The family Rhizobiaceae contains plant-associated bacteria with critical roles in ecology and agriculture. Within this family, many Rhizobium and Sinorhizobium strains are nitrogen-fixing plant mutualists, while many strains designated as Agrobacterium are plant pathogens. These contrasting lifestyles are primarily dependent on the transmissible plasmids each strain harbors. Members of the Rhizobiaceae also have diverse genome architectures that include single chromosomes, multiple chromosomes, and plasmids of various sizes. Agrobacterium strains have been divided into three biovars, based on physiological and biochemical properties. The genome of a biovar I strain, A. tumefaciens C58, has been previously sequenced. In this study, the genomes of the biovar II strain A. radiobacter K84, a commercially available biological control strain that inhibits certain pathogenic agrobacteria, and the biovar III strain A. vitis S4, a narrow-host-range strain that infects grapes and invokes a hypersensitive response on nonhost plants, were fully sequenced and annotated. Comparison with other sequenced members of the Alphaproteobacteria provides new data on the evolution of multipartite bacterial genomes. Primary chromosomes show extensive conservation of both gene content and order. In contrast, secondary chromosomes share smaller percentages of genes, and conserved gene order is restricted to short blocks. We propose that secondary chromosomes originated from an ancestral plasmid to which genes have been transferred from a progenitor primary chromosome. Similar patterns are observed in select Beta-and Gammaproteobacteria species. Together, these results define the evolution of chromosome architecture and gene content among the Rhizobiaceae and support a generalized mechanism for second-chromosome formation among bacteria.The family Rhizobiaceae (order Rhizobiales) of the Alphaproteobacteria includes the plant pathogens of the genus Agrobacterium and the nitrogen-fixing plant mutualists of the genera Rhizobium and Sinorhizobium. Members house single and multiple chromosome arrangements, linear replicons, and plasmids of various sizes. Genes of pathogenicity, mutualism, and other symbiotic properties are primarily encoded on large transmissible plasmids. Given the promiscuous nature of these elements, different genomic lineages within the Rhizobiaceae exhibit a variety of symbiotic phenotypes that range from pathogenesis to nitrogen-fixing mutualism.Agrobacterium taxonomy and phylogeny display a marked disparity. Empirically, organisms of the genus Agrobacterium are grouped into five species based on the disease phenotype associated with the resident disease-inducing plasmid: A. tumefaciens causes crown gall on dicotyledonous plants, including stone fruit and nut trees; A. rubi causes crown gall on raspberries; A. vitis causes gall formation that is limited to grapes; A. rhizogenes causes hairy root disease; and A. radiobacter is avirulent. An alternative classification scheme

Small RNAs (∼20 to 24 nucleotides) function as naturally occurring molecules critical in developmental pathways in plants and animals [1], [2]. Here we analyze small RNA populations from mature rice grain and seedlings by pyrosequencing. Using a clustering algorithm to locate regions producing small RNAs, we classified hotspots of small RNA generation within the genome. Hotspots here are defined as 1 kb regions within which small RNAs are significantly overproduced relative to the rest of the genome. Hotspots were identified to facilitate characterization of different categories of small RNA regulatory elements. Included in the hotspots, we found known members of 23 miRNA families representing 92 genes, one trans acting siRNA (ta-siRNA) gene, novel siRNA-generating coding genes and phased siRNA generating genes. Interestingly, over 20% of the small RNA population in grain came from a single foldback structure, which generated eight phased 21-nt siRNAs. This is reminiscent of a newly arising miRNA derived from duplication of progenitor genes [3], [4]. Our results provide data identifying distinct populations of small RNAs, including phased small RNAs, in mature grain to facilitate characterization of small regulatory RNA expression in monocot species.

