EncoMPASS: An encyclopedia of membrane proteins analyzed by structure and symmetry

Protein structure determination and prediction, active site detection, and protein sequence alignment techniques all exploit information about protein structure and structural relationships. For membrane proteins, however, there is limited agreement among available online tools for highlighting and mapping such structural similarities. Moreover, no available resource provides a systematic overview of quaternary and internal symmetries, and their orientation relative to the membrane, despite the fact that these properties can provide key insights into membrane protein function and evolution. Here, we describe the Encyclopedia of Membrane Proteins Analyzed by Structure and Symmetry (EncoMPASS), a database for relating integral membrane proteins of known structure from the points of view of sequence, structure, and symmetry. EncoMPASS is accessible through a web interface, and its contents can be easily downloaded. This allows the user not only to focus on specific proteins, but also to study general properties of the structure and evolution of membrane proteins.

Biosurfer for systematic tracking of regulatory mechanisms leading to protein isoform diversity

Long-read RNA sequencing has shed light on transcriptomic complexity, but questions remain about the functionality of downstream protein products. We introduce Biosurfer, a computational approach for comparing protein isoforms, while systematically tracking the transcriptional, splicing, and translational variations that underlie differences in the sequences of the protein products. Using Biosurfer, we analyzed the differences in 32,799 pairs of GENCODE annotated protein isoforms, finding a majority (70%) of variable N-termini are due to the alternative transcription start sites, while only 9% arise from 5' UTR alternative splicing. Biosurfer's detailed tracking of nucleotide-to-residue relationships helped reveal an uncommonly tracked source of single amino acid residue changes arising from the codon splits at junctions. For 17% of internal sequence changes, such split codon patterns lead to single residue differences, termed "ragged codons". Of variable C-termini, 72% involve splice- or intron retention-induced reading frameshifts. We found an unusual pattern of reading frame changes, in which the first frameshift is closely followed by a distinct second frameshift that restores the original frame, which we term a "snapback" frameshift. We analyzed long read RNA-seq-predicted proteome of a human cell line and found similar trends as compared to our GENCODE analysis, with the exception of a higher proportion of isoforms predicted to undergo nonsense-mediated decay. Biosurfer's comprehensive characterization of long-read RNA-seq datasets should accelerate insights of the functional role of protein isoforms, providing mechanistic explanation of the origins of the proteomic diversity driven by the alternative splicing. Biosurfer is available as a Python package at https://github.com/sheynkman-lab/biosurfer.

A weighted two-stage sequence alignment framework to identify motifs from ChIP-exo data

In this study, we introduce TESA (weighted two-stage alignment), an innovative motif prediction tool that refines the identification of DNA-binding protein motifs, essential for deciphering transcriptional regulatory mechanisms. Unlike traditional algorithms that rely solely on sequence data, TESA integrates the high-resolution chromatin immunoprecipitation (ChIP) signal, specifically from ChIP-exonuclease (ChIP-exo), by assigning weights to sequence positions, thereby enhancing motif discovery. TESA employs a nuanced approach combining a binomial distribution model with a graph model, further supported by a "bookend" model, to improve the accuracy of predicting motifs of varying lengths. Our evaluation, utilizing an extensive compilation of 90 prokaryotic ChIP-exo datasets from proChIPdb and 167 H. sapiens datasets, compared TESA's performance against seven established tools. The results indicate TESA's improved precision in motif identification, suggesting its valuable contribution to the field of genomic research.

Finding Highly Similar Regions of Genomic Sequences Through Homomorphic Encryption

Finding highly similar regions of genomic sequences is a basic computation of genomic analysis. Genomic analyses on a large amount of data are efficiently processed in cloud environments, but outsourcing them to a cloud raises concerns over the privacy and security issues. Homomorphic encryption (HE) is a powerful cryptographic primitive that preserves privacy of genomic data in various analyses processed in an untrusted cloud environment. We introduce an efficient algorithm for finding highly similar regions of two homomorphically encrypted sequences, and describe how to implement it using the bit-wise and word-wise HE schemes. In the experiment, our algorithm outperforms an existing algorithm by up to two orders of magnitude in terms of elapsed time. Overall, it finds highly similar regions of the sequences in real data sets in a feasible time.

Measuring, visualizing and diagnosing reference bias with biastools

Many bioinformatics methods seek to reduce reference bias, but no methods exist to comprehensively measure it. Biastools analyzes and categorizes instances of reference bias. It works in various scenarios, i.e. (a) when the donor's variants are known and reads are simulated, (b) when donor variants are known and reads are real, and (c) when variants are unknown and reads are real. Using biastools, we observe that more inclusive graph genomes result in fewer biased sites. We find that end-to-end alignment reduces bias at indels relative to local aligners. Finally, we use biastools to characterize how T2T references improve large-scale bias.

pathMap: a path-based mapping tool for long noisy reads with high sensitivity

With the rapid development of single-molecule sequencing (SMS) technologies, the output read length is continuously increasing. Mapping such reads onto a reference genome is one of the most fundamental tasks in sequence analysis. Mapping sensitivity is becoming a major concern since high sensitivity can detect more aligned regions on the reference and obtain more aligned bases, which are useful for downstream analysis. In this study, we present pathMap, a novel k-mer graph-based mapper that is specifically designed for mapping SMS reads with high sensitivity. By viewing the alignment chain as a path containing as many anchors as possible in the matched k-mer graph, pathMap treats chaining as a path selection problem in the directed graph. pathMap iteratively searches the longest path in the remaining nodes; more candidate chains with high quality can be effectively detected and aligned. Compared to other state-of-the-art mapping methods such as minimap2 and Winnowmap2, experiment results on simulated and real-life datasets demonstrate that pathMap obtains the number of mapped chains at least 11.50% more than its closest competitor and increases the mapping sensitivity by 17.28% and 13.84% of bases over the next-best mapper for Pacific Biosciences and Oxford Nanopore sequencing data, respectively. In addition, pathMap is more robust to sequence errors and more sensitive to species- and strain-specific identification of pathogens using MinION reads.

Rational design of peptide inhibitors targeting HSP90-CDC37 protein-protein interaction

Background: Specifically blocking HSP90-CDC37 interaction is emerging as a prospective strategy for cancer therapy. Aim: Applying a kinase pseudopeptide rationale to the discovery of HSP90-CDC37 protein-protein interaction (PPI) inhibitors. Methods: Pseudosubstrates were identified through sequence alignment and evaluated by biolayer interferometry assay, co-immunoprecipitation assay and antiproliferation assay. Results: TAT-DDO-59120 was identified to disrupt HSP90-CDC37 PPI through directly binding to HSP90, both extracellularly and intracellularly. In addition, the identified peptide showed ideal antiproliferative activity against the colorectal cancer cell HCT116 (IC50 = 12.82 μM). Conclusion: Compared with the traditional method of screening a large compound library to identify PPI inhibitors, this method is rapid and efficient with strong purpose, which provides a novel strategy for designing HSP90-CDC37 PPI inhibitors.

