Identification of novel regulatory modules in dicotyledonous plants using expression data and comparative genomics

BACKGROUND: Transcriptional regulation plays an important role in the control of many biological processes. Transcription factor binding sites (TFBSs) are the functional elements that determine transcriptional activity and are organized into separable cis-regulatory modules, each defining the cooperation of several transcription factors required for a specific spatio-temporal expression pattern. Consequently, the discovery of novel TFBSs in promoter sequences is an important step to improve our understanding of gene regulation. RESULTS: Here, we applied a detection strategy that combines features of classic motif overrepresentation approaches in co-regulated genes with general comparative footprinting principles for the identification of biologically relevant regulatory elements and modules in Arabidopsis thaliana, a model system for plant biology. In total, we identified 80 TFBSs and 139 regulatory modules, most of which are novel, and primarily consist of two or three regulatory elements that could be linked to different important biological processes, such as protein biosynthesis, cell cycle control, photosynthesis and embryonic development. Moreover, studying the physical properties of some specific regulatory modules revealed that Arabidopsis promoters have a compact nature, with cooperative TFBSs located in close proximity of each other. CONCLUSION: These results create a starting point to unravel regulatory networks in plants and to study the regulation of biological processes from a systems biology point of view

In situ analysis of cross-hybridisation on microarrays and the inference of expression correlation

<p>Abstract</p> <p>Background</p> <p>Microarray co-expression signatures are an important tool for studying gene function and relations between genes. In addition to genuine biological co-expression, correlated signals can result from technical deficiencies like hybridization of reporters with off-target transcripts. An approach that is able to distinguish these factors permits the detection of more biologically relevant co-expression signatures.</p> <p>Results</p> <p>We demonstrate a positive relation between off-target reporter alignment strength and expression correlation in data from oligonucleotide genechips. Furthermore, we describe a method that allows the identification, from their expression data, of individual probe sets affected by off-target hybridization.</p> <p>Conclusion</p> <p>The effects of off-target hybridization on expression correlation coefficients can be substantial, and can be alleviated by more accurate mapping between microarray reporters and the target transcriptome. We recommend attention to the mapping for any microarray analysis of gene expression patterns.</p

Nonrandom divergence of gene expression following gene and genome duplications in the flowering plant Arabidopsis thaliana

BACKGROUND: Genome analyses have revealed that gene duplication in plants is rampant. Furthermore, many of the duplicated genes seem to have been created through ancient genome-wide duplication events. Recently, we have shown that gene loss is strikingly different for large- and small-scale duplication events and highly biased towards the functional class to which a gene belongs. Here, we study the expression divergence of genes that were created during large- and small-scale gene duplication events by means of microarray data and investigate both the influence of the origin (mode of duplication) and the function of the duplicated genes on expression divergence. RESULTS: Duplicates that have been created by large-scale duplication events and that can still be found in duplicated segments have expression patterns that are more correlated than those that were created by small-scale duplications or those that no longer lie in duplicated segments. Moreover, the former tend to have highly redundant or overlapping expression patterns and are mostly expressed in the same tissues, while the latter show asymmetric divergence. In addition, a strong bias in divergence of gene expression was observed towards gene function and the biological process genes are involved in. CONCLUSION: By using microarray expression data for Arabidopsis thaliana, we show that the mode of duplication, the function of the genes involved, and the time since duplication play important roles in the divergence of gene expression and, therefore, in the functional divergence of genes after duplication

Joint Belgian recommendation on screening for DPD-deficiency in patients treated with 5-FU, capecitabine (and tegafur)

Objectives: Fluoropyrimidines such as 5-Fluorouracil (5-FU), capecitabine and tegafur are drugs that are often used in the treatment of maliginancies. The enzyme dihydropyrimidine dehydrogenase (DPD) is the first and rate limiting enzyme of 5-FU catabolism. Genetic variations within the DPYD gene (encoding for DPD protein) can lead to reduced or absent DPD activity. Treatment of DPD deficient patients with fluoropyrimidines can result in severe and, rarely, fatal toxicity. Screening for DPD deficiency should be implemented in practice. Methods: The available methods in routine to screen for DPD deficiency were analyzed and discussed in several group meetings involving members of the oncological, genetic and toxicological societies in Belgium: targeted genotyping based on the detection of 4 DPYD variants and phenotyping, through the measurement of uracil and dihydrouracil/uracil ratio in plasma samples. Results: The main advantage of targeted genotyping is the existence of prospectively validated genotype-based dosing guidelines. The main limitations of this approach are the relatively low sensitivity to detect total and partial DPD deficiency and the fact that this approach has only been validated in Caucasians so far. Phenotyping has a better sensitivity to detect total and partial DPD deficiency when performed in the correct analytical conditions and is not dependent on the ethnic origin of the patient. Conclusion: In Belgium, we recommend phenotype or targeted genotype testing for DPD deficiency before starting 5-FU, capecitabine or tegafur. We strongly suggest a stepwise approach using phenotype testing upfront because of the higher sensitivity and the lower cost to society

Cross-hybridization modeling on Affymetrix exon arrays

Motivation: Microarray designs have become increasingly probe-rich, enabling targeting of specific features, such as individual exons or single nucleotide polymorphisms. These arrays have the potential to achieve quantitative high-throughput estimates of transcript abundances, but currently these estimates are affected by biases due to cross-hybridization, in which probes hybridize to off-target transcripts

