Mutations In Protein-coding Sequences Research Articles

Cancer Conformational Landscape Shapes Tumorigenesis.

During tumorigenesis, DNA mutations in protein coding sequences can alter amino acid sequences which can change the structures of proteins. While the 3D structure of mutated proteins has been studied with atomic resolution, the precise impact of somatic mutations on the 3D proteome during malignant transformation remains unknown because methods to reveal in vivo protein structures in high throughput are limited. Here, we measured the accessibility of the lysine ε-amine for chemical modification across proteomes using covalent protein painting (CPP) to indirectly determine alterations in the 3D proteome. CPP is a novel, high-throughput quantitative mass spectrometric method that surveyed a total of 8052 lysine sites across the 60 cell lines of the well-studied anticancer cell line panel (NCI60). Overall, 5.2 structural alterations differentiated any cancer cell line from the other 59. Structural aberrations in 98 effector proteins correlated with the selected presence of 90 commonly mutated proteins in the NCI60 cell line panel, suggesting that different tumor genotypes reshape a limited set of effector proteins. We searched our dataset for druggable conformational aberrations and identified 49 changes in the cancer conformational landscape that correlated with the growth inhibition profiles of 300 drug candidates out of 50,000 small molecules. We found that alterations in heat shock proteins are key predictors of anticancer drug efficacy, which implies that the proteostasis network may have a general but hitherto unrecognized role in maintaining malignancy. Individual lysine sites may serve as biomarkers to guide drug selection or may be directly targeted for anticancer drug development.

Fail-safe genetic codes designed to intrinsically contain engineered organisms

One challenge in engineering organisms is taking responsibility for their behavior over many generations. Spontaneous mutations arising before or during use can impact heterologous genetic functions, disrupt system integration, or change organism phenotype. Here, we propose restructuring the genetic code itself such that point mutations in protein-coding sequences are selected against. Synthetic genetic systems so-encoded should fail more safely in response to most spontaneous mutations. We designed fail-safe codes and simulated their expected effects on the evolution of so-encoded proteins. We predict fail-safe codes supporting expression of 20 or 15 amino acids could slow protein evolution to ∼30% or 0% the rate of standard-encoded proteins, respectively. We also designed quadruplet-codon codes that should ensure all single point mutations in protein-coding sequences are selected against while maintaining expression of 20 or more amino acids. We demonstrate experimentally that a reduced set of 21 tRNAs is capable of expressing a protein encoded by only 20 sense codons, whereas a standard 64-codon encoding is not expressed. Our work suggests that biological systems using rationally depleted but otherwise natural translation systems should evolve more slowly and that such hypoevolvable organisms may be less likely to invade new niches or outcompete native populations.

A Statistical Framework for Mapping Risk Genes from De Novo Mutations in Whole-Genome-Sequencing Studies

Analysis of de novo mutations (DNMs) from sequencing data of nuclear families has identified risk genes for many complex diseases, including multiple neurodevelopmental and psychiatric disorders. Most of these efforts have focused on mutations in protein-coding sequences. Evidence from genome-wide association studies (GWASs) strongly suggests that variants important to human diseases often lie in non-coding regions. Extending DNM-based approaches to non-coding sequences is challenging, however, because the functional significance of non-coding mutations is difficult to predict. We propose a statistical framework for analyzing DNMs from whole-genome sequencing (WGS) data. This method, TADA-Annotations (TADA-A), is a major advance of the TADA method we developed earlier for DNM analysis in coding regions. TADA-A is able to incorporate many functional annotations such as conservation and enhancer marks, to learn from data which annotations are informative of pathogenic mutations, and to combine both coding and non-coding mutations at the gene level to detect risk genes. It also supports meta-analysis of multiple DNM studies, while adjusting for study-specific technical effects. We applied TADA-A to WGS data of ∼300 autism-affected family trios across five studies and discovered several autism risk genes. The software is freely available for all research uses.

Teff, an Orphan Cereal in the Chloridoideae, Provides Insights into the Evolution of Storage Proteins in Grasses.

