The long-tailed macaque, also referred to as cynomolgus monkey (Macaca fascicularis), is one of the most important nonhuman primate animal models in basic and applied biomedical research. To improve the predictive power of primate experiments for humans, we determined the genome sequence of a Macaca fascicularis female of Mauritian origin using a whole-genome shotgun sequencing approach. We applied a template switch strategy that uses either the rhesus or the human genome to assemble sequence reads. The sixfold sequence coverage of the draft genome sequence enabled discovery of about 2.1 million potential single-nucleotide polymorphisms based on occurrence of a dimorphic nucleotide at a given position in the genome sequence. Homology-based annotation allowed us to identify 17,387 orthologs of human protein-coding genes in the M. fascicularis draft genome, and the predicted transcripts enabled the design of a M. fascicularis–specific gene expression microarray. Using liver samples from 36 individuals of different geographic origin we identified 718 genes with highly variable expression in liver, whereas the majority of the transcriptome shows relatively stable and comparable expression. Knowledge of the M. fascicularis draft genome is an important contribution to both the use of this animal in disease models and the safety assessment of drugs and their metabolites. In particular, this information allows high-resolution genotyping and microarray-based gene-expression profiling for animal stratification, thereby allowing the use of well-characterized animals for safety testing. Finally, the genome sequence presented here is a significant contribution to the global “3R” animal welfare initiative, which has the goal to reduce, refine, and replace animal experiments.

Comparative genomics has greatly improved our understanding of the evolution of pathogenic mycobacteria such as Mycobacterium tuberculosis. Here we have used data from a genome microarray analysis to explore insertion-deletion (InDel) polymorphism among a diverse strain collection of Mycobacterium ulcerans, the causative agent of the devastating skin disease, Buruli ulcer. Detailed analysis of large sequence polymorphisms in twelve regions of difference (RDs), comprising irreversible genetic markers, enabled us to refine the phylogenetic succession within M. ulcerans, to define features of a hypothetical M. ulcerans most recent common ancestor and to confirm its origin from Mycobacterium marinum.

Background: Theileria parva is a tick-borne protozoan parasite, which causes East Coast Fever, a disease of cattle in sub-Saharan Africa. Like Plasmodium falciparum, the parasite undergoes a transient diploid life-cycle stage in the gut of the arthropod vector, which involves an obligate sexual cycle. As assessed using low-resolution VNTR markers, the crossover (CO) rate in T. parva is relatively high and has been reported to vary across different regions of the genome; non-crossovers (NCOs) and CO-associated gene conversions have not yet been characterised due to the lack of informative markers. To examine all recombination events at high marker resolution, we sequenced the haploid genomes of two parental strains, and two recombinant clones derived from ticks fed on cattle that had been simultaneously co-infected with two different parasite isolates. Results: By comparing the genome sequences, we were able to genotype over 64 thousand SNP markers with an average spacing of 127 bp in the two progeny clones. Previously unrecognized COs in sub-telomeric regions were detected. About 50% of CO breakpoints were accompanied by gene conversion events. Such a high fraction of COs accompanied by gene conversions demonstrated the contributions of meiotic recombination to the diversity and evolutionary success of T. parva, as the process not only redistributed existing genetic variations, but also altered allelic frequencies. Compared to COs, NCOs were more frequently observed and more uniformly distributed across the genome. In both progeny clones, genomic regions with more SNP markers had a reduced frequency of COs or NCOs, suggesting that the sequence divergence between the parental strains was high enough to adversely affect recombination frequencies. Intra-species polymorphism analysis identified 81 loci as likely to be under selection in the sequenced genomes. Conclusions: Using whole genome sequencing of two recombinant clones and their parents, we generated maps of COs, NCOs, and CO-associated gene conversion events for T. parva. The data comprises one of the highest-resolution genome-wide analyses of the multiple outcomes of meiotic recombination for this pathogen. The study also demonstrates the usefulness of high throughput sequencing typing for detailed analysis of recombination in organisms in which conventional genetic analysis is technically difficult.

Mutations and gene expression alterations in brain tumors have been extensively investigated, however the causes of brain tumorigenesis are largely unknown. Animal models are necessary to correlate altered transcriptional activity and tumor phenotype and to better understand how these alterations cause malignant growth. In order to gain insights into the in vivo transcriptional activity associated with a brain tumor, we carried out genome-wide microarray expression analyses of an adult brain tumor in Drosophila caused by homozygous mutation in the tumor suppressor gene brain tumor (brat). Two independent genome-wide gene expression studies using two different oligonucleotide microarray platforms were used to compare the transcriptome of adult wildtype flies with mutants displaying the adult brat ^k06028 mutant brain tumor. Cross-validation and stringent statistical criteria identified a core transcriptional signature of brat ^k06028 neoplastic tissue. We find significant expression level changes for 321 annotated genes associated with the adult neoplastic brat ^k06028 tissue indicating elevated and aberrant metabolic and cell cycle activity, upregulation of the basal transcriptional machinery, as well as elevated and aberrant activity of ribosome synthesis and translation control. One fifth of these genes show homology to known mammalian genes involved in cancer formation. Our results identify for the first time the genome-wide transcriptional alterations associated with an adult brain tumor in Drosophila and reveal insights into the possible mechanisms of tumor formation caused by homozygous mutation of the translational repressor brat.

In clinical and basic research custom panels for transcript profiling are gaining importance because only project specific informative genes are interrogated. This approach reduces costs and complexity of data analysis and allows multiplexing of samples. Polymerase-chain-reaction (PCR) based TaqMan assays have high sensitivity but suffer from a limited dynamic range and sample throughput. Hence, there is a gap for a technology able to measure expression of large gene sets in multiple samples. We have adapted a commercially available mRNA quantification assay (AmpliSeq-RNA) that measures mRNA abundance based on the frequency of PCR amplicons determined by high-throughput semiconductor sequencing. This approach allows for parallel, accurate quantification of about 1000 transcripts in multiple samples covering a dynamic range of five orders of magnitude. Using samples derived from a well-characterized stem cell differentiation model, we obtained a good correlation (r = 0.78) of transcript levels measured by AmpliSeq-RNA and DNA-microarrays. A significant portion of low abundant transcripts escapes detection by microarrays due to limited sensitivity. Standard quantitative RNA sequencing of the same samples confirms expression of low abundant genes with an overall correlation coefficient of r = 0.87. Based on digital AmpliSeq-RNA imaging we show switches of signaling cascades at four time points during differentiation of stem cells into cardiomyocytes. The AmpliSeq-RNA technology adapted to high-throughput semiconductor sequencing allows robust transcript quantification based on amplicon frequency. Multiplexing of at least 900 parallel PCR reactions is feasible because sequencing-based quantification eliminates artefacts coming from off-target amplification. Using this approach, RNA quantification and detection of genetic variations can be performed in the same experiment.