CAOS Group

African swine fever (ASF) is a re-expanding devastating viral disease currently threatening the pig industry worldwide. MicroRNAs are a class of 17-25 nucleotide non- coding RNAs that have been shown to have critical functions in a wide variety of biological processes, such as cell differentiation, cell cycle regulation, carcinogenesis, apoptosis, regulation of immunity as well as in viral infections by cleavage or translational repression of mRNAs. Nevertheless, there is no information about miRNA expression in an ASFV infection. In this proof-of-concept study, we have analyzed miRNAs expressed in spleen and submandibular lymph node of experimentally infected pigs with a virulent (E75) or its derived attenuated (E75CV1) ASFV strain, as well as, at different times post-infection with the virulent strain, by high throughput sequencing of small RNA libraries. Spleen presented a more differential expression pattern than lymph nodes in an ASFV infection. Of the most abundant miRNAs, 12 ...

African swine fever virus (ASFV) is the etiological agent of African swine fever (ASF), a re-expanding devastating and highly lethal hemorrhagic viral disease. microRNAs (miRNAs) are a new class of small non-coding RNAs that regulate gene expression post-transcriptionally. The discovery of virus specific miRNAs has increased both in number and importance in the past few years. We have recently described the differential expression of several porcine miRNAs during in vivo infection with attenuated and virulent ASFV strains. Here, we have extended these studies trying to identify the presence of viral miRNAs encoded by ASFV in an in vivo infection in pigs. Sixteen small RNA libraries were analyzed from spleen and submandibular lymph nodes obtained from eight pigs, seven infected with either the virulent E75 ASFV strain or its attenuated counterpart E75CV1, or from pigs surviving E75CV1-infection and challenged with BA71 (heterologous challenge) and one non infected as negative control...

Motivation: Genomic research laboratories need adequate infrastructure to support management of their data production and research workflow. But what makes infrastructure adequate? A lack of appropriate criteria makes any decision on buying or developing a system difficult. Here, we report on the decision process for the case of a molecular genetics group establishing a microarray laboratory. Results: Five typical requirements for experimental genomics database systems were identified: (i) evolution ability to keep up with the fast developing genomics field; (ii) a suitable data model to deal with local diversity; (iii) suitable storage of data files in the system; (iv) easy exchange with other software; and (v) low maintenance costs. The computer scientists and the researchers of the local microarray laboratory considered alternative solutions for these five requirements and chose the following options: (i) use of automatic code generation; (ii) a customized data model based on sta...

Background R is the preferred tool for statistical analysis of many bioinformaticians due in part to the increasing number of freely available analytical methods. Such methods can be quickly reused and adapted to each particular experiment. However, in experiments where large amounts of data are generated, for example using high-throughput screening devices, the processing time required to analyze data is often quite long. A solution to reduce the processing time is the use of parallel computing technologies. Because R does not support parallel computations, several tools have been developed to enable such technologies. However, these tools require multiple modications to the way R programs are usually written or run. Although these tools can finally speed up the calculations, the time, skills and additional resources required to use them are an obstacle for most bioinformaticians. Results We have designed and implemented an R add-on package, R/parallel, that extends R by adding use...

We present an extensible software model for the genotype and phenotype community, XGAP. Readers can download a standard XGAP (http://www.xgap.org) or auto-generate a custom version using MOLGENIS with programming interfaces to R-software and web-services or user interfaces for biologists. XGAP has simple load formats for any type of genotype, epigenotype, transcript, protein, metabolite or other phenotype data. Current functionality includes tools ranging from eQTL analysis in mouse to genome-wide association studies in humans.

The accurate estimation of nucleotide variability using next-generation sequencing data is challenged by the high number of sequencing errors produced by new sequencing technologies, especially for nonmodel species, where reference sequences may not be available and the read depth may be low due to limited budgets. The most popular single-nucleotide polymorphism (SNP) callers are designed to obtain a high SNP recovery and low false discovery rate but are not designed to account appropriately the frequency of the variants. Instead, algorithms designed to account for the frequency of SNPs give precise results for estimating the levels and the patterns of variability. These algorithms are focused on the unbiased estimation of the variability and not on the high recovery of SNPs. Here, we implemented a fast and optimized parallel algorithm that includes the method developed by Roesti et al and Lynch, which estimates the genotype of each individual at each site, considering the possibili...