Two trans-acting eQTLs modulate the penetrance of PRPF31 mutations

Dominant mutations in the gene encoding the ubiquitously-expressed splicing factor PRPF31 cause retinitis pigmentosa, a form of hereditary retinal degeneration, with reduced penetrance. We and others have previously shown that penetrance is tightly correlated with PRPF31 expression, as lymphoblastoid cell lines (LCLs) from affected patients produce less abundant PRPF31 transcripts than LCLs from their unaffected relatives carrying the same mutation. We have investigated the genetic elements determining the variable expression of PRPF31, and therefore possibly influencing the penetrance of its mutations, by quantifying PRPF31 mRNA levels in LCLs derived from 15 CEPH families (200 individuals), representative of the general population. We found that PRPF31 transcript abundance was a highly variable and highly heritable character. Moreover, by linkage analysis we showed that PRPF31 expression was significantly associated with at least one expression quantitative trait locus (eQTL), spanning a 8.2-Mb region on chromosome 14q21-23. We also investigated a previously mapped penetrance factor located near PRPF31 itself in LCLs from individuals belonging to selected families segregating PRPF31 mutations that displayed reduced penetrance. Our results indicate that, despite its constant association with the non-mutant allele, this factor was able to modulate the expression of both PRPF31 alleles. Furthermore, we showed that LCLs from affected patients have less PRPF31 RNA than those of asymptomatic patients, even at the pre-splicing stage. Altogether, these data demonstrate that PRPF31 mRNA expression and consequently the penetrance of PRPF31 mutations is managed by diffusible compounds encoded by at least two modifiers, acting in a co-regulatory system on both PRPF31 alleles during transcriptio

The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article

Developing Molecular Signatures for Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is a clonal malignancy of mature B cells that displays a great clinical heterogeneity, with many patients having an indolent disease that will not require intervention for many years, while others present an aggressive and symptomatic leukemia requiring immediate treatment. Although there is no cure for CLL, the disease is treatable and current standard chemotherapy regimens have been shown to prolong survival. Recent advances in our understanding of the biology of CLL have led to the identification of numerous cellular and molecular markers with potential diagnostic, prognostic and therapeutic significance. We have used the recently developed digital multiplexed gene-expression technique (DMGE) to analyze a cohort of 30 CLL patients for the presence of specific genes with known diagnostic and prognostic potential. Starting from a set of 290 genes we were able to develop a molecular signature, based on the analysis of 13 genes, which allows distinguishing CLL from normal peripheral blood and from normal B cells, and a second signature based on 24 genes, which distinguishes mutated from unmutated cases (LymphCLL Mut). A third classifier (LymphCLL Diag), based on a 44-gene signature, distinguished CLL cases from a series of other B-cell chronic lymphoproliferative disorders (n = 51). While the methodology presented here has the potential to provide a "ready to use" classification tool in routine diagnostics and clinical trials, application to larger sample numbers are still needed and should provide further insights about its robustness and utility in clinical practice

Transcriptomic approach for assessment of the impact on microalga and macrophyte of in-situ exposure in river sites contaminated by chlor-alkali plant effluents

Water quality degradation is a worldwide problem, but risk evaluation of chronic pollution in-situ is still a challenge. The present study aimed to evaluate the potential of transcriptomic analyses in representative aquatic primary producers to assess the impact of environmental pollution in-situ: the microalga Chlamydomonas reinhardtii and the macrophyte Elodea nuttallii were exposed 2 h in the Babeni Reservoir of the Olt River impacted by chlor-alkali plant effluent release resulting in increased concentrations of Hg and NaCl in receiving water. The response at the transcriptomic level was strong, resulting in up to 5485, and 8700 dysregulated genes (DG) for the microalga and for the macrophyte exposed in the most contaminated site, respectively. Transcriptomic response was congruent with the concentrations of Hg and NaCl in the water of the impacted reservoir. Genes involved in development, energy metabolism, lipid metabolism, nutrition, and RedOx homeostasis were dysregulated during in-situ exposure of both organisms. In addition, genes involved in the cell motility of C. reinhardtii and development of the cell wall of E. nuttallii were affected. DG were in line with adverse outcome pathways and transcriptomic studies reported after exposure to high concentrations of Hg and NaCl under controlled conditions in the laboratory. Transcriptomic response provided a sensitive measurement of the exposure as well as hints on the tolerance mechanisms of environmental pollution, and is thus promising as an early-warning tool to assess water quality degradation

LDOC1 expression in CLL samples.

<p>CLL samples were separated into those highly expressing LDOC1 and those with absent/low expression. Listed are those genes that fulfill the following criteria: >2-fold change in expression between LDOC1 pos samples compared to LDOC1 neg samples, with a p-value < 0.05 or >2-fold change in expression between LDOC1 neg samples compared to LDOC1 pos samples, with a p-value < 0.05.</p><p>LDOC1 expression in CLL samples.</p

Characterization of different types of CLL samples using PCA analysis.

<p>Samples from PB (n = 5), B cell samples (n = 4), and samples from CLL patients (n = 30) were analyzed by PCA, based on the results of the differential expression of 44 genes. Mutated CLL cases are shown in blue (n = 11), unmutated in green (n = 17), and borderline cases in red (n = 2).</p

Quantification of mRNA transcripts for surface proteins.

<p>Quantification of mRNA transcripts for surface proteins.</p

Comparison of CLL to other B-CLPD using PCA.

<p>Samples from CLL patients (n = 30) and of other B-CLPD (n = 51) were analyzed by PCA, based on the results of the differential expression of the selected 44 genes.</p