Localization of AtH1.1 and AtHMGB1 at different cell stages detected by immunolabeling.

<p>DAPI staining of chromosome (column 1), EGFP fluorescence signals (column 2), Rhodamine Red-X fluorescence signals (column 3) and DIC image (column 4) of transgenic tobacco BY-2 cells were detected using confocal microscopy. AtH1.1-EGFP interacted with chromosome at different cell stages with fixation (rows 1–3). The interaction between AtHMGB1-EGFP with mitotic chromosomes cannot be detected by both EGFP fluorescence and Rhodamine Red-X immunolabeled fluorescence upon fixation (rows 4–6). White arrow heads indicate the position of the metaphase chromosomes. Only one typical image of each cell stage was shown. Additional images can be found in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135033#pone.0135033.s006" target="_blank">S6</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135033#pone.0135033.s007" target="_blank">S7</a> Figs. Eight images each of the metaphase chromosomes using AtHMGB1 or AtH1.1 antibodies were taken.</p

Localization of AtH1.1 and AtHMGB1 at different cell stages with or without paraformaldehyde fixation.

<p>EGFP signals of living unfixed (columns 1–2) and fixed (columns 3–6) transgenic tobacco BY-2 cells were detected using confocal microscopy. AtH1.1-EGFP interacted with chromosome at different cell stages with or without fixation (rows 1–4). AtHMGB1-EGFP in living cells interacted with chromosomes at different cell stages captured (rows 5–8). However the interaction between AtHMGB1-EGFP with mitotic chromosomes was abolished when the cells were fixed with paraformaldehyde. White arrow heads indicate the position of the metaphase chromosomes. Only one typical image of each cell stage was shown. Additional images can be found in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135033#pone.0135033.s002" target="_blank">S2</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135033#pone.0135033.s005" target="_blank">S5</a> Figs. A total of 10, 8, 9 and 6 metaphase chromosomes images of unfixed AtHMGB1, unfixed AtH1.1, fixed AtHMGB1 and fixed AtH1.1 were taken, respectively.</p

Interphase localization of EGFP tagged AtHMGB and AtH1.1 proteins.

<p>Live transgenic tobacco BY-2 cells expressing free EGFP, AtH1.1-EGFP, AtHMGB1-EGFP, AtHMGB5-EGFP, AtHMGB12-EGFP, and AtHMGB14-EGFP. Confocal microscope was used to study the localization of the EGFP tagged AtHMGB proteins at interphase without fixation. Top row: EGFP signal; middle row: Differential Interference Contrast (DIC); low row: merged image.</p

FRAP analysis of AtH1.1 and AtHMGB1 in prophase nuclei.

<p>(A) FRAP images of AtH1.1-EGFP transgenic BY-2 cells. (B) FRAP recovery curves of AtH1.1-EGFP. (C) FRAP images of AtHMGB1-EGFP transgenic BY-2 cells. (D) FRAP recovery curves of AtHMGB1-EGFP. For (B) and (D), blue lines showed the relative signal of the bleached zones. Bleach started at the 3.39^th second and ended at 3.99^th second. Red lines showed the relative signal of the unbleached zones. Bleaching sites were marked with white arrow heads. Each curve represented the average of 9 and 10 separate FRAPs analysis of AtH1.1 and AtHMGB1, respectively. Error bar: standard error.</p

DataSheet1_Co-crystalization reveals the interaction between AtYchF1 and ppGpp.docx

AtYchF1 is an unconventional G-protein in Arabidopsis thaliana that exhibits relaxed nucleotide-binding specificity. The bindings between AtYchF1 and biomolecules including GTP, ATP, and 26S rRNA have been reported. In this study, we demonstrated the binding of AtYchF1 to ppGpp in addition to the above molecules. AtYchF1 is a cytosolic protein previously reported as a negative regulator of both biotic and abiotic stresses while the accumulation of ppGpp in the cytoplasm induces retarded plant growth and development. By co-crystallization, in vitro pull-down experiments, and hydrolytic biochemical assays, we demonstrated the binding and hydrolysis of ppGpp by AtYchF1. ppGpp inhibits the binding of AtYchF1 to ATP, GTP, and 26S rRNA. The ppGpp hydrolyzing activity of AtYchF1 failed to be activated by AtGAP1. The AtYchF1-ppGpp co-crystal structure suggests that ppGpp might prevent His136 from executing nucleotide hydrolysis. In addition, upon the binding of ppGpp, the conformation between the TGS and helical domains of AtYchF1 changes. Such structural changes probably influence the binding between AtYchF1 and other molecules such as 26S rRNA. Since YchF proteins are conserved among different kingdoms of life, the findings advance the knowledge on the role of AtYchF1 in regulating nucleotide signaling as well as hint at the possible involvement of YchF proteins in regulating ppGpp level in other species.</p

Genotype and Phenotype of 96 Recombinant Inbred Lines

The data files contain the genotypic and phenotypic information of a recombinant inbred (RI) population. This population was obtained by crossing the cultivated Glycine max (C08) with the wild type Glycine soja (W05) was adopted from a previous study (Qi et al., 2014). In our previous research (Qi et al., 2014), a core panel of 96 RI lines was re-sequenced at ~1 X depth to generate high-quality single nucleotide polymorphism (SNP) information. An array of high-quality SNPs were grouped into 2,757 bin markers distributed on the 20 chromosomes. A bin map of 2,992.0 cM in the Kosambi mapping function was generated using the bin markers. Biological nitrogen fixation related phenotypes of the RILs were collected in controlled environment as mentioned in materials and methods

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

<div><p>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. <i>In silico</i> 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 <i>Bic-C2</i>, <i>F-box protein2</i>, and <i>VPS-like</i> gave the best overall performance, together with the commonly used <i>ELF1b</i>. 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.</p></div

Geomeans of ranking values of (A) tissue types, (B) stress treatments, and (C) all samples.

<p>Genes are arranged in descending order of stability from left to right. Commonly used reference genes are marked with asterisk (*).</p

Evaluation of previously reported reference genes and new candidate reference genes.

<p>A boxplot of RNA-Seq data showing the expression levels of 37 previously reported primer sets from 28 known reference genes and 7 new candidate reference genes. The expression level of each target was shown. White boxes: Group 1 RNA-Seq data; Grey boxes: Group 2 RNA-Seq data. Primer sets with multiple targets were marked with brackets. Primer sets marked in red were chosen for RT-qPCR validation.</p

Evaluation of selected reference genes using RNA-Seq data.

<p>* Commonly used reference genes.</p><p>Evaluation of selected reference genes using RNA-Seq data.</p