Pistachio (Pistacia vera L.) is one of the most important commercial nut crops worldwide. It is a salt-tolerant and long-lived tree, with the largest cultivation area in Iran. Climate change and subsequent increased soil salt content have adversely affected the pistachio yield in recent years. However, the lack of genomic/global transcriptomic sequences on P. vera impedes comprehensive researches at the molecular level. Hence, whole transcriptome sequencing is required to gain insight into functional genes and pathways in response to salt stress. RNA sequencing of a pooled sample representing 24 different tissues of two pistachio cultivars with contrasting salinity tolerance under control and salt treatment by Illumina Hiseq 2000 platform resulted in 368,953,262 clean 100 bp paired-ends reads (90 Gb). Following creating several assemblies and assessing their quality from multiple perspectives, we found that using the annotation-based metrics together with the length-based parameters allows an improved assessment of the transcriptome assembly quality, compared to the solely use of the length-based parameters. The generated assembly by Trinity was adopted for functional annotation and subsequent analyses. In total, 29,119 contigs annotated against all of five public databases, including NR, UniProt, TAIR10, KOG and InterProScan. Among 279 KEGG pathways supported by our assembly, we further examined the pathways involved in the plant hormone biosynthesis and signaling as well as those to be contributed to secondary metabolite biosynthesis due to their importance under salinity stress. In total, 11,337 SSRs were also identified, which the most abundant being dinucleotide repeats. Besides, 13,097 transcripts as candidate stress-responsive genes were identified. Expression of some of these genes experimentally validated through quantitative real-time PCR (qRT-PCR) that further confirmed the accuracy of the assembly. From this analysis, the contrasting expression pattern of NCED3 and SOS1 genes were observed between salt-sensitive and salt-tolerant cultivars. This study, as the first report on the whole transcriptome survey of P. vera, provides important resources and paves the way for functional and comparative genomic studies on this major tree to discover the salinity tolerance-related markers and stress response mechanisms for breeding of new pistachio cultivars with more salinity tolerance.

Long non-coding RNAs (lncRNAs) play crucial roles in regulating gene expression in response to plant stresses. Given the importance regulatory roles of lncRNAs, providing methods for predicting the function of these molecules, especially in non-model plants, is strongly demanded by researchers. Here, we constructed a reference sequence for lncRNAs in P. vera (Pistacia vera L.) with 53220 transcripts. In total, we identified 1909 and 2802 salt responsive lncRNAs in Ghazvini, a salt tolerant cultivar, after 6 and 24 h salt treatment, respectively and 1820 lncRNAs in Sarakhs, a salt sensitive cultivar, after 6 h salt treatment. Functional analysis of these lncRNAs by several hybrid methods, revealed that salt responsive NAT-related lncRNAs associated with transcription factors, CERK1, LEA, Laccase genes and several genes involved in the hormone signaling pathways. Moreover, gene ontology (GO) enrichment analysis of salt responsive target genes related to top five selected lncRNAs showed their involvement in the regulation of ATPase, cation transporter, kinase and UDP-glycosyltransferases genes. Quantitative real-time PCR (qRT-PCR) experiment results of lncRNAs, pre-miRNAs and mature miRNAs were in accordance with our RNA-seq analysis. In the present study, a comparative analysis of differentially expressed lncRNAs and microRNA precursors between salt tolerant and sensitive pistachio cultivars provides valuable knowledge on gene expression regulation under salt stress condition.

The tree species, Pistacia vera (P. vera) is an important commercial product that is salt-tolerant and long-lived, with a possible lifespan of over one thousand years. Gene expression analysis is an efficient method to explore the possible regulatory mechanisms underlying these characteristics. Therefore, having the most suitable set of reference genes is required for transcript level normalization under different conditions in P. vera. In the present study, we selected eight widely used reference genes, ACT, EF1α, α-TUB, β-TUB, GAPDH, CYP2, UBQ10, and 18S rRNA. Using qRT-PCR their expression was assessed in 54 different samples of three cultivars of P. vera. The samples were collected from different organs under various abiotic treatments (cold, drought, and salt) across three time points. Several statistical programs (geNorm, NormFinder, and BestKeeper) were applied to estimate the expression stability of candidate reference genes. Results obtained from the statistical analysis were then exposed to Rank aggregation package to generate a consensus gene rank. Based on our results, EF1α was found to be the superior reference gene in all samples under all abiotic treatments. In addition to EF1α, ACT and β-TUB were the second best reference genes for gene expression analysis in leaf and root. We recommended β-TUB as the second most stable gene for samples under the cold and drought treatments, while ACT holds the same position in samples analyzed under salt treatment. This report will benefit future research on the expression profiling of P. vera and other members of the Anacardiaceae family.