Natural Selection Shapes Codon Usage in the Human Genome

A New Comparative Framework for Estimating Selection on Synonymous Substitutions

Selection on synonymous codon usage is a well-known and widespread phenomenon, yet existing models often do not account for it or its effect on synonymous substitution rates. In this article, we develop and expand the capabilities of multiclass synonymous substitution (MSS) models, which account for such selection by partitioning synonymous substitutions into 2 or more classes and estimating a relative substitution rate for each class, while accounting for important confounders like mutation bias. We identify extensive heterogeneity among relative synonymous substitution rates in an empirical dataset of ∼12,000 gene alignments from 12 Drosophila species. We validate model performance using data simulated under a forward population genetic simulation, demonstrating that MSS models are robust to model misspecification. MSS rates are significantly correlated with other covariates of selection on codon usage (population-level polymorphism data and tRNA abundance data), suggesting that models can detect weak signatures of selection on codon usage. With the MSS model, we can now study selection on synonymous substitutions in diverse taxa, independent of any a priori assumptions about the forces driving that selection.

Diverse ancestral representation improves genetic intolerance metrics

The unprecedented scale of genomic databases has revolutionized our ability to identify regions in the human genome intolerant to variation-regions often implicated in disease. However, these datasets remain constrained by limited ancestral diversity. Here, we analyze whole-exome sequencing data from 460,551 UK Biobank and 125,748 Genome Aggregation Database (gnomAD) participants across multiple ancestries to test several key intolerance metrics, including the Residual Variance Intolerance Score (RVIS), Missense Tolerance Ratio (MTR), and Loss-of-Function Observed/Expected ratio (LOF O/E). We demonstrate that increasing ancestral representation, rather than sample size alone, critically drives their performance. Scores trained on variation observed in African and Admixed American ancestral groups show higher resolution in detecting haploinsufficient and neurodevelopmental disease risk genes compared to scores trained on European ancestry groups. Most strikingly, MTR trained on 43,000 multi-ancestry exomes demonstrates greater predictive power than when trained on a nearly 10-fold larger dataset of 440,000 non-Finnish European exomes. We further find that European ancestry group-based scores are likely approaching saturation. These findings highlight the need for enhanced population representation in genomic resources to fully realize the potential of precision medicine and drug discovery. Ancestry group-specific scores are publicly available through an interactive portal: http://intolerance.public.cgr.astrazeneca.com/ .

Genome-wide prediction of dominant and recessive neurodevelopmental disorder-associated genes

Despite great progress, thousands of neurodevelopmental disorder (NDD) risk genes remain to be discovered. We present a computational approach that accelerates NDD risk gene identification using machine learning. First, we demonstrate that models trained solely on single-cell RNA sequencing data can robustly predict genes implicated in autism spectrum disorder (ASD), developmental and epileptic encephalopathy (DEE), and developmental delay (DD). Notably, we find differences in gene expression patterns of genes with monoallelic and bi-allelic inheritance patterns in the developing human cortex. We then integrate expression data with 300 orthogonal features, including intolerance metrics, protein-protein interaction data, and others, in a semi-supervised machine learning framework (mantis-ml) to train inheritance-specific models for these disorders. The models have high predictive power (area under the receiver operator curves [AUCs]: 0.84-0.95), and the top-ranked genes were up to 2-fold (monoallelic models) and 6-fold (bi-allelic models) more enriched for high-confidence NDD risk genes compared to genic intolerance metrics alone. Additionally, genes ranking in the top decile were 45 to 180 times more likely to have literature support than those in the bottom decile. Collectively, this work provides robust NDD risk gene predictions that can complement large-scale gene discovery efforts and underscores the importance of considering inheritance in gene risk prediction.

Interpreting mammalian synonymous site conservation in light of the unwanted transcript hypothesis

Mammalian genomes are biased towards GC bases at third codon positions, likely due to a GC-biased ancestral genome and the selectively neutral recombination-related process of GC-biased gene conversion. The unwanted transcript hypothesis posits that this high GC content at synonymous sites may be beneficial for protecting against spurious transcripts, particularly in species with low effective population sizes. Utilising a 240 placental mammal genome alignment and single-base resolution conservation scores, we interpret sequence conservation at mammalian four-fold degenerate sites in this context and find evidence in support of the unwanted transcript hypothesis, including a strong GC bias, high conservation at sites relating to exon splicing, less human genetic variation at conserved four-fold degenerate sites, and conservation of sites important for epigenetic regulation of developmental genes. Additionally, we show that high conservation of four-fold degenerate sites in essential developmental genes, including homeobox genes, likely relates to the low mutation rates experienced by these genes.

A new comparative framework for estimating selection on synonymous substitutions

Selection on synonymous codon usage is a well known and widespread phenomenon, yet existing models often do not account for it or its effect on synonymous substitution rates. In this article, we develop and expand the capabilities of Multiclass Synonymous Substitution (MSS) models, which account for such selection by partitioning synonymous substitutions into two or more classes and estimating a relative substitution rate for each class, while accounting for important confounders like mutation bias. We identify extensive heterogeneity among relative synonymous substitution rates in an empirical dataset of ~12,000 gene alignments from twelve Drosophila species. We validate model performance using data simulated under a forward population genetic simulation, demonstrating that MSS models are robust to model misspecification. MSS rates are significantly correlated with other covariates of selection on codon usage (population-level polymorphism data and tRNA abundance data), suggesting that models can detect weak signatures of selection on codon usage. With the MSS model, we can now study selection on synonymous substitutions in diverse taxa, independent of any a priori assumptions about the forces driving that selection.

The De Novo Emergence of Two Brain Genes in the Human Lineage Appears to be Unsupported

Recently, certain studies have claimed that cognitive features and pathologies unique to humans can be traced to certain changes in the nervous system. These are caused by genes that have likely evolved "from scratch," not having any coding precursors. The translated proteins would not appear outside of the human lineage and any orthologs in other species should be non-coding. This contrasts with research that has identified a decisive role for duplication, and modifications to regulatory sequences, for such phenotypic traits. Closer examination, however, reveals that the inferred lineage-specific emergence of at least two of these genes is likely a misinterpretation owing to a lack of peptide verification, experimental oversights, and insufficient species comparisons. A possible pseudogenic origin is proposed for one of them. The implications of these claims for the study of molecular evolution are discussed.