Chromosome-level phased genome assembly of "Antonovka" identified candidate apple scab-resistance genes highly homologous to HcrVf2 and HcrVf1 on linkage group 1

Apple scab, a fungal disease caused by Venturia inaequalis, leads to losses in both yield and fruit quality of apples (Malus domestica Borkh.). Most commercial apple cultivars, including those containing the well-characterized Rvi6-scab-resistance locus on linkage group (LG) 1, are susceptible to scab. HcrVf2 and HcrVf1 are considered the main paralogs of the Rvi6 locus. The major apple scab-resistance loci Vhc1 in "Honeycrisp" and Rvi17 in "Antonovka," were identified in close proximity to HcrVf2. In this study, we used long-read sequencing and in silico gene sequence characterization to identify candidate resistance genes homologous to HcrVf2 and HcrVf1 in Honeycrisp and Antonovka. Previously published chromosome-scale phased assembly of Honeycrisp and a newly assembled phased genome of Antonovka 172670-B were used to identify HcrVf2 and HcrVf1 homologs spanning Vhc1 and Rvi17 loci. In combination with 8 available Malus assemblies, 43 and 46 DNA sequences highly homologous to HcrVf2 and HcrVf1, respectively, were identified on LG 1 and 6, with identity and coverage ranging between 87-95 and 81-95%, respectively. Among these homologs, 2 candidate genes in Antonovka and Honeycrisp haplome A are located in close physical proximity to the scab-resistance marker Ch-Vf1 on LG 1. They showed the highest identity and coverage (95%) of HcrVf2 and only minor changes in the protein motifs. They were identical by state between each other, but not with HcrVf2. This study offers novel genomic resources and insights into the Vhc1 and Rvi17 loci on LG 1 and identifies candidate genes for further resistance characterization.

The Molecular Evolution, Structure, and Function of Coproporphyrinogen Oxidase and Protoporphyrinogen Oxidase in Prokaryotes

Coproporphyrinogen oxidase (CgoX) and protoporphyrinogen oxidase (PgoX) catalyze the oxidation of the flexible cyclic tetrapyrrole of porphyrinogen compounds into fully conjugated, planar macrocyclic porphyrin compounds during heme biosynthesis. These enzymes are activated via different pathways. CgoX oxidizes coproporphyrinogen III to coproporphyrin III in the coproporphyrin-dependent pathway, whereas PgoX oxidizes protoporphyrinogen IX to protoporphyrin IX in the penultimate step of the protoporphyrin-dependent pathway. The phylogenetic analysis presented herein demonstrates a clear differentiation between the two enzyme classes, as evidenced by the clustering of sequences in distinct clades, and it shows that, at the origin of porphyrinogen-type oxidase evolution, PgoXs from cyanobacteria were found, which were noticeably separated from descendant PgoX representatives of Deltaproteobacteria and all later PgoX variants, leading to many eukaryotic clades. CgoX sequences originating from the monoderm Actinomycetota and Bacillota were well separated from the predecessor clades containing PgoX types and represent a peculiar type of gene speciation. The structural similarities and differences between these two oxidases are discussed based on their protein sequence alignment and a structural comparison.

Gap-Sensitive Colinear Chaining Algorithms for Acyclic Pangenome Graphs

A pangenome graph can serve as a better reference for genomic studies because it allows a compact representation of multiple genomes within a species. Aligning sequences to a graph is critical for pangenome-based resequencing. The seed-chain-extend heuristic works by finding short exact matches between a sequence and a graph. In this heuristic, colinear chaining helps identify a good cluster of exact matches that can be combined to form an alignment. Colinear chaining algorithms have been extensively studied for aligning two sequences with various gap costs, including linear, concave, and convex cost functions. However, extending these algorithms for sequence-to-graph alignment presents significant challenges. Recently, Makinen et al. introduced a sparse dynamic programming framework that exploits the small path cover property of acyclic pangenome graphs, enabling efficient chaining. However, this framework does not consider gap costs, limiting its practical effectiveness. We address this limitation by developing novel problem formulations and provably good chaining algorithms that support a variety of gap cost functions. These functions are carefully designed to enable fast chaining algorithms whose time requirements are parameterized in terms of the size of the minimum path cover. Through an empirical evaluation, we demonstrate the superior performance of our algorithm compared with existing aligners. When mapping simulated long reads to a pangenome graph comprising 95 human haplotypes, we achieved 98.7% precision while leaving <2% of reads unmapped.

Application of Feature Definition and Quantification in Biological Sequence Analysis

Biological sequence analysis is the most fundamental work in bioinformatics. Many research methods have been developed in the development of biological sequence analysis. These methods include sequence alignment-based methods and alignment-free methods. In addition, there are also some sequence analysis methods based on the feature definition and quantification of the sequence itself. This editorial introduces the methods of biological sequence analysis and explores the significance of defining features and quantitative research of biological sequences.

Sequence Alignment/Map format: a comprehensive review of approaches and applications

The Sequence Alignment/Map (SAM) format file is the text file used to record alignment information. Alignment is the core of sequencing analysis, and downstream tasks accept mapping results for further processing. Given the rapid development of the sequencing industry today, a comprehensive understanding of the SAM format and related tools is necessary to meet the challenges of data processing and analysis. This paper is devoted to retrieving knowledge in the broad field of SAM. First, the format of SAM is introduced to understand the overall process of the sequencing analysis. Then, existing work is systematically classified in accordance with generation, compression and application, and the involved SAM tools are specifically mined. Lastly, a summary and some thoughts on future directions are provided.

Chromosome-level assemblies of the Pieris mannii butterfly genome suggest Z-origin and rapid evolution of the W chromosome

The insect order Lepidoptera (butterflies and moth) represents the largest group of organisms with ZW/ZZ sex determination. While the origin of the Z chromosome predates the evolution of the Lepidoptera, the W chromosomes are considered younger, but their origin is debated. To shed light on the origin of the lepidopteran W, we here produce chromosome-level genome assemblies for the butterfly Pieris mannii, and compare the sex chromosomes within and between P. mannii and its sister species P. rapae. Our analyses clearly indicate a common origin of the W chromosomes of the two Pieris species, and reveal similarity between the Z and W in chromosome sequence and structure. This supports the view that the W in these species originates from Z-autosome fusion rather than from a redundant B chromosome. We further demonstrate the extremely rapid evolution of the W relative to the other chromosomes and argue that this may preclude reliable conclusions about the origins of W chromosomes based on comparisons among distantly related Lepidoptera. Finally, we find that sequence similarity between the Z and W chromosomes is greatest toward the chromosome ends, perhaps reflecting selection for the maintenance of recognition sites essential to chromosome segregation. Our study highlights the utility of long-read sequencing technology for illuminating chromosome evolution.

