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An incomplete ascertainment of genetic variation within the highly polymorphic immunoglobulin heavy chain locus (IGH) has hindered our ability to define genetic factors that influence antibody-mediated processes. Due to locus complexity, standard high-throughput approaches have failed to accurately and comprehensively capture IGH polymorphism. As a result, the locus has only been fully characterized two times, severely limiting our knowledge of human IGH diversity. Here, we combine targeted long-read sequencing with a novel bioinformatics tool, IGenotyper, to fully characterize IGH variation in a haplotype-specific manner. We apply this approach to eight human samples, including a haploid cell line and two mother-father-child trios, and demonstrate the ability to generate high-quality assemblies (>98% complete and >99% accurate), genotypes, and gene annotations, identifying 2 novel structural variants and 15 novel IGH alleles. We show multiplexing allows for scaling of the approach without impacting data quality, and that our genotype call sets are more accurate than short-read (>35% increase in true positives and >97% decrease in false-positives) and array/imputation-based datasets. This framework establishes a desperately needed foundation for leveraging IG genomic data to study population-level variation in antibody-mediated immunity, critical for bettering our understanding of disease risk, and responses to vaccines and therapeutics.

Whole-genome sequencing (WGS) of Staphylococcus aureus is increasingly used as part of infection prevention practices. In this study, we established a long-read technology-based WGS screening program of all first-episode methicillin-resistant Staphylococcus aureus (MRSA) blood infections at a major urban hospital., Whole-genome sequencing (WGS) of Staphylococcus aureus is increasingly used as part of infection prevention practices. In this study, we established a long-read technology-based WGS screening program of all first-episode methicillin-resistant Staphylococcus aureus (MRSA) blood infections at a major urban hospital. A survey of 132 MRSA genomes assembled from long reads enabled detailed characterization of an outbreak lasting several months of a CC5/ST105/USA100 clone among 18 infants in a neonatal intensive care unit (NICU). Available hospital-wide genome surveillance data traced the origins of the outbreak to three patients admitted to adult wards during a 4-month period preceding the NICU outbreak. The pattern of changes among complete outbreak genomes provided full spatiotemporal resolution of its progression, which was characterized by multiple subtransmissions and likely precipitated by equipment sharing between adults and infants. Compared to other hospital strains, the outbreak strain carried distinct mutations and accessory genetic elements that impacted genes with roles in metabolism, resistance, and persistence. This included a DNA recognition domain recombination in the hsdS gene of a type I restriction modification system that altered DNA methylation. Transcriptome sequencing (RNA-Seq) profiling showed that the (epi)genetic changes in the outbreak clone attenuated agr gene expression and upregulated genes involved in stress response and biofilm formation. Overall, our findings demonstrate the utility of long-read sequencing for hospital surveillance and for characterizing accessory genomic elements that may impact MRSA virulence and persistence.

The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (, Structural variants (SVs) in human genomes contribute diversity and diseases. Here, the authors use a multi-platform strategy to generate haplotype-resolved SVs for three human parent–child trios.

Whole-genome sequencing (WGS) of Staphylococcus aureus is increasingly used as part of infection prevention practices, but most applications are focused on conserved core genomic regions due to limitations of short-read technologies. In this study we established a long-read technology-based WGS screening program of all first-episode MRSA blood infections at a major urban hospital. A survey of 132 MRSA genomes assembled from long reads revealed widespread gain/loss of accessory mobile genetic elements among established hospital- and community-associated lineages impacting >10% of each genome, and frequent megabase-scale inversions between endogenous prophages. We also characterized an outbreak of a CC5/ST105/USA100 clone among 3 adults and 18 infants in a neonatal intensive care unit (NICU) lasting 7 months. The pattern of changes among complete outbreak genomes provided full spatiotemporal resolution of its origins and progression, which was characterized by multiple sub-transmissions and likely precipitated by equipment sharing. Compared to other hospital strains, the outbreak strain carried distinct mutations and accessory genetic elements that impacted genes with roles in metabolism, resistance and persistence. This included a DNA-recognition domain recombination in the hsdS gene of a Type-I restriction-modification system that altered DNA methylation. RNA-Seq profiling showed that the (epi)genetic changes in the outbreak clone attenuated agr gene expression and upregulated genes involved in stress response and biofilm formation. Overall our findings demonstrate that long-read sequencing substantially improves our ability to characterize accessory genomic elements that impact MRSA virulence and persistence, and provides valuable information for infection control efforts.

Motivation: Long arrays of near-identical tandem repeats are a common feature of centromeric and subtelomeric regions in complex genomes. These sequences present a source of repeat structure diversity that is commonly ignored by standard genomic tools. Unlike reads shorter than the underlying repeat structure that rely on indirect inference methods, e.g. assembly, long reads allow direct inference of satellite higher order repeat structure. To automate characterization of local centromeric tandem repeat sequence variation we have designed Alpha-CENTAURI (ALPHA satellite CENTromeric AUtomated Repeat Identification), that takes advantage of Pacific Bioscience long-reads from whole-genome sequencing datasets. By operating on reads prior to assembly, our approach provides a more comprehensive set of repeat-structure variants and is not impacted by rearrangements or sequence underrepresentation due to misassembly. Results: We demonstrate the utility of Alpha-CENTAURI in characterizing repeat structure for alpha satellite containing reads in the hydatidiform mole (CHM1, haploid-like) genome. The pipeline is designed to report local repeat organization summaries for each read, thereby monitoring rearrangements in repeat units, shifts in repeat orientation and sites of array transition into non-satellite DNA, typically defined by transposable element insertion. We validate the method by showing consistency with existing centromere high order repeat references. Alpha-CENTAURI can, in principle, run on any sequence data, offering a method to generate a sequence repeat resolution that could be readily performed using consensus sequences available for other satellite families in genomes without high-quality reference assemblies. Availability and implementation: Documentation and source code for Alpha-CENTAURI are freely available at http://github.com/volkansevim/alpha-CENTAURI. Contact: ali.bashir@mssm.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Therapy for bacteremia caused by Staphylococcus aureus is often ineffective, even when treatment conditions are optimal according to experimental protocols. Adapted subclones, such as those bearing mutations that attenuate agr-mediated virulence activation, are associated with persistent infection and patient mortality., Therapy for bacteremia caused by Staphylococcus aureus is often ineffective, even when treatment conditions are optimal according to experimental protocols. Adapted subclones, such as those bearing mutations that attenuate agr-mediated virulence activation, are associated with persistent infection and patient mortality. To identify additional alterations in agr-defective mutants, we sequenced and assembled the complete genomes of clone pairs from colonizing and infected sites of several patients in whom S. aureus demonstrated a within-host loss of agr function. We report that events associated with agr inactivation result in agr-defective blood and nares strain pairs that are enriched in mutations compared to pairs from wild-type controls. The random distribution of mutations between colonizing and infecting strains from the same patient, and between strains from different patients, suggests that much of the genetic complexity of agr-defective strains results from prolonged infection or therapy-induced stress. However, in one of the agr-defective infecting strains, multiple genetic changes resulted in increased virulence in a murine model of bloodstream infection, bypassing the mutation of agr and raising the possibility that some changes were selected. Expression profiling correlated the elevated virulence of this agr-defective mutant to restored expression of the agr-regulated ESAT6-like type VII secretion system, a known virulence factor. Thus, additional mutations outside the agr locus can contribute to diversification and adaptation during infection by S. aureus agr mutants associated with poor patient outcomes.