Link Between Individual Codon Frequencies and Protein Expression: Going Beyond Codon Adaptation Index

An important role of a particular synonymous codon composition of a gene in its expression level is well known. There are a number of algorithms optimizing codon usage of recombinant genes to maximize their expression in host cells. Nevertheless, the underlying mechanism remains unsolved and is of significant relevance. In the realm of modern biotechnology, directing protein production to a specific level is crucial for metabolic engineering, genome rewriting and a growing number of other applications. In this study, we propose two new simple statistical and empirical methods for predicting the protein expression level from the nucleotide sequence of the corresponding gene: Codon Expression Index Score (CEIS) and Codon Productivity Score (CPS). Both of these methods are based on the influence of each individual codon in the gene on the overall expression level of the encoded protein and the frequencies of isoacceptors in the species. Our predictions achieve a correlation level of up to r = 0.7 with experimentally measured quantitative proteome data of Escherichia coli, which is superior to any previously proposed methods. Our work helps understand how codons determine protein abundances. Based on these methods, it is possible to design proteins optimized for expression in a particular organism.

Codon Bias of the DDR1 Gene and Transcription Factor EHF in Multiple Species

Milk production is an essential economic trait in cattle, and understanding the genetic regulation of this trait can enhance breeding strategies. The discoidin domain receptor 1 (DDR1) gene has been identified as a key candidate gene that influences milk production, and ETS homologous factor (EHF) is recognized as a critical transcription factor that regulates DDR1 expression. Codon usage bias, which affects gene expression and protein function, has not been fully explored in cattle. This study aims to examine the codon usage bias of DDR1 and EHF transcription factors to understand their roles in dairy production traits. Data from 24 species revealed that both DDR1 and EHF predominantly used G/C-ending codons, with the GC3 content averaging 75.49% for DDR1 and 61.72% for EHF. Synonymous codon usage analysis identified high-frequency codons for both DDR1 and EHF, with 17 codons common to both genes. Correlation analysis indicated a negative relationship between the effective number of codons and codon adaptation index for both DDR1 and EHF. Phylogenetic and clustering analyses revealed similar codon usage patterns among closely related species. These findings suggest that EHF plays a crucial role in regulating DDR1 expression, offering new insights into genetically regulating milk production in cattle.

Comparative Analysis of Codon Usage Bias in Six Eimeria Genomes

The codon usage bias (CUB) of genes encoded by different species' genomes varies greatly. The analysis of codon usage patterns enriches our comprehension of genetic and evolutionary characteristics across diverse species. In this study, we performed a genome-wide analysis of CUB and its influencing factors in six sequenced Eimeria species that cause coccidiosis in poultry: Eimeria acervulina, Eimeria necatrix, Eimeria brunetti, Eimeria tenella, Eimeria praecox, and Eimeria maxima. The GC content of protein-coding genes varies between 52.67% and 58.24% among the six Eimeria species. The distribution trend of GC content at different codon positions follows GC1 > GC3 > GC2. Most high-frequency codons tend to end with C/G, except in E. maxima. Additionally, there is a positive correlation between GC3 content and GC3s/C3s, but a significantly negative correlation with A3s. Analysis of the ENC-Plot, neutrality plot, and PR2-bias plot suggests that selection pressure has a stronger influence than mutational pressure on CUB in the six Eimeria genomes. Finally, we identified from 11 to 15 optimal codons, with GCA, CAG, and AGC being the most commonly used optimal codons across these species. This study offers a thorough exploration of the relationships between CUB and selection pressures within the protein-coding genes of Eimeria species. Genetic evolution in these species appears to be influenced by mutations and selection pressures. Additionally, the findings shed light on unique characteristics and evolutionary traits specific to the six Eimeria species.

VP1 is the primary determinant of neuropathogenesis in a mouse model of enterovirus D68 acute flaccid myelitis

Enterovirus D68 (EV-D68) is an emerging pathogen that can cause severe respiratory and neurologic disease [acute flaccid myelitis (AFM)]. Intramuscular (IM) injection of neonatal Swiss Webster (SW) mice with US/IL/14-18952 (IL52), a clinical isolate from the 2014 EV-D68 epidemic, results in many of the pathogenic features of human AFM, including viral infection of the spinal cord, death of motor neurons, and resultant progressive paralysis. In distinction, CA/14-4231 (CA4231), another clinical isolate from the 2014 EV-D68 outbreak, does not cause paralysis in mice, does not grow in the spinal cord, and does not cause motor neuron loss following IM injection. A panel of chimeric viruses containing sequences from IL52 and CA4231 was used to demonstrate that VP1 is the main determinant of EV-D68 neurovirulence following IM injection of neonatal SW mice. VP1 contains four amino acid differences between IL52 and CA4231. Mutations resulting in substituting these four amino acids (CA4231 residues into the IL52 polyprotein) completely abolished neurovirulence. Conversely, mutations resulting in substituting VP1 IL52 amino acid residues into the CA4231 polyprotein created a virus that induced paralysis to the same degree as IL52. Neurovirulence following infection of neonatal SW mice with parental and chimeric viruses was associated with viral growth in the spinal cord.

IMPORTANCE

Emerging viruses allow us to investigate mutations leading to increased disease severity. Enterovirus D68 (EV-D68), once the cause of rare cases of respiratory illness, recently acquired the ability to cause severe respiratory and neurologic disease. Chimeric viruses were used to demonstrate that viral structural protein VP1 determines growth in the spinal cord, motor neuron loss, and paralysis following intramuscular (IM) injection of neonatal Swiss Webster (SW) mice with EV-D68. These results have relevance for predicting the clinical outcome of future EV-D68 epidemics as well as targeting retrograde transport as a potential strategy for treating virus-induced neurologic disease.

NeMu: a comprehensive pipeline for accurate reconstruction of neutral mutation spectra from evolutionary data

The recognized importance of mutational spectra in molecular evolution is yet to be fully exploited beyond human cancer studies and model organisms. The wealth of intraspecific polymorphism data in the GenBank repository, covering a broad spectrum of genes and species, presents an untapped opportunity for detailed mutational spectrum analysis. Existing methods fall short by ignoring intermediate substitutions on the inner branches of phylogenetic trees and lacking the capability for cross-species mutational comparisons. To address these challenges, we present the NeMu pipeline, available at https://nemu-pipeline.com, a tool grounded in phylogenetic principles designed to provide comprehensive and scalable analysis of mutational spectra. Utilizing extensive sequence data from numerous available genome projects, NeMu rapidly and accurately reconstructs the neutral mutational spectrum. This tool, facilitating the reconstruction of gene- and species-specific mutational spectra, contributes to a deeper understanding of evolutionary mechanisms across the broad spectrum of known species.

