The correct identification of differentially expressed genes (DEGs) between specific conditions is a key in the understanding phenotypic variation. High-throughput transcriptome sequencing (RNA-Seq) has become the main option for these studies. Thus, the number of methods and softwares for differential expression analysis from RNA-Seq data also increased rapidly. However, there is no consensus about the most appropriate pipeline or protocol for identifying differentially expressed genes from RNA-Seq data. This work presents an extended review on the topic that includes the evaluation of six methods of mapping reads, including pseudo-alignment and quasi-mapping and nine methods of differential expression analysis from RNA-Seq data. The adopted methods were evaluated based on real RNA-Seq data, using qRT-PCR data as reference (gold-standard). As part of the results, we developed a software that performs all the analysis presented in this work, which is freely available at https://github.com/costasilvati/consexpression. The results indicated that mapping methods have minimal impact on the final DEGs analysis, considering that adopted data have an annotated reference genome. Regarding the adopted experimental model, the DEGs identification methods that have more consistent results were the limma+voom, NOIseq and DESeq2. Additionally, the consensus among five DEGs identification methods guarantees a list of DEGs with great accuracy, indicating that the combination of different methods can produce more suitable results. The consensus option is also included for use in the available software.

On the world stage, the increase in temperatures due to global warming is already a reality that has become one of the main challenges faced by the scientific community. Since agriculture is highly dependent on climatic conditions, it may suffer a great impact in the short term if no measures are taken to adapt and mitigate the agricultural system. Plant responses to abiotic stresses have been the subject of research by numerous groups worldwide. Initially, these studies were concentrated on model plants, and, later, they expanded their studies in several economically important crops such as rice, corn, soybeans, coffee, and others. However, agronomic evaluations for the launching of cultivars and the classical genetic improvement process focus, above all, on productivity, historically leaving factors such as tolerance to abiotic stresses in the background. Considering the importance of the impact that abiotic stresses can have on agriculture in the short term, new strategies are currently being sought and adopted in breeding programs to understand the physiological, biochemical, and molecular responses to environmental disturbances in plants of agronomic interest, thus ensuring the world food security. Moreover, integration of these approaches is bringing new insights on breeding. We will discuss how water deficit, high temperatures, and salinity exert effects on plants.

Coffea arabica, an allotetraploid hybrid of Coffea eugenioides and Coffea canephora, is the source of approximately 60% of coffee products worldwide, and its cultivated accessions have undergone several population bottlenecks. We present chromosome-level assemblies of a di-haploid C. arabica accession and modern representatives of its diploid progenitors, C. eugenioides and C. canephora. The three species exhibit largely conserved genome structures between diploid parents and descendant subgenomes, with no obvious global subgenome dominance. We find evidence for a founding polyploidy event 350,000–610,000 years ago, followed by several pre-domestication bottlenecks, resulting in narrow genetic variation. A split between wild accessions and cultivar progenitors occurred ~30.5 thousand years ago, followed by a period of migration between the two populations. Analysis of modern varieties, including lines historically introgressed with C. canephora, highlights their breeding histories and loci that may contribute to pathogen resistance, laying the groundwork for future genomics-based breeding of C. arabica.

Genotypic, developmental, and environmental factors converge to determine the degree of Crassulacean acid metabolism (CAM) expression. To characterize the signaling events controlling CAM expression in young pineapple (Ananas comosus) plants, this photosynthetic pathway was modulated through manipulations in water availability. Rapid, intense, and completely reversible up-regulation in CAM expression was triggered by water deficit, as indicated by the rise in nocturnal malate accumulation and in the expression and activity of important CAM enzymes. During both up- and down-regulation of CAM, the degree of CAM expression was positively and negatively correlated with the endogenous levels of abscisic acid (ABA) and cytokinins, respectively. When exogenously applied, ABA stimulated and cytokinins repressed the expression of CAM. However, inhibition of water deficit-induced ABA accumulation did not block the up-regulation of CAM, suggesting that a parallel, non-ABA-dependent signaling route was also operating. Moreover, strong evidence revealed that nitric oxide (NO) may fulfill an important role during CAM signaling. Up-regulation of CAM was clearly observed in NO-treated plants, and a conspicuous temporal and spatial correlation was also evident between NO production and CAM expression. Removal of NO from the tissues either by adding NO scavenger or by inhibiting NO production significantly impaired ABA-induced up-regulation of CAM, indicating that NO likely acts as a key downstream component in the ABA-dependent signaling pathway. Finally, tungstate or glutamine inhibition of the NO-generating enzyme nitrate reductase completely blocked NO production during ABA-induced up-regulation of CAM, characterizing this enzyme as responsible for NO synthesis during CAM signaling in pineapple plants.

Lipids, including the diterpenes cafestol and kahweol, are key compounds that contribute to the quality of coffee beverages. We determined total lipid content and cafestol and kahweol concentrations in green beans and genotyped 107 Coffea arabica accessions, including wild genotypes from the historical FAO collection from Ethiopia. A genome-wide association study was performed to identify genomic regions associated with lipid, cafestol and kahweol contents and cafestol/kahweol ratio. Using the diploid Coffea canephora genome as a reference, we identified 6,696 SNPs. Population structure analyses suggested the presence of two to three groups (K = 2 and K = 3) corresponding to the east and west sides of the Great Rift Valley and an additional group formed by wild accessions collected in western forests. We identified 5 SNPs associated with lipid content, 4 with cafestol, 3 with kahweol and 9 with cafestol/kahweol ratio. Most of these SNPs are located inside or near candidate genes related to metabolic pathways of these chemical compounds in coffee beans. In addition, three trait-associated SNPs showed evidence of directional selection among cultivated and wild coffee accessions. Our results also confirm a great allelic richness in wild accessions from Ethiopia, especially in accessions originating from forests in the west side of the Great Rift Valley.