Högskolan i Skövde

Co-occurrence of abiotic stresses, especially drought and salinity, is a natural phenomenon in field conditions and is worse for crop production than any single stress. Nowadays, rigorous methods of meta-analysis and systems biology have made it possible to perform cross-study comparisons of single stress experiments, which can uncover main overlapping mechanisms underlying tolerance to combined stress. In this study, a meta-analysis of RNA-Seq data was conducted to obtain the overlapping gene network of drought and salinity stresses in barley (Hordeum vulgare L.), which identified Rubisco activase A (RcaA) as a hub gene in the dual-stress response. Thereafter, a greenhouse experiment was carried out using two barley genotypes with different abiotic stress tolerance and evaluated several physiochemical properties as well as the expression profile and protein activity of RcaA. Finally, machine learning analysis was applied to uncover relationships among combined stress tolerance and evaluated properties. We identified 441 genes which were differentially expressed under both drought and salinity stress. Results revealed that the photosynthesis pathway and, in particular, the RcaA gene are major components of the dual-stress responsive transcriptome. Comparative physiochemical and molecular evaluations further confirmed that enhanced photosynthesis capability, mainly through regulation of RcaA expression and activity as well as accumulation of proline content, have a significant association with combined drought and salinity stress tolerance in barley. Overall, our results clarify the importance of RcaA in combined stress tolerance and may provide new insights for future investigations. 

Background

Oat is an important crop in North America and northern Europe. In Scandinavia, yields are limited by the fact that oat cannot be used as a winter crop. In order to develop such a crop, more knowledge about mechanisms of cold tolerance in oat is required.

Results

From an oat cDNA library 9792 single-pass EST sequences were obtained. The library was prepared from pooled RNA samples isolated from leaves of four-week old Avena sativa (oat) plants incubated at +4°C for 4, 8, 16 and 32 hours. Exclusion of sequences shorter than 100 bp resulted in 8508 high-quality ESTs with a mean length of 710.7 bp. Clustering and assembly identified a set of 2800 different transcripts denoted the Avena sativa cold induced UniGene set (AsCIUniGene set). Taking advantage of various tools and databases, putative functions were assigned to 1620 (58%) of these genes. Of the remaining 1180 unclassified sequences, 427 appeared to be oat-specific since they lacked any significant sequence similarity (Blast E values > 10-10) to any sequence available in the public databases. Of the 2800 UniGene sequences, 398 displayed significant homology (BlastX E values ≤ 10-10) to genes previously reported to be involved in cold stress related processes. 107 novel oat transcription factors were also identified, out of which 51 were similar to genes previously shown to be cold induced. The CBF transcription factors have a major role in regulating cold acclimation. Four oat CBF sequences were found, belonging to the monocot cluster of DREB family ERF/AP2 domain proteins. Finally in the total EST sequence data (5.3 Mbp) approximately 400 potential SSRs were found, a frequency similar to what has previously been identified in Arabidopsis ESTs.

Conclusion

The AsCIUniGene set will now be used to fabricate an oat biochip, to perform various expression studies with different oat cultivars incubated at varying temperatures, to generate molecular markers and provide tools for various genetic transformation experiments in oat. This will lead to a better understanding of the cellular biology of this important crop and will open up new ways to improve its agronomical properties.

Background

With the advent of microarray technology, it has become feasible to identify virtually all genes in an organism that are induced by developmental or environmental changes. However, relying solely on gene expression data may be of limited value if the aim is to infer the underlying genetic networks. Development of computational methods to combine microarray data with other information sources is therefore necessary. Here we describe one such method.

Results

By means of our method, previously published Arabidopsis microarray data from cold acclimated plants at six different time points, promoter motif sequence data extracted from ~24,000 Arabidopsis promoters and known transcription factor binding sites were combined to construct a putative genetic regulatory interaction network. The inferred network includes both previously characterised and hitherto un-described regulatory interactions between transcription factor (TF) genes and genes that encode other TFs or other proteins. Part of the obtained transcription factor regulatory network is presented here. More detailed information is available in the additional files.

Conclusion

The rule-based method described here can be used to infer genetic networks by combining data from microarrays, promoter sequences and known promoter binding sites. This method should in principle be applicable to any biological system. We tested the method on the cold acclimation process in Arabidopsis and could identify a more complex putative genetic regulatory network than previously described. However, it should be noted that information on specific binding sites for individual TFs were in most cases not available. Thus, gene targets for the entire TF gene families were predicted. In addition, the networks were built solely by a bioinformatics approach and experimental verifications will be necessary for their final validation. On the other hand, since our method highlights putative novel interactions, more directed experiments could now be performed.

