Distribution Of Nucleotides Research Articles

An independent base composition of each rate class for improved likelihood-based phylogeny estimation; the 5rf model.

The combination of a time reversible Markov process with a "hidden" mixture of gamma distributed relative site rates plus invariant sites have become the most favoured options for likelihood and other probabilistic models of nucleotide evolution (e.g., tr4gi which approximates a gamma with four rate classes). However, these models assume a homogeneous and stationary distribution of nucleotide (character or base) frequencies. Here, we explore the potential benefits and pitfalls of allowing each rate category (rate class) of a 4gi mixture model to have its own base frequencies. This is achieved by starting each of the five rate classes, at the tree's root, with its own free choice of nucleotide frequencies to create a 4gi5rf model or a 5rf model in shorthand. We assess the practical identifiability of this approach with a BEAST 2 implementation, aiming to determine if it can accurately estimate credibility intervals and expected values for a wide range of plausible parameter values. Practical identifiability, as distinguished from mathematical identifiability, gauges the model's ability to identify parameters in real-world scenarios, as opposed to theoretically with infinite data. One of the most common types of phylogenetic data is mitochondrial DNA (mtDNA) protein coding sequence. It is often assumed current models analyse robustly such data and that higher likelihood/posterior probability models do better. However, this abstract shows that vertebrate mtDNA remains a very difficult type of data to fully model, and that dramatically higher likelihoods do not mean a model is measurably more accurate with respect to recovering key parameters of biological interest (e.g., monophyletic groups, their support and their ages). The 4gi5rf model considerably improves marginal likelihoods and seems to reverse some apparent errors exacerbated by the 4gi model, while introducing others. Problems appear to be linked to non-stationary DNA repair processes that alter the mutation/substitution spectra across lineages and time. We also show such problems are not unique to mtDNA and are encountered in analysing nuclear sequences. Non-stationarity of DNA repair processes mutation/substitution spectra thus pose an active challenge to obtaining reliable inferences of relationships and divergence times near the root of placental mammals, for example. An open source implementation is available under the LGPL 3.0 license in the beastbooster package for BEAST 2, available from https://github.com/rbouckaert/beastbooster.

Deciphering the Nucleotide Distribution Dynamics of rDNA Internal Transcribed Spacer 1 in Fish Species Rita rita Using R Programming

Deciphering the Nucleotide Distribution Dynamics of rDNA Internal Transcribed Spacer 1 in Fish Species Rita rita Using R Programming

Reconstitution of peripheral blood T cell receptor β immune repertoire in immune checkpoint inhibitors associated myocarditis

PurposeImmune checkpoint inhibitors (ICIs)-associated myocarditis was a rare yet severe complication observed in individuals undergoing immunotherapy. This study investigated the immune status and characteristics of patients diagnosed with ICIs- associated myocarditis.MethodsA total of seven patients diagnosed with ICIs-associated myocarditis were included in the study, while five tumor patients without myocarditis were recruited as reference controls. Additionally, 30 healthy individuals were recruited as blank controls. Biochemical indices, electrocardiogram, and echocardiography measurements were obtained both prior to and following the occurrence of myocarditis. High-throughput sequencing of T cell receptor (TCR) was employed to assess the diversity and distribution characteristics of TCR CDR3 length, as well as the diversity of variable (V) and joining (J) genes of T lymphocytes in peripheral blood.ResultsIn the seven patients with ICIs-associated myocarditis, Troponin T (TNT) levels exhibited a significant increase following myocarditis, while other parameters such as brain natriuretic peptide (BNP), QTc interval, and left ventricular ejection fraction (LVEF) did not show any significant differences. Through sequencing, it was observed that the diversity and uniformity of CDR3 in the ICIs-associated myocarditis patients were significantly diminished. Additionally, the distribution of CDR3 nucleotides deviated from normality, and variations in the utilization of V and J gene segments.ConclusionThe reconstitution of the TCR immune repertoire may play a pivotal role in the recognition of antigens in patients with ICIs-associated myocarditis.

