The genetic diversity of Neotropical fish fauna is underrepresented in public databases. This distortion is evident for the order Siluriformes, in which the suborders Siluroidei and Loricarioidei share equivalent proportion of species, although far less is known about the genetics of the latter clade, endemic to the Neotropical Region. Recently, this information gap was evident in a study about the structural diversity of fish mitochondrial genomes, and hampered a precise chronological resolution of Siluriformes. It has also prevented molecular ecology investigations about these catfishes, their interactions with the environment, responses to anthropogenic changes and potential uses.

CRISPR is a microbial immune system likely to be involved in host-parasite coevolution. It functions using target sequences encoded by the bacterial genome, which interfere with invading nucleic acids using a homology-dependent system. The system also requires protospacer associated motifs (PAMs), short motifs close to the target sequence that are required for interference in CRISPR types I and II. Here, we investigate whether PAMs are depleted in phage genomes due to selection pressure to escape recognition.

Pulmonary surfactant is required for lung function at birth and throughout life. Lung lipid and surfactant homeostasis requires regulation among multi-tiered processes, coordinating the synthesis of surfactant proteins and lipids, their assembly, trafficking, and storage in type II cells of the lung. The mechanisms regulating these interrelated processes are largely unknown.

Strand specific RNA sequencing is rapidly replacing conventional cDNA sequencing as an approach for assessing information about the transcriptome. Alongside improved laboratory protocols the development of bioinformatical tools is steadily progressing. In the current procedure the Illumina TruSeq library preparation kit is used, along with additional reagents, to make stranded libraries in an automated fashion which are then sequenced on Illumina HiSeq 2000. By the use of freely available bioinformatical tools we show, through quality metrics, that the protocol is robust and reproducible. We further highlight the practicality of strand specific libraries by comparing expression of strand specific libraries to non-stranded libraries, by looking at known antisense transcription of pseudogenes and by identifying novel transcription. Furthermore, two ribosomal depletion kits, RiboMinus and RiboZero, are compared and two sequence aligners, Tophat2 and STAR, are also compared.

The basic process of RNA splicing is conserved among eukaryotic species. Three signals (5' and 3' splice sites and branch site) are commonly used to directly conduct splicing, while other features are also related to the recognition of an intron. Although there is experimental evidence pointing to the significant species specificities in the features of intron recognition, a quantitative evaluation of the divergence of these features among a wide variety of eukaryotes has yet to be conducted.

The molecular, biochemical, and genetic mechanisms that regulate the complex metabolic network of soybean seed development determine the ultimate balance of protein, lipid, and carbohydrate stored in the mature seed. Many of the genes and metabolites that participate in seed metabolism are unknown or poorly defined; even more remains to be understood about the regulation of their metabolic networks. A global omics analysis can provide insights into the regulation of seed metabolism, even without a priori assumptions about the structure of these networks.

Recent developments in deep (next-generation) sequencing technologies are significantly impacting medical research. The global analysis of protein coding regions in genomes of interest by whole exome sequencing is a widely used application. Many technologies for exome capture are commercially available; here we compare the performance of four of them: NimbleGen's SeqCap EZ v3.0, Agilent's SureSelect v4.0, Illumina's TruSeq Exome, and Illumina's Nextera Exome, all applied to the same human tumor DNA sample.

Since the establishment of the first biomedical ontology Gene Ontology (GO), the number of biomedical ontology has increased dramatically. Nowadays over 300 ontologies have been built including extensively used Disease Ontology (DO) and Human Phenotype Ontology (HPO). Because of the advantage of identifying novel relationships between terms, calculating similarity between ontology terms is one of the major tasks in this research area. Though similarities between terms within each ontology have been studied with in silico methods, term similarities across different ontologies were not investigated as deeply. The latest method took advantage of gene functional interaction network (GFIN) to explore such inter-ontology similarities of terms. However, it only used gene interactions and failed to make full use of the connectivity among gene nodes of the network. In addition, all existent methods are particularly designed for GO and their performances on the extended ontology community remain unknown.

Complex diseases are characterized by multiple subtle perturbations to biological processes. New omics platforms can detect these perturbations, but translating the diverse molecular and statistical information into testable mechanistic hypotheses is challenging. Therefore, we set out to create a public tool that integrates these data across multiple datasets, platforms, study designs and species in order to detect the most promising targets for further mechanistic studies.

Inference of protein's membership in metabolic pathways has become an important task in functional annotation of protein. The membership information can provide valuable context to the basic functional annotation and also aid reconstruction of incomplete pathways. Previous works have shown success of inference by using various similarity measures of gene ontology.

