Pangenome graph construction from genome alignments with Minigraph-Cactus

Pangenome references address biases of reference genomes by storing a representative set of diverse haplotypes and their alignment, usually as a graph. Alternate alleles determined by variant callers can be used to construct pangenome graphs, but advances in long-read sequencing are leading to widely available, high-quality phased assemblies. Constructing a pangenome graph directly from assemblies, as opposed to variant calls, leverages the graph's ability to represent variation at different scales. Here we present the Minigraph-Cactus pangenome pipeline, which creates pangenomes directly from whole-genome alignments, and demonstrate its ability to scale to 90 human haplotypes from the Human Pangenome Reference Consortium. The method builds graphs containing all forms of genetic variation while allowing use of current mapping and genotyping tools. We measure the effect of the quality and completeness of reference genomes used for analysis within the pangenomes and show that using the CHM13 reference from the Telomere-to-Telomere Consortium improves the accuracy of our methods. We also demonstrate construction of a Drosophila melanogaster pangenome.

A draft human pangenome reference

Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals1. These assemblies cover more than 99% of the expected sequence in each genome and are more than 99% accurate at the structural and base pair levels. Based on alignments of the assemblies, we generate a draft pangenome that captures known variants and haplotypes and reveals new alleles at structurally complex loci. We also add 119 million base pairs of euchromatic polymorphic sequences and 1,115 gene duplications relative to the existing reference GRCh38. Roughly 90 million of the additional base pairs are derived from structural variation. Using our draft pangenome to analyse short-read data reduced small variant discovery errors by 34% and increased the number of structural variants detected per haplotype by 104% compared with GRCh38-based workflows, which enabled the typing of the vast majority of structural variant alleles per sample.

FAVOR: functional annotation of variants online resource and annotator for variation across the human genome

Large biobank-scale whole genome sequencing (WGS) studies are rapidly identifying a multitude of coding and non-coding variants. They provide an unprecedented resource for illuminating the genetic basis of human diseases. Variant functional annotations play a critical role in WGS analysis, result interpretation, and prioritization of disease- or trait-associated causal variants. Existing functional annotation databases have limited scope to perform online queries and functionally annotate the genotype data of large biobank-scale WGS studies. We develop the Functional Annotation of Variants Online Resources (FAVOR) to meet these pressing needs. FAVOR provides a comprehensive multi-faceted variant functional annotation online portal that summarizes and visualizes findings of all possible nine billion single nucleotide variants (SNVs) across the genome. It allows for rapid variant-, gene- and region-level queries of variant functional annotations. FAVOR integrates variant functional information from multiple sources to describe the functional characteristics of variants and facilitates prioritizing plausible causal variants influencing human phenotypes. Furthermore, we provide a scalable annotation tool, FAVORannotator, to functionally annotate large-scale WGS studies and efficiently store the genotype and their variant functional annotation data in a single file using the annotated Genomic Data Structure (aGDS) format, making downstream analysis more convenient. FAVOR and FAVORannotator are available at https://favor.genohub.org.

The Data Use Ontology to streamline responsible access to human biomedical datasets

Human biomedical datasets that are critical for research and clinical studies to benefit human health also often contain sensitive or potentially identifying information of individual participants. Thus, care must be taken when they are processed and made available to comply with ethical and regulatory frameworks and informed consent data conditions. To enable and streamline data access for these biomedical datasets, the Global Alliance for Genomics and Health (GA4GH) Data Use and Researcher Identities (DURI) work stream developed and approved the Data Use Ontology (DUO) standard. DUO is a hierarchical vocabulary of human and machine-readable data use terms that consistently and unambiguously represents a dataset's allowable data uses. DUO has been implemented by major international stakeholders such as the Broad and Sanger Institutes and is currently used in annotation of over 200,000 datasets worldwide. Using DUO in data management and access facilitates researchers' discovery and access of relevant datasets. DUO annotations increase the FAIRness of datasets and support data linkages using common data use profiles when integrating the data for secondary analyses. DUO is implemented in the Web Ontology Language (OWL) and, to increase community awareness and engagement, hosted in an open, centralized GitHub repository. DUO, together with the GA4GH Passport standard, offers a new, efficient, and streamlined data authorization and access framework that has enabled increased sharing of biomedical datasets worldwide.

GA4GH: International policies and standards for data sharing across genomic research and healthcare

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits.

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1-3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10-18.

Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines

The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different cancer types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple Cancers project, our effort to generate a comprehensive encyclopedia of somatic mutation calls for the TCGA data to enable robust cross-tumor-type analyses. Our approach accounts for variance and batch effects introduced by the rapid advancement of DNA extraction, hybridization-capture, sequencing, and analysis methods over time. We present best practices for applying an ensemble of seven mutation-calling algorithms with scoring and artifact filtering. The dataset created by this analysis includes 3.5 million somatic variants and forms the basis for PanCan Atlas papers. The results have been made available to the research community along with the methods used to generate them. This project is the result of collaboration from a number of institutes and demonstrates how team science drives extremely large genomics projects.

Comprehensive Molecular Characterization of Papillary Renal-Cell Carcinoma

BACKGROUND

Papillary renal-cell carcinoma, which accounts for 15 to 20% of renal-cell carcinomas, is a heterogeneous disease that consists of various types of renal cancer, including tumors with indolent, multifocal presentation and solitary tumors with an aggressive, highly lethal phenotype. Little is known about the genetic basis of sporadic papillary renal-cell carcinoma, and no effective forms of therapy for advanced disease exist.

METHODS

We performed comprehensive molecular characterization of 161 primary papillary renal-cell carcinomas, using whole-exome sequencing, copy-number analysis, messenger RNA and microRNA sequencing, DNA-methylation analysis, and proteomic analysis.

RESULTS

Type 1 and type 2 papillary renal-cell carcinomas were shown to be different types of renal cancer characterized by specific genetic alterations, with type 2 further classified into three individual subgroups on the basis of molecular differences associated with patient survival. Type 1 tumors were associated with MET alterations, whereas type 2 tumors were characterized by CDKN2A silencing, SETD2 mutations, TFE3 fusions, and increased expression of the NRF2-antioxidant response element (ARE) pathway. A CpG island methylator phenotype (CIMP) was observed in a distinct subgroup of type 2 papillary renal-cell carcinomas that was characterized by poor survival and mutation of the gene encoding fumarate hydratase (FH).

CONCLUSIONS

Type 1 and type 2 papillary renal-cell carcinomas were shown to be clinically and biologically distinct. Alterations in the MET pathway were associated with type 1, and activation of the NRF2-ARE pathway was associated with type 2; CDKN2A loss and CIMP in type 2 conveyed a poor prognosis. Furthermore, type 2 papillary renal-cell carcinoma consisted of at least three subtypes based on molecular and phenotypic features. (Funded by the National Institutes of Health.).

Comprehensive, Integrative Genomic Analysis of Diffuse Lower-Grade Gliomas

BACKGROUND

Diffuse low-grade and intermediate-grade gliomas (which together make up the lower-grade gliomas, World Health Organization grades II and III) have highly variable clinical behavior that is not adequately predicted on the basis of histologic class. Some are indolent; others quickly progress to glioblastoma. The uncertainty is compounded by interobserver variability in histologic diagnosis. Mutations in IDH, TP53, and ATRX and codeletion of chromosome arms 1p and 19q (1p/19q codeletion) have been implicated as clinically relevant markers of lower-grade gliomas.

METHODS

We performed genomewide analyses of 293 lower-grade gliomas from adults, incorporating exome sequence, DNA copy number, DNA methylation, messenger RNA expression, microRNA expression, and targeted protein expression. These data were integrated and tested for correlation with clinical outcomes.

RESULTS

Unsupervised clustering of mutations and data from RNA, DNA-copy-number, and DNA-methylation platforms uncovered concordant classification of three robust, nonoverlapping, prognostically significant subtypes of lower-grade glioma that were captured more accurately by IDH, 1p/19q, and TP53 status than by histologic class. Patients who had lower-grade gliomas with an IDH mutation and 1p/19q codeletion had the most favorable clinical outcomes. Their gliomas harbored mutations in CIC, FUBP1, NOTCH1, and the TERT promoter. Nearly all lower-grade gliomas with IDH mutations and no 1p/19q codeletion had mutations in TP53 (94%) and ATRX inactivation (86%). The large majority of lower-grade gliomas without an IDH mutation had genomic aberrations and clinical behavior strikingly similar to those found in primary glioblastoma.

CONCLUSIONS

The integration of genomewide data from multiple platforms delineated three molecular classes of lower-grade gliomas that were more concordant with IDH, 1p/19q, and TP53 status than with histologic class. Lower-grade gliomas with an IDH mutation either had 1p/19q codeletion or carried a TP53 mutation. Most lower-grade gliomas without an IDH mutation were molecularly and clinically similar to glioblastoma. (Funded by the National Institutes of Health.).

Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia

BACKGROUND

Many mutations that contribute to the pathogenesis of acute myeloid leukemia (AML) are undefined. The relationships between patterns of mutations and epigenetic phenotypes are not yet clear.

