Contact with poison ivy plants is widely dreaded because they produce a natural product called urushiol that is responsible for allergenic contact delayed-dermatitis symptoms lasting for weeks. For this reason, the catchphrase most associated with poison ivy is “leaves of three, let it be”, which serves the purpose of both identification and an appeal for avoidance. Ironically, despite this notoriety, there is a dearth of specific knowledge about nearly all other aspects of poison ivy physiology and ecology. As a means of gaining a more molecular-oriented understanding of poison ivy physiology and ecology, Next Generation DNA sequencing technology was used to develop poison ivy root and leaf RNA-seq transcriptome resources. De novo assembled transcriptomes were analyzed to generate a core set of high quality expressed transcripts present in poison ivy tissue. The predicted protein sequences were evaluated for similarity to SwissProt homologs and InterProScan domains, as well as assigned both GO terms and KEGG annotations. Over 23,000 simple sequence repeats were identified in the transcriptome, and corresponding oligo nucleotide primer pairs were designed. A pan-transcriptome analysis of existing Anacardiaceae transcriptomes revealed conserved and unique transcripts among these species.

Deoxyribonucleic acid (DNA) methylation is an epigenetic alteration crucial for regulating stress responses. Identifying large-scale DNA methylation at single nucleotide resolution is made possible by whole genome bisulfite sequencing. An essential task following the generation of bisulfite sequencing data is to detect differentially methylated cytosines (DMCs) among treatments. Most statistical methods for DMC detection do not consider the dependency of methylation patterns across the genome, thus possibly inflating type I error. Furthermore, small sample sizes and weak methylation effects among different phenotype categories make it difficult for these statistical methods to accurately detect DMCs. To address these issues, the wavelet-based functional mixed model (WFMM) was introduced to detect DMCs. To further examine the performance of WFMM in detecting weak differential methylation events, we used both simulated and empirical data and compare WFMM performance to a popular DMC detection tool methylKit. Analyses of simulated data that replicated the effects of the herbicide glyphosate on DNA methylation in Arabidopsis thaliana show that WFMM results in higher sensitivity and specificity in detecting DMCs compared to methylKit, especially when the methylation differences among phenotype groups are small. Moreover, the performance of WFMM is robust with respect to small sample sizes, making it particularly attractive considering the current high costs of bisulfite sequencing. Analysis of empirical Arabidopsis thaliana data under varying glyphosate dosages, and the analysis of monozygotic (MZ) twins who have different pain sensitivities—both datasets have weak methylation effects of <1%—show that WFMM can identify more relevant DMCs related to the phenotype of interest than methylKit. Differentially methylated regions (DMRs) are genomic regions with different DNA methylation status across biological samples. DMRs and DMCs are essentially the same concepts, with the only difference being how methylation information across the genome is summarized. If methylation levels are determined by grouping neighboring cytosine sites, then they are DMRs; if methylation levels are calculated based on single cytosines, they are DMCs.

First paragraph: Dodders ( Cuscuta spp.) are obligate parasitic plants that obtain water and nutrients from the stems of host plants via specialized feeding structures called haustoria. Dodder haustoria facilitate bi-directional movement of viruses, proteins, and mRNAs between host and parasite ¹ , but the functional effects of these movements are not clear. Here we show that C. campestris haustoria accumulate high levels of many novel microRNAs (miRNAs) while parasitizing Arabidopsis thaliana hosts. Many of these miRNAs are 22 nts long, a usually rare size of plant miRNA associated with amplification of target silencing through secondary small interfering RNA (siRNA) production ² . Several A. thaliana mRNAs are targeted by C. campestris 22 nt miRNAs during parasitism, resulting in mRNA cleavage, secondary siRNA production, and decreased mRNA accumulation levels. Hosts with mutations in two of the targets supported significantly higher growth of C. campestris. Homologs of target mRNAs from diverse plants also have predicted target sites to induced C. campestris miRNAs, and the same miRNAs are expressed and active against host targets when C. campestris parasitizes a different host, Nicotiana benthamiana . These data show that C. campestris miRNAs act as trans -species regulators of host gene expression, and suggest that they may act as virulence factors during parasitism.