MediPlEx - a tool to combine in silico & experimental gene expression profiles of the model legume Medicago truncatula

Background: Expressed Sequence Tags (ESTs) are in general used to gain a first insight into gene activities from a species of interest. Subsequently, and typically based on a combination of EST and genome sequences, microarray-based expression analyses are performed for a variety of conditions. In some cases, a multitude of EST and microarray experiments are conducted for one species, covering different tissues, cell states, and cell types. Under these circumstances, the challenge arises to combine results derived from the different expression profiling strategies, with the goal to uncover novel information on the basis of the integrated datasets. Findings: Using our new analysis tool, MediPlEx (MEDIcago truncatula multiPLe EXpression analysis), expression data from EST experiments, oligonucleotide microarrays and Affymetrix GeneChips® can be combined and analyzed, leading to a novel approach to integrated transcriptome analysis. We have validated our tool via the identification of a set of well-characterized AM-specific and AM-induced marker genes, identified by MediPlEx on the basis of in silico and experimental gene expression profiles from roots colonized with AM fungi. Conclusions: MediPlEx offers an integrated analysis pipeline for different sets of expression data generated for the model legume Medicago truncatula. As expected, in silico and experimental gene expression data that cover the same biological condition correlate well. The collection of differentially expressed genes identified via MediPlEx provides a starting point for functional studies in plant mutants.

A 1.77 Mb deletion in 3p26.3 encompassing CNTN6 and CNTN4 genes: case report

Chromosome microarray analysis is a powerful diagnostic tool and is being used as a first-line approach to detect chromosome imbalances associated with intellectual disability, dysmorphic features and congenital abnormalities. This test enables the identification of new copy number variants (CNVs) and their association with new microdeletion/microduplication syndromes in patients previously without diagnosis. We report the case of a 7 year-old female with moderate intellectual disability, severe speech delay and auto and hetero aggressivity with a previous 45,XX,der(13;14)mat karyotype performed at a younger age. Affymetrix CytoScan 750K chromosome microarray analysis was performed detecting a 1.77 Mb deletion at 3p26.3, encompassing 2 OMIM genes, CNTN6 and CNTN4. These genes play an important role in the formation, maintenance, and plasticity of functional neuronal networks. Deletions or mutations in CNTN4 gene have been implicated in intellectual disability and learning disabilities. Disruptions or deletions in the CNTN6 gene have been associated with development delay and other neurodevelopmental disorders. The haploinsufficiency of these genes has been suggested to participate to the typical clinical features of 3p deletion syndrome. Nevertheless inheritance from a healthy parent has been reported, suggesting incomplete penetrance and variable phenotype for this CNV. We compare our patient with other similar reported cases, adding additional value to the phenotype-genotype correlation of deletions in this region.

Pre-announcement of symbiotic guests: transcriptional reprogramming by mycorrhizal lipochitooligosaccharides shows a strict co-dependency on the GRAS transcription factors NSP1 and RAM1

BACKGROUND: More than 80 % of all terrestrial plant species establish an arbuscular mycorrhiza (AM) symbiosis with Glomeromycota fungi. This plant-microbe interaction primarily improves phosphate uptake, but also supports nitrogen, mineral, and water aquisition. During the pre-contact stage, the AM symbiosis is controled by an exchange of diffusible factors from either partner. Amongst others, fungal signals were identified as a mix of sulfated and non-sulfated lipochitooligosaccharides (LCOs), being structurally related to rhizobial nodulation (Nod)-factor LCOs that in legumes induce the formation of nitrogen-fixing root nodules. LCO signals are transduced via a common symbiotic signaling pathway (CSSP) that activates a group of GRAS transcription factors (TFs). Using complex gene expression fingerprints as molecular phenotypes, this study primarily intended to shed light on the importance of the GRAS TFs NSP1 and RAM1 for LCO-activated gene expression during pre-symbiotic signaling. RESULTS: We investigated the genome-wide transcriptional responses in 5 days old primary roots of the Medicago truncatula wild type and four symbiotic mutants to a 6 h challenge with LCO signals supplied at 10(-7/-8) M. We were able to show that during the pre-symbiotic stage, sulfated Myc-, non-sulfated Myc-, and Nod-LCO-activated gene expression almost exclusively depends on the LysM receptor kinase NFP and is largely controled by the CSSP, although responses independent of this pathway exist. Our results show that downstream of the CSSP, gene expression activation by Myc-LCOs supplied at 10(-7/-8) M strictly required both the GRAS transcription factors RAM1 and NSP1, whereas those genes either co- or specifically activated by Nod-LCOs displayed a preferential NSP1-dependency. RAM1, a central regulator of root colonization by AM fungi, controled genes activated by non-sulfated Myc-LCOs during the pre-symbiotic stage that are also up-regulated in areas with early physical contact, e.g. hyphopodia and infecting hyphae; linking responses to externally applied LCOs with early root colonization. CONCLUSIONS: Since both RAM1 and NSP1 were essential for the pre-symbiotic transcriptional reprogramming by Myc-LCOs, we propose that downstream of the CSSP, these GRAS transcription factors act synergistically in the transduction of those diffusible signals that pre-announce the presence of symbiotic fungi.

