Big data in genomic research for big questions with examples from covid-19 and other zoonoses.

Omics research inevitably involves the collection and analysis of big data, which can only be handled by automated approaches. Here we point out that the analysis of big data in the field of genomics dictates certain requirements, such as specialized software, quality control of input data, and simplification for visualization of the results. The latter results in a loss of information, as is exemplified for phylogenetic trees. Clear communication of big data analyses can be enhanced by novel visualization strategies. The interpretation of findings is sometimes hampered when dedicated analytical tools are not fully understood by microbiologists, while the researchers performing these analyses may not have a full overview of the biology of the microbes under study. These issues are illustrated here, using SARS-Cov-2 and Salmonella enterica as zoonotic examples. Whereas in scientific communications jargon should be avoided or explained, nomenclature to group similar organisms and distinguish these from more distant relatives is not only essential, but also influences the interpretation of results. Unfortunately, changes in taxonomically accepted names are now so frequent that they hamper rather than assist research, as is illustrated with difficulties of microbiome studies. Nomenclature to group viral isolates, as is done for SARS-Cov2, is also not without difficulties. Some weaknesses in current omics research stem from poor quality of data or biased databases, and problems can be magnified by machine learning approaches. Moreover, the overall opus of scientific publications can now be considered "big data", as is illustrated by the avalanche of COVID-19-related publications. The peer-review model of scientific publishing is only barely coping with this novel situation, resulting in retractions and the publication of bogus works. The avalanche of scientific publications that originated from the current pandemic can obstruct literature searches, and this will unfortunately continue over time.

Decoding the epitranscriptional landscape from native RNA sequences.

Traditional epitranscriptomics relies on capturing a single RNA modification by antibody or chemical treatment, combined with short-read sequencing to identify its transcriptomic location. This approach is labor-intensive and may introduce experimental artifacts. Direct sequencing of native RNA using Oxford Nanopore Technologies (ONT) can allow for directly detecting the RNA base modifications, although these modifications might appear as sequencing errors. The percent Error of Specific Bases (%ESB) was higher for native RNA than unmodified RNA, which enabled the detection of ribonucleotide modification sites. Based on the %ESB differences, we developed a bioinformatic tool, epitranscriptional landscape inferring from glitches of ONT signals (ELIGOS), that is based on various types of synthetic modified RNA and applied to rRNA and mRNA. ELIGOS is able to accurately predict known classes of RNA methylation sites (AUC > 0.93) in rRNAs from Escherichiacoli, yeast, and human cells, using either unmodified in vitro transcription RNA or a background error model, which mimics the systematic error of direct RNA sequencing as the reference. The well-known DRACH/RRACH motif was localized and identified, consistent with previous studies, using differential analysis of ELIGOS to study the impact of RNA m6A methyltransferase by comparing wild type and knockouts in yeast and mouse cells. Lastly, the DRACH motif could also be identified in the mRNA of three human cell lines. The mRNA modification identified by ELIGOS is at the level of individual base resolution. In summary, we have developed a bioinformatic software package to uncover native RNA modifications.

Comparison of Monkeypox virus genomes from the 2017 Nigeria outbreak and the 2022 outbreak.

AIMS: The current Monkeypox virus (MPX) outbreak is not only the largest known outbreak to date caused by a strain belonging to the West-African clade, but also results in remarkably different clinical and epidemiological features compared to previous outbreaks of this virus. Here, we consider the possibility that mutations in the viral genome may be responsible for its changed characteristics. METHODS AND RESULTS: Six genome sequences of isolates from the current outbreak were compared to five genomes of isolates from the 2017 outbreak in Nigeria and to two historic genomes, all belonging to the West-African clade. We report differences that are consistently present in the 2022 isolates but not in the others. Although some variation in repeat units was observed, only two were consistently found in the 2022 genomes only, and these were located in intergenic regions. A total of 55 single nucleotide polymorphisms were consistently present in the 2022 isolates compared to the 2017 isolates. Of these, 25 caused an amino acid substitution in a predicted protein. CONCLUSIONS: The nature of the substitution and the annotation of the affected protein identified potential candidates that might affect the virulence of the virus. These included the viral DNA helicase and transcription factors. SIGNIFICANCE: This bioinformatic analysis provides guidance for wet-lab research to identify changed properties of the MPX.

Report of the 2019 NIST-FDA workshop on standards for next generation sequencing detection of viral adventitious agents in biologics and biomanufacturing.