Low temperature is a key factor that limits growth and productivity of many important agronomical crops worldwide. Rice (Oryza sativa L.) is negatively affected already at temperatures below +10°C and is therefore denoted as chilling sensitive. However, chilling tolerant rice cultivars exist and can be commercially cultivated at altitudes up to 3,050 meters with temperatures reaching as low as +4°C. In this work, the global transcriptional response to cold stress (+4°C) was studied in the Nepalese highland variety Jumli Marshi (spp. japonica) and 4,636 genes were identified as significantly differentially expressed within 24 hours of cold stress. Comparison with previously published microarray data from one chilling tolerant and two sensitive rice cultivars identified 182 genes differentially expressed (DE) upon cold stress in all four rice cultivars and 511 genes DE only in the chilling tolerant rice. Promoter analysis of the 182 genes suggests a complex cross-talk between ABRE and CBF regulons. Promoter analysis of the 511 genes identified over-represented ABRE motifs but not DRE motifs, suggesting a role for ABA signaling in cold tolerance. Moreover, 2,101 genes were DE in Jumli Marshi alone. By chromosomal localization analysis, 473 of these cold responsive genes were located within 13 different QTLs previously identified as cold associated.

Low-density arrays for quantitative real-time PCR (qPCR) are increasingly being used as an experimental technique for miRNA expression profiling. As with gene expression profiling using microarrays, data from such experiments needs effective analysis methods to produce reliable and high-quality results. In the pre-processing of the data, one crucial analysis step is normalization, which aims to reduce measurement errors and technical variability among arrays that might have arisen during the execution of the experiments. However, there are currently a number of different approaches to choose among and an unsuitable applied method may induce misleading effects, which could affect the subsequent analysis steps and thereby any conclusions drawn from the results. The choice of normalization method is hence an important issue to consider. In this study we present the comparison of a number of data-driven normalization methods for TaqMan low-density arrays for qPCR and different descriptive statistical techniques that can facilitate the choice of normalization method. The performance of the normalization methods was assessed and compared against each other as well as against standard normalization using endogenous controls. The results clearly show that the data-driven methods reduce variation and represent robust alternatives to using endogenous controls.

BACKGROUND: Neuroblastoma (NB) is a childhood neural crest tumor. There are two groups of aggressive NBs, one with MYCN amplification, and another with 11q chromosomal deletion; these chromosomal aberrations are generally mutually exclusive. The DLG2 gene resides in the 11q-deleted region, thus makes it an interesting NB candidate tumor suppressor gene. METHODS: We evaluated the association of DLG2 gene expression in NB with patient outcomes, stage and MYCN status, using online microarray data combining independent NB patient data sets. Functional studies were also conducted using NB cell models and the fruit fly. RESULTS: Using the array data we concluded that higher DLG2 expression was positively correlated to patient survival. We could also see that expression of DLG2 was inversely correlated with MYCN status and tumor stage. Cell proliferation was lowered in both 11q-normal and 11q-deleted NB cells after DLG2 over expression, and increased in 11q-normal NB cells after DLG2 silencing. Higher level of DLG2 increased the percentage of cells in the G2/M phase and decreased the percentage of cells in the G1 phase. We detected increased protein levels of Cyclin A and Cyclin B in fruit fly models either over expressing dMyc or with RNAi-silenced dmDLG, indicating that both events resulted in enhanced cell cycling. Induced MYCN expression in NB cells lowered DLG2 gene expression, which was confirmed in the fly; when dMyc was over expressed, the dmDLG protein level was lowered, indicating a link between Myc over expression and low dmDLG level. CONCLUSION: We conclude that low DLG2 expression level forces cell cycle progression, and that it predicts poor NB patient survival. The low DLG2 expression level could be caused by either MYCN-amplification or 11q-deletion. Video Abstract.

The technology of sequencing expressed sequence tags (ESTs) offers a relatively cheap alternative to whole genome sequencing and has become a valuable resource for gene discovery. The inherent characteristics of ESTs, such as transcript redundancy, low sequence quality and high error rates, require processing of the sequences before any gene prediction can be made. The process includes EST pre-processing, analysis and similarity searches, and the data are generally stored in a database to organise the results and thereby assist the search for interesting genes.

Cold acclimation is a process which increases the freezing tolerance of an organism, after exposure to low, non-freezing temperatures. The acclimation ensures that cold tolerant species can endure harsh winter conditions, by preparing them to sub-zero temperatures. Cold-sensitive plants such as oat and rice have limited abilities to cold acclimate and are therefore easily damaged during winter time.

