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Human genomics comes of age To mark the tenth anniversary of the publication reporting a draft sequence of the human genome by the Human Genome Project, this issue of Nature presents three major papers about human genomics. Eric Lander, present at the birth of the Human Genome Project, looks back at what has been achieved in genomics and speculates on future prospects. Elaine Mardis discusses the DNA sequencing technologies that have catalysed the rapid genomic advances over the past ten years. And Eric Green, Mark Guyer and others from the US National Human Genome Research Institute provide a vision for the future of genomic medicine. The sequence of the human genome has dramatically accelerated biomedical research. Here I explore its impact, in the decade since its publication, on our understanding of the biological functions encoded in the genome, on the biological basis of inherited diseases and cancer, and on the evolution and history of the human species. I also discuss the road ahead in fulfilling the promise of genomics for medicine.

Genome editing holds great therapeutic promise, but its application in humans would require not only overcoming serious technical challenges but also addressing serious risks and fraught ethical issues. Fifty years ago, microbiologists sparked the recombinant-DNA revolution with the discovery that bacteria have innate immune systems based on restriction enzymes. These enzymes bind and cut invading viral genomes at specific short sequences, and scientists rapidly repurposed them to cut and paste DNA in vitro — transforming biologic science and giving rise to the biotechnology industry. Ten years ago, microbiologists discovered that bacteria also harbor adaptive immune systems, and subsequent progress has been breathtakingly rapid. 1 Between 2005 and 2009, microbial genetic studies conducted by the laboratories of Mojica, Jansen, Koonin, Horvath, van der Oost, Sontheimer, Marraffini, and others revealed that . . .

Eric Lander, Françoise Baylis, Feng Zhang, Emmanuelle Charpentier, Paul Berg and specialists from seven countries call for an international governance framework. Eric Lander, Françoise Baylis, Feng Zhang, Emmanuelle Charpentier, Paul Berg and specialists from seven countries call for an international governance framework. Embryo culture dish used for in vitro fertilisation

Genome-wide association studies (GWASs), also called common variant association studies (CVASs), have uncovered thousands of genetic variants associated with hundreds of diseases. However, the variants that reach statistical significance typically explain only a small fraction of the heritability. One explanation for the “missing heritability” is that there are many additional disease-associated common variants whose effects are too small to detect with current sample sizes. It therefore is useful to have methods to quantify the heritability due to common variation, without having to identify all causal variants. Recent studies applied restricted maximum likelihood (REML) estimation to case–control studies for diseases. Here, we show that REML considerably underestimates the fraction of heritability due to common variation in this setting. The degree of underestimation increases with the rarity of disease, the heritability of the disease, and the size of the sample. Instead, we develop a general framework for heritability estimation, called phenotype correlation–genotype correlation (PCGC) regression, which generalizes the well-known Haseman–Elston regression method. We show that PCGC regression yields unbiased estimates. Applying PCGC regression to six diseases, we estimate the proportion of the phenotypic variance due to common variants to range from 25% to 56% and the proportion of heritability due to common variants from 41% to 68% (mean 60%). These results suggest that common variants may explain at least half the heritability for many diseases. PCGC regression also is readily applicable to other settings, including analyzing extreme-phenotype studies and adjusting for covariates such as sex, age, and population structure. Significance Studies have identified thousands of common genetic variants associated with hundreds of diseases. Yet, these common variants typically account for a minority of the heritability, a problem known as “missing heritability.” Geneticists recently proposed indirect methods for estimating the total heritability attributable to common variants, including those whose effects are too small to allow identification in current studies. Here, we show that these methods seriously underestimate the true heritability when applied to case–control studies of disease. We describe a method that provides unbiased estimates. Applying it to six diseases, we estimate that common variants explain an average of 60% of the heritability for these diseases. The framework also may be applied to case–control studies, extreme-phenotype studies, and other settings.

The bacterial clustered regularly interspaced short palindromic repeats (CRISPR)–Cas9 system for genome editing has greatly expanded the toolbox for mammalian genetics, enabling the rapid generation of isogenic cell lines and mice with modified alleles. Here, we describe a pooled, loss-of-function genetic screening approach suitable for both positive and negative selection that uses a genome-scale lentiviral single-guide RNA (sgRNA) library. sgRNA expression cassettes were stably integrated into the genome, which enabled a complex mutant pool to be tracked by massively parallel sequencing. We used a library containing 73,000 sgRNAs to generate knockout collections and performed screens in two human cell lines. A screen for resistance to the nucleotide analog 6-thioguanine identified all expected members of the DNA mismatch repair pathway, whereas another for the DNA topoisomerase II (TOP2A) poison etoposide identified TOP2A, as expected, and also cyclin-dependent kinase 6, CDK6. A negative selection screen for essential genes identified numerous gene sets corresponding to fundamental processes. Last, we show that sgRNA efficiency is associated with specific sequence motifs, enabling the prediction of more effective sgRNAs. Collectively, these results establish Cas9/sgRNA screens as a powerful tool for systematic genetic analysis in mammalian cells.

Human genetics has been haunted by the mystery of \"missing heritability\" of common traits. Although studies have discovered >1,200 variants associated with common diseases and traits, these variants typically appear to explain only a minority of the heritability. The proportion of heritability explained by a set of variants is the ratio of (i) the heritability due to these variants (numerator), estimated directly from their observed effects, to (ii) the total heritability (denominator), inferred indirectly from population data. The prevailing view has been that the explanation for missing heritability lies in the numerator—that is, in as-yet undiscovered variants. While many variants surely remain to be found, we show here that a substantial portion of missing heritability could arise from overestimation of the denominator, creating \"phantom heritability.\" Specifically, (i) estimates of total heritability implicitly assume the trait involves no genetic interactions (epistasis) among loci; (ii) this assumption is not justified, because models with interactions are also consistent with observable data; and (iii) under such models, the total heritability may be much smaller and thus the proportion of heritability explained much larger. For example, 80% of the currently missing heritability for Crohn's disease could be due to genetic interactions, if the disease involves interaction among three pathways. In short, missing heritability need not directly correspond to missing variants, because current estimates of total heritability may be significantly inflated by genetic interactions. Finally, we describe a method for estimating heritability from isolated populations that is not inflated by genetic interactions.

