An annotated genetic map of loblolly pine based on microsatellite and cDNA markers

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, H-e, 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.