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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.

The lack of preparedness for detecting the highly infectious SARS-CoV-2 pathogen, the pathogen responsible for the COVID-19 disease, has caused enormous harm to public health and the economy. It took ∼60 days for the first reverse transcription quantitative polymerase chain reaction (RT-qPCR) tests for SARS-CoV-2 infection developed by the United States Centers for Disease Control (CDC) to be made publicly available. It then took >270 days to deploy 800,000 of these tests at a time when the estimated actual testing needs required over 6 million tests per day. Testing was therefore limited to individuals with symptoms or in close contact with confirmed positive cases. Testing strategies deployed on a population scale at ‘Day Zero’ i.e., at the time of the first reported case, would be of significant value. Next Generation Sequencing (NGS) has such Day Zero capabilities with the potential for broad and large-scale testing. However, it has limited detection sensitivity for low copy numbers of pathogens which may be present. Here we demonstrate that by using CRISPR-Cas9 to remove abundant sequences that do not contribute to pathogen detection, NGS detection sensitivity of COVID-19 is comparable to RT-qPCR. In addition, we show that this assay can be used for variant strain typing, co-infection detection, and individual human host response assessment, all in a single workflow using existing open-source analysis pipelines. This NGS workflow is pathogen agnostic, and therefore has the potential to transform how both large-scale pandemic response and focused clinical infectious disease testing are pursued in the future.SIGNIFICANCE STATEMENTThe lack of preparedness for detecting infectious pathogens has had a devastating effect on the global economy and society. Thus, a ‘Day Zero’ testing strategy, that can be deployed at the first reported case and expanded to population scale, is required. Next generation sequencing enables Day Zero capabilities but is inadequate for detecting low levels of pathogen due to abundant sequences of little biological interest. By applying the CRISPR-Cas system to remove these sequences in vitro, we show sensitivity of pathogen detection equivalent to RT-qPCR. The workflow is pathogen agnostic, and enables detection of strain types, co-infections and human host response with a single workflow and open-source analysis tools. These results highlight the potential to transform future large-scale pandemic response.

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 S. purpurea, diploid S. viminalis, and tetraploid S. 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.

Summary 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 http://sps:urlprefix::https; RNA‐seq data at http://sps:urlprefix::https and http://sps:urlprefix::https. Code is available at http://sps:urlprefix::https, Significance Statement We present a tool, the eFP‐Seq Browser, for rapidly identifying RNA sequencing samples with strong expression levels of a given gene, or where the read maps for a given gene/sample best match a particular gene model. Details can be called up with convenient links to the Integrated Genome Browser.

MEF2C has been shown to be a critical transcription factor for neurodevelopment, whose loss-of-function mutation in humans results in MEF2C haploinsufficiency syndrome (MHS), a severe form of autism spectrum disorder (ASD)/intellectual disability (ID). Here, we use patient hiPSC-derived cerebrocortical neurons and cerebral organoids to characterize MHS deficits. Unexpectedly, we found an aberrant micro-RNA-mediated gliogenesis pathway that contributes to decreased neurogenesis. We also demonstrate network-level hyperexcitability in neurons, as evidenced by excessive synaptic and extrasynaptic activity contributing to excitatory/inhibitory (E/I) imbalance. Notably, the extrasynaptic NMDA receptor antagonist, NitroSynapsin, corrects this aberrant electrical activity associated with abnormal phenotypes. During neurodevelopment, MEF2C regulates many ASD-associated gene networks suggesting that our approach may lead to personalized therapy for multiple forms of ASD.One sentence summaryAutism-like MEF2C+/- patient hiPSC models show miRNA-mediated overproduction of astrocytes and hyperactivity of neurons.