Clostridioides difficileis a leading cause of health care-associated infections. Although significant progress has been made in the understanding of its genome, the epigenome ofC. difficileand its functional impact has not been systematically explored. Here, we performed the first comprehensive DNA methylome analysis ofC. difficileusing 36 human isolates and observed great epigenomic diversity. We discovered an orphan DNA methyltransferase with a well-defined specificity whose corresponding gene is highly conserved across our dataset and in all ~300 globalC. difficilegenomes examined. Inactivation of the methyltransferase gene negatively impacted sporulation, a key step inC. difficiledisease transmission, consistently supported by multi-omics data, genetic experiments, and a mouse colonization model. Further experimental and transcriptomic analysis also suggested that epigenetic regulation is associated with cell length, biofilm formation, and host colonization. These findings open up a new epigenetic dimension to characterize medically relevant biological processes in this critical pathogen. This work also provides a set of methods for comparative epigenomics and integrative analysis, which we expect to be broadly applicable to bacterial epigenomics studies.

Clostridioides (formerly Clostridium) difficile is a leading cause of healthcare-associated infections. Although considerable progress has been made in the understanding of its genome, the epigenome of C. difficile and its functional impact has not been systematically explored. Here, we perform a comprehensive DNA methylome analysis of C. difficile using 36 human isolates and observe a high level of epigenomic diversity. We discovered an orphan DNA methyltransferase with a well-defined specificity, the corresponding gene of which is highly conserved across our dataset and in all of the approximately 300 global C. difficile genomes examined. Inactivation of the methyltransferase gene negatively impacts sporulation, a key step in C. difficile disease transmission, and these results are consistently supported by multiomics data, genetic experiments and a mouse colonization model. Further experimental and transcriptomic analyses suggest that epigenetic regulation is associated with cell length, biofilm formation and host colonization. These findings provide a unique epigenetic dimension to characterize medically relevant biological processes in this important pathogen. This study also provides a set of methods for comparative epigenomics and integrative analysis, which we expect to be broadly applicable to bacterial epigenomic studies. In this work, Fang et al. analyse the epigenetic landscape of Clostridioides difficile and identify a DNA methyltransferase present across C. difficile strains that is required for optimal sporulation and in vivo colonization and disease.

The mammalian lacrimal gland secretes an aqueous solution in which different chemical substances are present, including proteins and carbohydrates. The histochemical investigations on characterization of camel lacrimal secretion are limited. This study aimed to determine the histochemical properties of the dromedary camel lacrimal gland. Glandular samples of twenty healthy adult camels of both sexes were collected at Omdurman slaughterhouse, Sudan. The camel lacrimal gland was compound with tubulo-acinar mixed secretory units, having serous and mucous cells. Best’s carmine reactionwas negative, whereas a strong positive reaction to periodic acid-Schiff's (PAS) diastase resistant was observed in most of the secretory units; the reactions to alcian blue (AB pH 2.5) and aldehyde fuchsin (AF) were strong in the glandular tubules and weak or negative in the acini. Goblet cells in the epithelium of the interlobular ducts were strongly PAS, AB pH2.5 and AF positive.Both acini and tubules showed positive reactions to acid and alkaline phosphatases especially in their apical parts. These results suggest that the predominant acini secretion was serous which contained mainly neutral mucopolysaccharides, whereas the tubules secretion was mucous thatcontained sulfated and carboxylated acid mucopolysaccharides. Moreover, the different staining properties of the camel lacrimal secretion reflect various physiological functions.

Unlike other domestic animals the dromedary camel (Camelusdromedarius) lacks the lacrimal puncta, and hence, the lacrimal secretion function seems to be confined to the washing and moistening of the anterior surface of the eyeball. This study was conducted with the aim of studying the histological structure of the lacrimal gland of the dromedary camel. The study was performed on lacrimalglandsoffifteen animals obtained from Omdurman slaughter house, Khartoum, Sudan. The results revealed that the lacrimal gland was lobulated compound tubuloacinar with clusters of serous secretory end-pieces which were lined by a simple cuboidal epithelium of pyramidal cells. The dense connective tissue capsule sent connective tissue septa which divided the gland into lobes and lobules. The intralobular ducts were lined by simple columnar epithelium, whereas the interlobular and excretory ducts were lined by stratified columnar or pseudo-stratified columnar epithelium rich in goblet cells, melanin granules and lymphatic infiltration. The lymphocytes were replaced by a well-defined ring of lymphatic nodules around the conjunctival end of the excretory duct. The watery lacrimal secretion is suggested to be helpful in washing and moistening activitiesof the anterior part of the eyeball which is important in the camel dry, hot and dusty environment. Moreover, the increased diffuse and nodular lymphaticsin the excretory ducts might be due toincreased immune response along the draining duct. Keywords: Lacrimal gland,Dromedary Camel, Histology.

The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, and strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three human parent–child trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (

It was with great interest that we read the recently published article by Yu et al. ([1][1]), which proposes a solution to the problem of building complete and accurate databases of germline Ig (IG) and TCR genes and alleles. This highlights one of the most formidable challenges in the

Background The human genome contains variants ranging in size from small single nucleotide polymorphisms (SNPs) to large structural variants (SVs). High-quality benchmark small variant calls for the pilot National Institute of Standards and Technology (NIST) Reference Material (NA12878) have been developed by the Genome in a Bottle Consortium, but no similar high-quality benchmark SV calls exist for this genome. Since SV callers output highly discordant results, we developed methods to combine multiple forms of evidence from multiple sequencing technologies to classify candidate SVs into likely true or false positives. Our method (svclassify) calculates annotations from one or more aligned bam files from many high-throughput sequencing technologies, and then builds a one-class model using these annotations to classify candidate SVs as likely true or false positives. Results We first used pedigree analysis to develop a set of high-confidence breakpoint-resolved large deletions. We then used svclassify to cluster and classify these deletions as well as a set of high-confidence deletions from the 1000 Genomes Project and a set of breakpoint-resolved complex insertions from Spiral Genetics. We find that likely SVs cluster separately from likely non-SVs based on our annotations, and that the SVs cluster into different types of deletions. We then developed a supervised one-class classification method that uses a training set of random non-SV regions to determine whether candidate SVs have abnormal annotations different from most of the genome. To test this classification method, we use our pedigree-based breakpoint-resolved SVs, SVs validated by the 1000 Genomes Project, and assembly-based breakpoint-resolved insertions, along with semi-automated visualization using svviz. Conclusions We find that candidate SVs with high scores from multiple technologies have high concordance with PCR validation and an orthogonal consensus method MetaSV (99.7 % concordant), and candidate SVs with low scores are questionable. We distribute a set of 2676 high-confidence deletions and 68 high-confidence insertions with high svclassify scores from these call sets for benchmarking SV callers. We expect these methods to be particularly useful for establishing high-confidence SV calls for benchmark samples that have been characterized by multiple technologies. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2366-2) contains supplementary material, which is available to authorized users.

