The complete genome of an individual by massively parallel DNA sequencing

Comparing platforms for C. elegans mutant identification using high-throughput whole-genome sequencing

BACKGROUND

Whole-genome sequencing represents a promising approach to pinpoint chemically induced mutations in genetic model organisms, thereby short-cutting time-consuming genetic mapping efforts.

PRINCIPAL FINDINGS

We compare here the ability of two leading high-throughput platforms for paired-end deep sequencing, SOLiD (ABI) and Genome Analyzer (Illumina; "Solexa"), to achieve the goal of mutant detection. As a test case we used a mutant C. elegans strain that harbors a mutation in the lsy-12 locus which we compare to the reference wild-type genome sequence. We analyzed the accuracy, sensitivity, and depth-coverage characteristics of the two platforms. Both platforms were able to identify the mutation that causes the phenotype of the mutant C. elegans strain, lsy-12. Based on a 4 MB genomic region in which individual variants were validated by Sanger sequencing, we observe tradeoffs between rates of false positives and false negatives when using both platforms under similar coverage and mapping criteria.

SIGNIFICANCE

In conclusion, whole-genome sequencing conducted by either platform is a viable approach for the identification of single-nucleotide variations in the C. elegans genome.

Sequencing the nuclear genome of the extinct woolly mammoth

In 1994, two independent groups extracted DNA from several Pleistocene epoch mammoths and noted differences among individual specimens. Subsequently, DNA sequences have been published for a number of extinct species. However, such ancient DNA is often fragmented and damaged, and studies to date have typically focused on short mitochondrial sequences, never yielding more than a fraction of a per cent of any nuclear genome. Here we describe 4.17 billion bases (Gb) of sequence from several mammoth specimens, 3.3 billion (80%) of which are from the woolly mammoth (Mammuthus primigenius) genome and thus comprise an extensive set of genome-wide sequence from an extinct species. Our data support earlier reports that elephantid genomes exceed 4 Gb. The estimated divergence rate between mammoth and African elephant is half of that between human and chimpanzee. The observed number of nucleotide differences between two particular mammoths was approximately one-eighth of that between one of them and the African elephant, corresponding to a separation between the mammoths of 1.5-2.0 Myr. The estimated probability that orthologous elephant and mammoth amino acids differ is 0.002, corresponding to about one residue per protein. Differences were discovered between mammoth and African elephant in amino-acid positions that are otherwise invariant over several billion years of combined mammalian evolution. This study shows that nuclear genome sequencing of extinct species can reveal population differences not evident from the fossil record, and perhaps even discover genetic factors that affect extinction.

Sequence assembly

Despite the rapidly increasing number of sequenced and re-sequenced genomes, many issues regarding the computational assembly of large-scale sequencing data have remain unresolved. Computational assembly is crucial in large genome projects as well for the evolving high-throughput technologies and plays an important role in processing the information generated by these methods. Here, we provide a comprehensive overview of the current publicly available sequence assembly programs. We describe the basic principles of computational assembly along with the main concerns, such as repetitive sequences in genomic DNA, highly expressed genes and alternative transcripts in EST sequences. We summarize existing comparisons of different assemblers and provide a detailed descriptions and directions for download of assembly programs at: http://genome.ku.dk/resources/assembly/methods.html.

DNA sequencing of a cytogenetically normal acute myeloid leukaemia genome

Acute myeloid leukemia is a highly malignant hematopoietic tumor that affects about 13,000 adults yearly in the United States. The treatment of this disease has changed little in the past two decades, since most of the genetic events that initiate the disease remain undiscovered. Whole genome sequencing is now possible at a reasonable cost and timeframe to utilize this approach for unbiased discovery of tumor-specific somatic mutations that alter the protein-coding genes. Here we show the results obtained by sequencing a typical acute myeloid leukemia genome and its matched normal counterpart, obtained from the patient’s skin. We discovered 10 genes with acquired mutations; two were previously described mutations thought to contribute to tumor progression, and 8 were novel mutations present in virtually all tumor cells at presentation and relapse, whose function is not yet known. Our study establishes whole genome sequencing as an unbiased method for discovering initiating mutations in cancer genomes, and for identifying novel genes that may respond to targeted therapies.

