Detailed molecular characterisation of acute myeloid leukaemia with a normal karyotype using targeted DNA capture.

Advances in sequencing technologies are giving unprecedented insights into the spectrum of somatic mutations underlying acute myeloid leukaemia with a normal karyotype (AML-NK). It is clear that the prognosis of individual patients is strongly influenced by the combination of mutations in their leukaemia and that many leukaemias are composed of multiple subclones, with differential susceptibilities to treatment. Here, we describe a method, employing targeted capture coupled with next-generation sequencing and tailored bioinformatic analysis, for the simultaneous study of 24 genes recurrently mutated in AML-NK. Mutational analysis was performed using open source software and an in-house script (Mutation Identification and Analysis Software), which identified dominant clone mutations with 100% specificity. In each of seven cases of AML-NK studied, we identified and verified mutations in 2-4 genes in the main leukaemic clone. Additionally, high sequencing depth enabled us to identify putative subclonal mutations and detect leukaemia-specific mutations in DNA from remission marrow. Finally, we used normalised read depths to detect copy number changes and identified and subsequently verified a tandem duplication of exons 2-9 of MLL and at least one deletion involving PTEN. This methodology reliably detects sequence and copy number mutations, and can thus greatly facilitate the classification, clinical research, diagnosis and management of AML-NK

Analysis and comparison of very large metagenomes with fast clustering and functional annotation

<p>Abstract</p> <p>Background</p> <p>The remarkable advance of metagenomics presents significant new challenges in data analysis. Metagenomic datasets (metagenomes) are large collections of sequencing reads from anonymous species within particular environments. Computational analyses for very large metagenomes are extremely time-consuming, and there are often many novel sequences in these metagenomes that are not fully utilized. The number of available metagenomes is rapidly increasing, so fast and efficient metagenome comparison methods are in great demand.</p> <p>Results</p> <p>The new metagenomic data analysis method Rapid Analysis of Multiple Metagenomes with a Clustering and Annotation Pipeline (<b>RAMMCAP</b>) was developed using an ultra-fast sequence clustering algorithm, fast protein family annotation tools, and a novel statistical metagenome comparison method that employs a unique graphic interface. RAMMCAP processes extremely large datasets with only moderate computational effort. It identifies raw read clusters and protein clusters that may include novel gene families, and compares metagenomes using clusters or functional annotations calculated by RAMMCAP. In this study, RAMMCAP was applied to the two largest available metagenomic collections, the "Global Ocean Sampling" and the "Metagenomic Profiling of Nine Biomes".</p> <p>Conclusion</p> <p>RAMMCAP is a very fast method that can cluster and annotate one million metagenomic reads in only hundreds of CPU hours. It is available from <url>http://tools.camera.calit2.net/camera/rammcap/</url>.</p

Using data-driven rules to predict mortality in severe community acquired pneumonia

Prediction of patient-centered outcomes in hospitals is useful for performance benchmarking, resource allocation, and guidance regarding active treatment and withdrawal of care. Yet, their use by clinicians is limited by the complexity of available tools and amount of data required. We propose to use Disjunctive Normal Forms as a novel approach to predict hospital and 90-day mortality from instance-based patient data, comprising demographic, genetic, and physiologic information in a large cohort of patients admitted with severe community acquired pneumonia. We develop two algorithms to efficiently learn Disjunctive Normal Forms, which yield easy-to-interpret rules that explicitly map data to the outcome of interest. Disjunctive Normal Forms achieve higher prediction performance quality compared to a set of state-of-the-art machine learning models, and unveils insights unavailable with standard methods. Disjunctive Normal Forms constitute an intuitive set of prediction rules that could be easily implemented to predict outcomes and guide criteria-based clinical decision making and clinical trial execution, and thus of greater practical usefulness than currently available prediction tools. The Java implementation of the tool JavaDNF will be publicly available. © 2014 Wu et al

Chromosomal-level assembly of the Asian Seabass genome using long sequence reads and multi-layered scaffolding

We report here the ~670 Mb genome assembly of the Asian seabass (Lates calcarifer), a tropical marine teleost. We used long-read sequencing augmented by transcriptomics, optical and genetic mapping along with shared synteny from closely related fish species to derive a chromosome-level assembly with a contig N50 size over 1 Mb and scaffold N50 size over 25 Mb that span ~90% of the genome. The population structure of L. calcarifer species complex was analyzed by re-sequencing 61 individuals representing various regions across the species' native range. SNP analyses identified high levels of genetic diversity and confirmed earlier indications of a population stratification comprising three clades with signs of admixture apparent in the South-East Asian population. The quality of the Asian seabass genome assembly far exceeds that of any other fish species, and will serve as a new standard for fish genomics

