Trifoliate orange, known for its high-quality fruit and tolerance to various biotic and abiotic stressors was compared to rough lemon which historically produces high yield and large fruit that are lacking in flavor. In Chapter 1, I report a detailed analysis of the temporal changes and genotypic differences in gene and miRNA expression in root tissue of different root stocks. To the best of my knowledge, this is the first comparison of root transcriptomes performed in citrus. In Chapter 2, expression data from fruit of trees grafted onto the four different root stocks was assessed. Changes in expression throughout development were linked to fruit quality variation. Additionally, the role of miRNAs in regulating the biological and metabolic processes that were affected in each of these chapters was investigated. The results provide a global examination of the molecular mechanisms underlying graft-induced changes in citrus fruit development and ripening. Citrus is grown in more than 140 countries and is one of the most economically important crops in the world. The total production of citrus in the United States in the 2018 growing season was 6.1 million tons on a total of 679 thousand acres. California produced 58 percent of the United States total, producing 3.6 million tons of citrus on 278 thousand acres. Approximately 75 percent of California’s citrus production is sold to the fresh market opposed to being processed into other commodities, such as juice. Oranges accounted for 64 percent of the total citrus produced in the United States and were valued at $1.8 billion, according to the United States Department of Agriculture. Citrus trees are rarely grown from seed and virtually all commercial citrus is propagated by grafting.
This reduces the juvenile phase,hydroponic gutter allowing for the trees to produce fruit many years earlier than those grown from seed. Root stocks impart certain traits onto the scion and the effects of root stocks can be large. The most significant impacts are on growth and vigor, tree nutrition, stress resistance, and fruit quality. In citrus, phenotypic differences in fruit quality have been well documented. However, understanding of the molecular mechanisms underlying these differences is lacking, especially regulatory mechanisms. Previous studies in apple, grape, sweet cherry, and other fruit crops have examined transcriptome changes in various root stock-scion combinations. In citrus, gene expression profiling has been used to understand root stock effects on growth of trees and responses to biotic and abiotic factors. Many transcriptomic studies have also been performed in citrus to elucidate fruit ripening and development in commonly grown citrus cultivars. To date, none of these reports have linked the genetic effects of citrus root stocks to fruit quality. Fruit growth and development and the mechanisms underlying fruit quality are complex. Signal transduction systems regulate many aspects of fruit ripening32. During citrus development, the ABA-signal pathway may act as a central regulator of ripening, combined with other hormones, including auxin and ethylene. A recent study showed that ABA is a positive regulator of citrus ripening and exogenously applied ABA regulates citrus fruit maturation, suggesting that ABA metabolism plays a crucial role in citrus fruit development and ripening35. Previous studies identified Protein phosphatase 2C family proteins as negative regulators of ABA signaling. PP2C dephosphorylates and inactivates a SNF1-related kinases family 2 protein, which is a positive regulator of ABA-response pathways.
Plants with an inactive form of PP2C were hypersensitive to ABA, causing increased activation of ABA-responsive genes. ABA-signaling response has also been linked with drought-stress tolerance. This study suggested that ABA accumulation is associated with a decrease in relative water content and Romero et al. suggest that ABA increases caused by dehydration upregulate levels of PP2C. Auxin, another phytohormone important for fleshy fruit development, regulates many growth and development processes. The auxin-signaling pathway regulates transcription of hundreds of auxin-inducible genes. Promoters of these auxin-responsive genes contain auxin-responsive elements , which bind the auxin-response factor family of transcription factors. ARF activity is regulated in part by Aux/IAA genes, which are transcriptional repressors of the auxin response. In the absence of auxin, Aux/IAA proteins dimerize with ARFs and recruit corepressors of the TOPLESS family, which in turn recruit chromatin-remodeling proteins that stabilize the repressed state. When auxin is present, it acts as a “glue” between Aux/IAAs and F-box proteins that are part of a ubiquitin protein ligase complex. This causes polyubiquitination and subsequent degradation of Aux/IAAs, which releases its repression, leading to the activation of auxin-regulated genes. Together with ABA and other hormones, auxin regulates several aspects of fruit development, including fruit set, fruit size, and ripening related events. Additionally, prior studies have indicated that small RNAs may play a regulatory role in fruit development and ripening. Small RNAs are a type of single-stranded, non-coding RNA that is typically 20-24 nucleotides in length, of which microRNAs are the most extensively researched class and are known to post-transcriptionally down regulate the expression of target mRNAs through mRNA cleavage or translational inhibition.
In strawberry, miR159 was shown to act as a ripening regulator by targeting a MYB transcription factor, which plays a crucial role in the ripening process51. Several examples of miRNA involvement in fruit development and maturation have been described in a variety of crop species, including apple, grape, peach, blueberry, date palm, and tomato. miRNAs that suppress specific transcription factors that are thought to be regulators of citrus fruit development and ripening have also been identified58. However, the expression profiles of miRNAs in various scion-root stock combinations and their subsequent impact on fruit quality have not yet been evaluated. In this study, trees grafted on four root stocks were chosen from a root stock trial at the University of California, Riverside to assess for various fruit quality traits; Argentina sweet orange, Schaub rough lemon, Carrizo citrange, and Rich 16-6 trifoliate orange. In general, rough lemon root stocks produce the highest yield and fruit size, but fruit is of lower quality, containing lower acidity and lower levels of total soluble solids, also known as the “dilution effect”. On the other hand, trees on trifoliate orange produce smaller, high quality fruit with high yield on often smaller trees. Carrizo citrange root stocks produce intermediate yield with good fruit quality. Sweet orange root stocks produce good quality fruit, but trees are very susceptible to various citrus diseases. An RNA-seq approach was implemented to investigate differences in gene expression in fruit due to genetically varying root stocks,hydroponic nft channel with the aim of identifying genes that could potentially play a role in improvement of fruit quality.
