IMG/M: integrated genome and metagenome comparative data analysis system.

The Integrated Microbial Genomes with Microbiome Samples (IMG/M: https://img.jgi.doe.gov/m/) system contains annotated DNA and RNA sequence data of (i) archaeal, bacterial, eukaryotic and viral genomes from cultured organisms, (ii) single cell genomes (SCG) and genomes from metagenomes (GFM) from uncultured archaea, bacteria and viruses and (iii) metagenomes from environmental, host associated and engineered microbiome samples. Sequence data are generated by DOE's Joint Genome Institute (JGI), submitted by individual scientists, or collected from public sequence data archives. Structural and functional annotation is carried out by JGI's genome and metagenome annotation pipelines. A variety of analytical and visualization tools provide support for examining and comparing IMG/M's datasets. IMG/M allows open access interactive analysis of publicly available datasets, while manual curation, submission and access to private datasets and computationally intensive workspace-based analysis require login/password access to its expert review (ER) companion system (IMG/M ER: https://img.jgi.doe.gov/mer/). Since the last report published in the 2014 NAR Database Issue, IMG/M's dataset content has tripled in terms of number of datasets and overall protein coding genes, while its analysis tools have been extended to cope with the rapid growth in the number and size of datasets handled by the system.

IMG/M 4 version of the integrated metagenome comparative analysis system.

IMG/M (http://img.jgi.doe.gov/m) provides support for comparative analysis of microbial community aggregate genomes (metagenomes) in the context of a comprehensive set of reference genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG/M's data content and analytical tools have expanded continuously since its first version was released in 2007. Since the last report published in the 2012 NAR Database Issue, IMG/M's database architecture, annotation and data integration pipelines and analysis tools have been extended to copewith the rapid growth in the number and size of metagenome data sets handled by the system. IMG/M data marts provide support for the analysis of publicly available genomes, expert review of metagenome annotations (IMG/M ER: http://img.jgi.doe.gov/mer) and Human Microbiome Project (HMP)-specific metagenome samples (IMG/M HMP: http://img.jgi.doe.gov/imgm_hmp).

ProDeGe: a computational protocol for fully automated decontamination of genomes.

Single amplified genomes and genomes assembled from metagenomes have enabled the exploration of uncultured microorganisms at an unprecedented scale. However, both these types of products are plagued by contamination. Since these genomes are now being generated in a high-throughput manner and sequences from them are propagating into public databases to drive novel scientific discoveries, rigorous quality controls and decontamination protocols are urgently needed. Here, we present ProDeGe (Protocol for fully automated Decontamination of Genomes), the first computational protocol for fully automated decontamination of draft genomes. ProDeGe classifies sequences into two classes--clean and contaminant--using a combination of homology and feature-based methodologies. On average, 84% of sequence from the non-target organism is removed from the data set (specificity) and 84% of the sequence from the target organism is retained (sensitivity). The procedure operates successfully at a rate of ~0.30 CPU core hours per megabase of sequence and can be applied to any type of genome sequence.

The standard operating procedure of the DOE-JGI Metagenome Annotation Pipeline (MAP v.4).

The DOE-JGI Metagenome Annotation Pipeline (MAP v.4) performs structural and functional annotation for metagenomic sequences that are submitted to the Integrated Microbial Genomes with Microbiomes (IMG/M) system for comparative analysis. The pipeline runs on nucleotide sequences provided via the IMG submission site. Users must first define their analysis projects in GOLD and then submit the associated sequence datasets consisting of scaffolds/contigs with optional coverage information and/or unassembled reads in fasta and fastq file formats. The MAP processing consists of feature prediction including identification of protein-coding genes, non-coding RNAs and regulatory RNAs, as well as CRISPR elements. Structural annotation is followed by functional annotation including assignment of protein product names and connection to various protein family databases.

Discovery of Novel Plant Interaction Determinants from the Genomes of 163 Root Nodule Bacteria.

Root nodule bacteria (RNB) or "rhizobia" are a type of plant growth promoting bacteria, typified by their ability to fix nitrogen for their plant host, fixing nearly 65% of the nitrogen currently utilized in sustainable agricultural production of legume crops and pastures. In this study, we sequenced the genomes of 110 RNB from diverse hosts and biogeographical regions, and undertook a global exploration of all available RNB genera with the aim of identifying novel genetic determinants of symbiotic association and plant growth promotion. Specifically, we performed a subtractive comparative analysis with non-RNB genomes, employed relevant transcriptomic data, and leveraged phylogenetic distribution patterns and sequence signatures based on known precepts of symbiotic- and host-microbe interactions. A total of 184 protein families were delineated, including known factors for nodulation and nitrogen fixation, and candidates with previously unexplored functions, for which a role in host-interaction, -regulation, biocontrol, and more, could be posited. These analyses expand our knowledge of the RNB purview and provide novel targets for strain improvement in the ultimate quest to enhance plant productivity and agricultural sustainability.

Clusters and superclusters of phased small RNAs in the developing inflorescence of rice.

To address the role of small regulatory RNAs in rice development, we generated a large data set of small RNAs from mature leaves and developing roots, shoots, and inflorescences. Using a spatial clustering algorithm, we identified 36,780 genomic groups of small RNAs. Most consisted of 24-nt RNAs that are expressed in all four tissues and enriched in repeat regions of the genome; 1029 clusters were composed primarily of 21-nt small RNAs and, strikingly, 831 of these contained phased RNAs and were preferentially expressed in developing inflorescences. Thirty-eight of the 24-mer clusters were also phased and preferentially expressed in inflorescences. The phased 21-mer clusters derive from nonprotein coding, nonrepeat regions of the genome and are grouped together into superclusters containing 10-46 clusters. The majority of these 21-mer clusters (705/831) are flanked by a degenerate 22-nt motif that is offset by 12 nt from the main phase of the cluster. Small RNAs complementary to these flanking 22-nt motifs define a new miRNA family, which is conserved in maize and expressed in developing reproductive tissues in both plants. These results suggest that the biogenesis of phased inflorescence RNAs resembles that of tasiRNAs and raise the possibility that these novel small RNAs function in early reproductive development in rice and other monocots.