Incorporating PCA and fuzzy-ART techniques into achieve organism classification based on codon usage consideration

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.

Homoeolog expression bias in allopolyploid oleaginous marine diatom Fistulifera solaris

Background

Allopolyploidy is a genomic structure wherein two or more sets of chromosomes derived from divergent parental species coexist within an organism. It is a prevalent genomic configuration in plants, as an important source of genetic variation, and also frequently confers environmental adaptability and increased crop productivity. We previously reported the oleaginous marine diatom Fistulifera solaris JPCC DA0580 to be a promising host for biofuel production and that its genome is allopolyploid, which had never previously been reported in eukaryotic microalgae. However, the study of allopolyploidy in F. solaris was hindered by the difficulty in classifying the homoeologous genes based on their progenitor origins, owing to the shortage of diatom genomic references.

Results

In this study, the allopolyploid genome of F. solaris was tentatively classified into two pseudo-parental subgenomes using sequence analysis based on GC content and codon frequency in each homoeologous gene pair. This approach clearly separated the genome into two distinct fractions, subgenome Fso_h and Fso_l, which also showed the potency of codon usage analysis to differentiate the allopolyploid subgenome. Subsequent homoeolog expression bias analysis revealed that, although both subgenomes appear to contribute to global transcription, there were subgenomic preferences in approximately 61% of homoeologous gene pairs, and the majority of these genes showed continuous bias towards a specific subgenome during lipid accumulation. Additional promoter analysis indicated the possibility of promoter motifs involved in biased transcription of homoeologous genes. Among these subgenomic preferences, genes involved in lipid metabolic pathways showed interesting patterns in that biosynthetic and degradative pathways showed opposite subgenomic preferences, suggesting the possibility that the oleaginous characteristics of F. solaris derived from one of its progenitors.

Conclusions

We report the detailed genomic structure and expression patterns in the allopolyploid eukaryotic microalga F. solaris. The allele-specific patterns reported may contribute to the oleaginous characteristics of F. solaris and also suggest the robust oleaginous characteristics of one of its progenitors. Our data reveal novel aspects of allopolyploidy in a diatom that is not only important for evolutionary studies but may also be advantageous for biofuel production in microalgae.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4691-0) contains supplementary material, which is available to authorized users.

Gene expression signatures but not cell cycle checkpoint functions distinguish AT carriers from normal individuals

Ataxia telangiectasia (AT) is a rare autosomal recessive disease caused by mutations in the ataxia telangiectasia-mutated gene (ATM). AT carriers with one mutant ATM allele are usually not severely affected although they carry an increased risk of developing cancer. There has not been an easy and reliable diagnostic method to identify AT carriers. Cell cycle checkpoint functions upon ionizing radiation (IR)-induced DNA damage and gene expression signatures were analyzed in the current study to test for differential responses in human lymphoblastoid cell lines with different ATM genotypes. While both dose- and time-dependent G1 and G2 checkpoint functions were highly attenuated in ATM-/- cell lines, these functions were preserved in ATM+/- cell lines equivalent to ATM+/+ cell lines. However, gene expression signatures at both baseline (consisting of 203 probes) and post-IR treatment (consisting of 126 probes) were able to distinguish ATM+/- cell lines from ATM+/+ and ATM-/- cell lines. Gene ontology (GO) and pathway analysis of the genes in the baseline signature indicate that ATM function-related categories, DNA metabolism, cell cycle, cell death control, and the p53 signaling pathway, were overrepresented. The same analyses of the genes in the IR-responsive signature revealed that biological categories including response to DNA damage stimulus, p53 signaling, and cell cycle pathways were overrepresented, which again confirmed involvement of ATM functions. The results indicate that AT carriers who have unaffected G1 and G2 checkpoint functions can be distinguished from normal individuals and AT patients by expression signatures of genes related to ATM functions.

Codon usage bias: causative factors, quantification methods and genome-wide patterns: with emphasis on insect genomes

Codon usage bias refers to the phenomenon where specific codons are used more often than other synonymous codons during translation of genes, the extent of which varies within and among species. Molecular evolutionary investigations suggest that codon bias is manifested as a result of balance between mutational and translational selection of such genes and that this phenomenon is widespread across species and may contribute to genome evolution in a significant manner. With the advent of whole-genome sequencing of numerous species, both prokaryotes and eukaryotes, genome-wide patterns of codon bias are emerging in different organisms. Various factors such as expression level, GC content, recombination rates, RNA stability, codon position, gene length and others (including environmental stress and population size) can influence codon usage bias within and among species. Moreover, there has been a continuous quest towards developing new concepts and tools to measure the extent of codon usage bias of genes. In this review, we outline the fundamental concepts of evolution of the genetic code, discuss various factors that may influence biased usage of synonymous codons and then outline different principles and methods of measurement of codon usage bias. Finally, we discuss selected studies performed using whole-genome sequences of different insect species to show how codon bias patterns vary within and among genomes. We conclude with generalized remarks on specific emerging aspects of codon bias studies and highlight the recent explosion of genome-sequencing efforts on arthropods (such as twelve Drosophila species, species of ants, honeybee, Nasonia and Anopheles mosquitoes as well as the recent launch of a genome-sequencing project involving 5000 insects and other arthropods) that may help us to understand better the evolution of codon bias and its biological significance.