Personalized Sliding Window Recommendation Algorithm Based on Sequence Alignment

With the explosive growth of the amount of information in social networks, the recommendation system, as an application of social networks, has attracted widespread attention in recent years on how to obtain user-interested content in massive data. At present, in the process of algorithm design of the recommending system, most methods ignore structural relationships between users. Therefore, in this paper, we designed a personalized sliding window for different users by combining timing information and network topology information, then extracted the information sequence of each user in the sliding window and obtained the similarity between users through sequence alignment. The algorithm only needs to extract part of the data in the original dataset, and the time series comparison shows that our method is superior to the traditional algorithm in recommendation Accuracy, Popularity, and Diversity.

Development of functional anti-Gn nanobodies specific for SFTSV based on next-generation sequencing and proteomics

Severe fever with thrombocytopenia syndrome (SFTS) is an acute infectious disease caused by novel bunyavirus (SFTSV), with a mortality rate of 6.3% ~ 30%. To date, there is no specific treatment for SFTS. Previously, we demonstrated that SFTSV surface glycoprotein (Glycoprotein N, Gn) was a potential target for the development of SFTS vaccine or therapeutic antibodies, and anti-Gn neutralizing antibodies played a protective role in SFTS infection. Compared with traditional antibodies, nanobodies from camelids have various advantages, including small molecular weight, high affinity, low immunogenicity, convenient production by gene engineering, etc. In this study, we combined next-generation sequencing (NGS) with proteomics technology based on affinity purification-mass spectrometry (AP-MS) and bioinformatics analysis to high-throughput screen monoclonal anti-Gn nanobodies from camel immunized with Gn protein. We identified 19 anti-Gn monoclonal nanobody sequences, of which six sequences were selected for recombinant protein expression and purification. Among these six anti-Gn nanobodies, nanobody 57,493 was validated to be highly specific for Gn. The innovative high-throughput technical route developed in this study could also be expanded to the production of nanobodies specific for other viruses like SARS-CoV-2.

Uncovering Pseudogenes and Intergenic Protein-coding Sequences in TriTryps' Genomes

Trypanosomatids belong to a remarkable group of unicellular, parasitic organisms of the order Kinetoplastida, an early diverging branch of the phylogenetic tree of eukaryotes, exhibiting intriguing biological characteristics affecting gene expression (intronless polycistronic transcription, trans-splicing, and RNA editing), metabolism, surface molecules, and organelles (compartmentalization of glycolysis, variation of the surface molecules, and unique mitochondrial DNA), cell biology and life cycle (phagocytic vacuoles evasion and intricate patterns of cell morphogenesis). With numerous genomic-scale data of several trypanosomatids becoming available since 2005 (genomes, transcriptomes, and proteomes), the scientific community can further investigate the mechanisms underlying these unusual features and address other unexplored phenomena possibly revealing biological aspects of the early evolution of eukaryotes. One fundamental aspect comprises the processes and mechanisms involved in the acquisition and loss of genes throughout the evolutionary history of these primitive microorganisms. Here, we present a comprehensive in silico analysis of pseudogenes in three major representatives of this group: Leishmania major, Trypanosoma brucei, and Trypanosoma cruzi. Pseudogenes, DNA segments originating from altered genes that lost their original function, are genomic relics that can offer an essential record of the evolutionary history of functional genes, as well as clues about the dynamics and evolution of hosting genomes. Scanning these genomes with functional proteins as proxies to reveal intergenic regions with protein-coding features, relying on a customized threshold to distinguish statistically and biologically significant sequence similarities, and reassembling remnant sequences from their debris, we found thousands of pseudogenes and hundreds of open reading frames, with particular characteristics in each trypanosomatid: mutation profile, number, content, density, codon bias, average size, single- or multi-copy gene origin, number and type of mutations, putative primitive function, and transcriptional activity. These features suggest a common process of pseudogene formation, different patterns of pseudogene evolution and extant biological functions, and/or distinct genome organization undertaken by those parasites during evolution, as well as different evolutionary and/or selective pressures acting on distinct lineages.

NBLAST: a graphical user interface-based two-way BLAST software with a dot plot viewer

BLAST, a basic bioinformatics tool for searching local sequence similarity, has been one of the most widely used bioinformatics programs since its introduction in 1990. Users generally use the web-based NCBI-BLAST program for BLAST analysis. However, users with large sequence data are often faced with a problem of upload size limitation while using the web-based BLAST program. This proves inconvenient as scientists often want to run BLAST on their own data, such as transcriptome or whole genome sequences. To overcome this issue, we developed NBLAST, a graphical user interface-based BLAST program that employs a two-way system, allowing the use of input sequences either as "query" or "target" in the BLAST analysis. NBLAST is also equipped with a dot plot viewer, thus allowing researchers to create custom database for BLAST and run a dot plot similarity analysis within a single program. It is available to access to the NBLAST with http://nbitglobal.com/nblast.

Highly Similar Sequences of Mature IgA1 Proteases from Neisseria meningitidis, Neisseria gonorrhoeae and Haemophilus influenzae

The mature serine-type IgA1 protease from Neisseria meningitidis serogroup B strain H44/76 (IgA1pr1_28-1004) is considered here as the basis for creating a candidate vaccine against meningococcal meningitis. In this work, we examine the primary structure similarity of IgA1 proteases from various strains of a number of Gram-negative bacteria (N. meningitidis, Neisseria gonorrhoeae, Haemophilus influenzae) in order to find a structural groundwork for creating a broad-spectrum vaccine based on fragments of this enzyme. BLAST has shown high similarity between the primary structure of IgA1pr1_28-1004 and hypothetical sequences of mature IgA1 proteases from N. meningitidis (in 1060 out of 1061 examined strains), N. gonorrhoeae (in all 602 examined strains) and H. influenzae (in no less than 137 out of 521 examined strains). For these enzymes, common regions of sequence correspond to IgA1pr1_28-1004 fragments 28-84, 146-193, 253-539, 567-628, 639-795 and 811-1004, with identity of at least 85%. We believe that these fragments can be used in the development of a vaccine to prevent diseases caused by pathogenic strains of N. meningitidis and N. gonorrhoeae as well as a significant number of strains of H. influenzae.