Intraspecific and interspecific variations in the synonymous codon usage in mitochondrial genomes of 8 pleurotus strains

In this study, we investigated the codon bias of twelve mitochondrial core protein coding genes (PCGs) in eight Pleurotus strains, two of which are from the same species. The results revealed that the codons of all Pleurotus strains had a preference for ending in A/T. Furthermore, the correlation between codon base compositions and codon adaptation index (CAI), codon bias index (CBI) and frequency of optimal codons (FOP) indices was also detected, implying the influence of base composition on codon bias. The two P. ostreatus species were found to have differences in various base bias indicators. The average effective number of codons (ENC) of mitochondrial core PCGs of Pleurotus was found to be less than 35, indicating strong codon preference of mitochondrial core PCGs of Pleurotus. The neutrality plot analysis and PR2-Bias plot analysis further suggested that natural selection plays an important role in Pleurotus codon bias. Additionally, six to ten optimal codons (ΔRSCU > 0.08 and RSCU > 1) were identified in eight Pleurotus strains, with UGU and ACU being the most widely used optimal codons in Pleurotus. Finally, based on the combined mitochondrial sequence and RSCU value, the genetic relationship between different Pleurotus strains was deduced, showing large variations between them. This research has improved our understanding of synonymous codon usage characteristics and evolution of this important fungal group.

Putative protective genomic variation in the Lithuanian population

Genomic effect variants associated with survival and protection against complex diseases vary between populations due to microevolutionary processes. The aim of this study was to analyse diversity and distribution of effect variants in a context of potential positive selection. In total, 475 individuals of Lithuanian origin were genotyped using high-throughput scanning and/or sequencing technologies. Allele frequency analysis for the pre-selected effect variants was performed using the catalogue of single nucleotide polymorphisms. Comparison of the pre-selected effect variants with variants in primate species was carried out to ascertain which allele was derived and potentially of protective nature. Recent positive selection analysis was performed to verify this protective effect. Four variants having significantly different frequencies compared to European populations were identified while two other variants reached borderline significance. Effect variant in SLC30A8 gene may potentially protect against type 2 diabetes. The existing paradox of high rates of type 2 diabetes in the Lithuanian population and the relatively high frequencies of potentially protective genome variants against it indicate a lack of knowledge about the interactions between environmental factors, regulatory regions, and other genome variation. Identification of effect variants is a step towards better understanding of the microevolutionary processes, etiopathogenetic mechanisms, and personalised medicine.

Quantifying negative selection on synonymous variants

Widespread adoption of DNA sequencing has resulted in large numbers of genetic variants, whose contribution to disease is not easily determined. Although many types of variation are known to disrupt cellular processes in predictable ways, for some categories of variants, the effects may not be directly detectable. A particular example is synonymous variants, that is, those single-nucleotide variants that create a codon substitution, such that the produced amino acid sequence is unaffected. Contrary to the original theory suggesting that synonymous variants are benign, there is a growing volume of research showing that, despite their "silent" mechanism of action, some synonymous variation may be deleterious. Here, we studied the extent of the negative selective pressure acting on different classes of synonymous variants by analyzing the relative enrichment of synonymous singleton variants in the human exomes provided by gnomAD. Using a modification of the mutability-adjusted proportion of singletons (MAPS) metric as a measure of purifying selection, we found that some classes of synonymous variants are subject to stronger negative selection than others. For instance, variants that reduce codon optimality undergo stronger selection than optimality-increasing variants. Besides, selection affects synonymous variants implicated in splice-site-loss or splice-site-gain events. To understand what drives this negative selection, we tested a number of predictors in the aim to explain the variability in the selection scores. Our findings provide insights into the effects of synonymous variants at the population level, highlighting the specifics of the role that these variants play in health and disease.

Systematic analysis of the codon usage patterns of African swine fever virus genome coding sequences reveals its host adaptation phenotype

African swine fever (ASF) is a severe haemorrhagic disease caused by the African swine fever virus (ASFV), transmitted by ticks, resulting in high mortality among domestic pigs and wild boars. The global spread of ASFV poses significant economic threats to the swine industry. This study employs diverse analytical methods to explore ASFV's evolution and host adaptation, focusing on codon usage patterns and associated factors. Utilizing phylogenetic analysis methods including neighbour-joining and maximum-likelihood, 64 ASFV strains were categorized into four clades. Codon usage bias (CUB) is modest in ASFV coding sequences. This research identifies multiple factors - such as nucleotide composition, mutational pressures, natural selection and geographical diversity - contributing to the formation of CUB in ASFV. Analysis of relative synonymous codon usage reveals CUB variations within clades and among ASFVs and their hosts. Both Codon Adaptation Index and Similarity Index analyses confirm that ASFV strains are highly adapted to soft ticks (Ornithodoros moubata) but less so to domestic pigs, which could be a result of the long-term co-evolution of ASFV with ticks. This study sheds light on the factors influencing ASFV's codon usage and fitness dynamics, enriching our understanding of its evolution, adaptation and host interactions.

Analysis of codon usage patterns in 48 Aconitum species

BACKGROUND

The Aconitum genus is a crucial member of the Ranunculaceae family. There are 350 Aconitum species worldwide, with about 170 species found in China. These species are known for their various pharmacological effects and are commonly used to treat joint pain, cold abdominal pain, and other ailments. Codon usage bias (CUB) analysis contributes to evolutionary relationships and phylogeny. Based on protein-coding sequences (PCGs), we selected 48 species of Aconitum for CUB analysis.

RESULTS

The results revealed that Aconitum species had less than 50% GC content. Furthermore, the distribution of GC content was irregular and followed a trend of GC1 > GC2 > GC3, indicating a bias towards A/T bases. The relative synonymous codon usage (RSCU) heat map revealed the presence of conservative codons with slight variations within the genus. The effective number of codons (ENC)-Plot and the parity rule 2 (PR2)-bias plot analysis indicate that natural selection is the primary factor influencing the variation in codon usage. As a result, we screened various optimal codons and found that A/T bases were preferred as the last codon. Furthermore, our Maximum Likelihood (ML) analysis based on PCGs among 48 Aconitum species yielded results consistent with those obtained from complete chloroplast (cp.) genome data. This suggests that analyzing mutation in PCGs is an efficient method for demonstrating the phylogeny of species at the genus level.

CONCLUSIONS

The CUB analysis of 48 species of Aconitum was mainly influenced by natural selection. This study reveals the CUB pattern of Aconitum and lays the foundation for future genetic modification and phylogenetic analyses.

