Increasing temperature can accelerate metabolism, including sugar biosynthesis and transport, but the increase in metabolism is not uniform. For example, the increase in anthocyanin concentration during the ripening phase is not affected as much as the increase in sugar concentration. These responses vary with the cultivar, complicating this kind of analysis even further. Direct studies of temperature effects on Cabernet Sauvignon berry composition also are consistent with our data. In one study, the composition of Cabernet Sauvignon berries was altered substantially for vines grown in phytotrons at 20 or 30 °C temperatures. Cooler temperatures promoted anthocyanin development and malate concentrations and higher temperatures promoted TSS and proline concentrations. In a second study, vines were grown at 20 or 30 °C day temperatures with night temperatures 5 °C cooler than the day. In this study, higher temperatures increased berry volume and veraison started earlier by about 3 to 4 weeks. The authors concluded that warmer temperatures hastened berry development. In a third study, Cabernet Sauvignon berry composition was affected in a similar manner by soil temperatures that differed by 13 °C. TSS concentrations are also affected by light and the vine water status. Light is generally not a factor because there is usually a large enough leaf area and sufficient light levels to saturate this source to sink relationship. Sun-exposed Cabernet Sauvignon berries in the vineyard had higher TSS than shaded berries. This sunlight effect was attributed largely to an increase in berry temperature rather than an increase in the fluence rate perse.
A higher grapevine water status results in larger berry size and lower sugar concentrations and water deficit is known to increase sugar concentrations in Cabernet Sauvignon. However, nft hydroponic system temperature is thought to have the largest effect on sugar concentrations. Other transcriptomic data in the present study indicated that BOD berries were more mature at a lower sugar level than RNO berries. These included the transcript abundance profiles of genes involved in autophagy, auxin and ABA signaling, iron homeostasis and seed development. Many of these DEGs had an accelerated rate of change in BOD berries. While these transcripts are in the skins, they may be influenced by signals coming from the seed. In addition, there was a higher transcript abundance for most genes involved with the circadian clock in BOD berries. PHYB can regulate the circadian clock and PHYB activity is very sensitive to night temperatures ; PHYB reversion is accelerated to the inactive form at warmer temperatures. The inactivity of phytochrome promotes the expression of RVE1, which promotes auxin concentrations and seed dormancy. Thus, all things considered, it is likely that temperature and/or the temperature differentials between day and night significantly contributed to the differences in the rate of berry development and sugar accumulation in the two locations.Determining maturity of grapes is a difficult and error prone process. Reliable markers could aid in the decision of when to harvest the grapes. “Optimum” maturity is a judgement call and will ultimately depend on the winemaker’s or grower’s specific goals or preferences. A combination of empirical factors can be utilized including °Brix, total acidity, berry tasting in the mouth for aroma and tannins, seed color, etc. °Brix or total soluble solids by itself may not be the best marker for berry ripening as it appears to be uncoupled from berry maturity by temperature.
Phenylpropanoid metabolism, including anthocyanin metabolism, is also highly sensitive to both abiotic and biotic stresses and may not be a good indicator of full maturity. Thus, color may not be a good indicator either. Specific developmental signals from the seed or embryo, such as those involved with auxin and ABA signaling, may provide more reliable markers for berry ripening in diverse environments, but will not be useful in seedless grapes. Aromatic compounds may also be reliable markers but they will need to be generic, developmental markers that are not influenced by the environment. This study revealed many genes that are not reliable markers because they were expressed differently in different environments. One candidate marker that is noteworthy is ATG18G . Its transcript abundance increased and was relatively linear with increasing °Brix and these trends were offset at the two locations relative to their level of putative fruit maturity . ATG18G is required for the autophagy process and maybe important during the fruit ripening phase. It was found to be a hub gene in a gene subnetwork associated with fruit ripening and chloroplast degradation. Further testing will be required to know if it is essential for fruit ripening and whether its transcript abundance is influenced by abiotic and biotic stresses in grape berry skins.The ultimate function of a fruit is to produce fully mature seeds in order to reproduce another generation of plants. The ripe berry exhibits multiple traits that signal to other organisms when the fruit is ready for consumption and seed dispersal. In this study, we show that there were large differences in transcript abundance in grape skins in two different locations with different environments, confirming our original hypothesis. We also identified a set of DEGs with common profiles in the two locations.
