Regulatory mechanisms behind the phenotypic plasticity associated with Setaria italica water deficit tolerance.

Drought is one of the main environmental stresses that negatively impacts vegetative and reproductive yield. Water deficit responses are determined by the duration and intensity of the stress, which, together with plant genotype, will define the chances of plant survival. The metabolic adjustments in response to water deficit are complex and involve gene expression modulation regulated by DNA-binding proteins and epigenetic modifications. This last mechanism may also regulate the activity of transposable elements, which in turn impact the expression of nearby loci. Setaria italica plants submitted to five water deficit regimes were analyzed through a phenotypical approach, including growth, physiological, RNA-seq and sRNA-seq analyses. The results showed a progressive reduction in yield as a function of water deficit intensity associated with signaling pathway modulation and metabolic adjustments. We identified a group of loci that were consistently associated with drought responses, some of which were related to water deficit perception, signaling and regulation. Finally, an analysis of the transcriptome and sRNAome allowed us to identify genes putatively regulated by TE- and sRNA-related mechanisms and an intriguing positive correlation between transcript levels and sRNA accumulation in gene body regions. These findings shed light on the processes that allow S. italica to overcome drought and survive under water restrictive conditions.

The population genetic structure approach adds new insights into the evolution of plant LTR retrotransposon lineages.

Long terminal repeat retrotransposons (LTR-RTs) in plant genomes differ in abundance, structure and genomic distribution, reflecting the large number of evolutionary lineages. Elements within lineages can be considered populations, in which each element is an individual in its genomic environment. In this way, it would be reasonable to apply microevolutionary analyses to understand transposable element (TE) evolution, such as those used to study the genetic structure of natural populations. Here, we applied a Bayesian method to infer genetic structure of populations together with classical phylogenetic and dating tools to analyze LTR-RT evolution using the monocot Setaria italica as a model species. In contrast to a phylogeny, the Bayesian clusterization method identifies populations by assigning individuals to one or more clusters according to the most probabilistic scenario of admixture, based on genetic diversity patterns. In this work, each LTR-RT insertion was considered to be one individual and each LTR-RT lineage was considered to be a single species. Nine evolutionary lineages of LTR-RTs were identified in the S. italica genome that had different genetic structures with variable numbers of clusters and levels of admixture. Comprehensive analysis of the phylogenetic, clusterization and time of insertion data allowed us to hypothesize that admixed elements represent sequences that harbor ancestral polymorphic sequence signatures. In conclusion, application of microevolutionary concepts in genome evolution studies is suitable as a complementary approach to phylogenetic analyses to address the evolutionary history and functional features of TEs.

The genetic architecture of photosynthesis and plant growth-related traits in tomato.

To identify genomic regions involved in the regulation of fundamental physiological processes such as photosynthesis and respiration, a population of Solanum pennellii introgression lines was analyzed. We determined phenotypes for physiological, metabolic, and growth related traits, including gas exchange and chlorophyll fluorescence parameters. Data analysis allowed the identification of 208 physiological and metabolic quantitative trait loci with 33 of these being associated to smaller intervals of the genomic regions, termed BINs. Eight BINs were identified that were associated with higher assimilation rates than the recurrent parent M82. Two and 10 genomic regions were related to shoot and root dry matter accumulation, respectively. Nine genomic regions were associated with starch levels, whereas 12 BINs were associated with the levels of other metabolites. Additionally, a comprehensive and detailed annotation of the genomic regions spanning these quantitative trait loci allowed us to identify 87 candidate genes that putatively control the investigated traits. We confirmed 8 of these at the level of variance in gene expression. Taken together, our results allowed the identification of candidate genes that most likely regulate photosynthesis, primary metabolism, and plant growth and as such provide new avenues for crop improvement.