Michael Waterman's Contributions to Computational Biology and Bioinformatics

On the occasion of Dr. Michael Waterman's 80th birthday, we review his major contributions to the field of computational biology and bioinformatics including the famous Smith-Waterman algorithm for sequence alignment, the probability and statistics theory related to sequence alignment, algorithms for sequence assembly, the Lander-Waterman model for genome physical mapping, combinatorics and predictions of ribonucleic acid structures, word counting statistics in molecular sequences, alignment-free sequence comparison, and algorithms for haplotype block partition and tagSNP selection related to the International HapMap Project. His books Introduction to Computational Biology: Maps, Sequences and Genomes for graduate students and Computational Genome Analysis: An Introduction geared toward undergraduate students played key roles in computational biology and bioinformatics education. We also highlight his efforts of building the computational biology and bioinformatics community as the founding editor of the Journal of Computational Biology and a founding member of the International Conference on Research in Computational Molecular Biology (RECOMB).

In silico insights into the dimer structure and deiodinase activity of type III iodothyronine deiodinase from bioinformatics, molecular dynamics simulations, and QM/MM calculations

The homodimeric family of iodothyronine deiodinases (Dios) regioselectively remove iodine from thyroid hormones. Currently, structural data has only been reported for the monomer of the mus type III thioredoxin (Trx) fold catalytic domain (Dio3^Trx), but the mode of dimerization has not yet been determined. Various groups have proposed dimer structures that are similar to the A-type and B-type dimerization modes of peroxiredoxins. Computational methods are used to compare the sequence of Dio3^Trx to related proteins known to form A-type and B-type dimers. Sequence analysis and in silico protein-protein docking methods suggest that Dio3^Trx is more consistent with proteins that adopt B-type dimerization. Molecular dynamics (MD) simulations of the refined Dio3^Trx dimer constructed using the SymmDock and GalaxyRefineComplex databases indicate stable dimer formation along the β₄α₃ interface consistent with other Trx fold B-type dimers. Free energy calculations show that the dimer is stabilized by interdimer interactions between the β-sheets and α-helices. A comparison of MD simulations of the apo and thyroxine-bound dimers suggests that the active site binding pocket is not affected by dimerization. Determination of the transition state for deiodination of thyroxine from the monomer structure using QM/MM methods provides an activation barrier consistent with previous small model DFT studies.Communicated by Ramaswamy H. Sarma.

Structural Modeling of Drosophila melanogaster Gut Cytochrome P450s and Docking Comparison of Fruit Fly Gut and Human Cytochrome P450s

Drosophila melanogaster is a prominent model organism in developmental biology research and in studies related to pathophysiological conditions like cancer and Alzheimer's disease. The fruit fly gut contains several cytochrome P450s (CYP450s) which have central roles in Drosophila development and in the normal physiology of the gut. Since the crystal structures of these proteins have not been deciphered yet, we modeled the structure of 29 different D. melanogaster gut CYP450s using Prime (Schrödinger). The sequences of chosen D. melanogaster gut CYP450s were compared with that of their human counterparts. The common gut (and liver) microsomal CYP450s in humans were chosen for structural comparison to find the homology and identity % of D. melanogaster CYPs with that of their human counterparts. The modeled structures were validated using PROCHECK and the best fit models were used for docking several known human pharmacological agents/drugs to the modeled D. melanogaster gut CYP450s. Based on the binding affinities (ΔG values) of the selected drug molecules with the modeled fly gut CYPs, the plausible differences in metabolism of the prominent drugs in humans and fly were projected. The gut is involved in absorption of oral drugs/pharmacological agents and hence, upregulation of intestinal CYP450 and their reactions with endobiotics and xenobiotics is envisaged. The insights gleaned from this work can validate D. melanogaster as a model organism for studying intestinal drug metabolism, particularly in the context of a) toxicology of pharmacological agents to the gut cells and b) how gut P450 metabolites/products can influence gut homeostasis. This work can help establish a platform for further in vitro investigations on how intestinal CYP450 metabolism can influence gut health. The data from this work can be used for further in silico studies and this work can serve as a platform for future in vitro investigations on intestinal CYP450-mediated metabolism of endo- and xeno-biotics in D. melanogaster.

Sequence alignment of folk song melodies reveals cross-cultural regularities of musical evolution

Culture evolves,^1-5 but the existence of cross-culturally general regularities of cultural evolution is debated.^6-8 As a diverse but universal cultural phenomenon, music provides a novel domain to test for the existence of such regularities.^9-12 Folk song melodies can be thought of as culturally transmitted sequences of notes that change over time under the influence of cognitive and acoustic/physical constraints.^9-15 Modeling melodies as evolving sequences constructed from an "alphabet" of 12 scale degrees¹⁶ allows us to quantitatively test for the presence of cross-cultural regularities using a sample of 10,062 melodies from musically divergent Japanese and English (British/American) folk song traditions.^17,18 Our analysis identifies 328 pairs of highly related melodies, finding that note changes are more likely when they have smaller impacts on a song's melody. Specifically, (1) notes with stronger rhythmic functions are less likely to change, and (2) note substitutions are most likely between neighboring notes. We also find that note insertions/deletions ("indels") are more common than note substitutions, unlike genetic evolution where the reverse is true. Our results are consistent across English and Japanese samples despite major differences in their scales and tonal systems. These findings demonstrate that even a creative art form such as music is subject to evolutionary constraints analogous to those governing the evolution of genes, languages, and other domains of culture.

Releasing the Kraken

Ten years ago, the dramatic rise in the number of microbial genomes led to an inflection point, when the approach of finding short, exact matches in a comprehensive database became just as accurate as older, slower approaches. The new idea led to a method that was hundreds of times times faster than those that came before. Today, exact k-mer matching is a standard technique at the heart of many microbiome analysis tools.

Analysis and Sequence Alignment of Peste des Petits Ruminants Virus ChinaSX2020

The peste des petits ruminants virus (PPRV) mainly infects goats and sheep and causes a highly contagious disease, PPR. Recently, a PPRV strain named ChinaSX2020 was isolated and confirmed following an indirect immunofluorescence assay and PCR using PPRV-specific antibody and primers, respectively. A sequencing of the ChinaSX2020 strain showed a genome length of 15,954 nucleotides. A phylogenetic tree analysis showed that the ChinaSX2020 genome was classified into lineage IV of the PRRV genotypes. The genome of the ChinaSX2020 strain was found to be closely related to PPRVs isolated in China between 2013 and 2014. These findings revealed that not a variety of PRRVs but similar PPRVs were continuously spreading and causing sporadic outbreaks in China.

Post-Alignment Adjustment and Its Automation

Multiple sequence alignment (MSA) is the basis for almost all sequence comparison and molecular phylogenetic inferences. Large-scale genomic analyses are typically associated with automated progressive MSA without subsequent manual adjustment, which itself is often error-prone because of the lack of a consistent and explicit criterion. Here, I outlined several commonly encountered alignment errors that cannot be avoided by progressive MSA for nucleotide, amino acid, and codon sequences. Methods that could be automated to fix such alignment errors were then presented. I emphasized the utility of position weight matrix as a new tool for MSA refinement and illustrated its usage by refining the MSA of nucleotide and amino acid sequences. The main advantages of the position weight matrix approach include (1) its use of information from all sequences, in contrast to other commonly used methods based on pairwise alignment scores and inconsistency measures, and (2) its speedy computation, making it suitable for a large number of long viral genomic sequences.

