Drought Event Analysis and Projection of Future Precipitation Scenario in Abaya Chamo Sub-Basin, Ethiopia

Monthly observed and future precipitation magnitudes were subjected to statistical trend analysis to examine possible time series behavior. Future precipitation was downscaled from large-scale output through statistical downscaling. The observed and downscaled future precipitation was analyzed for drought events using the Standardized Precipitation Index (SPI) method. In the Abaya Chamo sub-basin, Ethiopia precipitation is explained by below average magnitudes in most of the low land area, characterized by moderate to extreme drought episodes. Nine drought events were discerned during the period of 1988 to 2015, i.e. once in three years, resulting in harvest failure and subsequent food insecurity. The NCEP-NCAR and CanESM2 model predictors were used to statistically downscale the precipitation data. The monthly observed and downscaled precipitation magnitudes were in good agreement. The RCP-2.6, RCP-4.5 and RCP-8.5 long-term future scenarios were computed to evaluate future drought patterns. The mean annual precipitation scenario decreased by 0.2% to 13.7%, 0.5% to 6.4% and 0.1% to 1.3% for the period from 2016 to 2040, 2050s and 2080s respectively. The increase in mean precipitation was projected to be 0.7% to 12.2%, 0.2% to 11.7% and 0.1% to 17.8% for the period from 2016 to 2040, 2050s and 2080s respectively. The present analysis may provide useful information associated to drought events to decision makers and can be used as a basis for future research in this area

Gene coexpression network analysis of fruit transcriptomes uncovers a possible mechanistically distinct class of sugar/acid ratio-associated genes in sweet orange

Background: The ratio of sugars to organic acids, two of the major metabolites in fleshy fruits, has been considered the most important contributor to fruit sweetness. Although accumulation of sugars and acids have been extensively studied, whether plants evolve a mechanism to maintain, sense or respond to the fruit sugar/acid ratio remains a mystery. In a prior study, we used an integrated systems biology tool to identify a group of 39 acid-associated genes from the fruit transcriptomes in four sweet orange varieties (Citrus sinensis L. Osbeck) with varying fruit acidity, Succari (acidless), Bingtang (low acid), and Newhall and Xinhui (normal acid). Results: We reanalyzed the prior sweet orange fruit transcriptome data, leading to the identification of 72 genes highly correlated with the fruit sugar/acid ratio. The majority of these sugar/acid ratio-related genes are predicted to be involved in regulatory functions such as transport, signaling and transcription or encode enzymes involved in metabolism. Surprisingly, only three of these sugar/acid ratio-correlated genes are weakly correlated with sugar level and none of them overlaps with the acid-associated genes. Weighted Gene Coexpression Network Analysis (WGCNA) has revealed that these genes belong to four modules, Blue, Grey, Brown and Turquoise, with the former two modules being unique to the sugar/acid ratio control. Conclusion: Our results indicate that orange fruits contain a possible mechanistically distinct class of genes that may potentially be involved in maintaining fruit sugar/acid ratios and/or responding to the cellular sugar/acid ratio status. Therefore, our analysis of orange transcriptomes provides an intriguing insight into the potentially novel genetic or molecular mechanisms controlling the sugar/acid ratio in fruits

Transcriptome comparison and gene coexpression network analysis provide a systems view of citrus response to ‘Candidatus Liberibacter asiaticus’ infection

Background: Huanglongbing (HLB) is arguably the most destructive disease for the citrus industry. HLB is caused by infection of the bacterium, Candidatus Liberibacter spp. Several citrus GeneChip studies have revealed thousands of genes that are up- or down-regulated by infection with Ca. Liberibacter asiaticus. However, whether and how these host genes act to protect against HLB remains poorly understood. Results: As a first step towards a mechanistic view of citrus in response to the HLB bacterial infection, we performed a comparative transcriptome analysis and found that a total of 21 Probesets are commonly up-regulated by the HLB bacterial infection. In addition, a number of genes are likely regulated specifically at early, late or very late stages of the infection. Furthermore, using Pearson correlation coefficient-based gene coexpression analysis, we constructed a citrus HLB response network consisting of 3,507 Probesets and 56,287 interactions. Genes involved in carbohydrate and nitrogen metabolic processes, transport, defense, signaling and hormone response were overrepresented in the HLB response network and the subnetworks for these processes were constructed. Analysis of the defense and hormone response subnetworks indicates that hormone response is interconnected with defense response. In addition, mapping the commonly up-regulated HLB responsive genes into the HLB response network resulted in a core subnetwork where transport plays a key role in the citrus response to the HLB bacterial infection. Moreover, analysis of a phloem protein subnetwork indicates a role for this protein and zinc transporters or zinc-binding proteins in the citrus HLB defense response. Conclusion: Through integrating transcriptome comparison and gene coexpression network analysis, we have provided for the first time a systems view of citrus in response to the Ca. Liberibacter spp. infection causing HLB