Mutations at positions 70 and/or 91 in the core protein of genotype-1b, hepatitis C virus (HCV) are associated with hepatocellular carcinoma (HCC) risk in Asian patients. To evaluate this in a US population, the relationship between the percentage of 70 and/or 91 mutant HCV quasispecies in baseline serum samples of chronic HCV patients from the HALT-C trial and the incidence of HCC was determined by deep sequencing. Quasispecies percentage cut-points, ≥42% of non-arginine at 70 (non-R70) or ≥98.5% of non-leucine at 91 (non-L91) had optimal sensitivity at discerning higher or lower HCC risk. In baseline samples, 88.5% of chronic HCV patients who later developed HCC and 68.8% of matched HCC-free control patients had ≥42% non-R70 quasispecies (P = 0.06). Furthermore, 30.8% of patients who developed HCC and 54.7% of matched HCC-free patients had quasispecies with ≥98.5% non-L91 (P = 0.06). By Kaplan-Meier analysis, HCC incidence was higher, but not statistically significant, among patients with quasispecies ≥42% non-R70 (P = 0.08), while HCC incidence was significantly reduced among patients with quasispecies ≥98.5% non-L91 (P = 0.01). In a Cox regression model, non-R70 ≥42% was associated with increased HCC risk. This study of US patients indicates the potential utility of HCV quasispecies analysis as a non-invasive biomarker of HCC risk.

The multikilobase reads that can be produced by single-molecule sequencing technologies may span complex, repetitive genomic regions but have high error rates. Bashir et al. use these reads to organize contigs assembled from accurate, short-read data, facilitating the analysis of clinically important regions of an outbreak strain of cholera. Advances in DNA sequencing technology have improved our ability to characterize most genomic diversity. However, accurate resolution of large structural events is challenging because of the short read lengths of second-generation technologies. Third-generation sequencing technologies, which can yield longer multikilobase reads, have the potential to address limitations associated with genome assembly. Here we combine sequencing data from second- and third-generation DNA sequencing technologies to assemble the two-chromosome genome of a recent Haitian cholera outbreak strain into two nearly finished contigs at >99.9% accuracy. Complex regions with clinically relevant structure were completely resolved. In separate control assemblies on experimental and simulated data for the canonical N16961 cholera reference strain, we obtained 14 scaffolds of greater than 1 kb for the experimental data and 8 scaffolds of greater than 1 kb for the simulated data, which allowed us to correct several errors in contigs assembled from the short-read data alone. This work provides a blueprint for the next generation of rapid microbial identification and full-genome assembly.

Motivation: Structural variation including deletions, duplications and rearrangements of DNA sequence are an important contributor to genome variation in many organisms. In human, many structural variants are found in complex and highly repetitive regions of the genome making their identification difficult. A new sequencing technology called strobe sequencing generates strobe reads containing multiple subreads from a single contiguous fragment of DNA. Strobe reads thus generalize the concept of paired reads, or mate pairs, that have been routinely used for structural variant detection. Strobe sequencing holds promise for unraveling complex variants that have been difficult to characterize with current sequencing technologies.Results: We introduce an algorithm for identification of structural variants using strobe sequencing data. We consider strobe reads from a test genome that have multiple possible alignments to a reference genome due to sequencing errors and/or repetitive sequences in the reference. We formulate the combinatorial optimization problem of finding the minimum number of structural variants in the test genome that are consistent with these alignments. We solve this problem using an integer linear program. Using simulated strobe sequencing data, we show that our algorithm has better sensitivity and specificity than paired read approaches for structural variation identification.Contact: braphael@brown.edu

Motivation: Structural variants, including duplications, insertions, deletions and inversions of large blocks of DNA sequence, are an important contributor to human genome variation. Measuring structural variants in a genome sequence is typically more challenging than measuring single nucleotide changes. Current approaches for structural variant identification, including paired-end DNA sequencing/mapping and array comparative genomic hybridization (aCGH), do not identify the boundaries of variants precisely. Consequently, most reported human structural variants are poorly defined and not readily compared across different studies and measurement techniques. Results: We introduce Geometric Analysis of Structural Variants (GASV), a geometric approach for identification, classification and comparison of structural variants. This approach represents the uncertainty in measurement of a structural variant as a polygon in the plane, and identifies measurements supporting the same variant by computing intersections of polygons. We derive a computational geometry algorithm to efficiently identify all such intersections. We apply GASV to sequencing data from nine individual human genomes and several cancer genomes. We obtain better localization of the boundaries of structural variants, distinguish genetic from putative somatic structural variants in cancer genomes, and integrate aCGH and paired-end sequencing measurements of structural variants. This work presents the first general framework for comparing structural variants across multiple samples and measurement techniques, and will be useful for studies of both genetic structural variants and somatic rearrangements in cancer. Availability: http://cs.brown.edu/people/braphael/software.html Contact: braphael@brown.edu

Background High-throughput bacterial 16S rRNA gene sequencing followed by clustering of short sequences into operational taxonomic units (OTUs) is widely used for microbiome profiling. However, clustering of short 16S rRNA gene reads into biologically meaningful OTUs is challenging, in part because nucleotide variation along the 16S rRNA gene is only partially captured by short reads. The recent emergence of long-read platforms, such as single-molecule real-time (SMRT) sequencing from Pacific Biosciences, offers the potential for improved taxonomic and phylogenetic profiling. Here, we evaluate the performance of long- and short-read 16S rRNA gene sequencing using simulated and experimental data, followed by OTU inference using computational pipelines based on heuristic and complete-linkage hierarchical clustering. Results In simulated data, long-read sequencing was shown to improve OTU quality and decrease variance. We then profiled 40 human gut microbiome samples using a combination of Illumina MiSeq and Blautia-specific SMRT sequencing, further supporting the notion that long reads can identify additional OTUs. We implemented a complete-linkage hierarchical clustering strategy using a flexible computational pipeline, tailored specifically for PacBio circular consensus sequencing (CCS) data that outperforms heuristic methods in most settings: https://github.com/oscar-franzen/oclust/. Conclusion Our data demonstrate that long reads can improve OTU inference; however, the choice of clustering algorithm and associated clustering thresholds has significant impact on performance. Electronic supplementary material The online version of this article (doi:10.1186/s40168-015-0105-6) contains supplementary material, which is available to authorized users.

The growing gap between the demand for genome sequencing and the supply of trained genomics professionals is creating an acute need to develop more effective genomics education. In response we developed “Practical Analysis of Your Personal Genome”, a novel laboratory-style medical genomics course in which students have the opportunity to obtain and analyze their own whole genome. This report describes our motivations for and the content of a “practical” genomics course that incorporates personal genome sequencing and the lessons we learned during the first three iterations of this course. Electronic supplementary material The online version of this article (doi:10.1186/s12920-015-0124-y) contains supplementary material, which is available to authorized users.

Whole-genome sequences for Stenotrophomonas maltophilia serial isolates from a bacteremic patient before and after development of levofloxacin resistance were assembled de novo and differed by one single-nucleotide variant in smeT , a repressor for multidrug efflux operon smeDEF . Along with sequenced isolates from five contemporaneous cases, they displayed considerable diversity compared against all published complete genomes. Whole-genome sequencing and complete assembly can conclusively identify resistance mechanisms emerging in S. maltophilia strains during clinical therapy.

Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.

