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Abstract Background Expression traits can vary quantitatively between individuals and have a complex inheritance. Identification of the genetics underlying transcript variation can help in the understanding of phenotypic variation due to genetic factors regulating transcript abundance and shed light into divergence patterns. So far, only a limited number of studies have addressed this subject in Arabidopsis, with contrasting results due to dissimilar statistical power. Here, we present the transcriptome architecture in leaf tissue of two RIL sets obtained from a connected-cross design involving 3 commonly used accessions. We also present the transcriptome architecture observed in developing seeds of a third independent cross. Results The utilisation of the novel R/eqtl package (which goal is to automatize and extend functions from the R/qtl package) allowed us to map 4,290 and 6,534 eQTLs in the Cvi-0 × Col-0 and Bur-0 × Col-0 recombinant populations respectively. In agreement with previous studies, we observed a larger phenotypic variance explained by eQTLs in linkage with the controlled gene (potentially cis-acting), compared to distant loci (acting necessarily indirectly or in trans). Distant eQTLs hotspots were essentially not conserved between crosses, but instead, cross-specific. Accounting for confounding factors using a probabilistic approach (VBQTL) increased the mapping resolution and the number of significant associations. Moreover, using local eQTLs obtained from this approach, we detected evidence for a directional allelic effect in genes with related function, where significantly more eQTLs than expected by chance were up-regulated from one of the accessions. Primary experimental data, analysis parameters, eQTL results and visualisation of LOD score curves presented here are stored and accessible through the QTLstore service database http://qtlstore.versailles.inra.fr/. Conclusions Our results demonstrate the extensive diversity and moderately conserved eQTL landscape between crosses and validate the utilisation of expression traits to explore for candidates behind phenotypic variation among accessions. Furthermore, this stresses the need for a wider spectrum of diversity to fully understand expression trait variation within a species.

Abstract Background One of the key goals of oak genomics research is to identify genes of adaptive significance. This information may help to improve the conservation of adaptive genetic variation and the management of forests to increase their health and productivity. Deep-coverage large-insert genomic libraries are a crucial tool for attaining this objective. We report herein the construction of a BAC library for Quercus robur, its characterization and an analysis of BAC end sequences. Results The EcoRI library generated consisted of 92,160 clones, 7% of which had no insert. Levels of chloroplast and mitochondrial contamination were below 3% and 1%, respectively. Mean clone insert size was estimated at 135 kb. The library represents 12 haploid genome equivalents and, the likelihood of finding a particular oak sequence of interest is greater than 99%. Genome coverage was confirmed by PCR screening of the library with 60 unique genetic loci sampled from the genetic linkage map. In total, about 20,000 high-quality BAC end sequences (BESs) were generated by sequencing 15,000 clones. Roughly 5.88% of the combined BAC end sequence length corresponded to known retroelements while ab initio repeat detection methods identified 41 additional repeats. Collectively, characterized and novel repeats account for roughly 8.94% of the genome. Further analysis of the BESs revealed 1,823 putative genes suggesting at least 29,340 genes in the oak genome. BESs were aligned with the genome sequences of Arabidopsis thaliana, Vitis vinifera and Populus trichocarpa. One putative collinear microsyntenic region encoding an alcohol acyl transferase protein was observed between oak and chromosome 2 of V. vinifera. Conclusions This BAC library provides a new resource for genomic studies, including SSR marker development, physical mapping, comparative genomics and genome sequencing. BES analysis provided insight into the structure of the oak genome. These sequences will be used in the assembly of a future genome sequence for oak.

