Background Passiflora edulis , known as passion fruit and native to South America, is now widely cultivated throughout southern China for its edible value, medicinal efficacy and ornamental properties. We have developed a cold-tolerant variety of P. edulis (‘Pingtang 1’) that can survive subzero temperatures and is highly adaptable in Karst areas. In this study, cuttings of ‘Pingtang 1’ were cultivated in a limestone (L) rocky desertification area and a sandy dolomite (D) rock desertification area. Changes in nutrient elements in both the soils and plants were revealed in the two plots. Moreover, RNA sequencing (RNA-Seq) was performed to profile the root transcriptomes for further exploration of nutrient adaptative mechanism of Passiflora edulis in Karst regions. Results In this study, a total of, 244,705,162 clean reads were generated from four cDNA libraries and assembled into 84,198 unigenes, of which 56,962 were annotated by publicly available databases. Transcriptome profiles were generated, and 1314 unigenes (531 upregulated and 801 downregulated) were significantly differentially expressed between the L and D root cDNA libraries (L_R and D_R, respectively); these profiles provide a global overview of the gene expression patterns associated with P. edulis adaptability to Karst soils. Most unigenes including a number of differentially expressed genes (DEGs) were involved in nutrient element uptake, utilization, signal regulation. And DEGs enriched in KEGG pathways of plant hormone signal transduction, phenylpropanoid biosynthesis, and biosynthesis of unsaturated fatty acids were significantly expressed. Conclusion These results could contribute to better understanding the adaptation of this species to environmental stress and thus enhance the potential for successfully introducing and commercially deploying P. edulis . Electronic supplementary material The online version of this article (10.1186/s12870-019-1797-8) contains supplementary material, which is available to authorized users.

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Xylem is required for the growth and development of higher plants to provide water and mineral elements. The thickening of the xylem secondary cell wall (SCW) not only improves plant survival, but also provides raw materials for industrial production. Numerous studies have found that transcription factors and non-coding RNAs regulate the process of SCW thickening. Pinus massoniana is an important woody tree species in China and is widely used to produce materials for construction, furniture, and packaging. However, the target genes of microRNAs (miRNAs) in the developing xylem of P. massoniana are not known. In this study, a total of 25 conserved miRNAs and 173 novel miRNAs were identified via small RNA sequencing, and 58 differentially expressed miRNAs were identified between the developing xylem (PM_X) and protoplasts isolated from the developing xylem (PM_XP); 26 of these miRNAs were significantly up-regulated in PM_XP compared with PM_X, and 32 were significantly down-regulated. A total of 153 target genes of 20 conserved miRNAs and 712 target genes of 113 novel miRNAs were verified by degradome sequencing. There may be conserved miRNA-mRNA modules (miRNA-MYB, miRNA-ARF, and miRNA-LAC) involved in softwood and hardwood formation. The results of qRT-PCR-based parallel validation were in relatively high agreement. This study explored the potential regulatory network of miRNAs in the developing xylem of P. massoniana and provides new insights into wood formation in coniferous species.

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Single nucleotide polymorphism (SNP) is one of the most widely used molecular markers to help researchers understand the relationship between phenotypes and genotypes. SNP calling mainly consists of two steps, including read alignment and locus identification based on statistical models, and various software have been developed and applied in this issue. Meanwhile, in our study, very low agreement (<25%) was found among the prediction results generated by different software, which was much less consistent than expected. In order to obtain the optimal protocol of SNP mining in tree species, the algorithm principles of different alignment and SNP mining software were discussed in detail. And the prediction results were further validated based on in silico and experimental methods. In addition, hundreds of validated SNPs were provided along with some practical suggestions on program selection and accuracy improvement were provided, and we wish that these results could lay the foundation for the subsequent analysis of SNP mining.