S. Senthilvel

In silico mapping of important genes and markers available in the public domain for efficient sorghum breeding.

Crop genome sequencing projects generate massive amounts of genomic sequence information, and the utilization of this information in applied crop improvement programs has been augmented by the availability of sophisticated bioinformatics tools. Here, we present the possible direct utilization of sequence data from a sorghum genome sequencing project in applied crop breeding programs. Based on sequence homology, we aligned all publicly available simple sequence repeat markers on a sequence-based physical map for sorghum. Linking this physical map with already existing linkage map(s) provides better options for applied molecular breeding programs. When a new set of markers is made available, the new markers can be first aligned on a sequence-based physical map, and those located near the quantitative trait locus (QTL) can be identified from this map, thereby reducing the number of markers to be tested in order to identify polymorphic flanking markers for the QTL for any given donor × recurrent parent combination. Polymorphic markers that are expected (on the basis of their position on the sequence-based physical map) to be closely linked to the target can be used for foreground selection in marker-assisted breeding. This map facilitates the identification of a set of markers representing the entire genome, which would provide better resolution in diversity analyses and further linkage disequilibrium mapping. Filling the gaps in existing linkage maps and fine mapping can be achieved more efficiently by targeting the specific genomic regions of interest. It also opens up new exciting opportunities for comparative mapping and for the development of new genomic resources in related crops, both of which are lagging behind in the current genomic revolution. This paper also presents a number of examples of potential applications of sequence-based physical map for sorghum.

Laboratory Information Management Software for genotyping workflows: applications in high throughput crop genotyping

BackgroundWith the advances in DNA sequencer-based technologies, it has become possible to automate several steps of the genotyping process leading to increased throughput. To efficiently handle the large amounts of genotypic data generated and help with quality control, there is a strong need for a software system that can help with the tracking of samples and capture and management of data at different steps of the process. Such systems, while serving to manage the workflow precisely, also encourage good laboratory practice by standardizing protocols, recording and annotating data from every step of the workflow.ResultsA laboratory information management system (LIMS) has been designed and implemented at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that meets the requirements of a moderately high throughput molecular genotyping facility. The application is designed as modules and is simple to learn and use. The application leads the user through each step of the process from starting an experiment to the storing of output data from the genotype detection step with auto-binning of alleles; thus ensuring that every DNA sample is handled in an identical manner and all the necessary data are captured. The application keeps track of DNA samples and generated data. Data entry into the system is through the use of forms for file uploads. The LIMS provides functions to trace back to the electrophoresis gel files or sample source for any genotypic data and for repeating experiments. The LIMS is being presently used for the capture of high throughput SSR (simple-sequence repeat) genotyping data from the legume (chickpea, groundnut and pigeonpea) and cereal (sorghum and millets) crops of importance in the semi-arid tropics.ConclusionA laboratory information management system is available that has been found useful in the management of microsatellite genotype data in a moderately high throughput genotyping laboratory. The application with source code is freely available for academic users and can be downloaded from http://www.icrisat.org/gt-bt/lims/lims.asp.

Identification and Characterization of Toxigenic Fusaria Associated with Sorghum Grain Mold Complex in India

Fusarium species are dominant within the sorghum grain mold complex. Some species of Fusarium involved in grain mold complex produce mycotoxins, such as fumonisins. An attempt was made to identify Fusarium spp. associated with grain mold complex in major sorghum-growing areas in India through AFLP-based grouping of the isolates and to further confirm the species by sequencing part of α-Elongation factor gene and comparing the sequences with that available in the NCBI database. The dendrogram generated from the AFLP data clustered the isolates into 5 groups. Five species of Fusarium—F. proliferatum, F. thapsinum, F. equiseti, F. andiyazi and F. sacchari were identified based on sequence similarity of α-Elongation factor gene of the test isolates with those in the NCBI database. Fusarium thapsinum was identified as predominant species in Fusarium—grain mold complex in India and F. proliferatum as highly toxigenic for fumonisins production. Analysis of molecular variance (AMOVA) revealed 54% of the variation in the AFLP patterns of 63 isolates was due to the differences between Fusarium species, and 46% was due to differences between the strains within a species.