Tyrosine kinase domain mutations are a common cause of acquired clinical resistance to tyrosine kinase inhibitors (TKI) used to treat cancer, including the FLT3 inhibitor quizartinib. Mutation of kinase “gatekeeper” residues, which control access to an allosteric pocket adjacent to the ATP-binding site, has been frequently implicated in TKI resistance. The molecular underpinnings of gatekeeper mutation–mediated resistance are incompletely understood. We report the first cocrystal structure of FLT3 with the TKI quizartinib, which demonstrates that quizartinib binding relies on essential edge-to-face aromatic interactions with the gatekeeper F691 residue, and F830 within the highly conserved Asp-Phe-Gly motif in the activation loop. This reliance makes quizartinib critically vulnerable to gatekeeper and activation loop substitutions while minimizing the impact of mutations elsewhere. Moreover, we identify PLX3397, a novel FLT3 inhibitor that retains activity against the F691L mutant due to a binding mode that depends less vitally on specific interactions with the gatekeeper position. Significance: We report the first cocrystal structure of FLT3 with a kinase inhibitor, elucidating the structural mechanism of resistance due to the gatekeeper F691L mutation. PLX3397 is a novel FLT3 inhibitor with in vitro activity against this mutation but is vulnerable to kinase domain mutations in the FLT3 activation loop. Cancer Discov; 5(6); 668–79. ©2015 AACR. This article is highlighted in the In This Issue feature, p. 565

Knowledge about structural variation in the human genome has grown tremendously in the past few years. However, inversions represent a class of structural variation that remains difficult to detect. We present a statistical method to identify large inversion polymorphisms using unusual Linkage Disequilibrium (LD) patterns from high-density SNP data. The method is designed to detect chromosomal segments that are inverted (in a majority of the chromosomes) in a population with respect to the reference human genome sequence. We demonstrate the power of this method to detect such inversion polymorphisms through simulations done using the HapMap data. Application of this method to the data from the first phase of the International HapMap project resulted in 176 candidate inversions ranging from 200 kb to several megabases in length. Our predicted inversions include an 800-kb polymorphic inversion at 7p22, a 1.1-Mb inversion at 16p12, and a novel 1.2-Mb inversion on chromosome 10 that is supported by the presence of two discordant fosmids. Analysis of the genomic sequence around inversion breakpoints showed that 11 predicted inversions are flanked by pairs of highly homologous repeats in the inverted orientation. In addition, for three candidate inversions, the inverted orientation is represented in the Celera genome assembly. Although the power of our method to detect inversions is restricted because of inherently noisy LD patterns in population data, inversions predicted by our method represent strong candidates for experimental validation and analysis.

We present the first comprehensive analysis of a diploid human genome that combines single-molecule sequencing with single-molecule genome maps. Our hybrid assembly markedly improves upon the contiguity observed from traditional shotgun sequencing approaches, with scaffold N50 values approaching 30 Mb, and we identified complex structural variants (SVs) missed by other high-throughput approaches. Furthermore, by combining Illumina short-read data with long reads, we phased both single-nucleotide variants and SVs, generating haplotypes with over 99% consistency with previous trio-based studies. Our work shows that it is now possible to integrate single-molecule and high-throughput sequence data to generate de novo assembled genomes that approach reference quality.

Motivation : Structural variation is common in human and cancer genomes. High-throughput DNA sequencing has enabled genome-scale surveys of structural variation. However, the short reads produced by these technologies limit the study of complex variants, particularly those involving repetitive regions. Recent ‘third-generation’ sequencing technologies provide single-molecule templates and longer sequencing reads, but at the cost of higher per-nucleotide error rates. Results : We present MultiBreak-SV, an algorithm to detect structural variants (SVs) from single molecule sequencing data, paired read sequencing data, or a combination of sequencing data from different platforms. We demonstrate that combining low-coverage third-generation data from Pacific Biosciences (PacBio) with high-coverage paired read data is advantageous on simulated chromosomes. We apply MultiBreak-SV to PacBio data from four human fosmids and show that it detects known SVs with high sensitivity and specificity. Finally, we perform a whole-genome analysis on PacBio data from a complete hydatidiform mole cell line and predict 1002 high-probability SVs, over half of which are confirmed by an Illumina-based assembly. Availability and implementation : MultiBreak-SV is available at http://compbio.cs.brown.edu/software/ . Contact : annaritz@vt.edu or braphael@cs.brown.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Hepatitis C virus (HCV) replication is dependent on a liver-specific microRNA (miRNA), miR-122. A recent clinical trial reported that transient inhibition of miR-122 reduced viral titers in HCV infected patients. Here we set out to better understand how miR-122 inhibition influences HCV replication over time. Unexpectedly, we observed the emergence of a HCV variant that is resistant to miR-122 knockdown. Next-generation sequencing revealed that this was due to a single nucleotide change at position 28 (G28A) of the HCV genome, which falls between the two miR-122 seed-binding sites. Naturally occurring HCV isolates encoding G28A are similarly resistant to miR-122 inhibition, indicating that subtle differences in viral sequence, even outside the seed-binding site, greatly influence HCV’s miR-122 concentration requirement. Additionally, we found that HCV itself reduces miR-122’s activity in the cell, possibly through binding and sequestering miR-122. Our study provides insight into the interaction between miR-122 and HCV, including viral adaptation to reduced miR-122 bioavailability, and has implications for the development of anti-miR-122-based HCV drugs.

In a liver transplant recipient with vancomycin-resistant Enterococcus (VRE) surgical site and bloodstream infection, a combination of pulsed-field gel electrophoresis, multilocus sequence typing, and whole genome sequencing identified that donor and recipient VRE isolates were highly similar when compared to time-matched hospital isolates. Comparison of de novo assembled isolate genomes was highly suggestive of transplant transmission rather than hospital-acquired transmission and also identified subtle internal rearrangements between donor and recipient missed by other genomic approaches. Given the improved resolution, whole-genome assembly of pathogen genomes is likely to become an essential tool for investigation of potential organ transplant transmissions.

Motivation : Resolving tandemly repeated genomic sequences is a necessary step in improving our understanding of the human genome. Short tandem repeats (TRs), or microsatellites, are often used as molecular markers in genetics, and clinically, variation in microsatellites can lead to genetic disorders like Huntington’s diseases. Accurately resolving repeats, and in particular TRs, remains a challenging task in genome alignment, assembly and variation calling. Though tools have been developed for detecting microsatellites in short-read sequencing data, these are limited in the size and types of events they can resolve. Single-molecule sequencing technologies may potentially resolve a broader spectrum of TRs given their increased length, but require new approaches given their significantly higher raw error profiles. However, due to inherent error profiles of the single-molecule technologies, these reads presents a unique challenge in terms of accurately identifying and estimating the TRs. Results : Here we present P acmon STR, a reference-based probabilistic approach, to identify the TR region and estimate the number of these TR elements in long DNA reads. We present a multistep approach that requires as input, a reference region and the reference TR element. Initially, the TR region is identified from the long DNA reads via a 3-stage modified Smith–Waterman approach and then, expected number of TR elements is calculated using a pair-Hidden Markov Models –based method. Finally, TR-based genotype selection (or clustering: homozygous/heterozygous) is performed with Gaussian mixture models , using the Akaike information criteria , and coverage expectations. Availability and implementation: https://github.com/alibashir/pacmonstr Contact: ajayummat@gmail.com or ali.bashir@mssm.edu

