Analyzing gene expression from relative codon usage bias in Yeast genome: a statistical significance and biological relevance

The pattern of coding sequences in the chloroplast genome of Atropa belladonna and a comparative analysis with other related genomes in the nightshade family

Atropa belladonna is a valuable medicinal plant and a commercial source of tropane alkaloids, which are frequently utilized in therapeutic practice. In this study, bioinformaticmethodologies were used to examine the pattern of coding sequences and the factors thatmight influence codon usage bias in the chloroplast genome of Atropa belladonna andother nightshade genomes. The chloroplast engineering being a promising field in modernbiotechnology, the characterization of chloroplast genome is very important. The resultsrevealed that the chloroplast genomes of Nicotiana tabacum, Solanum lycopersicum, Capsicum frutescens, Datura stramonium, Lyciumbarbarum, Solanum melongena, and Solanumtuberosum exhibited comparable codon usage patterns. In these chloroplast genomes, weobserved a weak codon usage bias. According to the correspondence analysis, the genesisof the codon use bias in these chloroplast genes might be explained by natural selection,directed mutational pressure, and other factors. GC12 and GC3S were shown to have nomeaningful relationship. Further research revealed that natural selection primarily shapedthe codon usage in A. belladonna and other nightshade genomes for translational efficiency. The sequencing properties of these chloroplast genomes were also investigated by investing the occurrences of palindromes and inverted repeats, which would be useful forfuture research on medicinal plants.

Enhanced Secretory Expression and Surface Display Level of Bombyx mori Acetylcholinesterase 2 by Pichia pastoris Based on Codon Optimization Strategy for Pesticides Setection

The cholinesterase-based spectrophotometric assay, also called enzyme inhibition method, is a good choice for rapid detection of organophosphate pesticides (OPs) and carbamate pesticides (CPs). Obviously, the cholinesterase is the core reagent in enzyme inhibition method. In our previous work, a recombinant acetylcholinesterase 2 from Bombyx mori (rBmAChE2) was expressed in yeast successfully and exhibited great sensitivity. However, the yield of rBmAChE2 is not desirable. In this study, a codon optimization strategy was employed to enhance the yield of rBmAChE2 in Pichia pastoris GS115. Results showed that by replacing 6 key rare codons and increasing the percentage of bases G and C up to 46.85%, codon adaptation index (CAI) of Bombyx mori acetylcholinesterase 2 (bmace2) gene was improved from 0.70 to 0.81. After being transformed into Pichia pastoris GS115 via electroporation, the expression transformant can produce 139.7 U/mL secretory codon-optimized rBmAChE2 (opt-rBmAChE2) in the culture supernatant, 3.62 times higher than that of strain bearing the wild-type bmace2 gene. Meanwhile, opt-rBmAChE2 displayed on the yeast surface was up to 2280.02 U/g, 2.8 times higher than wild-type displayed rBmAChE2. In addition, either secretory or surface-displayed opt-rBmAChE2 maintained the similar sensitivities to the wild-type rBmAChE2 for tested inhibitors. Furthermore, the detection limits of the opt-rBmAChE2-based enzyme inhibition method for 10 kinds of OPs or CPs (0.01-2.69 mg/kg) were lower than most of the indexes present in current standard method (GB/T 5009.199-2003) or the maximum residue limits (GB 2763-2019) in China. The results might contribute to the utilization of rBmAChE2 for pesticide residue screening detection in practice.

Codon usage of human hepatitis C virus clearance genes in relation to its expression

Hepatitis C virus (HCV) infection is among the leading causes of hepatocellular carcinoma and liver cirrhosis globally, with a high economic burden. The disease progression is well established, but less is known about the spontaneous HCV infection clearance. This study tries to establish the relationship between codon biasness and expression of HCV clearance candidate genes in normal and HCV infected liver tissues. A total of 112 coding sequences comprising 151 679 codons were subjected to the computation of codon indices, namely relative synonymous codon usage, an effective number of codon (Nc), frequency of optimal codon, codon adaptation index, codon bias index, and base compositions. Codon indices report of GC3s, GC12, hydropathicity, and aromaticity implicates both mutational and translational selection in the candidate gene set. This was further correlated with the differentially expressed genes among the selected genes using BioGPS. A significant correlation is observed between the gene expression of normal liver and cancerous liver tissues with codon bias (Nc). Gene expression is also correlated with relative codon bias values, indicating that CCL5, APOA2, CD28, IFITM1, and TNFSF4 genes have higher expression. These results are quite encouraging in selecting the high responsive genes in HCV clearance. However, there could be additional genes which could also orchestrate the clearance role with the above mentioned first line of defensive genes.