CrossHybDetector: detection of cross-hybridization events in DNA microarray experiments

Background\ud DNA microarrays contain thousands of different probe sequences represented on their surface. These are designed in such a way that potential cross-hybridization reactions with non-target sequences are minimized. However, given the large number of probes, the occurrence of cross hybridization events cannot be excluded. This problem can dramatically affect the data quality and cause false positive/false negative results.\ud \ud Results\ud CrossHybDetector is a software package aimed at the identification of cross-hybridization events occurred during individual array hybridization, by using the probe sequences and the array intensity values. As output, the software provides the user with a list of array spots potentially &apos;corrupted&apos; and their associated p-values calculated by Monte Carlo simulations. Graphical plots are also generated, which provide a visual and global overview of the quality of the microarray experiment with respect to cross-hybridization issues.\ud \ud Conclusion\ud CrossHybDetector is implemented as a package for the statistical computing environment R and is freely available under the LGPL license within the CRAN project

Genetic subtypes of smoldering multiple myeloma are associated with distinct pathogenic phenotypes and clinical outcomes

Smoldering multiple myeloma (SMM) is a precursor condition of multiple myeloma (MM) with significant heterogeneity in disease progression. Existing clinical models of progression risk do not fully capture this heterogeneity. Here we integrate 42 genetic alterations from 214 SMM patients using unsupervised binary matrix factorization (BMF) clustering and identify six distinct genetic subtypes. These subtypes are differentially associated with established MM-related RNA signatures, oncogenic and immune transcriptional profiles, and evolving clinical biomarkers. Three genetic subtypes are associated with increased risk of progression to active MM in both the primary and validation cohorts, indicating they can be used to better predict high and low-risk patients within the currently used clinical risk stratification models

Daratumumab, bortezomib, and dexamethasone in relapsed or refractory multiple myeloma: subgroup analysis of CASTOR based on cytogenetic risk

BACKGROUND: Multiple myeloma (MM) patients with high cytogenetic risk have poor outcomes. In CASTOR, daratumumab plus bortezomib/dexamethasone (D-Vd) prolonged progression-free survival (PFS) versus bortezomib/dexamethasone (Vd) alone and exhibited tolerability in patients with relapsed or refractory MM (RRMM). METHODS: This subgroup analysis evaluated D-Vd versus Vd in CASTOR based on cytogenetic risk, determined using fluorescence in situ hybridization and/or karyotype testing performed locally. High-risk patients had t(4;14), t(14;16), and/or del17p abnormalities. Minimal residual disease (MRD; 10-5 sensitivity threshold) was assessed via the clonoSEQ\uae assay V2.0. Of the 498 patients randomized, 40 (16%) in the D-Vd group and 35 (14%) in the Vd group were categorized as high risk. RESULTS: After a median follow-up of 40.0\u2009months, D-Vd prolonged median PFS versus Vd in patients with standard (16.6 vs 6.6\u2009months; HR, 0.26; 95% CI, 0.19-0.37; P &lt; 0.0001) and high (12.6 vs 6.2\u2009months; HR, 0.41; 95% CI, 0.21-0.83; P = 0.0106) cytogenetic risk. D-Vd achieved deep responses, including higher rates of MRD negativity and sustained MRD negativity versus Vd, regardless of cytogenetic risk. The safety profile was consistent with the overall population of CASTOR. CONCLUSION: These updated data reinforce the effectiveness and tolerability of daratumumab-based regimens for RRMM, regardless of cytogenetic risk status. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02136134 . Registered 12 May 2014

Genomic Profiling of Smoldering Multiple Myeloma Identifies Patients at a High Risk of Disease Progression

PURPOSE: Smoldering multiple myeloma (SMM) is a precursor condition of multiple myeloma (MM) with a 10% annual risk of progression. Various prognostic models exist for risk stratification; however, those are based on solely clinical metrics. The discovery of genomic alterations that underlie disease progression to MM could improve current risk models. METHODS: We used next-generation sequencing to study 214 patients with SMM. We performed whole-exome sequencing on 166 tumors, including 5 with serial samples, and deep targeted sequencing on 48 tumors. RESULTS: We observed that most of the genetic alterations necessary for progression have already been acquired by the diagnosis of SMM. Particularly, we found that alterations of the mitogen-activated protein kinase pathway (KRAS and NRAS single nucleotide variants [SNVs]), the DNA repair pathway (deletion 17p, TP53, and ATM SNVs), and MYC (translocations or copy number variations) were all independent risk factors of progression after accounting for clinical risk staging. We validated these findings in an external SMM cohort by showing that patients who have any of these three features have a higher risk of progressing to MM. Moreover, APOBEC associated mutations were enriched in patients who progressed and were associated with a shorter time to progression in our cohort. CONCLUSION: SMM is a genetically mature entity whereby most driver genetic alterations have already occurred, which suggests the existence of a right-skewed model of genetic evolution from monoclonal gammopathy of undetermined significance to MM. We identified and externally validated genomic predictors of progression that could distinguish patients at high risk of progression to MM and, thus, improve on the precision of current clinical models