Borrelia PeptideAtlas: A proteome resource of common Borrelia burgdorferi isolates for Lyme research.

Lyme disease, caused by an infection with the spirochete Borrelia burgdorferi, is the most common vector-borne disease in North America. B. burgdorferi strains harbor extensive genomic and proteomic variability and further comparison is key to understanding the spirochetes infectivity and biological impacts of identified sequence variants. To achieve this goal, both transcript and mass spectrometry (MS)-based proteomics was applied to assemble peptide datasets of laboratory strains B31, MM1, B31-ML23, infective isolates B31-5A4, B31-A3, and 297, and other public datasets, to provide a publicly available Borrelia PeptideAtlas http://www.peptideatlas.org/builds/borrelia/. Included is information on total proteome, secretome, and membrane proteome of these B. burgdorferi strains. Proteomic data collected from 35 different experiment datasets, with a total of 855 mass spectrometry runs, identified 76,936 distinct peptides at a 0.1% peptide false-discovery-rate, which map to 1,221 canonical proteins (924 core canonical and 297 noncore canonical) and covers 86% of the total base B31 proteome. The diverse proteomic information from multiple isolates with credible data presented by the Borrelia PeptideAtlas can be useful to pinpoint potential protein targets which are common to infective isolates and may be key in the infection process.

A CRISPR-enhanced metagenomic NGS test to improve pandemic preparedness.

The lack of preparedness for detecting and responding to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pathogen (i.e., COVID-19) has caused enormous harm to public health and the economy. Testing strategies deployed on a population scale at day zero, i.e., the time of the first reported case, would be of significant value. Next-generation sequencing (NGS) has such capabilities; however, it has limited detection sensitivity for low-copy-number pathogens. Here, we leverage the CRISPR-Cas9 system to effectively remove abundant sequences not contributing to pathogen detection and show that NGS detection sensitivity of SARS-CoV-2 approaches that of RT-qPCR. The resulting sequence data can also be used for variant strain typing, co-infection detection, and individual human host response assessment, all in a single molecular and analysis workflow. This NGS work flow is pathogen agnostic and, therefore, has the potential to transform how large-scale pandemic response and focused clinical infectious disease testing are pursued in the future.

Interrogating the Human Diplome: Computational Methods, Emerging Applications, and Challenges.

Human DNA sequencing protocols have revolutionized human biology, biomedical science, and clinical practice, but still have very important limitations. One limitation is that most protocols do not separate or assemble (i.e., "phase") the nucleotide content of each of the maternally and paternally derived chromosomal homologs making up the 22 autosomal pairs and the chromosomal pair making up the pseudo-autosomal region of the sex chromosomes. This has led to a dearth of studies and a consequent underappreciation of many phenomena of fundamental importance to basic and clinical genomic science. We discuss a few protocols for obtaining phase information as well as their limitations, including those that could be used in tumor phasing settings. We then describe a number of biological and clinical phenomena that require phase information. These include phenomena that require precise knowledge of the nucleotide sequence in a chromosomal segment from germline or somatic cells, such as DNA binding events, and insight into unique cis vs. trans-acting functionally impactful variant combinations-for example, variants implicated in a phenotype governed by compound heterozygosity. In addition, we also comment on the need for reliable and consensus-based diploid-context computational workflows for variant identification as well as the need for laboratory-based functional verification strategies for validating cis vs. trans effects of variant combinations. We also briefly describe available resources, example studies, as well as areas of further research, and ultimately argue that the science behind the study of human diploidy, referred to as "diplomics," which will be enabled by nucleotide-level resolution of phased genomes, is a logical next step in the analysis of human genome biology.

Nonadditive gene expression is correlated with nonadditive phenotypic expression in interspecific triploid hybrids of willow (Salix spp.).

