Context-Dependent Mutation Dynamics, Not Selection, Explains the Codon Usage Bias of Most Angiosperm Chloroplast Genes

Two competing proposals about the degree to which selection affects codon usage of angiosperm chloroplast genes are examined. The first, based on observations that codon usage does not match expectations under the naïve assumption that base composition will be identical at all neutral sites, is that selection plays a significant role. The second is that codon usage is determined almost solely by mutation bias and drift, with selection influencing only one or two highly expressed genes, in particular psbA. First it is shown that, as a result of an influence of neighboring base composition on mutation dynamics, compositional biases are expected to be widely divergent at different sites in the absence of selection. The observed mutation properties are then used to predict expected neutral codon usage biases and to show that observed deviations from the naïve expectations are in fact expected given the context-dependent mutational dynamics. It is also shown that there is a match between the observed and expected codon usage when context effects are taken into consideration, with psbA being a notable exception. Overall, the data support the model that selection is not a widespread factor affecting the codon usage of angiosperm chloroplast genes and highlight the need to have an accurate model of mutational dynamics.

Interacting evolutionary pressures drive mutation dynamics and health outcomes in aging blood

Age-related clonal hematopoiesis (ARCH) is characterized by age-associated accumulation of somatic mutations in hematopoietic stem cells (HSCs) or their pluripotent descendants. HSCs harboring driver mutations will be positively selected and cells carrying these mutations will rise in frequency. While ARCH is a known risk factor for blood malignancies, such as Acute Myeloid Leukemia (AML), why some people who harbor ARCH driver mutations do not progress to AML remains unclear. Here, we model the interaction of positive and negative selection in deeply sequenced blood samples from individuals who subsequently progressed to AML, compared to healthy controls, using deep learning and population genetics. Our modeling allows us to discriminate amongst evolutionary classes with high accuracy and captures signatures of purifying selection in most individuals. Purifying selection, acting on benign or mildly damaging passenger mutations, appears to play a critical role in preventing disease-predisposing clones from rising to dominance and is associated with longer disease-free survival. Through exploring a range of evolutionary models, we show how different classes of selection shape clonal dynamics and health outcomes thus enabling us to better identify individuals at a high risk of malignancy.

Analysis of SARS-CoV-2 mutations reveals three types of temporal dynamics and one is correlated with international travels

Coronavirus disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This disease has spread globally, causing more than 161.5 million cases and 3.3 million deaths. Keeping on the identification, surveillance and the study of the temporal dynamics of mutations with significant representation is central to understand the adaptation of SARS-CoV-2. Furthermore, how lockdown policies influence the dynamics of SARS-CoV-2 mutations is poorly understood. Here, using 1 058 020 SARS-CoV-2 genomes and COVID-19 cases from 714 country-month combinations representing 98 countries, we performed a normalization by COVID-19 cases calculation of relative frequency of SARS-CoV-2 mutations. We found 115 mutations estimated to be present in more than 3 % of global COVID-19 cases and determined three types of mutation dynamics: High-Frequency, Medium-Frequency, and Low-Frequency. Classification of mutations based on temporal dynamics helps to study viral adaptation and can be used to evaluate the effects of human behaviors in the pandemic. For instance, we report a negative and positive correlation of the frequency change of High-Frequency mutations with the level of international movement controls and the number of flight departures, respectively.

Redundancy-selection trade-off in phenotype-structured populations

Realistic fitness landscapes generally display a redundancy-fitness trade-off: highly fit trait configurations are inevitably rare, while less fit trait configurations are expected to be more redundant. The resulting sub-optimal patterns in the fitness distribution are typically described by means of effective formulations. However, the extent to which effective formulations are compatible with explicitly redundant landscapes is yet to be understood, as well as the consequences of a potential miss-match. Here we investigate the effects of such trade-off on the evolution of phenotype-structured populations, characterised by continuous quantitative traits. We consider a typical replication-mutation dynamics, and we model redundancy by means of two dimensional landscapes displaying both selective and neutral traits. We show that asymmetries of the landscapes will generate neutral contributions to the marginalised fitness-level description, that cannot be described by effective formulations, nor disentangled by the full trait distribution. Rather, they appear as effective sources, whose magnitude depends on the geometry of the landscape. Our results highlight new important aspects on the nature of sub-optimality. We discuss practical implications for rapidly mutant populations such as pathogens and cancer cells, where the qualitative knowledge of their trait and fitness distributions can drive disease management and intervention policies.