Location deviations of DNA functional elements affected SNP mapping in the published databases and references

The recent extensive application of next-generation sequencing has led to the rapid accumulation of multiple types of data for functional DNA elements. With the advent of precision medicine, the fine-mapping of risk loci based on these elements has become of paramount importance. In this study, we obtained the human reference genome (GRCh38) and the main DNA sequence elements, including protein-coding genes, miRNAs, lncRNAs and single nucleotide polymorphism flanking sequences, from different repositories. We then realigned these elements to identify their exact locations on the genome. Overall, 5%-20% of all sequence element locations deviated among databases, on the scale of kilobase-pair to megabase-pair. These deviations even affected the selection of genome-wide association study risk-associated genes. Our results implied that the location information for functional DNA elements may deviate among public databases. Researchers should take care when using cross-database sources and should perform pilot sequence alignments before element location-based studies.

A Structure Based Study of Selective Inhibition of Factor IXa over Factor Xa

Blood coagulation is an essential physiological process for hemostasis; however, abnormal coagulation can lead to various potentially fatal disorders, generally known as thromboembolic disorders, which are a major cause of mortality in the modern world. Recently, the FDA has approved several anticoagulant drugs for Factor Xa (FXa) which work via the common pathway of the coagulation cascade. A main side effect of these drugs is the potential risk for bleeding in patients. Coagulation Factor IXa (FIXa) has recently emerged as the strategic target to ease these risks as it selectively regulates the intrinsic pathway. These aforementioned coagulation factors are highly similar in structure, functional architecture, and inhibitor binding mode. Therefore, it remains a challenge to design a selective inhibitor which may affect only FIXa. With the availability of a number of X-ray co-crystal structures of these two coagulation factors as protein–ligand complexes, structural alignment, molecular docking, and pharmacophore modeling were employed to derive the relevant criteria for selective inhibition of FIXa over FXa. In this study, six ligands (three potent, two selective, and one inactive) were selected for FIXa inhibition and six potent ligands (four FDA approved drugs) were considered for FXa. The pharmacophore hypotheses provide the distribution patterns for the principal interactions that take place in the binding site. None of the pharmacophoric patterns of the FXa inhibitors matched with any of the patterns of FIXa inhibitors. Based on pharmacophore analysis, a selectivity of a ligand for FIXa over FXa may be defined quantitatively as a docking score of lower than −8.0 kcal/mol in the FIXa-grids and higher than −7.5 kcal/mol in the FXa-grids.

Computational Analysis of the Crystal and Cryo-EM Structures of P-Loop Channels with Drugs

The superfamily of P-loop channels includes various potassium channels, voltage-gated sodium and calcium channels, transient receptor potential channels, and ionotropic glutamate receptors. Despite huge structural and functional diversity of the channels, their pore-forming domain has a conserved folding. In the past two decades, scores of atomic-scale structures of P-loop channels with medically important drugs in the inner pore have been published. High structural diversity of these complexes complicates the comparative analysis of these structures. Here we 3D-aligned structures of drug-bound P-loop channels, compared their geometric characteristics, and analyzed the energetics of ligand-channel interactions. In the superimposed structures drugs occupy most of the sterically available space in the inner pore and subunit/repeat interfaces. Cationic groups of some drugs occupy vacant binding sites of permeant ions in the inner pore and selectivity-filter region. Various electroneutral drugs, lipids, and detergent molecules are seen in the interfaces between subunits/repeats. In many structures the drugs strongly interact with lipid and detergent molecules, but physiological relevance of such interactions is unclear. Some eukaryotic sodium and calcium channels have state-dependent or drug-induced π-bulges in the inner helices, which would be difficult to predict. The drug-induced π-bulges may represent a novel mechanism of gating modulation.

Condition-Invariant Robot Localization Using Global Sequence Alignment of Deep Features

Localization is one of the essential process in robotics, as it plays an important role in autonomous navigation, simultaneous localization, and mapping for mobile robots. As robots perform large-scale and long-term operations, identifying the same locations in a changing environment has become an important problem. In this paper, we describe a robust visual localization system under severe appearance changes. First, a robust feature extraction method based on a deep variational autoencoder is described to calculate the similarity between images. Then, a global sequence alignment is proposed to find the actual trajectory of the robot. To align sequences, local fragments are detected from the similarity matrix and connected using a rectangle chaining algorithm considering the robot's motion constraint. Since the chained fragments provide reliable clues to find the global path, false matches on featureless structures or partial failures during the alignment could be recovered and perform accurate robot localization in changing environments. The presented experimental results demonstrated the benefits of the proposed method, which outperformed existing algorithms in long-term conditions.

A General Framework to Learn Tertiary Structure for Protein Sequence Characterization

During the past five years, deep-learning algorithms have enabled ground-breaking progress towards the prediction of tertiary structure from a protein sequence. Very recently, we developed SAdLSA, a new computational algorithm for protein sequence comparison via deep-learning of protein structural alignments. SAdLSA shows significant improvement over established sequence alignment methods. In this contribution, we show that SAdLSA provides a general machine-learning framework for structurally characterizing protein sequences. By aligning a protein sequence against itself, SAdLSA generates a fold distogram for the input sequence, including challenging cases whose structural folds were not present in the training set. About 70% of the predicted distograms are statistically significant. Although at present the accuracy of the intra-sequence distogram predicted by SAdLSA self-alignment is not as good as deep-learning algorithms specifically trained for distogram prediction, it is remarkable that the prediction of single protein structures is encoded by an algorithm that learns ensembles of pairwise structural comparisons, without being explicitly trained to recognize individual structural folds. As such, SAdLSA can not only predict protein folds for individual sequences, but also detects subtle, yet significant, structural relationships between multiple protein sequences using the same deep-learning neural network. The former reduces to a special case in this general framework for protein sequence annotation.

Methods of privacy-preserving genomic sequencing data alignments

Genomic data alignment, a fundamental operation in sequencing, can be utilized to map reads into a reference sequence, query on a genomic database and perform genetic tests. However, with the reduction of sequencing cost and the accumulation of genome data, privacy-preserving genomic sequencing data alignment is becoming unprecedentedly important. In this paper, we present a comprehensive review of secure genomic data comparison schemes. We discuss the privacy threats, including adversaries and privacy attacks. The attacks can be categorized into inference, membership, identity tracing and completion attacks and have been applied to obtaining the genomic privacy information. We classify the state-of-the-art genomic privacy-preserving alignment methods into three different scenarios: large-scale reads mapping, encrypted genomic datasets querying and genetic testing to ease privacy threats. A comprehensive analysis of these approaches has been carried out to evaluate the computation and communication complexity as well as the privacy requirements. The survey provides the researchers with the current trends and the insights on the significance and challenges of privacy issues in genomic data alignment.

