Measuring the distribution of fitness effects in somatic evolution by combining clonal dynamics with dN/dS ratios

Complete chloroplast genome of eight Phaius (Orchidaceae) species from China: comparative analysis and phylogenetic relationship

BACKGROUND

Phaius Lour. (Collabieae, Orchidaceae) is a small genus consisting of about 45 species, with highly ornamental and medicinal values. However, the phylogenetic relationship of Phaius among Calanthe s. l. has been highly debated based on morphological and molecular data. The complete chloroplast (cp) genome has been widely used as a useful molecular marker for resolving phylogenetic problems, while few genomic data on Phaius was available. Therefore, complete cp genomes of eight Phaius species were sequenced and characterized in detail to provide a better understanding of its phylogenetics in Calanthe s. l.

RESULTS

The cp genomes of eight species investigated exhibited conserved quadripartite structures with varied lengths ranging between 157,997 bp to 158,735 bp. The overall GC content of these genomes ranged between 36.82 and 36.97%. Gene annotation revealed 136 genes in all eight genomes, of which 21 were duplicated in inverted regions and 15 with introns. Comparative analysis of eight cp genomes revealed stable sequence identity with greater variation in the single-copy regions, alongside notable differences in the genes at the LSC/IRb and IRb/SSC junctions, as well as in the number of SSRs. The phylogenetic analysis based on CDS from 49 complete cp genomes of Collabieae indicated that the eight Phaius species, together with other two species P. philippinensis and P. hainanensis, were clustered into a monophyletic clade among Calanthe s. l. and divided into two subclades with strong supports. Additionally, it was also supported that Calanthe s. l. should be divided into five genera with strong supports, including Calanthe s. s., Cephalantheropsis, Styloglossum, Phaius, and Preptanthe.

CONCLUSIONS

It was the first report on the complete cp genome of six Phaius species (P. columnaris, P. mishmensis, P. takeoi, P. tonkinensis, P. wallichii and P. wenshanensis) and has been comparatively analyzed in detail with P. flavus and P. tancarvilleae. It provided a comprehensive investigation of various cp genomic features for phylogenetic implications, including overall genome structure, codon usage, repeat sequences, IR boundaries, DNA polymorphisms, and phylogenetic reconstruction. It was suggested that Phaius and Calanthe s. s. should be treated as two independent genera. The concept of new genus Paraphaius was not confirmed by complete cp genomic data here. The intergeneric relationship of Phaius and its alliance in Calanthe group could be understood better by more cp genomic data.

Complete chloroplast genome data reveal the existence of the Solidago canadensis L. complex and its potential introduction pathways into China

Solidago canadensis, native to North America, is an invasive species in many areas of the world, where it causes serious damage to natural ecosystems and economic losses. However, a dearth of genetic resources and molecular markers has hampered our understanding of its invasion history. Here, we de novo assembled 40 complete chloroplast genomes of Solidago species, including 21 S. canadensis individuals, 15 S. altissima individuals, and four S. decurrens individuals, the sizes of which ranged from 152,412 bp to 153,170 bp. The phylogenetic trees based on the complete chloroplast genome sequences and nuclear genome-wide SNP data showed that S. canadensis and S. altissima cluster together and form a monophyletic pair, as sister to S. decurrens, indicating the existence of the S. canadensis L. complex in China. Three potential introduction pathways were identified. The chloroplast-genome structure and gene contents are conservative in the genomes of the S. canadensis L. complex and S. decurrens. The analysis of sequence divergence indicated five variable regions, and 10 chloroplast protein-coding genes that underwent positive selection were identified. Our findings shed new light on the invasion history of S. canadensis and the data sets generated in this study will facilitate future research on its chloroplast genome evolution.

Complete chloroplast genome structural characterization of two Aerides (Orchidaceae) species with a focus on phylogenetic position of Aerides flabellata

BACKGROUND

The disputed phylogenetic position of Aerides flabellata Rolfe ex Downie, due to morphological overlaps with related species, was investigated based on evidence of complete chloroplast (cp) genomes. The structural characterization of complete cp genomes of A. flabellata and A. rosea Lodd. ex Lindl. & Paxton were analyzed and compared with those of six related species in "Vanda-Aerides alliance" to provide genomic information on taxonomy and phylogeny.