Adventitious virus testing assures product safety by demonstrating the absence of viruses that could be unintentionally introduced during the manufacturing process. The capabilities of next-generation sequencing (NGS) for broad virus detection in biologics have been demonstrated by the detection of known and novel viruses that were previously missed using the recommended routine assays for adventitious agent testing. A meeting was co-organized by the National Institute of Standards and Technology and the U.S. Food and Drug Administration on September 18-19, 2019 in Gaithersburg, Maryland, USA, to facilitate standardization of NGS technologies for applications of adventitious virus testing in biologics. The goal was to assess the currently used standards for virus detection by NGS and their public availability, and to identify additional needs for different types of reference materials and standards (natural and synthetic). The meeting focused on the NGS processes from sample preparation through sequencing but did not thoroughly cover bioinformatics, since this was considered to be the topic of a separate meeting.

Complete genomic and transcriptional landscape analysis using third-generation sequencing: a case study of Saccharomyces cerevisiae CEN.PK113-7D.

Completion of eukaryal genomes can be difficult task with the highly repetitive sequences along the chromosomes and short read lengths of second-generation sequencing. Saccharomyces cerevisiae strain CEN.PK113-7D, widely used as a model organism and a cell factory, was selected for this study to demonstrate the superior capability of very long sequence reads for de novo genome assembly. We generated long reads using two common third-generation sequencing technologies (Oxford Nanopore Technology (ONT) and Pacific Biosciences (PacBio)) and used short reads obtained using Illumina sequencing for error correction. Assembly of the reads derived from all three technologies resulted in complete sequences for all 16 yeast chromosomes, as well as the mitochondrial chromosome, in one step. Further, we identified three types of DNA methylation (5mC, 4mC and 6mA). Comparison between the reference strain S288C and strain CEN.PK113-7D identified chromosomal rearrangements against a background of similar gene content between the two strains. We identified full-length transcripts through ONT direct RNA sequencing technology. This allows for the identification of transcriptional landscapes, including untranslated regions (UTRs) (5' UTR and 3' UTR) as well as differential gene expression quantification. About 91% of the predicted transcripts could be consistently detected across biological replicates grown either on glucose or ethanol. Direct RNA sequencing identified many polyadenylated non-coding RNAs, rRNAs, telomere-RNA, long non-coding RNA and antisense RNA. This work demonstrates a strategy to obtain complete genome sequences and transcriptional landscapes that can be applied to other eukaryal organisms.

Mechanisms linking preterm birth to onset of cardiovascular disease later in adulthood.

Cardiovascular disease (CVD) rates in adulthood are high in premature infants; unfortunately, the underlying mechanisms are not well defined. In this review, we discuss potential pathways that could lead to CVD in premature babies. Studies show intense oxidant stress and inflammation at tissue levels in these neonates. Alterations in lipid profile, foetal epigenomics, and gut microbiota in these infants may also underlie the development of CVD. Recently, probiotic bacteria, such as the mucin-degrading bacterium Akkermansia muciniphila have been shown to reduce inflammation and prevent heart disease in animal models. All this information might enable scientists and clinicians to target pathways to act early to curtail the adverse effects of prematurity on the cardiovascular system. This could lead to primary and secondary prevention of CVD and improve survival among preterm neonates later in adult life.

Machine Learning Methods in Drug Discovery.

The advancements of information technology and related processing techniques have created a fertile base for progress in many scientific fields and industries. In the fields of drug discovery and development, machine learning techniques have been used for the development of novel drug candidates. The methods for designing drug targets and novel drug discovery now routinely combine machine learning and deep learning algorithms to enhance the efficiency, efficacy, and quality of developed outputs. The generation and incorporation of big data, through technologies such as high-throughput screening and high through-put computational analysis of databases used for both lead and target discovery, has increased the reliability of the machine learning and deep learning incorporated techniques. The use of these virtual screening and encompassing online information has also been highlighted in developing lead synthesis pathways. In this review, machine learning and deep learning algorithms utilized in drug discovery and associated techniques will be discussed. The applications that produce promising results and methods will be reviewed.

SMARC-B1 deficient sinonasal carcinoma metastasis to the brain with next generation sequencing data: a case report of perineural invasion progressing to leptomeningeal invasion.

