Arginine Depletion in Human Cancers

Arginine is encoded by six different codons. Base pair changes in any of these codons can have a broad spectrum of effects including substitutions to twelve different amino acids, eighteen synonymous changes, and two stop codons. Four amino acids (histidine, cysteine, glutamine, and tryptophan) account for over 75% of amino acid substitutions of arginine. This suggests that a mutational bias, or “purifying selection”, mechanism is at work. This bias appears to be driven by C > T and G > A transitions in four of the six arginine codons, a signature that is universal and independent of cancer tissue of origin or histology. Here, we provide a review of the available literature and reanalyze publicly available data from the Catalogue of Somatic Mutations in Cancer (COSMIC). Our analysis identifies several genes with an arginine substitution bias. These include known factors such as IDH1, as well as previously unreported genes, including four cancer driver genes (FGFR3, PPP6C, MAX, GNAQ). We propose that base pair substitution bias and amino acid physiology both play a role in purifying selection. This model may explain the documented arginine substitution bias in cancers.

Mitochondrial mutational spectrum is associated with mammalian longevity: a novel signature of oxidative damage.

The mutational spectrum of the mitochondrial DNA (mtDNA) does not resemble any of the known mutational signatures of the nuclear genome and variation in mtDNA mutational spectra between different tissues and organisms is still incomprehensible. Since mitochondria is tightly involved in aerobic energy production, it is expected that mtDNA mutational spectra may be affected by the oxidative damage which is increasing with organismal aging. However, the well-documented mutational signature of the oxidative damage, G>T substitutions, is typical only for the nuclear genome while it is extremely rare in mtDNA. Thus it is still unclear if there is a mitochondria-specific mutational signature of the oxidative damage. Here, reconstructing mtDNA mutational spectra for 424 mammalian species with variable generation length which is a proxy for oocyte age, we observed that the frequency of AH>GH substitutions (H - heavy chain notation) is positively correlated with organismal longevity. This mutational bias from AH to GH significantly affected the nucleotide content of analyzed 650 complete mammalian mitochondrial genomes, where fourfold degenerative synonymous positions of long-lived species become more AH poor and GH rich. Because (i) A>G is a substitution, typical for mtDNA; (ii) it is characterized by very strong asymmetry: A>G is several-fold more frequent on a heavy chain as compared to the light one; (iii) it is sensitive to the time being single-stranded during mtDNA asynchronous replication; (iv) it is associated with oxidative damage of single-stranded DNA in recent experimental studies we propose that A>G is a novel mutational signature of age-associated oxidative damage of single-stranded mtDNA. The described association of the mtDNA mutational spectra with a species-specific life-history trait can significantly affect general patterns of molecular evolution of mtDNA.

TERT Promoter Mutations Increase Sense and Antisense Transcription from the TERT Promoter

Background: Chief among mechanisms of telomerase reverse transcriptase (TERT) reactivation is the appearance of mutations in the TERT promoter. The two main TERT promoter mutations are C>T transitions located −146C>T and −124C>T upstream from the translational start site. They generate a novel Ets/TCF binding site. Both mutations are mutually exclusive and −124C>T is strikingly overrepresented in most cancers. We investigated whether this mutational bias and mutual exclusion could be due to transcriptional constraints. Methods: We compared sense and antisense transcription of a panel of TERT promoter-luciferase vectors harboring the −124C>T and -146C>T mutations alone or together. lncRNA TAPAS levels were measured by RT-PCR. Results: Both mutations generally increased TERT transcription by 2–4-fold regardless of upstream and downstream regulatory elements. The double mutant increased transcription in an additive fashion, arguing against a direct transcriptional constraint. The −146C>T mutation, alone or in combination with −124C>T, also unleashed antisense transcription. In line with this finding, lncRNA TAPAS was higher in cells with mutated TERT promoter (T98G and U87) than in cells with wild-type promoter, suggesting that lncRNA TAPAS may balance the effect of TERT promoter mutations. Conclusions: −146C>T and −124C>T TERT promoter mutations increase TERT sense and antisense transcription, and the double mutant features higher transcription levels. Increased antisense transcription may contain TERT expression within sustainable levels.

Integrating genomics and multivariate evolutionary quantitative genetics: a case study of constraints on sexual selection in Drosophila serrata

In evolutionary quantitative genetics, the genetic variance–covariance matrix, G , and the vector of directional selection gradients, β , are key parameters for predicting multivariate selection responses and genetic constraints. Historically, investigations of G and β have not overlapped with those dissecting the genetic basis of quantitative traits. Thus, it remains unknown whether these parameters reflect pleiotropic effects at individual loci. Here, we integrate multivariate genome-wide association study (GWAS) with G and β estimation in a well-studied system of multivariate constraint: sexual selection on male cuticular hydrocarbons (CHCs) in Drosophila serrata . In a panel of wild-derived re-sequenced lines, we augment genome-based restricted maximum likelihood to estimate G alongside multivariate single nucleotide polymorphism (SNP) effects, detecting 532 significant associations from 1 652 276 SNPs. Constraint was evident, with β lying in a direction of G with low evolvability. Interestingly, minor frequency alleles typically increased male CHC-attractiveness suggesting opposing natural selection on β . SNP effects were significantly misaligned with the major eigenvector of G , g max , but well aligned to the second and third eigenvectors g 2 and g 3 . We discuss potential factors leading to these varied results including multivariate stabilizing selection and mutational bias. Our framework may be useful as researchers increasingly access genomic methods to study multivariate selection responses in wild populations.

