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.

Background

Previous loblolly pine (Pinus taeda L.) genetic linkage maps have been based on a variety of DNA polymorphisms, such as AFLPs, RAPDs, RFLPs, and ESTPs, but only a few SSRs (simple sequence repeats), also known as simple tandem repeats or microsatellites, have been mapped in P. taeda. The objective of this study was to integrate a large set of SSR markers from a variety of sources and published cDNA markers into a composite P. taeda genetic map constructed from two reference mapping pedigrees. A dense genetic map that incorporates SSR loci will benefit complete pine genome sequencing, pine population genetics studies, and pine breeding programs. Careful marker annotation using a variety of references further enhances the utility of the integrated SSR map.

Results

The updated P. taeda genetic map, with an estimated genome coverage of 1,515 cM(Kosambi) across 12 linkage groups, incorporated 170 new SSR markers and 290 previously reported SSR, RFLP, and ESTP markers. The average marker interval was 3.1 cM. Of 233 mapped SSR loci, 84 were from cDNA-derived sequences (EST-SSRs) and 149 were from non-transcribed genomic sequences (genomic-SSRs). Of all 311 mapped cDNA-derived markers, 77% were associated with NCBI Pta UniGene clusters, 67% with RefSeq proteins, and 62% with functional Gene Ontology (GO) terms. Duplicate (i.e., redundant accessory) and paralogous markers were tentatively identified by evaluating marker sequences by their UniGene cluster IDs, clone IDs, and relative map positions. The average gene diversity, He, among polymorphic SSR loci, including those that were not mapped, was 0.43 for 94 EST-SSRs and 0.72 for 83 genomic-SSRs. The genetic map can be viewed and queried at http://www.conifergdb.org/pinemap.

Conclusions

Many polymorphic and genetically mapped SSR markers are now available for use in P. taeda population genetics, studies of adaptive traits, and various germplasm management applications. Annotating mapped genes with UniGene clusters and GO terms allowed assessment of redundant and paralogous EST markers and further improved the quality and utility of the genetic map for P. taeda.

Identification of dispersed repetitive elements can be difficult, especially when elements share little or no homology with previously described repeats. Consequently, a growing number of computational tools have been designed to identify repetitive elements in an ab initio manner, i.e. without using prior sequence data. Here we present the results of side-by-side evaluations of six of the most widely used ab initio repeat finding programs. Using sequence from rice chromosome 12, tools were compared with regard to time requirements, ability to find known repeats, utility in identifying potential novel repeats, number and types of repeat elements recognized and compactness of family descriptions. The study reveals profound differences in the utility of the tools with some identifying virtually their entire substrate as repetitive, others making reasonable estimates of repetition, and some missing almost all repeats. Of note, even when tools recognized similar numbers of repeats they often showed marked differences in the nature and number of repeat families identified. Within the context of this comparative study, ReAS and RepeatScout showed the most promise in analysis of sequence reads and assembled genomic regions, respectively. Our results should help biologists identify the program(s), if any, that is best suited for their needs.