Prior to the epidemic that emerged in Haiti in October of 2010, cholera had not been documented in this country. After its introduction, a strain of Vibrio cholerae O1 spread rapidly throughout Haiti, where it caused over 600,000 cases of disease and >7,500 deaths in the first two years of the epidemic. We applied whole-genome sequencing to a temporal series of V. cholerae isolates from Haiti to gain insight into the mode and tempo of evolution in this isolated population of V. cholerae O1. Phylogenetic and Bayesian analyses supported the hypothesis that all isolates in the sample set diverged from a common ancestor within a time frame that is consistent with epidemiological observations. A pangenome analysis showed nearly homogeneous genomic content, with no evidence of gene acquisition among Haiti isolates. Nine nearly closed genomes assembled from continuous-long-read data showed evidence of genome rearrangements and supported the observation of no gene acquisition among isolates. Thus, intrinsic mutational processes can account for virtually all of the observed genetic polymorphism, with no demonstrable contribution from horizontal gene transfer (HGT). Consistent with this, the 12 Haiti isolates tested by laboratory HGT assays were severely impaired for transformation, although unlike previously characterized noncompetent V. cholerae isolates, each expressed hapR and possessed a functional quorum-sensing system. Continued monitoring of V. cholerae in Haiti will illuminate the processes influencing the origin and fate of genome variants, which will facilitate interpretation of genetic variation in future epidemics., IMPORTANCE Vibrio cholerae is the cause of substantial morbidity and mortality worldwide, with over three million cases of disease each year. An understanding of the mode and rate of evolutionary change is critical for proper interpretation of genome sequence data and attribution of outbreak sources. The Haiti epidemic provides an unprecedented opportunity to study an isolated, single-source outbreak of Vibrio cholerae O1 over an established time frame. By using multiple approaches to assay genetic variation, we found no evidence that the Haiti strain has acquired any genes by horizontal gene transfer, an observation that led us to discover that it is also poorly transformable. We have found no evidence that environmental strains have played a role in the evolution of the outbreak strain.

Objectives: This study was aimed to assess the diversity of the meconium microbiome and determine if the bacterial community is affected by maternal diabetes status. Methods: The first intestinal discharge (meconium) was collected from 23 newborns stratified by maternal diabetes status: 4 mothers had pre-gestational type 2 diabetes mellitus (DM) including one mother with dizygotic twins, 5 developed gestational diabetes mellitus (GDM) and 13 had no diabetes. The meconium microbiome was profiled using multi-barcode 16S rRNA sequencing followed by taxonomic assignment and diversity analysis. Results: All meconium samples were not sterile and contained diversified microbiota. Compared with adult feces, the meconium showed a lower species diversity, higher sample-to-sample variation, and enrichment of Proteobacteria and reduction of Bacteroidetes. Among the meconium samples, the taxonomy analyses suggested that the overall bacterial content significantly differed by maternal diabetes status, with the microbiome of the DM group showing higher alphadiversity than that of no-diabetes or GDM groups. No global difference was found between babies delivered vaginally versus via Cesarean-section. Regression analysis showed that the most robust predictor for the meconium microbiota composition was the maternal diabetes status that preceded pregnancy. Specifically, Bacteroidetes (phyla) and Parabacteriodes (genus) were enriched in the meconium in the DM group compared to the no-diabetes group. Conclusions: Our study provides evidence that meconium contains diversified microbiota and is not affected by the mode of delivery. It also suggests that the meconium microbiome of infants born to mothers with DM is enriched for the same bacterial taxa as those reported in the fecal microbiome of adult DM patients.

Drug combination therapies in the cancer setting often succeed where mono-therapies fail, facilitating durable and robust responses that may curtail metastases and even be accompanied by milder side-effects. Here we incorporate transcriptional splicing dynamics with a gene level expression analysis to assess the transcriptional landscape of MCF-7 (ER+) cell-lines across mono or combination therapies in a time course short-read RNA-seq experiment. We leverage the most comprehensive known splicing database of MCF7 to assess the sensitivity and specificity our short-read splicing inference by interrogating the long-read PacBio isoform sequencing (IsoSeq) MCF7 database. We infer robust isoforms which are strongly associated with phenotypic synergy and demonstrate their novel functional role by computing gene-gene coexpression networks which are sensitive to their expression. Briefly, we use RNA-seq to study the transcriptional response over time (0, 3, 6, 9, 12, and 24 h) for three drugs (A, B and C) and their combinations (AB, AC and BC) in MCF-7 (ER+) breast cancer cells lines. Cell viability measurements show that one of the combinations (AB) is strongly synergistic, whereas the other two (AC and BC) are merely additive. We show that in addition to a novel transcriptional signature driven by differential expression, the combination AB transcriptional landscape is characterized by persistent alternative splicing signatures mostly comprised of genes which are not differentially expressed with respect to A or B, but whose functional role has been dramatically changed by the addition (deletion) of a key regulatory protein domain encoded by the extra(missing) exon. We integrate this synergistic splicing signal into a gene regulatory network (GRN) via adaptive network refinement to show that it strongly contributes to the emergence of extensive transcriptional cascades by creating and removing key gene-gene correlations and altering the modular structure of the network. Using this approach we show that a key (heretofor poorly understood) isoform of Protein beta-arrestin-1 (ARBB1), which participates in the desensitization of G-protein coupled receptors through intracellular response to Estrogen, becomes enriched in the calcium ion-dependent exocytosis coexpression module for synergistic therapies only, despite being absent in the baseline MCF-7 long-read PacBio IsoSeq data. Our results directly show that alternative splicing is crucial in any molecular characterization of phenotypic drug synergy in drug-tumor interactions. Citation Format: Xintong Chen, Ali Bashir, Gustavo Stolovitzky, Bojan Losic. Dynamic alternative splicing correlates with drug synergy and induces novel gene regulatory networks in MCF7. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-286.

A large outbreak of diarrhea and the hemolytic-uremic syndrome caused by an unusual serotype of Shiga-toxin-producing Escherichia coli (O104:H4) began in Germany in May 2011. As of July 22, a large number of cases of diarrhea caused by Shiga-toxin-producing E. coli have been reported--3167 without the hemolytic-uremic syndrome (16 deaths) and 908 with the hemolytic-uremic syndrome (34 deaths)--indicating that this strain is notably more virulent than most of the Shiga-toxin-producing E. coli strains. Preliminary genetic characterization of the outbreak strain suggested that, unlike most of these strains, it should be classified within the enteroaggregative pathotype of E. coli.We used third-generation, single-molecule, real-time DNA sequencing to determine the complete genome sequence of the German outbreak strain, as well as the genome sequences of seven diarrhea-associated enteroaggregative E. coli serotype O104:H4 strains from Africa and four enteroaggregative E. coli reference strains belonging to other serotypes. Genomewide comparisons were performed with the use of these enteroaggregative E. coli genomes, as well as those of 40 previously sequenced E. coli isolates.The enteroaggregative E. coli O104:H4 strains are closely related and form a distinct clade among E. coli and enteroaggregative E. coli strains. However, the genome of the German outbreak strain can be distinguished from those of other O104:H4 strains because it contains a prophage encoding Shiga toxin 2 and a distinct set of additional virulence and antibiotic-resistance factors.Our findings suggest that horizontal genetic exchange allowed for the emergence of the highly virulent Shiga-toxin-producing enteroaggregative E. coli O104:H4 strain that caused the German outbreak. More broadly, these findings highlight the way in which the plasticity of bacterial genomes facilitates the emergence of new pathogens.