Furthermore, miRNA expression profiles were obtained for each of the root stocks to identify potential regulatory mechanisms associated with their target genes.Fruit were harvested in January at the end of the 2016 growing season when fruit were ripe. Total yield was recorded. Ten fresh fruit per tree were collected and analyzed for the following traits: weight, height, width, rind color, rind texture, peel thickness, internal texture and taste. The juice was then pooled from all ten fruit and percent juice, total titratable acid , and total soluble solids for each pool were calculated at the UC ANR Lind cove Research and Extension Center. The average for each trait of the ten fruit per tree were considered one biological replicate and ten biological replicate trees were sampled for statistical analyses. Statistical differences in fruit quality between fruit from trees on different root stocks were evaluated using an analysis of variance test and Chi-squared test. The differences among treatment means were evaluated by Fisher’s Least Significant Difference test and Duncan’s Multiple Range Test. Data were considered to be statistically significant when P < 0.05.The juice vesicles of three representative fruit per tree from two biological replicates of each of the four root stock genotypes at the four collection time points were subjected to RNA-seq . Samples were ground in liquid nitrogen and total RNA was extracted from ~200 mg tissue using the ZR Plant RNA MiniPrep™ kit per manufacturer’s instructions. An Agilent Bioanalyzer was used to confirm the integrity of the total RNA. The RNA with a RIN value greater than seven qualified for RNA-seq. For messenger RNA-seq, sequencing libraries were created using TruSeq Stranded mRNA Library Preparation Kit according to the manufacturer’s protocol. For small RNA-seq, sequencing libraries were created using TruSeq Small RNA Library Preparation Kit according to the manufacturer’s protocol. Each library was prepared for multiplexing with a unique indexed primer. Quantification of all libraries was performed with Nanodrop and Qubit fluorometer. The library size distribution and quality were measured with an Agilent Bioanalyzer. Multiplexed libraries were sequenced in a single lane on an Illumina NextSeq 500 instrument at the University of California, Riverside Genomics Core facility. An average of 11 samples were sequenced per lane. The data analysis was carried out using the RNA-seq workflow module of the systemPipeR package available on Bioconductor60.
Quality reports were created with the FastQC function. Citrus clementina v 1.0 genome assembly and annotations were downloaded from JGI’s portal . Sequencing reads were then mapped against the Citrus clementina v 1.0 reference genome using the Bowtie2 alignment suite for small RNAs and HISAT2 alignment suite for messenger RNAs. Messenger RNA raw reads were counted in a strand-specific manner. Known miRNA gene coordinates, required for counting, were acquired by downloading all known plant miRNAs from the plant miRNA database, aligning these sequences to the Citrus clementina v 1.0 reference genome using Bowtie2 with perfect alignment, and extracting the alignment coordinates. Small RNA raw reads were then counted at the known miRNA locations using the summarize Overlaps function. Sample-wise correlation analysis was performed using rlog transformed expression values generated by the DESeq2 package. In this study, RNA-seq generated reads that mapped to 19,359, 19,124, 19,336, and 19,374 citrus genes in samples from fruit of trees grafted onto sweet orange, Carrizo citrange, rough lemon, and trifoliate orange root stocks, respectively. With criterium of at least 2-fold difference and a p-value less than 0.05 , a total of 1,633 differentially expressed genes were identified between genotypes at one or more time points . There were 684 genes found to be DE between rough lemon and sweet orange root stocks, 388 DEGs between Carrizo citrange and sweet orange, 361 DEGs between trifoliate orange and sweet orange, 178 DEGs between rough lemon and Carrizo citrange, 395 DEGs between trifoliate orange and Carrizo citrange, and 855 DEGs between trifoliate and rough lemon. None of these DEGs overlapped in all 6 comparisons . The majority of the DEGs were specific to one pairwise comparison, but the largest overlap of was a group of 122 DEGs that were commonly shared between RL-SO, CZ-SO, TF-RL, and TF-CZ. Due to the large number of DEGs observed between fruit grafted onto trifoliate orange and rough lemon root stocks and the fact that the largest phenotypic differences in fruit quality traits were generally seen when comparing fruit grown on these root stocks, we primarily focused on this contrast for the remainder of this study. DEGs uniquely belonging to this comparison are more likely to play a role in the phenotypic changes seen when fruit are grown on trifoliate orange versus rough lemon root stock. Gene Ontology and pathway enrichment analyses were conducted to explore the functions of genes that were DE in trees on different root stocks. GO categorization showed that the molecular function GO terms ‘DNA-binding transcription factor activity’ and ‘transferase activity’ were significantly enriched . Genes associated with photosynthesis and located in the photosynthetic membrane were also enriched . KEGG pathway analysis revealed that genes for plant-hormone signal transduction, carotenoid biosynthesis, and fructose and mannose metabolism were significantly enriched when comparing fruit grown on trifoliate to rough lemon root stocks . The hormone-signaling-related pathway included DEGs involved in auxin, gibberellin , abscisic acid , ethylene , and jasmonic acid signaling . Visualization of fold changes using MapMan software revealed that several genes in the ABA and GA pathways were down-regulated in fruit grown on rough lemon compared to trifoliate root stocks.Many genes involved in other cellular responses, as well as transporters were also DE . To further understand the genetic influence of root stocks on fruit quality, we focused on the expression changes of miRNAs and their target genes.