The development of more tolerant varieties by using biotechnological methods is desirable, since the yields are expected to improve due to a prolonged vegetation period. However, in order to apply such methods, more knowledge about the underlying mechanisms regulating the cold tolerance and acclimation is required. One step in this direction is to analyze gene expression data generated from cold stressed oat (Part I) and rice plants (Part II).

The focus of this thesis is, consequently, analysis of expression profiling data, which was generated using the EST sequencing and cDNA microarray technologies. The results show that both oat and rice are cold responsive,with many of the previously identified cold regulated genes having a counterpart in these species. In rice, however, the response is less dynamic than in the model organism Arabidopsis thaliana and this may explain its inability to fully cold acclimate.

Additionally, the work in this thesis focuses on evaluating if small-scale EST sets can be used for ‘digital-Northern’, in order to identify genes that are involved in the regulation of the cold stress response. The results show that small-scaled EST sets are not optimal for such an analysis, since the method detected only a portion of cold responsive genes represented in the sets. This has to due with the inherent properties of EST data and limitations in the analysis steps of the sequences.

The work also concerns the identification of cis-elements coupled to transcription factors prominent in the regulation of the response. Since cold acclimation is a quantitative trait the response and regulation of cold stress is under combinatorial control of several transcription factors and the results show that this should be taken into account when identifying binding sites.

Low  temperature  is  one  of  the  major  factors  that  adversely affect  crop  yields  by  causing  restraints  on  plant  growth  and productivity.   However,   most   temperate   plants   have   the ability  to  acclimate  to  cooler  temperatures.  Cold  acclimation is  a  process  which  increases  the  freezing  tolerance  of  an organism  after  exposure  to  low,  non-freezing  temperatures. The main trigger is a decrease in temperature levels, but light reduction has also been shown to have an important impact on  acquired  tolerance.  Since  the  lowest  temperatures  are commonly reached during the night hours in winter time and is an annually recurring event, a favorable trait for plants is the possibility of sensing an imminent cold period. Consequently, extensive crosstalk between light- and temperature signaling pathways has been demonstrated and in this review interesting interaction  points  that  have  been  previously  reported  in  the literature are highlighted.

The hippocampus has been shown to have a major role in learning and memory, but also to participate in the regulation of emotions. However, its specific role(s) in memory is still unclear. Hippocampal damage or dysfunction mainly results in memory issues, especially in the declarative memory but, in animal studies, has also shown to lead to hyperactivity and difficulty in inhibiting responses previously taught. The brain structure is affected in neuropathological disorders, such as Alzheimer’s, epilepsy, and schizophrenia, and also by depression and stress. The hippocampus structure is far from mature at birth and undergoes substantial development throughout infant and juvenile life. The aim of this study was to survey genes highly expressed throughout the postnatal period in mouse hippocampus and which have also been linked to an abnormal phenotype through mutational studies to achieve a greater understanding about hippocampal functions during postnatal development. Publicly available gene expression data from C57BL/6 mouse hippocampus was analyzed; from a total of 5 time points (at postnatal day 1, 10, 15, 21, and 30), 547 genes highly expressed in all of these time points were selected for analysis. Highly expressed genes are considered to be of potential biological importance and appear to be multifunctional, and hence any dysfunction in such a gene will most likely have a large impact on the development of abilities during the postnatal and juvenile period. Phenotypic annotation data downloaded from Mouse Genomic Informatics database were analyzed for these genes, and the results showed that many of them are important for proper embryo development and infant survival, proper growth, and increase in body size, as well as for voluntary movement functions, motor coordination, and balance. The results also indicated an association with seizures that have primarily been characterized by uncontrolled motor activity and the development of proper grooming abilities. The complete list of genes and their phenotypic annotation data have been compiled in a file for easy access.

Freezing tolerance in plants is obtained during a period of low non-freezing temperatures before the winter sets on, through a biological process known as cold acclimation. Cold is one of the major stress factors that limits the growth, productivity and distribution of plants, and understanding the mechanism of cold tolerance is therefore important for crop improvement. Expressed sequence tags (EST) analysis is a powerful, economical and time-efficient way of assembling information on the transcriptome. To date, several EST sets have been generated from cold-induced cDNA libraries from several different plant species. In this study we utilize the variation in the frequency of ESTs sampled from different cold-stressed plant libraries, in order to identify genes preferentially expressed in cold in comparison to a number of control sets. The species included in the comparative study are oat (Avena sativa), barley (Hordeum vulgare), wheat (Triticum aestivum), rice (Oryza sativa) and Arabidopsis thaliana. However, in order to get comparable gene expression estimates across multiple species and data sets, we choose to compare the expression of tentative ortholog groups (TOGs) instead of single genes, as in the normal procedure. We consider TOGs as preferentially expressed if they are detected as differentially expressed by a test statistic and up-regulated in comparison to all control sets, and/or uniquely expressed during cold stress, i.e., not present in any of the control sets. The result of this analysis revealed a diverse representation of genes in the different species. In addition, the derived TOGs mainly represent genes that are long-term highly or moderately expressed in response to cold and/or other stresses.