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., Author summary As antimicrobial resistance is on the rise, the need for compounds with novel targets or mechanisms-of-action [MOA] are of the utmost importance from the standpoint of public health. A major bottleneck in drug discovery is the ability to rapidly screen candidate compounds for precise MOA activity as current approaches are expensive, time consuming, and are difficult to implement in high-throughput. To alleviate this bottleneck in drug discovery, we developed a human interpretable artificial intelligence classification framework that can be used to build highly accurate and flexible predictive models. In this study, we investigated antimicrobial MOA through the transcriptional responses of Escherichia coli challenged with 41 known antibiotic compounds, 9 crude extracts, and a recently discovered (circa 2019) compound, darobactin, with novel MOA activity. We implemented a highly stringent Leave Compound Out Cross-Validation procedure to stress-test our predictive models by simulating the scenario of observing novel compounds. Furthermore, we developed a versatile feature selection algorithm, Clairvoyance, that we apply to our hierarchical ensemble of classifiers framework to build high performance explainable machine-learning models. Although the methods in this study were developed and stress-tested to predict the primary MOA from transcriptomic responses in E. coli, we designed these methods for general application to any classification problem and open-sourced the implementations in our Soothsayer Python package. We further demonstrate the versatility of these methods by deploying them on recent Mycobacterium smegmatis metabolomic and E. coli transcriptomics datasets to predict MOA with high accuracy.

The CoV disease 2019 (COVID-19) infectious disease 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., 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.

MicroRNAs (miRNAs) are small non-coding endogenous riboregulators that play significant roles in plant growth, development, metabolism, defense, and stress responses. Upland cotton is best known for its economic value as natural fiber and oil. It is also an important model for genome evolution, polyploidy effects, cell growth, and cell wall biosynthesis. The polyploid species, Gossypium hirsutum L. (2n = 52), evolved from two progenitors (2n = 26), one contributing an ancestral genome similar to A genomes of G. herbaceum and G. arboreum, and the other like the D genome of G. raimondii. There is much to be learned about Gossypium miRNAs and their gene targets, about the effects of polyploidy and their practical ramifications. In this study, small-RNA (sRNA) libraries from four Gossypium species and three tissue libraries (seed, seedling, and leaf) from G. hirsutum were constructed and analyzed using high-throughput sequencing with Illumina/MiSeq then computational prediction by MIREAP. Results showed 245 known miRNAs belonging to 67 miRNA families and 149 novel (non-redundant and redundant) miRNAs derived from 394 genomic loci. This unified study identified 21 and 33 conserved miRNA families across four Gossypium species and three tissue libraries, respectively. Similar to canonical miRNAs, the 5′ of novel miRNAs had the higher preference for U and A residues. In this study, 551 potential target genes were predicted in 45 conserved miRNA families, while 439 targets were associated with 113 novel miRNAs. The majority of the conserved (34%) and novel (22%) miRNA targets identified belonged to cellular processes and signaling. However, the functional diversity of novel miRNA targets is attributed to the tissue and species bias. Most of the identified targets were regulated by mRNA cleavage than by translational repression. These results provide a basis for better understanding regulatory networks in upland cotton (G. hirsutum) and its closest progenitors. Keywords: Cotton, Progenitor, Sequencing, Prediction, MIREAP, sRNA, miRNA, Family, Known, Novel, Gene regulation, Target

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.

Summary 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.

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/β-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.

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., 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.

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., 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.

In clinical practice, point-of-care diagnostic testing has progressed rapidly in the last decade. For the field of wound care, there is a compelling need to develop rapid alternatives for bacterial identification in the clinical setting, where it generally takes over 24 hours to receive a positive identification. Even new molecular and biochemical identification methods require an initial incubation period of several hours to obtain a sufficient number of cells prior to performing the analysis. Here we report the use of an inexpensive, disposable electrochemical sensor to detect pyocyanin, a unique, redox-active quorum sensing molecule released by Pseudomonas aeruginosa, in wound fluid from patients with chronic wounds enrolled in the WE-HEAL Study. By measuring the metabolite excreted by the cells, this electrochemical detection strategy eliminates sample preparation, takes less than a minute to complete, and requires only 7.5 μL of sample to complete the analysis. The electrochemical results were compared against 16S rRNA profiling using 454 pyrosequencing. Blind identification yielded 9 correct matches, 2 false negatives, and 3 false positives giving a sensitivity of 71% and specificity of 57% for detection of Pseudomonas. Ongoing enhancement and development of this approach with a view to develop a rapid point-of-care diagnostic tool is planned.