Abstract Background Comparative genomics has emerged as a promising means of unravelling the molecular networks underlying complex traits such as drought tolerance. Here we assess the genotype-dependent component of the drought-induced transcriptome response in two poplar genotypes differing in drought tolerance. Drought-induced responses were analysed in leaves and root apices and were compared with available transcriptome data from other Populus species. Results Using a multi-species designed microarray, a genomic DNA-based selection of probesets provided an unambiguous between-genotype comparison. Analyses of functional group enrichment enabled the extraction of processes physiologically relevant to drought response. The drought-driven changes in gene expression occurring in root apices were consistent across treatments and genotypes. For mature leaves, the transcriptome response varied weakly but in accordance with the duration of water deficit. A differential clustering algorithm revealed similar and divergent gene co-expression patterns among the two genotypes. Since moderate stress levels induced similar physiological responses in both genotypes, the genotype-dependent transcriptional responses could be considered as intrinsic divergences in genome functioning. Our meta-analysis detected several candidate genes and processes that are differentially regulated in root and leaf, potentially under developmental control, and preferentially involved in early and long-term responses to drought. Conclusions In poplar, the well-known drought-induced activation of sensing and signalling cascades was specific to the early response in leaves but was found to be general in root apices. Comparing our results to what is known in arabidopsis, we found that transcriptional remodelling included signalling and a response to energy deficit in roots in parallel with transcriptional indices of hampered assimilation in leaves, particularly in the drought-sensitive poplar genotype.

Abstract Background The physiological function of the prion protein remains largely elusive while its key role in prion infection has been expansively documented. To potentially assess this conundrum, we performed a comparative transcriptomic analysis of the brain of wild-type mice with that of transgenic mice invalidated at this locus either at the zygotic or at the adult stages. Results Only subtle transcriptomic differences resulting from the Prnp knockout could be evidenced, beside Prnp itself, in the analyzed adult brains following microarray analysis of 24 109 mouse genes and QPCR assessment of some of the putatively marginally modulated loci. When performed at the adult stage, neuronal Prnp disruption appeared to sequentially induce a response to an oxidative stress and a remodeling of the nervous system. However, these events involved only a limited number of genes, expression levels of which were only slightly modified and not always confirmed by RT-qPCR. If not, the qPCR obtained data suggested even less pronounced differences. Conclusions These results suggest that the physiological function of PrP is redundant at the adult stage or important for only a small subset of the brain cell population under classical breeding conditions. Following its early reported embryonic developmental regulation, this lack of response could also imply that PrP has a more detrimental role during mouse embryogenesis and that potential transient compensatory mechanisms have to be searched for at the time this locus becomes transcriptionally activated.

Abstract Background Most microarray studies are made using labelling with one or two dyes which allows the hybridization of one or two samples on the same slide. In such experiments, the most frequently used dyes are Cy3 and Cy5. Recent improvements in the technology (dye-labelling, scanner and, image analysis) allow hybridization up to four samples simultaneously. The two additional dyes are Alexa488 and Alexa494. The triple-target or four-target technology is very promising, since it allows more flexibility in the design of experiments, an increase in the statistical power when comparing gene expressions induced by different conditions and a scaled down number of slides. However, there have been few methods proposed for statistical analysis of such data. Moreover the lowess correction of the global dye effect is available for only two-color experiments, and even if its application can be derived, it does not allow simultaneous correction of the raw data. Results We propose a two-step normalization procedure for triple-target experiments. First the dye bleeding is evaluated and corrected if necessary. Then the signal in each channel is normalized using a generalized lowess procedure to correct a global dye bias. The normalization procedure is validated using triple-self experiments and by comparing the results of triple-target and two-color experiments. Although the focus is on triple-target microarrays, the proposed method can be used to normalize p differently labelled targets co-hybridized on a same array, for any value of p greater than 2. Conclusion The proposed normalization procedure is effective: the technical biases are reduced, the number of false positives is under control in the analysis of differentially expressed genes, and the triple-target experiments are more powerful than the corresponding two-color experiments. There is room for improving the microarray experiments by simultaneously hybridizing more than two samples.