Many studies have highlighted the complex and diverse basis for heterosis in inbred crops. Despite the lack of a consensus model, it is vital that we turn our attention to understanding heterosis in undomesticated, heterozygous, and polyploid species, such as willow (Salix spp.). Shrub willow is a dedicated energy crop bred to be fast-growing and high yielding on marginal land without competing with food crops. A trend in willow breeding is the consistent pattern of heterosis in triploids produced from crosses between diploid and tetraploid species. Here, we test whether differentially expressed genes are associated with heterosis in triploid families derived from diploid Salix purpurea, diploid Salix viminalis, and tetraploid Salix miyabeana parents. Three biological replicates of shoot tips from all family progeny and parents were collected after 12 weeks in the greenhouse and RNA extracted for RNA-Seq analysis. This study provides evidence that nonadditive patterns of gene expression are correlated with nonadditive phenotypic expression in interspecific triploid hybrids of willow. Expression-level dominance was most correlated with heterosis for biomass yield traits and was highly enriched for processes involved in starch and sucrose metabolism. In addition, there was a global dosage effect of parent alleles in triploid hybrids, with expression proportional to copy number variation. Importantly, differentially expressed genes between family parents were most predictive of heterosis for both field and greenhouse collected traits. Altogether, these data will be used to progress models of heterosis to complement the growing genomic resources available for the improvement of heterozygous perennial bioenergy crops.

Predicting antimicrobial mechanism-of-action from transcriptomes: A generalizable explainable artificial intelligence approach.

To better combat the expansion of antibiotic resistance in pathogens, new compounds, particularly those with novel mechanisms-of-action [MOA], represent a major research priority in biomedical science. However, rediscovery of known antibiotics demonstrates a need for approaches that accurately identify potential novelty with higher throughput and reduced labor. Here we describe an explainable artificial intelligence classification methodology that emphasizes prediction performance and human interpretability by using a Hierarchical Ensemble of Classifiers model optimized with a novel feature selection algorithm called Clairvoyance; collectively referred to as a CoHEC model. We evaluated our methods using whole transcriptome responses from Escherichia coli challenged with 41 known antibiotics and 9 crude extracts while depositing 122 transcriptomes unique to this study. Our CoHEC model can properly predict the primary MOA of previously unobserved compounds in both purified forms and crude extracts at an accuracy above 99%, while also correctly identifying darobactin, a newly discovered antibiotic, as having a novel MOA. In addition, we deploy our methods on a recent E. coli transcriptomics dataset from a different strain and a Mycobacterium smegmatis metabolomics timeseries dataset showcasing exceptionally high performance; improving upon the performance metrics of the original publications. We not only provide insight into the biological interpretation of our model but also that the concept of MOA is a non-discrete heuristic with diverse effects for different compounds within the same MOA, suggesting substantial antibiotic diversity awaiting discovery within existing MOA.

Conserved Genomic Terminals of SARS-CoV-2 as Coevolving Functional Elements and Potential Therapeutic Targets.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over 40 million people worldwide, with over 1 million deaths as of October 2020 and with multiple efforts in the development and testing of antiviral drugs and vaccines under way. In order to gain insights into SARS-CoV-2 evolution and drug targets, we investigated how and to what extent the SARS-CoV-2 genome sequence differs from those of other well-characterized human and animal coronavirus genomes, as well as how polymorphic SARS-CoV-2 genomes are generally. We ultimately sought to identify features in the SARS-CoV-2 genome that may contribute to its viral replication, host pathogenicity, and vulnerabilities. Our analyses suggest the presence of unique sequence signatures in the 3' untranslated region (3'-UTR) of betacoronavirus lineage B, which phylogenetically encompasses SARS-CoV-2 and SARS-CoV as well as multiple groups of bat and animal coronaviruses. In addition, we identified genome-wide patterns of variation across different SARS-CoV-2 strains that likely reflect the effects of selection. Finally, we provide evidence for a possible host-microRNA-mediated interaction between the 3'-UTR and human microRNA hsa-miR-1307-3p based on the results of multiple computational target prediction analyses and an assessment of similar interactions involving the influenza A H1N1 virus. This interaction also suggests a possible survival mechanism, whereby a mutation in the SARS-CoV-2 3'-UTR leads to a weakened host immune response. The potential roles of host microRNAs in SARS-CoV-2 replication and infection and the exploitation of conserved features in the 3'-UTR as therapeutic targets warrant further investigation.IMPORTANCE The coronavirus disease 2019 (COVID-19) outbreak is having a dramatic global effect on public health and the economy. As of October 2020, SARS-CoV-2 has been detected in over 189 countries, has infected over 40 million people, and is responsible for more than 1 million deaths. The genome of SARS-CoV-2 is small but complex, and its functions and interactions with human host factors are being studied extensively. The significance of our study is that, using extensive SARS-CoV-2 genome analysis techniques, we identified potential interacting human host microRNA targets that share similarity with those of influenza A virus H1N1. Our study results will allow the development of virus-host interaction models that will enhance our understanding of SARS-CoV-2 pathogenesis and motivate the exploitation of both the interacting viral and host factors as therapeutic targets.