We used massively parallel sequencing technology to sequence the genomic DNA of tumor and normal skin cells obtained from a patient with a typical presentation of FAB M1 Acute Myeloid Leukemia (AML) with normal cytogenetics. 32.7-fold ‘haploid’ coverage (98 billion bases) was obtained for the tumor genome, and 13.9-fold coverage (41.8 billion bases) was obtained for the normal sample. Of 2,647,695 well-supported Single Nucleotide Variants (SNVs) found in the tumor genome, 2,588,486 (97.7%) also were detected in the patient’s skin genome, limiting the number of variants that required further study. For the purposes of this initial study, we restricted our downstream analysis to the coding sequences of annotated genes: we found only eight heterozygous, non-synonymous somatic SNVs in the entire genome. All were novel, including mutations in protocadherin/cadherin family members (CDH24 and PCLKC), G-protein coupled receptors (GPR123 and EBI2), a protein phosphatase (PTPRT), a potential guanine nucleotide exchange factor (KNDC1), a peptide/drug transporter (SLC15A1), and a glutamate receptor gene (GRINL1B). We also detected previously described, recurrent somatic insertions in the FLT3 and NPM1 genes. Based on deep readcount data, we determined that all of these mutations (except FLT3) were present in nearly all tumor cells at presentation, and again at relapse 11 months later, suggesting that the patient had a single dominant clone containing all of the mutations. These results demonstrate the power of whole genome sequencing to discover novel cancer-associated mutations.

MSB: a mean-shift-based approach for the analysis of structural variation in the genome

Genome structural variation includes segmental duplications, deletions, and other rearrangements, and array-based comparative genomic hybridization (array-CGH) is a popular technology for determining this. Drawing relevant conclusions from array-CGH requires computational methods for partitioning the chromosome into segments of elevated, reduced, or unchanged copy number. Several approaches have been described, most of which attempt to explicitly model the underlying distribution of data based on particular assumptions. Often, they optimize likelihood functions for estimating model parameters, by expectation maximization or related approaches; however, this requires good parameter initialization through prespecifying the number of segments. Moreover, convergence is difficult to achieve, since many parameters are required to characterize an experiment. To overcome these limitations, we propose a nonparametric method without a global criterion to be optimized. Our method involves mean-shift-based (MSB) procedures; it considers the observed array-CGH signal as sampling from a probability-density function, uses a kernel-based approach to estimate local gradients for this function, and iteratively follows them to determine local modes of the signal. Overall, our method achieves robust discontinuity-preserving smoothing, thus accurately segmenting chromosomes into regions of duplication and deletion. It does not require the number of segments as input, nor does its convergence depend on this. We successfully applied our method to both simulated data and array-CGH experiments on glioblastoma and adenocarcinoma. We show that it performs at least as well as, and often better than, 10 previously published algorithms. Finally, we show that our approach can be extended to segmenting the signal resulting from the depth-of-coverage of mapped reads from next-generation sequencing.

The HuRef Browser: a web resource for individual human genomics

The HuRef Genome Browser is a web application for the navigation and analysis of the previously published genome of a human individual, termed HuRef. The browser provides a comparative view between the NCBI human reference sequence and the HuRef assembly, and it enables the navigation of the HuRef genome in the context of HuRef, NCBI and Ensembl annotations. Single nucleotide polymorphisms, indels, inversions, structural and copy-number variations are shown in the context of existing functional annotations on either genome in the comparative view. Demonstrated here are some potential uses of the browser to enable a better understanding of individual human genetic variation. The browser provides full access to the underlying reads with sequence and quality information, the genome assembly and the evidence supporting the identification of DNA polymorphisms. The HuRef Browser is a unique and versatile tool for browsing genome assemblies and studying individual human sequence variation in a diploid context. The browser is available online at http://huref.jcvi.org.