RESULTS

The cp genomes of A. flabellata and A. rosea exhibited conserved quadripartite structures, 148,145 bp and 147,925 bp in length, with similar GC content (36.7 ~ 36.8%). Gene annotations revealed 110 single-copy genes, 18 duplicated in inverted regions, and ten with introns. Comparative analysis across related species confirmed stable sequence identity and higher variation in single-copy regions. However, there are notable differences in the IR regions between two Aerides Lour. species and the other six related species. The phylogenetic analysis based on CDS from complete cp genomes indicated that Aerides species except A. flabellata formed a monophyletic clade nested in the subtribe Aeridinae, being a sister group to Renanthera Lour., consistent with previous studies. Meanwhile, a separate clade consisted of A. flabellata and six Vanda R. Br. species was formed, as a sister taxon to Holcoglossum Schltr.

CONCLUSIONS

This research was the first report on the complete cp genomes of A. flabellata. The results provided insights into understanding of plastome evolution and phylogenetic relationships of Aerides. The phylogenetic analysis based on complete cp genomes showed that A. flabellata should be placed in Vanda rather than in Aerides.

Genomic insights into local-scale evolution of ocular Chlamydia trachomatis strains within and between individuals in Gambian trachoma-endemic villages

Trachoma, a neglected tropical disease caused by Chlamydia trachomatis (Ct) serovars A-C, is the leading infectious cause of blindness worldwide. Africa bears the highest burden, accounting for over 86 % of global trachoma cases. We investigated Ct serovar A (SvA) and B (SvB) whole genome sequences prior to the induction of mass antibiotic drug administration in The Gambia. Here, we explore the factors contributing to Ct strain diversification and the implications for Ct evolution within the context of ocular infection. A cohort study in 2002-2003 collected ocular swabs across nine Gambian villages during a 6 month follow-up study. To explore the genetic diversity of Ct within and between individuals, we conducted whole-genome sequencing (WGS) on a limited number (n=43) of Ct-positive samples with an omcB load ≥10 from four villages. WGS was performed using target enrichment with SureSelect and Illumina paired-end sequencing. Out of 43 WGS samples, 41 provided sufficient quality for further analysis. ompA analysis revealed that 11 samples had highest identity to ompA from strain A/HAR13 (NC_007429) and 30 had highest identity to ompA from strain B/Jali20 (NC_012686). While SvB genome sequences formed two distinct village-driven subclades, the heterogeneity of SvA sequences led to the formation of many individual branches within the Gambian SvA subclade. Comparing the Gambian SvA and SvB sequences with their reference strains, Ct A/HAR13 and Ct B/Jali20, indicated an single nucleotide polymorphism accumulation rate of 2.4×10-5 per site per year for the Gambian SvA and 1.3×10-5 per site per year for SvB variants (P<0.0001). Variant calling resulted in a total of 1371 single nucleotide variants (SNVs) with a frequency >25 % in SvA sequences, and 438 SNVs in SvB sequences. Of note, in SvA variants, highest evolutionary pressure was recorded on genes responsible for host cell modulation and intracellular survival mechanisms, whereas in SvB variants this pressure was mainly on genes essential for DNA replication/repair mechanisms and protein synthesis. A comparison of the sequences between observed separate infection events (4-20 weeks between infections) suggested that the majority of the variations accumulated in genes responsible for host-pathogen interaction such as CTA_0166 (phospholipase D-like protein), CTA_0498 (TarP) and CTA_0948 (deubiquitinase). This comparison of Ct SvA and SvB variants within a trachoma endemic population focused on their local evolutionary adaptation. We found a different variation accumulation pattern in the Gambian SvA chromosomal genes compared with SvB, hinting at the potential of Ct serovar-specific variation in diversification and evolutionary fitness. These findings may have implications for optimizing trachoma control and prevention strategies.

