The objectives of this study were (i) to assess the level of genetic diversity in elite sterility‐maintaining (B) and fertility‐restoring (R) sorghum [Sorghum bicolor (L.) Moench] lines as compared with a group of exotic and converted germplasm (IS) from the World Collection, (ii) to compare the classification of germplasm on the basis of estimates of genetic similarities obtained by means of AFLP and microsatellite (SSR) markers, and (iii) to compare the classification of germplasm obtained by different classes of molecular markers. A set of 100 SSRs, 1318 EcoRI/MseI AFLP, and 496 PstI/MseI AFLP markers with known map positions were utilized to determine the genetic similarity in a group of B, R, and IS public inbreds. Cluster analysis of genetic similarity estimates (GSij) revealed that the classification of sorghum inbreds is based on the sorghum working groups, Zera‐zera, Kafir, Kafir‐Milo, Durra, and Feterita. Cluster analyses failed to give a clear differentiation between B‐ and R‐lines, suggesting that R‐ and B‐lines do not represent well‐defined heterotic groups in this set of public lines. By comparing the different classes of molecular markers (SSRs, AFLPs, combinations of SSRs and AFLPs), we determined that the distribution of the markers and the coverage of the genome by the markers did affect the classification of genotypes. Dendrograms of genetic similarity (GS) based on PstI/MseI AFLP markers, or a set of markers spaced at 1‐ to 2‐cM intervals across the genome, produced clusters that were in better agreement with pedigree information than the analysis based solely on the EcoRI/MseI AFLP or SSR markers used in this study.

We sought to refine genetic management of the endangered Whooping Crane ( Grus americana ) population by developing comprehensive genetic pedigrees for the captive population. Improvements to the studbook were accomplished by addition of pedigree information derived from leg-banding data on wild juvenile and founder similarity coefficients calculated from microsatellite DNA profiles to the original studbook pedigree. Incorporation of pedigrees derived from data on leg-banding of wild juveniles did not greatly alter the previous relatedness structure of the captive population, but incorporation of microsatellite similarity coefficients produced a substantially different view of the population structure. Microsatellite data provided new information on shared founder genotypes and provided a new DNA-based studbook pedigree that will assist in genetic management of the Whooping Crane population.Refinando el Registro Genealógico de la Grulla Americana Mediante la Incorporación de ADN Microsatélite y el Análisis de Agrupamientos Resumen: Intentamos refinar el manejo genético de la población de una especie amenazada, la Grulla Americana (Grus americana) mediante el desarrollo integral del pedigrí genético de una población cautiva. Las mejoras al registro genealógico se lograron mediante la adición de información de pedigrí derivada de datos de agrupamiento de juveniles silvestres y coeficientes de similitud de fundadores calculados a partir de perfiles de ADN microsatélite al registro genealógico original. La incorporación de pedigrí derivados del agrupamiento de datos juveniles silvestres no alteraron mucho la estructura previa de relación de la población cautiva; sin embargo, la incorporación de los coeficientes de similitud de microsatélites condujeron a una visión de la estructura poblacional substancialmente diferente. Los datos de microsatélite proveyeron información nueva sobre los genotipos fundadores y proporcionan un registro genealógico de pedigrí basado en ADN que contribuirá al manejo genético de la población de grulla americana. ‡ ‡

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Using AFLP technology and a recombinant inbred line population derived from the sorghum cross of BTx623 x IS3620C, a high-density genetic map of the sorghum genome was constructed. The 1713 cM map encompassed 2926 loci distributed on ten linkage groups; 2454 of those loci are AFLP products generated from either the EcoRI/MseI or PstI/MseI enzyme combinations. Among the non-AFLP markers, 136 are SSRs previously mapped in sorghum, and 203 are cDNA and genomic clones from rice, barley, oat, and maize. This latter group of markers has been mapped in various grass species and, as such, can serve as reference markers in comparative mapping. Of the nearly 3000 markers mapped, 692 comprised a LOD >3.0 framework map on which the remaining markers were placed with lower resolution (LOD <3.0). By comparing the map positions of the common grass markers in all sorghum maps reported to date, it was determined that these reference markers were essentially collinear in all published maps. Some clustering of the EcoRI/MseI AFLP markers was observed, possibly in centromeric regions. In general, however, the AFLP markers filled most of the gaps left by the RFLP/SSR markers demonstrating that AFLP technology is effective in providing excellent genome coverage. A web site, http://SorghumGenome.tamu.edu, has been created to provide all the necessary information to facilitate the use of this map and the 2590 PCR-based markers. Finally, we discuss how the information contained in this map is being integrated into a sorghum physical map for map-based gene isolation, comparative genome analysis, and as a source of sequence-ready clones for genome sequencing projects.

A simple and rapid gas chromatographic procedure was developed for determining low concentrations of propionate added as a preservative to bread. A bread sample to be analyzed was ground in a meat grinder with a 3 mm hole plate and finely divided by rubbing through a No. 8 sieve. The propionate was then extracted into 0.050M formic acid in a blender at low speed for 5 min, and an aliquot of a filtrate was analyzed directly by gas chromatography. Chromatographic separation was accomplished on a Carbopack C column coated with 0.3% (w/w) Carbowax 20M and 0.1% (w/w) phosphoric acid. Less than 0.2 ppm propionic acid could be detected in the aqueous extract. Over the range of 0.03-0.23% calcium propionate, average relative error was —1.20% with an average coefficient of variation of 2.02%.