New technologies for delineating and characterizing the lipid exome: prospects for understanding familial combined hyperlipidemia

This review summarizes the progress made in cutting through the biological and genetic complexity of the Gordian knot that is familial combined hyperlipidemia. We particularly focus on how the application of new genomic technologies, especially massively parallel sequencing and high-throughput genotyping platforms, promise to accelerate the gene discovery process in this common, highly atherogenic disorder, with important diagnostic and therapeutic implications.

Sequencing by Cyclic Ligation and Cleavage (CycLiC) directly on a microarray captured template

Next generation sequencing methods that can be applied to both the resequencing of whole genomes and to the selective resequencing of specific parts of genomes are needed. We describe (i) a massively scalable biochemistry, Cyclical Ligation and Cleavage (CycLiC) for contiguous base sequencing and (ii) apply it directly to a template captured on a microarray. CycLiC uses four color-coded DNA/RNA chimeric oligonucleotide libraries (OL) to extend a primer, a base at a time, along a template. The cycles comprise the steps: (i) ligation of OLs, (ii) identification of extended base by label detection, and (iii) cleavage to remove label/terminator and undetermined bases. For proof-of-principle, we show that the method conforms to design and that we can read contiguous bases of sequence correctly from a template captured by hybridization from solution to a microarray probe. The method is amenable to massive scale-up, miniaturization and automation. Implementation on a microarray format offers the potential for both selection and sequencing of a large number of genomic regions on a single platform. Because the method uses commonly available reagents it can be developed further by a community of users.

Next-generation sequencing: applications beyond genomes

The development of DNA sequencing more than 30 years ago has profoundly impacted biological research. In the last couple of years, remarkable technological innovations have emerged that allow the direct and cost-effective sequencing of complex samples at unprecedented scale and speed. These next-generation technologies make it feasible to sequence not only static genomes, but also entire transcriptomes expressed under different conditions. These and other powerful applications of next-generation sequencing are rapidly revolutionizing the way genomic studies are carried out. Below, we provide a snapshot of these exciting new approaches to understanding the properties and functions of genomes. Given that sequencing-based assays may increasingly supersede microarray-based assays, we also compare and contrast data obtained from these distinct approaches.

Human genomes as email attachments

SUMMARY

The amount of genomic sequence data being generated and made available through public databases continues to increase at an ever-expanding rate. Downloading, copying, sharing and manipulating these large datasets are becoming difficult and time consuming for researchers. We need to consider using advanced compression techniques as part of a standard data format for genomic data. The inherent structure of genome data allows for more efficient lossless compression than can be obtained through the use of generic compression programs. We apply a series of techniques to James Watson's genome that in combination reduce it to a mere 4MB, small enough to be sent as an email attachment.

High-resolution copy-number variation map reflects human olfactory receptor diversity and evolution

Olfactory receptors (ORs), which are involved in odorant recognition, form the largest mammalian protein superfamily. The genomic content of OR genes is considerably reduced in humans, as reflected by the relatively small repertoire size and the high fraction (∼55%) of human pseudogenes. Since several recent low-resolution surveys suggested that OR genomic loci are frequently affected by copy-number variants (CNVs), we hypothesized that CNVs may play an important role in the evolution of the human olfactory repertoire. We used high-resolution oligonucleotide tiling microarrays to detect CNVs across 851 OR gene and pseudogene loci. Examining genomic DNA from 25 individuals with ancestry from three populations, we identified 93 OR gene loci and 151 pseudogene loci affected by CNVs, generating a mosaic of OR dosages across persons. Our data suggest that ∼50% of the CNVs involve more than one OR, with the largest CNV spanning 11 loci. In contrast to earlier reports, we observe that CNVs are more frequent among OR pseudogenes than among intact genes, presumably due to both selective constraints and CNV formation biases. Furthermore, our results show an enrichment of CNVs among ORs with a close human paralog or lacking a one-to-one ortholog in chimpanzee. Interestingly, among the latter we observed an enrichment in CNV losses over gains, a finding potentially related to the known diminution of the human OR repertoire. Quantitative PCR experiments performed for 122 sampled ORs agreed well with the microarray results and uncovered 23 additional CNVs. Importantly, these experiments allowed us to uncover nine common deletion alleles that affect 15 OR genes and five pseudogenes. Comparison to the chimpanzee reference genome revealed that all of the deletion alleles are human derived, therefore indicating a profound effect of human-specific deletions on the individual OR gene content. Furthermore, these deletion alleles may be used in future genetic association studies of olfactory inter-individual differences.

