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Escherichia coli is a model laboratory bacterium, a species that is widely distributed in the environment, as well as a mutualist and pathogen in its human hosts. As such, E. coli represents an attractive organism to study how environment impacts microbial genome structure and function. Uropathogenic E. coli (UPEC) must adapt to life in several microbial communities in the human body, and has a complex life cycle in the bladder when it causes acute or recurrent urinary tract infection (UTI). Several studies designed to identify virulence factors have focused on genes that are uniquely represented in UPEC strains, whereas the role of genes that are common to all E. coli has received much less attention. Here we describe the complete 5,065,741-bp genome sequence of a UPEC strain recovered from a patient with an acute bladder infection and compare it with six other finished E. coli genome sequences. We searched 3,470 ortholog sets for genes that are under positive selection only in UPEC strains. Our maximum likelihood-based analysis yielded 29 genes involved in various aspects of cell surface structure, DNA metabolism, nutrient acquisition, and UTI. These results were validated by resequencing a subset of the 29 genes in a panel of 50 urinary, periurethral, and rectal E. coli isolates from patients with UTI. These studies outline a computational approach that may be broadly applicable for studying strain-specific adaptation and pathogenesis in other bacteria.

Salmonella enterica serovars often have a broad host range, and some cause both gastrointestinal and systemic disease. But the serovars Paratyphi A and Typhi are restricted to humans and cause only systemic disease. It has been estimated that Typhi arose in the last few thousand years. The sequence and microarray analysis of the Paratyphi A genome indicates that it is similar to the Typhi genome but suggests that it has a more recent evolutionary origin. Both genomes have independently accumulated many pseudogenes among their approximately 4,400 protein coding sequences: 173 in Paratyphi A and approximately 210 in Typhi. The recent convergence of these two similar genomes on a similar phenotype is subtly reflected in their genotypes: only 30 genes are degraded in both serovars. Nevertheless, these 30 genes include three known to be important in gastroenteritis, which does not occur in these serovars, and four for Salmonella-translocated effectors, which are normally secreted into host cells to subvert host functions. Loss of function also occurs by mutation in different genes in the same pathway (e.g., in chemotaxis and in the production of fimbriae).

Multiple myeloma (MM) is an incurable, B-cell malignancy characterized by the clonal proliferation and accumulation of malignant plasma cells in bone marrow. Despite recent advances in the understanding of genomic aberrations, a comprehensive catalogue of clinically actionable mutations in MM is just beginning to emerge. The tyrosine kinase (TK) and RAS oncogenes, which encode important regulators of various signaling pathways, are among the most frequently altered gene families in cancer. To clarify the role of TK and RAS genes in the pathogenesis of MM, we performed a systematic, targeted screening of mutations on prioritized RAS and TK genes, in CD138-sorted bone marrow specimens from 42 untreated patients. We identified a total of 24 mutations in the KRAS, PIK3CA, INSR, LTK, and MERTK genes. In particular, seven novel mutations in addition to known KRAS mutations were observed. Prediction analysis tools PolyPhen and Sorting Intolerant from Tolerant (SIFT) were used to assess the functional significance of these novel mutations. Our analysis predicted that these mutations may have a deleterious effect, resulting in the functional alteration of proteins involved in the pathogenesis of myeloma. While further investigation is needed to determine the functional consequences of these proteins, mutational testing of the RAS and TK genes in larger myeloma cohorts might also be useful to establish the recurrent nature of these mutations.

The sequence of any genome becomes most useful for biological experimentation when a complete and accurate gene set is available. Gene prediction programs offer an efficient way to generate an automated gene set. Manual annotation, when performed by experienced annotators, is more accurate and complete than automated annotation. However, it is a laborious and expensive process, and by its nature, introduces a degree of variability not found with automated annotation. EAnnot (Electronic Annotation) is a program originally developed for manually annotating the human genome. It combines the latest bioinformatics tools to extract and analyze a wide range of publicly available data in order to achieve fast and reliable automatic gene prediction and annotation. EAnnot builds gene models based on mRNA, EST, and protein alignments to genomic sequence, attaches supporting evidence to the corresponding genes, identifies pseudogenes, and locates poly(A) sites and signals. Here, we compare manual annotation of human chromosome 6 with annotation performed by EAnnot in order to assess the latter's accuracy. EAnnot can readily be applied to manual annotation of other eukaryotic genomes and can be used to rapidly obtain an automated gene set.