Background Humans are diploid, carrying two copies of each chromosome, one from each parent. Separating the paternal and maternal chromosomes is an important component of genetic analyses such as determining genetic association, inferring evolutionary scenarios, computing recombination rates, and detecting cis-regulatory events. As the pair of chromosomes are mostly identical to each other, linking together of alleles at heterozygous sites is sufficient to phase, or separate the two chromosomes. In Haplotype Assembly, the linking is done by sequenced fragments that overlap two heterozygous sites. While there has been a lot of research on correcting errors to achieve accurate haplotypes via assembly, relatively little work has been done on designing sequencing experiments to get long haplotypes. Here, we describe the different design parameters that can be adjusted with next generation and upcoming sequencing technologies, and study the impact of design choice on the length of the haplotype. Results We show that a number of parameters influence haplotype length, with the most significant one being the advance length (distance between two fragments of a clone). Given technologies like strobe sequencing that allow for large variations in advance lengths, we design and implement a simulated annealing algorithm to sample a large space of distributions over advance-lengths. Extensive simulations on individual genomic sequences suggest that a non-trivial distribution over advance lengths results a 1-2 order of magnitude improvement in median haplotype length. Conclusions Our results suggest that haplotyping of large, biologically important genomic regions is feasible with current technologies.

Through long-term laboratory selection (over 200 generations), we have generated Drosophila melanogaster populations that tolerate severe, normally lethal, levels of hypoxia. Because of initial experiments suspecting genetic mechanisms underlying this adaptation, we compared the genomes of the hypoxia-selected flies with those of controls using deep resequencing. By applying unique computing and analytical methods we identified a number of DNA regions under selection, mostly on the X chromosome. Several of the hypoxia-selected regions contained genes encoding or regulating the Notch pathway. In addition, previous expression profiling revealed an activation of the Notch pathway in the hypoxia-selected flies. We confirmed the contribution of Notch activation to hypoxia tolerance using a specific γ-secretase inhibitor, N-[N-(3,5-Difluorophenacetyl)-L-alanyl]-S-phenylglycine t-butyl ester (DAPT), which significantly reduced adult survival and life span in the hypoxia-selected flies. We also demonstrated that flies with loss-of-function Notch mutations or RNAi-mediated Notch knockdown had a significant reduction in hypoxia tolerance, but those with a gain-of-function had a dramatic opposite effect. Using the UAS-Gal4 system, we also showed that specific overexpression of the Notch intracellular domain in glial cells was critical for conferring hypoxia tolerance. Unique analytical tools and genetic and bioinformatic strategies allowed us to discover that Notch activation plays a major role in this hypoxia tolerance in Drosophila melanogaster .

Somatically acquired DNA rearrangements are characteristic of many cancers. The use of these mutations as diagnostic markers is challenging, because tumor cells are frequently admixed with normal cells, particularly in early stage tumor samples, and thus the samples contain a high background of normal DNA. Detection is further confounded by the fact that the rearrangement boundaries are not conserved across individuals, and might vary over hundreds of kilobases. Here, we present an algorithm for designing polymerase chain reaction (PCR) primers and oligonucleotide probes to assay for these variant rearrangements. Specifically, the primers and probes tile the entire genomic region surrounding a rearrangement, so as to amplify the mutant DNA over a wide range of possible breakpoints and robustly assay for the amplified signal on an array. Our solution involves the design of a complex combinatorial optimization problem, and also includes a novel alternating multiplexing strategy that makes efficient detection possible. Simulations show that we can achieve near-optimal detection in many different cases, even when the regions are highly non-symmetric. Additionally, we prove that the suggested multiplexing strategy is optimal in breakpoint detection. We applied our technique to create a custom design to assay for genomic lesions in several cancer cell-lines associated with a disruption in the CDKN2A locus. The CDKN2A deletion has highly variable boundaries across many cancers. We successfully detect the breakpoint in all cell-lines, even when the region has undergone multiple rearrangements. These results point to the development of a successful protocol for early diagnosis and monitoring of cancer. For online Supplementary Material, see www.liebertonline.com.

Background Massively parallel DNA sequencing technologies have enabled the sequencing of several individual human genomes. These technologies are also being used in novel ways for mRNA expression profiling, genome-wide discovery of transcription-factor binding sites, small RNA discovery, etc. The multitude of sequencing platforms, each with their unique characteristics, pose a number of design challenges, regarding the technology to be used and the depth of sequencing required for a particular sequencing application. Here we describe a number of analytical and empirical results to address design questions for two applications: detection of structural variations from paired-end sequencing and estimating mRNA transcript abundance. Results For structural variation, our results provide explicit trade-offs between the detection and resolution of rearrangement breakpoints, and the optimal mix of paired-read insert lengths. Specifically, we prove that optimal detection and resolution of breakpoints is achieved using a mix of exactly two insert library lengths. Furthermore, we derive explicit formulae to determine these insert length combinations, enabling a 15% improvement in breakpoint detection at the same experimental cost. On empirical short read data, these predictions show good concordance with Illumina 200 bp and 2 Kbp insert length libraries. For transcriptome sequencing, we determine the sequencing depth needed to detect rare transcripts from a small pilot study. With only 1 Million reads, we derive corrections that enable almost perfect prediction of the underlying expression probability distribution, and use this to predict the sequencing depth required to detect low expressed genes with greater than 95% probability. Conclusions Together, our results form a generic framework for many design considerations related to high-throughput sequencing. We provide software tools http://bix.ucsd.edu/projects/NGS-DesignTools to derive platform independent guidelines for designing sequencing experiments (amount of sequencing, choice of insert length, mix of libraries) for novel applications of next generation sequencing.

We describe the genome sequencing of an anonymous individual of African origin using a novel ligation-based sequencing assay that enables a unique form of error correction that improves the raw accuracy of the aligned reads to >99.9%, allowing us to accurately call SNPs with as few as two reads per allele. We collected several billion mate-paired reads yielding ∼18× haploid coverage of aligned sequence and close to 300× clone coverage. Over 98% of the reference genome is covered with at least one uniquely placed read, and 99.65% is spanned by at least one uniquely placed mate-paired clone. We identify over 3.8 million SNPs, 19% of which are novel. Mate-paired data are used to physically resolve haplotype phases of nearly two-thirds of the genotypes obtained and produce phased segments of up to 215 kb. We detect 226,529 intra-read indels, 5590 indels between mate-paired reads, 91 inversions, and four gene fusions. We use a novel approach for detecting indels between mate-paired reads that are smaller than the standard deviation of the insert size of the library and discover deletions in common with those detected with our intra-read approach. Dozens of mutations previously described in OMIM and hundreds of nonsynonymous single-nucleotide and structural variants in genes previously implicated in disease are identified in this individual. There is more genetic variation in the human genome still to be uncovered, and we provide guidance for future surveys in populations and cancer biopsies.

Somatically acquired DNA rearrangements are characteristic of many cancers. The use of these mutations as diagnostic markers is challenging, because tumor cells are frequently admixed with normal cells, particularly in early stage tumor samples, and thus the samples contain a high background of normal DNA. Detection is further confounded by the fact that the rearrangement boundaries are not conserved across individuals, and might vary over hundreds of kilobases. Here, we present an algorithm for designing PCR primers and oligonucleotide probes to assay for these variant rearrangements. Specifically, the primers and probes tile the entire genomic region surrounding a rearrangement, so as to amplify the mutant DNA over a wide range of possible breakpoints and robustly assay for the amplified signal on an array. Our solution involves the design of a complex combinatorial optimization problem, and also includes a novel alternating multiplexing strategy that makes efficient detection possible. Simulations show that we can achieve near-optimal detection in many different cases, even when the regions are highly non-symmetric. Additionally, we prove that the suggested multiplexing strategy is optimal in breakpoint detection. We applied our technique to create a custom design to assay for genomic lesions in several cancer cell-lines associated with a disruption in the CDKN2A locus. The CDKN2A deletion has highly variable boundaries across many cancers. We successfully detect the breakpoint in all cell-lines, even when the region has undergone multiple rearrangements. These results point to the development of a successful protocol for early diagnosis and monitoring of cancer.