AbGRI4, a novel antibiotic resistance island in multiply antibiotic-resistant Acinetobacter baumannii clinical isolates.

OBJECTIVES: To investigate the genomic context of a novel resistance island (RI) in multiply antibiotic-resistant Acinetobacter baumannii clinical isolates and global isolates. METHODS: Using a combination of long and short reads generated from the Oxford Nanopore and Illumina platforms, contiguous chromosomes and plasmid sequences were determined. BLAST-based analysis was used to identify the RI insertion target. RESULTS: Genomes of four multiply antibiotic-resistant A. baumannii clinical strains, from a US hospital system, belonging to prevalent MLST ST2 (Pasteur scheme) and ST281 (Oxford scheme) clade F isolates were sequenced to completion. A class 1 integron carrying aadB (tobramycin resistance) and aadA2 (streptomycin/spectinomycin resistance) was identified. The class 1 integron was 6.8 kb, bounded by IS26 at both ends, and embedded in a new target location between an α/ß-hydrolase and a reductase. Due to its novel insertion site and unique RI composition, we suggest naming this novel RI AbGRI4. Molecular analysis of global A. baumannii isolates identified multiple AbGRI4 RI variants in non-ST2 clonal lineages, including variations in the resistance gene cassettes, integron backbone and insertion breakpoints at the hydrolase gene. CONCLUSIONS: A novel RI insertion target harbouring a class 1 integron was identified in a subgroup of ST2/ST281 clinical isolates. Variants of the RI suggested evolution and horizontal transfer of the RI across clonal lineages. Long- and short-read hybrid assembly technology completely resolved the genomic context of IS-bounded RIs, which was not possible using short reads alone.

Conserved Genomic Terminals of SARS-CoV-2 as Co-evolving Functional Elements and Potential Therapeutic Targets.

To identify features in the genome of the SARS-CoV-2 pathogen responsible for the COVID-19 pandemic that may contribute to its viral replication, host pathogenicity, and vulnerabilities, we investigated how and to what extent the SARS-CoV-2 genome sequence differs from other well-characterized human and animal coronavirus genomes. Our analyses suggest the presence of unique sequence signatures in the 3'-untranslated region (UTR) of betacoronavirus lineage B, which phylogenetically encompasses SARS-CoV-2, SARS-CoV, as well as multiple groups of bat and animal coronaviruses. In addition, we identified genome-wide patterns of variation across different SARS-CoV-2 strains that likely reflect the effects of selection. Finally, we provide evidence for a possible host microRNA-mediated interaction between the 3'-UTR and human microRNA hsa-miR-1307-3p based on predicted, yet extensive, complementary base-pairings and similar interactions involving the Influenza A H1N1 virus. This interaction also suggests a possible survival mechanism, whereby a mutation in the SARS-CoV-2 3'-UTR leads to a weakened host immune response. The potential roles of host microRNAs in SARS-CoV-2 replication and infection, and the exploitation of conserved features in the 3'-UTR as therapeutic targets warrant further investigation.

Mechanism-of-Action Classification of Antibiotics by Global Transcriptome Profiling.

Antimicrobial resistance (AMR) is an ever-growing public health problem worldwide. The low rate of antibiotic discovery coupled with the rapid spread of drug-resistant bacterial pathogens is causing a global health crisis. To facilitate the drug discovery processes, we present a large-scale study of reference antibiotic challenge bacterial transcriptome profiles, which included 37 antibiotics across 6 mechanisms of actions (MOAs) and provide an economical approach to aid in antimicrobial dereplication in the discovery process. We demonstrate that classical MOAs can be sorted based upon the magnitude of gene expression profiles despite some overlap in the secondary effects of antibiotic exposures across MOAs. Additionally, using gene subsets, we were able to subdivide broad MOA classes into subMOAs. Furthermore, we provide a biomarker gene set that can be used to classify most antimicrobial challenges according to their canonical MOA. We also demonstrate the ability of this rapid MOA diagnostic tool to predict and classify the expression profiles of pure compounds and crude extracts to their expression profile-associated MOA class.

