Sharing and archiving nucleic acid structure mapping data.

Nucleic acids are particularly amenable to structural characterization using chemical and enzymatic probes. Each individual structure mapping experiment reveals specific information about the structure and/or dynamics of the nucleic acid. Currently, there is no simple approach for making these data publically available in a standardized format. We therefore developed a standard for reporting the results of single nucleotide resolution nucleic acid structure mapping experiments, or SNRNASMs. We propose a schema for sharing nucleic acid chemical probing data that uses generic public servers for storing, retrieving, and searching the data. We have also developed a consistent nomenclature (ontology) within the Ontology of Biomedical Investigations (OBI), which provides unique identifiers (termed persistent URLs, or PURLs) for classifying the data. Links to standardized data sets shared using our proposed format along with a tutorial and links to templates can be found at http://snrnasm.bio.unc.edu.

QTL analysis of heterostyly in Primula sieboldii and its application for morph identification in wild populations.

BACKGROUND AND AIMS: Primula sieboldii is a perennial clonal herb that is distributed around the Sea of Japan and is endangered in Japan. Its breeding system is characterized by heteromorphic self-incompatibility, and the morph ratio within a population is very important for reproductive success. The aims of this study were to construct a linkage map, map the S locus as a qualitative trait and quantitative trait loci (QTLs) for floral morphological traits related to heterostyly, and predict the morph type in wild populations by using molecular markers for devising a conservation strategy. METHODS: A linkage map was constructed with 126 markers. The QTLs for four floral traits and the S locus were mapped. Using the genotypes of loci that were located near both the S locus and the QTLs with large effects, morphs of 59 wild genets were predicted. KEY RESULTS: The linkage map consisted of 14 linkage groups (LGs). The S locus was mapped to LG 7. Major QTLs for stigma and anther heights were detected in the same region as the S locus. These QTLs exhibited high logarithm of the odds scores and explained a high percentage of the phenotypic variance (>85 %). By analysing these two traits within each morph, additional QTLs for each trait were detected. Using the four loci linked to the S locus, the morphs of 43 genets in three wild populations could be predicted. CONCLUSIONS: This is the first report of a linkage map and QTL analysis for floral morphology related to heterostyly in P. sieboldii. Floral morphologies related to heterostyly are controlled by the S locus in LG 7 and by several QTLs in other LGs. Additionally, this study showed that molecular markers are effective tools for investigating morph ratios in a population containing the non-flowering individuals or during the non-flowering seasons.

Fixing the broken system of genetic locus symbols: Parkinson disease and dystonia as examples.

Originally, locus symbols (e.g., DYT1) were introduced to specify chromosomal regions that had been linked to a familial disorder with a yet unknown gene. Symbols were systematically assigned in a numerical series to designate mapped loci for a specific phenotype or group of phenotypes. Since the system of designating and using locus symbols was originally established, both our knowledge and our techniques of gene discovery have evolved substantially. The current system has problems that are sources of confusion, perpetuate misinformation, and misrepresent the system as a useful reference tool for a list of inherited disorders of a particular phenotypic class. These include erroneously assigned loci, duplicated loci, missing symbols, missing loci, unconfirmed loci in a consecutively numbered system, combining causative genes and risk factor genes in the same list, and discordance between phenotype and list assignment. In this article, we describe these problems and their impact, and propose solutions. The system could be significantly improved by creating distinct lists for clinical and research purposes, creating more informative locus symbols, distinguishing disease-causing mutations from risk factors, raising the threshold of evidence prior to assigning a locus symbol, paying strict attention to the predominant phenotype when assigning symbols lists, and having a formal system for reviewing and continually revising the list that includes input from both clinical and genetics experts.