Copy-number variants (CNVs) are deletions and duplications of DNA segments, responsible for most of the genome variation in mammals. To help elucidate the impact of CNVs on evolution and function, we provide a high-resolution CNV map of the largest gene superfamily in humans, i.e., the olfactory receptor (OR) gene superfamily. Our map reveals twice as many olfactory CNVs per person than previously reported, indicating considerable OR dosage variations in humans. In particular, our findings indicate that CNVs are specifically enriched among evolutionary “young” ORs, some of which originated following the human-chimpanzee split, implying that CNVs may play an important role in the gene-birth and gene-loss processes that continuously shape the human OR repertoire. Furthermore, we describe 15 OR gene loci showing frequent human-specific deletion alleles. Additionally, we present evidence for a recent non-allelic homologous recombination event involving a pair of OR genes, forming a novel fusion OR that may harbor novel odorant-binding properties. Such events may potentially relate to individual functional “holes” in the human smell-detection repertoire, and future studies will address the specific chemosensory impact of our genomic variation map.

The diploid genome sequence of an Asian individual

Here we present the first diploid genome sequence of an Asian individual. The genome was sequenced to 36-fold average coverage using massively parallel sequencing technology. We aligned the short reads onto the NCBI human reference genome to 99.97% coverage, and guided by the reference genome, we used uniquely mapped reads to assemble a high-quality consensus sequence for 92% of the Asian individual's genome. We identified approximately 3 million single-nucleotide polymorphisms (SNPs) inside this region, of which 13.6% were not in the dbSNP database. Genotyping analysis showed that SNP identification had high accuracy and consistency, indicating the high sequence quality of this assembly. We also carried out heterozygote phasing and haplotype prediction against HapMap CHB and JPT haplotypes (Chinese and Japanese, respectively), sequence comparison with the two available individual genomes (J. D. Watson and J. C. Venter), and structural variation identification. These variations were considered for their potential biological impact. Our sequence data and analyses demonstrate the potential usefulness of next-generation sequencing technologies for personal genomics.

[Trial to predict interactions between proteins and biomolecules based on their three-dimensional structures]

A vast amount of DNA sequence data, protein three-dimensional (3D) structure data, and RNA expression data have been produced by the efforts of genome sequencing, structural genomics, and omics projects, and we are at the stage where comprehensive views of cell activity and molecular mechanisms of life can be deduced. But in reality, we are inundated with massive amounts of data and are still in the process of finding ways to fully utilize the data. In this report, I would like to present our observations on the growth of protein 3D structure data and our effort to deduce the functions from the 3D structures. We found that the 3D structure of quite a high proportion of proteins derived from genome sequences can be now predicted and methods to predict the functions from 3D structures are in high demand. The methods we have developed can be used to predict some functions, namely RNA and ligand interfaces, based on those 3D structures and DNA sequences with relatively high accuracy. The methods enable predictions that are accurate enough to help with deducing the atomic structures of the complexes.

Aggressive assembly of pyrosequencing reads with mates

MOTIVATION

DNA sequence reads from Sanger and pyrosequencing platforms differ in cost, accuracy, typical coverage, average read length and the variety of available paired-end protocols. Both read types can complement one another in a 'hybrid' approach to whole-genome shotgun sequencing projects, but assembly software must be modified to accommodate their different characteristics. This is true even of pyrosequencing mated and unmated read combinations. Without special modifications, assemblers tuned for homogeneous sequence data may perform poorly on hybrid data.

