De novo Genome Assembly of the Fungal Plant Pathogen Pyrenophora semeniperda

Pyrenophora semeniperda (anamorph Drechslera campulata) is a necrotrophic fungal seed pathogen that has a wide host range within the Poaceae. One of its hosts is cheatgrass (Bromus tectorum), a species exotic to the United States that has invaded natural ecosystems of the Intermountain West. As a natural pathogen of cheatgrass, P. semeniperda has potential as a biocontrol agent due to its effectiveness at killing seeds within the seed bank; however, few genetic resources exist for the fungus. Here, the genome of P. semeniperda isolate assembled from sequence reads of 454 pyrosequencing is presented. The total assembly is 32.5 Mb and includes 11,453 gene models encoding putative proteins larger than 24 amino acids. The models represent a variety of putative genes that are involved in pathogenic pathways typically found in necrotrophic fungi. In addition, extensive rearrangements, including inter- and intrachromosomal rearrangements, were found when the P. semeniperda genome was compared to P. tritici-repentis, a related fungal species.     

De novo reconstruction of DNA origami structures through atomistic molecular dynamics simulation

The DNA origami method has brought nanometer-precision fabrication to molecular biology labs, offering myriads of potential applications in the fields of synthetic biology, medicine, molecular computation, etc. Advancing the method further requires controlling self-assembly down to the atomic scale. Here we demonstrate a computational method that allows the equilibrium structure of a large, complex DNA origami object to be determined to atomic resolution. Through direct comparison with the results of cryo-electron microscopy, we demonstrate de novo reconstruction of a 4.7 megadalton pointer structure by means of fully atomistic molecular dynamics simulations. Furthermore, we show that elastic network-guided simulations performed without solvent can yield similar accuracy at a fraction of the computational cost, making this method an attractive approach for prototyping and validation of self-assembled DNA nanostructures.     

De novo Cancers Following Liver Transplantation: A Single Center Experience in China

Background

De novo cancers are a growing problem that has become one of the leading causes of late mortality after liver transplantation. The incidences and risk factors varied among literatures and fewer concerned the Eastern population.

Aims

The aim of this study was to examine the incidence and clinical features of de novo cancers after liver transplantation in a single Chinese center.

Methods

569 patients who received liver transplantation and survived for more than 3 months in a single Chinese center were retrospectively reviewed.

Results

A total of 18 de novo cancers were diagnosed in 17 recipients (13 male and 4 female) after a mean of 41±26 months, with an overall incidence of 3.2%, which was lower than that in Western people. Of these, 8 (3.32%) cases were from 241 recipients with malignant liver diseases before transplant, while 10 (3.05%) cases were from 328 recipients with benign diseases. The incidence rates were comparable, p = 0.86. Furthermore, 2 cases developed in 1 year, 5 cases in 3 years and 11 cases over 3 years. The most frequent cancers developed after liver transplantation were similar to those in the general Chinese population but had much higher incidence rates.

Conclusions

Liver transplant recipients were at increased risk for developing de novo cancers. The incidence rates and pattern of de novo cancers in Chinese population are different from Western people due to racial and social factors. Pre-transplant malignant condition had no relationship to de novo cancer. Exact risk factors need further studies.     

De novo Assembly of highly diverse viral populations

ABSTRACT: BACKGROUND: Extensive genetic diversity in viral populations within infected hosts and the divergence of variants from existing reference genomes impede the analysis of deep viral sequencing data. A de novo population consensus assembly is valuable both as a single linear representation of the population and, as a backbone on which intra-host variants can be accurately mapped. The availability of consensus assemblies and robustly mapped variants are crucial to the genetic study of viral disease progression, transmission dynamics, and viral evolution. Existing de novo assembly techniques fail to robustly assemble ultra-deep sequence data from genetically heterogeneous populations such as viruses into full-length genomes due to the presence of extensive genetic variability, contaminants, and variable sequence coverage. RESULTS: We present VICUNA, a de novo assembly algorithm suitable for generating consensus assemblies from genetically heterogeneous populations. We demonstrate its effectiveness on Dengue, Human Immunodeficiency and West Nile viral populations, representing a range of intra-host diversity. Compared to state-of-the-art assemblers designed for haploid or diploid systems, VICUNA recovers full-length consensus and captures insertion/deletion polymorphisms in diverse samples. Final assemblies maintain a high base calling accuracy. VICUNA program is publicly available at: http://www.broadinstitute.org/scientific-community/science/projects/viral-genomics/viral-genomics-analysis-software CONCLUSIONS: We developed VICUNA, a publicly available software tool, that enables consensus assembly of ultra-deep sequence derived from diverse viral populations. While VICUNA was developed for the analysis of viral populations, its application to other heterogeneous sequence data sets such as metagenomic or tumor cell population samples may prove beneficial in these fields of research.