The rhesus macaque ( Macaca mulatta ) is an abundant primate species that diverged from the ancestors of Homo sapiens about 25 million years ago. Because they are genetically and physiologically similar to humans, rhesus monkeys are the most widely used nonhuman primate in basic and applied biomedical research. We determined the genome sequence of an Indian-origin Macaca mulatta female and compared the data with chimpanzees and humans to reveal the structure of ancestral primate genomes and to identify evidence for positive selection and lineage-specific expansions and contractions of gene families. A comparison of sequences from individual animals was used to investigate their underlying genetic diversity. The complete description of the macaque genome blueprint enhances the utility of this animal model for biomedical research and improves our understanding of the basic biology of the species. 

Evolutionary and Biomedical Insights from the Rhesus Macaque Genome

The rhesus macaque (Macaca mulatta) is an abundant primate species that diverged from the ancestors of Homo sapiens about 25 million years ago. Because they are genetically and physiologically similar to humans, rhesus monkeys are the most widely used nonhuman primate in basic and applied biomedical research. We determined the genome sequence of an Indian-origin Macaca mulatta female and compared the data with chimpanzees and humans to reveal the structure of ancestral primate genomes and to identify evidence for positive selection and lineage-specific expansions and contractions of gene families. A comparison of sequences from individual animals was used to investigate their underlying genetic diversity. The complete description of the macaque genome blueprint enhances the utility of this animal model for biomedical research and improves our understanding of the basic biology of the species.

https://science.sciencemag.org/content/sci/316/5822/222.full.pdf

Evolutionary and biomedical insights from the rhesus macaque genome

A comprehensive understanding of cancer is predicated upon knowledge of the structure of malignant genomes underlying its many variant forms and the molecular mechanisms giving rise to them. It is well established that solid tumor genomes accumulate a large number of genome rearrangements during tumorigenesis. End Sequence Profiling (ESP) maps and clones genome breakpoints associated with all types of genome rearrangements elucidating the structural organization of tumor genomes. Here we extend the ESP methodology in several directions using the breast cancer cell line MCF-7. First, targeted ESP is applied to multiple amplified loci, revealing a complex process of rearrangement and coamplification in these regions reminiscent of breakage/fusion/bridge cycles. Second, genome breakpoints identified by ESP are confirmed using a combination of DNA sequencing and PCR. Third, in vitro functional studies assign biological function to a rearranged tumor BAC clone, demonstrating that it encodes antiapoptotic activity. Finally, ESP is extended to the transcriptome identifying four novel fusion transcripts and providing evidence that expression of fusion genes may be common in tumors. These results demonstrate the distinct advantages of ESP including: (1) the ability to detect all types of rearrangements and copy number changes; (2) straightforward integration of ESP data with the annotated genome sequence; (3) immortalization of the genome; (4) ability to generate tumor-specific reagents for in vitro and in vivo functional studies. Given these properties, ESP could play an important role in a tumor genome project.

/pdf/decoding-the-fine-scale-structure-of-a-breast-cancer-genome-51zt5bai7a.pdf

Decoding the fine-scale structure of a breast cancer genome and transcriptome.

For the vast majority of species – including many economically or ecologically important organisms, progress in biological research is hampered due to the lack of a reference genome sequence. Despite recent advances in sequencing technologies, several factors still limit the availability of such a critical resource. At the same time, many research groups and international consortia have already produced BAC libraries and physical maps and now are in a position to proceed with the development of whole-genome sequences organized around a physical map anchored to a genetic map. We propose a BAC-by-BAC sequencing protocol that combines combinatorial pooling design and second-generation sequencing technology to efficiently approach denovo selective genome sequencing. We show that combinatorial pooling is a cost-effective and practical alternative to exhaustive DNA barcoding when preparing sequencing libraries for hundreds or thousands of DNA samples, such as in this case gene-bearing minimum-tiling-path BAC clones. The novelty of the protocol hinges on the computational ability to efficiently compare hundred millions of short reads and assign them to the correct BAC clones (deconvolution) so that the assembly can be carried out clone-by-clone. Experimental results on simulated data for the rice genome show that the deconvolution is very accurate, and the resulting BAC assemblies have high quality. Results on real data for a gene-rich subset of the barley genome confirm that the deconvolution is accurate and the BAC assemblies have good quality. While our method cannot provide the level of completeness that one would achieve with a comprehensive whole-genome sequencing project, we show that it is quite successful in reconstructing the gene sequences within BACs. In the case of plants such as barley, this level of sequence knowledge is sufficient to support critical end-point objectives such as map-based cloning and marker-assisted breeding.

/pdf/combinatorial-pooling-enables-selective-sequencing-of-the-vt7fpvw7kj.pdf

Combinatorial Pooling Enables Selective Sequencing of the Barley Gene Space

X chromosome dosage compensation ensures balanced gene dosage between the X chromosome and autosomes and between the sexes, involving divergent mechanisms among mammals. We elucidated a distinct me...

The X chromosome dosage compensation program during the development of cynomolgus monkeys.

Pooled genomic indexing (PGI) is a method for mapping collections of bacterial artificial chromosome (BAC) clones between species by using a combination of clone pooling and DNA sequencing. PGI has been used to map a total of 3858 BAC clones covering approximately 24% of the rhesus macaque (Macaca mulatta) genome onto 4178 homologous loci in the human genome. A number of intrachromosomal rearrangements were detected by mapping multiple segments within the individual rhesus BACs onto multiple disjoined loci in the human genome. Transversal pooling designs involving shuffled BAC arrays were employed for robust mapping even with modest DNA sequence read coverage. A further innovation, short-tag pooled genomic indexing (ST-PGI), was also introduced to further improve the economy of mapping by sequencing multiple, short, mapable tags within a single sequencing reaction.

/pdf/pooled-genomic-indexing-of-rhesus-macaque-4mj20z69q5.pdf

Pooled genomic indexing of rhesus macaque

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Pooled genomic indexing of rhesus macaque