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High quality gene models are necessary to expand the molecular and genetic tools available for a target organism, but these are available for only a handful of model organisms that have undergone extensive curation and experimental validation over the course of many years. The majority of gene models present in biological databases today have been identified in draft genome assemblies using automated annotation pipelines that are frequently based on orthologs from distantly related model organisms and usually have minor or major errors. Manual curation is time consuming and often requires substantial expertise, but is instrumental in improving gene model structure and identification. Manual annotation may seem to be a daunting and cost-prohibitive task for small research communities but involving undergraduates in community genome annotation consortiums can be mutually beneficial for both education and improved genomic resources. We outline a workflow for efficient manual annotation driven by a team of primarily undergraduate annotators. This model can be scaled to large teams and includes quality control processes through incremental evaluation. Moreover, it gives students an opportunity to increase their understanding of genome biology and to participate in scientific research in collaboration with peers and senior researchers at multiple institutions. [ABSTRACT FROM AUTHOR]

Diaphorina citri (Hemiptera: Psyllidae), the Asian citrus psyllid, is the insect vector of Ca. Liberibacter asiaticus, the causal agent of citrus greening disease. Sequencing of the D. citri metagenome has been initiated to gain better understanding of the biology of this organism and the potential roles of its bacterial endosymbionts. To corroborate candidate endosymbionts previously identified by rDNA amplification, raw reads from the D. citri metagenome sequence were mapped to reference genome sequences. Results of the read mapping provided the most support for Wolbachia and an enteric bacterium most similar to Salmonella. Wolbachia-derived reads were extracted using the complete genome sequences for four Wolbachia strains. Reads were assembled into a draft genome sequence, and the annotation assessed for the presence of features potentially involved in host interaction. Genome alignment with the complete sequences reveals membership of Wolbachia wDi in supergroup B, further supported by phylogenetic analysis of FtsZ. FtsZ and Wsp phylogenies additionally indicate that the Wolbachia strain in the Florida D. citri isolate falls into a sub-clade of supergroup B, distinct from Wolbachia present in Chinese D. citri isolates, supporting the hypothesis that the D. citri introduced into Florida did not originate from China. [ABSTRACT FROM AUTHOR]

Abstract: In the absence of a complete genome sequence, considerable insight into genome structure can be gained from survey sequencing of genomic DNA. To facilitate high-throughput characterization of genome structure based on shotgun sequence reads, we have developed an automated sequence read classification pipeline (SRCP). The SRCP uses a battery of novel and standard sequence analysis algorithms along with a sophisticated decision tree to place reads into “best fit” functional/descriptive categories. Once “primed” with genomic sequence data, the SRCP also permits estimation of gene/repeat enrichment afforded by reduced-representation sequencing techniques. To our knowledge, the SRCP is the only tool that has been designed to provide a description of a genome or a genome component based on sample sequence reads. In an initial test of the SRCP using sequence data from Sorghum bicolor, it was shown to provide results similar in quality to results generated by manual classification. Although the SRCP is not a replacement for manual sequence characterization, it can provide a rapid, high-quality overview of genome sequence content and facilitate subsequent annotation. The SRCP presumably can be adapted for analysis of any eukaryotic genome. [Copyright &y& Elsevier]

Solanum pimpinellifolium (SP) is the wild progenitor of cultivated tomato. Because of its remarkable stress tolerance and intense flavor, SP has been used as an important germplasm donor in modern tomato breeding. Here, we present a high-quality chromosome-scale genome sequence of SP LA2093. Genome comparison identifies more than 92,000 structural variants (SVs) between LA2093 and the modern cultivar, Heinz 1706. Genotyping these SVs in ~600 representative tomato accessions identifies alleles under selection during tomato domestication, improvement and modern breeding, and discovers numerous SVs overlapping genes known to regulate important breeding traits such as fruit weight and lycopene content. Expression quantitative trait locus (eQTL) analysis detects hotspots harboring master regulators controlling important fruit quality traits, including cuticular wax accumulation and flavonoid biosynthesis, and SVs contributing to these complex regulatory networks. The LA2093 genome sequence and the identified SVs provide rich resources for future research and biodiversity-based breeding. Solanum pimpinellifolium (SP) is the progenitor of cultivated tomato and an important germplasm. Here, the authors assemble SP genome, identify structural variants (SVs) by comparing with modern cultivar, reveal SVs associated with important breeding traits, and detect SVs harboring master regulators of fruit quality traits. [ABSTRACT FROM AUTHOR]

Background DNA in eukaryotic genomes is characterized, and often dominated, by repetitive, non-genic DNA sequences. Initially thought to be non-functional, repeats have been found to influence gene expression and provide diversity to the genome via mutation. Mobile repeat sequences (transposons) have played a prominent role in the evolutionary histories of eukaryotic genomes and their persistence in eukaryotic DNA indicates that they have, on the whole, been evolutionarily advantageous. While there are an increasing number of algorithms that have been developed for discovering novel dispersed repeats, significant analysis of the repeats and their relationships to other genome features will be required before we can truly understand the complex ways in which dispersed repeat sequences contribute to evolutionary fitness. We propose a spatial proximity rule based data mining technique to discover highly fragmented repeat regions for which only the conserved parts are reported by a computational repeat finder. Materials and methods We present an algorithm for mining the coordinates of different families of ab initio identified repetitive regions on chromosomal length DNA sequences to yield proximity relationships between repeat families. Association rule mining is used to compute the statistical significance of the discovered relationships. False positives are screened out by means of Monte Carlo methods. The filtered proximity relationships are in turn used to build graphs in which repeat families correspond to the vertices and the discovered proximity relationships correspond to edges. Connected components are extracted from the graphs to yield sets of related families denoting diverged repeat regions. Results and conclusion We demonstrate that this approach applied to the rice genome can discover annotated repeat regions and can identify novel relationships among repetitive DNA sequences. The novel relationships can be used to detect hitherto unknown repeat regions in sequenced genomes. The approach described can be extended to address and investigate proximity relationships between all annotated elements within a genome including genes, repetitive elements, non-coding RNAs, and regulatory elements. [ABSTRACT FROM AUTHOR]