An 'eFP-Seq Browser' for visualizing and exploring RNA sequencing data.

Improvements in next-generation sequencing technologies have resulted in dramatically reduced sequencing costs. This has led to an explosion of '-seq'-based methods, of which RNA sequencing (RNA-seq) for generating transcriptomic data is the most popular. By analysing global patterns of gene expression in organs/tissues/cells of interest or in response to chemical or environmental perturbations, researchers can better understand an organism's biology. Tools designed to work with large RNA-seq data sets enable analyses and visualizations to help generate hypotheses about a gene's function. We present here a user-friendly RNA-seq data exploration tool, called the 'eFP-Seq Browser', that shows the read map coverage of a gene of interest in each of the samples along with 'electronic fluorescent pictographic' (eFP) images that serve as visual representations of expression levels. The tool also summarizes the details of each RNA-seq experiment, providing links to archival databases and publications. It automatically computes the reads per kilobase per million reads mapped expression-level summaries and point biserial correlation scores to sort the samples based on a gene's expression level or by how dissimilar the read map profile is from a gene splice variant, to quickly identify samples with the strongest expression level or where alternative splicing might be occurring. Links to the Integrated Genome Browser desktop visualization tool allow researchers to visualize and explore the details of RNA-seq alignments summarized in eFP-Seq Browser as coverage graphs. We present four cases of use of the eFP-Seq Browser for ABI3, SR34, SR45a and U2AF65B, where we examine expression levels and identify alternative splicing. The URL for the browser is https://bar.utoronto.ca/eFP-Seq_Browser/. OPEN RESEARCH BADGES: This article has earned an Open Data Badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. Tool is at https://bar.utoronto.ca/eFP-Seq_Browser/; RNA-seq data at https://s3.amazonaws.com/iplant-cdn/iplant/home/araport/rnaseq_bam/ and https://s3.amazonaws.com/iplant-cdn/iplant/home/araport/rnaseq_bam/Klepikova/. Code is available at https://github.com/BioAnalyticResource/eFP-Seq-Browser.

Rapid Replacement of Acinetobacter baumannii Strains Accompanied by Changes in Lipooligosaccharide Loci and Resistance Gene Repertoire.

The population structure of health care-associated pathogens reflects patterns of diversification, selection, and dispersal over time. Empirical data detailing the long-term population dynamics of nosocomial pathogens provide information about how pathogens adapt in the face of exposure to diverse antimicrobial agents and other host and environmental pressures and can inform infection control priorities. Extensive sequencing of clinical isolates from one hospital spanning a decade and a second hospital in the Cleveland, OH, metropolitan area over a 3-year time period provided high-resolution genomic analysis of the Acinetobacter baumannii metapopulation. Genomic analysis demonstrated an almost complete replacement of the predominant strain groups with a new, genetically distinct strain group during the study period. The new group, termed clade F, differs from other global clone 2 (GC2) strains of A. baumannii in several ways, including its antibiotic resistance and lipooligosaccharide biosynthesis genes. Clade F strains are part of a large phylogenetic group with broad geographic representation. Phylogenetic analysis of single-nucleotide variants in core genome regions showed that although the Cleveland strains are phylogenetically distinct from those isolated from other locations, extensive intermixing of strains from the two hospital systems was apparent, suggesting either substantial exchange of strains or a shared, but geographically restricted, external pool from which infectious isolates were drawn. These findings document the rapid evolution of A. baumannii strains in two hospitals, with replacement of the predominant clade by a new clade with altered lipooligosaccharide loci and resistance gene repertoires.IMPORTANCE Multidrug-resistant (MDR) A. baumannii is a difficult-to-treat health care-associated pathogen. Knowing the resistance genes present in isolates causing infection aids in empirical treatment selection. Furthermore, knowledge of the genetic background can assist in tracking patterns of transmission to limit the spread of infections in hospitals. The appearance of a new genetic background in A. baumannii strains with a different set of resistance genes and cell surface structures suggests that strong selective pressures exist, even in highly MDR pathogens. Because the new strains have levels of antimicrobial resistance similar to those of the strains that were displaced, we hypothesize that other features, including host colonization and infection, may confer additional selective advantages and contribute to their increased prevalence.