METHODS

We analyzed the genomes of 200 clinically annotated adult cases of de novo AML, using either whole-genome sequencing (50 cases) or whole-exome sequencing (150 cases), along with RNA and microRNA sequencing and DNA-methylation analysis.

RESULTS

AML genomes have fewer mutations than most other adult cancers, with an average of only 13 mutations found in genes. Of these, an average of 5 are in genes that are recurrently mutated in AML. A total of 23 genes were significantly mutated, and another 237 were mutated in two or more samples. Nearly all samples had at least 1 nonsynonymous mutation in one of nine categories of genes that are almost certainly relevant for pathogenesis, including transcription-factor fusions (18% of cases), the gene encoding nucleophosmin (NPM1) (27%), tumor-suppressor genes (16%), DNA-methylation-related genes (44%), signaling genes (59%), chromatin-modifying genes (30%), myeloid transcription-factor genes (22%), cohesin-complex genes (13%), and spliceosome-complex genes (14%). Patterns of cooperation and mutual exclusivity suggested strong biologic relationships among several of the genes and categories.

CONCLUSIONS

We identified at least one potential driver mutation in nearly all AML samples and found that a complex interplay of genetic events contributes to AML pathogenesis in individual patients. The databases from this study are widely available to serve as a foundation for further investigations of AML pathogenesis, classification, and risk stratification. (Funded by the National Institutes of Health.).

The third pillar of bacterial signal transduction: classification of the extracytoplasmic function (ECF) sigma factor protein family

The ability of a bacterial cell to monitor and adaptively respond to its environment is crucial for survival. After one- and two-component systems, extracytoplasmic function (ECF) sigma factors - the largest group of alternative sigma factors - represent the third fundamental mechanism of bacterial signal transduction, with about six such regulators on average per bacterial genome. Together with their cognate anti-sigma factors, they represent a highly modular design that primarily facilitates transmembrane signal transduction. A comprehensive analysis of the ECF sigma factor protein family identified more than 40 distinct major groups of ECF sigma factors. The functional relevance of this classification is supported by the sequence similarity and domain architecture of cognate anti-sigma factors, genomic context conservation, and potential target promoter motifs. Moreover, this phylogenetic analysis revealed unique features indicating novel mechanisms of ECF-mediated signal transduction. This classification, together with the web tool ECFfinder and the information stored in the Microbial Signal Transduction (MiST) database, provides a comprehensive resource for the analysis of ECF sigma factor-dependent gene regulation.

Backbone 1H, 13C, and 15N NMR assignments for the Cyanothece 51142 protein cce_0567: a protein associated with nitrogen fixation in the DUF683 family

Cyanothece 51142 contains a 78-residue protein, cce_0567, that falls into the DUF683 family of proteins associated with nitrogen fixation. Here we report the assignment of most of the main chain and 13C(beta) side chain resonances of the approximately 40 kDa homo-tetramer.

BioGraphE: high-performance bionetwork analysis using the Biological Graph Environment

Background

Graphs and networks are common analysis representations for biological systems. Many traditional graph algorithms such as k-clique, k-coloring, and subgraph matching have great potential as analysis techniques for newly available data in biology. Yet, as the amount of genomic and bionetwork information rapidly grows, scientists need advanced new computational strategies and tools for dealing with the complexities of the bionetwork analysis and the volume of the data.

Results

We introduce a computational framework for graph analysis called the Biological Graph Environment (BioGraphE), which provides a general, scalable integration platform for connecting graph problems in biology to optimized computational solvers and high-performance systems. This framework enables biology researchers and computational scientists to identify and deploy network analysis applications and to easily connect them to efficient and powerful computational software and hardware that are specifically designed and tuned to solve complex graph problems. In our particular application of BioGraphE to support network analysis in genome biology, we investigate the use of a Boolean satisfiability solver known as Survey Propagation as a core computational solver executing on standard high-performance parallel systems, as well as multi-threaded architectures.

Conclusion

In our application of BioGraphE to conduct bionetwork analysis of homology networks, we found that BioGraphE and a custom, parallel implementation of the Survey Propagation SAT solver were capable of solving very large bionetwork problems at high rates of execution on different high-performance computing platforms.