Catestatin: Antimicrobial Functions and Potential Therapeutics

The rapid increase in drug-resistant and multidrug-resistant infections poses a serious challenge to antimicrobial therapies, and has created a global health crisis. Since antimicrobial peptides (AMPs) have escaped bacterial resistance throughout evolution, AMPs are a category of potential alternatives for antibiotic-resistant "superbugs". The Chromogranin A (CgA)-derived peptide Catestatin (CST: hCgA352-372; bCgA344-364) was initially identified in 1997 as an acute nicotinic-cholinergic antagonist. Subsequently, CST was established as a pleiotropic hormone. In 2005, it was reported that N-terminal 15 amino acids of bovine CST (bCST1-15 aka cateslytin) exert antibacterial, antifungal, and antiyeast effects without showing any hemolytic effects. In 2017, D-bCST1-15 (where L-amino acids were changed to D-amino acids) was shown to exert very effective antimicrobial effects against various bacterial strains. Beyond antimicrobial effects, D-bCST1-15 potentiated (additive/synergistic) antibacterial effects of cefotaxime, amoxicillin, and methicillin. Furthermore, D-bCST1-15 neither triggered bacterial resistance nor elicited cytokine release. The present review will highlight the antimicrobial effects of CST, bCST1-15 (aka cateslytin), D-bCST1-15, and human variants of CST (Gly364Ser-CST and Pro370Leu-CST); evolutionary conservation of CST in mammals; and their potential as a therapy for antibiotic-resistant "superbugs".

Possible involvement of silent mutations in cancer pathogenesis and evolution

Recent studies have shown that some silent mutations can be harmful to various processes. In this study, we performed a comprehensive in silico analysis to elucidate the effects of silent mutations on cancer pathogenesis using exome sequencing data derived from the Cancer Genome Atlas. We focused on the codon optimality scores of silent mutations, which were defined as the difference between the optimality of synonymous codons, calculated using the codon usage table. The relationship between cancer evolution and silent mutations showed that the codon optimality score of the mutations that occurred later in carcinogenesis was significantly higher than of those that occurred earlier. In addition, mutations with higher scores were enriched in genes involved in the cell cycle and cell division, while those with lower scores were enriched in genes involved in apoptosis and cellular senescence. Our results demonstrate that some silent mutations can be involved in cancer pathogenesis.

Insight on genetic features prevalent in five Ipomoea species using comparative codon pattern analysis reveals differences in major codons and reduced GC content at the 5’ end of CDS

Ipomoea plants possess important commercial, medicinal, and ornamental value. Molecular and morphological studies have confirmed that most species of this genus exhibit similar phenotypes but complex phylogenetic relationships. To date, limited information is available on these evolutionary relationships. In this study, systematic analysis of diverse species from Ipomoea was used to elucidate the relationships in this genus. To this end, we employed the concept of codon usage bias (CUB) to analyze the codon usage bias of five Ipomoea species such as effective number of codons (ENC) and GC content at the third synonym codon position (GC3s). Three types of plots including ENC-GC3s, parity rule 2 (PR2) and neutrality plots were employed to discover the factors determining CUB, and the frequency of hydrogen bonds and nucleotide were calculated to dissect changes in GC content at the 5'-end of the coding sequence. Our results showed little distinctness in CUB among the five species, with a reduction of hydrogen bonds content at the 5'-end (with similar changes in cytosines). In addition, optimal codons of Ipomoea aquatica ended with G or C, different from those of the other four species, which ended in A or T. These results may be useful for exploring the evolutionary relationships among this group, and for understanding the reasons for the variation among Ipomoea species.

Transcriptomic, proteomic, and functional consequences of codon usage bias in human cells during heterologous gene expression

Differences in codon frequency between genomes, genes, or positions along a gene, modulate transcription and translation efficiency, leading to phenotypic and functional differences. Here, we present a multiscale analysis of the effects of synonymous codon recoding during heterologous gene expression in human cells, quantifying the phenotypic consequences of codon usage bias at different molecular and cellular levels, with an emphasis on translation elongation. Six synonymous versions of an antibiotic resistance gene were generated, fused to a fluorescent reporter, and independently expressed in HEK293 cells. Multiscale phenotype was analyzed by means of quantitative transcriptome and proteome assessment, as proxies for gene expression; cellular fluorescence, as a proxy for single-cell level expression; and real-time cell proliferation in absence or presence of antibiotic, as a proxy for the cell fitness. We show that differences in codon usage bias strongly impact the molecular and cellular phenotype: (i) they result in large differences in mRNA levels and protein levels, leading to differences of over 15 times in translation efficiency; (ii) they introduce unpredicted splicing events; (iii) they lead to reproducible phenotypic heterogeneity; and (iv) they lead to a trade-off between the benefit of antibiotic resistance and the burden of heterologous expression. In human cells in culture, codon usage bias modulates gene expression by modifying mRNA availability and suitability for translation, leading to differences in protein levels and eventually eliciting functional phenotypic changes.

Comprehensive analysis of codon bias in 13 Ganoderma mitochondrial genomes

Introduction

Codon usage bias is a prevalent phenomenon observed across various species and genes. However, the specific attributes of codon usage in the mitochondrial genome of Ganoderma species remain unknown.

Methods

In this study, we investigated the codon bias of 12 mitochondrial core protein-coding genes (PCGs) in 9 Ganoderma species, including 13 Ganoderma strains.

Results

The codons of all Ganoderma strains showed a preference for ending in A/T. Additionally, correlations between codon base composition and the codon adaptation index (CAI), codon bias index (CBI) and frequency of optimal codons (FOP) were identified, demonstrating the impact of base composition on codon bias. Various base bias indicators were found to vary between or within Ganoderma strains, including GC3s, the CAI, the CBI, and the FOP. The results also revealed that the mitochondrial core PCGs of Ganoderma have an average effective number of codons (ENC) lower than 35, indicating strong bias toward certain codons. Evidence from neutrality plot and PR2-bias plot analysis indicates that natural selection is a major factor affecting codon bias in Ganoderma. Additionally, 11 to 22 optimal codons (ΔRSCU>0.08 and RSCU>1) were identified in 13 Ganoderma strains, with GCA, AUC, and UUC being the most widely used optimal codons in Ganoderma. By analyzing the combined mitochondrial sequences and relative synonymous codon usage (RSCU) values, the genetic relationships between or within Ganoderma strains were determined, indicating variations between them. Nevertheless, RSCU-based analysis illustrated the intra- and interspecies relationships of certain Ganoderma species.

Discussion

This study deepens our insight into the synonymous codon usage characteristics, genetics, and evolution of this important fungal group.

