CUBAP: an interactive web portal for analyzing codon usage biases across populations

Ramp Sequence May Explain Synonymous Variant Association with Alzheimer's Disease in the Paired Immunoglobulin-like Type 2 Receptor Alpha (PILRA)

Background: The synonymous variant NC_000007.14:g.100373690T>C (rs2405442:T>C) in the Paired Immunoglobulin-like Type 2 Receptor Alpha (PILRA) gene was previously associated with decreased risk for Alzheimer's disease (AD) in genome-wide association studies, but its biological impact is largely unknown. Objective: We hypothesized that rs2405442:T>C decreases mRNA and protein levels by destroying a ramp of slowly translated codons at the 5' end of PILRA. Methods: We assessed rs2405442:T>C predicted effects on PILRA through quantitative polymerase chain reactions (qPCRs) and enzyme-linked immunosorbent assays (ELISAs) using Chinese hamster ovary (CHO) cells. RESULTS: Both mRNA (p = 1.9184 × 10-13) and protein (p = 0.01296) levels significantly decreased in the mutant versus the wildtype in the direction that we predicted based on the destruction of a ramp sequence. Conclusions: We show that rs2405442:T>C alone directly impacts PILRA mRNA and protein expression, and ramp sequences may play a role in regulating AD-associated genes without modifying the protein product.

Ramp sequence may explain synonymous variant association with Alzheimer's disease in the Paired Immunoglobulin-like Type 2 Receptor Alpha (PILRA)

BACKGROUND

Synonymous variant NC_000007.14:g.100373690T>C (rs2405442:T>C) in the Paired Immunoglobulin-like Type 2 Receptor Alpha (PILRA) gene was previously associated with decreased risk for Alzheimer's disease (AD) in genome-wide association studies, but its biological impact is largely unknown.

OBJECTIVE

We hypothesized that rs2405442:T>C decreases mRNA and protein levels by destroying a ramp of slowly translated codons at the 5' end of PILRA.

METHODS

We assessed rs2405442:T>C predicted effects on PILRA through quantitative polymerase chain reactions (qPCR) and enzyme-linked immunosorbent assays (ELISA) using Chinese hamster ovary (CHO) cells.

RESULTS

Both mRNA (P=1.9184 × 10-13) and protein (P=0.01296) levels significantly decreased in the mutant versus the wildtype in the direction that we predicted based on destroying a ramp sequence.

CONCLUSIONS

We show that rs2405442:T>C alone directly impacts PILRA mRNA and protein expression, and ramp sequences may play a role in regulating AD-associated genes without modifying the protein product.

CodonU: A Python Package for Codon Usage Analysis

Codon Usage Analysis (CUA) has been accompanied by several web servers and independent programs written in several programming languages. Also this diversity speaks for the need of a reusable software that can be helpful in reading, manipulating and acting as a pipeline for such data and file formats. This kind of analyses use multiple tools to address the multifaceted aspects of CUA. So, we propose CodonU, a package written in Python language to integrate all aspects. It is compatible with existing file formats and can be used solely or with a group of other such packages. The proposed package incorporates various statistical measures necessary for codon usage analysis. The measures vary with nature of the sequences, viz. for nucleotide, codon adaptation index (CAI), codon bias index (CBI), tRNA adaptation index (tAI) etc. and for protein sequences Gravy score etc. Users can also perform the correspondence analysis (COA). This package also provides the liberty to generate graphics to users, and also develop phylogenetic tree. Capabilities of the proposed package were checked thoroughly on a genomic set of Staphylococcus aureus.

In-silico Codon Context and Synonymous Usage Analysis of Genes for Molecular Mechanisms Inducing Autophagy and Apoptosis with Reference to Neurodegenerative Disorders

Background

Autophagy and apoptosis are cellular processes that maintain cellular homeostasis and remove damaged or aged organelles or aggregated and misfolded proteins. Stress factors initiate the signaling pathways common to autophagy and apoptosis. An imbalance in the autophagy and apoptosis, led by cascade of molecular mechanism prior to both processes culminate into neurodegeneration.

Objective

In present study, we urge to investigate the codon usage pattern of genes which are common before initiating autophagy and apoptosis.

Methods

In the present study, we took up eleven genes (DAPK1, BECN1, PIK3C3 (VPS34), BCL2, MAPK8, BNIP3 L (NIX), PMAIP1, BAD, BID, BBC3, MCL1) that are part of molecular signaling mechanism prior to autophagy and apoptosis. We analyzed dinucleotide odds ratio, codon bias, usage, context, and rare codon analysis.