BACKGROUND: SMARCB1-deficient sinonasal carcinoma (SDSC) is an aggressive subtype of head and neck cancers that has a poor prognosis despite multimodal therapy. We present a unique case with next generation sequencing data of a patient who had SDSC with perineural invasion to the trigeminal nerve that progressed to a brain metastasis and eventually leptomeningeal spread. CASE PRESENTATION: A 42 year old female presented with facial pain and had resection of a tumor along the V2 division of the trigeminal nerve on the right. She underwent adjuvant stereotactic radiation. She developed further neurological symptoms and imaging demonstrated the tumor had infiltrated into the cavernous sinus as well as intradurally. She had surgical resection for removal of her brain metastasis and decompression of the cavernous sinus. Following her second surgery, she had adjuvant radiation and chemotherapy. Several months later she had quadriparesis and imaging was consistent with leptomeningeal spread. She underwent palliative radiation and ultimately transitioned quickly to comfort care and expired. Overall survival from time of diagnosis was 13 months. Next generation sequencing was carried out on her primary tumor and brain metastasis. The brain metastatic tissue had an increased tumor mutational burden in comparison to the primary. CONCLUSIONS: This is the first report of SDSC with perineural invasion progressing to leptomeningeal carcinomatosis. Continued next generation sequencing of the primary and metastatic tissue by clinicians is encouraged toprovide further insights into metastatic progression of rare solid tumors.

Case of Microcephaly after Congenital Infection with Asian Lineage Zika Virus, Thailand.

We sequenced the virus genomes from 3 pregnant women in Thailand with Zika virus diagnoses. All had infections with the Asian lineage. The woman infected at gestational week 9, and not those infected at weeks 20 and 24, had a fetus with microcephaly. Asian lineage Zika viruses can cause microcephaly.

PanViz: interactive visualization of the structure of functionally annotated pangenomes.

Summary: PanViz is a novel, interactive, visualization tool for pangenome analysis. PanViz allows visualization of changes in gene group (groups of similar genes across genomes) classification as different subsets of pangenomes are selected, as well as comparisons of individual genomes to pangenomes with gene ontology based navigation of gene groups. Furthermore it allows for rich and complex visual querying of gene groups in the pangenome. PanViz visualizations require no external programs and are easily sharable, allowing for rapid pangenome analyses. Availability and Implementation: PanViz is written entirely in JavaScript and is available on https://github.com/thomasp85/PanViz . A companion R package that facilitates the creation of PanViz visualizations from a range of data formats is released through Bioconductor and is available at https://bioconductor.org/packages/PanVizGenerator . Contact: thomasp85@gmail.com. Supplementary information: Supplementary data are available at Bioinformatics online.

Genome-Based Comparison of Clostridioides difficile: Average Amino Acid Identity Analysis of Core Genomes.

Infections due to Clostridioides difficile (previously known as Clostridium difficile) are a major problem in hospitals, where cases can be caused by community-acquired strains as well as by nosocomial spread. Whole genome sequences from clinical samples contain a lot of information but that needs to be analyzed and compared in such a way that the outcome is useful for clinicians or epidemiologists. Here, we compare 663 public available complete genome sequences of C. difficile using average amino acid identity (AAI) scores. This analysis revealed that most of these genomes (640, 96.5%) clearly belong to the same species, while the remaining 23 genomes produce four distinct clusters within the Clostridioides genus. The main C. difficile cluster can be further divided into sub-clusters, depending on the chosen cutoff. We demonstrate that MLST, either based on partial or full gene-length, results in biased estimates of genetic differences and does not capture the true degree of similarity or differences of complete genomes. Presence of genes coding for C. difficile toxins A and B (ToxA/B), as well as the binary C. difficile toxin (CDT), was deduced from their unique PfamA domain architectures. Out of the 663 C. difficile genomes, 535 (80.7%) contained at least one copy of ToxA or ToxB, while these genes were missing from 128 genomes. Although some clusters were enriched for toxin presence, these genes are variably present in a given genetic background. The CDT genes were found in 191 genomes, which were restricted to a few clusters only, and only one cluster lacked the toxin A/B genes consistently. A total of 310 genomes contained ToxA/B without CDT (47%). Further, published metagenomic data from stools were used to assess the presence of C. difficile sequences in blinded cases of C. difficile infection (CDI) and controls, to test if metagenomic analysis is sensitive enough to detect the pathogen, and to establish strain relationships between cases from the same hospital. We conclude that metagenomics can contribute to the identification of CDI and can assist in characterization of the most probable causative strain in CDI patients.

dBBQs: dataBase of Bacterial Quality scores.

