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Abstract Background Knowledge of the origins, distribution, and inheritance of variation in the malaria parasite (Plasmodium falciparum) genome is crucial for understanding its evolution; however the 81% (A+T) genome poses challenges to high-throughput sequencing technologies. We explore the viability of the Roche 454 Genome Sequencer FLX (GS FLX) high throughput sequencing technology for both whole genome sequencing and fine-resolution characterization of genetic exchange in malaria parasites. Results We present a scheme to survey recombination in the haploid stage genomes of two sibling parasite clones, using whole genome pyrosequencing that includes a sliding window approach to predict recombination breakpoints. Whole genome shotgun (WGS) sequencing generated approximately 2 million reads, with an average read length of approximately 300 bp. De novo assembly using a combination of WGS and 3 kb paired end libraries resulted in contigs ≤ 34 kb. More than 8,000 of the 24,599 SNP markers identified between parents were genotyped in the progeny, resulting in a marker density of approximately 1 marker/3.3 kb and allowing for the detection of previously unrecognized crossovers (COs) and many non crossover (NCO) gene conversions throughout the genome. Conclusions By sequencing the 23 Mb genomes of two haploid progeny clones derived from a genetic cross at more than 30× coverage, we captured high resolution information on COs, NCOs and genetic variation within the progeny genomes. This study is the first to resequence progeny clones to examine fine structure of COs and NCOs in malaria parasites.

Abstract Background Several recent studies have demonstrated the use of Roche 454 sequencing technology for de novo transcriptome analysis. Low error rates and high coverage also allow for effective SNP discovery and genetic diversity estimates. However, genetically diverse datasets, such as those sourced from natural populations, pose challenges for assembly programs and subsequent analysis. Further, estimating the effectiveness of transcript discovery using Roche 454 transcriptome data is still a difficult task. Results Using the Roche 454 FLX Titanium platform, we sequenced and assembled larval transcriptomes for two butterfly species: the Propertius duskywing, Erynnis propertius (Lepidoptera: Hesperiidae) and the Anise swallowtail, Papilio zelicaon (Lepidoptera: Papilionidae). The Expressed Sequence Tags (ESTs) generated represent a diverse sample drawn from multiple populations, developmental stages, and stress treatments. Despite this diversity, > 95% of the ESTs assembled into long (> 714 bp on average) and highly covered (> 9.6× on average) contigs. To estimate the effectiveness of transcript discovery, we compared the number of bases in the hit region of unigenes (contigs and singletons) to the length of the best match silkworm (Bombyx mori) protein--this "ortholog hit ratio" gives a close estimate on the amount of the transcript discovered relative to a model lepidopteran genome. For each species, we tested two assembly programs and two parameter sets; although CAP3 is commonly used for such data, the assemblies produced by Celera Assembler with modified parameters were chosen over those produced by CAP3 based on contig and singleton counts as well as ortholog hit ratio analysis. In the final assemblies, 1,413 E. propertius and 1,940 P. zelicaon unigenes had a ratio > 0.8; 2,866 E. propertius and 4,015 P. zelicaon unigenes had a ratio > 0.5. Conclusions Ultimately, these assemblies and SNP data will be used to generate microarrays for ecoinformatics examining climate change tolerance of different natural populations. These studies will benefit from high quality assemblies with few singletons (less than 26% of bases for each assembled transcriptome are present in unassembled singleton ESTs) and effective transcript discovery (over 6,500 of our putative orthologs cover at least 50% of the corresponding model silkworm gene).

Background: Restriction site associated DNA sequencing (RADseq) has the potential to be a broadly applicable, low-cost approach for high-quality genetic linkage mapping in forest trees lacking a reference genome. The statistical inference of linear order must be as accurate as possible for the correct ordering of sequence scaffolds and contigs to chromosomal locations. Accurate maps also facilitate the discovery of chromosome segments containing allelic variants conferring resistance to the biotic and abiotic stresses that threaten forest trees worldwide. We used ddRADseq for genetic mapping in the tree Quercus rubra, with an approach optimized to produce a high-quality map. Our study design also enabled us to model the results we would have obtained with less depth of coverage., Results: Our sequencing design produced a high sequencing depth in the parents (248×) and a moderate sequencing depth (15×) in the progeny. The digital normalization method of generating a de novo reference and the SAMtools SNP variant caller yielded the most SNP calls (78,725). The major drivers of map inflation were multiple SNPs located within the same sequence (77% of SNPs called). The highest quality map was generated with a low level of missing data (5%) and a genome-wide threshold of 0.025 for deviation from Mendelian expectation. The final map included 849 SNP markers (1.8% of the 78,725 SNPs called). Downsampling the individual FASTQ files to model lower depth of coverage revealed that sequencing the progeny using 96 samples per lane would have yielded too few SNP markers to generate a map, even if we had sequenced the parents at depth 248×., Conclusions: The ddRADseq technology produced enough high-quality SNP markers to make a moderately dense, high-quality map. The success of this project was due to high depth of coverage of the parents, moderate depth of coverage of the progeny, a good framework map, an optimized bioinformatics pipeline, and rigorous premapping filters. The ddRADseq approach is useful for the construction of high-quality genetic maps in organisms lacking a reference genome if the parents and progeny are sequenced at sufficient depth. Technical improvements in reduced representation sequencing (RRS) approaches are needed to reduce the amount of missing data.