patients, stage III and IV. Using the least squares method, approximation of the relative frequencies by the Rayleigh distribution density was conducted for each parameter. The likelihood functions were constructed and intervals for each measurement on each stage were determined. Approximation accuracy was identified while checking the hypothesis of correspondence of parameter practical value to the theoretical law of density distribution by Pearson criterion. Conclusions: The obtained results suggest that the level of the oxidative modification of proteins may serve as a reliable indicator for the differential diagnosis of stages III and IV ovarian cancer.

In this paper we present a simple technique of analog electronic circuits synthesis by means of a linear representation. The approach is based on generalized parameter extraction method. It describes the procedure for developing the circuit topology both for passive or active circuits. The input data for the proposed synthesis method are the arbitrary network function approximated in polynomial form and specified elements set. In contrast to other synthesis approaches the proposed technique provides the realization of full set of equivalent circuits and allow to choose the best circuit solutions by various criteria. Experiments conducted on the low-pass filter design demonstrate the simplicity and effectiveness of synthesis method.

Background: Ovarian cancer (OC) is the most lethal of gynecologic tumors because women generally present with advanced stage disease. Platinum-based chemotherapy play a pivotal role in OC treatment. The aim of the study was to assess the effects of CAP-regimen chemotherapy on blood redox status in patients with ovarian cancer. Materials and Methods: Patients were 132 women with primary OC with FIGO stage III-IV. Patients were examined before treatment, 3 and 14 days after the first and 3 and 14 days after the second course of CAP-regimen chemotherapy. The activity of antioxidant enzymes, the intensity of lipid peroxidation, the level of oxidative modification of proteins (OMP) were evaluated. Results: We have found elevated levels of OMP products in plasma and erythrocytes of patients with ovarian cancer in comparison with donors. Our results suggest activation of lipid peroxidation in plasma and erythrocytes of ovarian cancer patients in comparison with healthy women. Sensitive and specific indicators of oxidative stress are levels of glutathione-S-transferase (sensitivity 80%, specificity 89%), diene conjugates (sensitivity 85,71%, specificity 72,73%) and OMP 430 nm (sensitivity 80%, specificity 90%) in blood plasma and the activity of catalase in erythrocytes (sensitivity 100%, specificity 89%). Conclusion: CAP chemotherapy in patients with ovarian cancer with FIGO stage III-IV induces radical formation and changes the homeostasis of the patient. The lipid peroxidation and antioxidant system in plasma move to a higher level of functioning, and the erythrocytes develop oxidative stress.