The population frequency of human mitochondrial DNA variants is highly dependent upon mutational bias

Next-generation sequencing can quickly reveal genetic variation potentially linked to heritable disease. As databases encompassing human variation continue to expand, rare variants have been of high interest, since the frequency of a variant is expected to be low if the genetic change leads to a loss of fitness or fecundity. However, the use of variant frequency when seeking genomic changes linked to disease remains very challenging. Here, we explore the role of selection in controlling human variant frequency using the HelixMT database, which encompasses hundreds of thousands of mitochondrial DNA (mtDNA) samples. We find that a substantial number of synonymous substitutions, which have no effect on protein sequence, were never encountered in this large study, while many other synonymous changes are found at very low frequencies. Further analyses of human and mammalian mtDNA datasets indicate that the population frequency of synonymous variants is predominantly determined by mutational biases rather than by strong selection acting upon nucleotide choice. Our work has important implications that extend to the interpretation of variant frequency for non-synonymous substitutions.

Integrated gene analyses of de novo mutations from 46,612 trios with autism and developmental disorders

ABSTRACTMost genetic studies consider autism spectrum disorder (ASD) and developmental disorder (DD) separately despite overwhelming comorbidity and shared genetic etiology. Here we analyzed de novo mutations (DNMs) from 15,560 ASD (6,557 are new) and 31,052 DD trios independently and combined as broader neurodevelopmental disorders (NDD) using three models. We identify 615 candidate genes (FDR 5%, 189 potentially novel) by one or more models, including 138 reaching exome-wide significance (p < 3.64e-07) in all models. We find no evidence for ASD-specific genes in contrast to 18 genes significantly enriched for DD. There are 53 genes show particular mutational-bias including enrichments for missense (n=41) or truncating DNM (n=12). We find 22 genes with evidence of sex-bias including five X chromosome genes also with significant female burden (DDX3X, MECP2, SMC1A, WDR45, and HDAC8). NDD risk genes group into five functional networks associating with different brain developmental lineages based on single-cell nuclei transcriptomic data, which provides important insights into disease subtypes and future functional studies.

Variability in Codon Usage in Coronaviruses Is Mainly Driven by Mutational Bias and Selective Constraints on CpG Dinucleotide

The Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the third human-emerged virus of the 21st century from the Coronaviridae family, causing the ongoing coronavirus disease 2019 (COVID-19) pandemic. Due to the high zoonotic potential of coronaviruses, it is critical to unravel their evolutionary history of host species breadth, host-switch potential, adaptation and emergence, to identify viruses posing a pandemic risk in humans. We present here a comprehensive analysis of the composition and codon usage bias of the 82 Orthocoronavirinae members, infecting 47 different avian and mammalian hosts. Our results clearly establish that synonymous codon usage varies widely among viruses, is only weakly dependent on their primary host, and is dominated by mutational bias towards AU-enrichment and by CpG avoidance. Indeed, variation in GC3 explains around 34%, while variation in CpG frequency explains around 14% of total variation in codon usage bias. Further insight on the mutational equilibrium within Orthocoronavirinae revealed that most coronavirus genomes are close to their neutral equilibrium, the exception being the three recently infecting human coronaviruses, which lie further away from the mutational equilibrium than their endemic human coronavirus counterparts. Finally, our results suggest that, while replicating in humans, SARS-CoV-2 is slowly becoming AU-richer, likely until attaining a new mutational equilibrium.

Mutational bias in spermatogonia impacts the anatomy of regulatory sites in the human genome

Mutation in the germline is the ultimate source of genetic variation, but little is known about the influence of germline chromatin structure on mutational processes. Using ATAC-seq, we profile the open chromatin landscape of human spermatogonia, the most proliferative cell type of the germline, identifying transcription factor binding sites (TFBSs) and PRDM9 binding sites, a subset of which will initiate meiotic recombination. We observe an increase in rare structural variant (SV) breakpoints at PRDM9-bound sites, implicating meiotic recombination in the generation of structural variation. Many germline TFBSs, such as NRF1, are also associated with increased rates of SV breakpoints, apparently independent of recombination. Singleton short insertions (≥5 bp) are highly enriched at TFBSs, particularly at sites bound by testis active TFs, and their rates correlate with those of structural variant breakpoints. Short insertions often duplicate the TFBS motif, leading to clustering of motif sites near regulatory regions in this male-driven evolutionary process. Increased mutation loads at germline TFBSs disproportionately affect neural enhancers with activity in spermatogonia, potentially altering neurodevelopmental regulatory architecture. Local chromatin structure in spermatogonia is thus pervasive in shaping both evolution and disease.

Integrating genomics and multivariate evolutionary quantitative genetics: A case study of multivariate constraints on sexual selection in Drosophila serrata

In evolutionary quantitative genetics, the genetic variance-covariance matrix, G, and the vector of directional selection gradients, β , are key parameters for predicting multivariate selection responses and genetic constraints. Historically, investigations of G and β have not overlapped with those dissecting the genetic basis of quantitative traits. Thus, it remains unknown whether these parameters reflect pleiotropic effects at individual loci. Here, we integrate multivariate GWAS with G and β estimation in a well-studied system of multivariate constraint; sexual selection on male cuticular hydrocarbons (CHCs) in Drosophila serrata. In a panel of wild-derived resequenced lines, we augment genome-based REML, (GREML) to estimate G alongside multivariate SNP effects, detecting 532 significant associations from 1,652,276 SNPs. Constraint was evident, with β lying in a direction of G with low evolvability. Interestingly, minor frequency alleles typically increased male CHC-attractiveness suggesting opposing natural selection on β. SNP effects were significantly misaligned with the major eigenvector of G, gmax, but well aligned to the second and third eigenvectors g2 and g3. We discuss potential factors leading to these varied results including multivariate stabilising selection and mutational bias. Our framework may be useful as researchers increasingly access genomic methods to study multivariate selection responses in wild populations.