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., Author summary Humans are a diploid species that inherit one set of chromosomes paternally and one set of chromosomes maternally. Separating the nucleotide content of the maternally and paternally-derived chromosomes for an individual, i.e., ‘phasing’ that individual’s genome, is not trivial with today’s sequencing technologies. This is in part due to the fact that most available sequencing technologies generate short sequencing reads that make it hard to assemble individual homologous chromosome pairs. Phase information can be crucial for putting into context the likely functional consequences of DNA sequence variants as well as certain evolutionary and population genetics phenomena. In order to assess the reliability of current sequencing-based phasing strategies, we compared 11 different approaches using a public domain reference genome as a test case. These phasing strategies included laboratory-based experimental techniques as well as purely computational approaches. Importantly, our comparisons show that a hybrid or combined approach that leverages population-based phasing via the SHAPEIT software suite works well and can be improved with the addition of genome-wide sequence read or parental genotype data.

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.

Castor bean (Ricinus communis) was the first plant species with its genome sequenced in the spurge family which also includes cassava, rubber tree, and physic nut. Castor bean is a unique plant species because the seeds are a primary source for the natural product castor oil that contains an unusual fatty acid of economic interest, as well as ricin, the world’s deadliest toxin to humans. A draft version of the castor bean genome has been produced using a conventional clone-based and paired-end sequencing approach that reached a sequence coverage of 4.6-fold. Based on the genome sequence assembly, members of the ricin gene family and key oil synthesis genes were identified in a comprehensive manner, representing an important resource for future trait improvement. Importantly, comparative genomics analysis of the castor bean genome with other dicotyledonous plant genomes supported the presence of a conserved ancient hexaploidization event shared throughout the dicot lineage.

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.

Summary: 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.

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.

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, noncoding RNA, and small RNA. The most recent annotation update (TAIR10) released more than five years ago had a profound impact on Arabidopsis research. 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 noncoding RNA including small RNA, long intergenic RNA, small nucleolar RNA, natural antisense transcript, small nuclear RNA, and microRNA using published datasets and in-house analytic results. Altogether, we identified 738 novel protein-coding genes, 508 novel transcribed regions, 5051 non-coding genes, and 35846 small-RNA loci that formerly eluded annotation. Analysis on the splicing events and RNA-seq based expression profile 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.

Nine different regions totaling 9.7 Mb of the 4.02 Gb Aegilops tauschii genome were sequenced using the Sanger sequencing technology and compared with orthologous Brachypodium distachyon, Oryza sativa (rice), and Sorghum bicolor (sorghum) genomic sequences. The ancestral gene content in these regions was inferred and used to estimate gene deletion and gene duplication rates along each branch of the phylogenetic tree relating the four species. The total gene number in the extant Ae. tauschii genome was estimated to be 36,371. The gene deletion and gene duplication rates and total gene numbers in the four genomes were used to estimate the total gene number in each node of the phylogenetic tree. The common ancestor of the Brachypodieae and Triticeae lineages was estimated to have had 28,558 genes, and the common ancestor of the Panicoideae, Ehrhartoideae, and Pooideae subfamilies was estimated to have had 27,152 or 28,350 genes, depending on the ancestral gene scenario. Relative to the Brachypodieae and Triticeae common ancestor, the gene number was reduced in B. distachyon by 3,026 genes and increased in Ae. tauschii by 7,813 genes. The sum of gene deletion and gene duplication rates, which reflects the rate of gene synteny loss, was correlated with the rate of structural chromosome rearrangements and was highest in the Ae. tauschii lineage and lowest in the rice lineage. The high rate of gene space evolution in the Ae. tauschii lineage accounts for the fact that, contrary to the expectations, the level of synteny between the phylogenetically more related Ae. tauschii and B. distachyon genomes is similar to the level of synteny between the Ae. tauschii genome and the genomes of the less related rice and sorghum. The ratio of gene duplication to gene deletion rates in these four grass species closely parallels both the total number of genes in a species and the overall genome size. Because the overall genome size is to a large extent a function of the repeated sequence content in a genome, we suggest that the amount and activity of repeated sequences are important factors determining the number of genes in a genome.

Strawberry ( spp.) is a eudicotyledonous plant that belongs to the Rosaceae family, which includes other agronomically important plants such as raspberry ( L.) and several tree-fruit species. Despite the vital role played by cultivated strawberry in agriculture, few stress-related gene expression characterizations of this crop are available. To increase the diversity of available transcriptome sequence, we produced 41,430 L. expressed sequence tags (ESTs) from plants growing under water-, temperature-, and osmotic-stress conditions as well as a combination of heat and osmotic stresses that is often found in irrigated fields. Clustering and assembling of the ESTs resulted in a total of 11,836 contigs and singletons that were annotated using Gene Ontology (GO) terms. Furthermore, over 1200 sequences with no match to available Rosaceae ESTs were found, including six that were assigned the “response to stress” GO category. Analysis of EST frequency provided an estimate of steady state transcript levels, with 91 sequences exhibiting at least a 20-fold difference between treatments. This EST collection represents a useful resource to advance our understanding of the abiotic stress-response mechanisms in strawberry. The sequence information may be translated to valuable tree crops in the Rosaceae family, where whole-plant treatments are not as simple or practical.