Short Linear Motifs Characterizing Snake Venom and Mammalian Phospholipases A2

Snake venom phospholipases A2 (PLA2s) have sequences and structures very similar to those of mammalian group I and II secretory PLA2s, but they possess many toxic properties, ranging from the inhibition of coagulation to the blockage of nerve transmission, and the induction of muscle necrosis. The biological properties of these proteins are not only due to their enzymatic activity, but also to protein–protein interactions which are still unidentified. Here, we compare sequence alignments of snake venom and mammalian PLA2s, grouped according to their structure and biological activity, looking for differences that can justify their different behavior. This bioinformatics analysis has evidenced three distinct regions, two central and one C-terminal, having amino acid compositions that distinguish the different categories of PLA2s. In these regions, we identified short linear motifs (SLiMs), peptide modules involved in protein–protein interactions, conserved in mammalian and not in snake venom PLA2s, or vice versa. The different content in the SLiMs of snake venom with respect to mammalian PLA2s may result in the formation of protein membrane complexes having a toxic activity, or in the formation of complexes whose activity cannot be blocked due to the lack of switches in the toxic PLA2s, as the motif recognized by the prolyl isomerase Pin1.

The bird's-eye view: A data-driven approach to understanding patient journeys from claims data

OBJECTIVE

In preference-sensitive conditions such as back pain, there can be high levels of variability in the trajectory of patient care. We sought to develop a methodology that extracts a realistic and comprehensive understanding of the patient journey using medical and pharmaceutical insurance claims data.

MATERIALS AND METHODS

We processed a sample of 10 000 patient episodes (comprised of 113 215 back pain-related claims) into strings of characters, where each letter corresponds to a distinct encounter with the healthcare system. We customized the Levenshtein edit distance algorithm to evaluate the level of similarity between each pair of episodes based on both their content (types of events) and ordering (sequence of events). We then used clustering to extract the main variations of the patient journey.

RESULTS

The algorithm resulted in 12 comprehensive and clinically distinct patterns (clusters) of patient journeys that represent the main ways patients are diagnosed and treated for back pain. We further characterized demographic and utilization metrics for each cluster and observed clear differentiation between the clusters in terms of both clinical content and patient characteristics.

DISCUSSION

Despite being a complex and often noisy data source, administrative claims provide a unique longitudinal overview of patient care across multiple service providers and locations. This methodology leverages claims to capture a data-driven understanding of how patients traverse the healthcare system.

CONCLUSIONS

When tailored to various conditions and patient settings, this methodology can provide accurate overviews of patient journeys and facilitate a shift toward high-quality practice patterns.

AASRA: an anchor alignment-based small RNA annotation pipeline†

Small noncoding RNAs deep sequencing (sncRNA-Seq) has become a routine for sncRNA detection and quantification. However, the software packages currently available for sncRNA annotation can neither recognize sncRNA variants in the sequencing reads, nor annotate all known sncRNA simultaneously. Here, we report a novel anchor alignment-based small RNA annotation (AASRA) software package (https://github.com/biogramming/AASRA). AASRA represents an all-in-one sncRNA annotation pipeline, which allows for high-speed, simultaneous annotation of all known sncRNA species with the capability to distinguish mature from precursor microRNAs, and to identify novel sncRNA variants in the sncRNA-Seq sequencing reads.

Elizabethkingia Intra-Abdominal Infection and Related Trimethoprim-Sulfamethoxazole Resistance: A Clinical-Genomic Study

(1) Background: Elizabethkingia spp. is an emerging nosocomial pathogen which causes mostly blood stream infection and nosocomial pneumonia. Among Elizabethkingia species, Elizabethkingia anophelis is the major pathogen, but misidentification as Elizabethkingia meningoseptica is a common problem. Elizabethkingia also possesses broad antibiotic resistance, resulting in high morbidity and mortality of the infection. The aim of our study was to review Elizabethkingia intra-abdominal infections and investigate resistance mechanisms against TMP/SMX in Elizabethkingia anophelis by whole genome sequencing. (2) Methods: We retrospectively searched records of patients with Elizabethkingia intra-abdominal infection between 1990 and 2019. We also conducted whole genome sequencing for a TMP/SMX-resistant Elizabethkingia anophelis to identify possible mechanisms of resistance. (3) Results: We identified a total of nine cases of Elizabethkingia intra-abdominal infection in a review of the literature, including our own case. The cases included three biliary tract infections, three CAPD-related infection, two with infected ascites, and two postoperation infections. Host factor, indwelling-catheter, and previous invasive procedure, including surgery, play important roles in Elizabethkingia infection. Removal of the catheter is crucial for successful treatment. Genomic analysis revealed accumulated mutations leading to TMP/SMX-resistance in folP. (4) Conclusions: Patients with underlying disease and indwelling catheter are more susceptible to Elizabethkingia intra-abdominal infection, and successful treatment requires removal of the catheter. The emerging resistance to TMP/SMX may be related to accumulated mutations in folP.

Molecular Basis of the Anticancer and Antibacterial Properties of CecropinXJ Peptide: An In Silico Study

Esophageal cancer is an aggressive lethal malignancy causing thousands of deaths every year. While current treatments have poor outcomes, cecropinXJ (CXJ) is one of the very few peptides with demonstrated in vivo activity. The great interest in CXJ stems from its low toxicity and additional activity against most ESKAPE bacteria and fungi. Here, we present the first study of its mechanism of action based on molecular dynamics (MD) simulations and sequence-property alignment. Although unstructured in solution, predictions highlight the presence of two helices separated by a flexible hinge containing P24 and stabilized by the interaction of W2 with target biomembranes: an amphipathic helix-I and a poorly structured helix-II. Both MD and sequence-property alignment point to the important role of helix I in both the activity and the interaction with biomembranes. MD reveals that CXJ interacts mainly with phosphatidylserine (PS) but also with phosphatidylethanolamine (PE) headgroups, both found in the outer leaflet of cancer cells, while salt bridges with phosphate moieties are prevalent in bacterial biomimetic membranes composed of PE, phosphatidylglycerol (PG) and cardiolipin (CL). The antibacterial activity of CXJ might also explain its interaction with mitochondria, whose phospholipid composition recalls that of bacteria and its capability to induce apoptosis in cancer cells.

