Premise of the study: Targeted sequencing using next‐generation sequencing (NGS) platforms offers enormous potential for plant systematics by enabling economical acquisition of multilocus data sets that can resolve difficult phylogenetic problems. However, because discovery of single‐copy nuclear (SCN) loci from NGS data requires both bioinformatics skills and access to high‐performance computing resources, the application of NGS data has been limited.Methods and Results: We developed MarkerMiner 1.0, a fully automated, open‐access bioinformatic workflow and application for discovery of SCN loci in angiosperms. Our new tool identified as many as 1993 SCN loci from transcriptomic data sampled as part of four independent test cases representing marker development projects at different phylogenetic scales.Conclusions: MarkerMiner is an easy‐to‐use and effective tool for discovery of putative SCN loci. It can be run locally or via the Web, and its tabular and alignment outputs facilitate efficient downstream assessments of phylogenetic utility, locus selection, intron‐exon boundary prediction, and primer or probe development.

Next-generation sequencing plays a central role in the characterization and quantification of transcriptomes. Although numerous metrics are purported to quantify the quality of RNA, there have been no large-scale empirical evaluations of the major determinants of sequencing success. We used a combination of existing and newly developed methods to isolate total RNA from 1115 samples from 695 plant species in 324 families, which represents >900 million years of phylogenetic diversity from green algae through flowering plants, including many plants of economic importance. We then sequenced 629 of these samples on Illumina GAIIx and HiSeq platforms and performed a large comparative analysis to identify predictors of RNA quality and the diversity of putative genes (scaffolds) expressed within samples. Tissue types (e.g., leaf vs. flower) varied in RNA quality, sequencing depth and the number of scaffolds. Tissue age also influenced RNA quality but not the number of scaffolds ≥1000 bp. Overall, 36% of the variation in the number of scaffolds was explained by metrics of RNA integrity (RIN score), RNA purity (OD 260/230), sequencing platform (GAIIx vs HiSeq) and the amount of total RNA used for sequencing. However, our results show that the most commonly used measures of RNA quality (e.g., RIN) are weak predictors of the number of scaffolds because Illumina sequencing is robust to variation in RNA quality. These results provide novel insight into the methods that are most important in isolating high quality RNA for sequencing and assembling plant transcriptomes. The methods and recommendations provided here could increase the efficiency and decrease the cost of RNA sequencing for individual labs and genome centers.

Click on the article title to read more.

Premise of the study: Here we present a series of protocols for RNA extraction across a diverse array of plants; we focus on woody, aromatic, aquatic, and other chemically complex taxa.Methods and Results: Ninety‐one taxa were subjected to RNA extraction with three methods presented here: (1) TRIzol/TURBO DNA‐free kits using the manufacturer's protocol with the addition of sarkosyl; (2) a combination method using cetyltrimethylammonium bromide (CTAB) and TRIzol/sarkosyl/TURBO DNA‐free; and (3) a combination of CTAB and QIAGEN RNeasy Plant Mini Kit. Bench‐ready protocols are given.Conclusions: After an iterative process of working with chemically complex taxa, we conclude that the use of TRIzol supplemented with sarkosyl and the TURBO DNA‐free kit is an effective, efficient, and robust method for obtaining RNA from 100 mg of leaf tissue of land plant species (Embryophyta) examined. Our protocols can be used to provide RNA of suitable stability, quantity, and quality for transcriptome sequencing.