Characterisation of the novel HLA-DPB1*04:02:24 allele by next-generation sequencing.

HLA-DPB1*04:02:24 differs from HLA-DPB1*04:02:01:01 by a single synonmous nucleotide substitution at position 639 G>A.

Identification of the novel HLA-C*08:291 allele by next-generation sequencing.

HLA-C*08:291, a novel HLA class I allele detected by next-generation sequencing.

A novel null HLA-B allele, B*40:510N, due to a single nucleotide deletion in exon 2.

One nucleotide deletion in codon 15 of HLA-B*40:01:02:01 results in a novel null allele, HLA-B*40:510N.

Identification of the novel HLA-B*56:100 allele by next-generation sequencing.

HLA-B*56:100 differs from HLA-B*56:20:02 by one nucleotide substitution at codon 147.2 in exon 3.

The novel HLA-A*32 allele, HLA-A*32:01:56, identified by next generation sequencing.

HLA-A*32:01:56 differs from HLA-A-32:01:01 by a single nucleotide variation in Exon 5, codon 313.3.

Characterisation of two new HLA-DPA1 alleles: HLA-DPA1*02:139 and -DPA1*02:140N.

HLA-DPA1*02:139 and -DPA1*02:140N, two novel HLA-DPA1 alleles detected by next-generation sequencing.

The novel HLA-A*24:393 allele, identified by Sanger dideoxy nucleotide sequencing in a Taiwanese individual.

HLA-A*24:393 differs from HLA-A*24:02:01:01 by one nucleotide substitution at position 376 (G → A) in exon 3.

Discovery of the novel HLA-B*35:611 allele, a variant of the HLA-B*35:64:01 allele.

Five nucleotide substitutions in exon 3 of HLA-B*35:64:01 results in the novel allele, HLA-B*35:611.

N1-Methylpseudouridine and pseudouridine modifications modulate mRNA decoding during translation.

The ribosome utilizes hydrogen bonding between mRNA codons and aminoacyl-tRNAs to ensure rapid and accurate protein production. Chemical modification of mRNA nucleobases can adjust the strength and pattern of this hydrogen bonding to alter protein synthesis. We investigate how the N1-methylpseudouridine (m1Ψ) modification, commonly incorporated into therapeutic and vaccine mRNA sequences, influences the speed and fidelity of translation. We find that m1Ψ does not substantially change the rate constants for amino acid addition by cognate tRNAs or termination by release factors. However, we also find that m1Ψ can subtly modulate the fidelity of amino acid incorporation in a codon-position and tRNA dependent manner in vitro and in human cells. Our computational modeling shows that altered energetics of mRNA:tRNA interactions largely account for the context dependence of the low levels of miscoding we observe on Ψ and m1Ψ containing codons. The outcome of translation on modified mRNA bases is thus governed by the sequence context in which they occur.

Characterisation of the novel HLA-DQA1*01:02:24 allele by sequencing-based typing.

HLA-DQA1*01:02:24 differs from HLA-DQA1*01:02:01:03 by one nucleotide substitution in codon 167 in exon 3.

Characterisation of the novel HLA-DRB3*02:202 allele by sequencing-based typing.

HLA-DRB3*02:202 differs from DRB3*02:112 by one nucleotide substitution in codon 51 in exon 2.

Characterisation of the novel HLA-A*26:247 allele by sequencing-based typing.

HLA-A*26:247 differs from HLA-A*26:01:01:01 by one nucleotide substitution in codon 245 in exon 4.

The protein domains of vertebrate species in which selection is more effective have greater intrinsic structural disorder.

The nearly neutral theory of molecular evolution posits variation among species in the effectiveness of selection. In an idealized model, the census population size determines both this minimum magnitude of the selection coefficient required for deleterious variants to be reliably purged, and the amount of neutral diversity. Empirically, an 'effective population size' is often estimated from the amount of putatively neutral genetic diversity and is assumed to also capture a species' effectiveness of selection. A potentially more direct measure of the effectiveness of selection is the degree to which selection maintains preferred codons. However, past metrics that compare codon bias across species are confounded by among-species variation in %GC content and/or amino acid composition. Here, we propose a new Codon Adaptation Index of Species (CAIS), based on Kullback-Leibler divergence, that corrects for both confounders. We demonstrate the use of CAIS correlations, as well as the Effective Number of Codons, to show that the protein domains of more highly adapted vertebrate species evolve higher intrinsic structural disorder.

