Martin Kircher

A draft sequence of the Neandertal genome.

Kissing Cousins Neandertals, our closest relatives, ranged across Europe and Southwest Asia before their extinction approximately 30,000 years ago. Green et al. (p. 710) report a draft sequence of the Neandertal genome, created from three individuals, and compare it with genomes of five modern humans. The results suggest that ancient genomes of human relatives can be recovered with acceptably low contamination from modern human DNA. Because ancient DNA can be contaminated with microbial DNA, Burbano et al. (p. 723) developed a target sequence capture approach to obtain 14 kilobases of Neandertal DNA from a fairly poorly preserved sample with a high microbial load. A number of genomic regions and genes were revealed as candidates for positive selection early in modern human history. The genomic data suggest that Neandertals mixed with modern human ancestors some 120,000 years ago, leaving traces of Neandertal DNA in contemporary humans. Gene flow has occurred from Neandertals to humans of Eurasian descent, but not to Africans. Neandertals, the closest evolutionary relatives of present-day humans, lived in large parts of Europe and western Asia before disappearing 30,000 years ago. We present a draft sequence of the Neandertal genome composed of more than 4 billion nucleotides from three individuals. Comparisons of the Neandertal genome to the genomes of five present-day humans from different parts of the world identify a number of genomic regions that may have been affected by positive selection in ancestral modern humans, including genes involved in metabolism and in cognitive and skeletal development. We show that Neandertals shared more genetic variants with present-day humans in Eurasia than with present-day humans in sub-Saharan Africa, suggesting that gene flow from Neandertals into the ancestors of non-Africans occurred before the divergence of Eurasian groups from each other.

Genetic history of an archaic hominin group from Denisova Cave in Siberia

Using DNA extracted from a finger bone found in Denisova Cave in southern Siberia, we have sequenced the genome of an archaic hominin to about 1.9-fold coverage. This individual is from a group that shares a common origin with Neanderthals. This population was not involved in the putative gene flow from Neanderthals into Eurasians; however, the data suggest that it contributed 4–6% of its genetic material to the genomes of present-day Melanesians. We designate this hominin population ‘Denisovans’ and suggest that it may have been widespread in Asia during the Late Pleistocene epoch. A tooth found in Denisova Cave carries a mitochondrial genome highly similar to that of the finger bone. This tooth shares no derived morphological features with Neanderthals or modern humans, further indicating that Denisovans have an evolutionary history distinct from Neanderthals and modern humans.

A High-Coverage Genome Sequence from an Archaic Denisovan Individual

Ancient Genomics The Denisovans were archaic humans closely related to Neandertals, whose populations overlapped with the ancestors of modern-day humans. Using a single-stranded library preparation method, Meyer et al. (p. 222, published online 30 August) provide a detailed analysis of a high-quality Denisovan genome. The genomic sequence provides evidence for very low rates of heterozygosity in the Denisova, probably not because of recent inbreeding, but instead because of a small population size. The genome sequence also illuminates the relationships between humans and archaics, including Neandertals, and establishes a catalog of genetic changes within the human lineage. A close-up look provides clues to the relationships between modern humans, Denisovans, and Neandertals. We present a DNA library preparation method that has allowed us to reconstruct a high-coverage (30×) genome sequence of a Denisovan, an extinct relative of Neandertals. The quality of this genome allows a direct estimation of Denisovan heterozygosity indicating that genetic diversity in these archaic hominins was extremely low. It also allows tentative dating of the specimen on the basis of “missing evolution” in its genome, detailed measurements of Denisovan and Neandertal admixture into present-day human populations, and the generation of a near-complete catalog of genetic changes that swept to high frequency in modern humans since their divergence from Denisovans.

The complete genome sequence of a Neanderthal from the Altai Mountains

We present a high-quality genome sequence of a Neanderthal woman from Siberia. We show that her parents were related at the level of half-siblings and that mating among close relatives was common among her recent ancestors. We also sequenced the genome of a Neanderthal from the Caucasus to low coverage. An analysis of the relationships and population history of available archaic genomes and 25 present-day human genomes shows that several gene flow events occurred among Neanderthals, Denisovans and early modern humans, possibly including gene flow into Denisovans from an unknown archaic group. Thus, interbreeding, albeit of low magnitude, occurred among many hominin groups in the Late Pleistocene. In addition, the high-quality Neanderthal genome allows us to establish a definitive list of substitutions that became fixed in modern humans after their separation from the ancestors of Neanderthals and Denisovans.

