Results for Adonis and ANOSIM comparing unweighted Unifrac matrix with four categorizations (Course, PhyChem, Location and Season).

<p>The results with p<0.05 are bolded.</p><p>Results for Adonis and ANOSIM comparing unweighted Unifrac matrix with four categorizations (Course, PhyChem, Location and Season).</p

The Source of the River as a Nursery for Microbial Diversity

<div><p>Bacteria are highly diverse and ubiquitous organisms that play a key role as drivers for ecosystem processes. The application of NGS (next-generation sequencing technologies) for 16S analysis has been broadly used for understanding bacterioplankton composition and structure. Most of studies conducted on aquatic ecosystems with 16S NGS have been in seawater and lakes. A few studies using NGS have been conducted in river environments and have suggested the presence of a bacterial seed-bank. We performed 16S highly variable V4 region high-throughput analysis in the Sinos River, which is located in one of most important Brazilian industrial centers. This region has several contrasts in its environmental characteristics, presenting a longitudinal gradient of eutrophication and making it a remarkable study site for observing the dynamics of bacterioplankton. We demonstrated consistent evidence for the existence of a bacterial seed-bank and its longitudinal persistence. Seasonal shifts reinforce the importance of the source of the river in maintaining the bacterial seed-bank that spreads throughout the river. Therefore, the preservation of the source of the river is important not only for hydrologic reasons but also to maintain the microbial composition and the ecological integrity of the river.</p></div

Sinos River course and collection sites.

<p>The Sinos River is located in southern Brazil. 14 sampling sites are indicated moving downstream. The Sinos River is indicated by the rectangles separating it into the upper, middle and lower courses. In addition, the physicochemical groupings are indicated by the rectangles in the lower panel as Set1–4.</p

Archaeal and bacterial diversities.

<p><b>(A)</b> Proportion of reads classified as Euryarchaeota from Domain Archaea. In summer, this phylum increased its representation with increasing eutrophication, and in winter, there is a gradual longitudinal decrease in the abundance of this phylum. <b>(B)</b> Alpha-diversity results using Chao1 for summer and winter. The results show a tendency of greater homogeneity and Chao1 values in the winter than in the summer. <b>(C)</b> Beta-diversity results, using unweighted Unifrac. The analyses were performed independently for the sample groups representing seasons, course and PhyChem classification.</p

Sinos River OTUs analysis and classification.

<p><b>(A)</b> The Venn diagram shows the number of OTUs present in both seasons combined and each season. Blue circles indicate winter, and red indicates summer. In addition, the total number of reads belonging to the OTUs and their correspondent percentage in the total are shown. <b>(B)</b> Table of the most abundant phyla found in the analysis, with their respective proportions in the summer and winter samples. <b>(C)</b> Profile showing the proportion of phyla for each sample in summer (S01-S14) and winter (W01-W14). The profile also represents the proportion grouped along the course of the Sinos River (upper, middle and lower) and PhyChem analysis (Set1–4). Colored profiles correspond to the most abundant phyla presented in (B).</p

Identifying MicroRNAs and Transcript Targets in <i>Jatropha</i> Seeds

<div><p>MicroRNAs, or miRNAs, are endogenously encoded small RNAs that play a key role in diverse plant biological processes. <i>Jatropha curcas</i> L. has received significant attention as a potential oilseed crop for the production of renewable oil. Here, a sRNA library of mature seeds and three mRNA libraries from three different seed development stages were generated by deep sequencing to identify and characterize the miRNAs and pre-miRNAs of <i>J. curcas</i>. Computational analysis was used for the identification of 180 conserved miRNAs and 41 precursors (pre-miRNAs) as well as 16 novel pre-miRNAs. The predicted miRNA target genes are involved in a broad range of physiological functions, including cellular structure, nuclear function, translation, transport, hormone synthesis, defense<b>,</b> and lipid metabolism. Some pre-miRNA and miRNA targets vary in abundance between the three stages of seed development. A search for sequences that produce siRNA was performed, and the results indicated that <i>J. curcas</i> siRNAs play a role in nuclear functions, transport, catalytic processes and disease resistance. This study presents the first large scale identification of <i>J. curcas</i> miRNAs and their targets in mature seeds based on deep sequencing, and it contributes to a functional understanding of these miRNAs.</p></div

Targets of the miRNAs identified in mature seeds of <i>J. curcas</i>.

<p>The percentage (%) of contigs for each Gene Ontology (GO) term is relative to the total number of contigs from each gene category.</p

Raw data from sequencing <i>Jatropha curcas</i> sRNAs.

<p>Raw data from sequencing <i>Jatropha curcas</i> sRNAs.</p

Data from reads of the sRNA database of mature <i>Jatropha curcas</i> seeds filtered with non-coding RNAs.

<p>*Total reads before filtering with non-coding and organellar small RNAs. The small RNAs were clustered according to their origin as follows: ribosome (rRNA), transporter (tRNA), small nuclear (snRNA), small nucleolar (snoRNA), mitochondrial (mtRNA) and chloroplastic (cpRNA).</p

Known miRNA families identified in mature <i>J. curcas</i> seeds.

<p>(<b>A</b>) The total number of miRNA members (isomiRNAs) from each miRNA family. (<b>B</b>) The number of total read counts of each miRNA family.</p