A conserved structural module regulates transcriptional responses to diverse stress signals in bacteria

A transcriptional response to singlet oxygen in Rhodobacter sphaeroides is controlled by the group IV sigma factor sigma(E) and its cognate anti-sigma ChrR. Crystal structures of the sigma(E)/ChrR complex reveal a modular, two-domain architecture for ChrR. The ChrR N-terminal anti-sigma domain (ASD) binds a Zn(2+) ion, contacts sigma(E), and is sufficient to inhibit sigma(E)-dependent transcription. The ChrR C-terminal domain adopts a cupin fold, can coordinate an additional Zn(2+), and is required for the transcriptional response to singlet oxygen. Structure-based sequence analyses predict that the ASD defines a common structural fold among predicted group IV anti-sigmas. These ASDs are fused to diverse C-terminal domains that are likely involved in responding to specific environmental signals that control the activity of their cognate sigma factor.

Phylogeny of the bacterial superfamily of Crp-Fnr transcription regulators: exploiting the metabolic spectrum by controlling alternative gene programs

The Crp-Fnr regulators, named after the first two identified members, are DNA-binding proteins which predominantly function as positive transcription factors, though roles of repressors are also important. Among over 1200 proteins with an N-terminally located nucleotide-binding domain similar to the cyclic adenosine monophosphate (cAMP) receptor protein, the distinctive additional trait of the Crp-Fnr superfamily is a C-terminally located helix-turn-helix motif for DNA binding. From a curated database of 369 family members exhibiting both features, we provide a protein tree of Crp-Fnr proteins according to their phylogenetic relationships. This results in the assembly of the regulators ArcR, CooA, CprK, Crp, Dnr, FixK, Flp, Fnr, FnrN, MalR, NnrR, NtcA, PrfA, and YeiL and their homologs in distinct clusters. Lead members and representatives of these groups are described, placing emphasis on the less well-known regulators and target processes. Several more groups consist of sequence-derived proteins of unknown physiological roles; some of them are tight clusters of highly similar members. The Crp-Fnr regulators stand out in responding to a broad spectrum of intracellular and exogenous signals such as cAMP, anoxia, the redox state, oxidative and nitrosative stress, nitric oxide, carbon monoxide, 2-oxoglutarate, or temperature. To accomplish their roles, Crp-Fnr members have intrinsic sensory modules allowing the binding of allosteric effector molecules, or have prosthetic groups for the interaction with the signal. The regulatory adaptability and structural flexibility represented in the Crp-Fnr scaffold has led to the evolution of an important group of physiologically versatile transcription factors.

beta -Amyloid peptide-induced apoptosis regulated by a novel protein containing a g protein activation module

Degeneration of neurons in Alzheimer's disease is mediated by beta-amyloid peptide by diverse mechanisms, which include a putative apoptotic component stimulated by unidentified signaling events. This report describes a novel beta-amyloid peptide-binding protein (denoted BBP) containing a G protein-coupling module. BBP is one member of a family of three proteins containing this conserved structure. The BBP subtype bound human beta-amyloid peptide in vitro with high affinity and specificity. Expression of BBP in cell culture induced caspase-dependent vulnerability to beta-amyloid peptide toxicity. Expression of a signaling-deficient dominant negative BBP mutant suppressed sensitivity of human Ntera-2 neurons to beta-amyloid peptide mediated toxicity. These findings suggest that BBP is a target of neurotoxic beta-amyloid peptide and provide new insight into the molecular pathophysiology of Alzheimer's disease.

Radical SAM, a novel protein superfamily linking unresolved steps in familiar biosynthetic pathways with radical mechanisms: functional characterization using new analysis and information visualization methods

A novel protein superfamily with over 600 members was discovered by iterative profile searches and analyzed with powerful bioinformatics and information visualization methods. Evidence exists that these proteins generate a radical species by reductive cleavage of S:-adenosylmethionine (SAM) through an unusual Fe-S center. The superfamily (named here Radical SAM) provides evidence that radical-based catalysis is important in a number of previously well- studied but unresolved biochemical pathways and reflects an ancient conserved mechanistic approach to difficult chemistries. Radical SAM proteins catalyze diverse reactions, including unusual methylations, isomerization, sulfur insertion, ring formation, anaerobic oxidation and protein radical formation. They function in DNA precursor, vitamin, cofactor, antibiotic and herbicide biosynthesis and in biodegradation pathways. One eukaryotic member is interferon-inducible and is considered a candidate drug target for osteoporosis; another is observed to bind the neuronal Cdk5 activator protein. Five defining members not previously recognized as homologs are lysine 2,3-aminomutase, biotin synthase, lipoic acid synthase and the activating enzymes for pyruvate formate-lyase and anaerobic ribonucleotide reductase. Two functional predictions for unknown proteins are made based on integrating other data types such as motif, domain, operon and biochemical pathway into an organized view of similarity relationships.