Phased genomics reveals hidden somatic mutations and provides insight into fruit development in sweet orange

Although revisiting the discoveries and implications of genetic variations using phased genomics is critical, such efforts are still lacking. Somatic mutations represent a crucial source of genetic diversity for breeding and are especially remarkable in heterozygous perennial and asexual crops. In this study, we focused on a diploid sweet orange (Citrus sinensis) and constructed a haplotype-resolved genome using high fidelity (HiFi) reads, which revealed 10.6% new sequences. Based on the phased genome, we elucidate significant genetic admixtures and haplotype differences. We developed a somatic detection strategy that reveals hidden somatic mutations overlooked in a single reference genome. We generated a phased somatic variation map by combining high-depth whole-genome sequencing (WGS) data from 87 sweet orange somatic varieties. Notably, we found twice as many somatic mutations relative to a single reference genome. Using these hidden somatic mutations, we separated sweet oranges into seven major clades and provide insight into unprecedented genetic mosaicism and strong positive selection. Furthermore, these phased genomics data indicate that genomic heterozygous variations contribute to allele-specific expression during fruit development. By integrating allelic expression differences and somatic mutations, we identified a somatic mutation that induces increases in fruit size. Applications of phased genomics will lead to powerful approaches for discovering genetic variations and uncovering their effects in highly heterozygous plants. Our data provide insight into the hidden somatic mutation landscape in the sweet orange genome, which will facilitate citrus breeding.

Measures of genetic diversification in somatic tissues at bulk and single-cell resolution

Intra-tissue genetic heterogeneity is universal to both healthy and cancerous tissues. It emerges from the stochastic accumulation of somatic mutations throughout development and homeostasis. By combining population genetics theory and genomic information, genetic heterogeneity can be exploited to infer tissue organization and dynamics in vivo. However, many basic quantities, for example the dynamics of tissue-specific stem cells remain difficult to quantify precisely. Here, we show that single-cell and bulk sequencing data inform on different aspects of the underlying stochastic processes. Bulk-derived variant allele frequency spectra (VAF) show transitions from growing to constant stem cell populations with age in samples of healthy esophagus epithelium. Single-cell mutational burden distributions allow a sample size independent measure of mutation and proliferation rates. Mutation rates in adult hematopietic stem cells are higher compared to inferences during development, suggesting additional proliferation-independent effects. Furthermore, single-cell derived VAF spectra contain information on the number of tissue-specific stem cells. In hematopiesis, we find approximately 2 × 105 HSCs, if all stem cells divide symmetrically. However, the single-cell mutational burden distribution is over-dispersed compared to a model of Poisson distributed random mutations. A time-associated model of mutation accumulation with a constant rate alone cannot generate such a pattern. At least one additional source of stochasticity would be needed. Possible candidates for these processes may be occasional bursts of stem cell divisions, potentially in response to injury, or non-constant mutation rates either through environmental exposures or cell-intrinsic variation.

Incorporating mutational heterogeneity to identify genes that are enriched for synonymous mutations in cancer

BACKGROUND

Synonymous mutations, which change the DNA sequence but not the encoded protein sequence, can affect protein structure and function, mRNA maturation, and mRNA half-lives. The possibility that synonymous mutations might be enriched in cancer has been explored in several recent studies. However, none of these studies control for all three types of mutational heterogeneity (patient, histology, and gene) that are known to affect the accurate identification of non-synonymous cancer-associated genes. Our goal is to adopt the current standard for non-synonymous mutations in an investigation of synonymous mutations.

RESULTS

Here, we create an algorithm, MutSigCVsyn, an adaptation of MutSigCV, to identify cancer-associated genes that are enriched for synonymous mutations based on a non-coding background model that takes into account the mutational heterogeneity across these levels. Using MutSigCVsyn, we first analyzed 2572 cancer whole-genome samples from the Pan-cancer Analysis of Whole Genomes (PCAWG) to identify non-synonymous cancer drivers as a quality control. Indicative of the algorithm accuracy we find that 58.6% of these candidate genes were also found in Cancer Census Gene (CGC) list, and 66.2% were found within the PCAWG cancer driver list. We then applied it to identify 30 putative cancer-associated genes that are enriched for synonymous mutations within the same samples. One of the promising gene candidates is the B cell lymphoma 2 (BCL-2) gene. BCL-2 regulates apoptosis by antagonizing the action of proapoptotic BCL-2 family member proteins. The synonymous mutations in BCL2 are enriched in its anti-apoptotic domain and likely play a role in cancer cell proliferation.