Environmental shotgun sequencing (metagenomics) provides a new way to study communities in microbial ecology. We here use sequence data from the Global Ocean Sampling (GOS) expedition to investigate toxicant selection pressures revealed by the presence of detoxification genes in marine bacteria. To capture a broad range of potential toxicants we selected detoxification protein families representing systems protecting microorganisms from a variety of stressors, such as metals, organic compounds, antibiotics and oxygen radicals.

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by inflammation and destruction of synovial joints. RA affects up to 1 % of the population worldwide. Currently, there are no drugs that can cure RA or achieve sustained remission. The unknown cause of the disease represents a significant challenge in the drug development. In this study, we address this challenge by proposing an alternative drug discovery approach that integrates and reasons over genetic interrelationships between RA and other genetic diseases as well as a large amount of higher-level drug treatment data. We first constructed a genetic disease network using disease genetics data from Genome-Wide Association Studies (GWAS). We developed a network-based ranking algorithm to prioritize diseases genetically-related to RA (RA-related diseases). We then developed a drug prioritization algorithm to reposition drugs from RA-related diseases to treat RA.

The unicellular green alga Chlamydomonas reinhardtii is an important eukaryotic model organism for the study of photosynthesis and plant growth. In the era of modern high-throughput technologies there is an imperative need to integrate large-scale data sets from high-throughput experimental techniques using computational methods and database resources to provide comprehensive information about the molecular and cellular organization of a single organism.

Genomic data from various organisms have been used to study how sexual selection has shaped genetic diversity in reproductive proteins, and in particular, to elucidate how mating systems may have influenced evolution at the molecular and phenotypic levels. However, large-scale proteomic data including protein identifications and abundances are only now entering the field of evolutionary and comparative genomics. Variation in both protein sequence and expression level may play important roles in the evolution of sexual traits and behaviors.

The pig, which shares greater similarities with human than with mouse, is important for agriculture and for studying human diseases. However, similarities in the genetic architecture and molecular regulations underlying phenotypic variations in humans and swine have not been systematically assessed.

Large-scale genetic screening using CRISPR-Cas9 technology has emerged as a powerful approach to uncover and validate gene functions. The ability to control the timing of genetic perturbation during CRISPR screens will facilitate precise dissection of dynamic and complex biological processes. Here, we report the optimization of a drug-inducible CRISPR-Cas9 system that allows high-throughput gene interrogation with a temporal control.

Riemerella anatipestifer infection is a contagious disease that has resulted in major economic losses in the duck industry worldwide. This study attempted to characterize CRISPR-Cas systems in the disease-causing agent, Riemerella anatipestifer (R. anatipestifer). The CRISPR-Cas system provides adaptive immunity against foreign genetic elements in prokaryotes and CRISPR-cas loci extensively exist in the genomes of archaea and bacteria. However, the structure characteristics of R. anatipestifer CRISPR-Cas systems remains to be elucidated due to the limited availability of genomic data.

Traditional approaches to studying molecular networks are based on linking genes or proteins. Higher-level networks linking gene sets or pathways have been proposed recently. Several types of gene set networks have been used to study complex molecular networks such as co-membership gene set networks (M-GSNs) and co-enrichment gene set networks (E-GSNs). Gene set networks are useful for studying biological mechanism of diseases and drug perturbations.

Obesity and phenotypic traits associated with this condition exhibit significant heritability in natural populations of most organisms. While a number of genes and genetic pathways have been implicated to play a role in obesity associated traits, the genetic architecture that underlies the natural variation in these traits is largely unknown. Here, we used 40 wild-derived inbred lines of Drosophila melanogaster to quantify genetic variation in body weight, the content of three major metabolites (glycogen, triacylglycerol, and glycerol) associated with obesity, and metabolic rate in young flies. We chose these lines because they were previously screened for variation in whole-genome transcript abundance and in several adult life-history traits, including longevity, resistance to starvation stress, chill-coma recovery, mating behavior, and competitive fitness. This enabled us not only to identify candidate genes and transcriptional networks that might explain variation for energy metabolism traits, but also to investigate the genetic interrelationships among energy metabolism, behavioral, and life-history traits that have evolved in natural populations.

Bacteria are prey for many viruses that hijack the bacterial cell in order to propagate, which can result in bacterial cell lysis and death. Bacteria have developed diverse strategies to counteract virus predation, one of which is the clustered regularly interspaced short palindromic repeat (CRISPR) and CRISPR associated (Cas) proteins immune defense system. Species within the bacterial family Vibrionaceae are marine organisms that encounter large numbers of phages. Our goal was to determine the significance of CRISPR-Cas systems as a mechanism of defense in this group by investigating their prevalence, phylogenetic distribution, and genome context.