Genome sequencing also revealed the extent of complex genomic rearrangements (CGRs) in disease. Over 700 genomes from different cancers were studied, and 'chromosome catastrophes' were identified in 2 to 3% of all cancers and in up to 25% of bone cancers [2]. This phenomenon, also termed 'chromothripsis' (shattering and regluing of chromosomes), is primarily localized to single chromosomes, but includes multiple structural genomic changes, such as gains, losses and inversions. As a result, chromothripsis can lead to the simultaneous occurrence of mutations in a number of different cancer-causing genes. Cancer is known to be driven by somatically acquired point mutations and chromosomal rearrangements, conventionally thought to accumulate gradually over time. However, chromothripsis is a one-off event resulting in multigenic changes [2]. It remains to be shown whether chromothripsis is a major driver of cancer.

Intriguingly, a similar chromosome catastrophe event that resulted in CGRs was found to be associated with a small fraction of genomic disorders [3]. This involved a germline or constitutional rearrangement event early in embryogenesis rather than somatically acquired mutations and seemed to occur via a DNA-replication-based mechanism. Triplicated genomic segments were also identified within the rearrangements, and microhomology was present at many of the breakpoint junctions. The triplication cannot readily be explained by chromothripsis, as it requires a gain of genetic information, probably resulting from DNA replication. Other CGRs identified in association with genomic disorders included triplications; triplicated dosage-sensitive genes conveyed a more severe clinical phenotype than duplication. Triplications seem to occur by a double crossover event within a flanking low-copy repeat and are tandem in nature, similar to earlier predictions from an unequal crossing-over or non-allelic homologous recombination (NAHR) model [4]. However, many of the observed triplications have a complex 'duplication-inverted triplication-duplication' structure, which requires only two breakpoint junctions. One of these is generated by an initial NAHR event between inverted repeats, and the other occurs by a nonhomologous mechanism, potentially a DNA replication-based mechanism that results in microhomology at the breakpoint junction [5]. The inversion allows distant genomic regions to be brought into spatial proximity.

A summary of 2011 would not be complete without highlighting exome sequencing and its role in the elucidation of the gene(s) responsible for a number of different Mendelian disorders [6]. Genomic studies have so far revealed the tremendous extent of rare variants in individual genomes. This has led to the concept of 'clan genomics' [7], wherein the most relevant medically actionable variation may be rare variants that occurred as novel combinations or as new mutations in your personal genome or that of your nearest relatives.

Recent studies have moved to develop techniques to supply this vital piece of information. Selbach and colleagues [8] used a combination of stable isotope incorporation and MS to quantify pulse-labeled proteins and 4-thiouridine incorporation to quantify newly synthesized RNA in mouse cells. These results showed that genes that respond quickly to stimuli (such as those encoding transcription factors and signaling proteins) have short protein and mRNA half lives. Constitutive processes (such as translation and central metabolism) were populated by genes giving rise to stable proteins and mRNA. A more recent study by Aebersold and colleagues [9] provided an absolute quantitative estimate of approximately 7,000 proteins in a human cell line during exponential and M-phase growth. This study also found that proteins related to translation were found in high abundance, whereas those involved in processes such as transcription and signaling are present in very low abundance. These results are in agreement with those found by Selbach and colleagues [8], with both studies suggesting that the correlation between mRNA and protein levels is greater than previously reported [10,11].

Although it is possible to measure the absolute number of specific proteins within complex mixtures [12], these studies represent a new, hopefully broader, effort in determining the absolute abundances of proteins across an entire proteome. Frankly, without this quantitative information it is impossible to accurately understand cellular processes at a systems-level view.

The gut microbiome is the most extensively studied part of the human microbiome so far, and this past year the international MetaHIT Consortium has consolidated the data to support the existence of a limited number of 'enterotypes', stable clusters of bacterial communities that are common to groups of individuals belonging to different human populations rather than specific for each population [13,14]. Enterotypes are 'well-balanced host-microbial symbiotic states that might respond differently to diet and drug intake' and warrant functional analysis to complement species identification obtained through next-generation sequencing.

The same sequencing approach is being successfully extended to characterize the microbiome in other human tissues, such as nasal passages, oral cavities, skin and urogenital tract within the Human Microbiome Project [15,16]. Significant challenges remain in establishing robust and efficient bioinformatics pipelines to deal with the very large sequence datasets generated [17], but the integration of metagenomics with functional genomics has started to provide new insights into the role of the microbiome in health and in disease susceptibility, diagnosis, progression and treatment, as reviewed extensively by Nicholson and colleagues in this journal [18]. Although emphasis so far has been on bacterial communities, metagenomics provide simultaneous access to fungi, protozoa and viruses, revealing that the vast majority had not been identified through classical culture-based techniques. Functional metagenomics is thus opening a window into an as-yet largely unexplored biological world, and is starting to fill gaps in our knowledge of health and diseases. It is likely that microbiome studies will flourish in the coming years and will contribute to a more personal appraisal of our medical condition and potential response to treatment.

