A novel pairwise comparison method for in silico discovery of statistically significant cis-regulatory elements in eukaryotic promoter regions: application to Arabidopsis

Rubisco activase A (RcaA) is a central node in overlapping gene network of drought and salinity in Barley (Hordeum vulgare L.) and may contribute to combined stress tolerance

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.

Novel cis-acting regulatory elements in wild Oryza species impart improved rice bran quality by lowering the expression of phospholipase D alpha1 enzyme (OsPLDα1)

Rice bran oil is good quality edible oil, rich in antioxidants and comprised typically of oleic-linoleic type fatty acids. However, presence of a highly lipolytic enzyme Phospholipase D alpha1 (OsPLDα1) increases free fatty acid content in the oil which further leads to stale flavor and rancidity of the oil, making it unfit for human consumption. In this study, we compared the upstream regions of OsPLDα1 orthologs across 34 accessions representing 5 wild Oryza species and 8 cultivars, to uncover sequence variations and identify cis-elements involved in differential transcription of orthologs. Alignment of the upstream sequences to the Nipponbare OsPLDα1 reference sequence revealed the presence of 39 SNPs. Phylogenetic analysis showed that all the selected cultivars and wild species accessions are closely related to the reference except for three accessions of O. rufipogon (IRGC89224, IRGC104425, and IRGC105902). Furthermore, using exon-specific qRT-PCR, OsPLDα1 expression patterns in immature grains indicated significant differences in transcript abundance between the wild species accessions. In comparison to the control, lowest gene expression was observed in IRGC89224 accession (0.20-fold) followed by IRGC105902 (0.26-fold) and IRGC104425 (0.41-fold) accessions. In-silico analysis of the OsPLDα1 promoter revealed that the copy number variations of CGCGBOXAT, GT1CONSENSUS, IBOXCORE, NODCON2GM, OSE2ROOTNODULE, SURECOREATSULTR11, and SORLIP1AT cis-elements play an important role in the transcriptional activities of orthologous genes. Owing to the presence of ARFAT and SEBF elements only in the IRGC89224 accession, which had the lowest gene expression as well, these putative upstream regulatory sequences have been identified as novel cis-elements which may act as repressors in regulating the OsPLDα1 gene expression. The accessions identified with low OsPLDα1 expressions could be further deployed as potential donors of ideal OsPLDα1 allele for transfer of the desired trait into elite rice cultivars.

Genome wide analysis of W-box element in Arabidopsis thaliana reveals TGAC motif with genes down regulated by heat and salinity

To design, synthetic promoters leading to stress-specific induction of a transgene, the study of cis-regulatory elements is of great importance. Cis-regulatory elements play a major role in regulating the gene expression spatially and temporally at the transcriptional level. The present work focuses on one of the important cis-regulatory element, W-box having TGAC as a core motif which serves as a binding site for the members of the WRKY transcription factor family. In the present study, we have analyzed the occurrence frequency of TGAC core motifs for varying spacer lengths (ranging from 0 to 30 base pairs) across the Arabidopsis thaliana genome in order to determine the biological and functional significance of these conserved sequences. Further, the available microarray data was used to determine the role of TGAC motif in abiotic stresses namely salinity, osmolarity and heat. It was observed that TGAC motifs with spacer sequences like TGACCCATTTTGAC and TGACCCATGAATTTTGAC had a significant deviation in frequency and were thought to be favored for transcriptional bindings. The microarray data analysis revealed the involvement of TGAC motif mainly with genes down-regulated under abiotic stress conditions. These results were further confirmed by the transient expression studies with promoter-reporter cassettes carrying TGAC and TGAC-ACGT variant motifs with spacer lengths of 5 and 10.