The Formation and Evolution of the First Massive Black Holes

The first massive astrophysical black holes likely formed at high redshifts (z>10) at the centers of low mass (~10^6 Msun) dark matter concentrations. These black holes grow by mergers and gas accretion, evolve into the population of bright quasars observed at lower redshifts, and eventually leave the supermassive black hole remnants that are ubiquitous at the centers of galaxies in the nearby universe. The astrophysical processes responsible for the formation of the earliest seed black holes are poorly understood. The purpose of this review is threefold: (1) to describe theoretical expectations for the formation and growth of the earliest black holes within the general paradigm of hierarchical cold dark matter cosmologies, (2) to summarize several relevant recent observations that have implications for the formation of the earliest black holes, and (3) to look into the future and assess the power of forthcoming observations to probe the physics of the first active galactic nuclei.Comment: 39 pages, review for "Supermassive Black Holes in the Distant Universe", Ed. A. J. Barger, Kluwer Academic Publisher

LOCAS – A Low Coverage Assembly Tool for Resequencing Projects

Motivation: Next Generation Sequencing (NGS) is a frequently applied approach to detect sequence variations between highly related genomes. Recent large-scale re-sequencing studies as the Human 1000 Genomes Project utilize NGS data of low coverage to afford sequencing of hundreds of individuals. Here, SNPs and micro-indels can be detected by applying an alignment-consensus approach. However, computational methods capable of discovering other variations such as novel insertions or highly diverged sequence from low coverage NGS data are still lacking. Results: We present LOCAS, a new NGS assembler particularly designed for low coverage assembly of eukaryotic genomes using a mismatch sensitive overlap-layout-consensus approach. LOCAS assembles homologous regions in a homologyguided manner while it performs de novo assemblies of insertions and highly polymorphic target regions subsequently to an alignment-consensus approach. LOCAS has been evaluated in homology-guided assembly scenarios with low sequence coverage of Arabidopsis thaliana strains sequenced as part of the Arabidopsis 1001 Genomes Project. While assembling the same amount of long insertions as state-of-the-art NGS assemblers, LOCAS showed best results regarding contig size, error rate and runtime. Conclusion: LOCAS produces excellent results for homology-guided assembly of eukaryotic genomes with short reads and low sequencing depth, and therefore appears to be the assembly tool of choice for the detection of novel sequenc

P110 and P140 Cytadherence-Related Proteins Are Negative Effectors of Terminal Organelle Duplication in Mycoplasma genitalium

BACKGROUND:The terminal organelle is a complex structure involved in many aspects of the biology of mycoplasmas such as cell adherence, motility or cell division. Mycoplasma genitalium cells display a single terminal organelle and duplicate this structure prior to cytokinesis in a coordinated manner with the cell division process. Despite the significance of the terminal organelle in mycoplasma virulence, little is known about the mechanisms governing its duplication. METHODOLOGY/PRINCIPAL FINDINGS:In this study we describe the isolation of a mutant, named T192, with a transposon insertion close to the 3' end of the mg192 gene encoding for P110 adhesin. This mutant shows a truncated P110, low levels of P140 and P110 adhesins, a large number of non-motile cells and a high frequency of new terminal organelle formation. Further analyses revealed that the high rates of new terminal organelle formation in T192 cells are a direct consequence of the reduced levels of P110 and P140 rather than to the expression of a truncated P110. Consistently, the phenotype of the T192 mutant was successfully complemented by the reintroduction of the mg192 WT allele which restored the levels of P110 and P140 to those of the WT strain. Quantification of DAPI-stained DNA also showed that the increase in the number of terminal organelles in T192 cells is not accompanied by a higher DNA content, indicating that terminal organelle duplication does not trigger DNA replication in mycoplasmas. CONCLUSIONS/SIGNIFICANCE:Our results demonstrate the existence of a mechanism regulating terminal organelle duplication in M. genitalium and strongly suggest the implication of P110 and P140 adhesins in this mechanism

Hip abduction weakness in elite junior footballers is common but easy to correct quickly: a prospective sports team cohort based study

Background: Hip abduction weakness has never been documented on a population basis as a common finding in a healthy group of athletes and would not normally be found in an elite adolescent athlete. This study aimed to show that hip abduction weakness not only occurs in this group but also is common and easy to correct with an unsupervised home based program. Methods: A prospective sports team cohort based study was performed with thirty elite adolescent under-17 Australian Rules Footballers in the Australian Institute of Sport/Australian Football League Under-17 training academy. The players had their hip abduction performance assessed and were then instructed in a hip abduction muscle training exercise. This was performed on a daily basis for two months and then they were reassessed.Results: The results showed 14 of 28 athletes who completed the protocol had marked weakness or a side-to-side difference of more than 25% at baseline. Two months later ten players recorded an improvement of ≥ 80% in their recorded scores. The mean muscle performance on the right side improved from 151 Newton (N) to 202 N (p<0.001) while on the left, the recorded results improved from 158 N to 223 N (p<0.001). Conclusions: The baseline values show widespread profound deficiencies in hip abduction performance not previously reported. Very large performance increases can be achieved, unsupervised, in a short period of time to potentially allow large clinically significant gains. This assessment should be an integral part of preparticipation screening and assessed in those with lower limb injuries. This particular exercise should be used clinically and more research is needed to determine its injury prevention and performance enhancement implications