CONCLUSION

Our study introduces MutSigCVsyn, an algorithm that accounts for mutational heterogeneity at patient, histology, and gene levels, to identify cancer-associated genes that are enriched for synonymous mutations using whole genome sequencing data. We identified 30 putative candidate genes that will benefit from future experimental studies on the role of synonymous mutations in cancer biology.

Complete chloroplast genome structural characterization of two Phalaenopsis (Orchidaceae) species and comparative analysis with their alliance

BACKGROUND

The taxonomy and infrageneric delimitation of Phalaenopsis Blume has been significantly disputed due to some overlapping morphological features between species related, which needed further evidence for clarification. The structural characterization of complete chloroplast genomes of P. storbatiana and P. wilsonii were analyzed and compared with those of related taxa to provide a better understanding of their genomic information on taxonomy and phylogeny.

RESULTS

It was shown that chloroplast genomes of Phalaenopsis storbatiana and P. wilsonii had a typical quadripartite structure with conserved genome arrangements and moderate divergence. The chloroplast genomes of P. storbatiana and P. wilsonii were 145,885 bp and 145,445 bp in length, respectively, and shared a similar GC content of 36.8%. Gene annotations of two species revealed 109 single-copy genes consistently. In addition, 20 genes duplicated in the inverted regions, 16 genes each possessed one or more introns, and five ndh (NA (D)H dehydrogenase) genes were observed in both. Comparative analysis of the total cp genomes of P. storbatiana and P. wilsonii with those of other six related Phalaenopsis species confirmed the stable sequence identity for coding and non-coding regions and higher sequence variation in SC regions than IR regions. Most of their protein-coding genes had a high degree of codon preference. Moreover, 45 genes were discovered with significantly positive selection. However, different amplifications in IR regions were observed in these eight species. Phylogenetic analysis based on CDS from 60 species representing main clades in Orchidaceae indicated that Phalaenopsis species including P. stobartiana and P. wilsonii formed a monophyletic clade with high bootstrap nested in tribe Vandeae of Epidendroideae, which was consistent with those from previous studies.

CONCLUSIONS

The results could provide insight into understanding the plastome evolution and phylogenetic relationships of Phalaenopsis.

Distinct Traits of Structural and Regulatory Evolutional Conservation of Human Genes with Specific Focus on Major Cancer Molecular Pathways

The evolution of protein-coding genes has both structural and regulatory components. The first can be assessed by measuring the ratio of non-synonymous to synonymous nucleotide substitutions. The second component can be measured as the normalized proportion of transposable elements that are used as regulatory elements. For the first time, we characterized in parallel the regulatory and structural evolutionary profiles for 10,890 human genes and 2972 molecular pathways. We observed a ~0.1 correlation between the structural and regulatory metrics at the gene level, which appeared much higher (~0.4) at the pathway level. We deposited the data in the publicly available database RetroSpect. We also analyzed the evolutionary dynamics of six cancer pathways of two major axes: Notch/WNT/Hedgehog and AKT/mTOR/EGFR. The Hedgehog pathway had both components slower, whereas the Akt pathway had clearly accelerated structural evolution. In particular, the major hub nodes Akt and beta-catenin showed both components strongly decreased, whereas two major regulators of Akt TCL1 and CTMP had outstandingly high evolutionary rates. We also noticed structural conservation of serine/threonine kinases and the genes related to guanosine metabolism in cancer signaling: GPCRs, G proteins, and small regulatory GTPases (Src, Rac, Ras); however, this was compensated by the accelerated regulatory evolution.