Characterization of the evolutionary dynamics of influenza A H3N2 hemagglutinin

Virus evolution drives the annual influenza epidemics in human population worldwide. However, it has been challenging to evaluate the mutation effect of the influenza virus on evading the population immunity. In this study, we introduce a novel statistical and computational approach to measure the dynamic molecular determinants underlying epidemics by the effective mutations (EMs), and account for the time of waning mutation advantage against herd immunity by the effective mutation periods (EMPs). Extensive analysis is performed on the genome and epidemiology data of 13-year worldwide H3N2 epidemics involving nine regions in four continents. We showed that the identified EM processed similar profile in geographically adjacent regions, while only 40% are common to Europe, North America, Asia and Oceania, indicating that the regional specific mutations also contributed significantly to the global H3N2 epidemics. The mutation dynamics calibrated that around 90% of the common EMs underlying global epidemics were originated from South East Asia, led by Thailand and India, and the rest were originated from North America. New Zealand was found to be the dominate sink region of H3N2 circulation, followed by UK. All regions might act as the intersection in the H3N2 transmission network. The proposed methodology provided a way to characterize key amino acids from the genetic epidemiology point of view. This approach is not restricted by the genomic region or type of the virus, and will find broad applications in identifying therapeutic targets for combating infectious diseases.

Analysis of the mutation dynamics of SARS-CoV-2 reveals the spread history and emergence of RBD mutant with lower ACE2 binding affinity

SummaryMonitoring the mutation dynamics of SARS-CoV-2 is critical for the development of effective approaches to contain the pathogen. By analyzing 106 SARS-CoV-2 and 39 SARS genome sequences, we provided direct genetic evidence that SARS-CoV-2 has a much lower mutation rate than SARS. Minimum Evolution phylogeny analysis revealed the putative original status of SARS-CoV-2 and the early-stage spread history. The discrepant phylogenies for the spike protein and its receptor binding domain proved a previously reported structural rearrangement prior to the emergence of SARS-CoV-2. Despite that we found the spike glycoprotein of SARS-CoV-2 is particularly more conserved, we identified a mutation that leads to weaker receptor binding capability, which concerns a SARS-CoV-2 sample collected on 27th January 2020 from India. This represents the first report of a significant SARS-CoV-2 mutant, and raises the alarm that the ongoing vaccine development may become futile in future epidemic if more mutations were identified.HighlightsBased on the currently available genome sequence data, we proved that SARS-COV-2 genome has a much lower mutation rate and genetic diversity than SARS during the 2002-2003 outbreak.The spike (S) protein encoding gene of SARS-COV-2 is found relatively more conserved than other protein-encoding genes, which is a good indication for the ongoing antiviral drug and vaccine development.Minimum Evolution phylogeny analysis revealed the putative original status of SARS-CoV-2 and the early-stage spread history.We confirmed a previously reported rearrangement in the S protein arrangement of SARS-COV-2, and propose that this rearrangement should have occurred between human SARS-CoV and a bat SARS-CoV, at a time point much earlier before SARS-COV-2 transmission to human.We provided first evidence that a mutated SARS-COV-2 with reduced human ACE2 receptor binding affinity have emerged in India based on a sample collected on 27th January 2020.

Cytosine Methylation Affects the Mutability of Neighboring Nucleotides in Germline and Soma

Methylated cytosines deaminate at higher rates than unmethylated cytosines, and the lesions they produce are repaired less efficiently. As a result, methylated cytosines are mutational hotspots. Here, combining rare polymorphism and base-resolution methylation data in humans, Arabidopsis thaliana, and rice (Oryza sativa), we present evidence that methylation state affects mutation dynamics not only at the focal cytosine but also at neighboring nucleotides. In humans, contrary to prior suggestions, we find that nucleotides in the close vicinity (±3 bp) of methylated cytosines mutate less frequently. Reduced mutability around methylated CpGs is also observed in cancer genomes, considering single nucleotide variants alongside tissue-of-origin-matched methylation data. In contrast, methylation is associated with increased neighborhood mutation risk in A. thaliana and rice. The difference in neighborhood mutation risk is less pronounced further away from the focal CpG and modulated by regional GC content. Our results are consistent with a model where altered risk at neighboring bases is linked to lesion formation at the focal CpG and subsequent long-patch repair. Our findings indicate that cytosine methylation has a broader mutational footprint than is commonly assumed.

Cytosine methylation affects the mutability of neighbouring nucleotides in human, Arabidopsis, and rice

ABSTRACTMethylated cytosines deaminate at higher rates than unmethylated cytosines and the lesions they produce are repaired less efficiently. As a result, methylated cytosines are mutational hotspots. Here, combining rare polymorphism and base-resolution methylation data in humans, Arabidopsis thaliana, and rice (Oryza sativa), we present evidence that methylation state affects mutation dynamics not only at the focal cytosine but also at neighbouring nucleotides. In humans, contrary to prior suggestions, we find that nucleotides in the close vicinity (±3nt) of methylated cytosines mutate less frequently. In contrast, methylation is associated with increased neighbourhood mutation risk in A. thaliana and rice. The difference in mutation risk associated with methylation is less pronounced further away from the focal CpG, is modulated by regional GC content, and enhanced in heterochromatic regions. Our results are consistent with a model where elevated risk at neighbouring bases is linked to lesion formation at the focal cytosine and subsequent long-patch repair. Our results provide evidence that cytosine methylation has a broader mutational footprints than commonly assumed. They also illustrate that methylation is not intrinsically associated with higher mutation risk for surrounding bases, but that mutagenic effects reflect evolved species-specific and lesion-specific predispositions to elicit error-prone long-patch DNA repair.