Combining Genetic and Transcriptomic Approaches to Identify Transporter-Coding Genes as Likely Responsible for a Repeatable Salt Tolerance QTL in Citrus.

The excessive accumulation of chloride (Cl-) in leaves due to salinity is frequently related to decreased yield in citrus. Two salt tolerance experiments to detect quantitative trait loci (QTLs) for leaf concentrations of Cl-, Na+, and other traits using the same reference progeny derived from the salt-tolerant Cleopatra mandarin (Citrus reshni) and the disease-resistant donor Poncirus trifoliata were performed with the aim to identify repeatable QTLs that regulate leaf Cl- (and/or Na+) exclusion across independent experiments in citrus, as well as potential candidate genes involved. A repeatable QTL controlling leaf Cl- was detected in chromosome 6 (LCl-6), where 23 potential candidate genes coding for transporters were identified using the C. clementina genome as reference. Transcriptomic analysis revealed two important candidate genes coding for a member of the nitrate transporter 1/peptide transporter family (NPF5.9) and a major facilitator superfamily (MFS) protein. Cell wall biosynthesis- and secondary metabolism-related processes appeared to play a significant role in differential gene expression in LCl-6. Six likely gene candidates were mapped in LCl-6, showing conserved synteny in C. reshni. In conclusion, markers to select beneficial Cleopatra mandarin alleles of likely candidate genes in LCl-6 to improve salt tolerance in citrus rootstock breeding programs are provided.

Transcriptomic Insight into the Pollen Tube Growth of Olea europaea L. subsp. europaea Reveals Reprogramming and Pollen-Specific Genes Including New Transcription Factors.

The pollen tube is a key innovation of land plants that is essential for successful fertilisation. Its development and growth have been profusely studied in model organisms, but in spite of the economic impact of olive trees, little is known regarding the genome-wide events underlying pollen hydration and growth in this species. To fill this gap, triplicate mRNA samples at 0, 1, 3, and 6 h of in vitro germination of olive cultivar Picual pollen were analysed by RNA-seq. A bioinformatics R workflow called RSeqFlow was developed contemplating the best practices described in the literature, covering from expression data filtering to differential expression and clustering, to finally propose hub genes. The resulting olive pollen transcriptome consisted of 22,418 reliable transcripts, where 5364 were differentially expressed, out of which 173 have no orthologue in plants and up to 3 of them might be pollen-specific transcription factors. Functional enrichment revealed a deep transcriptional reprogramming in mature olive pollen that is also dependent on protein stability and turnover to allow pollen tube emergence, with many hub genes related to heat shock proteins and F-box-containing proteins. Reprogramming extends to the first 3 h of growth, including processes consistent with studies performed in other plant species, such as global down-regulation of biosynthetic processes, vesicle/organelle trafficking and cytoskeleton remodelling. In the last stages, growth should be maintained from persistent transcripts. Mature pollen is equipped with transcripts to successfully cope with adverse environments, even though the in vitro growth seems to induce several stress responses. Finally, pollen-specific transcription factors were proposed as probable drivers of pollen germination in olive trees, which also shows an overall increased number of pollen-specific gene isoforms relative to other plants.

MangoBase: A Genomics Portal and Gene Expression Atlas for Mangifera indica.

Mango (Mangifera indica L.) (2n = 40) is a member of the Anacardiaceae family, which was domesticated at least 4000 years ago in Asia. Mangoes are delicious fruits with great nutritional value. They are one of the major fruit crops worldwide, cultivated in more than 100 countries, with a production of more than 40 million tons. Recently the genome sequences of several mango varieties have been released, but there are no bioinformatics platforms dedicated to mango genomics and breeding to host mango omics data. Here, we present MangoBase, a web portal dedicated to mango genomics, which provides multiple interactive bioinformatics tools, sequences, and annotations to analyze, visualize, and download omics data related to mango. Additionally, MangoBase includes a gene expression atlas with 12 datasets and 80 experiments representing some of the most significant mango RNA-seq experiments published to this date. These experiments study mango fruit ripening in several cultivars with different pulp firmness and sweetness or peel coloration, and other experiments also study hot water postharvest treatment, infection with C. gloeosporioides, and the main mango tree organ tissues.

OliveAtlas: A Gene Expression Atlas Tool for Olea europaea.

The olive (Olea europaea L.) is an ancient crop of great importance in the Mediterranean basin due to the production of olive oil and table olives, which are important sources of fat and have benefits for human health. This crop is expanding and increasing its production worldwide and five olive genomes have recently been sequenced, representing a wild olive and important cultivars in terms of olive oil production, intensive agriculture, and adaptation to the East Asian climate. However, few bioinformatic and genomic resources are available to assist olive research and breeding, and there are no platforms to query olive gene expression data. Here, we present OliveAtlas, an interactive gene expression atlas for olive with multiple bioinformatics tools and visualization methods, enabling multiple gene comparison, replicate inspection, gene set enrichment, and data downloading. It contains 70 RNA-seq experiments, organized in 10 data sets representing the main olive plant organs, the pollen germination and pollen tube elongation process, and the response to a collection of biotic and abiotic stresses, among other experimental conditions. OliveAtlas is a web tool based on easyGDB with expression data based on the 'Picual' genome reference and gene annotation.