The detection of differentially expressed genes from EST data is of importance for the discovery of potential biological or pharmaceutical targets, especially when studying biological processes in less characterized organisms and where large-scale microarrays are not an option. We present a comparison of five different statistical methods for identifying up-regulated genes through pairwise comparison of EST sets, where one of the sets is generated from a treatment and the other one serves as a control. In addition, we specifically address situations where the sets are relatively small (~2,000– 10,000 ESTs) and may differ in size. The methods were tested on both simulated and experimentally derived data, and compared to a collection of cold stress induced genes identified by microarrays. We found that combining the method pro- posed by Audic and Claverie with Fisher’s exact test and a method based on calculating the difference in relative frequency was the best combination for maximizing the detection of up-regulated genes. We also introduced the use of a flexible cutoff, which takes the size of the EST sets into consideration. This could be considered as an alternative to a static cutoff. Finally, the detected genes showed a low overlap with those identified by microarrays, which indicates, as in previous studies, low overall concordance between the two platforms.

Motivation:Cold acclimation involves a number of different cellularprocesses that together increase the freezing tolerance of anorganism. The DREB1/CBFs are transcription factors (TFs) thatare prominent in the regulation of cold responses in Arabidopsisthaliana, rice and many other crops. We investigated if theexpression of DREB1/CBFs and co-expressed genes relies on combinatorialcontrol by several TFs. Our results support this notion andindicate that methods for studying the regulation of complexcellular processes should include identification of combinationsof motifs, in addition to searching for individual overrepresentedbinding sites.

Introduction

Low temperature is one of the major environmental factors that adversely affect plant growth and yield. Many cereal crops from tropical regions, such as rice, are chilling sensitive and, therefore, are affected already at <10°C. Interestingly, it has been demonstrated that chilling susceptibility varies greatly among rice varieties, which indicates differences in the underlying molecular responses. Understanding these differences is vital for continued development of rational breeding and transgenic strategies for more tolerant varieties. Thus, in this study, we conducted a comparative global gene expression profiling analysis of the chilling tolerant varieties Sijung and Jumli Marshi (spp. Japonica) during early chilling stress (<24 h, 10°C).

Methods and Results

Global gene expression experiments were conducted with Agilent Rice Gene Expression Microarray 4x44K. The analysed results showed that there was a relatively low (percentage or number) overlap in differentially expressed genes in the two varieties and that substantially more genes were up-regulated in Jumli Marshi than in Sijung but the number of down-regulated genes were higher in Sijung. In broad GO annotation terms, the activated response pathways in Sijung and Jumli Marshi were coherent, as a majority of the genes belonged to the catalytic, transcription regulator or transporter activity categories. However, a more detailed analysis revealed essential differences. For example, in Sijung, activation of calcium and phosphorylation signaling pathways, as well as of lipid transporters and exocytosis-related proteins take place very early in the stress response. Such responses can be coupled to processes aimed at strengthening the cell wall and plasma membrane against disruption. On the contrary, in Jumli Marshi, sugar production, detoxification, ROS scavenging, protection of chloroplast translation, and plausibly the activation of the jasmonic acid pathway were the very first response activities. These can instead be coupled to detoxification processes.

Conclusions

Based on the results inferred from this study, we conclude that different, but overlapping, strategies are undertaken by the two varieties to cope with the chilling stress; in Sijung the initial molecular responses seem to be mainly targeted at strengthening the cell wall and plasma membrane, whereas in Jumli Marshi the protection of chloroplast translation and detoxification is prioritized.

Recent research on large scale microarray analysis has explored the use of Relevance Networks to find networks of genes that are associated to each other in gene expression data. In this work, we compare Relevance Networks with other types of clustering methods to test some of the stated advantages of this method. The dataset we used consists of artificial time series of Boolean gene expression values, with the aim of mimicking microarray data, generated from simple artificial genetic networks. By using this dataset, we could not confirm that Relevance Networks based on mutual information perform better than Relevance Networks based on Pearson correlation, partitional clustering or hierarchical clustering, since the results from all methods were very similar. However, all three methods successfully revealed the subsets of co-expressed genes, which is a valuable step in identifying co-regulation.