A minimal role for synonymous variation in human disease

Synonymous mutations change the DNA sequence of a gene without affecting the amino acid sequence of the encoded protein. Although some synonymous mutations can affect RNA splicing, translational efficiency, and mRNA stability, studies in human genetics, mutagenesis screens, and other experiments and evolutionary analyses have repeatedly shown that most synonymous variants are neutral or only weakly deleterious, with some notable exceptions. Based on a recent study in yeast, there have been claims that synonymous mutations could be as important as nonsynonymous mutations in causing disease, assuming the yeast findings hold up and translate to humans. Here, we argue that there is insufficient evidence to overturn the large, coherent body of knowledge establishing the predominant neutrality of synonymous variants in the human genome.

Cancer-driving mutations are enriched in genic regions intolerant to germline variation

Large reference datasets of protein-coding variation in human populations have allowed us to determine which genes and genic subregions are intolerant to germline genetic variation. There is also a growing number of genes implicated in severe Mendelian diseases that overlap with genes implicated in cancer. We hypothesized that cancer-driving mutations might be enriched in genic subregions that are depleted of germline variation relative to somatic variation. We introduce a new metric, OncMTR (oncology missense tolerance ratio), which uses 125,748 exomes in the Genome Aggregation Database (gnomAD) to identify these genic subregions. We demonstrate that OncMTR can significantly predict driver mutations implicated in hematologic malignancies. Divergent OncMTR regions were enriched for cancer-relevant protein domains, and overlaying OncMTR scores on protein structures identified functionally important protein residues. Last, we performed a rare variant, gene-based collapsing analysis on an independent set of 394,694 exomes from the UK Biobank and find that OncMTR markedly improves genetic signals for hematologic malignancies.

PP2C1 fine-tunes melatonin biosynthesis and phytomelatonin receptor PMTR1 binding to melatonin in cassava

Melatonin is an important molecule in both animals and plants, regulating circadian rhythms and stress responses. Therefore, the improvement of melatonin accumulation not only strengthens the function of melatonin but also improves stress resistance in crops. Although melatonin biosynthetic enzymes have been identified through reverse genetics previously, an investigation of melatonin level-related genes through forward genetics in plants has yet to be performed. In this study, a genome-wide association study using cassava natural population of 298 genetic resources identified melatonin accumulation 1 (MA1), which regulates the natural variation of melatonin levels in cassava. We found that MA1 encodes type 2C protein phosphatase 1 (PP2C1), which serves as a negative regulator of melatonin levels in cassava. MePP2C1 physically interacts with MeRAV1/2 and MeWRKY20 and dephosphorylates them at serine (S) 35 residue, S34 residue, and S176 residue, respectively, thereby hindering their transcriptional activation on downstream melatonin biosynthetic genes. Notably, MePP2C1 interacts with phytomelatonin receptor MePMTR1 and dephosphorylates it at S11 residue, repressing its binding to melatonin. In summary, this study demonstrates that MePP2C1 as MA1 plays dual roles in negatively regulating both melatonin accumulation and signaling, extending the understanding of the molecular mechanism underlying melatonin accumulation and signaling through forward genetics in plants.

Pan-cancer analyses of synonymous mutations based on tissue-specific codon optimality

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Developed tissue-specific codon optimality in 29 human tissues.

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Applied these to analyze synonymous mutations in ∼10,000 tumor and normal samples.

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Synonymous mutations frequently increase optimal codons in most cancer types.

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Synonymous mutations frequently increase optimal codons cell cycle-related genes.

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Frequency of optimal codon gain relates to proliferation, DDR deficiency, and survival.

Codon optimality has been demonstrated to be an important determinant of mRNA stability and expression levels in multiple model organisms and human cell lines. However, tissue-specific codon optimality has not been developed to investigate how codon optimality is usually perturbed by somatic synonymous mutations in human cancers. Here, we determined tissue-specific codon optimality in 29 human tissues based on mRNA expression data from the Genotype-Tissue Expression project. We found that optimal codons were associated with differentiation, whereas non-optimal codons were correlated with proliferation. Furthermore, codons biased toward differentiation displayed greater tissue specificity in codon optimality, and the tissue specificity of codon optimality was primarily present in amino acids with high degeneracy of the genetic code. By applying tissue-specific codon optimality to somatic synonymous mutations in 8532 tumor samples across 24 cancer types and to those in 416 normal cells across six human tissues, we found that synonymous mutations frequently increased optimal codons in tumor cells and cancer-related genes (e.g., genes involved in cell cycle). Furthermore, an elevated frequency of optimal codon gain was found to promote tumor cell proliferation in three cancer types characterized by DNA damage repair deficiency and could act as a prognostic biomarker for patients with triple-negative breast cancer. In summary, this study profiled tissue-specific codon optimality in human tissues, revealed alterations in codon optimality caused by synonymous mutations in human cancers, and highlighted the non-negligible role of optimal codon gain in tumorigenesis and therapeutics.

The sequences of 150,119 genomes in the UK Biobank

Detailed knowledge of how diversity in the sequence of the human genome affects phenotypic diversity depends on a comprehensive and reliable characterization of both sequences and phenotypic variation. Over the past decade, insights into this relationship have been obtained from whole-exome sequencing or whole-genome sequencing of large cohorts with rich phenotypic data^1,2. Here we describe the analysis of whole-genome sequencing of 150,119 individuals from the UK Biobank³. This constitutes a set of high-quality variants, including 585,040,410 single-nucleotide polymorphisms, representing 7.0% of all possible human single-nucleotide polymorphisms, and 58,707,036 indels. This large set of variants allows us to characterize selection based on sequence variation within a population through a depletion rank score of windows along the genome. Depletion rank analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UK Biobank: a large British Irish cohort, a smaller African cohort and a South Asian cohort. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large-scale whole-genome sequencing studies. Using this formidable new resource, we provide several examples of trait associations for rare variants with large effects not found previously through studies based on whole-exome sequencing and/or imputation.

The 3D mutational constraint on amino acid sites in the human proteome

Quantification of the tolerance of protein sites to genetic variation has become a cornerstone of variant interpretation. We hypothesize that the constraint on missense variation at individual amino acid sites is largely shaped by direct interactions with 3D neighboring sites. To quantify this constraint, we introduce a framework called COntact Set MISsense tolerance (or COSMIS) and comprehensively map the landscape of 3D mutational constraint on 6.1 million amino acid sites covering 16,533 human proteins. We show that 3D mutational constraint is pervasive and that the level of constraint is strongly associated with disease relevance both at the site and the protein level. We demonstrate that COSMIS performs significantly better at variant interpretation tasks than other population-based constraint metrics while also providing structural insight into the functional roles of constrained sites. We anticipate that COSMIS will facilitate the interpretation of protein-coding variation in evolution and prioritization of sites for mechanistic investigation.