BACKGROUND: It is well-known that genome sequencing technologies are becoming significantly cheaper and faster. As a result of this, the exponential growth in sequencing data in public databases allows us to explore ever growing large collections of genome sequences. However, it is less known that the majority of available sequenced genome sequences in public databases are not complete, drafts of varying qualities. We have calculated quality scores for around 100,000 bacterial genomes from all major genome repositories and put them in a fast and easy-to-use database. RESULTS: Prokaryotic genomic data from all sources were collected and combined to make a non-redundant set of bacterial genomes. The genome quality score for each was calculated by four different measurements: assembly quality, number of rRNA and tRNA genes, and the occurrence of conserved functional domains. The dataBase of Bacterial Quality scores (dBBQs) was designed to store and retrieve quality scores. It offers fast searching and download features which the result can be used for further analysis. In addition, the search results are shown in interactive JavaScript chart framework using DC.js. The analysis of quality scores across major public genome databases find that around 68% of the genomes are of acceptable quality for many uses. CONCLUSIONS: dBBQs (available at http://arc-gem.uams.edu/dbbqs ) provides genome quality scores for all available prokaryotic genome sequences with a user-friendly Web-interface. These scores can be used as cut-offs to get a high-quality set of genomes for testing bioinformatics tools or improving the analysis. Moreover, all data of the four measurements that were combined to make the quality score for each genome, which can potentially be used for further analysis. dBBQs will be updated regularly and is freely use for non-commercial purpose.

Suggested mechanisms for Zika virus causing microcephaly: what do the genomes tell us?

BACKGROUND: Zika virus (ZIKV) is an emerging human pathogen. Since its arrival in the Western hemisphere, from Africa via Asia, it has become a serious threat to pregnant women, causing microcephaly and other neuropathies in developing fetuses. The mechanisms behind these teratogenic effects are unknown, although epidemiological evidence suggests that microcephaly is not associated with the original, African lineage of ZIKV. The sequences of 196 published ZIKV genomes were used to assess whether recently proposed mechanistic explanations for microcephaly are supported by molecular level changes that may have increased its virulence since the virus left Africa. For this we performed phylogenetic, recombination, adaptive evolution and tetramer frequency analyses, and compared protein sequences for the presence of protease cleavage sites, Pfam domains, glycosylation sites, signal peptides, trans-membrane protein domains, and phosphorylation sites. RESULTS: Recombination events within or between Asian and Brazilian lineages were not observed, and likewise there were no differences in protease cleavage, glycosylation sites, signal peptides or trans-membrane domains between African and Brazilian strains. The frequency of Retinoic Acid Response Element (RARE) sequences was increased in Brazilian strains. Genetic adaptation was also apparent by tetramer signatures that had undergone major changes in the past but has stabilized in the Brazilian lineage despite subsequent geographic spread, suggesting the viral population presently propagates in the same host species in various regions. Evidence for selection pressure was recognized for several amino acid sites in the Brazilian lineage compared to the African lineage, mainly in nonstructural proteins, especially protein NS4B. A number of these positively selected mutations resulted in an increased potential to be phosphorylated in the Brazilian lineage compared to the African linage, which may have increased their potential to interfere with neural fetal development. CONCLUSIONS: ZIKV seems to have adapted to a limited number of hosts, including humans, during which its virulence increased. Its protein NS4B, together with NS4A, has recently been shown to inhibit Akt-mTOR signaling in human fetal neural stem cells, a key pathway for brain development. We hypothesize that positive selection of novel phosphorylation sites in the protein NS4B of the Brazilian lineage could interfere with phosphorylation of Akt and mTOR, impairing Akt-mTOR signaling and this may result in an increased risk for developmental neuropathies.

From essential to persistent genes: a functional approach to constructing synthetic life.

A central undertaking in synthetic biology (SB) is the quest for the 'minimal genome'. However, 'minimal sets' of essential genes are strongly context-dependent and, in all prokaryotic genomes sequenced to date, not a single protein-coding gene is entirely conserved. Furthermore, a lack of consensus in the field as to what attributes make a gene truly essential adds another aspect of variation. Thus, a universal minimal genome remains elusive. Here, as an alternative to defining a minimal genome, we propose that the concept of gene persistence can be used to classify genes needed for robust long-term survival. Persistent genes, although not ubiquitous, are conserved in a majority of genomes, tend to be expressed at high levels, and are frequently located on the leading DNA strand. These criteria impose constraints on genome organization, and these are important considerations for engineering cells and for creating cellular life-like forms in SB.