Antimicrobial Peptide K11 Selectively Recognizes Bacterial Biomimetic Membranes and Acts by Twisting Their Bilayers

K11 is a synthetic peptide originating from the introduction of a lysine residue in position 11 within the sequence of a rationally designed antibacterial scaffold. Despite its remarkable antibacterial properties towards many ESKAPE bacteria and its optimal therapeutic index (320), a detailed description of its mechanism of action is missing. As most antimicrobial peptides act by destabilizing the membranes of the target organisms, we investigated the interaction of K11 with biomimetic membranes of various phospholipid compositions by liquid and solid-state NMR. Our data show that K11 can selectively destabilize bacterial biomimetic membranes and torque the surface of their bilayers. The same is observed for membranes containing other negatively charged phospholipids which might suggest additional biological activities. Molecular dynamic simulations reveal that K11 can penetrate the membrane in four steps: after binding to phosphate groups by means of the lysine residue at the N-terminus (anchoring), three couples of lysine residues act subsequently to exert a torque in the membrane (twisting) which allows the insertion of aromatic side chains at both termini (insertion) eventually leading to the flip of the amphipathic helix inside the bilayer core (helix flip and internalization).

A fusion method based on alignment software with SNP and Indel detection methods

BACKGROUND

With the advent of the second generation sequencing technology, the discovery of sequence alignment and sequence variation is a long-standing challenge.

RESULTS

A method based on general alignment software, SNP and Indel software tools was proposed in this paper. By comparing the advantages of traditional alignment software, we can produce the best alignment. SNP and Indel detection tools fusion research found that different depth of sequencing effect is different. When the sequence depth reaches a certain value, select one of the software for testing.

CONCLUSIONS

Finally, the experimental verification shows that SNP and Indel have certain advantages in the comparison of the effects of the fusion method.

Structural and functional diversity calls for a new classification of ABC transporters

Members of the ATP-binding cassette (ABC) transporter superfamily translocate a broad spectrum of chemically diverse substrates. While their eponymous ATP-binding cassette in the nucleotide-binding domains (NBDs) is highly conserved, their transmembrane domains (TMDs) forming the translocation pathway exhibit distinct folds and topologies, suggesting that during evolution the ancient motor domains were combined with different transmembrane mechanical systems to orchestrate a variety of cellular processes. In recent years, it has become increasingly evident that the distinct TMD folds are best suited to categorize the multitude of ABC transporters. We therefore propose a new ABC transporter classification that is based on structural homology in the TMDs.

The impact of post-alignment processing procedures on whole-exome sequencing data

The use of post-alignment procedures has been suggested to prevent the identification of false-positives in massive DNA sequencing data. Insertions and deletions are most likely to be misinterpreted by variant calling algorithms. Using known genetic variants as references for post-processing pipelines can minimize mismatches. They allow reads to be correctly realigned and recalibrated, resulting in more parsimonious variant calling. In this work, we aim to investigate the impact of using different sets of common variants as references to facilitate variant calling from whole-exome sequencing data. We selected reference variants from common insertions and deletions available within the 1K Genomes project data and from databases from the Latin American Database of Genetic Variation (LatinGen). We used the Genome Analysis Toolkit to perform post-processing procedures like local realignment, quality recalibration procedures, and variant calling in whole exome samples. We identified an increased number of variants from the call set for all groups when no post-processing procedure was performed. We found that there was a higher concordance rate between variants called using 1K Genomes and LatinGen. Therefore, we believe that the increased number of rare variants identified in the analysis without realignment or quality recalibration indicated that they were likely false-positives.

Predicted structural differences of four fertility-related Y-chromosome proteins in Macaca mulatta, M. fascicularis, and their Indochinese hybrids

Species in the genus Macaca typically live in multimale-multifemale social groups with male macaques exhibiting some of the largest testis: body weight ratios among primates. Males are believed to experience intense levels of sperm competition. Several spermatogenesis genes are located on the Y-chromosome and, interestingly, occasional hybridization between two species has led to the introgression of the rhesus macaque (Macaca mulatta) Y-chromosome deep into the range of the long-tailed macaque (M. fascicularis). These observations have led to the prediction that the successful introgression of the rhesus Y-haplotype is due to functional differences in spermatogenesis genes compared to those of the native long-tailed Y-haplotype. We examine here four Y-chromosomal loci-RBMY, XKRY, and two nearly identical copies of CDY-and their corresponding protein sequences. The genes were surveyed in representative animals from north of, south of, and within the rhesus x long-tailed introgression zone. Our results show a series of non-synonymous amino acid substitutions present between the two Y-haplotypes. Protein structure modeling via I-TASSER revealed different folding patterns between the two species' Y-proteins, and functional predictions via TreeSAAP further reveal physicochemical differences as a result of non-synonymous substitutions. These differences inform our understanding of the evolution of primate Y-proteins involved in spermatogenesis and, in turn, have biomedical implications for human male fertility.

Spectral Jaccard Similarity: A New Approach to Estimating Pairwise Sequence Alignments

Pairwise sequence alignment is often a computational bottleneck in genomic analysis pipelines, particularly in the context of third-generation sequencing technologies. To speed up this process, the pairwise k-mer Jaccard similarity is sometimes used as a proxy for alignment size in order to filter pairs of reads, and min-hashes are employed to efficiently estimate these similarities. However, when the k-mer distribution of a dataset is significantly non-uniform (e.g., due to GC biases and repeats), Jaccard similarity is no longer a good proxy for alignment size. In this work, we introduce a min-hash-based approach for estimating alignment sizes called Spectral Jaccard Similarity, which naturally accounts for uneven k-mer distributions. The Spectral Jaccard Similarity is computed by performing a singular value decomposition on a min-hash collision matrix. We empirically show that this new metric provides significantly better estimates for alignment sizes, and we provide a computationally efficient estimator for these spectral similarity scores.

Alternative N-terminal regions of Drosophila myosin heavy chain II regulate communication of the purine binding loop with the essential light chain

We investigated the biochemical and biophysical properties of one of the four alternative exon-encoded regions within the Drosophila myosin catalytic domain. This region is encoded by alternative exons 3a and 3b and includes part of the N-terminal β-barrel. Chimeric myosin constructs (IFI-3a and EMB-3b) were generated by exchanging the exon 3-encoded areas between native slow embryonic body wall (EMB) and fast indirect flight muscle myosin isoforms (IFI). We found that this exchange alters the kinetic properties of the myosin S1 head. The ADP release rate (k_-D ) in the absence of actin is completely reversed for each chimera compared with the native isoforms. Steady-state data also suggest a reciprocal shift, with basal and actin-activated ATPase activity of IFI-3a showing reduced values compared with wild-type (WT) IFI, whereas for EMB-3b these values are increased compared with wild-type (WT) EMB. In the presence of actin, ADP affinity (K_AD ) is unchanged for IFI-3a, compared with IFI, but ADP affinity for EMB-3b is increased, compared with EMB, and shifted toward IFI values. ATP-induced dissociation of acto-S1 (K₁k ₊₂ ) is reduced for both exon 3 chimeras. Homology modeling, combined with a recently reported crystal structure for Drosophila EMB, indicates that the exon 3-encoded region in the myosin head is part of the communication pathway between the nucleotide binding pocket (purine binding loop) and the essential light chain, emphasizing an important role for this variable N-terminal domain in regulating actomyosin crossbridge kinetics, in particular with respect to the force-sensing properties of myosin isoforms.