Assessing genetic diversity, allelic richness and genetic relationship among races in ICRISAT foxtail millet core collection

Foxtail millet (Setaria italica (L.) P. Beauv.) is an ideal crop for changing climate and food habits of peoples due to its short duration, high photosynthetic efficiency, nutritional richness and fair resistance to pest and diseases. However, foxtail millet yields are low mainly due to the lack of effort for its improvement and the lack of proper utilization of existing genetic variability. To enhance the use of diverse germplasm in breeding programmes, a core collection in foxtail millet consisting of 155 accessions was established. Core collection accessions were fingerprinted using 84 markers (81 simple sequence repeats (SSRs) and three Expressed Sequence Tag (EST)-SSRs). Our results showed the presence of greater molecular diversity in the foxtail millet core collection. The 84 markers detected a total of 1356 alleles with an average of 16.14 alleles (4–35) per locus. Of these, 368 were rare alleles, 906 common alleles and 82 the most frequent alleles. Sixty-one unique alleles that were specific to a particular accession and useful for germplasm identification were also detected. In this study, the genetic diversity of foxtail millet was fairly correlated well with racial classification, and the race Indica showed a greater genetic distance from the races Maxima and Moharia. The pairwise estimate of dissimilarity was >0.50 except in 123 out of 11,935 pairs which indicated a greater genetic variability. Two hundred and fifty pairs of genetically most diverse accessions were identified. This large molecular variation observed in the core collection could be utilized effectively by breeders or researchers for the selection of diverse parents for breeding cultivars and the development of mapping populations.

SSR allelic diversity in relation to morphological traits and resistance to grain mould in sorghum

Allelic variation at 46 simple sequence repeat (SSR) marker loci well distributed across the sorghum genome was used to assess genetic diversity among 92 sorghum lines, 74 resistant and 18 susceptible to grain mould. Of the 46 SSR markers, 44 were polymorphic, with the number of alleles ranging from 2 to 20 with an average of 7.55 alleles per locus. Genetic diversity among the sorghum lines was high as indicated by polymorphic information content (PIC) and gene diversity values. PIC values of polymorphic SSR markers ranged from 0.16 to 0.90, with an average of 0.54. Gene diversity among the sorghum lines varied from 0.16 to 0.91, with an average score of 0.58 per SSR marker. AMOVA indicated that 12% of the total variation observed among the sorghum lines was accounted for between grain mould resistant and susceptible types. Diversity based on six morphological traits and grain mould scores indicated major roles of panicle type and glumes coverage, followed by grain colour, in clustering of the lines. Seven grain mould resistant/ susceptible pairs with dissimilarity indices >0.50, but with similar flowering time, plant height, and panicle type/ inflorescence within each pair, were selected for use in developing recombinant inbred line mapping populations to identify genomic regions (and quantitative trait loci) associated with sorghum grain mould resistance.

Virulence Diversity in North Indian Isolates of Sclerospora Graminicola, the Pearl Millet Downy Mildew Pathogen

On-farm surveys were conducted in the Uttar Pradesh (India) during the two rainy seasons 2007 and 2008 to monitor pearl millet (Pennisetum glaucum) downy mildew incidence. Twenty-one isolates of Sclerospora graminicola, the pearl millet downy mildew pathogen, were collected from different hybrid cultivars. These isolates were established on seedlings of the highly susceptible line 7042S grown in the greenhouse and were characterized for their virulence diversity using a set of seven host differential lines. Quantitative differences in virulence among pathogen isolates were determined by calculating virulence index (percent disease incidence × latent period-1). Results were submitted to cluster analysis using the Average Linkage method to determine similarity among pathogen isolates. The two highly virulent isolates, Sg 492 from Aligarh and Sg 510 from Badaun, representing geographically diverse locations were selected for use in greenhouse screening of pearl millet breeding lines.

SSR and QTL map of Sorghum

Genetic map of sorghum consisting of SSRs and QTLs CMap Visualization Links: SorghumMarkers-QTLs Sorghum SSR Markers DOI: doi:10.1007/s11032-009-9365-9