Seed storage proteins (SSP) in cereals provide essential nutrition for humans and animals. Genes encoding these proteins have undergone rapid evolution in different grass species. To better understand the degree of divergence, we analyzed this gene family in the subfamily Chloridoideae, where the genome of teff (Eragrostis tef) has been sequenced. We find gene duplications, deletions, and rapid mutations in protein-coding sequences. The main SSPs in teff, like other grasses, are prolamins, here called eragrostins. Teff has γ- and δ-prolamins, but has no β-prolamins. One δ-type prolamin (δ1) in teff has higher methionine (33%) levels than in maize (23–25%). The other δ-type prolamin (δ2) has reduced methionine residues (<10%) and is phylogenetically closer to α prolamins. Prolamin δ2 in teff represents an intermediate between δ and α types that appears to have been lost in maize and other Panicoideae, and was replaced by the expansion of α-prolamins. Teff also has considerably larger numbers of α-prolamin genes, which we further divide into five sub-groups, where α2 and α5 represent the most abundant α-prolamins both in number and in expression. In addition, indolines that determine kernel softness are present in teff and the panicoid cereal called foxtail millet (Setaria italica) but not in sorghum or maize, indicating that these genes were only recently lost in some members of the Panicoideae. Moreover, this study provides not only information on the evolution of SSPs in the grass family but also the importance of α-globulins in protein aggregation and germplasm divergence.

The Intolerance of Regulatory Sequence to Genetic Variation Predicts Gene Dosage Sensitivity.

Noncoding sequence contains pathogenic mutations. Yet, compared with mutations in protein-coding sequence, pathogenic regulatory mutations are notoriously difficult to recognize. Most fundamentally, we are not yet adept at recognizing the sequence stretches in the human genome that are most important in regulating the expression of genes. For this reason, it is difficult to apply to the regulatory regions the same kinds of analytical paradigms that are being successfully applied to identify mutations among protein-coding regions that influence risk. To determine whether dosage sensitive genes have distinct patterns among their noncoding sequence, we present two primary approaches that focus solely on a gene’s proximal noncoding regulatory sequence. The first approach is a regulatory sequence analogue of the recently introduced residual variation intolerance score (RVIS), termed noncoding RVIS, or ncRVIS. The ncRVIS compares observed and predicted levels of standing variation in the regulatory sequence of human genes. The second approach, termed ncGERP, reflects the phylogenetic conservation of a gene’s regulatory sequence using GERP++. We assess how well these two approaches correlate with four gene lists that use different ways to identify genes known or likely to cause disease through changes in expression: 1) genes that are known to cause disease through haploinsufficiency, 2) genes curated as dosage sensitive in ClinGen’s Genome Dosage Map, 3) genes judged likely to be under purifying selection for mutations that change expression levels because they are statistically depleted of loss-of-function variants in the general population, and 4) genes judged unlikely to cause disease based on the presence of copy number variants in the general population. We find that both noncoding scores are highly predictive of dosage sensitivity using any of these criteria. In a similar way to ncGERP, we assess two ensemble-based predictors of regional noncoding importance, ncCADD and ncGWAVA, and find both scores are significantly predictive of human dosage sensitive genes and appear to carry information beyond conservation, as assessed by ncGERP. These results highlight that the intolerance of noncoding sequence stretches in the human genome can provide a critical complementary tool to other genome annotation approaches to help identify the parts of the human genome increasingly likely to harbor mutations that influence risk of disease.

Highly constrained intergenic Drosophila ultraconserved elements are candidate ncRNAs.

Eukaryotes contain short (∼80–200 bp) regions that have few or no substitutions among species that represent hundreds of millions of years of evolutionary divergence. These ultraconserved elements (UCEs) are candidates for containing essential functions, but their biological roles remain largely unknown. Here, we report the discovery and characterization of UCEs from 12 sequenced Drosophila species. We identified 98 elements ≥80 bp long with very high conservation across the Drosophila phylogeny. Population genetic analyses reveal that these UCEs are not present in mutational cold spots. Instead we infer that they experience a level of selective constraint almost 10-fold higher compared with missense mutations in protein-coding sequences, which is substantially higher than that observed previously for human UCEs. About one-half of these Drosophila UCEs overlap the transcribed portion of genes, with many of those that are within coding sequences likely to correspond to sites of ADAR-dependent RNA editing. For the remaining UCEs that are in nongenic regions, we find that many are potentially capable of forming RNA secondary structures. Among ten chosen for further analysis, we discovered that the majority are transcribed in multiple tissues of Drosophila melanogaster. We conclude that Drosophila species are rich with UCEs and that many of them may correspond to novel noncoding RNAs.