Cancer driver mutations: predictions and reality

Cancer cells accumulate many genetic alterations throughout their lifetime, but only a few of them drive cancer progression, termed driver mutations. Driver mutations may vary between cancer types and patients, can remain latent for a long time and become drivers at particular cancer stages, or may drive oncogenesis only in conjunction with other mutations. The high mutational, biochemical, and histological tumor heterogeneity makes driver mutation identification very challenging. In this review we summarize recent efforts to identify driver mutations in cancer and annotate their effects. We underline the success of computational methods to predict driver mutations in finding novel cancer biomarkers, including in circulating tumor DNA (ctDNA). We also report on the boundaries of their applicability in clinical research.

The origins and functional effects of postzygotic mutations throughout the human life span

Postzygotic mutations (PZMs) begin to accrue in the human genome immediately after fertilization, but how and when PZMs affect development and lifetime health remain unclear. To study the origins and functional consequences of PZMs, we generated a multitissue atlas of PZMs spanning 54 tissue and cell types from 948 donors. Nearly half the variation in mutation burden among tissue samples can be explained by measured technical and biological effects, and 9% can be attributed to donor-specific effects. Through phylogenetic reconstruction of PZMs, we found that their type and predicted functional impact vary during prenatal development, across tissues, and through the germ cell life cycle. Thus, methods for interpreting effects across the body and the life span are needed to fully understand the consequences of genetic variants.

The evolution of non-small cell lung cancer metastases in TRACERx

Metastatic disease is responsible for the majority of cancer-related deaths1. We report the longitudinal evolutionary analysis of 126 non-small cell lung cancer (NSCLC) tumours from 421 prospectively recruited patients in TRACERx who developed metastatic disease, compared with a control cohort of 144 non-metastatic tumours. In 25% of cases, metastases diverged early, before the last clonal sweep in the primary tumour, and early divergence was enriched for patients who were smokers at the time of initial diagnosis. Simulations suggested that early metastatic divergence more frequently occurred at smaller tumour diameters (less than 8 mm). Single-region primary tumour sampling resulted in 83% of late divergence cases being misclassified as early, highlighting the importance of extensive primary tumour sampling. Polyclonal dissemination, which was associated with extrathoracic disease recurrence, was found in 32% of cases. Primary lymph node disease contributed to metastatic relapse in less than 20% of cases, representing a hallmark of metastatic potential rather than a route to subsequent recurrences/disease progression. Metastasis-seeding subclones exhibited subclonal expansions within primary tumours, probably reflecting positive selection. Our findings highlight the importance of selection in metastatic clone evolution within untreated primary tumours, the distinction between monoclonal versus polyclonal seeding in dictating site of recurrence, the limitations of current radiological screening approaches for early diverging tumours and the need to develop strategies to target metastasis-seeding subclones before relapse.

Immune selection determines tumor antigenicity and influences response to checkpoint inhibitors

In cancer, evolutionary forces select for clones that evade the immune system. Here we analyzed >10,000 primary tumors and 356 immune-checkpoint-treated metastases using immune dN/dS, the ratio of nonsynonymous to synonymous mutations in the immunopeptidome, to measure immune selection in cohorts and individuals. We classified tumors as immune edited when antigenic mutations were removed by negative selection and immune escaped when antigenicity was covered up by aberrant immune modulation. Only in immune-edited tumors was immune predation linked to CD8 T cell infiltration. Immune-escaped metastases experienced the best response to immunotherapy, whereas immune-edited patients did not benefit, suggesting a preexisting resistance mechanism. Similarly, in a longitudinal cohort, nivolumab treatment removes neoantigens exclusively in the immunopeptidome of nonimmune-edited patients, the group with the best overall survival response. Our work uses dN/dS to differentiate between immune-edited and immune-escaped tumors, measuring potential antigenicity and ultimately helping predict response to treatment.

Longitudinal dynamics of clonal hematopoiesis identifies gene-specific fitness effects

Clonal hematopoiesis of indeterminate potential (CHIP) increases rapidly in prevalence beyond age 60 and has been associated with increased risk for malignancy, heart disease and ischemic stroke. CHIP is driven by somatic mutations in hematopoietic stem and progenitor cells (HSPCs). Because mutations in HSPCs often drive leukemia, we hypothesized that HSPC fitness substantially contributes to transformation from CHIP to leukemia. HSPC fitness is defined as the proliferative advantage over cells carrying no or only neutral mutations. If mutations in different genes lead to distinct fitness advantages, this could enable patient stratification. We quantified the fitness effects of mutations over 12 years in older age using longitudinal sequencing and developed a filtering method that considers individual mutational context alongside mutation co-occurrence to quantify the growth potential of variants within individuals. We found that gene-specific fitness differences can outweigh inter-individual variation and, therefore, could form the basis for personalized clinical management.