Global Genomic Epidemiology of Salmonella enterica Serovar Typhimurium DT104.

It has been 30 years since the initial emergence and subsequent rapid global spread of multidrug-resistant Salmonella entericaserovar Typhimurium DT104 (MDR DT104). Nonetheless, its origin and transmission route have never been revealed. We used whole-genome sequencing (WGS) and temporally structured sequence analysis within a Bayesian framework to reconstruct temporal and spatial phylogenetic trees and estimate the rates of mutation and divergence times of 315S Typhimurium DT104 isolates sampled from 1969 to 2012 from 21 countries on six continents. DT104 was estimated to have emerged initially as antimicrobial susceptible in ∼1948 (95% credible interval [CI], 1934 to 1962) and later became MDR DT104 in ∼1972 (95% CI, 1972 to 1988) through horizontal transfer of the 13-kb Salmonella genomic island 1 (SGI1) MDR region into susceptible strains already containing SGI1. This was followed by multiple transmission events, initially from central Europe and later between several European countries. An independent transmission to the United States and another to Japan occurred, and from there MDR DT104 was probably transmitted to Taiwan and Canada. An independent acquisition of resistance genes took place in Thailand in ∼1975 (95% CI, 1975 to 1990). In Denmark, WGS analysis provided evidence for transmission of the organism between herds of animals. Interestingly, the demographic history of Danish MDR DT104 provided evidence for the success of the program to eradicate Salmonellafrom pig herds in Denmark from 1996 to 2000. The results from this study refute several hypotheses on the evolution of DT104 and suggest that WGS may be useful in monitoring emerging clones and devising strategies for prevention of Salmonella infections.

Diversity of Pseudomonas Genomes, Including Populus-Associated Isolates, as Revealed by Comparative Genome Analysis.

The Pseudomonas genus contains a metabolically versatile group of organisms that are known to occupy numerous ecological niches, including the rhizosphere and endosphere of many plants. Their diversity influences the phylogenetic diversity and heterogeneity of these communities. On the basis of average amino acid identity, comparative genome analysis of >1,000 Pseudomonas genomes, including 21 Pseudomonas strains isolated from the roots of native Populus deltoides (eastern cottonwood) trees resulted in consistent and robust genomic clusters with phylogenetic homogeneity. All Pseudomonas aeruginosa genomes clustered together, and these were clearly distinct from other Pseudomonas species groups on the basis of pangenome and core genome analyses. In contrast, the genomes of Pseudomonas fluorescens were organized into 20 distinct genomic clusters, representing enormous diversity and heterogeneity. Most of our 21 Populus-associated isolates formed three distinct subgroups within the major P. fluorescens group, supported by pathway profile analysis, while two isolates were more closely related to Pseudomonas chlororaphis and Pseudomonas putida. Genes specific to Populus-associated subgroups were identified. Genes specific to subgroup 1 include several sensory systems that act in two-component signal transduction, a TonB-dependent receptor, and a phosphorelay sensor. Genes specific to subgroup 2 contain hypothetical genes, and genes specific to subgroup 3 were annotated with hydrolase activity. This study justifies the need to sequence multiple isolates, especially from P. fluorescens, which displays the most genetic variation, in order to study functional capabilities from a pangenomic perspective. This information will prove useful when choosing Pseudomonas strains for use to promote growth and increase disease resistance in plants.

Molecular analysis of asymptomatic bacteriuria Escherichia coli strain VR50 reveals adaptation to the urinary tract by gene acquisition.

Urinary tract infections (UTIs) are among the most common infectious diseases of humans, with Escherichia coli responsible for >80% of all cases. One extreme of UTI is asymptomatic bacteriuria (ABU), which occurs as an asymptomatic carrier state that resembles commensalism. To understand the evolution and molecular mechanisms that underpin ABU, the genome of the ABU E. coli strain VR50 was sequenced. Analysis of the complete genome indicated that it most resembles E. coli K-12, with the addition of a 94-kb genomic island (GI-VR50-pheV), eight prophages, and multiple plasmids. GI-VR50-pheV has a mosaic structure and contains genes encoding a number of UTI-associated virulence factors, namely, Afa (afimbrial adhesin), two autotransporter proteins (Ag43 and Sat), and aerobactin. We demonstrated that the presence of this island in VR50 confers its ability to colonize the murine bladder, as a VR50 mutant with GI-VR50-pheV deleted was attenuated in a mouse model of UTI in vivo. We established that Afa is the island-encoded factor responsible for this phenotype using two independent deletion (Afa operon and AfaE adhesin) mutants. E. coli VR50afa and VR50afaE displayed significantly decreased ability to adhere to human bladder epithelial cells. In the mouse model of UTI, VR50afa and VR50afaE displayed reduced bladder colonization compared to wild-type VR50, similar to the colonization level of the GI-VR50-pheV mutant. Our study suggests that E. coli VR50 is a commensal-like strain that has acquired fitness factors that facilitate colonization of the human bladder.