Human chromosome 2 is unique to the human lineage in being the product of a head-to-head fusion of two intermediate-sized ancestral chromosomes. Chromosome 4 has received attention primarily related to the search for the Huntington's disease gene, but also for genes associated with Wolf-Hirschhorn syndrome, polycystic kidney disease and a form of muscular dystrophy. Here we present approximately 237 million base pairs of sequence for chromosome 2, and 186 million base pairs for chromosome 4, representing more than 99.6% of their euchromatic sequences. Our initial analyses have identified 1,346 protein-coding genes and 1,239 pseudogenes on chromosome 2, and 796 protein-coding genes and 778 pseudogenes on chromosome 4. Extensive analyses confirm the underlying construction of the sequence, and expand our understanding of the structure and evolution of mammalian chromosomes, including gene deserts, segmental duplications and highly variant regions.

Abstract 301 Multiple myeloma (MM) is an incurable B-cell malignancy characterized by the clonal proliferation and accumulation of malignant plasma cells in the bone marrow. Despite the growing number of sequencing studies, the comprehensive view of somatic mutations in multiple myeloma is far from clear. One of the most frequently altered gene families in most human cancer is the Ras and the tyrosine kinase (TK) genes, which encode for important regulators of various signal transduction pathways. To uncover the somatic mutation profile of Ras gene and TKs in myeloma, we performed a systematic mutation screening from a selected group of 10 candidate genes in 42 primary myeloma patients. The candidate gene selections were based on the highly altered genes extracted from GEO data sets using Function Express, a data mining and viewer for microarray data. The sequencing of the entire gene region including the promoter and the 3`UTR was performed in the Genome sequencing center at Washington University medical center using the standard resequencing pipeline, from the design of the primers to data output. These data were analyzed with a clinical resequencing pipeline and visualized using the Mutation Viewer software (MV v5.1). We identified 24 nonsynonymous alterations in five genes (KRAS2, PIK3CA, INSR, LTK and MERTK) in our myeloma cohort (Table 1). In particular, we identified the previously reported pathogenic mutation in a KRAS gene and novel somatic mutations in the Kinase family (PIK3CA) that would be expected to cause structural changes. We assessed the frequency plots of the known variants and most but not all are significantly different from the normal data set. The overall results suggest that the germline genetic background besides the somatically acquired mutations may exert an important influence on the prognosis and outcome of the myeloma patient. Our genome-wide resequencing approach thus revealed previously known and novel oncogenic mutations in multiple myeloma, but its relevance needs to be considered in the context of other genetic abnormalities. Table 1: DNA alterations in candidate ras and TK genes in primary multiple myeloma Gene Gene IDa Nucleotide changeb Amino acid change Zygosityc PolyPhen COSMIC KRAS2 3845 c.35 G>A p.G12D Hetero P. Dam Yes KRAS2 3845 c.34 G>T, c.33 T>C p.G12C, A11A Hetero Benign Yes KRAS2 3845 c.183 A>C p.Q61H Hetero P. Dam Yes KRAS2 3845 c.186_194 del p.E62_Y64 Homo PIK3CA 5290 c.928 C>T p.R310C Hetero Yes PIK3CA 5290 c.1173 A>G p.I391M Hetero Benign INSR 3643 c.356 C>T p.A119V Hetero INSR 3643 c.2243 C>T p.S748L Hetero INSR 3643 c.3034 G>A p.V1012M Hetero P. Dam LTK 4058 c.125 G>A p.R42Q Hetero Benign LTK 4058 c.680 C>T p.P227L Hetero LTK 4058 c.728 G>A p.R243Q Hetero LTK 4058 c.1603 G>A p.D535N Hetero MERTK 10461 c.60 A>T p.R20S Hetero Benign MERTK 10461 c.1552 A>G p.I518V Hetero, Homo Benign MERTK 10461 c.1397 G>A p.R466K Hetero, Homo Benign MERTK 10461 c.353 G>A p.S118N Hetero, Homo Benign MERTK 10461 c.2608 G>A p.V870I Hetero Benign MERTK 10461 c.844 G>A p.A282T Hetero Benign MERTK 10461 c.1493 A>G, c.1494 C>T p.N498S Hetero Benign MERTK 10461 c.878 G>A p.R293H Hetero Benign MERTK 10461 c.2593 C>T p.R865W Hetero P. Dam MERTK 10461 c.2069 C>T p.T690I Hetero Benign MERTK 10461 c.2467 G>C p.E823Q Hetero Benign a Gene ID at National center for biotechnology information (http://www.ncbi.nlm.nih.gov/sites/entrez) b del., deletion c Homo, homozygous; hetero, heterozygous Disclosures: No relevant conflicts of interest to declare.