The complete DNA sequence and analysis of the large virulence plasmid of Escherichia coli O157:H7

The complete DNA sequence of pO157, the large virulence plasmid of EHEC strain O157:H7 EDL 933, is presented. The 92 kb F-like plasmid is composed of segments of putative virulence genes in a framework of replication and maintenance regions, with seven insertion sequence elements, located mostly at the boundaries of the virulence segments. One hundred open reading frames (ORFs) were identified, of which 19 were previously sequenced potential virulence genes. Forty-two ORFs were sufficiently similar to known proteins for suggested functions to be assigned, and 22 had no convincing similarity with any known proteins. Of the newly identified genes, an unusually large ORF of 3169 amino acids has a putative cytotoxin active site shared with the large clostridial toxin (LCT) family and proteins such as ToxA and B of Clostridium difficile . A conserved motif was detected that links the large ORF and the LCT proteins with the OCH1 family of glycosyltransferases. In the complete sequence, the mosaic form can be observed at the levels of base composition, codon usage and gene organization. Insights were obtained from patterns of DNA composition as well as the pathogenic and 'housekeeping' gene segments. Evolutionary trees built from shared plasmid maintenance genes show that even these genes have heterogeneous origins.

Analysis of the Escherichia coli genome VI: DNA sequence of the region from 92.8 through 100 minutes

The 338.5 kb of the Escherichia coli genome described here together with previously described segments bring the total of contiguous finished sequence of this genome to > 1 Mb. Of 319 open reading frames (ORFs) found in this 338.5 kb segment, 147 (46%) are potential new genes. The positions of several genes which had been previously located here by mapping or partial sequencing have been confirmed. Several ORFs have functions suggested by similarities to other characterised genes but cannot be assigned with certainty. Fifteen of the ORFs of unknown function had been previously sequenced. Eight transfer RNAs are encoded in the region and there are two grey holes in which no features were found. The attachment site for phage P4 and three insertion sequences were located. The region was also analysed for chi sites, bend sites, REP elements and other repeats. A computer search identified potential promoters and tentative transcription units were assigned. The occurrence of the rare tetramer CTAG was analysed in 1.6 Mb of contiguous E.coli sequence. Hypotheses addressing the rarity and distribution of CTAG are discussed.

Analysis of the Escherichia coli genome. V. DNA sequence of the region from 76.0 to 81.5 minutes

The DNA sequence of a 225.4 kilobase segment of the Escherichia coli K-12 genome is described here, from 76.0 to 81.5 minutes on the genetic map. This brings the total of contiguous sequence from the E.coli genome project to 725.1 kb (76.0 to 92.8 minutes). We found 191 putative coding genes (ORFs) of which 72 genes were previously known, and 110 of which remain unidentified despite literature and similarity searches. Seven new genes--arsE, arsF, arsG, treF, xylR, xylG, and xylH--were identified as well as the previously mapped pit and dctA genes. The arrangement of proposed genes relative to possible promoters and terminators suggests 90 potential transcription units. Other features include 19 REP elements, 95 computer-predicted bends, 50 Chi sites, and one grey hole. Thirty-one putative signal peptides were found, including those of thirteen known membrane or periplasmic proteins. One tRNA gene (proK) and two insertion sequences (IS5 and IS150) are located in this segment. The genes in this region are organized with equal numbers oriented with or against replication.

Analysis of the Escherichia coli genome. IV. DNA sequence of the region from 89.2 to 92.8 minutes

We present the sequence of 176 kilobases of the Escherichia coli K-12 genome, from katG at 89.2 to an open reading frame (ORF) of unknown function at 92.8 minutes on the genetic map. This brings the total of contiguous sequence from the E. coli genome project to 500 kb (81.5 to 92.8 minutes). This segment contains 134 putative coding genes (ORFs) of which 66 genes were previously identified. Eight new genes--acs, pepE, and nrfB-G--were identified as well as the previously mapped gldA and alr genes. Still, 58 ORFs remain unidentified despite literature and similarity searches. The arrangement of proposed genes relative to possible promoters and terminators suggests 55 potential transcription units. Other features include 13 REP elements, one IRU (ERIC) repeat, 59 computer-predicted bends, 42 Chi sites and one new grey hole. Sixteen signal peptides were found, including those of lamB, btuB, and malE. Two ribosomal RNA loci, rrnB and rrnE, are located in this segment, so we have now sequenced four of the seven E. coli rRNA loci. Comparison of the rRNA loci reveals some differences in the ribosomal structural RNAs which are generally compatible with the proposed secondary structures.