Evolution is the process through which populations change over time, starting with mutations in the genetic sequence of an organism. Many of these mutations harm the survival and reproduction of an organism, but only by a very small amount. Some species, especially those with large populations, can purge these slightly harmful mutations more effectively than other species. This fact has been used by the 'drift barrier theory' to explain various profound differences amongst species, including differences in biological complexity. In this theory, the effectiveness of eliminating slightly harmful mutations is specified by an 'effective' population size, which depends on factors beyond just the number of individuals in the population. Effective population size is normally calculated from the amount of time a 'neutral' mutation (one with no effect at all) stays in the population before becoming lost or taking over. Estimating this time requires both representative data for genetic diversity and knowledge of the mutation rate. A major limitation is that these data are unavailable for most species. A second limitation is that a brief, temporary reduction in the number of individuals has an oversized impact on the metric, relative to its impact on the number of slighly harmful mutations accumulated. Weibel, Wheeler et al. developed a new metric to more directly determine how effectively a species purges slightly harmful mutations. Their approach is based on the fact that the genetic code has 'synonymous' sequences. These sequences code for the same amino acid building block, with one of these sequences being only slightly preferred over others. The metric by Weibel, Wheeler et al. quantifies the proportion of the genome from which less preferred synonymous sequences have been effectively purged. It judges a population to have a higher effective population size when the usage of synonymous sequences departs further from the usage predicted from mutational processes. The researchers expected that natural selection would favour 'ordered' proteins with robust three-dimensional structures, i.e., that species with a higher effective population size would tend to have more ordered versions of a protein. Instead, they found the opposite: species with a higher effective population size tend to have more disordered versions of the same protein. This changes our view of how natural selection acts on proteins. Why species are so different remains a fundamental question in biology. Weibel, Wheeler et al. provide a useful tool for future applications of drift barrier theory to a broad range of ways that species differ.

Maximal Genetic Code Symmetry Is a Physicochemical Purine-Pyrimidine Symmetry Language for Transcription and Translation in the Flow of Genetic Information from DNA to Proteins.

Until now, research has not taken into consideration the physicochemical purine-pyrimidine symmetries of the genetic code in the transcription and translation processes of proteinogenesis. Our Supersymmetry Genetic Code table, developed in 2022, is common and unique for all RNA and DNA living species. Its basic structure is a purine-pyrimidine symmetry net with double mirror symmetry. Accordingly, the symmetry of the genetic code directly shows its organisation based on the principle of nucleotide Watson-Crick and codon-anticodon pairing. The maximal purine-pyrimidine symmetries of codons show that each codon has a strictly defined and unchangeable position within the genetic code. We discovered that the physicochemical symmetries of the genetic code play a fundamental role in recognising and differentiating codons from mRNA and the anticodon tRNA and aminoacyl-tRNA synthetases in the transcription and translation processes. These symmetries also support the wobble hypothesis with non-Watson-Crick pairing interactions between the translation process from mRNA to tRNA. The Supersymmetry Genetic Code table shows a specific arrangement of the second base of codons, according to which it is possible that an anticodon from tRNA recognises whether a codon from mRNA belongs to an amino acid with two or four codons, which is very important in the purposeful use of the wobble pairing process. Therefore, we show that canonical and wobble pairings essentially do not lead to misreading and errors during translation, and we point out the role of physicochemical purine-pyrimidine symmetries in decreasing disorder according to error minimisation and preserving the integrity of biological processes during proteinogenesis.

Genetic analysis of tomato brown rugose fruit virus reveals evolutionary adaptation and codon usage bias patterns.