Codon usage pattern and predicted gene expression in Arabidopsis thaliana

The extensive research for predicting highly expressed genes in plant genome sequences has been going on for decades. The codon usage pattern of genes in Arabidopsis thaliana genome is a classical topic for plant biologists for its significance in the understanding of molecular plant biology. Here we have used a gene expression profiling methodology based on the score of modified relative codon bias (MRCBS) to elucidate expression pattern of genes in Arabidopsis thaliana. MRCBS relies exclusively on sequence features for identifying the highly expressed genes. In this study, a critical analysis of predicted highly expressed (PHE) genes in Arabidopsis thaliana has been performed using MRCBS as a numerical estimator of gene expression level. Consistent with previous other results, our study indicates that codon composition plays an important role in the regulation of gene expression. We found a systematic strong correlation between MRCBS and CAI (codon adaptation index) or other expression-measures. Additionally, MRCBS correlates well with experimental gene expression data. Our study highlights the relationship between gene expression and compositional signature in relation to codon usage bias and sets the ground for the further investigation of the evolution of the protein-coding genes in the plant genome.

Synonymous Codon Usages as an Evolutionary Dynamic for Chlamydiaceae

The family of Chlamydiaceae contains a group of obligate intracellular bacteria that can infect a wide range of hosts. The evolutionary trend of members in this family is a hot topic, which benefits our understanding of the cross-infection of these pathogens. In this study, 14 whole genomes of 12 Chlamydia species were used to investigate the nucleotide, codon, and amino acid usage bias by synonymous codon usage value and information entropy method. The results showed that all the studied Chlamydia spp. had A/T rich genes with over-represented A or T at the third positions and G or C under-represented at these positions, suggesting that nucleotide usages influenced synonymous codon usages. The overall codon usage trend from synonymous codon usage variations divides the Chlamydia spp. into four separate clusters, while amino acid usage divides the Chlamydia spp. into two clusters with some exceptions, which reflected the genetic diversity of the Chlamydiaceae family members. The overall codon usage pattern represented by the effective number of codons (ENC) was significantly positively correlated to gene GC3 content. A negative correlation exists between ENC and the codon adaptation index for some Chlamydia species. These results suggested that mutation pressure caused by nucleotide composition constraint played an important role in shaping synonymous codon usage patterns. Furthermore, codon usage of T3ss and Pmps gene families adapted to that of the corresponding genome. Taken together, analyses help our understanding of evolutionary interactions between nucleotide, synonymous codon, and amino acid usages in genes of Chlamydiaceae family members.

Comparative Analysis of Predicted Gene Expression among Crenarchaeal Genomes

Research into new methods for identifying highly expressed genes in anonymous genome sequences has been going on for more than 15 years. We presented here an alternative approach based on modified score of relative codon usage bias to identify highly expressed genes in crenarchaeal genomes. The proposed algorithm relies exclusively on sequence features for identifying the highly expressed genes. In this study, a comparative analysis of predicted highly expressed genes in five crenarchaeal genomes was performed using the score of Modified Relative Codon Bias Strength (MRCBS) as a numerical estimator of gene expression level. We found a systematic strong correlation between Codon Adaptation Index and MRCBS. Additionally, MRCBS correlated well with other expression measures. Our study indicates that MRCBS can consistently capture the highly expressed genes.