23Small interfering RNAs (siRNAs) and microRNAs (miRNAs) are effector molecules of RNA 24 interference (RNAi), a highly conserved RNA-based gene suppression mechanism in plants, 25 mammals and other eukaryotes. Endogenous RNAi-based gene suppression has been harnessed 26 naturally and through conventional breeding to achieve desired plant phenotypes. The present 27 study demonstrates that endogenous small RNAs, such as siRNAs and miRNAs, are abundant in 28 soybean seeds, corn kernels, and rice grain, plant tissues that are traditionally used for food and 29 feed. Numerous endogenous plant small RNAs were found to have perfect complementarity to 30 human genes as well as those of other mammals. The abundance of endogenous small RNA 31 molecules in grain from safely consumed food and feed crops such as soybean, corn, and rice 32 ACCEPTED MANUSCRIPT 3 and the homology of a number of these dietary small RNAs to human and animal genomes and 1 transcriptomes establishes a history of safe consumption for dietary small RNAs. 2 3 Introduction: 4 RNA-mediated gene regulation (RNA interference, RNAi) is a highly conserved endogenous 5 mechanism for regulation of gene expression in eukaryotes that operates through multiple 6 pathways (Di Serio et al., 2001;Bantounas et al., 2004;Mello and Conte, 2004; Brodersen and 7 Voinnet, 2006;Mallory and Vaucheret, 2006). RNAi plays important roles in development, 8 pathogen defense and disease response in mammals, plants, and insects (Chang and Mendell, 9 2007;Pedersen et al., 2007). RNAi pathways are triggered by small RNAs that are usually 20 to 10 26 nucleotides (nt) long and are represented by diverse classes that differ from each other in their 11 biogenesis such as small interfering RNAs (siRNAs), microRNAs (miRNAs), trans-acting 12 siRNAs and other classes of small RNAs (Brodersen and Voinnet, 2006; Mallory and Vaucheret, 13 2006;Peters and Meister, 2007). The function of these various classes of small RNAs in animal 14 and plant RNAi pathways involves sequence-specific recruitment of the RNA silencing complex 15 to mRNA or DNA, leading to target mRNA cleavage, translational inhibition, or DNA 16 modifications ( Figure 1). Small RNA regulatory networks are highly conserved in plants and 17 animals and are an essential part of endogenous gene regulation. For example, it has been 18 predicted that endogenous miRNAs likely regulate expression of at least one third of all human 19 genes (Lewis et al., 2005). 20 21RNAi has been harnessed in the improvement of several conventional crops including soybean, 22 rice and maize. Soybean varieties that are precursors to those currently cultivated have a dark 23 ACCEPTED MANUSCRIPT 4 pigmentation due to anthocyanin content. Breeders have selected for soybeans with a yellow 1 seed coat attributed to RNAi-mediated suppression of the chalcone synthase gene (Tuteja et al., 2 2004). RNAi has also been attributed to a conventional low-glutelin (seed storage protein) rice 3 variety useful for those who must restrict dietary p...

The outbreak and transmission of disease-causing pathogens are contributing to the unprecedented rate of biodiversity decline. Recent advances in genomics have coalesced into powerful tools to monitor, detect, and reconstruct the role of pathogens impacting wildlife populations. Wildlife researchers are thus uniquely positioned to merge ecological and evolutionary studies with genomic technologies to exploit unprecedented "Big Data" tools in disease research; however, many researchers lack the training and expertise required to use these computationally intensive methodologies. To address this disparity, the inaugural "Genomics of Disease in Wildlife" workshop assembled early to mid-career professionals with expertise across scientific disciplines (e.g., genomics, wildlife biology, veterinary sciences, and conservation management) for training in the application of genomic tools to wildlife disease research. A horizon scanning-like exercise, an activity to identify forthcoming trends and challenges, performed by the workshop participants identified and discussed 5 themes considered to be the most pressing to the application of genomics in wildlife disease research: 1) "Improving communication, " 2) "Methodological and analytical advancements, " 3) "Translation into practice, " 4) "Integrating landscape ecology and genomics, " and 5) "Emerging new questions. " Wide-ranging solutions from the horizon scan were international in scope, itemized both deficiencies and strengths in wildlife genomic initiatives, promoted the use of genomic technologies to unite wildlife and human disease research, and advocated best practices for optimal use of genomic tools in wildlife disease projects. The results offer a glimpse of the potential revolution in human and wildlife disease research possible through multi-disciplinary collaborations at local, regional, and global scales.

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