Castor bean (Ricinus communis) is an oilseed crop that belongs to the spurge (Euphorbiaceae) family, which comprises approximately 6,300 species that include cassava (Manihot esculenta), rubber tree (Hevea brasiliensis) and physic nut (Jatropha curcas). It is primarily of economic interest as a source of castor oil, used for the production of high-quality lubricants because of its high proportion of the unusual fatty acid ricinoleic acid. However, castor bean genomics is also relevant to biosecurity as the seeds contain high levels of ricin, a highly toxic, ribosome-inactivating protein. Here we report the draft genome sequence of castor bean (4.6-fold coverage), the first for a member of the Euphorbiaceae. Whereas most of the key genes involved in oil synthesis and turnover are single copy, the number of members of the ricin gene family is larger than previously thought. Comparative genomics analysis suggests the presence of an ancient hexaploidization event that is conserved across the dicotyledonous lineage.

Genomic resources have significantly impacted plant biology research in recent years. Cell biology has been further enabled by an ongoing revolution in visualization technologies. Using fluorescent proteins (FPs), we now have unprecedented views of cellular architecture, and we can study real-time dynamics of cell structure, function, and protein localization. To date, these technologies have been most widely used in Arabidopsis (Arabidopsis thaliana); however, the grasses provide a unique opportunity to study the underlying mechanisms and inter-related controls of cell growth, morphogenesis, and physiology in leading crop models. Here, we present a resource that leverages the emerging maize (Zea mays) genome sequence to develop tools to study protein structure and function in a cellular context. Traditionally, such studies relied on fixed tissue or FP fusions driven by constitutive promoters, which can lead to significant artifacts. The maize genome sequence now provides access to regulatory regions that can be used to drive native expression. We have developed streamlined methods to generate maize FP-tagged lines using these regulatory elements, allowing analysis of tissue-specific expression and localized function. Identification of diverse proteins that function in specific subcellular compartments will provide the tools for understanding basic developmental, biochemical, and physiological processes in maize, with direct application potential for crop improvement.

Worldwide genetic diversity in 200 individuals comprising 41 castor bean accessions was assessed using amplified fragment polymorphisms (AFLPs) and simple sequence repeats (SSRs). We found that, despite surveying five continents and 35 countries, genetic diversity in castor bean germplasm is relatively low (overall He = 0.126 for AFLPs and 0.188 for SSRs) compared to estimates of genetic diversity in other plant species. Our data also show no geographic structuring of genotypes across continents or countries within continents. An assessment of the congruence between AFLP and SSRs indicates a low correlation (R2 = 0.19) between the two data sets, but each marker class nonetheless shows similar patterns of low-genetic diversity and a lack of geographic structure. Our data do suggest that SSRs yield a higher percentage of polymorphic loci, higher heterozyosity and a greater range of genetic distances, and are therefore more informative than are AFLPs on a locus-by-locus basis. Based on comparisons with numerous other plant species, we suggest that the lower genetic variation in this worldwide collection may be due to one or more factors including: sampling strategies that have not captured the full extent of genetic variation in the species; artifactual variation due to long-term germplasm storage and seed regeneration; or intense selection followed by domestic cultivation of a limited number of castor bean genotypes, which are widely propagated for their horticultural and agro-economic value.