Homozygous might be hemizygous: CRISPR/Cas9 editing in iPSCs results in detrimental on-target defects that escape standard quality controls

The ability to precisely edit the genome of human induced pluripotent stem cell (iPSC) lines using CRISPR/Cas9 has enabled the development of cellular models that can address genotype to phenotype relationships. While genome editing is becoming an essential tool in iPSC-based disease modeling studies, there is no established quality control workflow for edited cells. Moreover, large on-target deletions and insertions that occur through DNA repair mechanisms have recently been uncovered in CRISPR/Cas9-edited loci. Yet the frequency of these events in human iPSCs remains unclear, as they can be difficult to detect. We examined 27 iPSC clones generated after targeting 9 loci and found that 33% had acquired large, on-target genomic defects, including insertions and loss of heterozygosity. Critically, all defects had escaped standard PCR and Sanger sequencing analysis. We describe a cost-efficient quality control strategy that successfully identified all edited clones with detrimental on-target events and could facilitate the integrity of iPSC-based studies.

Calculating and comparing codon usage values in rare disease genes highlights codon clustering with disease-and tissue- specific hierarchy

We designed a novel strategy to define codon usage bias (CUB) in 6 specific small cohorts of human genes. We calculated codon usage (CU) values in 29 non-disease-causing (NDC) and 31 disease-causing (DC) human genes which are highly expressed in 3 distinct tissues, kidney, muscle, and skin. We applied our strategy to the same selected genes annotated in 15 mammalian species. We obtained CUB hierarchical clusters for each gene cohort which showed tissue-specific and disease-specific CUB fingerprints. We showed that DC genes (especially those expressed in muscle) display a low CUB, well recognizable in codon hierarchical clustering. We defined the extremely biased codons as "zero codons" and found that their number is significantly higher in all DC genes, all tissues, and that this trend is conserved across mammals. Based on this calculation in different gene cohorts, we identified 5 codons which are more differentially used across genes and mammals, underlining that some genes have favorite synonymous codons in use. Since of the muscle genes clear clusters, and, among these, dystrophin gene surprisingly does not show any "zero codon" we adopted a novel approach to study CUB, we called "mapping-on-codons". We positioned 2828 dystrophin missense and nonsense pathogenic variations on their respective codon, highlighting that its frequency and occurrence is not dependent on the CU values. We conclude our strategy consents to identify a hierarchical clustering of CU values in a gene cohort-specific fingerprints, with recognizable trend across mammals. In DC muscle genes also a disease-related fingerprint can be observed, allowing discrimination between DC and NDC genes. We propose that using our strategy which studies CU in specific gene cohorts, as rare disease genes, and tissue specific genes, may provide novel information about the CUB role in human and medical genetics, with implications on synonymous variations interpretation and codon optimization algorithms.

Large-Scale Analysis of SARS-CoV-2 Synonymous Mutations Reveals the Adaptation to the Human Codon Usage During the Virus Evolution

Many large national and transnational studies have been dedicated to the analysis of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) genome, most of which focused on missense and nonsense mutations. However, approximately 30 per cent of the SARS-CoV-2 variants are synonymous, therefore changing the target codon without affecting the corresponding protein sequence.

By performing a large-scale analysis of sequencing data generated from almost 400,000 SARS-CoV-2 samples, we show that silent mutations increasing the similarity of viral codons to the human ones tend to fixate in the viral genome overtime. This indicates that SARS-CoV-2 codon usage is adapting to the human host, likely improving its effectiveness in using the human aminoacyl-tRNA set through the accumulation of deceitfully neutral silent mutations.

One-Sentence Summary. Synonymous SARS-CoV-2 mutations related to the activity of different mutational processes may positively impact viral evolution by increasing its adaptation to the human codon usage.

Neurodevelopmental Syndrome with Intellectual Disability, Speech Impairment, and Quadrupedia Is Associated with Glutamate Receptor Delta 2 Gene Defect

Bipedalism, speech, and intellect are the most prominent traits that emerged in the evolution of Homo sapiens. Here, we describe a novel genetic cause of an "involution" phenotype in four patients, who are characterized by quadrupedal locomotion, intellectual impairment, the absence of speech, small stature, and hirsutism, observed in a consanguineous Brazilian family. Using whole-genome sequencing analysis and homozygous genetic mapping, we identified genes bearing homozygous genetic variants and found a homozygous 36.2 kb deletion in the gene of glutamate receptor delta 2 (GRID2) in the patients, resulting in the lack of a coding region from the fifth to the seventh exons. The GRID2 gene is highly expressed in the cerebellum cortex from prenatal development to adulthood, specifically in Purkinje neurons. Deletion in this gene leads to the loss of the alpha chain in the extracellular amino-terminal protein domain (ATD), essential in protein folding and transport from the endoplasmic reticulum (ER) to the cell surface. Then, we studied the evolutionary trajectories of the GRID2 gene. There was no sign of strong selection of the highly conservative GRID2 gene in ancient hominids (Neanderthals and Denisovans) or modern humans; however, according to in silico tests using the Mfold tool, the GRID2 gene possibly gained human-specific mutations that increased the stability of GRID2 mRNA.

Haplotype-based inference of the distribution of fitness effects

Recent genome sequencing studies with large sample sizes in humans have discovered a vast quantity of low-frequency variants, providing an important source of information to analyze how selection is acting on human genetic variation. In order to estimate the strength of natural selection acting on low-frequency variants, we have developed a likelihood-based method that uses the lengths of pairwise identity-by-state between haplotypes carrying low-frequency variants. We show that in some non-equilibrium populations (such as those that have had recent population expansions) it is possible to distinguish between positive or negative selection acting on a set of variants. With our new framework, one can infer a fixed selection intensity acting on a set of variants at a particular frequency, or a distribution of selection coefficients for standing variants and new mutations. We show an application of our method to the UK10K phased haplotype dataset of individuals.