Results

CpC and GpG dinucleotides were abundant, with the dominance of G/C ending codons as preferred codons. Clustering analysis revealed that MAPK8 had a distinct codon usage pattern compared to other envisaged genes. Both positive and negative contexts were observed, and GAG-GAG followed by CTG-GCC was the most abundant codon pair. Of the six synonymous arginine codons, two codons CGT and CGA were the rarest.

Conclusions

The information presented in the study may be used to manipulate the process of autophagy and apoptosis and to check the pathophysiology associated with their dysregulation.

Synonymous Codon Variant Analysis for Autophagic Genes Dysregulated in Neurodegeneration

Neurodegenerative disorders are often a culmination of the accumulation of abnormally folded proteins and defective organelles. Autophagy is a process of removing these defective proteins, organelles, and harmful substances from the body, and it works to maintain homeostasis. If autophagic removal of defective proteins has interfered, it affects neuronal health. Some of the autophagic genes are specifically found to be associated with neurodegenerative phenotypes. Non-functional, mutated, or gene copies having silent mutations, often termed synonymous variants, might explain this. However, these synonymous variant which codes for exactly similar proteins have different translation rates, stability, and gene expression profiling. Hence, it would be interesting to study the pattern of synonymous variant usage. In the study, synonymous variant usage in various transcripts of autophagic genes ATG5, ATG7, ATG8A, ATG16, and ATG17/FIP200 reported to cause neurodegeneration (if dysregulated) is studied. These genes were analyzed for their synonymous variant usage; nucleotide composition; any possible nucleotide skew in a gene; physical properties of autophagic protein including GRAVY and AROMA; hydropathicity; instability index; and frequency of acidic, basic, neutral amino acids; and gene expression level. The study will help understand various evolutionary forces acting on these genes and the possible augmentation of a gene if showing unusual behavior.

The Ramp Atlas: facilitating tissue and cell-specific ramp sequence analyses through an intuitive web interface

Ramp sequences occur when the average translational efficiency of codons near the 5′ end of highly expressed genes is significantly lower than the rest of the gene sequence, which counterintuitively increases translational efficiency by decreasing downstream ribosomal collisions. Here, we show that the relative codon adaptiveness within different tissues changes the existence of a ramp sequence without altering the underlying genetic code. We present the first comprehensive analysis of tissue and cell type-specific ramp sequences and report 3108 genes with ramp sequences that change between tissues and cell types, which corresponds with increased gene expression within those tissues and cells. The Ramp Atlas (https://ramps.byu.edu/) allows researchers to query precomputed ramp sequences in 18 388 genes across 62 tissues and 66 cell types and calculate tissue-specific ramp sequences from user-uploaded FASTA files through an intuitive web interface. We used The Ramp Atlas to identify seven SARS-CoV-2 genes and seven human SARS-CoV-2 entry factor genes with tissue-specific ramp sequences that may help explain viral proliferation within those tissues. We anticipate that The Ramp Atlas will facilitate personalized and creative tissue-specific ramp sequence analyses for both human and viral genes that will increase our ability to utilize this often-overlooked regulatory region.

CompoDynamics: a comprehensive database for characterizing sequence composition dynamics

Sequence compositions of nucleic acids and proteins have significant impact on gene expression, RNA stability, translation efficiency, RNA/protein structure and molecular function, and are associated with genome evolution and adaptation across all kingdoms of life. Therefore, a devoted resource of sequence compositions and associated features is fundamentally crucial for a wide range of biological research. Here, we present CompoDynamics (https://ngdc.cncb.ac.cn/compodynamics/), a comprehensive database of sequence compositions of coding sequences (CDSs) and genomes for all kinds of species. Taking advantage of the exponential growth of RefSeq data, CompoDynamics presents a wealth of sequence compositions (nucleotide content, codon usage, amino acid usage) and derived features (coding potential, physicochemical property and phase separation) for 118 689 747 high-quality CDSs and 34 562 genomes across 24 995 species. Additionally, interactive analytical tools are provided to enable comparative analyses of sequence compositions and molecular features across different species and gene groups. Collectively, CompoDynamics bears the great potential to better understand the underlying roles of sequence composition dynamics across genes and genomes, providing a fundamental resource in support of a broad spectrum of biological studies.

Codon usage bias analysis of genes linked with esophagus cancer

Esophageal cancer involves multiple genetic alternations. A systematic codon usage bias analysis was completed to investigate the bias among the esophageal cancer responsive genes. GC-rich genes were low (average effective number of codon value was 49.28). CAG and GTA are over-represented and under-represented codons, respectively. Correspondence analysis, neutrality plot, and parity rule 2 plot analysis confirmed the dominance over mutation pressure in modulating the codon usage pattern of genes linked with esophageal cancer.