Evaluating the effect of reference genome divergence on the analysis of empirical RADseq datasets

The advent of high-throughput sequencing (HTS) has made genomic-level analyses feasible for nonmodel organisms. A critical step of many HTS pipelines involves aligning reads to a reference genome to identify variants. Despite recent initiatives, only a fraction of species has publically available reference genomes. Therefore, a common practice is to align reads to the genome of an organism related to the target species; however, this could affect read alignment and bias genotyping. In this study, I conducted an experiment using empirical RADseq datasets generated for two species of salmonids (Actinopterygii; Teleostei; Salmonidae) to address these questions. There are currently reference genomes for six salmonids of varying phylogenetic distance. I aligned the RADseq data to all six genomes and identified variants with several different genotypers, which were then fed into population genetic analyses. Increasing phylogenetic distance between target species and reference genome reduced the proportion of reads that successfully aligned and mapping quality. Reference genome also influenced the number of SNPs that were generated and depth at those SNPs, although the affect varied by genotyper. Inferences of population structure were mixed: increasing reference genome divergence reduced estimates of differentiation but similar patterns of population relationships were found across scenarios. These findings reveal how the choice of reference genome can influence the output of bioinformatic pipelines. It also emphasizes the need to identify best practices and guidelines for the burgeoning field of biodiversity genomics.

Thousands of missing variants in the UK Biobank are recoverable by genome realignment

The UK Biobank is an unprecedented resource for human disease research. In March 2019, 49,997 exomes were made publicly available to investigators. Here we note that thousands of variant calls are unexpectedly absent from this dataset, with 641 genes showing zero variation. We show that the reason for this was an erroneous read alignment to the GRCh38 reference. The missing variants can be recovered by modifying read alignment parameters to correctly handle the expanded set of contigs available in the human genome reference. Given the size and complexity of such population scale datasets, we propose a simple heuristic that can uncover systematic errors using summary data accessible to most investigators.

A guideline for homology modeling of the proteins from newly discovered betacoronavirus, 2019 novel coronavirus (2019-nCoV)

During an outbreak of respiratory diseases including atypical pneumonia in Wuhan, a previously unknown β‐coronavirus was detected in patients. The newly discovered coronavirus is similar to some β‐coronaviruses found in bats but different from previously known SARS‐CoV and MERS‐CoV. High sequence identities and similarities between 2019‐nCoV and SARS‐CoV were found. In this study, we searched the homologous templates of all nonstructural and structural proteins of 2019‐nCoV. Among the nonstructural proteins, the leader protein (nsp1), the papain‐like protease (nsp3), the nsp4, the 3C‐like protease (nsp5), the nsp7, the nsp8, the nsp9, the nsp10, the RNA‐directed RNA polymerase (nsp12), the helicase (nsp13), the guanine‐N7 methyltransferase (nsp14), the uridylate‐specific endoribonuclease (nsp15), the 2'‐O‐methyltransferase (nsp16), and the ORF7a protein could be built on the basis of homology templates. Among the structural proteins, the spike protein (S‐protein), the envelope protein (E‐protein), and the nucleocapsid protein (N‐protein) can be constructed based on the crystal structures of the proteins from SARS‐CoV. It is known that PL‐Pro, 3CL‐Pro, and RdRp are important targets for design antiviral drugs against 2019‐nCoV. And S protein is a critical target candidate for inhibitor screening or vaccine design against 2019‐nCoV because coronavirus replication is initiated by the binding of S protein to cell surface receptors. It is believed that these proteins should be useful for further structure‐based virtual screening and related computer‐aided drug development and vaccine design.

High sequence identities between 2019‐nCoV and SARS‐CoV were found. Homology templates of all structural proteins of 2019‐nCoV were identified. Homology templates of all nonstructural proteins of 2019‐nCoV were identified.

Toward a Dynamic Threshold for Quality Score Distortion in Reference-Based Alignment

The intrinsic high-entropy sequence metadata, known as quality scores, is largely the cause of the substantial size of sequence data files. Yet, there is no consensus on a viable reduction of the resolution of the quality score scale, arguably because of collateral side effects. In this article, we leverage on the penalty functions of HISAT2 aligner to rebin the quality score scale in such a way as to avoid any impact on sequence alignment, identifying alongside a distortion threshold for "safe" quality score representation. We tested our findings on whole-genome and RNA-seq data, and contrasted the results with three methods for lossy compression of the quality scores.

Guidelines for systematic reporting of sequence alignments

Bioinformatics methods are increasingly needed and used to analyze and interpret extensive datasets many of which are produced by diverse high-throughput technologies. Unfortunately, it is quite common that published articles do not contain sufficient information to allow the reader to fully comprehend and repeat computational and other studies. Guidelines were developed for reporting studies and results from sequence alignment. Brief and concise checklist of required data items was compiled making it easy to provide necessary details. Implementation of the guidelines requires similar meticulous attitude toward details as other parts of publications. If the journal does not allow reporting full details in the main article, it can be provided in supplementary material. It is important to make the alignments available. Systematic and detailed description of bioinformatics analyses adds to the value of papers and makes it easier for the scientific community to evaluate, understand, verify, and extend the published articles and their results.

OptCAM: An ultra-fast all-optical architecture for DNA variant discovery

Nowadays, the accelerated expansion of genetic data challenges speed of current DNA sequence alignment algorithms due to their electrical implementations. Essential needs of an efficient and accurate method for DNA variant discovery demand new approaches for parallel processing in real time. Fortunately, photonics, as an emerging technology in data computing, proposes optical correlation as a fast similarity measurement algorithm; while complexity of existing local alignment algorithms severely limits their applicability. Hence, in this paper, employing optical correlation for global alignment, we present an optical processing approach for local DNA sequence alignment to benefit both high-speed processing and operational parallelism, inherently exist in optics. The proposed method, named as OptCAM, utilizes amplitude and wavelength of the optical signals, to accurately locate mutations through three main procedures. Furthermore, an all-optical implementation of the OptCAM method is proposed consisting of three units, corresponding to the three OptCAM procedures. Performing considerably fast processes by passing optical signals through high-throughput photonic devices, OptCAM avoids various limitations of electrical implementations. Accuracy and efficiency of the OptCAM method and its optical implementation are validated through numerical simulation by a gold standard simulation benchmark. The results indicate the proposed method is significantly faster than its electrical counterparts, in both single node and grid computation.