Rocking the foundations of molecular genetics

In PNAS, Nelson et al. present intriguing evidence that challenges the fundamental tenets of genetics (1). It has long been assumed that the inherited contribution to phenotype is embedded in DNA sequence variations in, and interactions between, the genes endogenous to the organism, i.e., alleles derived from parents with some degree of de novo variation. This assumption underlies most genetic analysis, including the fleet of genome-wide association studies launched in recent years to identify genomic loci that influence complex human traits and diseases. Not surprisingly, in contrast to mutations in protein-coding sequences, which underlie high penetrance monogenic disorders, the vast majority of the identified loci map to non–protein-coding intergenic and intronic regions, which comprise the vast majority of the genome. These regions contain the regulatory information that controls gene expression and underlies most phenotypic variation (2).

Large-Scale CLL Genome Analysis Reveals Novel Cancer Genes, Including SF3B1

Abstract 463The somatic genetic basis of chronic lymphocytic leukemia (CLL), a common and clinically heterogenous adult leukemia, remains poorly understood. Massively parallel sequencing technology provides a method for systematic discovery of genetic alterations that underlie disease, and for uncovering new therapeutic targets and biomarkers. We therefore performed DNA sequencing of 91 CLL samples with matched germline, consisting of 88 exomes and 3 genomes. Samples were collected from patients displaying a range of characteristics representing the broad clinical spectrum of CLL. Libraries were constructed and sequenced on an Illumina GA-II sequencer to deep coverage. Point mutations and indels were detected by comparing sequences of each tumor to its corresponding normal.We detected 1828 non-silent mutations in protein-coding sequences, corresponding to an average somatic mutation rate of 0.72/Mb (range 0.075–2.14). Nine cancer genes were identified, as they were mutated significantly more often than the background rate given their sequence composition across all 91 CLL/normal pairs. Four have been previously described in CLL (TP53, ATM, MYD88 and NOTCH1); the others were novel (SF3B1, ZMYM3, MAPK1, FBXW7 and DDX3X). Strikingly, SF3B1, which functions at the catalytic core of the spliceosome, was mutated the second most frequently (15%). All 14 identified mutations localized to a discrete region (exons 12–18), and 7 were recurrent (K700E). We additionally validated the SF3B1-K700E mutation through genotyping of 101 independent CLL samples. The 9 significantly mutated genes fell into 5 core signaling pathways, in which the genes play established roles: DNA damage repair and cell-cycle control (TP53, ATM), Notch signaling (FBXW7, NOTCH1), inflammatory pathways (MYD88, DDX3X, MAPK1) and RNA splicing/processing (SF3B1, DDX3X).The common cytogenetic aberrations in CLL carry strong prognostic significance, implying that they reflect distinct pathogenesis. Supporting this hypothesis, we discovered strong associations between different driver mutations and key FISH abnormalities. Most TP53 mutations were in samples with del(17p) (p<0.001), resulting in homozygous p53 inactivation. Del(11q) was marginally associated with mutation in ATM which lies in the minimally deleted region of chr. 11q (p=0.09); but clearly associated with SF3B1 mutation (p=0.004), suggesting interaction within this clinical subgroup of CLL. NOTCH1 and FBXW7 mutations (present in independent samples) were associated with trisomy 12 (p=0.009 and 0.05), suggesting that aberrant Notch signaling plays an important role in this clinical subgroup. Finally, all detected mutations in MYD88 (known to be activating for the NFkB pathway) were present in samples harboring heterozygous del(13q) (p=0.009) with mutated IGHV status (p=0.002). These findings suggest that NFkB activation plays a driving role in this low risk clinical subgroup.To define the impact of the mutated cancer genes on disease outcome, we constructed a Cox multivariable regression model for factors contributing to earlier time to first therapy (TTFT) in the 91 CLLs. SF3B1 mutation was predictive of poor prognosis (HR 3.17, p=0.004), independent of other established markers (i.e. IGVH mutation; del(17p); ATM mutation). Consistent with this analysis, patients harboring the SF3B1 mutation alone had short TTFT, as did patients with del(11q) or del(11q)+SF3B1 mutation. All 3 groups demonstrated significantly shorter TTFT than patients without either SF3B1 mutation or del(11q). Because SF3B1 encodes a splicing factor, we looked for functional evidence of splicing alterations associated with SF3B1 mutation. Indeed, mRNA targets of the spliceosome exhibited greater intron retention in CLLs with mutated vs nonmutated SF3B1, confirming alteration in normal SF3B1 function.Understanding the mutational landscape of CLL provides a starting point for systematic analyses to address fundamental questions in CLL, including how mutated genes alter cellular networks and phenotypes, and thereby contribute to disease heterogeneity. Our discovery of striking associations between driver mutations and standard CLL prognostic markers (cytogenetic aberrations, IGVH mutational status) suggest synergistic interactions. In particular, our studies highlight pre-mRNA splicing as a critical but thus far unexplored cellular process contributing to CLL. Disclosures:No relevant conflicts of interest to declare.

