A First Generation Microsatellite- and SNP-Based Linkage Map of Jatropha

Jatropha curcas is a potential plant species for biodiesel production. However, its seed yield is too low for profitable production of biodiesel. To improve the productivity, genetic improvement through breeding is essential. A linkage map is an important component in molecular breeding. We established a first-generation linkage map using a mapping panel containing two backcross populations with 93 progeny. We mapped 506 markers (216 microsatellites and 290 SNPs from ESTs) onto 11 linkage groups. The total length of the map was 1440.9 cM with an average marker space of 2.8 cM. Blasting of 222 Jatropha ESTs containing polymorphic SSR or SNP markers against EST-databases revealed that 91.0%, 86.5% and 79.2% of Jatropha ESTs were homologous to counterparts in castor bean, poplar and Arabidopsis respectively. Mapping 192 orthologous markers to the assembled whole genome sequence of Arabidopsis thaliana identified 38 syntenic blocks and revealed that small linkage blocks were well conserved, but often shuffled. The first generation linkage map and the data of comparative mapping could lay a solid foundation for QTL mapping of agronomic traits, marker-assisted breeding and cloning genes responsible for phenotypic variation

Evaluation of next-generation sequencing software in mapping and assembly

Next-generation high-throughput DNA sequencing technologies have advanced progressively in sequence-based genomic research and novel biological applications with the promise of sequencing DNA at unprecedented speed. These new non-Sanger-based technologies feature several advantages when compared with traditional sequencing methods in terms of higher sequencing speed, lower per run cost and higher accuracy. However, reads from next-generation sequencing (NGS) platforms, such as 454/Roche, ABI/SOLiD and Illumina/Solexa, are usually short, thereby restricting the applications of NGS platforms in genome assembly and annotation. We presented an overview of the challenges that these novel technologies meet and particularly illustrated various bioinformatics attempts on mapping and assembly for problem solving. We then compared the performance of several programs in these two fields, and further provided advices on selecting suitable tools for specific biological applications.published_or_final_versio