Abstract Background The initial stages of development depend on mRNA and proteins accumulated in the oocyte, and during these stages, certain genes are essential for fertilization, first cleavage and embryonic genome activation. The aim of this study was first to search for avian oocyte-specific genes using an in silico and a microarray approaches, then to investigate the temporal and spatial dynamics of the expression of some of these genes during follicular maturation and early embryogenesis. Results The in silico approach allowed us to identify 18 chicken homologs of mouse potential oocyte genes found by digital differential display. Using the chicken Affymetrix microarray, we identified 461 genes overexpressed in granulosa cells (GCs) and 250 genes overexpressed in the germinal disc (GD) of the hen oocyte. Six genes were identified using both in silico and microarray approaches. Based on GO annotations, GC and GD genes were differentially involved in biological processes, reflecting different physiological destinations of these two cell layers. Finally we studied the spatial and temporal dynamics of the expression of 21 chicken genes. According to their expression patterns all these genes are involved in different stages of final follicular maturation and/or early embryogenesis in the chicken. Among them, 8 genes (btg4, chkmos, wee, zpA, dazL, cvh, zar1 and ktfn) were preferentially expressed in the maturing occyte and cvh, zar1 and ktfn were also highly expressed in the early embryo. Conclusion We showed that in silico and Affymetrix microarray approaches were relevant and complementary in order to find new avian genes potentially involved in oocyte maturation and/or early embryo development, and allowed the discovery of new potential chicken mature oocyte and chicken granulosa cell markers for future studies. Moreover, detailed study of the expression of some of these genes revealed promising candidates for maternal effect genes in the chicken. Finally, the finding concerning the different state of rRNA compared to that of mRNA during the postovulatory period shed light on some mechanisms through which oocyte to embryo transition occurs in the hen.

Prostate cancer (PCa) immunotherapy has shown limited efficacy so far, even in advanced-stage cancers. The success rate of PCa immunotherapy might be improved by approaches more adapted to the immunobiology of the disease. The objective of this study was to perform a multi-omics analysis to identify immune genes associated with PCa progression to better characterize PCa immunobiology and propose new immunotherapeutic targets. mRNA, miRNA, methylation, copy number aberration, and single nucleotide variant datasets from The Cancer Genome Atlas PRAD cohort were analyzed after filtering for genes associated with immunity. Sparse partial least squares-discriminant analyses were performed to identify features associated with biochemical recurrence (BCR) in each type of omics data. Selected features predicted BCR with a balanced error rate (BER) of 0.20 to 0.51 in single-omics and of 0.05 in multi-omics analyses. Amongst features associated with BCR were genes from the Immunoglobulin Ig-like Receptor (LILR) family which are immune checkpoints with immunotherapeutic potential. Using Multivariate INTegrative (MINT) analysis, the association of five LILR genes with BCR was quantified in a combination of three RNA-seq datasets and confirmed with Kaplan-Meier analysis in both these and in an independent RNA-seq dataset. Finally, immunohistochemistry showed that a high number of LILRB1 positive cells within the tumors predicted long-term adverse outcomes. Thus, tumors characterized by abnormal expression of LILR genes have an elevated risk of recurring after definitive local therapy. The immunotherapeutic potential of these regulators to stimulate the immune response against PCa should be evaluated in pre-clinical models.

Abstract Background Soluble sugars, which play a central role in plant structure and metabolism, are also involved in the responses to a number of stresses, and act as metabolite signalling molecules that activate specific or hormone-crosstalk transduction pathways. The different roles of exogenous sucrose in the tolerance of Arabidopsis thaliana plantlets to the herbicide atrazine and oxidative stress were studied by a transcriptomic approach using CATMA arrays. Results Parallel situations of xenobiotic stress and sucrose-induced tolerance in the presence of atrazine, of sucrose, and of sucrose plus atrazine were compared. These approaches revealed that atrazine affected gene expression and therefore seedling physiology at a much larger scale than previously described, with potential impairment of protein translation and of reactive-oxygen-species (ROS) defence mechanisms. Correlatively, sucrose-induced protection against atrazine injury was associated with important modifications of gene expression related to ROS defence mechanisms and repair mechanisms. These protection-related changes of gene expression did not result only from the effects of sucrose itself, but from combined effects of sucrose and atrazine, thus strongly suggesting important interactions of sucrose and xenobiotic signalling or of sucrose and ROS signalling. Conclusion These interactions resulted in characteristic differential expression of gene families such as ascorbate peroxidases, glutathione-S-transferases and cytochrome P450s, and in the early induction of an original set of transcription factors. These genes used as molecular markers will eventually be of great importance in the context of xenobiotic tolerance and phytoremediation.