Co-occurrence of Anaerobes in Human Chronic Wounds.

Chronic wounds are wounds that have failed to heal after 3 months of appropriate wound care. Previous reports have identified a diverse collection of bacteria in chronic wounds, and it has been postulated that bacterial profile may contribute to delayed healing. The purpose of this study was to perform a microbiome assessment of the Wound Healing and Etiology (WE-HEAL) Study cohort, including underlying comorbidities less commonly studied in the context of chronic wounds, such as autoimmune diseases, and investigate possible relationships of the wound microbiota with clinical healing trends. We examined chronic wound specimens from 60 patients collected through the WE-HEAL Study using 16S ribosomal RNA gene sequencing. A group of co-occurring obligate anaerobes was identified from taxonomic analysis guided by Dirichlet multinomial mixtures (DMM) modeling. The group includes members of the Gram-positive anaerobic cocci (GPAC) of the Clostridia class (i.e., Anaerococcus, Finegoldia, and Peptoniphilus) and additional strict anaerobes (i.e., Porphyromonas and Prevotella). We showed that the co-occurring group of obligate anaerobes not only co-exists with commonly identified wound species (such as Staphylococcus aureus, Staphylococcus epidermidis, Pseudomonas, Corynebacterium, and Streptococcus), but importantly, they could also predominate the wound microbiota. Furthermore, examination of clinical comorbidities of the WE-HEAL specimens showed that specific obligate and facultative anaerobes were significantly reduced in wounds presented with autoimmune disease. With respect to future healing trends, no association with the wound microbiome community or the abundance of individual wound species could be established. In conclusion, we identified a co-occurring obligate anaerobic community type that predominated some human chronic wounds and underrepresentation of anaerobes in wounds associated with autoimmune diseases. Possible elucidation of host environments or key factors that influence anaerobe colonization warrants further investigation in a larger cohort.

Multidrug resistant pathogens respond differently to the presence of co-pathogen, commensal, probiotic and host cells.

In light of the ongoing antimicrobial resistance crisis, there is a need to understand the role of co-pathogens, commensals, and the local microbiome in modulating virulence and antibiotic resistance. To identify possible interactions that influence the expression of virulence or survival mechanisms in both the multidrug-resistant organisms (MDROs) and human host cells, unique cohorts of clinical isolates were selected for whole genome sequencing with enhanced assembly and full annotation, pairwise co-culturing, and transcriptome profiling. The MDROs were co-cultured in pairwise combinations either with: (1) another MDRO, (2) skin commensals (Staphylococcus epidermidis and Corynebacterium jeikeium), (3) the common probiotic Lactobacillus reuteri, and (4) human fibroblasts. RNA-Seq analysis showed distinct regulation of virulence and antimicrobial resistance gene responses across different combinations of MDROs, commensals, and human cells. Co-culture assays demonstrated that microbial interactions can modulate gene responses of both the target and pathogen/commensal species, and that the responses are specific to the identity of the pathogen/commensal species. In summary, bacteria have mechanisms to distinguish between friends, foe and host cells. These results provide foundational data and insight into the possibility of manipulating the local microbiome when treating complicated polymicrobial wound, intra-abdominal, or respiratory infections.

Comparison of phasing strategies for whole human genomes.

