Bonnie L Hurwitz

Gramene (www.gramene.org) is a curated resource for genetic, genomic and comparative genomics data for the major crop species, including rice, maize, wheat and many other plant (mainly grass) species. Gramene is an open-source project. All data and software are freely downloadable through the ftp site (ftp.gramene.org/pub/gramene) and available for use without restriction. Gramene's core data types include genome assembly and annotations, other DNA/mRNA sequences, genetic and physical maps/markers, genes, quantitative trait loci (QTLs), proteins, ontologies, literature and comparative mappings. Since our last NAR publication 2 years ago, we have updated these data types to include new datasets and new connections among them. Completely new features include rice pathways for functional annotation of rice genes; genetic diversity data from rice, maize and wheat to show genetic variations among different germplasms; large-scale genome comparisons among Oryza sativa and its wild relatives for evolutionary studies; and the creation of orthologous gene sets and phylogenetic trees among rice, Arabidopsis thaliana, maize, poplar and several animal species (for reference purpose). We have significantly improved the web interface in order to provide a more user-friendly browsing experience, including a dropdown navigation menu system, unified web page for markers, genes, QTLs and proteins, and enhanced quick search functions.

Bacteria and their viruses (phage) are fundamental drivers of many ecosystem processes including global biogeochemistry and horizontal gene transfer. While databases and resources for studying function in uncultured bacterial communities are relatively advanced, many fewer exist for their viral counterparts. The issue is largely technical in that the majority (often 90%) of viral sequences are functionally 'unknown' making viruses a virtually untapped resource of functional and physiological information. Here, we provide a community resource that organizes this unknown sequence space into 27 K high confidence protein clusters using 32 viral metagenomes from four biogeographic regions in the Pacific Ocean that vary by season, depth, and proximity to land, and include some of the first deep pelagic ocean viral metagenomes. These protein clusters more than double currently available viral protein clusters, including those from environmental datasets. Further, a protein cluster guided analysis of functional diversity revealed that richness decreased (i) from deep to surface waters, (ii) from winter to summer, (iii) and with distance from shore in surface waters only. These data provide a framework from which to draw on for future metadata-enabled functional inquiries of the vast viral unknown.

Maize is an important crop species of high genetic diversity. We identified and genotyped several million sequence polymorphisms among 27 diverse maize inbred lines and discovered that the genome was characterized by highly divergent haplotypes and showed 10- to 30-fold variation in recombination rates. Most chromosomes have pericentromeric regions with highly suppressed recombination that appear to have influenced the effectiveness of selection during maize inbred development and may be a major component of heterosis. We found hundreds of selective sweeps and highly differentiated regions that probably contain loci that are key to geographic adaptation. This survey of genetic diversity provides a foundation for uniting breeding efforts across the world and for dissecting complex traits through genome-wide association studies.

Rapid progress in comparative genomics among the grasses has revealed similar gene content and order despite exceptional differences in chromosome size and number. Large- and small-scale genomic variations are of particular interest, especially among cultivated and wild species, as they encode rapidly evolving features that may be important in adaptation to particular environments. We present a genome-wide study of intermediate-sized structural variation (SV) among rice (Oryza sativa) and three of its closest relatives in the genus Oryza (Oryza nivara, Oryza rufipogon and Oryza glaberrima). We computationally identified regional expansions, contractions and inversions in the Oryza species genomes relative to O. sativa by combining data from paired-end clone alignments to the O. sativa reference genome and physical maps. A subset of the computational predictions was validated using a new approach for BAC size determination. The result was a confirmed catalog of 674 expansions (25-38 Mb) and 611 (4-19 Mb) contractions, and 140 putative inversions (14-19 Mb) between the three Oryza species and O. sativa. In the expanded regions unique to O. sativa we found enrichment in transposable elements (TEs): long terminal repeats (LTRs) were randomly located across the chromosomes, and their insertion times corresponded to the date of the A genome radiation. Also, rice-expanded regions contained an over-representation of single-copy genes related to defense factors in the environment. This catalog of confirmed SV in reference to O. sativa provides an entry point for future research in genome evolution, speciation, domestication and novel gene discovery.

Metagenomics promises insight into uncultured microbes across space and time. Yet, the tsunami of low-cost sequencing meant to enable these discoveries is leaving scientists drowning in data. We present Libra, a comparative metagenomics algorithm, that considers genetic distance and microbial abundance simultaneously using a vector-space model, and scales using Apache Hadoop. We compare Libra to other tools to examine effects of data reduction and distance metrics using simulated metagenomes, controlled bacterial mixtures, and metagenomes from the Human Microbiome Project and Tara Oceans Expedition. We show that Libra provides accurate, efficient, and scalable compute for discerning global patterns in microbial ecology.