RESULTS

Celera Assembler was modified for combinations of ABI 3730 and 454 FLX reads. The revised pipeline called CABOG (Celera Assembler with the Best Overlap Graph) is robust to homopolymer run length uncertainty, high read coverage and heterogeneous read lengths. In tests on four genomes, it generated the longest contigs among all assemblers tested. It exploited the mate constraints provided by paired-end reads from either platform to build larger contigs and scaffolds, which were validated by comparison to a finished reference sequence. A low rate of contig mis-assembly was detected in some CABOG assemblies, but this was reduced in the presence of sufficient mate pair data.

AVAILABILITY

The software is freely available as open-source from http://wgs-assembler.sf.net under the GNU Public License.

Rapidly developing functional genomics in ecological model systems via 454 transcriptome sequencing

Next generation sequencing technology affords new opportunities in ecological genetics. This paper addresses how an ecological genetics research program focused on a phenotype of interest can quickly move from no genetic resources to having various functional genomic tools. 454 sequencing and its error rates are discussed, followed by a review of de novo transcriptome assemblies focused on the first successful de novo assembly which happens to be in an ecological model system (the Glanville fritillary butterfly). The potential future developments in 454 sequencing are also covered. Particular attention is paid to the difficulties ecological geneticists are likely to encounter through reviewing relevant studies in both model and non-model systems. Various post-sequencing issues and applications of 454 generated data are presented (e.g. database management, microarray construction, molecular marker and candidate gene development). How to use species with genomic resources to inform study of those without is also discussed. In closing, some of the drawbacks of 454 sequencing are presented along with future prospects of this technology.

DDBJ dealing with mass data produced by the second generation sequencer

DNA Data Bank of Japan (DDBJ) (http://www.ddbj.nig.ac.jp) collected and released 2 368 110 entries or 1 415 106 598 bases in the period from July 2007 to June 2008. The releases in this period include genome scale data of Bombyx mori, Oryzas latipes, Drosophila and Lotus japonicus. In addition, from this year we collected and released trace archive data in collaboration with National Center for Biotechnology Information (NCBI). The first release contains those of O. latipes and bacterial meta genomes in human gut. To cope with the current progress of sequencing technology, we also accepted and released more than 100 million of short reads of parasitic protozoa and their hosts that were produced by using a Solexa sequencer.

An MCMC algorithm for haplotype assembly from whole-genome sequence data

In comparison to genotypes, knowledge about haplotypes (the combination of alleles present on a single chromosome) is much more useful for whole-genome association studies and for making inferences about human evolutionary history. Haplotypes are typically inferred from population genotype data using computational methods. Whole-genome sequence data represent a promising resource for constructing haplotypes spanning hundreds of kilobases for an individual. In this article, we propose a Markov chain Monte Carlo (MCMC) algorithm, HASH (haplotype assembly for single human), for assembling haplotypes from sequenced DNA fragments that have been mapped to a reference genome assembly. The transitions of the Markov chain are generated using min-cut computations on graphs derived from the sequenced fragments. We have applied our method to infer haplotypes using whole-genome shotgun sequence data from a recently sequenced human individual. The high sequence coverage and presence of mate pairs result in fairly long haplotypes (N50 length ~ 350 kb). Based on comparison of the sequenced fragments against the individual haplotypes, we demonstrate that the haplotypes for this individual inferred using HASH are significantly more accurate than the haplotypes estimated using a previously proposed greedy heuristic and a simple MCMC method. Using haplotypes from the HapMap project, we estimate the switch error rate of the haplotypes inferred using HASH to be quite low, ~1.1%. Our Markov chain Monte Carlo algorithm represents a general framework for haplotype assembly that can be applied to sequence data generated by other sequencing technologies. The code implementing the methods and the phased individual haplotypes can be downloaded from (http://www.cse.ucsd.edu/users/vibansal/HASH/).