ТЕСТ-СИСТЕМА ДЛЯ ПРОВЕДЕНИЯ ПЦР В РЕЖИМЕ РЕАЛЬНОГО ВРЕМЕНИ ДЛЯ ОБНАРУЖЕНИЯ ДНК ТТV В БИОЛОГИЧЕСКОМ МАТЕРИАЛЕ

Background. The study of biological material for the presence of TTV DNA using the PCR method allows for a timely assessment of the functional state of the human liver and immune system. Objective. To develop components for real-time PCR for TTV DNA detection in biological material. Material and methods. The design and selection of optimal primers and probes (taking into account the size (length) of the amplicon, annealing temperature, nucleotide composition, distribution of nucleotides along the length of the primer, length of primers, the possibility of formation of hairpins and dimers by primers) were performed using the Primer-BLAST/Primer3, FastPCR programs. Since primers, even absolutely unique for certain DNA sequences, could anneal at nonspecific sites, not related to the gene analyzed, we checked the correspondence of the primers to the sequences of the target gene. For this purpose, we used the NCBI Primer BLAST online service and assessed the local pairwise alignment of each primer with all nucleotide sequences of the Refseq databases. Results. As the result of studies carried out on the selection of the optimal primer annealing temperature, primer concentrations, as well as the selection of the optimal nucleotide pair, the main parameters of the designed primers were determined. Conclusions. A kit for the detection and quantification of TTV DNA using the polymerase chain reaction method with hybridization-fluorescent detection in real time was created and became the basis for the development of a commercial test system.

Long extrachromosomal circular DNA identification by fusing sequence-derived features of physicochemical properties and nucleotide distribution patterns

Long extrachromosomal circular DNA (leccDNA) regulates several biological processes such as genomic instability, gene amplification, and oncogenesis. The identification of leccDNA holds significant importance to investigate its potential associations with cancer, autoimmune, cardiovascular, and neurological diseases. In addition, understanding these associations can provide valuable insights about disease mechanisms and potential therapeutic approaches. Conventionally, wet lab-based methods are utilized to identify leccDNA, which are hindered by the need for prior knowledge, and resource-intensive processes, potentially limiting their broader applicability. To empower the process of leccDNA identification across multiple species, the paper in hand presents the very first computational predictor. The proposed iLEC-DNA predictor makes use of SVM classifier along with sequence-derived nucleotide distribution patterns and physicochemical properties-based features. In addition, the study introduces a set of 12 benchmark leccDNA datasets related to three species, namely Homo sapiens (HM), Arabidopsis Thaliana (AT), and Saccharomyces cerevisiae (SC/YS). It performs large-scale experimentation across 12 benchmark datasets under different experimental settings using the proposed predictor, more than 140 baseline predictors, and 858 encoder ensembles. The proposed predictor outperforms baseline predictors and encoder ensembles across diverse leccDNA datasets by producing average performance values of 81.09%, 62.2% and 81.08% in terms of ACC, MCC and AUC-ROC across all the datasets. The source code of the proposed and baseline predictors is available at https://github.com/FAhtisham/Extrachrosmosomal-DNA-Prediction. To facilitate the scientific community, a web application for leccDNA identification is available at https://sds_genetic_analysis.opendfki.de/iLEC_DNA/.

Position-specific evolution in transcription factor binding sites, and a fast likelihood calculation for the F81 model.

Transcription factor binding sites (TFBS), like other DNA sequence, evolve via mutation and selection relating to their function. Models of nucleotide evolution describe DNA evolution via single-nucleotide mutation. A stationary vector of such a model is the long-term distribution of nucleotides, unchanging under the model. Neutrally evolving sites may have uniform stationary vectors, but one expects that sites within a TFBS instead have stationary vectors reflective of the fitness of various nucleotides at those positions. We introduce 'position-specific stationary vectors' (PSSVs), the collection of stationary vectors at each site in a TFBS locus, analogous to the position weight matrix (PWM) commonly used to describe TFBS. We infer PSSVs for human TFs using two evolutionary models (Felsenstein 1981 and Hasegawa-Kishino-Yano 1985). We find that PSSVs reflect the nucleotide distribution from PWMs, but with reduced specificity. We infer ancestral nucleotide distributions at individual positions and calculate 'conditional PSSVs' conditioned on specific choices of majority ancestral nucleotide. We find that certain ancestral nucleotides exert a strong evolutionary pressure on neighbouring sequence while others have a negligible effect. Finally, we present a fast likelihood calculation for the F81 model on moderate-sized trees that makes this approach feasible for large-scale studies along these lines.