Lineage tracing in human tissues

The dynamical process of cell division that underpins homeostasis in the human body cannot be directly observed in vivo, but instead is measurable from the pattern of somatic genetic or epigenetic mutations that accrue in tissues over an individual's lifetime. Because somatic mutations are heritable, they serve as natural lineage tracing markers that delineate clonal expansions. Mathematical analysis of the distribution of somatic clone sizes gives a quantitative readout of the rates of cell birth, death, and replacement. In this review we explore the broad range of somatic mutation types that have been used for lineage tracing in human tissues, introduce the mathematical concepts used to infer dynamical information from these clone size data, and discuss the insights of this lineage tracing approach for our understanding of homeostasis and cancer development. We use the human colon as a particularly instructive exemplar tissue. There is a rich history of human somatic cell dynamics surreptitiously written into the cell genomes that is being uncovered by advances in sequencing and careful mathematical analysis lineage of tracing data. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Quantification of the Selective Advantage of Driver Mutations Is Dependent on the Underlying Model and Stage of Tumor Evolution

Measuring the selective fitness advantages provided by driver mutations has the potential to facilitate a precise quantitative understanding of cancer evolution. However, accurately measuring the selective advantage of driver mutations has remained a challenge in the field. Early studies reported small selective advantages of drivers, on the order of 1%, whereas newer studies report much larger selective advantages, as high as 1,200%. In this article, we argue that the calculated selective advantages of cancer drivers are dependent on the underlying mathematical model and stage of cancer evolution and that comparisons of numerical values of selective advantage without regard for the underlying model and stage can lead to spurious conclusions.

Multiscale heterogeneity in gastric adenocarcinoma evolution is an obstacle to precision medicine

BACKGROUND

Cancer is a somatic evolutionary disease and adenocarcinomas of the stomach and gastroesophageal junction (GC) may serve as a two-dimensional model of cancer expansion, in which tumor subclones are not evenly mixed during tumor progression but rather spatially separated and diversified. We hypothesize that precision medicine efforts are compromised when clinical decisions are based on a single-sample analysis, which ignores the mechanisms of cancer evolution and resulting intratumoral heterogeneity. Using multiregional whole-exome sequencing, we investigated the effect of somatic evolution on intratumoral heterogeneity aiming to shed light on the evolutionary biology of GC.

METHODS

The study comprised a prospective discovery cohort of 9 and a validation cohort of 463 GCs. Multiregional whole-exome sequencing was performed using samples form 45 primary tumors and 3 lymph node metastases (range 3-10 tumor samples/patient) of the discovery cohort.

RESULTS

In total, the discovery cohort harbored 16,537 non-synonymous mutations. Intratumoral heterogeneity of somatic mutations and copy number variants were present in all tumors of the discovery cohort. Of the non-synonymous mutations, 53-91% were not present in each patient's sample; 399 genes harbored 2-4 different non-synonymous mutations in the same patient; 175 genes showed copy number variations, the majority being heterogeneous, including CD274 (PD-L1). Multi-sample tree-based analyses provided evidence for branched evolution being most complex in a microsatellite instable GC. The analysis of the mode of evolution showed a high degree of heterogeneity in deviation from neutrality within each tumor. We found evidence of parallel evolution and evolutionary trajectories: different mutations of SMAD4 aligned with different subclones and were found only in TP53 mutant GCs.

CONCLUSIONS

Neutral and non-neutral somatic evolution shape the mutational landscape in GC along its lateral expansions. It leads to complex spatial intratumoral heterogeneity, where lymph node metastases may stem from different areas of the primary tumor, synchronously. Our findings may have profound effects on future patient management. They illustrate the risk of mis-interpreting tumor genetics based on single-sample analysis and open new avenues for an evolutionary classification of GC, i.e., the discovery of distinct evolutionary trajectories which can be utilized for precision medicine.