BioCode: two biologically compatible Algorithms for embedding data in non-coding and coding regions of DNA

BACKGROUND

In recent times, the application of deoxyribonucleic acid (DNA) has diversified with the emergence of fields such as DNA computing and DNA data embedding. DNA data embedding, also known as DNA watermarking or DNA steganography, aims to develop robust algorithms for encoding non-genetic information in DNA. Inherently DNA is a digital medium whereby the nucleotide bases act as digital symbols, a fact which underpins all bioinformatics techniques, and which also makes trivial information encoding using DNA straightforward. However, the situation is more complex in methods which aim at embedding information in the genomes of living organisms. DNA is susceptible to mutations, which act as a noisy channel from the point of view of information encoded using DNA. This means that the DNA data embedding field is closely related to digital communications. Moreover it is a particularly unique digital communications area, because important biological constraints must be observed by all methods. Many DNA data embedding algorithms have been presented to date, all of which operate in one of two regions: non-coding DNA (ncDNA) or protein-coding DNA (pcDNA).

RESULTS

This paper proposes two novel DNA data embedding algorithms jointly called BioCode, which operate in ncDNA and pcDNA, respectively, and which comply fully with stricter biological restrictions. Existing methods comply with some elementary biological constraints, such as preserving protein translation in pcDNA. However there exist further biological restrictions which no DNA data embedding methods to date account for. Observing these constraints is key to increasing the biocompatibility and in turn, the robustness of information encoded in DNA.

CONCLUSION

The algorithms encode information in near optimal ways from a coding point of view, as we demonstrate by means of theoretical and empirical (in silico) analyses. Also, they are shown to encode information in a robust way, such that mutations have isolated effects. Furthermore, the preservation of codon statistics, while achieving a near-optimum embedding rate, implies that BioCode pcDNA is also a near-optimum first-order steganographic method.

Universal pattern and diverse strengths of successive synonymous codon bias in three domains of life, particularly among prokaryotic genomes

There has been significant progress in understanding the process of protein translation in recent years. One of the best examples is the discovery of usage bias in successive synonymous codons and its role in eukaryotic translation efficiency. We observed here a similar type of bias in the other two life domains, bacteria and archaea, although the bias strength was much smaller than in eukaryotes. Among 136 prokaryotic genomes, 98 were found to have significant bias from random use of successive synonymous codons with Z scores larger than three. Furthermore, significantly different bias strengths were found between prokaryotes grouped by various genomic or biochemical characteristics. Interestingly, the bias strength measured by a general Z score could be fitted well (R = 0.83, P < 10⁻¹⁵) by three genomic variables: genome size, G + C content, and tRNA gene number based on multiple linear regression. A different distribution of synonymous codon pairs between protein-coding genes and intergenic sequences suggests that bias is caused by translation selection. The present results indicate that protein translation is tuned by codon (pair) usage, and the intensity of the regulation is associated with genome size, tRNA gene number, and G + C content.

Comparative analysis of codon usage bias and codon context patterns between dipteran and hymenopteran sequenced genomes

Background

Codon bias is a phenomenon of non-uniform usage of codons whereas codon context generally refers to sequential pair of codons in a gene. Although genome sequencing of multiple species of dipteran and hymenopteran insects have been completed only a few of these species have been analyzed for codon usage bias.

Methods and Principal Findings

Here, we use bioinformatics approaches to analyze codon usage bias and codon context patterns in a genome-wide manner among 15 dipteran and 7 hymenopteran insect species. Results show that GAA is the most frequent codon in the dipteran species whereas GAG is the most frequent codon in the hymenopteran species. Data reveals that codons ending with C or G are frequently used in the dipteran genomes whereas codons ending with A or T are frequently used in the hymenopteran genomes. Synonymous codon usage orders (SCUO) vary within genomes in a pattern that seems to be distinct for each species. Based on comparison of 30 one-to-one orthologous genes among 17 species, the fruit fly Drosophila willistoni shows the least codon usage bias whereas the honey bee (Apis mellifera) shows the highest bias. Analysis of codon context patterns of these insects shows that specific codons are frequently used as the 3′- and 5′-context of start and stop codons, respectively.