Humans are a diploid species that inherit one set of chromosomes paternally and one homologous set of chromosomes maternally. Unfortunately, most human sequencing initiatives ignore this fact in that they do not directly delineate the nucleotide content of the maternal and paternal copies of the 23 chromosomes individuals possess (i.e., they do not 'phase' the genome) often because of the costs and complexities of doing so. We compared 11 different widely-used approaches to phasing human genomes using the publicly available 'Genome-In-A-Bottle' (GIAB) phased version of the NA12878 genome as a gold standard. The phasing strategies we compared included laboratory-based assays that prepare DNA in unique ways to facilitate phasing as well as purely computational approaches that seek to reconstruct phase information from general sequencing reads and constructs or population-level haplotype frequency information obtained through a reference panel of haplotypes. To assess the performance of the 11 approaches, we used metrics that included, among others, switch error rates, haplotype block lengths, the proportion of fully phase-resolved genes, phasing accuracy and yield between pairs of SNVs. Our comparisons suggest that a hybrid or combined approach that leverages: 1. population-based phasing using the SHAPEIT software suite, 2. either genome-wide sequencing read data or parental genotypes, and 3. a large reference panel of variant and haplotype frequencies, provides a fast and efficient way to produce highly accurate phase-resolved individual human genomes. We found that for population-based approaches, phasing performance is enhanced with the addition of genome-wide read data; e.g., whole genome shotgun and/or RNA sequencing reads. Further, we found that the inclusion of parental genotype data within a population-based phasing strategy can provide as much as a ten-fold reduction in phasing errors. We also considered a majority voting scheme for the construction of a consensus haplotype combining multiple predictions for enhanced performance and site coverage. Finally, we also identified DNA sequence signatures associated with the genomic regions harboring phasing switch errors, which included regions of low polymorphism or SNV density.

Dominance and Sexual Dimorphism Pervade the Salix purpurea L. Transcriptome.

The heritability of gene expression is critical in understanding heterosis and is dependent on allele-specific regulation by local and remote factors in the genome. We used RNA-Seq to test whether variation in gene expression among F1 and F2 intraspecific Salix purpurea progeny is attributable to cis- and trans-regulatory divergence. We assessed the mode of inheritance based on gene expression levels and allele-specific expression for F1 and F2 intraspecific progeny in two distinct tissue types: shoot tip and stem internode. In addition, we explored sexually dimorphic patterns of inheritance and regulatory divergence among F1 progeny individuals. We show that in S. purpurea intraspecific crosses, gene expression inheritance largely exhibits a maternal dominant pattern, regardless of tissue type or pedigree. A significantly greater number of cis- and trans-regulated genes coincided with upregulation of the maternal parent allele in the progeny, irrespective of the magnitude, whereas the paternal allele was higher expressed for genes showing cis × trans or compensatory regulation. Importantly, consistent with previous genetic mapping results for sex in shrub willow, we have delimited sex-biased gene expression to a 2 Mb pericentromeric region on S. purpurea chr15 and further refined the sex determination region. Altogether, our results offer insight into the inheritance of gene expression in S. purpurea as well as evidence of sexually dimorphic expression which may have contributed to the evolution of dioecy in Salix.

HSV-1 clinical isolates with unique in vivo and in vitro phenotypes and insight into genomic differences.

Strain-specific factors contribute in significant but undefined ways to the variable incidence of herpes simplex virus (HSV) recrudescence. Studies that investigate these strain-specific factors are needed. Here, we used qPCR, in vitro assays, and genomic sequencing to identify important relationships between in vitro and clinical phenotypes of unique HSV-1 clinical isolates. Nine HSV-1 isolates from individuals displaying varying reactivation patterns were studied. Isolates associated with frequent recurrent herpes labialis (RHL) (1) displayed higher rates of viral shedding in the oral cavity than those associated with rare RHL and (2) tended to replicate more efficiently at 33 °C than 39 °C. HSV-1 isolates also displayed a more stable phenotype during propagation in U2OS cells than in Vero cells. Draft genome sequences of four isolates and one variant spanning 95.6 to 97.2 % of the genome were achieved, and whole-genome alignment demonstrated that the majority of these isolates clustered with known North American/European isolates. These findings revealed procedures that could help identify unique genotypes and phenotypes associated with HSV-1 isolates, which can be important for determining viral factors critical for regulating HSV-1 reactivation.

Araport11: a complete reannotation of the Arabidopsis thaliana reference genome.