Non-coding and coding genomic variants distinguish prostate cancer, castration-resistant prostate cancer, familial prostate cancer, and metastatic castration-resistant prostate cancer from each other

A considerable number of deposited variants has provided new possibilities for knowledge discovery in different types of prostate cancer. Here, we analyzed variants located on 3'UTR, 5'UTR, CDs, Intergenic, and Intronic regions in castration-resistant prostate cancer (8496 variants), familial prostate cancer (3241 variants), metastatic castration-resistant prostate cancer (3693 variants), and prostate cancer (16599 variants). Chromosome regions 10p15-p14 and 2p13 were highly enriched (P < 0.00001) for variants located in 3'UTR, 5'UTR, CDs, intergenic, and intronic regions in castration-resistant prostate cancer. In contrast, 10p15-p14, 10q23.3, 12q13.11, 13q12.3, 1q25, and 8p22 regions were enriched (P < 0.001) in familial prostate cancer. In metastatic castration-resistant prostate cancer, 10p15-p14, 10q23.3, 11q22-q23, 14q21.1, and 14q32.13 were highly variant regions (P < 0.001). Chromosome 2 and chromosome 1 hosted many enriched variant regions. AKR1C3, BRCA1, BRCA2, CHGA, CYP19A1, HOXB13, KLK3, and PTEN contained the highest number of 3'UTR, 5'UTR, CDs, Intergenic, and Intronic variants. Network analysis showed that these genes are upstream of important functions including prostate gland development, tumor recurrence, prostate cancer-specific survival, tumor progression, cancer mortality, long-term survival, cancer recurrence, angiogenesis, and AR. Interestingly, all of EGFR, JAK2, NR3C1, PDZD2, and SEMA3C genes had single nucleotide polymorphisms (SNP) in castration-resistant prostate cancer, consistent with high selection pressure on these genes during drug treatment and consequent resistance. High occurrence of variants in 3'UTRs suggests the importance of regulatory variants in different types of prostate cancer; an area that has been neglected compared with coding variants. This study provides a comprehensive overview of genomic regions contributing to different types of prostate cancer.

Unified Transcriptomic Signature of Arbuscular Mycorrhiza Colonization in Roots of Medicago truncatula by Integration of Machine Learning, Promoter Analysis, and Direct Merging Meta-Analysis

Plant root symbiosis with Arbuscular mycorrhizal (AM) fungi improves uptake of water and mineral nutrients, improving plant development under stressful conditions. Unraveling the unified transcriptomic signature of a successful colonization provides a better understanding of symbiosis. We developed a framework for finding the transcriptomic signature of Arbuscular mycorrhiza colonization and its regulating transcription factors in roots of Medicago truncatula. Expression profiles of roots in response to AM species were collected from four separate studies and were combined by direct merging meta-analysis. Batch effect, the major concern in expression meta-analysis, was reduced by three normalization steps: Robust Multi-array Average algorithm, Z-standardization, and quartiling normalization. Then, expression profile of 33685 genes in 18 root samples of Medicago as numerical features, as well as study ID and Arbuscular mycorrhiza type as categorical features, were mined by seven models: RELIEF, UNCERTAINTY, GINI INDEX, Chi Squared, RULE, INFO GAIN, and INFO GAIN RATIO. In total, 73 genes selected by machine learning models were up-regulated in response to AM (Z-value difference > 0.5). Feature weighting models also documented that this signature is independent from study (batch) effect. The AM inoculation signature obtained was able to differentiate efficiently between AM inoculated and non-inoculated samples. The AP2 domain class transcription factor, GRAS family transcription factors, and cyclin-dependent kinase were among the highly expressed meta-genes identified in the signature. We found high correspondence between the AM colonization signature obtained in this study and independent RNA-seq experiments on AM colonization, validating the repeatability of the colonization signature. Promoter analysis of upregulated genes in the transcriptomic signature led to the key regulators of AM colonization, including the essential transcription factors for endosymbiosis establishment and development such as NF-YA factors. The approach developed in this study offers three distinct novel features: (I) it improves direct merging meta-analysis by integrating supervised machine learning models and normalization steps to reduce study-specific batch effects; (II) seven attribute weighting models assessed the suitability of each gene for the transcriptomic signature which contributes to robustness of the signature (III) the approach is justifiable, easy to apply, and useful in practice. Our integrative framework of meta-analysis, promoter analysis, and machine learning provides a foundation to reveal the transcriptomic signature and regulatory circuits governing Arbuscular mycorrhizal symbiosis and is transferable to the other biological settings.