Abstract Background Since the finishing of the sequencing of the Arabidopsis thaliana genome, the Arabidopsis community and the annotator centers have been working on the improvement of gene annotation at the structural and functional levels. In this context, we have used the large CATMA resource on the Arabidopsis transcriptome to search for genes missed by different annotation processes. Probes on the CATMA microarrays are specific gene sequence tags (GSTs) based on the CDS models predicted by the Eugene software. Among the 24 576 CATMA v2 GSTs, 677 are in regions considered as intergenic by the TAIR annotation. We analyzed the cognate transcriptome data in the CATMA resource and carried out data-mining to characterize novel genes and improve gene models. Results The statistical analysis of the results of more than 500 hybridized samples distributed among 12 organs provides an experimental validation for 465 novel genes. The hybridization evidence was confirmed by RT-PCR approaches for 88% of the 465 novel genes. Comparisons with the current annotation show that these novel genes often encode small proteins, with an average size of 137 aa. Our approach has also led to the improvement of pre-existing gene models through both the extension of 16 CDS and the identification of 13 gene models erroneously constituted of two merged CDS. Conclusion This work is a noticeable step forward in the improvement of the Arabidopsis genome annotation. We increased the number of Arabidopsis validated genes by 465 novel transcribed genes to which we associated several functional annotations such as expression profiles, sequence conservation in plants, cognate transcripts and protein motifs.

Control of organ morphology is a fundamental feature of living organisms. There is, however, observable variation in organ size and shape within a given genotype. Taking the sepal of Arabidopsis as a model, we investigated whether we can use variability of gene expression alongside variability of organ morphology to identify gene regulatory networks potentially involved in organ size and shape determination. We produced a dataset composed of morphological parameters and genome-wide transcriptome obtained from 27 individual sepals from wild-type plants with nearly identical genetic backgrounds, environment, and developmental stage. Sepals exhibited appreciable variability in both morphology and transcriptome, with response to stimulus genes and cell-wall related genes displaying high variability in expression. We additionally identified five modules of co-expressed genes which correlated significantly with morphology, revealing biologically relevant gene regulatory networks. Interestingly, cell-wall related genes were overrepresented in two of the top three modules. Overall, our work highlights the benefit of using coupled variation in gene expression and phenotype in wild-type plants to shed light on the mechanisms underlying organ size and shape determination. Although causality between gene expression and sepal morphology has not been established, our approach opens the way to informed analysis for mutant characterization and functional studies.

In the context of finite mixture models one considers the problem of classifying as many observations as possible in the classes of interest while controlling the classification error rate in these same classes. Similar to what is done in the framework of statistical test theory, different type I and type II-like classification error rates can be defined, along with their associated optimal rules, where optimality is defined as minimizing type II error rate while controlling type I error rate at some nominal level. It is first shown that finding an optimal classification rule boils down to searching an optimal region in the observation space where to apply the classical Maximum A Posteriori (MAP) rule. Depending on the misclassification rate to be controlled, the shape of the optimal region is provided, along with a heuristic to compute the optimal classification rule in practice. In particular, a multiclass FDR-like optimal rule is defined and compared to the thresholded MAP rules that is used in most applications. It is shown on both simulated and real datasets that the FDR-like optimal rule may be significantly less conservative than the thresholded MAP rule. [ABSTRACT FROM AUTHOR]