Conclusions

Codon bias pattern is distinct between dipteran and hymenopteran insects. While codon bias is favored by high GC content of dipteran genomes, high AT content of genes favors biased usage of synonymous codons in the hymenopteran insects. Also, codon context patterns vary among these species largely according to their phylogeny.

Gene expression profile of the cynobacterium synechocystis genome

The expression of functional proteins plays a crucial role in modern biotechnology. The free-living cynobacterium Synechocystis PCC 6803 is an interesting model organism to study oxygenic photosynthesis as well as other metabolic processes. Here we analyze a gene expression profiling methodology, RCBS (the scores of relative codon usage bias) to elucidate expression patterns of genes in the Synechocystis genome. To assess the predictive performance of the methodology, we propose a simple algorithm to calculate the threshold score to identify the highly expressed genes in a genome. Analysis of differential expression of the genes of this genome reveals that most of the genes in photosynthesis and respiration belong to the highly expressed category. The other genes with the higher predicted expression level include ribosomal proteins, translation processing factors and many hypothetical proteins. Only 9.5% genes are identified as highly expressed genes and we observe that highly expressed genes in Synechocystis genome often have strong compositional bias in terms of codon usage. An important application concerns the automatic detection of a set of impact codons and genes that are highly expressed tend to use this narrow set of preferred codons and display high codon bias .We further observe a strong correlation between RCBS and protein length indicating natural selection in favor of shorter genes to be expressed at higher level. The better correlations of RCBS with 2D electrophoresis and microarray data for heat shock proteins compared to the expression measure based on codon usage difference, E(g) and codon adaptive index, CAI indicate that the genomic expression profile available in our method can be applied in a meaningful way to study the mRNA expression patterns, which are by themselves necessary for the quantitative description of the biological states.

Construction of the yeast whole-cell Rhizopus oryzae lipase biocatalyst with high activity

Surface display is effectively utilized to construct a whole-cell biocatalyst. Codon optimization has been proven to be effective in maximizing production of heterologous proteins in yeast. Here, the cDNA sequence of Rhizopus oryzae lipase (ROL) was optimized and synthesized according to the codon bias of Saccharomyces cerevisiae, and based on the Saccharomyces cerevisiae cell surface display system with α-agglutinin as an anchor, recombinant yeast displaying fully codon-optimized ROL with high activity was successfully constructed. Compared with the wild-type ROL-displaying yeast, the activity of the codon-optimized ROL yeast whole-cell biocatalyst (25 U/g dried cells) was 12.8-fold higher in a hydrolysis reaction using p-nitrophenyl palmitate (pNPP) as the substrate. To our knowledge, this was the first attempt to combine the techniques of yeast surface display and codon optimization for whole-cell biocatalyst construction. Consequently, the yeast whole-cell ROL biocatalyst was constructed with high activity. The optimum pH and temperature for the yeast whole-cell ROL biocatalyst were pH 7.0 and 40 °C. Furthermore, this whole-cell biocatalyst was applied to the hydrolysis of tributyrin and the resulted conversion of butyric acid reached 96.91% after 144 h.

Interspecific and intragenic differences in codon usage bias among vertebrate myosin heavy-chain genes

Synonymous codon usage bias is a broadly observed phenomenon in bacteria, plants, and invertebrates and may result from selection. However, the role of selective pressures in shaping codon bias is still controversial in vertebrates, particularly for mammals. The myosin heavy-chain (MyHC) gene family comprises multiple isoforms of the major force-producing contractile protein in cardiac and skeletal muscles. Slow and fast genes are tandemly arrayed on separate chromosomes, and have distinct patterns of functionality and expression in muscle. We analyze both full-length MyHC genes (~5400 bp) and a larger collection of partial sequences at the 3' end (~500 bp). The MyHC isoforms are an interesting system in which to study codon usage bias because of their length, expression, and critical importance to organismal mobility. Codon bias and GC content differs among MyHC genes with regards to functional type, isoform, and position within the gene. Codon bias even varies by isoform within a species. We find evidence in favor of both chromosomal influences on nucleotide composition and selection against nonsense errors (SANE) acting on codon usage in MyHC genes. Intragenic variation in codon bias and elongation rate is significant, with a strong trend for increasing codon bias and elongation rate towards the 3' end of the gene, although the trend is dependent upon the degeneracy class of the codons. Therefore, patterns of codon usage in MyHC genes are consistent with models supporting SANE as a major force shaping codon usage.

