The Heroes of CRISPR Lander, Eric S.
Cell,
01/2016, Letnik:
164, Številka:
1-2
Journal Article
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Three years ago, scientists reported that CRISPR technology can enable precise and efficient genome editing in living eukaryotic cells. Since then, the method has taken the scientific community by ...storm, with thousands of labs using it for applications from biomedicine to agriculture. Yet, the preceding 20-year journey—the discovery of a strange microbial repeat sequence; its recognition as an adaptive immune system; its biological characterization; and its repurposing for genome engineering—remains little known. This Perspective aims to fill in this backstory—the history of ideas and the stories of pioneers—and draw lessons about the remarkable ecosystem underlying scientific discovery.
Eric Lander provides his perspectives on the personal stories of scientists who discovered the CRISPR system, unraveled its molecular mechanisms, and repurposed it as a powerful tool for biological research and biomedicine.
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.
Recent advances in genome engineering technologies based on the CRISPR-associated RNA-guided endonuclease Cas9 are enabling the systematic interrogation of mammalian genome function. Analogous to the ...search function in modern word processors, Cas9 can be guided to specific locations within complex genomes by a short RNA search string. Using this system, DNA sequences within the endogenous genome and their functional outputs are now easily edited or modulated in virtually any organism of choice. Cas9-mediated genetic perturbation is simple and scalable, empowering researchers to elucidate the functional organization of the genome at the systems level and establish causal linkages between genetic variations and biological phenotypes. In this Review, we describe the development and applications of Cas9 for a variety of research or translational applications while highlighting challenges as well as future directions. Derived from a remarkable microbial defense system, Cas9 is driving innovative applications from basic biology to biotechnology and medicine.
Lessons from the Cancer Genome Garraway, Levi A.; Lander, Eric S.
Cell,
03/2013, Letnik:
153, Številka:
1
Journal Article
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Systematic studies of the cancer genome have exploded in recent years. These studies have revealed scores of new cancer genes, including many in processes not previously known to be causal targets in ...cancer. The genes affect cell signaling, chromatin, and epigenomic regulation; RNA splicing; protein homeostasis; metabolism; and lineage maturation. Still, cancer genomics is in its infancy. Much work remains to complete the mutational catalog in primary tumors and across the natural history of cancer, to connect recurrent genomic alterations to altered pathways and acquired cellular vulnerabilities, and to use this information to guide the development and application of therapies.
Large noncoding RNAs are emerging as an important component in cellular regulation. Considerable evidence indicates that these transcripts act directly as functional RNAs rather than through an ...encoded protein product. However, a recent study of ribosome occupancy reported that many large intergenic ncRNAs (lincRNAs) are bound by ribosomes, raising the possibility that they are translated into proteins. Here, we show that classical noncoding RNAs and 5′ UTRs show the same ribosome occupancy as lincRNAs, demonstrating that ribosome occupancy alone is not sufficient to classify transcripts as coding or noncoding. Instead, we define a metric based on the known property of translation whereby translating ribosomes are released upon encountering a bona fide stop codon. We show that this metric accurately discriminates between protein-coding transcripts and all classes of known noncoding transcripts, including lincRNAs. Taken together, these results argue that the large majority of lincRNAs do not function through encoded proteins.
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•Ribosome occupancy levels of lincRNAs are similar to classical ncRNAs and 5′ UTRs•Ribosome occupancy does not distinguish between protein-coding and noncoding RNAs•Protein-coding RNAs show ribosome release at stop codons, and known ncRNAs do not•lincRNAs do not show evidence of ribosome release for any open reading frame
A reanalysis of ribosome profiling data from mammalian noncoding RNAs reveals that, although many large ncRNAs engage with ribosomes, the binding pattern is different from messenger RNAs, which is consistent with the ncRNAs operating through mechanisms that do not rely on protein coding potential.
Cancer cells within individual tumors often exist in distinct phenotypic states that differ in functional attributes. While cancer cell populations typically display distinctive equilibria in the ...proportion of cells in various states, the mechanisms by which this occurs are poorly understood. Here, we study the dynamics of phenotypic proportions in human breast cancer cell lines. We show that subpopulations of cells purified for a given phenotypic state return towards equilibrium proportions over time. These observations can be explained by a Markov model in which cells transition stochastically between states. A prediction of this model is that, given certain conditions, any subpopulation of cells will return to equilibrium phenotypic proportions over time. A second prediction is that breast cancer stem-like cells arise de novo from non-stem-like cells. These findings contribute to our understanding of cancer heterogeneity and reveal how stochasticity in single-cell behaviors promotes phenotypic equilibrium in populations of cancer cells.
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► Cancer cell populations interconvert between phenotypic states ► Cell-state transitions can be described with a stochastic Markov model ► Markov model predicts convergence to equilibrium phenotypic proportions ► Cancer stem cells can arise de novo from noncancer stem cells
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.
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.
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.
Clonal evolution is a key feature of cancer progression and relapse. We studied intratumoral heterogeneity in 149 chronic lymphocytic leukemia (CLL) cases by integrating whole-exome sequence and copy ...number to measure the fraction of cancer cells harboring each somatic mutation. We identified driver mutations as predominantly clonal (e.g., MYD88, trisomy 12, and del(13q)) or subclonal (e.g., SF3B1 and TP53), corresponding to earlier and later events in CLL evolution. We sampled leukemia cells from 18 patients at two time points. Ten of twelve CLL cases treated with chemotherapy (but only one of six without treatment) underwent clonal evolution, predominantly involving subclones with driver mutations (e.g., SF3B1 and TP53) that expanded over time. Furthermore, presence of a subclonal driver mutation was an independent risk factor for rapid disease progression. Our study thus uncovers patterns of clonal evolution in CLL, providing insights into its stepwise transformation, and links the presence of subclones with adverse clinical outcomes.
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► Whole-exome analysis of clonal heterogeneity in 149 chronic lymphocytic leukemias ► Earlier and later mutations in the temporal evolution of CLL are identified ► Clonal evolution is commonly seen with treatment, typically in a branched pattern ► A subclonal driver in a pretreatment sample is associated with adverse outcome
The intratumoral heterogeneity in 149 chronic lymphocytic leukemia (CLL) cases was evaluated by whole-exome sequencing. The evolutionary patterns of distinct clones enabled a temporal ordering of mutations in CLL, revealed the association of clonal evolution with chemotherapy, and linked the presence of subclonal driver mutations with adverse clinical outcomes.