The early development of metazoans is mainly regulated by differential translation and localization of maternal mRNAs in the embryo. In general, these processes are orchestrated by RNA-binding proteins interacting with specific sequence motifs in the 3'-untranslated region (UTR) of their target RNAs. Hermes is an RNA-binding protein, which contains a single RNA recognition motif (RRM) and is found in various vertebrate species from fish to human. In Xenopus laevis, Hermes mRNA and protein are localized in the vegetal region of oocytes. A subpopulation of Hermes protein is concentrated in a specific structure in the vegetal cortex, called the germ plasm (believed to contain determinants of the germ cell fate) where Hermes protein co-localizes with Xcat2 and RINGO/Spy mRNAs. The level of total Hermes protein decreases during maturation. The precocious depletion of Hermes protein by injection of Hermes antisense morpholino oligonucleotide (HE-MO) accelerates the process of maturation and results in cleavage defects in vegetal blastomeres of the embryo. It is known that several maternal mRNAs including RINGO/Spy and Mos are regulated at the translational level during meiotic maturation and early cleavage in Xenopus. The ectopic expression of RINGO/Spy or Mos causes resumption of meiotic maturation and cleavage arrests, which resemble the loss of Hermes phenotypes. We found that the injection of HE-MO enhances the acceleration of maturation caused by the injection of RINGO/Spy mRNA, and that Hermes protein is present as mRNP complex containing RINGO/Spy, Mos, and Xcat2 mRNAs in vivo. We propose that as an RNA-binding protein, Hermes may be involved in maturation, cleavage events at the vegetal pole and germ cell development by negatively regulating the expression of RINGO/Spy, Mos, and Xcat2 mRNAs.

In Xenopus species, the early stages of oogenesis take place in the developing tadpole ovary when the oocytes are in a period critical for the organization of the germ plasm (believed to be a determinant of germ-cell fate) and the initial stages of localization of RNAs involved in germ plasm functions. We constructed a cDNA library from the ovaries of stage 64 Xenopus tadpoles with the idea that it will be enriched for oogonia and pre-stage I and stage I oocytes and thus, RNAs involved in oocyte development and germ plasm formation and function. From this cDNA library, we cloned a new maternal localized mRNA which we named centroid. This RNA codes for the protein belonging to the DEAD-box RNA helicase family. Some of the members of this protein family are components of the messenger ribonucleoprotein (mRNP) particles stored in the germ plasm in oocytes of Xenopus, Drosophila and Caenorhabditis species and are believed to play a role in translational activation of stored mRNPs and sorting of mRNPs into the germ plasm. We found that centroid mRNA is localized in Xenopus oocytes by a combination of early and late pathways, a pattern of localization that is very similar to the intermediate pathway localization of fatvg mRNA, another germ-plasm-localized RNA in Xenopus oocytes. Also, centroid mRNA is present in the mitochondrial cloud and in the germ plasm at the surface of germinal granules. This suggests that centroid is involved in the regulation of germ plasm-stored mRNPs and/or germ plasm function.

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.

We have identified the RNA-binding protein Hermes in a screen for vegetally localized RNAs in Xenopus oocytes. The RNA localizes to the vegetal cortex through both the message transport organizer (METRO) and late pathways. Hermes mRNA and protein are both detected at the vegetal cortex of the oocyte; however, the protein is degraded within a several hour period during oocyte maturation. Injection of antisense morpholino oligonucleotides (HE-MO) against Hermes caused a precocious reduction in Hermes protein present during maturation and resulted in a phenotype characterized by cleavage defects in vegetal blastomeres. The phenotype can be partially rescued by injecting Hermes mRNA. These results demonstrate that the localized RNA-binding protein Hermes functions during oocyte maturation to regulate the cleavage of specific vegetally derived cell lineages. Hermes most likely performs its function by regulating the translation or processing of one or more target RNAs. This is an important mechanism by which the embryo can generate unique cell lineages. The regulation of region-specific cell division is a novel function for a localized mRNA.

Xenopus laevis short interspersed repeat transcripts (Xlsirts) are a family of noncoding RNAs defined by the presence of a specific repeated sequence that acts as a vegetal localization element. Previous studies have demonstrated that Xlsirts function as localization elements to localize RNA and also in anchoring mRNA at the vegetal cortex. However, the identity of the Xlsirts containing family members present at the cortex was unknown. We identified 17 new Xlsirt cDNAs from an oocyte cDNA library. In addition to being associated with noncoding sequences, the repeats were also present in cDNAs with open reading frames. Xlsirt RNAs with repeats in the correct orientation were capable of localizing to the vegetal cortex. Our observations demonstrate that a heterogeneous population of Xlsirt RNAs is present at the cortex and that this population contains both noncoding RNAs and RNAs encoding proteins that are likely to play important roles in the subsequent development of the embryo.