Deep proteome and transcriptome mapping of a human cancer cell line

While the number and identity of proteins expressed in a single human cell type is currently unknown, this fundamental question can be addressed by advanced mass spectrometry (MS)‐based proteomics. Online liquid chromatography coupled to high‐resolution MS and MS/MS yielded 166 420 peptides with unique amino‐acid sequence from HeLa cells. These peptides identified 10 255 different human proteins encoded by 9207 human genes, providing a lower limit on the proteome in this cancer cell line. Deep transcriptome sequencing revealed transcripts for nearly all detected proteins. We calculate copy numbers for the expressed proteins and show that the abundances of >90% of them are within a factor 60 of the median protein expression level. Comparisons of the proteome and the transcriptome, and analysis of protein complex databases and GO categories, suggest that we achieved deep coverage of the functional transcriptome and the proteome of a single cell type.

The evolution of gene expression levels in mammalian organs

Changes in gene expression are thought to underlie many of the phenotypic differences between species. However, large-scale analyses of gene expression evolution were until recently prevented by technological limitations. Here we report the sequencing of polyadenylated RNA from six organs across ten species that represent all major mammalian lineages (placentals, marsupials and monotremes) and birds (the evolutionary outgroup), with the goal of understanding the dynamics of mammalian transcriptome evolution. We show that the rate of gene expression evolution varies among organs, lineages and chromosomes, owing to differences in selective pressures: transcriptome change was slow in nervous tissues and rapid in testes, slower in rodents than in apes and monotremes, and rapid for the X chromosome right after its formation. Although gene expression evolution in mammals was strongly shaped by purifying selection, we identify numerous potentially selectively driven expression switches, which occurred at different rates across lineages and tissues and which probably contributed to the specific organ biology of various mammals.

High-throughput DNA sequencing – concepts and limitations

Recent advances in DNA sequencing have revolutionized the field of genomics, making it possible for even single research groups to generate large amounts of sequence data very rapidly and at a substantially lower cost. These high‐throughput sequencing technologies make deep transcriptome sequencing and transcript quantification, whole genome sequencing and resequencing available to many more researchers and projects. However, while the cost and time have been greatly reduced, the error profiles and limitations of the new platforms differ significantly from those of previous sequencing technologies. The selection of an appropriate sequencing platform for particular types of experiments is an important consideration, and requires a detailed understanding of the technologies available; including sources of error, error rate, as well as the speed and cost of sequencing. We review the relevant concepts and compare the issues raised by the current high‐throughput DNA sequencing technologies. We analyze how future developments may overcome these limitations and what challenges remain.

Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform

Due to the increasing throughput of current DNA sequencing instruments, sample multiplexing is necessary for making economical use of available sequencing capacities. A widely used multiplexing strategy for the Illumina Genome Analyzer utilizes sample-specific indexes, which are embedded in one of the library adapters. However, this and similar multiplex approaches come with a risk of sample misidentification. By introducing indexes into both library adapters (double indexing), we have developed a method that reveals the rate of sample misidentification within current multiplex sequencing experiments. With ~0.3% these rates are orders of magnitude higher than expected and may severely confound applications in cancer genomics and other fields requiring accurate detection of rare variants. We identified the occurrence of mixed clusters on the flow as the predominant source of error. The accuracy of sample identification is further impaired if indexed oligonucleotides are cross-contaminated or if indexed libraries are amplified in bulk. Double-indexing eliminates these problems and increases both the scope and accuracy of multiplex sequencing on the Illumina platform.

Improved base calling for the Illumina Genome Analyzer using machine learning strategies

The Illumina Genome Analyzer generates millions of short sequencing reads. We present Ibis (Improved base identification system), an accurate, fast and easy-to-use base caller that significantly reduces the error rate and increases the output of usable reads. Ibis is faster and more robust with respect to chemistry and technology than other publicly available packages. Ibis is freely available under the GPL from http://bioinf.eva.mpg.de/Ibis/.

Removal of deaminated cytosines and detection of in vivo methylation in ancient DNA

DNA sequences determined from ancient organisms have high error rates, primarily due to uracil bases created by cytosine deamination. We use synthetic oligonucleotides, as well as DNA extracted from mammoth and Neandertal remains, to show that treatment with uracil–DNA–glycosylase and endonuclease VIII removes uracil residues from ancient DNA and repairs most of the resulting abasic sites, leaving undamaged parts of the DNA fragments intact. Neandertal DNA sequences determined with this protocol have greatly increased accuracy. In addition, our results demonstrate that Neandertal DNA retains in vivo patterns of CpG methylation, potentially allowing future studies of gene inactivation and imprinting in ancient organisms.