BERT-5mC: an interpretable model for predicting 5-methylcytosine sites of DNA based on BERT

DNA 5-methylcytosine (5mC) is widely present in multicellular eukaryotes, which plays important roles in various developmental and physiological processes and a wide range of human diseases. Thus, it is essential to accurately detect the 5mC sites. Although current sequencing technologies can map genome-wide 5mC sites, these experimental methods are both costly and time-consuming. To achieve a fast and accurate prediction of 5mC sites, we propose a new computational approach, BERT-5mC. First, we pre-trained a domain-specific BERT (bidirectional encoder representations from transformers) model by using human promoter sequences as language corpus. BERT is a deep two-way language representation model based on Transformer. Second, we fine-tuned the domain-specific BERT model based on the 5mC training dataset to build the model. The cross-validation results show that our model achieves an AUROC of 0.966 which is higher than other state-of-the-art methods such as iPromoter-5mC, 5mC_Pred, and BiLSTM-5mC. Furthermore, our model was evaluated on the independent test set, which shows that our model achieves an AUROC of 0.966 that is also higher than other state-of-the-art methods. Moreover, we analyzed the attention weights generated by BERT to identify a number of nucleotide distributions that are closely associated with 5mC modifications. To facilitate the use of our model, we built a webserver which can be freely accessed at: http://5mc-pred.zhulab.org.cn.

Phosphodiesterase in heart and vessels: from physiology to diseases.

Phosphodiesterases (PDEs) are a superfamily of enzymes that hydrolyze cyclic nucleotides, including cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP). Both cyclic nucleotides are critical secondary messengers in the neurohormonal regulation in the cardiovascular system. PDEs precisely control spatiotemporal subcellular distribution of cyclic nucleotides in a cell- and tissue-specific manner, playing critical roles in physiological responses to hormone stimulation in the heart and vessels. Dysregulation of PDEs has been linked to the development of several cardiovascular diseases, such as hypertension, aneurysm, atherosclerosis, arrhythmia, and heart failure. Targeting these enzymes has been proven effective in treating cardiovascular diseases and is an attractive and promising strategy for the development of new drugs. In this review, we discuss the current understanding of the complex regulation of PDE isoforms in cardiovascular function, highlighting the divergent and even opposing roles of PDE isoforms in different pathogenesis.

Physics-Based Signal Analysis of Genome Sequences: An Overview of GenomeBits.

A comprehensive overview of the recent physics-inspired genome analysis tool, GenomeBits, is presented. This is based on traditional signal processing methods such as discrete Fourier transform (DFT). GenomeBits can be used to extract underlying genomics features from the distribution of nucleotides, and can be further used to analyze the mutation patterns in viral genomes. Examples of the main GenomeBits findings outlining the intrinsic signal organization of genomics sequences for different SARS-CoV-2 variants along the pandemic years 2020-2022 and Monkeypox cases in 2021 are presented to show the usefulness of GenomeBits. GenomeBits results for DFT of SARS-CoV-2 genomes in different geographical regions are discussed, together with the GenomeBits analysis of complete genome sequences for the first coronavirus variants reported: Alpha, Beta, Gamma, Epsilon and Eta. Interesting features of the Delta and Omicron variants in the form of a unique 'order-disorder' transition are uncovered from these samples, as well as from their cumulative distribution function and scatter plots. This class of transitions might reveal the cumulative outcome of mutations on the spike protein. A salient feature of GenomeBits is the mapping of the nucleotide bases (A,T,C,G) into an alternating spin-like numerical sequence via a series having binary (0,1) indicators for each A,T,C,G. This leads to the derivation of a set of statistical distribution curves. Furthermore, the quantum-based extension of the GenomeBits model to an analogous probability measure is shown to identify properties of genome sequences as wavefunctions via a superposition of states. An association of the integral of the GenomeBits coding and a binding-like energy can, in principle, also be established. The relevance of these different results in bioinformatics is analyzed.

Polarized distribution of extracellular nucleotides promotes gravity-directed polarization of development in spores of Ceratopteris richardii.

