Small RNAs in Plant Responses to Abiotic Stresses: Regulatory Roles and Study Methods.

To survive under abiotic stresses in the environment, plants trigger a reprogramming of gene expression, by transcriptional regulation or translational regulation, to turn on protective mechanisms. The current focus of research on how plants cope with abiotic stresses has transitioned from transcriptomic analyses to small RNA investigations. In this review, we have summarized and evaluated the current methodologies used in the identification and validation of small RNAs and their targets, in the context of plant responses to abiotic stresses.

QTLs Regulating the Contents of Antioxidants, Phenolics, and Flavonoids in Soybean Seeds Share a Common Genomic Region.

Soybean seeds are a rich source of phenolic compounds, especially isoflavonoids, which are important nutraceuticals. Our study using 14 wild- and 16 cultivated-soybean accessions shows that seeds from cultivated soybeans generally contain lower total antioxidants compared to their wild counterparts, likely an unintended consequence of domestication or human selection. Using a recombinant inbred population resulting from a wild and a cultivated soybean parent and a bin map approach, we have identified an overlapping genomic region containing major quantitative trait loci (QTLs) that regulate the seed contents of total antioxidants, phenolics, and flavonoids. The QTL for seed antioxidant content contains 14 annotated genes based on the Williams 82 reference genome (Gmax1.01). None of these genes encodes functions that are related to the phenylpropanoid pathway of soybean. However, we found three putative Multidrug And Toxic Compound Extrusion (MATE) transporter genes within this QTL and one adjacent to it (GmMATE1-4). Moreover, we have identified non-synonymous changes between GmMATE1 and GmMATE2, and that GmMATE3 encodes an antisense transcript that expresses in pods. Whether the polymorphisms in GmMATE proteins are major determinants of the antioxidant contents, or whether the antisense transcripts of GmMATE3 play important regulatory roles, awaits further functional investigations.

Using RNA-Seq Data to Evaluate Reference Genes Suitable for Gene Expression Studies in Soybean.

Differential gene expression profiles often provide important clues for gene functions. While reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is an important tool, the validity of the results depends heavily on the choice of proper reference genes. In this study, we employed new and published RNA-sequencing (RNA-Seq) datasets (26 sequencing libraries in total) to evaluate reference genes reported in previous soybean studies. In silico PCR showed that 13 out of 37 previously reported primer sets have multiple targets, and 4 of them have amplicons with different sizes. Using a probabilistic approach, we identified new and improved candidate reference genes. We further performed 2 validation tests (with 26 RNA samples) on 8 commonly used reference genes and 7 newly identified candidates, using RT-qPCR. In general, the new candidate reference genes exhibited more stable expression levels under the tested experimental conditions. The three newly identified candidate reference genes Bic-C2, F-box protein2, and VPS-like gave the best overall performance, together with the commonly used ELF1b. It is expected that the proposed probabilistic model could serve as an important tool to identify stable reference genes when more soybean RNA-Seq data from different growth stages and treatments are used.