Cytomics and nanobioengineering

The finding that an individual's genome differs as much as by many million variants from that of the human reference assembly diminished the great enthusiasm that every disease could be predicted based on nucleotide polymorphisms. Even individual cells of an organ may be specifically equipped to perform specific tasks and that the information of individual cells in a cell system is key information to understand function or dysfunction. Therefore, cytomics received great attention during the last years as it allows to quantitatively and qualitatively analyzing great number of individual cells, cell constituents, and of their intracellular and functional interactions in a cellular system and also giving the concept of analysis of these data.Exhaustive data extraction from multiparametric assays and multiple tests are the prerequisite for prediction of drug toxicity. Cytomics, as novel approach for unsupervised data analysis give a chance to find the most predictive parameters, which describe best the toxicity of a chemical. Cytomics is intrinsically connected to drug development and drug discovery.Focused on small structures, nanobioengineering is the ideal partner of cytomics, the systems biological discipline for cell population analysis. Realizing the idea "from the molecule to the patient" develops and offers chemical compounds, proteins, and other biomolecules, cells as well as tissues as instruments and products for a wide variety of biotechnological and biomedical applications.The integrative nanobioengineering combining different disciplines of nanotechnology will promote the development of innovative therapies and diagnostic methods. It can improve the precision of the measurements with focus on single cell analysis. By nanobioengineering and whole body imaging techniques, cytomics covers the field from molecules through bacterial cells, eukaryotic tissues, and organs to small animal live analysis. Toxicological testing and medical drug development are currently strongly broadening. It harbors the promise to substantially impact on various fields of biomedicine, drug discovery, and predictive medicine.As the number of scientific data is rising exponentially, new data analysis tools and strategies like cytomics and nanobioengineering take a lead and get closer to application. Bionanoengineering may strongly support the quantitative data supply, thus strengthening the rational for cytomics approach.

Functional genetic variation of human miRNAs and phenotypic consequences

A large number of human protein-coding genes are finely regulated by one or more microRNAs. Members of this small noncoding RNA family have emerged as important post-transcriptional regulators of gene expression and are involved in a number of disease phenotypes. Variability in the human genome is extensive and includes the common and rare single nucleotide polymorphisms (SNPs) and copy number variations (CNVs). The functional significance of the genome's variability is under intense investigation. In this article we review the emerging literature on how human genomic variation influences the outcome of microRNA targeting and the associated phenotypic effects. Illustrative examples are discussed that demonstrate the biological importance of functional polymorphisms affecting miRNA-mediated gene regulation.

Individual genomes instead of race for personalized medicine

The cost of sequencing and genotyping is aggressively decreasing, enabling pervasive personalized genomic screening for drug reactions. Drug-metabolizing genes have been characterized sufficiently to enable practitioners to go beyond simplistic ethnic characterization and into the precisely targeted world of personal genomics. We examine six drug-metabolizing genes in J. Craig Venter and James Watson, two Caucasian men whose genomes were recently sequenced. Their genetic differences underscore the importance of personalized genomics over a race-based approach to medicine. To attain truly personalized medicine, the scientific community must aim to elucidate the genetic and environmental factors that contribute to drug reactions and not be satisfied with a simple race-based approach.

Assessing the feasibility of GS FLX Pyrosequencing for sequencing the Atlantic salmon genome

Background

With a whole genome duplication event and wealth of biological data, salmonids are excellent model organisms for studying evolutionary processes, fates of duplicated genes and genetic and physiological processes associated with complex behavioral phenotypes. It is surprising therefore, that no salmonid genome has been sequenced. Atlantic salmon (Salmo salar) is a good representative salmonid for sequencing given its importance in aquaculture and the genomic resources available. However, the size and complexity of the genome combined with the lack of a sequenced reference genome from a closely related fish makes assembly challenging. Given the cost and time limitations of Sanger sequencing as well as recent improvements to next generation sequencing technologies, we examined the feasibility of using the Genome Sequencer (GS) FLX pyrosequencing system to obtain the sequence of a salmonid genome. Eight pooled BACs belonging to a minimum tiling path covering ~1 Mb of the Atlantic salmon genome were sequenced by GS FLX shotgun and Long Paired End sequencing and compared with a ninth BAC sequenced by Sanger sequencing of a shotgun library.