Paired-end sequencing is emerging as a key technique for assessing genome rearrangements and structural variation on a genome-wide scale. This technique is particularly useful for detecting copy-neutral rearrangements, such as inversions and translocations, which are common in cancer and can produce novel fusion genes. We address the question of how much sequencing is required to detect rearrangement breakpoints and to localize them precisely using both theoretical models and simulation. We derive a formula for the probability that a fusion gene exists in a cancer genome given a collection of paired-end sequences from this genome. We use this formula to compute fusion gene probabilities in several breast cancer samples, and we find that we are able to accurately predict fusion genes in these samples with a relatively small number of fragments of large size. We further demonstrate how the ability to detect fusion genes depends on the distribution of gene lengths, and we evaluate how different parameters of a sequencing strategy impact breakpoint detection, breakpoint localization, and fusion gene detection, even in the presence of errors that suggest false rearrangements. These results will be useful in calibrating future cancer sequencing efforts, particularly large-scale studies of many cancer genomes that are enabled by next-generation sequencing technologies., Author Summary Cancer is driven by genomic mutations that can range from single nucleotide changes to chromosomal aberrations that rearrange large pieces of DNA. Often, these chromosomal aberrations disrupt a gene sequence, and even fuse the sequences of two genes, producing a “fusion gene.” Fusion genes have been identified as key participants in the development of several types of cancer. Using genome-sequencing technology it is now possible to identify chromosomal aberrations genome-wide and at high resolution. In this paper, we address the question of how much sequencing is required to detect a chromosomal aberration and to determine the location of the aberration precisely enough to identify if a fusion gene is created by this aberration. We derive a mathematical formula that accurately predicts a number of fusion genes in a breast cancer sequencing study. We also demonstrate how the ability to detect chromosomal aberrations and fusion genes depends on both the size of the fusion gene and the parameters of the genome sequencing strategy that is used. These results will be useful in calibrating future cancer sequencing efforts, especially those using next-generation sequencing technologies.

Primer approximation multiplex PCR (PAMP) is a new experimental protocol for efficiently assaying structural variation in genomes. PAMP is particularly suited to cancer genomes where the precise breakpoints of alterations such as deletions or translocations vary between patients. The design of PCR primer sets for PAMP is challenging because a large number of primer pairs are required to detect alterations in the hundreds of kilobases range that can occur in cancer. These sets of primers must achieve high coverage of the region of interest, while avoiding primer dimers and satisfying the physico-chemical constraints of good PCR primers. We describe a natural formulation of these constraints as a combinatorial optimization problem. We show that the PAMP primer design problem is NP-hard, and design algorithms based on simulated annealing and integer programming, that provide good solutions to this problem in practice.The algorithms are applied to a test region around the known CDKN2A deletion, which show excellent results even in a 1:49 mixture of mutated:wild-type cells. We use these test results to help set design parameters for larger problems. We can achieve near-optimal designs for regions close to 1 Mb.Contact: abashir@ucsd.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Hepatitis C virus (HCV) replication is dependent on a liver-specific microRNA (miRNA), miR-122. A recent clinical trial reported that transient inhibition of miR-122 using locked nucleic acid (LNA) oligonucleotides reduced viral titers in HCV infected patients. Though viral resistance was not reported, the transient nature of these studies makes it unclear whether HCV can evolve resistance to miR-122 inhibition. To address this important question, we generated liver cells in which miR-122 was stably inhibited using a lentiviral vector-based miR-122 decoy.Strikingly, after 20 days in culture we observed the emergence of an HCV variant that was resistant to miR-122 knockdown. Deep-sequencing of the resistant virus revealed that this was due to a single nucleotide change at position 28 (G28A) of the HCV genome, which falls between the two miR-122 seed-binding sites in the virus. We could recapitulate resistance into a wildtype virus by introducing the G28A mutation, which confirmed that this single nucleotide change was responsible. We also found that the G28A mutation makes HCV similarly resistant to miR-122 knockdown by LNA. Importantly, HCV isolates that were innately G28A were similarly resistant to miR-122 inhibition by miR-122 decoy and LNA, indicating that our findings apply to natural strains of the virus, and to inhibition using oligonucleotides.To better understand the mechanism by which G28A confers resistance, we precisely quantitated both wild-type and mutant virus miR-122 stoichiometric requirements. Our results indicate that in the presence of excess miR-122 to viral genomes, there was no difference in target site interaction. Instead, when the bioavailable concentration of miR-122 become rate-limiting, the G28A target site became preferentially regulated. These results indicate that target site selection is strongly influenced by microRNA concentration, and demonstrate that subtle differences in viral sequence, even outside the seed-binding site, greatly affect HCV's miR-122 concentration requirement.This study provides insight into the interaction between miR-122 and HCV, including viral adaptation to reduced miR-122 bioavailability, and has broader implications for the development and use of microRNA-based drugs and for our understanding of microRNA target site selection.

Determining phylogenetic relationships between species is a difficult problem, and many phylogenetic relationships remain unresolved, even among eutherian mammals. Repetitive elements provide excellent markers for phylogenetic analysis, because their mode of evolution is predominantly homoplasy-free and unidirectional. Historically, phylogenetic studies using repetitive elements have relied on biological methods such as PCR analysis, and computational inference is limited to a few isolated repeats. Here, we present a novel computational method for inferring phylogenetic relationships from partial sequence data using orthologous repeats. We apply our method to reconstructing the phylogeny of 28 mammals, using more than 1000 orthologous repeats obtained from sequence data available from the NISC Comparative Sequencing Program. The resulting phylogeny has robust bootstrap numbers, and broadly matches results from previous studies which were obtained using entirely different data and methods. In addition, we shed light on some of the debatable aspects of the phylogeny. With rapid expansion of available partial sequence data, computational analysis of repetitive elements holds great promise for the future of phylogenetic inference.

As orthologous genes from related species diverge over time, some sequences are conserved in noncoding regions. In mammals, large phylogenetic footprints, or conserved noncoding sequences (CNSs), are known to be common features of genes. Here we present the first large-scale analysis of plant genes for CNSs. We used maize and rice, maximally diverged members of the grass family of monocots. Using a local sequence alignment set to deliver only significant alignments, we found one or more CNSs in the noncoding regions of the majority of genes studied. Grass genes have dramatically fewer and much smaller CNSs than mammalian genes. Twenty-seven percent of grass gene comparisons revealed no CNSs. Genes functioning in upstream regulatory roles, such as transcription factors, are greatly enriched for CNSs relative to genes encoding enzymes or structural proteins. Further, we show that a CNS cluster in an intron of the knotted1 homeobox gene serves as a site of negative regulation. We showthat CNSs in the adh1 gene do not correlate with known cis-acting sites. We discuss the potential meanings of CNSs and their value as analytical tools and evolutionary characters. We advance the idea that many CNSs function to lock-in gene regulatory decisions.