EMMA 2--a MAGE-compliant system for the collaborative analysis and integration of microarray data

Background: Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes. Attempts to standardize the annotation of microarray data include the Minimum Information About a Microarray Experiment (MIAME) recommendations, the MAGE-ML format for data interchange, and the use of controlled vocabularies or ontologies. The existing software systems for microarray data analysis implement the mentioned standards only partially and are often hard to use and extend. Integration of genomic annotation data and other sources of external knowledge using open standards is therefore a key requirement for future integrated analysis systems. Results: The EMMA 2 software has been designed to resolve shortcomings with respect to full MAGE-ML and ontology support and makes use of modern data integration techniques. We present a software system that features comprehensive data analysis functions for spotted arrays, and for the most common synthesized oligo arrays such as Agilent, Affymetrix and NimbleGen. The system is based on the full MAGE object model. Analysis functionality is based on R and Bioconductor packages and can make use of a compute cluster for distributed services. Conclusion: Our model-driven approach for automatically implementing a full MAGE object model provides high flexibility and compatibility. Data integration via SOAP-based web-services is advantageous in a distributed client-server environment as the collaborative analysis of microarray data is gaining more and more relevance in international research consortia. The adequacy of the EMMA 2 software design and implementation has been proven by its application in many distributed functional genomics projects. Its scalability makes the current architecture suited for extensions towards future transcriptomics methods based on high-throughput sequencing approaches which have much higher computational requirements than microarrays.

Analysis of human breast milk cells: gene expression profiles during pregnancy, lactation, involution, and mastitic infection

The molecular processes underlying human milk production and the effects of mastitic infection are largely unknown because of limitations in obtaining tissue samples. Determination of gene expression in normal lactating women would be a significant step toward understanding why some women display poor lactation outcomes. Here, we demonstrate the utility of RNA obtained directly from human milk cells to detect mammary epithelial cell (MEC)-specific gene expression. Milk cell RNA was collected from five time points (24 h prepartum during the colostrum period, midlactation, two involutions, and during a bout of mastitis) in addition to an involution series comprising three time points. Gene expression profiles were determined by use of human Affymetrix arrays. Milk cells collected during milk production showed that the most highly expressed genes were involved in milk synthesis (e.g., CEL, OLAH, FOLR1, BTN1A1, and ARG2), while milk cells collected during involution showed a significant downregulation of milk synthesis genes and activation of involution associated genes (e.g., STAT3, NF-kB, IRF5, and IRF7). Milk cells collected during mastitic infection revealed regulation of a unique set of genes specific to this disease state, while maintaining regulation of milk synthesis genes. Use of conventional epithelial cell markers was used to determine the population of MECs within each sample. This paper is the first to describe the milk cell transcriptome across the human lactation cycle and during mastitic infection, providing valuable insight into gene expression of the human mammary gland.

Multicentric genome-wide association study for primary spontaneous pneumothorax

Despite elevated incidence and recurrence rates for Primary Spontaneous Pneumothorax (PSP), little is known about its etiology, and the genetics of idiopathic PSP remains unexplored. To identify genetic variants contributing to sporadic PSP risk, we conducted the first PSP genome-wide association study. Two replicate pools of 92 Portuguese PSP cases and of 129 age- and sex-matched controls were allelotyped in triplicate on the Affymetrix Human SNP Array 6.0 arrays. Markers passing quality control were ranked by relative allele score difference between cases and controls (|RASdiff|), by a novel cluster method and by a combined Z-test. 101 single nucleotide polymorphisms (SNPs) were selected using these three approaches for technical validation by individual genotyping in the discovery dataset. 87 out of 94 successfully tested SNPs were nominally associated in the discovery dataset. Replication of the 87 technically validated SNPs was then carried out in an independent replication dataset of 100 Portuguese cases and 425 controls. The intergenic rs4733649 SNP in chromosome 8 (between LINC00824 and LINC00977) was associated with PSP in the discovery (P = 4.07E-03, ORC[95% CI] = 1.88[1.22–2.89]), replication (P = 1.50E-02, ORC[95% CI] = 1.50[1.08–2.09]) and combined datasets (P = 8.61E-05, ORC[95% CI] = 1.65[1.29–2.13]). This study identified for the first time one genetic risk factor for sporadic PSP, but future studies are warranted to further confirm this finding in other populations and uncover its functional role in PSP pathogenesis.