Results

An initial assembly using only GS FLX shotgun sequences (average read length 248.5 bp) with ~30× coverage allowed gene identification, but was incomplete even when 126 Sanger-generated BAC-end sequences (~0.09× coverage) were incorporated. The addition of paired end sequencing reads (additional ~26× coverage) produced a final assembly comprising 175 contigs assembled into four scaffolds with 171 gaps. Sanger sequencing of the ninth BAC (~10.5× coverage) produced nine contigs and two scaffolds. The number of scaffolds produced by the GS FLX assembly was comparable to Sanger-generated sequencing; however, the number of gaps was much higher in the GS FLX assembly.

Conclusion

These results represent the first use of GS FLX paired end reads for de novo sequence assembly. Our data demonstrated that this improved the GS FLX assemblies; however, with respect to de novo sequencing of complex genomes, the GS FLX technology is limited to gene mining and establishing a set of ordered sequence contigs. Currently, for a salmonid reference sequence, it appears that a substantial portion of sequencing should be done using Sanger technology.

Genetic variation in an individual human exome

There is much interest in characterizing the variation in a human individual, because this may elucidate what contributes significantly to a person's phenotype, thereby enabling personalized genomics. We focus here on the variants in a person's ‘exome,’ which is the set of exons in a genome, because the exome is believed to harbor much of the functional variation. We provide an analysis of the ∼12,500 variants that affect the protein coding portion of an individual's genome. We identified ∼10,400 nonsynonymous single nucleotide polymorphisms (nsSNPs) in this individual, of which ∼15–20% are rare in the human population. We predict ∼1,500 nsSNPs affect protein function and these tend be heterozygous, rare, or novel. Of the ∼700 coding indels, approximately half tend to have lengths that are a multiple of three, which causes insertions/deletions of amino acids in the corresponding protein, rather than introducing frameshifts. Coding indels also occur frequently at the termini of genes, so even if an indel causes a frameshift, an alternative start or stop site in the gene can still be used to make a functional protein. In summary, we reduced the set of ∼12,500 nonsilent coding variants by ∼8-fold to a set of variants that are most likely to have major effects on their proteins' functions. This is our first glimpse of an individual's exome and a snapshot of the current state of personalized genomics. The majority of coding variants in this individual are common and appear to be functionally neutral. Our results also indicate that some variants can be used to improve the current NCBI human reference genome. As more genomes are sequenced, many rare variants and non-SNP variants will be discovered. We present an approach to analyze the coding variation in humans by proposing multiple bioinformatic methods to hone in on possible functional variation.

Characterizing the functional variation in an individual is an important step towards the era of personalized medicine. Protein-coding exons are thought to be especially enriched in functional variation. In 2007, we published the genome sequence of J. Craig Venter. Here we analyze the genetic variation of J. Craig Venter's exome, focusing on variation in the coding portion of genes, which is thought to contribute significantly to a person's physical make-up. We survey ∼12,500 nonsilent coding variants and, by applying multiple bioinformatic approaches, we reduce the number of potential phenotypic variants by ∼8-fold. Our analysis provides a snapshot of the current state of personalized genomics. We find that <1% of variants are linked to any known phenotypes; this demonstrates the dearth of scientific knowledge for phenotype-genotype associations. However, ∼80% of an individual's nonsynonymous variants are commonly found in the human population and, because phenotypic associations to common variants will be elucidated via genome-wide association studies over the next few years, the capability to interpret personalized genomes will expand and evolve. As sequencing of individual genomes becomes more prevalent, the bioinformatic approaches we present in this study can be used as a paradigm to pursue the study of protein-coding variants for the genomes of many individuals.

More evidence against a causal association between C-reactive protein and diabetes

Bernard Keavney discusses a new study that uses Mendelian randomization to address the nature of the association between CRP and insulin resistance or diabetes.

Is gene discovery research or diagnosis?