Clustering of gene expression data and gene network inference from such data has been a major research topic in recent years. In clustering, pairwise measurements are performed when calculating the distance matrix upon which the clustering is based. Pairwise measurements can also be used for gene network inference, by deriving potential interactions above a certain correlation or distance threshold. Our experiments show how interaction networks derived by this simple approach exhibit low—but significant—sensitivity and specificity. We also explore the effects that normalization and prefiltering have on the results of methods for identifying interactions from expression data. Before derivation of interactions or clustering, preprocessing is often performed by applying normalization to rescale the expression profiles and prefiltering where genes that do not appear to contribute to regulation are removed. In this paper, different ways of normalizing in combination with different distance measurements are tested on both unfiltered and prefiltered data, different prefiltering criteria are considered.

Motivation: Automated text analysis is an important tool for facilitating the extraction of knowledge from biomedical abstracts, thereby enabling researchers to build pathway models that integrate and summarize information from a large number of sources. Advanced methods of in-depth analysis of texts using grammar-based approaches developed within the field of computational linguistics must be adapted to the special requirements and challenges posed by biomedical texts, so that these methods can be made available to the bioinformatics and computational biology communities. Results: Our system for automated text analysis and extraction of pathway information is here applied to a set of PubMed abstracts concerning the CBF signaling pathway, which is a key pathway involved in the cold-adaptation response of plants subjected to cold non-freezing temperatures. The system successfully and accurately re-discovers the main features of this pathway, while also pointing to interesting and plausible new hypotheses. The evaluation also reveals a number of issues which will be important targets in the continued development of the system, e.g. the need for an extended lexicon of taxonomic terms and an improved procedure for recognition of sentence boundaries.

MAIN CONCLUSION: Enhanced levels of endogenous melatonin in the root of wheat, mainly through the OMT1 gene, augment the antioxidant system, reestablish redox homeostasis and are associated with combined stress tolerance. A systems biology approach, including a collection of computational analyses and experimental assays, led us to uncover some aspects of a poorly understood phenomenon, namely wheat (Triticum aestivum L.) combined drought and salinity stress tolerance. Accordingly, a cross-study comparison of stress experiments was performed via a meta-analysis of Expressed Sequence Tags (ESTs) data from wheat roots to uncover the overlapping gene network of drought and salinity stresses. Identified differentially expressed genes were functionally annotated by gene ontology enrichment analysis and gene network analysis. Among those genes, O-methyl transferase 1 (OMT1) was highlighted as a more important (hub) gene in the dual-stress response gene network. Afterwards, the potential roles of OMT1 in mediating physiochemical indicators of stress tolerance were investigated in two wheat genotypes differing in abiotic stress tolerance. Regression analysis and correspondence analysis (CA) confirmed that the expression profiles of the OMT1 gene and variations in melatonin content, antioxidant enzyme activities, proline accumulation, H₂O₂ and malondialdehyde (MDA) contents are significantly associated with combined stress tolerance. These results reveal that the OMT1 gene may contribute to wheat combined drought and salinity stress tolerance through augmenting the antioxidant system and re-establishing redox homeostasis, probably via the regulation of melatonin biosynthesis as a master regulator molecule. Our findings provide new insights into the roles of melatonin in wheat combined drought and salinity stress tolerance and suggest a novel plausible regulatory node through the OMT1 gene to improve multiple-stress tolerant crops.

Studying the drought-responsive transcriptome is of high interest as it can serve as a blueprint for stress adaptation strategies. Despite extensive studies in this area, there are still many details to be uncovered, such as the importance of each gene involved in the stress response as well as the relationship between these genes and the physiochemical processes governing stress tolerance. This study was designed to address such important details and to gain insights into molecular responses of barley (Hordeum vulgare L.) to drought stress. To that, we combined RNA-seq data analysis with field and greenhouse drought experiments in a systems biology approach. RNA-sequence analysis identified a total of 665 differentially expressed genes (DEGs) belonging to diverse functional categories. A gene network was derived from the DEGs, which comprised of a total of 131 nodes and 257 edges. Gene network topology analysis highlighted two programmed cell death (PCD) modulating genes, MC1 (metacaspase 1) and TSN1 (Tudor-SN 1), as important (hub) genes in the predicted network. Based on the field trial, a drought-tolerant and a drought-susceptible barley genotype was identified from eight tested cultivars. Identified genotypes exhibited different physiochemical characteristics, including proline content, chlorophyll concentration, percentage of electrolyte leakage and malondialdehyde content as well as expression profiles of MC1 and TSN1 genes. Machine learning and correspondence analysis revealed a significant relationship between drought tolerance and measured characteristics in the context of PCD. Our study provides new insights which bridge barley drought tolerance to PCD through MC1 and TSN1 pathway.

