Showing papers by "Kay Prüfer published in 2007"

Evolutionary and biomedical insights from the rhesus macaque genome

Abstract: 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.

Patterns of damage in genomic DNA sequences from a Neandertal

Abstract: High-throughput direct sequencing techniques have recently opened the possibility to sequence genomes from Pleistocene organisms. Here we analyze DNA sequences determined from a Neandertal, a mammoth, and a cave bear. We show that purines are overrepresented at positions adjacent to the breaks in the ancient DNA, suggesting that depurination has contributed to its degradation. We furthermore show that substitutions resulting from miscoding cytosine residues are vastly overrepresented in the DNA sequences and drastically clustered in the ends of the molecules, whereas other substitutions are rare. We present a model where the observed substitution patterns are used to estimate the rate of deamination of cytosine residues in single- and double-stranded portions of the DNA, the length of single-stranded ends, and the frequency of nicks. The results suggest that reliable genome sequences can be obtained from Pleistocene organisms.

Neanderthals in central Asia and Siberia.

Abstract: The classic frame of the Neanderthals — stocky, long-headed, with distinctive features of the skull — began to emerge around 400,000 years ago, and disappeared from hominins around 30,000 years ago. However, determining the precise identity of fragmentary fossils can be difficult. Krause et al. come to the rescue with mitochondrial DNA sequences that confirm that the skeleton of a child recovered in Uzbekistan in the 1930s was of Neanderthal origin — and showing that remains from the Altai region of Siberia, much further east, are also Neanderthal. This extends the Neanderthal range 2,000 km further east than previously assumed. Determining the precise identity or origin of fragmentary fossils can be difficult. Here, mitochondrial DNA sequences are used to confirm that the skeleton of a child recovered in Uzbekistan in the 1930s was of Neanderthal origin and that remains from the Altai region of Siberia, much further east, are also Neanderthal, extending the Neanderthal range 2,000 km further east than previously assumed. Morphological traits typical of Neanderthals began to appear in European hominids at least 400,000 years ago1 and about 150,000 years ago2 in western Asia. After their initial appearance, such traits increased in frequency and the extent to which they are expressed until they disappeared shortly after 30,000 years ago. However, because most fossil hominid remains are fragmentary, it can be difficult or impossible to determine unambiguously whether a fossil is of Neanderthal origin. This limits the ability to determine when and where Neanderthals lived. To determine how far to the east Neanderthals ranged, we determined mitochondrial DNA (mtDNA) sequences from hominid remains found in Uzbekistan and in the Altai region of southern Siberia. Here we show that the DNA sequences from these fossils fall within the European Neanderthal mtDNA variation. Thus, the geographic range of Neanderthals is likely to have extended at least 2,000 km further to the east than commonly assumed.

Targeted high-throughput sequencing of tagged nucleic acid samples

Abstract: High-throughput 454 DNA sequencing technology allows much faster and more cost-effective sequencing than traditional Sanger sequencing. However, the technology imposes inherent limitations on the number of samples that can be processed in parallel. Here we introduce parallel tagged sequencing (PTS), a simple, inexpensive and flexible barcoding technique that can be used for parallel sequencing any number and type of double-stranded nucleic acid samples. We demonstrate that PTS is particularly powerful for sequencing contiguous DNA fragments such as mtDNA genomes: in theory as many as 250 mammalian mtDNA genomes can be sequenced in a single GS FLX run. PTS dramatically increases the sequencing throughput of samples in parallel and thus fully mobilizes the resources of the 454 technology for targeted sequencing.

FUNC: a package for detecting significant associations between gene sets and ontological annotations

Abstract: Genome-wide expression, sequence and association studies typically yield large sets of gene candidates, which must then be further analysed and interpreted. Information about these genes is increasingly being captured and organized in ontologies, such as the Gene Ontology. Relationships between the gene sets identified by experimental methods and biological knowledge can be made explicit and used in the interpretation of results. However, it is often difficult to assess the statistical significance of such analyses since many inter-dependent categories are tested simultaneously. We developed the program package FUNC that includes and expands on currently available methods to identify significant associations between gene sets and ontological annotations. Implemented are several tests in particular well suited for genome wide sequence comparisons, estimates of the family-wise error rate, the false discovery rate, a sensitive estimator of the global significance of the results and an algorithm to reduce the complexity of the results. FUNC is a versatile and useful tool for the analysis of genome-wide data. It is freely available under the GPL license and also accessible via a web service.