Background It has recently become possible to rapidly and accurately detect epigenetic signatures in bacterial genomes using third generation sequencing data. Monitoring the speed at which a single polymerase inserts a base in the read strand enables one to infer whether a modification is present at that specific site on the template strand. These sites can be challenging to detect in the absence of high coverage and reliable reference genomes. Methods Here we provide a new method for detecting epigenetic motifs in bacteria on datasets with low-coverage, with incomplete references, and with mixed samples (i.e. metagenomic data). Our approach treats motif inference as a kmer comparison problem. First, genomes (or contigs) are deconstructed into kmers. Then, native genome-wide distributions of interpulse durations (IPDs) for kmers are compared with corresponding whole genome amplified (WGA, modification free) IPD distributions using log likelihood ratios. Finally, kmers are ranked and greedily selected by iteratively correcting for sequences within a particular kmer's neighborhood. Conclusions Our method can detect multiple types of modifications, even at very low-coverage and in the presence of mixed genomes. Additionally, we are able to predict modified motifs when genomes with "neighbor" modified motifs exist within the sample. Lastly, we show that these motifs can provide an alternative source of information by which to cluster metagenomics contigs and that iterative refinement on these clustered contigs can further improve both sensitivity and specificity of motif detection. Availability https://github.com/alibashir/EMMCKmer

Background Activating mutations [primarily internal tandem duplication (ITD) events] in FLT3 are detected in 30% of acute myeloid leukemia (AML). The clinically active FLT3 tyrosine kinase inhibitor (TKI) AC220 (quizartinib) has achieved complete remissions in relapsed/refractory FLT3-ITD+ AML patients in a phase II study (Cortes, et al and Levis et al, ASH 2012, abstracts 48 and 673) but is vulnerable to resistance-conferring mutations in the FLT3 kinase domain (KD). The F691L “gatekeeper” substitution was the most commonly detected mutation in an in vitro mutagenesis screen for AC220 resistance (Smith et al, Nature 2012). This mutation, and substitutions at the activation loop residue D835, have been associated with acquired clinical resistance to AC220 (Smith et al, Nature 2012; Alber et al, Leukemia 2013). Mutations at gatekeeper residues such as F691 have repeatedly surfaced as mediators of clinical resistance to TKIs. Identifying TKIs that retain activity against these substitutions has consistently proven challenging. PLX3397 is a potent and selective inhibitor of FMS, KIT and FLT3-ITD with a half-life of 20 hours in humans, resulting in µM steady-state plasma concentrations at the recommended phase II dose for AML patients. PLX3397 retains activity against the AC220-resistant FLT3-ITD/F691L mutant, but not against several D835 mutants (Smith et al., ASH 2011, abstract 764). In this study, we conducted a mutagenesis screen of FLT3-ITD and FLT3-ITD/F691L to identify single and compound mutations that confer resistance to PLX3397 and may cause acquired resistance in patients. Results PLX3397 inhibited the proliferation of BaF3/ FLT3-ITD cells at a concentration well below that achieved in patients (IC50 0.14 µM) and retained activity against cells expressing the FLT3-ITD/F691L mutant (IC50 0.350 µM). Other AC220-resistant mutants (D835V/Y/F and Y842C/H) conferred substantial cross-resistance to PLX3397 (∼50 to 400-fold shift in IC50 of FLT3-ITD; ranging from 7.2 to >10 µM). An in vitro mutagenesis screen of FLT3-ITD identified several mutations conferring resistance to PLX3397, including novel substitutions in 3 residues which conferred ≥10X resistance relative to FLT3-ITD: D835E/G/N, D839A/G and R845G (IC50s 1.4 to 4.1 µM). Given the in vitro activity of PLX3397 against the AC220-resistant F691L mutant, it is anticipated that PLX3397 will be administered to patients who acquire resistance to AC220 or sorafenib due to this mutation; a mutagenesis screen of FLT3-ITD/F691L was therefore conducted. We identified multiple KD mutations in FLT3-ITD/F691L conferring ≥10X resistance to PLX3397 (compared to FLT3-ITD) including several mutations in the FLT3 activation loop: D835H/G/E/N, D839A/G/N, N841K, Y842S, R845G (IC50s 1.6 to >10 µM), and 2 mutations in residues located in the tyrosine kinase domain 1 (TK1) domain: N676S, a residue previously implicated in clinical resistance to the FLT3 inhibitor PKC412 (IC50 2.8 µM), and M664I, a residue not previously linked to FLT3 inhibitor resistance (IC50 2.0 µM). While all identified mutants conferred some degree of resistance to PLX3397 in the absence of an F691L mutation, most conferred a higher degree of resistance in the setting of F691L, suggesting a cooperation between the gatekeeper residue and residues in the activation loop and TK1 domain that impacts PLX3397 binding. Finally, we conducted a preliminary analysis of samples from AML patients who relapsed after an initial response to PLX3397. Using Pacific Biosciences Single Molecule Real-Time Sequencing, we identified evolution of polyclonal FLT3 KD mutations at the D835 residue at the time of relapse in 2 patients, including, in one patient, novel PLX3397-resistant D835E/H mutations identified in our mutagenesis screen. Analysis of additional patient samples for single and compound resistant mutations is ongoing and will be presented. Conclusions PLX3397 harbors promise for the treatment of FLT3-ITD+ AML, particularly for patients who have developed resistance to FLT3 TKIs due to the gatekeeper F691L mutation. However, a mutagenesis screen reveals PLX3397 is vulnerable to mutations in the FLT3 activation loop and TK1 domain. Patients acquire secondary FLT3 KD mutations at the time of resistance to PLX3397, confirming the mechanism of action of this clinically active FLT3 inhibitor. A multi-site phase I/II study of PLX3397 in FLT3-ITD+ AML is ongoing. Disclosures: Smith: Plexxikon Inc: Research Funding. Off Label Use: Unapproved drugs for AML: AC220 and PLX3397. Le:Plexxikon Inc: Employment. Zhang:Plexxikon Inc: Employment. West:Plexxikon Inc: Employment. Shah:Ariad Pharmaceuticals: Consultancy, Research Funding; Plexxikon Inc: Research Funding; Ambit Biosciences: Research Funding.

Tumors and cancer cell lines were surveyed with end-sequencing profiling, yielding the largest available collection of sequence-ready tumor genome breakpoints and providing evidence that some rearrangements may be recurrent., Background The genomes of many epithelial tumors exhibit extensive chromosomal rearrangements. All classes of genome rearrangements can be identified using end sequencing profiling, which relies on paired-end sequencing of cloned tumor genomes. Results In the present study brain, breast, ovary, and prostate tumors, along with three breast cancer cell lines, were surveyed using end sequencing profiling, yielding the largest available collection of sequence-ready tumor genome breakpoints and providing evidence that some rearrangements may be recurrent. Sequencing and fluorescence in situ hybridization confirmed translocations and complex tumor genome structures that include co-amplification and packaging of disparate genomic loci with associated molecular heterogeneity. Comparison of the tumor genomes suggests recurrent rearrangements. Some are likely to be novel structural polymorphisms, whereas others may be bona fide somatic rearrangements. A recurrent fusion transcript in breast tumors and a constitutional fusion transcript resulting from a segmental duplication were identified. Analysis of end sequences for single nucleotide polymorphisms revealed candidate somatic mutations and an elevated rate of novel single nucleotide polymorphisms in an ovarian tumor. Conclusion These results suggest that the genomes of many epithelial tumors may be far more dynamic and complex than was previously appreciated and that genomic fusions, including fusion transcripts and proteins, may be common, possibly yielding tumor-specific biomarkers and therapeutic targets.

We prove that the simply connected compact mixed foliate CR-submanifold in a hyperbolic complex space form is either a complex submanifold or a totally real submanifold. This is the problem posed by Chen.