Insights from 20 years of bacterial genome sequencing.

Since the first two complete bacterial genome sequences were published in 1995, the science of bacteria has dramatically changed. Using third-generation DNA sequencing, it is possible to completely sequence a bacterial genome in a few hours and identify some types of methylation sites along the genome as well. Sequencing of bacterial genome sequences is now a standard procedure, and the information from tens of thousands of bacterial genomes has had a major impact on our views of the bacterial world. In this review, we explore a series of questions to highlight some insights that comparative genomics has produced. To date, there are genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. However, the distribution is quite skewed towards a few phyla that contain model organisms. But the breadth is continuing to improve, with projects dedicated to filling in less characterized taxonomic groups. The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas system provides bacteria with immunity against viruses, which outnumber bacteria by tenfold. How fast can we go? Second-generation sequencing has produced a large number of draft genomes (close to 90 % of bacterial genomes in GenBank are currently not complete); third-generation sequencing can potentially produce a finished genome in a few hours, and at the same time provide methlylation sites along the entire chromosome. The diversity of bacterial communities is extensive as is evident from the genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. Genome sequencing can help in classifying an organism, and in the case where multiple genomes of the same species are available, it is possible to calculate the pan- and core genomes; comparison of more than 2000 Escherichia coli genomes finds an E. coli core genome of about 3100 gene families and a total of about 89,000 different gene families. Why do we care about bacterial genome sequencing? There are many practical applications, such as genome-scale metabolic modeling, biosurveillance, bioforensics, and infectious disease epidemiology. In the near future, high-throughput sequencing of patient metagenomic samples could revolutionize medicine in terms of speed and accuracy of finding pathogens and knowing how to treat them.

Microbial taxonomy in the post-genomic era: rebuilding from scratch?

Microbial taxonomy should provide adequate descriptions of bacterial, archaeal, and eukaryotic microbial diversity in ecological, clinical, and industrial environments. Its cornerstone, the prokaryote species has been re-evaluated twice. It is time to revisit polyphasic taxonomy, its principles, and its practice, including its underlying pragmatic species concept. Ultimately, we will be able to realize an old dream of our predecessor taxonomists and build a genomic-based microbial taxonomy, using standardized and automated curation of high-quality complete genome sequences as the new gold standard.

The transcriptional landscape and small RNAs of Salmonella enterica serovar Typhimurium.

More than 50 y of research have provided great insight into the physiology, metabolism, and molecular biology of Salmonella enterica serovar Typhimurium (S. Typhimurium), but important gaps in our knowledge remain. It is clear that a precise choreography of gene expression is required for Salmonella infection, but basic genetic information such as the global locations of transcription start sites (TSSs) has been lacking. We combined three RNA-sequencing techniques and two sequencing platforms to generate a robust picture of transcription in S. Typhimurium. Differential RNA sequencing identified 1,873 TSSs on the chromosome of S. Typhimurium SL1344 and 13% of these TSSs initiated antisense transcripts. Unique findings include the TSSs of the virulence regulators phoP, slyA, and invF. Chromatin immunoprecipitation revealed that RNA polymerase was bound to 70% of the TSSs, and two-thirds of these TSSs were associated with σ(70) (including phoP, slyA, and invF) from which we identified the -10 and -35 motifs of σ(70)-dependent S. Typhimurium gene promoters. Overall, we corrected the location of important genes and discovered 18 times more promoters than identified previously. S. Typhimurium expresses 140 small regulatory RNAs (sRNAs) at early stationary phase, including 60 newly identified sRNAs. Almost half of the experimentally verified sRNAs were found to be unique to the Salmonella genus, and <20% were found throughout the Enterobacteriaceae. This description of the transcriptional map of SL1344 advances our understanding of S. Typhimurium, arguably the most important bacterial infection model.