The criteria that distinguish human genetic research from clinical molecular diagnosis are frequently practical rather than theoretical. They are driven by the availability and costs of the relevant technologies and the systemic level of scientific fluency in interpreting laboratory results. The guiding principle in the practice of medicine is the primacy of patient care. In the service of this overarching goal the defining characteristic of clinical diagnosis is the definition of the disease entity, even when no immediate treatment is possible. For heritable disorders caused by single-gene defects, identifying the putative causal variant is the goal of molecular diagnostics. Current technologies, costs, and standards of institutional infrastructure have not typically permitted novel gene discovery to be performed within the realm of the clinical laboratory. Discovery is usually funded by self-defined research organizations and carried out by self-defined research personnel with the primary intent of publishing findings in research journals. However, exponential improvements in technological capabilities and the concurrent decline in associated costs seem poised to recast this landscape, bringing to clinical medicine some activities now considered research. Even whole genome resequencing of individual patient DNA is within clinical reach in the foreseeable future.

Positive selection in alternatively spliced exons of human genes

Alternative splicing is a well-recognized mechanism of accelerated genome evolution. We have studied single-nucleotide polymorphisms and human-chimpanzee divergence in the exons of 6672 alternatively spliced human genes, with the aim of understanding the forces driving the evolution of alternatively spliced sequences. Here, we show that alternatively spliced exons and exon fragments (alternative exons) from minor isoforms experience lower selective pressure at the amino acid level, accompanied by selection against synonymous sequence variation. The results of the McDonald-Kreitman test suggest that alternatively spliced exons, unlike exons constitutively included in the mRNA, are also subject to positive selection, with up to 27% of amino acids fixed by positive selection.

Ome sweet ome: what can the genome tell us about the connectome?

Some neuroscientists argue that detailed maps of synaptic connectivity--wiring diagrams--will be needed if we are to understand how the brain underlies behavior and how brain malfunctions underlie behavioral disorders. Such large-scale circuit reconstruction, which has been called connectomics, may soon be possible, owing to numerous advances in technologies for image acquisition and processing. Yet, the community is divided on the feasibility and value of the enterprise. Remarkably similar objections were voiced when the Human Genome Project, now widely viewed as a success, was first proposed. We revisit that controversy to ask if it holds any lessons for proposals to map the connectome.

Emerging DNA sequencing technologies for human genomic medicine

The completion of draft sequences of the human genome represented a remarkable achievement for automated DNA sequencing based on Sanger technology. However, the future requires substantial leaps in sequencing technology such that whole genome sequencing will become a standard component of biomedical research and patient care. In this review we describe current advances that are in early stages of development, but that point toward technology that will enable the onset of genomic medicine encompasses strategies for preventative medicine and intervention based on complete knowledge of an individual's genome.

Aspects of coverage in medical DNA sequencing

Background

DNA sequencing is now emerging as an important component in biomedical studies of diseases like cancer. Short-read, highly parallel sequencing instruments are expected to be used heavily for such projects, but many design specifications have yet to be conclusively established. Perhaps the most fundamental of these is the redundancy required to detect sequence variations, which bears directly upon genomic coverage and the consequent resolving power for discerning somatic mutations.

Results

We address the medical sequencing coverage problem via an extension of the standard mathematical theory of haploid coverage. The expected diploid multi-fold coverage, as well as its generalization for aneuploidy are derived and these expressions can be readily evaluated for any project. The resulting theory is used as a scaling law to calibrate performance to that of standard BAC sequencing at 8× to 10× redundancy, i.e. for expected coverages that exceed 99% of the unique sequence. A differential strategy is formalized for tumor/normal studies wherein tumor samples are sequenced more deeply than normal ones. In particular, both tumor alleles should be detected at least twice, while both normal alleles are detected at least once. Our theory predicts these requirements can be met for tumor and normal redundancies of approximately 26× and 21×, respectively. We explain why these values do not differ by a factor of 2, as might intuitively be expected. Future technology developments should prompt even deeper sequencing of tumors, but the 21× value for normal samples is essentially a constant.

Conclusion

Given the assumptions of standard coverage theory, our model gives pragmatic estimates for required redundancy. The differential strategy should be an efficient means of identifying potential somatic mutations for further study.