Structure, Function, and Thermodynamics of Lactate Dehydrogenases from Humans and the Malaria Parasite P. falciparum

Temperature adaptation is ubiquitous among all living organisms, yet the molecular basis for this process remains poorly understood. It can be assumed that for parasite-host systems, the same enzymes found in both organisms respond to the same selection factor (human body temperature) with similar structural changes. Herein, we report the existence of a reversible temperature-dependent structural transition for the glycolytic enzyme lactate dehydrogenase (LDH) from the malaria parasite Plasmodium falciparum (pfLDH) and human heart (hhLDH) occurring in the temperature range of human fever. This transition is observed for LDHs from psychrophiles, mesophiles, and moderate thermophiles in their operating temperature range. Thermodynamic analysis reveals unique thermodynamic signatures of the LDH-substrate complexes defining a specific temperature range to which human LDH is adapted and parasite LDH is not, despite their common mesophilic nature. The results of spectroscopic analysis combined with the available crystallographic data reveal the existence of an active center within pfLDH that imparts psychrophilic structural properties to the enzyme. This center consists of two pockets, one formed by the five amino acids (5AA insert) within the substrate specificity loop and the other by the active site, that mutually regulate one another in response to temperature and induce structural and functional changes in the Michaelis complex. Our findings pave the way toward a new strategy for malaria treatments and drug design using therapeutic agents that inactivate malarial LDH selectively at a specific temperature range of the cyclic malaria paroxysm.

Codon optimality in cancer

A key characteristic of cancer cells is their increased proliferative capacity, which requires elevated levels of protein synthesis. The process of protein synthesis involves the translation of codons within the mRNA coding sequence into a string of amino acids to form a polypeptide chain. As most amino acids are encoded by multiple codons, the nucleotide sequence of a coding region can vary dramatically without altering the polypeptide sequence of the encoded protein. Although mutations that do not alter the final amino acid sequence are often thought of as silent/synonymous, these can still have dramatic effects on protein output. Because each codon has a distinct translation elongation rate and can differentially impact mRNA stability, each codon has a different degree of 'optimality' for protein synthesis. Recent data demonstrates that the codon preference of a transcriptome matches the abundance of tRNAs within the cell and that this supply and demand between tRNAs and mRNAs varies between different cell types. The largest observed distinction is between mRNAs encoding proteins associated with proliferation or differentiation. Nevertheless, precisely how codon optimality and tRNA expression levels regulate cell fate decisions and their role in malignancy is not fully understood. This review describes the current mechanistic understanding on codon optimality, its role in malignancy and discusses the potential to target codon optimality therapeutically in the context of cancer.

Comparative analysis of transcriptomic data shows the effects of multiple evolutionary selection processes on codon usage in Marsupenaeus japonicus and Marsupenaeus pulchricaudatus

BACKGROUND

Kuruma shrimp, a major commercial shrimp species in the world, has two cryptic or sibling species, Marsupenaeus japonicus and Marsupenaeus pulchricaudatus. Codon usage analysis would contribute to our understanding of the genetic and evolutionary characteristics of the two Marsupenaeus species. In this study, we analyzed codon usage and related indices using coding sequences (CDSs) from RNA-seq data.

RESULTS

Using CodonW 1.4.2 software, we performed the codon bias analysis of transcriptomes obtained from hepatopancreas tissues, which indicated weak codon bias. Almost all parameters had similar correlations for both species. The gene expression level (FPKM) was negatively correlated with A/T3s. We determined 12 and 14 optimal codons for M. japonicus and M. pulchricaudatus, respectively, and all optimal codons have a C/G-ending. The two Marsupenaeus species had different usage frequencies of codon pairs, which contributed to further analysis of transcriptional differences between them. Orthologous genes that underwent positive selection (ω > 1) had a higher correlation coefficient than that of experienced purifying selection (ω < 1). Parity Rule 2 (PR2) and effective number of codons (ENc) plot analysis showed that the codon usage patterns of both species were influenced by both mutations and selection. Moreover, the average observed ENc value was lower than the expected value for both species, suggesting that factors other than GC may play roles in these phenomena. The results of multispecies clustering based on codon preference were consistent with traditional classification.

CONCLUSIONS

This study provides a relatively comprehensive understanding of the correlations among codon usage bias, gene expression, and selection pressures of CDSs for M. japonicus and M. pulchricaudatus. The genetic evolution was driven by mutations and selection pressure. Moreover, the results point out new insights into the specificities and evolutionary characteristics of the two Marsupenaeus species.

Codon Usage Bias: An Endless Tale

Since the genetic code is degenerate, several codons are translated to the same amino acid. Although these triplets were historically considered to be "synonymous" and therefore expected to be used at rather equal frequencies in all genomes, we now know that this is not the case. Indeed, since several coding sequences were obtained in the late '70s and early '80s in the last century, coming from either the same or different species, it was evident that (a) each genome, taken globally, displayed different codon usage patterns, which means that different genomes display a particular global codon usage table when all genes are considered together, and (b) there is a strong intragenomic diversity: in other words, within a given species the codon usage pattern can (and usually do) differ greatly among genes in the same genome. These different patterns were attributed to two main factors: first, the mutational bias characteristic of each genome, which determines that GC- poor species display a general bias towards A/T codons while the reverse is true for GC- rich species. Second, the differences in codon usage among genes from the same species are due to natural selection acting at the level of translation, in such a way that highly expressed genes tend to use codons that match with the most abundant isoacceptor tRNAs. Thus, these genes are translated at a highest rate, which in turn leads to avoid the limiting factor in translation which is the number of available ribosomes per cell. Although these explanations are still valid, new factors are almost constantly postulated to affect codon usage. In this mini review, we shall try to summarize them.

The association of TAP polymorphisms with non-small-cell lung cancer in the Han Chinese population

The host immune system plays a crucial role in multiple types of cancer, including non-small-cell lung cancer (NSCLC). Transporter associated with antigen processing (TAP) protein heterodimer complexes might promote intracellular antigen peptide binding with class I major histocompatibility complex (MHC-I) molecules, and in recent years, TAP1 and TAP2 have been reported to be associated with multiple cancer risks. In the current study, we investigated the association of single-nucleotide polymorphisms (SNPs) in TAP1 and TAP2 with NSCLC in a Han Chinese population. Six and seven TAP1 and TAP2 SNPs, respectively, were genotyped and analysed in healthy controls and NSCLC patients. Based on our data, none of the six SNPs in TAP1 is associated with NSCLC risk (P > 0.0038). However, rs2228396 alleles in TAP2 were significantly different between NSCLC patients and healthy controls, and the A allele might be associated with an increased risk of this cancer (P = 0.001, OR = 1.65, 95%CI: 1.23 ∼ 2.21). Moreover, the genotype frequencies of rs2228396 were significantly different between patients and healthy controls (P = 7 × 10^-4). Additionally, TAP2 rs241441 alleles exhibited a trend of difference between NSCLC patients and healthy controls, with the C allele possibly being associated with increased risk of NSCLC (P = 0.013; OR = 1.30, 95%CI: 1.06 ∼ 1.60). Moreover, the genotypes of rs241441 in TAP2 showed a significant difference between NSCLC patients and healthy controls (P = 1 × 10^-4). In haplotype analysis, the TAP2 SNP haplotype (CAC, TAP2*0102) was significantly associated with increased NSCLC risk in the Han Chinese population (P = 0.003; OR = 1.57, 95%CI: 1.17 ∼ 2.10). Our results indicate that TAP2 SNPs (rs2228396 and rs241441) have a potential role in NSCLC pathogenesis.