The Genetic Signatures of Noncoding RNAs

The majority of the genome in animals and plants is transcribed in a developmentally regulated manner to produce large numbers of non–protein-coding RNAs (ncRNAs), whose incidence increases with developmental complexity. There is growing evidence that these transcripts are functional, particularly in the regulation of epigenetic processes, leading to the suggestion that they compose a hitherto hidden layer of genomic programming in humans and other complex organisms. However, to date, very few have been identified in genetic screens. Here I show that this is explicable by an historic emphasis, both phenotypically and technically, on mutations in protein-coding sequences, and by presumptions about the nature of regulatory mutations. Most variations in regulatory sequences produce relatively subtle phenotypic changes, in contrast to mutations in protein-coding sequences that frequently cause catastrophic component failure. Until recently, most mapping projects have focused on protein-coding sequences, and the limited number of identified regulatory mutations have been interpreted as affecting conventional cis-acting promoter and enhancer elements, although these regions are often themselves transcribed. Moreover, ncRNA-directed regulatory circuits underpin most, if not all, complex genetic phenomena in eukaryotes, including RNA interference-related processes such as transcriptional and post-transcriptional gene silencing, position effect variegation, hybrid dysgenesis, chromosome dosage compensation, parental imprinting and allelic exclusion, paramutation, and possibly transvection and transinduction. The next frontier is the identification and functional characterization of the myriad sequence variations that influence quantitative traits, disease susceptibility, and other complex characteristics, which are being shown by genome-wide association studies to lie mostly in noncoding, presumably regulatory, regions. There is every possibility that many of these variations will alter the interactions between regulatory RNAs and their targets, a prospect that should be borne in mind in future functional analyses.

Genetic Basis of Virulence Attenuation Revealed by Comparative Genomic Analysis of Mycobacterium tuberculosis Strain H37Ra versus H37Rv

Tuberculosis, caused by Mycobacterium tuberculosis, remains a leading infectious disease despite the availability of chemotherapy and BCG vaccine. The commonly used avirulent M. tuberculosis strain H37Ra was derived from virulent strain H37 in 1935 but the basis of virulence attenuation has remained obscure despite numerous studies. We determined the complete genomic sequence of H37Ra ATCC25177 and compared that with its virulent counterpart H37Rv and a clinical isolate CDC1551. The H37Ra genome is highly similar to that of H37Rv with respect to gene content and order but is 8,445 bp larger as a result of 53 insertions and 21 deletions in H37Ra relative to H37Rv. Variations in repetitive sequences such as IS6110 and PE/PPE/PE-PGRS family genes are responsible for most of the gross genetic changes. A total of 198 single nucleotide variations (SNVs) that are different between H37Ra and H37Rv were identified, yet 119 of them are identical between H37Ra and CDC1551 and 3 are due to H37Rv strain variation, leaving only 76 H37Ra-specific SNVs that affect only 32 genes. The biological impact of missense mutations in protein coding sequences was analyzed in silico while nucleotide variations in potential promoter regions of several important genes were verified by quantitative RT-PCR. Mutations affecting transcription factors and/or global metabolic regulations related to in vitro survival under aging stress, and mutations affecting cell envelope, primary metabolism, in vivo growth as well as variations in the PE/PPE/PE-PGRS family genes, may underlie the basis of virulence attenuation. These findings have implications not only for improved understanding of pathogenesis of M. tuberculosis but also for development of new vaccines and new therapeutic agents.

Evolution Rates of Genes on Leading and Lagging DNA Strands

One of the main causes of bacterial chromosome asymmetry is replication-associated mutational pressure. Different rates of nucleotide substitution accumulation on leading and lagging strands implicate qualitative and quantitative differences in the accumulation of mutations in protein coding sequences lying on different DNA strands. We show that the divergence rate of orthologs situated on leading strands is lower than the divergence rate of those situated on lagging strands. The ratio of the mutation accumulation rate for sequences lying on lagging strands to that of sequences lying on leading strands is rather stable and time-independent. The divergence rate of sequences which changed their positions, with respect to the direction of replication fork movement, is not stable-sequences which have recently changed their positions are the most prone to mutation accumulation. This effect may influence estimations of evolutionary distances between species and the topology of phylogenetic trees.