The observations made in this study provide lists of such genes and generated a large number of hypotheses to be tested in the future. WGCNA was particularly powerful and enhanced our analyses. The transcript abundance during the late stages of berry ripening was very dynamic and may respond to many of the environmental and developmental factors identified in this study. Functional analysis of the genes and GO enrichment analysis were very useful tools to elucidate these factors. Some of the factors identified were temperature, moisture, light and biotic stress. The results of this study indicated that berries still have a “sense of place” during the late stages of berry ripening. Future studies are required to follow up on these observations. It appears that fruit ripening is very malleable. Manipulation of the canopy may offer a powerful lever to adjust gene expression and berry composition, since these parameters are strongly affected by light and temperature.The ability of a genotype to produce different phenotypes as a function of environmental cues is known as phenotypic plasticity . Phenotypic plasticity is considered one of the main processes by which plants, as sessile organisms, can face and adapt to the spatio-temporal variation of environmental factors . Grapevine berries are characterized by high phenotypic plasticity and a genotype can present variability within berries, among berriesin a cluster, and among vines . Berry phenotypic traits, such as the content of sugars, acids, phenolic, anthocyanins, and flavor compounds, are the result of cultivar and environmental influences , and often strong G × E interactions . Although grapevine plasticity in response to environmental conditions and viticulture practices may provide advantages related to the adaptation of a cultivar to specific growing conditions, it may also cause irregular ripening and large inter-seasonal fluctuations , which are undesirable characteristics for wine making . Due to its complex nature, hydroponic nft system the study of phenotypic plasticity is challenging and the mechanisms by which the genes affecting plastic responses operate are poorly characterized . In fact it is often difficult to assess the performance of different phenotypes in different environments . It has been suggested that genetic and epigenetic regulation of gene expression might be at the basis of phenotypic plasticity through the activation of alternative gene pathways or multiple genes . Epigenetics has been proposed as crucial in shaping plant phenotypic plasticity, putatively explaining the rapid and reversible alterations in gene expression in response to environmental changes. This fine-tuning of gene expression can be achieved through DNA methylation, histone modifications and chromatin remodeling . Small non-coding RNAs are ubiquitous and adjustable repressors of gene expression across a broad group of eukaryotic species and are directly involved in controlling, in a sequence specific manner, multiple epigenetic phenomena such as RNA-directed DNA methylation and chromatin remodeling and might play a role in genotype by environment interactions. In plants, small ncRNAs are typically 20–24 nt long RNA molecules and participate in a wide series of biological processes controlling gene expression via transcriptional and post-transcriptional regulation . Moreover, small RNAs have been recently shown to play an important role in plants environmental plasticity . Fruit maturation, the process that starts with fruit-set and ends with fruit ripening , has been largely investigated in fleshy fruits such as tomato and grapevine. These studies highlighted, among others, the vast transcriptomic reprogramming underlying the berry ripening process , the extensive plasticity of berry maturation in the context of a changing environment , and the epigenetic regulatory network which contributes to adjust gene expression to internal and external stimuli . In particular, small RNAs, and especially microRNAs , are involved, among others, in those biological processes governing fruit ripening . In this work, we assessed the role of small ncRNAs in the plasticity of grapevine berries development, by employing next-generation sequencing.
We focused on two cultivars of Vitis vinifera, Cabernet Sauvignon, and Sangiovese, collecting berries at four different developmental stages in three Italian vineyards, diversely located. First, we described the general landscape of small RNAs originated from hotspots present along the genome, examining their accumulation according to cultivars, environments and developmental stages. Subsequently, we analyzed miRNAs, identifying known and novel miRNA candidates and their distribution profiles in the various samples. Based on the in silico prediction of their targets, we suggest the potential involvement of this class of small RNAs in GxE interactions. The results obtained provide insights into the complex molecular machinery that connects the genotype and the environment.Two V. vinifera varieties Sangiovese , a red Italian grape variety, and Cabernet Sauvignon , an international variety, were grown side by side in three different Italian locations, representing traditional areas of Sangiovese cultivation in Italy with a long-standing wine making tradition. In order to reduce factors of variation, the age of the plants , the clone type , the rootstock , the cultivation techniques and the health status were the same among all the locations. Further details on the environmental conditions of the vineyards are provided in Supplementary Figure 1. Berries from four developmental stages were collected in two biological replicates, during the 2011 growing season, for a total of 48 samples . The four sampled stages corresponded to pea size , representing the first stage of berry development in this experimental plan, bunch closure also known as Lag Phase, 19–20 ◦Brix , which corresponds to 50% of sugar accumulation in berries, and harvest , when the berries are fully ripened and the onset of sugar accumulation is over. About 200 berries per each developmental berry stage were sampled from upper, central and lower part of cluster, both from sun exposed and shaded side and split in two biological replicates. Per each vineyard, the berries were collected from about 20 vines selected in a single uniform row and immediately frozen in liquid nitrogen and stored at −80◦C prior to analysis. The libraries were named using the initials of the vineyard where the berries were collected, followed by the initial of the cultivar and the developmental stage. For example, the sample containing berries of Sangiovese, collected in Montalcino at pea size, was named Mont_SG_ps.RNA extraction was performed as described in Kullan et al. . Briefly, total RNA was extracted from 200 mg of ground berries pericarp tissue using 1 ml of Plant RNA Isolation Reagent following manufacturer’s recommendations. The small RNA fraction was isolated from the total RNA using the mirPremier R microRNA Isolation kit and dissolved in DEPC water. All the steps suggested in the technical bulletin for small RNA isolation of plant tissues were followed except the “Filter Lysate” step, which was omitted. The quality and quantity of small RNAs were evaluated by a NanoDrop 1000 spectrometer , and their integrity assessed by an Agilent 2100 Bioanalyzer using a small RNA chip according to the manufacturer’s instructions. Small RNA libraries were prepared using the TruSeq Small RNA Sample Preparation Kit , following all manufacturers’ instructions. The quality of each library was assessed using an Agilent DNA 1000 chip for the Agilent 2100 Bioanalyzer. Libraries were grouped in pools with six libraries each . The pools of libraries were sequenced on an Illumina Hiseq 2000 at IGA Technology Services . The sequencing data were submitted to GEO–NCBI under the accession number GSE85611.