Polymorphisms in transporter associated with antigen presenting are associated with cervical intraepithelial neoplasia and cervical cancer in a Chinese Han population

The host immune system plays an important role in infectious diseases and cancers. The heterodimer formed by transporter associated with antigen presenting (TAP)1 and TAP2 is responsible for intracellular peptide loading onto MHC-I molecules. Studies have shown that single-nucleotide polymorphisms (SNPs) in TAP genes might affect the expression and function of TAP and be associated with cancer risk. We aimed to investigate the association of SNPs in the TAP1 and TAP2 genes with cervical intraepithelial neoplasia (CIN) and cervical cancer (CC) in a Chinese Han population. Six SNPs in the TAP1 gene and seven in the TAP2 gene were selected. The 13 SNPs were genotyped in 1255 healthy individuals, 575 patients with CIN and 1034 patients with CC using the SNaPshot assay. The association between these SNPs and CIN and CC risk was analysed. The allelic and genotypic distributions of rs41549617 and rs1135216 showed significant differences between the control and CC groups (P < 0.0038). The T allele of rs41549617 was associated with a decreased risk of CC (OR = 0.476, 95%CI: 0.286-0.791). Moreover, the G allele of rs1135216 appears to be associated with a decreased risk of CC (OR = 0.746; 95%CI: 0.632-0.881). The allele and genotype distribution of rs241441 showed a significant difference between the control and CC groups (P < 0.0038), and the rs241441 G allele was associated with an increased risk of CC (OR = 1.232, 95%CI: 1.092-1.398). In addition, the results of the association between TAP alleles and CC showed that TAP1*020101 and TAP1*0301 have an association with CC (P = 0.001 and P = 0.002, respectively). Our results demonstrate that the TAP1 and TAP2 genes are associated with CC in the Chinese Han population.

Ribosome states signal RNA quality control

Eukaryotic cells integrate multiple quality control (QC) responses during protein synthesis in the cytoplasm. These QC responses are signaled by slow or stalled elongating ribosomes. Depending on the nature of the delay, the signal may lead to translational repression, messenger RNA decay, ribosome rescue, and/or nascent protein degradation. Here, we discuss how the structure and composition of an elongating ribosome in a troubled state determine the downstream quality control pathway(s) that ensue. We highlight the intersecting pathways involved in RNA decay and the crosstalk that occurs between RNA decay and ribosome rescue.

A Transcriptome-Based Drug Discovery Paradigm for Neurodevelopmental Disorders

Advances in genetic discoveries have created substantial opportunities for precision medicine in neurodevelopmental disorders. Many of the genes implicated in these diseases encode proteins that regulate gene expression, such as chromatin-associated proteins, transcription factors, and RNA-binding proteins. The identification of targeted therapeutics for individuals carrying mutations in these genes remains a challenge, as the encoded proteins can theoretically regulate thousands of downstream targets in a considerable number of cell types. Here, we propose the application of a drug discovery approach originally developed for cancer called "transcriptome reversal" for these neurodevelopmental disorders. This approach attempts to identify compounds that reverse gene-expression signatures associated with disease states. ANN NEUROL 2021;89:199-211.

Distinct nucleotide patterns among three subgenomes of bread wheat and their potential origins during domestication after allopolyploidization

BACKGROUND

The speciation and fast global domestication of bread wheat have made a great impact on three subgenomes of bread wheat. DNA base composition is an essential genome feature, which follows the individual-strand base equality rule and [AT]-increase pattern at the genome, chromosome, and polymorphic site levels among thousands of species. Systematic analyses on base compositions of bread wheat and its wild progenitors could facilitate further understanding of the evolutionary pattern of genome/subgenome-wide base composition of allopolyploid species and its potential causes.

RESULTS

Genome/subgenome-wide base-composition patterns were investigated by using the data of polymorphic site in 93 accessions from worldwide populations of bread wheat, its diploid and tetraploid progenitors, and their corresponding reference genome sequences. Individual-strand base equality rule and [AT]-increase pattern remain in recently formed hexaploid species bread wheat at the genome, subgenome, chromosome, and polymorphic site levels. However, D subgenome showed the fastest [AT]-increase across polymorphic site from Aegilops tauschii to bread wheat than that on A and B subgenomes from wild emmer to bread wheat. The fastest [AT]-increase could be detected almost all chromosome windows on D subgenome, suggesting different mechanisms between D and other two subgenomes. Interestingly, the [AT]-increase is mainly contributed by intergenic regions at non-selective sweeps, especially the fastest [AT]-increase of D subgenome. Further transition frequency and sequence context analysis indicated that three subgenomes shared same mutation type, but D subgenome owns the highest mutation rate on high-frequency mutation type. The highest mutation rate on D subgenome was further confirmed by using a bread-wheat-private SNP set. The exploration of loci/genes related to the [AT] value of D subgenome suggests the fastest [AT]-increase of D subgenome could be involved in DNA repair systems distributed on three subgenomes of bread wheat.

CONCLUSIONS

The highest mutation rate is detected on D subgenome of bread wheat during domestication after allopolyploidization, leading to the fastest [AT]-increase pattern of D subgenome. The phenomenon may come from the joint action of multiple repair systems inherited from its wild progenitors.

SARS-CoV-2 Codon Usage Bias Downregulates Host Expressed Genes With Similar Codon Usage

Severe acute respiratory syndrome has spread quickly throughout the world and was declared a pandemic by the World Health Organization (WHO). The pathogenic agent is a new coronavirus (SARS-CoV-2) that infects pulmonary cells with great effectiveness. In this study we focus on the codon composition for the viral protein synthesis and its relationship with the protein synthesis of the host. Our analysis reveals that SARS-CoV-2 preferred codons have poor representation of G or C nucleotides in the third position, a characteristic which could result in an unbalance in the tRNAs pools of the infected cells with serious implications in host protein synthesis. By integrating this observation with proteomic data from infected cells, we observe a reduced translation rate of host proteins associated with highly expressed genes and that they share the codon usage bias of the virus. The functional analysis of these genes suggests that this mechanism of epistasis can contribute to understanding how this virus evades the immune response and the etiology of some deleterious collateral effect as a result of the viral replication. In this manner, our finding contributes to the understanding of the SARS-CoV-2 pathogeny and could be useful for the design of a vaccine based on the live attenuated strategy.