The flowering plant Arabidopsis thaliana is a dicot model organism for research in many aspects of plant biology. A comprehensive annotation of its genome paves the way for understanding the functions and activities of all types of transcripts, including mRNA, the various classes of non-coding RNA, and small RNA. The TAIR10 annotation update had a profound impact on Arabidopsis research but was released more than 5 years ago. Maintaining the accuracy of the annotation continues to be a prerequisite for future progress. Using an integrative annotation pipeline, we assembled tissue-specific RNA-Seq libraries from 113 datasets and constructed 48 359 transcript models of protein-coding genes in eleven tissues. In addition, we annotated various classes of non-coding RNA including microRNA, long intergenic RNA, small nucleolar RNA, natural antisense transcript, small nuclear RNA, and small RNA using published datasets and in-house analytic results. Altogether, we identified 635 novel protein-coding genes, 508 novel transcribed regions, 5178 non-coding RNAs, and 35 846 small RNA loci that were formerly unannotated. Analysis of the splicing events and RNA-Seq based expression profiles revealed the landscapes of gene structures, untranslated regions, and splicing activities to be more intricate than previously appreciated. Furthermore, we present 692 uniformly expressed housekeeping genes, 43% of whose human orthologs are also housekeeping genes. This updated Arabidopsis genome annotation with a substantially increased resolution of gene models will not only further our understanding of the biological processes of this plant model but also of other species.

ThaleMine: A Warehouse for Arabidopsis Data Integration and Discovery.

ThaleMine (https://apps.araport.org/thalemine/) is a comprehensive data warehouse that integrates a wide array of genomic information of the model plant Arabidopsis thaliana. The data collection currently includes the latest structural and functional annotation from the Araport11 update, the Col-0 genome sequence, RNA-seq and array expression, co-expression, protein interactions, homologs, pathways, publications, alleles, germplasm and phenotypes. The data are collected from a wide variety of public resources. Users can browse gene-specific data through Gene Report pages, identify and create gene lists based on experiments or indexed keywords, and run GO enrichment analysis to investigate the biological significance of selected gene sets. Developed by the Arabidopsis Information Portal project (Araport, https://www.araport.org/), ThaleMine uses the InterMine software framework, which builds well-structured data, and provides powerful data query and analysis functionality. The warehoused data can be accessed by users via graphical interfaces, as well as programmatically via web-services. Here we describe recent developments in ThaleMine including new features and extensions, and discuss future improvements. InterMine has been broadly adopted by the model organism research community including nematode, rat, mouse, zebrafish, budding yeast, the modENCODE project, as well as being used for human data. ThaleMine is the first InterMine developed for a plant model. As additional new plant InterMines are developed by the legume and other plant research communities, the potential of cross-organism integrative data analysis will be further enabled.

A novel method of consensus pan-chromosome assembly and large-scale comparative analysis reveal the highly flexible pan-genome of Acinetobacter baumannii.

BACKGROUND: Infections by pan-drug resistant Acinetobacter baumannii plague military and civilian healthcare systems. Previous A. baumannii pan-genomic studies used modest sample sizes of low diversity and comparisons to a single reference genome, limiting our understanding of gene order and content. A consensus representation of multiple genomes will provide a better framework for comparison. A large-scale comparative study will identify genomic determinants associated with their diversity and adaptation as a successful pathogen. RESULTS: We determine draft-level genomic sequence of 50 diverse military isolates and conduct the largest bacterial pan-genome analysis of 249 genomes. The pan-genome of A. baumannii is open when the input genomes are normalized for diversity with 1867 core proteins and a paralog-collapsed pan-genome size of 11,694 proteins. We developed a novel graph-based algorithm and use it to assemble the first consensus pan-chromosome, identifying both the order and orientation of core genes and flexible genomic regions. Comparative genome analyses demonstrate the existence of novel resistance islands and isolates with increased numbers of resistance island insertions over time, from single insertions in the 1950s to triple insertions in 2011. Gene clusters responsible for carbon utilization, siderophore production, and pilus assembly demonstrate frequent gain or loss among isolates. CONCLUSIONS: The highly variable and dynamic nature of the A. baumannii genome may be the result of its success in rapidly adapting to both abiotic and biotic environments through the gain and loss of gene clusters controlling fitness. Importantly, some archaic adaptation mechanisms appear to have reemerged among recent isolates.

PROVEAN web server: a tool to predict the functional effect of amino acid substitutions and indels.

UNLABELLED: We present a web server to predict the functional effect of single or multiple amino acid substitutions, insertions and deletions using the prediction tool PROVEAN. The server provides rapid analysis of protein variants from any organisms, and also supports high-throughput analysis for human and mouse variants at both the genomic and protein levels. AVAILABILITY AND IMPLEMENTATION: The web server is freely available and open to all users with no login requirements at http://provean.jcvi.org. CONTACT: achan@jcvi.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.