Recognized for its multifaceted functions, melatonin is a hormone found in both animals and plants. In the plant kingdom, it plays diverse roles, regulating growth, development, and stress responses. Notably, melatonin demonstrates its significance by mitigating the effects of abiotic stresses like drought. However, understanding the precise regulatory mechanisms controlling melatonin biosynthesis genes, especially during monocots' response to stresses, requires further exploration. Seeking to understand the molecular basis of drought stress tolerance in wheat, we analyzed RNA-Seq libraries of wheat exposed to drought stress using bioinformatics methods. In light of our findings, we identified that the Myelocytomatosis oncogenes 2 (MYC2) transcription factor is a hub gene upstream of a main melatonin biosynthesis gene, N-acetylserotonin methyltransferase (ASMT), in the wheat drought response-gene network. Promoter analysis of the ASMT gene suggested that it might be a target gene of MYC2. We conducted a set of molecular and physiochemical assays along with robust machine learning approaches to elevate those findings further. MYC2 and ASMT were co-regulated under Jasmonate, drought, and a combination of them in the leaf tissues of wheat was detected. A meaningful correlation was observed among gene expression profiles, melatonin contents, photosynthetic activities, antioxidant enzyme activities, H2O2 levels, and plasma membrane damage. The results indicated an evident relationship between jasmonic acid and the melatonin biosynthesis pathway. Moreover, it seems that the MYC2-ASMT module might contribute to wheat drought tolerance by regulating melatonin contents. 

Melatonin is a master regulator of diverse biological processes, including plant's abiotic stress responses and tolerance. Despite the extensive information on the role of melatonin in response to abiotic stress, how plants regulate endogenous melatonin content under stressful conditions remains largely unknown. In this study, we computationally mined Expressed Sequence Tag (EST) libraries of salinity-exposed Chinese cabbage (Brassica rapa) to identify the most reliable differentially expressed miRNA and its target gene(s). In light of these analyses, we found that miR168a potentially targets a key melatonin biosynthesis gene, namely O-METHYLTRANSFERASE 1 (OMT1). Accordingly, molecular and physiochemical evaluations were performed in a separate salinity experiment using contrasting B. rapa genotypes. Then, the association between B. rapa salinity tolerance and changes in measured molecular and physiochemical characteristics was determined. Results indicated that the expression profiles of miR168a and OMT1 significantly differed between B. rapa genotypes. Moreover, the expression profiles of miR168a and OMT1 significantly correlated with more melatonin content, robust antioxidant activities, and better ion homeostasis during salinity stress. Our results suggest that miR168a plausibly mediates melatonin biosynthesis, mainly through the OMT1 gene, under salinity conditions and thereby contributes to the salinity tolerance of B. rapa. To our knowledge, this is the first report on the role of miR168a and OMT1 in B. rapa salinity response.

Cis regulatory elements (CREs), located within promoter regions, play a significant role in the blueprint for transcriptional regulation of genes. There is a growing interest to study the combinatorial nature of CREs including presence or absence of CREs, the number of occurrences of each CRE, as well as of their order and location relative to their target genes. Comparative promoter analysis has been shown to be a reliable strategy to test the significance of each component of promoter architecture. However, it remains unclear what level of difference in the number of occurrences of each CRE is of statistical significance in order to explain different expression patterns of two genes. In this study, we present a novel statistical approach for pairwise comparison of promoters of Arabidopsis genes in the context of number of occurrences of each CRE within the promoters. First, using the sample of 1000 Arabidopsis promoters, the results of the goodness of fit test and non-parametric analysis revealed that the number of occurrences of CREs in a promoter sequence is Poisson distributed. As a promoter sequence contained functional and non-functional CREs, we addressed the issue of the statistical distribution of functional CREs by analyzing the ChIP-seq datasets. The results showed that the number of occurrences of functional CREs over the genomic regions was determined as being Poisson distributed. In accordance with the obtained distribution of CREs occurrences, we suggested the Audic and Claverie (AC) test to compare two promoters based on the number of occurrences for the CREs. Superiority of the AC test over Chi-square (2 2) and Fisher’s exact tests was also shown, as the AC test was able to detect a higher number of significant CREs. The two case studies on the Arabidopsis genes were performed in order to biologically verify the pairwise test for promoter comparison. Consequently, a number of CREs with significantly different occurrences was identified between the promoters. The results of the pairwise comparative analysis together with the expression data for the studied genes revealed the biological significance of the identified CREs. 