Tomato brown rugose fruit virus (ToBRFV) poses a significant threat to tomato production worldwide, prompting extensive research into its genetic diversity, evolutionary dynamics, and adaptive strategies. In this study, we conducted a comprehensive analysis of ToBRFV at the codon level, focusing on codon usage bias, selection pressures, and evolutionary patterns across multiple genes. Our analysis revealed distinct patterns of codon usage bias and selection pressures within the ToBRFV genome, with varying levels of genetic diversity and evolutionary constraints among different genes. We observed a transition/transversion bias of 2.07 across the entire ToBRFV genome, with the movement protein (MP) gene exhibiting the highest transition/transversion bias and SNP density, suggesting potential evolutionary pressures or a higher mutation rate in this gene. Furthermore, our study identified episodic positive selection primarily in the MP gene, highlighting specific codons subject to adaptive changes in response to host immune pressures or environmental factors. Comparative analysis of codon usage bias in the coat protein (CP) and RNA-dependent RNA polymerase (RdRp) genes revealed gene-specific patterns reflecting functional constraints and adaptation to the host's translational machinery. Our findings provide valuable insights into the molecular mechanisms driving ToBRFV evolution and adaptation, with implications for understanding viral pathogenesis, host-virus interactions, and the development of control strategies. Future research directions include further elucidating the functional significance of codon usage biases, exploring the role of episodic positive selection in viral adaptation, and leveraging these insights to inform the development of effective antiviral strategies and crop protection measures.

Comparative analysis of codon usage bias in the chloroplast genomes of eighteen Ampelopsideae species (Vitaceae).

BACKGROUND: The tribe Ampelopsideae plants are important garden plants with both medicinal and ornamental values. The study of codon usage bias (CUB) facilitates a deeper comprehension of the molecular genetic evolution of species and their adaptive strategies. The joint analysis of CUB in chloroplast genomes (cpDNA) offers valuable insights for in-depth research on molecular genetic evolution, biological resource conservation, and elite breeding within this plant family. RESULTS: The base composition and codon usage preferences of the eighteen chloroplast genomes were highly similar, with the GC content of bases at all positions of their codons being less than 50%. This indicates that they preferred A/T bases. Their effective codon numbers were all in the range of 35-61, which indicates that the codon preferences of the chloroplast genomes of the 18 Ampelopsideae plants were relatively weak. A series of analyses indicated that the codon preference of the chloroplast genomes of the 18 Ampelopsideae plants was influenced by a combination of multiple factors, with natural selection being the primary influence. The clustering tree generated based on the relative usage of synonymous codons is consistent with some of the results obtained from the phylogenetic tree of chloroplast genomes, which indicates that the clustering tree based on the relative usage of synonymous codons can be an important supplement to the results of the sequence-based phylogenetic analysis. Eventually, 10 shared best codons were screened on the basis of the chloroplast genomes of 18 species. CONCLUSION: The codon preferences of the chloroplast genome in Ampelopsideae plants are relatively weak and are primarily influenced by natural selection. The codon composition of the chloroplast genomes of the eighteen Ampelopsideae plants and their usage preferences were sufficiently similar to demonstrate that the chloroplast genomes of Ampelopsideae plants are highly conserved. This study provides a scientific basis for the genetic evolution of chloroplast genes in Ampelopsideae species and their suitable strategies.

Characterisation of the novel HLA-DPA1*01:12:03 allele by sequencing-based typing.

HLA-DPA1*01:12:03 differs from HLA-DPA1*01:12:01 by one nucleotide substitution in codon 204 in exon 4.

The novel HLA class I allele HLA-C*07:02:81 differs from HLA-C*07:02:01:01 by a synonymous mutation.

HLA-C*07:02:81 differs from HLA-C*07:02:01:01 by one nucleotide substitution at position 465 (C→A) in exon 3.

Characterisation of two novel HLA-B alleles, B*13:194 and B*15:694 in individuals from Lithuania.

Two novel Class I HLA-B alleles HLA-B*13:194 and HLA-B*15:694 are described.

Codon usage and expression-based features significantly improve prediction of CRISPR efficiency.

CRISPR is a precise and effective genome editing technology; but despite several advancements during the last decade, our ability to computationally design gRNAs remains limited. Most predictive models have relatively low predictive power and utilize only the sequence of the target site as input. Here we suggest a new category of features, which incorporate the target site genomic position and the presence of genes close to it. We calculate four features based on gene expression and codon usage bias indices. We show, on CRISPR datasets taken from 3 different cell types, that such features perform comparably with 425 state-of-the-art predictive features, ranking in the top 2-12% of features. We trained new predictive models, showing that adding expression features to them significantly improves their r2 by up to 0.04 (relative increase of 39%), achieving average correlations of up to 0.38 on their validation sets; and that these features are deemed important by different feature importance metrics. We believe that incorporating the target site's position, in addition to its sequence, in features such as we have generated here will improve our ability to predict, design and understand CRISPR experiments going forward.