Synonymous mutations reveal genome-wide levels of positive selection in healthy tissues

Genetic alterations under positive selection in healthy tissues have implications for cancer risk. However, total levels of positive selection across the genome remain unknown. Passenger mutations are influenced by all driver mutations, regardless of type or location in the genome. Therefore, the total number of passengers can be used to estimate the total number of drivers-including unidentified drivers outside of cancer genes that are traditionally missed. Here we analyze the variant allele frequency spectrum of synonymous mutations from healthy blood and esophagus to quantify levels of missing positive selection. In blood, we find that only 30% of passengers can be explained by single-nucleotide variants in driver genes, suggesting high levels of positive selection for mutations elsewhere in the genome. In contrast, more than half of all passengers in the esophagus can be explained by just the two driver genes NOTCH1 and TP53, suggesting little positive selection elsewhere.

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.

Superlinear growth reveals the Allee effect in tumors

Integrating experimental data into ecological models plays a central role in understanding biological mechanisms that drive tumor progression where such knowledge can be used to develop new therapeutic strategies. While the current studies emphasize the role of competition among tumor cells, they fail to explain recently observed superlinear growth dynamics across human tumors. Here we study tumor growth dynamics by developing a model that incorporates evolutionary dynamics inside tumors with tumor-microenvironment interactions. Our results reveal that tumor cells' ability to manipulate the environment and induce angiogenesis drives superlinear growth-a process compatible with the Allee effect. In light of this understanding, our model suggests that, for high-risk tumors that have a higher growth rate, suppressing angiogenesis can be the appropriate therapeutic intervention.

Spontaneous and inherited TP53 genetic alterations

The p53 protein is a transcription factor that prevents tumors from developing. In spontaneous and inherited cancers there are many different missense mutations in the DNA binding domain of the TP53 gene that contributes to tumor formation. These mutations produce a wide distribution in the transcriptional capabilities of the mutant p53 proteins with over four logs differences in the efficiencies of forming cancers in many diverse tissue types. These inherited and spontaneous TP53 mutations produce proteins that interact with both genetic and epigenetic cellular modifiers of p53 function and their inherited polymorphisms to produce a large number of diverse phenotypes in individual patients. This manuscript reviews these variables and discusses how the combinations of TP53 genetic alterations interact with genetic polymorphisms, epigenetic alterations, and environmental factors to begin predicting and modifying patient outcomes and provide a better understanding for new therapeutic opportunities.

Measuring evolutionary cancer dynamics from genome sequencing, one patient at a time

Cancers progress through the accumulation of somatic mutations which accrue during tumour evolution, allowing some cells to proliferate in an uncontrolled fashion. This growth process is intimately related to latent evolutionary forces moulding the genetic and epigenetic composition of tumour subpopulations. Understanding cancer requires therefore the understanding of these selective pressures. The adoption of widespread next-generation sequencing technologies opens up for the possibility of measuring molecular profiles of cancers at multiple resolutions, across one or multiple patients. In this review we discuss how cancer genome sequencing data from a single tumour can be used to understand these evolutionary forces, overviewing mathematical models and inferential methods adopted in field of Cancer Evolution.

Evolutionary dynamics of neoantigens in growing tumors

Cancers accumulate mutations that lead to neoantigens, novel peptides that elicit an immune response, and consequently undergo evolutionary selection. Here we establish how negative selection shapes the clonality of neoantigens in a growing cancer by constructing a mathematical model of neoantigen evolution. The model predicts that, without immune escape, tumor neoantigens are either clonal or at low frequency; hypermutated tumors can only establish after the evolution of immune escape. Moreover, the site frequency spectrum of somatic variants under negative selection appears more neutral as the strength of negative selection increases, which is consistent with classical neutral theory. These predictions are corroborated by the analysis of neoantigen frequencies and immune escape in exome and RNA sequencing data from 879 colon, stomach and endometrial cancers.