Carbamazepine, an antiepileptic drug also used for treatment of other conditions, including bipolar disorders, and for pain management in trigeminal neuralgia, induces different manifestations of these hypersensitivity reactions. In 2004 the HLA-B*1502 allele was strongly associated with SJS/TEN in Han Chinese people [20]. In a recent study, 4,855 Taiwanese were prospectively screened for the HLA-B*1502 allele before onset of carbamazepine treatment, and all HLA-B*1502-positive people (7.7%) were offered alternative medications to carbamazepine and did not develop SJS/TEN [21]. Although the estimated historical incidence for SJS/TEN in Southeast Asians is 0.23%, no cases of SJS/TEN were identified among the 4,120 study participants treated with carbamazepine. This prospective study clearly indicates that genetic testing for HLA-B*1502 seems to be warranted in clinical practice for the prevention of carbamazepine-associated SJS/TEN in Southeast Asians.

Recent data have suggested that different HLA alleles might contribute to carbamazepine-related hypersensitivity reactions in patients with other ethnic backgrounds [22], and a genome-wide association study (GWAS) found a strong association for the HLA-A*3101 allele in 22 people with Northern European ancestry and carbamazepine-induced hypersensitivity reactions, as compared with 2,691 healthy controls [23]. Whereas the HLA-B*1502 allele seems to be a phenotype-specific predictor for the development of SJS/TEN in Asians, in Europeans the HLA-A*3101 allele seems to be associated with multiple phenotypes of carbamazepine hypersensitivity reactions, including SJS/TEN. In a separate GWAS, multiple HLA class I and II alleles were identified as susceptibility factors for idiosyncratic amoxicillin-clavulanate-induced liver injury, further supporting the importance of genetic variation in the MHC region in idiosyncratic adverse drug reactions [24].

In addition to the major efforts to individualize drug therapy using genomic information alone, metabolomics promises significant achievements towards a better understanding of the potential relevance of genetic variants in disease susceptibility as well as drug therapy, by the study of metabolism at the global level. A highlight in this field was the first analysis that comprehensively combined genomic information (from GWAS) with non-targeted metabolic profiling of serum from subjects of two independent cohorts (n = 2,820) for hypothesis generation [25]. Meta-analysis revealed 37 independent loci with genome-wide significance, providing not only new functional insights for disease susceptibility but also novel biochemical data for genotype-dependent reactions to drug therapy. This approach highlights the enormous potential of integrated analyses for pharmacology and clinical pharmacology in the near future.

Currently, this translational research agenda is much less robust than discovery research, accounting for less than 2% of funded genomics research and research publications [28], but this is likely to change in the next decade as more and more applications make it to the bedside. Ongoing horizon scanning for genomic tests has revealed more than 330 genomic tests have reached the bedside since 2009 [29]. In addition, the US Food and Drug Administration has provided drug labeling information about adverse reactions for more than 80 gene-drug pairs [30].

With rapid improvements in technologies, we are seeing the leading edge of the applications of whole genome sequencing (WGS) in practice primarily in the identification of rare heritable conditions [31]. Deploying WGS in practice will require a systematic evidence-based approach to binning genes and gene variants into tiers based on levels of evidence for improving health; recently, Berg et al. [32] proposed a three-tier binning schema for WGS, based on the availability of information on their clinical validity and utility. The ultimate success of genomics for improving health will require adoption of evidence-based approaches for their use in clinical and public health practice.

The DTC industry has also allowed ELSI researchers to explore popular culture representations of genetics [37], how individuals react to genetic risk information and the motivations behind the use of DTC services [38]. Much of this research has provided surprising results - highlighting both problems (for example, the degree to which the benefits and limitations of testing are often misrepresented [39] and the reality that much provided risk information may be inaccurate [40]) and the fact that some concerns may not be as problematic as previously thought (for example, the degree to which people become anxious after receiving predisposition information [41]). Given the appearance of the DTC industry, ELSI researchers are now contemplating future policy challenges. For example, the use of DTC services for the testing of children and the availability of cheap WGS, which is inevitable in the near future, seem likely to add new and challenging dimensions to the DTC story.