MicroRNAs (miRNAs) belong to a class of noncoding, regulatory RNAs that is involved in oncogenesis and shows remarkable tissue specificity. Their potential for tumor classification suggests they may be used in identifying the tissue in which cancers of unknown primary origin arose, a major clinical problem. We measured miRNA expression levels in 400 paraffin-embedded and fresh-frozen samples from 22 different tumor tissues and metastases. We used miRNA microarray data of 253 samples to construct a transparent classifier based on 48 miRNAs. Two-thirds of samples were classified with high confidence, with accuracy >90%. In an independent blinded test-set of 83 samples, overall high-confidence accuracy reached 89%. Classification accuracy reached 100% for most tissue classes, including 131 metastatic samples. We further validated the utility of the miRNA biomarkers by quantitative RT-PCR using 65 additional blinded test samples. Our findings demonstrate the effectiveness of miRNAs as biomarkers for tracing the tissue of origin of cancers of unknown primary origin.

Plants intimately associate with diverse bacteria. Plant-associated (PA) bacteria have ostensibly evolved genes enabling adaptation to the plant environment. However, the identities of such genes are mostly unknown and their functions are poorly characterized. We sequenced 484 genomes of bacterial isolates from roots of Brassicaceae, poplar, and maize. We then compared 3837 bacterial genomes to identify thousands of PA gene clusters. Genomes of PA bacteria encode more carbohydrate metabolism functions and fewer mobile elements than related non-plant associated genomes. We experimentally validated candidates from two sets of PA genes, one involved in plant colonization, the other serving in microbe-microbe competition between PA bacteria. We also identified 64 PA protein domains that potentially mimic plant domains; some are shared with PA fungi and oomycetes. This work expands the genome-based understanding of plant-microbe interactions and provides leads for efficient and sustainable agriculture through microbiome engineering.

In the process of CRISPR adaptation, short pieces of DNA ("spacers") are acquired from foreign elements and integrated into the CRISPR array. It so far remained a mystery how spacers are preferentially acquired from the foreign DNA while the self chromosome is avoided. Here we show that spacer acquisition is replication-dependent, and that DNA breaks formed at stalled replication forks promote spacer acquisition. Chromosomal hotspots of spacer acquisition were confined by Chi sites, which are sequence octamers highly enriched on the bacterial chromosome, suggesting that these sites limit spacer acquisition from self DNA. We further show that the avoidance of "self" is mediated by the RecBCD dsDNA break repair complex. Our results suggest that in E. coli, acquisition of new spacers depends on RecBCD-mediated processing of dsDNA breaks occurring primarily at replication forks, and that the preference for foreign DNA is achieved through the higher density of Chi sites on the self chromosome, in combination with the higher number of forks on the foreign DNA. This model explains the strong preference to acquire spacers from both high copy plasmids and phages.

Over the past decade, high-throughput short-read 16S rRNA gene amplicon sequencing has eclipsed clone-dependent long-read Sanger sequencing for microbial community profiling. The transition to new technologies has provided more quantitative information at the expense of taxonomic resolution with implications for inferring metabolic traits in various ecosystems. We applied single-molecule real-time sequencing for microbial community profiling, generating full-length 16S rRNA gene sequences at high throughput, which we propose to name PhyloTags. We benchmarked and validated this approach using a defined microbial community. When further applied to samples from the water column of meromictic Sakinaw Lake, we show that while community structures at the phylum level are comparable between PhyloTags and Illumina V4 16S rRNA gene sequences (iTags), variance increases with community complexity at greater water depths. PhyloTags moreover allowed less ambiguous classification. Last, a platform-independent comparison of PhyloTags and in silico generated partial 16S rRNA gene sequences demonstrated significant differences in community structure and phylogenetic resolution across multiple taxonomic levels, including a severe underestimation in the abundance of specific microbial genera involved in nitrogen and methane cycling across the Lake's water column. Thus, PhyloTags provide a reliable adjunct or alternative to cost-effective iTags, enabling more accurate phylogenetic resolution of microbial communities and predictions on their metabolic potential.

MicroRNAs (miRNAs) are ∼22-nt long, non-coding RNAs that regulate gene silencing. It is known that many human miRNAs are deregulated in numerous types of tumors. Here we report the sequencing of small RNAs (17–25 nt) from 23 breast, bladder, colon and lung tumor samples using high throughput sequencing. We identified 49 novel miRNA and miR-sized small RNAs. We further validated the expression of 10 novel small RNAs in 31 different types of blood, normal and tumor tissue samples using two independent platforms, namely microarray and RT–PCR. Some of the novel sequences show a large difference in expression between tumor and tumor-adjacent tissues, between different tumor stages, or between different tumor types. We also report the identification of novel small RNA classes in human: highly expressed small RNA derived from Y-RNA and endogenous siRNA. Finally, we identified dozens of new miRNA sequence variants that demonstrate the existence of miRNA-related SNP or post-transcriptional modifications. Our work extends the current knowledge of the tumor small RNA transcriptome and provides novel candidates for molecular biomarkers and drug targets.