Triticum monococcum has recently drawn the attention of biologists to discover and utilize novel genes and alleles. To explore the molecular features of the genetic network governing floral transition in shoot apical meristem (SAM) of spring growth habit T. monococcum, two expressed sequence tag (EST) libraries containing 3,031 ESTs from vegetative SAM (VS) and 2,647 ESTs from early reproductive SAM (RS) were analyzed. Assembly of ESTs resulted in 2,303 unigenes for VS library (368 contigs and 1,935 singletons) and 1,890 unigenes (337 contigs and 1,553 singletons) for RS library. The 67.05 % of VS unigenes and 66.30 % of RS unigenes showed significant similarity with genes of known, putative and or unknown function, whereas the remaining 32.95 % of the VS unigenes and 33.7 % of RS unigenes displayed no significant match with the public protein database. The 1,064 and 866 unigenes of VS and RS libraries were assigned to functional categories using Pageman ontology tool. Further analysis revealed that the switch from VS to RS caused significant changes in the abundance of unigenes assigned to some functional categories. A total of 37 genes were identified which were significantly differentially expressed between vegetative and reproductive stages of T. monococcum SAM. Investigation of the differentially expressed genes revealed the importance of the genes involved in energy metabolism, ubiquitin/26S proteasome system, polyamines biosynthesis and signaling of reactive oxygen species in SAM differentiation towards floral transition in T. monococcum.

Understanding how plants respond to salinity stress is essential for developing tolerant genotypes, to keep human food secure since it is threaten by climate changes and increasing population worldwide. Barley (Hordeum vulgare) is a crop that possesses various salinity tolerance mechanisms that remain to be explored. In this study, data from an RNA-Seq experiment in barley was analyzed to identify changes in genome activities as well as differentially expressed genes (DEGs) in response to salinity stress. A gene network was predicted among identified DEGs and was subjected to network topology analysis, which resulted in the prediction of a hub gene, namely low expression of osmotically responsive gene 2 (LOS2). LOS2 and its two hierarchical downstream genes, salt-tolerant zinc finger (ZAT10) and ascorbate peroxidase 1 (APX1), were used in a genome-wide association (GWA) survey to confirm their importance. A field experiment was conducted to recognize susceptible and tolerant genotypes among 10 different barley genotypes based on the principle component analysis (PCA) of stress-related indices. In a separate salinity experiment, two of the genotypes were assessed to assign their physiological and biochemical responses as well as to identify expression profiles of LOS2, ZAT10, and APX1. From the results, the activity of the barley genome was significantly altered toward response to stress. In total, 5692 DEGs were identified and the gene network derived from these genes contained 131 nodes and 257 edges. The identified genotypes clearly showed the difference in water status, osmolyte accumulation, cell membrane damages, and ion homeostasis as well as in expression profiles for studied genes during salinity stress. Our results suggest that LOS2 along with the ZAT10 and APX1 genes may serve as an important part of barley salinity stress tolerance pathways. To our knowledge, this is the first report on the role(s) of LOS2 in barley salinity stress tolerance in a gene network system.

Genes coding for drought response element binding (DREB) proteins regulate transcription of a large number of downstream genes involved in the plant response to abiotic stresses. However the regulation of DREB genes themselves is not well understood. Using a bioinformatics approach, we identified the over-represented motifs in promoters of DREB genes of sorghum and rice as compared to all the other promoters in their genomes. Aligned orthologous promoter pairs of sorghum and rice DREBs were then used to identify co-localized motifs from among the over-represented ones, assuming that such motifs were likely to play a regulatory role. Finally the motifs over-represented in sorghum DREBs in comparison to their rice orthologs were identified. Results indicated over-representation of motifs pertaining to calcium, light, sugar, and hormone signaling in the DREB promoters. The co-localized motifs in DREB promoters were mainly those involved in abscisic acid-, light- and calcium-mediated regulation. These motifs along with others pertaining to ethylene signaling were over-represented in sorghum DREB promoters as compared to their orthologs from rice and could possibly contribute to its drought tolerance.  Besides calcium, an integration of abscisic acid, ethylene, auxin and methyl jasmonate signaling was probably involved in regulating expression of the drought response through DREB transcription factors.