Purpose of Review Esophageal cancer (EC) is a common cancer affecting many regions of the world and carries significant morbidity and mortality. In this article, we review the key risk factors and their associated impact on the changing incidence and prevalence of EC subtypes within different global regions. We also highlight potential reasons for the ever-changing epidemiology of this prevalent cancer type. Recent Findings There has been a shift in incidence of Esophageal Adenocarcinoma (AC) and Squamous Cell Carcinoma (SCC) within certain populations primarily due to an increase prevalence of primary risk factors. In Western nations, more often the United States, there has been a shift from SCC predominance to the majority of new cases of EC being adenocarcinoma. This shift within the United States has largely correlated with a rise in obesity. The prevalence of AC in Asia is also starting to rise as more countries adopt a western diet. Summary The pathophysiology, associated risk factors, and presentation of ESCC and AC are different. This difference is seen in varying lifestyles, population health, and certain genetic risks. With further development closer analysis of primary risk factors and implementation of policies and programs that promote public health literacy, there is a potential to decrease esophageal cancer’s global disease burden.

Various cis -regulatory functions of genomic loci that produce long non-coding RNAs are revealed, including instances where their promoters have enhancer-like activity and the lncRNA transcripts themselves are not required for activity. The search for lncRNA function Since the discovery of pervasive transcription of long non-coding RNAs (lncRNAs) in mammalian genomes, there has been pressure to determine their functions. Here, Eric Lander and colleagues use a CRISPR/Cas9 deletion approach to uncover various cis -regulatory functions of lncRNAs, including instances in which their promoters have enhancer-like activity and the lncRNA transcripts themselves are often not required for activity. Such effects on neighbouring genes are also seen for protein-coding loci. Mammalian genomes are pervasively transcribed 1 , 2 to produce thousands of long non-coding RNAs (lncRNAs) 3 , 4 . A few of these lncRNAs have been shown to recruit regulatory complexes through RNA–protein interactions to influence the expression of nearby genes 5 , 6 , 7 , and it has been suggested that many other lncRNAs can also act as local regulators 8 , 9 . Such local functions could explain the observation that lncRNA expression is often correlated with the expression of nearby genes 2 , 10 , 11 . However, these correlations have been challenging to dissect 12 and could alternatively result from processes that are not mediated by the lncRNA transcripts themselves. For example, some gene promoters have been proposed to have dual functions as enhancers 13 , 14 , 15 , 16 , and the process of transcription itself may contribute to gene regulation by recruiting activating factors or remodelling nucleosomes 10 , 17 , 18 . Here we use genetic manipulation in mouse cell lines to dissect 12 genomic loci that produce lncRNAs and find that 5 of these loci influence the expression of a neighbouring gene in cis . Notably, none of these effects requires the specific lncRNA transcripts themselves and instead involves general processes associated with their production, including enhancer-like activity of gene promoters, the process of transcription, and the splicing of the transcript. Furthermore, such effects are not limited to lncRNA loci: we find that four out of six protein-coding loci also influence the expression of a neighbour. These results demonstrate that cross-talk among neighbouring genes is a prevalent phenomenon that can involve multiple mechanisms and cis- regulatory signals, including a role for RNA splice sites. These mechanisms may explain the function and evolution of some genomic loci that produce lncRNAs and broadly contribute to the regulation of both coding and non-coding genes.

Large-scale genetic analysis of lethal phenotypes has elucidated the molecular underpinnings of many biological processes. Using the bacterial clustered regularly interspaced short palindromic repeats (CRISPR) system, we constructed a genome-wide single-guide RNA library to screen for genes required for proliferation and survival in a human cancer cell line. Our screen revealed the set of cell-essential genes, which was validated with an orthogonal gene-trap–based screen and comparison with yeast gene knockouts. This set is enriched for genes that encode components of fundamental pathways, are expressed at high levels, and contain few inactivating polymorphisms in the human population. We also uncovered a large group of uncharacterized genes involved in RNA processing, a number of whose products localize to the nucleolus. Last, screens in additional cell lines showed a high degree of overlap in gene essentiality but also revealed differences specific to each cell line and cancer type that reflect the developmental origin, oncogenic drivers, paralogous gene expression pattern, and chromosomal structure of each line. These results demonstrate the power of CRISPR-based screens and suggest a general strategy for identifying liabilities in cancer cells.

The new Precision Medicine Initiative will require advances in our regulatory frameworks, especially for genomic testing. The FDA has been exploring radical new approaches, aiming to promote rapid innovation while ensuring safety and efficacy. In his 2015 State of the Union address, President Barack Obama announced a new Precision Medicine Initiative (PMI), a national investment in research on approaches to disease treatment and prevention that take into account individual variability in each person's genes, environment, and lifestyle. In a recent Perspective article, Francis Collins and Harold Varmus sketched out initial ideas for the PMI research plans as envisioned by the National Institutes of Health (NIH). 1 But scientific progress alone won't guarantee that the public reaps the full benefits of precision medicine — an achievement that, as Collins and Varmus note, “will also require advancing the . . .