Functional Effects of let-7g Expression in Colon Cancer Metastasis.

MicroRNA regulation is crucial for gene expression and cell functions. It has been linked to tumorigenesis, development and metastasis in colorectal cancer (CRC). Recently, the let-7 family has been identified as a tumor suppressor in different types of cancers. However, the function of the let-7 family in CRC metastasis has not been fully investigated. Here, we focused on analyzing the role of let-7g in CRC. The Cancer Genome Atlas (TCGA) genomic datasets of CRC and detailed data from a Taiwanese CRC cohort were applied to study the expression pattern of let-7g. In addition, in vitro as well as in vivo studies have been performed to uncover the effects of let-7g on CRC. We found that the expression of let-7g was significantly lower in CRC specimens. Our results further supported the inhibitory effects of let-7g on CRC cell migration, invasion and extracellular calcium influx through store-operated calcium channels. We report a critical role for let-7g in the pathogenesis of CRC and suggest let-7g as a potential therapeutic target for CRC treatment

Mitochondrial metagenomics: letting the genes out of the bottle

‘Mitochondrial metagenomics’ (MMG) is a methodology for shotgun sequencing of total DNA from specimen mixtures and subsequent bioinformatic extraction of mitochondrial sequences. The approach can be applied to phylogenetic analysis of taxonomically selected taxa, as an economical alternative to mitogenome sequencing from individual species, or to environmental samples of mixed specimens, such as from mass trapping of invertebrates. The routine generation of mitochondrial genome sequences has great potential both for systematics and community phylogenetics. Mapping of reads from low-coverage shotgun sequencing of environmental samples also makes it possible to obtain data on spatial and temporal turnover in whole-community phylogenetic and species composition, even in complex ecosystems where species-level taxonomy and biodiversity patterns are poorly known. In addition, read mapping can produce information on species biomass, and potentially allows quantification of within-species genetic variation. The success of MMG relies on the formation of numerous mitochondrial genome contigs, achievable with standard genome assemblers, but various challenges for the efficiency of assembly remain, particularly in the face of variable relative species abundance and intra-specific genetic variation. Nevertheless, several studies have demonstrated the power of mitogenomes from MMG for accurate phylogenetic placement, evolutionary analysis of species traits, biodiversity discovery and the establishment of species distribution patterns; it offers a promising avenue for unifying the ecological and evolutionary understanding of species diversity

SpBase: the sea urchin genome database and web site

SpBase is a system of databases focused on the genomic information from sea urchins and related echinoderms. It is exposed to the public through a web site served with open source software (http://spbase.org/). The enterprise was undertaken to provide an easily used collection of information to directly support experimental work on these useful research models in cell and developmental biology. The information served from the databases emerges from the draft genomic sequence of the purple sea urchin, Strongylocentrotus purpuratus and includes sequence data and genomic resource descriptions for other members of the echinoderm clade which in total span 540 million years of evolutionary time. This version of the system contains two assemblies of the purple sea urchin genome, associated expressed sequences, gene annotations and accessory resources. Search mechanisms for the sequences and the gene annotations are provided. Because the system is maintained along with the Sea Urchin Genome resource, a database of sequenced clones is also provided

Fuzzy-based Spectral Alignment for Correcting DNA Sequence from Next Generation Sequencer

Next generation sequencing technology is able to generate short read in large numbers and in a relatively short in single running programs. Graph based DNA sequence assembly used to handle these big data in assembly step. The graph based DNA sequence assembly is very sensitive to DNA sequencing error. This problem could be solved by performing an error correction step before the assembly process. This research proposed fuzzy inference system (FIS) model based spectral alignment method which can detect and correct DNA sequencing error. The spectral alignment technique was implemented as a pre-processing step before the DNA sequence assembly process. The evaluation was conducted using Velvet assembler. The number of nodes yielded by the Velvet assembler become a measure of the success of error correction. The results shows that FIS model based spectral alignment created small number of nodes and therefore it successfully corrected the DNA reads

Whole-genome sequence analysis for pathogen detection and diagnostics

This dissertation focuses on computational methods for improving the accuracy of commonly used nucleic acid tests for pathogen detection and diagnostics. Three specific biomolecular techniques are addressed: polymerase chain reaction, microarray comparative genomic hybridization, and whole-genome sequencing. These methods are potentially the future of diagnostics, but each requires sophisticated computational design or analysis to operate effectively. This dissertation presents novel computational methods that unlock the potential of these diagnostics by efficiently analyzing whole-genome DNA sequences. Improvements in the accuracy and resolution of each of these diagnostic tests promises more effective diagnosis of illness and rapid detection of pathogens in the environment. For designing real-time detection assays, an efficient data structure and search algorithm are presented to identify the most distinguishing sequences of a pathogen that are absent from all other sequenced genomes. Results are presented that show these "signature" sequences can be used to detect pathogens in complex samples and differentiate them from their non-pathogenic, phylogenetic near neighbors. For microarray, novel pan-genomic design and analysis methods are presented for the characterization of unknown microbial isolates. To demonstrate the effectiveness of these methods, pan-genomic arrays are applied to the study of multiple strains of the foodborne pathogen, Listeria monocytogenes, revealing new insights into the diversity and evolution of the species. Finally, multiple methods are presented for the validation of whole-genome sequence assemblies, which are capable of identifying assembly errors in even finished genomes. These validated assemblies provide the ultimate nucleic acid diagnostic, revealing the entire sequence of a genome