Background

Endometrial cancer (EC) is the most frequently diagnosed gynecological malignancy and the fourth most common cancer diagnosis overall among women. As with many other forms of cancer, it has been shown that certain miRNAs are differentially expressed in EC and these miRNAs are believed to play important roles as regulators of processes involved in the development of the disease. With the rapidly growing number of studies of miRNA expression in EC, there is a need to organize the data, combine the findings from experimental studies of EC with information from various miRNA databases, and make the integrated information easily accessible for the EC research community.

Findings

The miREC database is an organized collection of data and information about miRNAs shown to be differentially expressed in EC. The database can be used to map connections between miRNAs and their target genes in order to identify specific miRNAs that are potentially important for the development of EC. The aim of the miREC database is to integrate all available information about miRNAs and target genes involved in the development of endometrial cancer, and to provide a comprehensive, up-to-date, and easily accessible source of knowledge regarding the role of miRNAs in the development of EC. Database URL: http://www.mirecdb.orgwebcite.

Conclusions

Several databases have been published that store information about all miRNA targets that have been predicted or experimentally verified to date. It would be a time-consuming task to navigate between these different data sources and literature to gather information about a specific disease, such as endometrial cancer. The miREC database is a specialized data repository that, in addition to miRNA target information, keeps track of the differential expression of genes and miRNAs potentially involved in endometrial cancer development. By providing flexible search functions it becomes easy to search for EC-associated genes and miRNAs from different starting points, such as differential expression and genomic loci (based on genomic aberrations).

Cancer is a broad term for a wide spectrum of diseases and which involves the alteration in expression levels of several hundreds of genes. As such, the study of the disease from a systems biology point of view becomes rational, as the properties of a system as a whole may be very different from the properties of its individual components. However, understanding a network at the systems level not only requires knowledge about the components of the network, but also the interactions between them.

Here, a systems biology view of the rat PHD finger protein 5A (Phf5a) gene was attempted; a gene previously identified as aberrantly expressed in estrogen dependent endometrial adenocarcinoma tumors from both rat and human. Phf5 ais a highly conserved cysteine rich (C4HC3) zinc finger and such proteins predominantly have a role in chromatin mediated transcriptional regulation. Moreover, PHF5A is a component of the macromolecular complex spliceosome that takes part in pre-mRNA splicing and spliceosome component coding genes have previously been shown to be implicated in various cancer types and suggested to potentially be novel antitumor drugs.

To derive a systems biology view, in this study, a weighted gene network was inferred from a list of genes having correlated expression profiles to Phf5a as nodes, and common transcription factors and microRNAs regulating these genes together with annotation about biological process ontology term(s) and pathway(s) as edge weights. In the inferred network a higher weight indicates more annotation shared between two genes and, hence, the network facilitates the identification of closely interacting genes with Phf5a. The results show that highly weighted edges connect Phf5a to other spliceosome components, but also to genes involved in the metabolism of proteins, proteasome and DNA replication, repair and recombination. The results also link Phf5a to the Myc/Rb/E2F pathway, one of the central pathways associated with cancer. The proposed method for inferring a weighted gene network can easily be applied to other genes and diseases. 

Aromatase is an important enzyme in the local synthesis of oestrogens and its expression has been shown to be increased in breast cancer through the activation of multiple promoters. However, the mechanisms behind this are not yet fully understood. A novel candidate in this context is the transcription factor forkhead box L2 (FOXL2), which has been recognised to be co-expressed with aromatase and transcriptionally active promoter II in developing goat and chicken ovaries. We propose that FOXL2 could be involved in the increased expression of aromatase in breast cancer. We examined FOXL2 and its relation to aromatase in 132 post-menopausal breast cancer patients by immunohistochemistry. Using in silico analysis, we further searched for FOXL2 binding-elements in the aromatase gene promoters. The results demonstrate that FOXL2 is expressed in breast cancer and influences clinical outcome with improved recurrence-free survival in cases with nuclear expression. In a multivariate Cox model, nuclear FOXL2 was a significant prognostic factor in ER-positive patients treated with tamoxifen (HR=0.18, 95% confidence interval (CI)=0.04-0.81, P=0.03). Tumours expressing nuclear FOXL2 were also more likely positive for stromal and/or cytoplasmic aromatase (P=0.03 and P=0.008, respectively). In silico analyses revealed binding elements of FOXL2 in promoters I.3, II and I.7 of the aromatase gene of which promoter I.7 was most significant. In conclusion, this is the first study to report that FOXL2 is expressed in breast cancer and correlates with aromatase as well as with clinical outcome. The results further strengthen a possible binding of FOXL2 to aromatase promoter I.7. Nevertheless, whether FOXL2 is a direct activator of aromatase requires further investigation.