Genes optimized by evolution for accurate and fast translation encode in Archaea and Bacteria a broad and characteristic spectrum of protein functions

Background

In many microbial genomes, a strong preference for a small number of codons can be observed in genes whose products are needed by the cell in large quantities. This codon usage bias (CUB) improves translational accuracy and speed and is one of several factors optimizing cell growth. Whereas CUB and the overrepresentation of individual proteins have been studied in detail, it is still unclear which high-level metabolic categories are subject to translational optimization in different habitats.

Results

In a systematic study of 388 microbial species, we have identified for each genome a specific subset of genes characterized by a marked CUB, which we named the effectome. As expected, gene products related to protein synthesis are abundant in both archaeal and bacterial effectomes. In addition, enzymes contributing to energy production and gene products involved in protein folding and stabilization are overrepresented. The comparison of genomes from eleven habitats shows that the environment has only a minor effect on the composition of the effectomes. As a paradigmatic example, we detailed the effectome content of 37 bacterial genomes that are most likely exposed to strongest selective pressure towards translational optimization. These effectomes accommodate a broad range of protein functions like enzymes related to glycolysis/gluconeogenesis and the TCA cycle, ATP synthases, aminoacyl-tRNA synthetases, chaperones, proteases that degrade misfolded proteins, protectants against oxidative damage, as well as cold shock and outer membrane proteins.

Conclusions

We made clear that effectomes consist of specific subsets of the proteome being involved in several cellular functions. As expected, some functions are related to cell growth and affect speed and quality of protein synthesis. Additionally, the effectomes contain enzymes of central metabolic pathways and cellular functions sustaining microbial life under stress situations. These findings indicate that cell growth is an important but not the only factor modulating translational accuracy and speed by means of CUB.

Expression breadth and expression abundance behave differently in correlations with evolutionary rates

Background

One of the main objectives of the molecular evolution and evolutionary systems biology field is to reveal the underlying principles that dictate protein evolutionary rates. Several studies argue that expression abundance is the most critical component in determining the rate of evolution, especially in unicellular organisms. However, the expression breadth also needs to be considered for multicellular organisms.

Results

In the present paper, we analyzed the relationship between the two expression variables and rates using two different genome-scale expression datasets, microarrays and ESTs. A significant positive correlation between the expression abundance (EA) and expression breadth (EB) was revealed by Kendall's rank correlation tests. A novel random shuffling approach was applied for EA and EB to compare the correlation coefficients obtained from real data sets to those estimated based on random chance. A novel method called a Fixed Group Analysis (FGA) was designed and applied to investigate the correlations between expression variables and rates when one of the two expression variables was evenly fixed.

Conclusions

In conclusion, all of these analyses and tests consistently showed that the breadth rather than the abundance of gene expression is tightly linked with the evolutionary rate in multicellular organisms.

Relative codon adaptation: a generic codon bias index for prediction of gene expression

The development of codon bias indices (CBIs) remains an active field of research due to their myriad applications in computational biology. Recently, the relative codon usage bias (RCBS) was introduced as a novel CBI able to estimate codon bias without using a reference set. The results of this new index when applied to Escherichia coli and Saccharomyces cerevisiae led the authors of the original publications to conclude that natural selection favours higher expression and enhanced codon usage optimization in short genes. Here, we show that this conclusion was flawed and based on the systematic oversight of an intrinsic bias for short sequences in the RCBS index and of biases in the small data sets used for validation in E. coli. Furthermore, we reveal that how the RCBS can be corrected to produce useful results and how its underlying principle, which we here term relative codon adaptation (RCA), can be made into a powerful reference-set-based index that directly takes into account the genomic base composition. Finally, we show that RCA outperforms the codon adaptation index (CAI) as a predictor of gene expression when operating on the CAI reference set and that this improvement is significantly larger when analysing genomes with high mutational bias.