Gravity directs the polarization of Ceratopteris fern spores. This process begins with the uptake of calcium through channels at the bottom of the spore, a step necessary for the gravity response. Data showing that extracellular ATP (eATP) regulates calcium channels led to the hypothesis that extracellular nucleotides could play a role in the gravity-directed polarization of Ceratopteris spores. In animal and plant cells ATP can be released from mechanosensitive channels. This report tests the hypothesis that the polarized release of ATP from spores could be activated by gravity, preferentially along the bottom of the spore, leading to an asymmetrical accumulation of eATP. In order to carry out this test, an ATP biosensor was used to measure the [eATP] at the bottom and top of germinating spores during gravity-directed polarization. The [eATP] along the bottom of the spore averaged 7-fold higher than the concentration at the top. All treatments that disrupted eATP signaling resulted in a statistically significant decrease in the gravity response. In order to investigate the source of ATP release, spores were treated with Brefeldin A (BFA) and gadolinium trichloride (GdCl3). These treatments resulted in a significant decrease in gravity-directed polarization. An ATP biosensor was also used to measure ATP release after treatment with both BFA and GdCl3. Both of these treatments caused a significant decrease in [ATP] measured around spores. These results support the hypothesis that ATP could be released from mechanosensitive channels and secretory vesicles during the gravity-directed polarization of Ceratopteris spores.

Molecular variability of the Ancylostoma secreted Protein-2 (Aca-asp-2) gene from Ancylostoma caninum contributes to expand information on population genetic studies of hookworms

Hookworm infection is a major public health problem in many regions of the world. Given the high levels of host morbidity and even mortality of the host caused by these infections, it is crucial to understand the genetic structure of hookworm populations. This understanding can provide insights into the ecology, transmission patterns, mechanisms of drug resistance, and the development of vaccines and immunotherapeutic strategies. Previously, we examined presumably neutral molecular markers, such as microsatellites and COI (Cytochrome C oxidase subunit 1) in Brazilian populations of Ancylostoma caninum. Here we analyze the molecular variability of a genomic fragment of the Aca-asp-2 (Ancylostoma secreted protein-2) gene from Ancylostoma caninum. This gene is a highly expressed and activated following the infection of the L3 larvae in the host. We obtained individuals of A. caninum from five different geographic locations in Brazil, sequenced and analyzed parts of the gene. The results revealed extensive polymorphism at this fragment, especially in the intronic region, indicating low selective pressure acting on these sequences. However, we also observed irregular distributions of nucleotides and polymorphisms in the coding region of this gene, resulting in the identification of 27 alleles. The data presented here contribute to expanding the understanding of population genetic studies of hookworms.

Feeding the microbiota–gut–brain axis: Nucleotides and their role in early life

AbstractNucleotides ingested from breast milk and complementary foods during infancy play a vital role in the development of the immune and nervous system, as well as the maturation of gut function, and are considered a “special dietary nutrient.” Based on the existing research progress and theoretical basis, this review takes the distribution of dietary nucleotides (NTs) in the early life (after birth to the age of 3 years) diet and the in vivo metabolism/absorption process as the starting point and expounds on its potential impact and mechanism of action on early gastrointestinal and brain development. With the understanding of gut microbiota (GM), the interaction between dietary factors and GM has become a focus of food research. It is of great significance to reexamine the biological effects of early dietary nucleotide intake on infant gut–brain development from the perspective of the GM–gut–brain axis. This paper reveals the potential relationship between the NTs–GM–gut–brain axis and provides new ideas and theories for the research and application of NTs in the field of infant nutrition.

The Influence of the Selection at the Amino Acid Level on Synonymous Codon Usage from the Viewpoint of Alternative Genetic Codes

Synonymous codon usage can be influenced by mutations and/or selection, e.g., for speed of protein translation and correct folding. However, this codon bias can also be affected by a general selection at the amino acid level due to differences in the acceptance of the loss and generation of these codons. To assess the importance of this effect, we constructed a mutation-selection model model, in which we generated almost 90,000 stationary nucleotide distributions produced by mutational processes and applied a selection based on differences in physicochemical properties of amino acids. Under these conditions, we calculated the usage of fourfold degenerated (4FD) codons and compared it with the usage characteristic of the pure mutations. We considered both the standard genetic code (SGC) and alternative genetic codes (AGCs). The analyses showed that a majority of AGCs produced a greater 4FD codon bias than the SGC. The mutations producing more thymine or adenine than guanine and cytosine increased the differences in usage. On the other hand, the mutational pressures generating a lot of cytosine or guanine with a low content of adenine and thymine decreased this bias because the nucleotide content of most 4FD codons stayed in the compositional equilibrium with these pressures. The comparison of the theoretical results with those for real protein coding sequences showed that the influence of selection at the amino acid level on the synonymous codon usage cannot be neglected. The analyses indicate that the effect of amino acid selection cannot be disregarded and that it can interfere with other selection factors influencing codon usage, especially in AT-rich genomes, in which AGCs are usually used.

Boquila: NGS read simulator to eliminate read nucleotide bias in sequence analysis.

Sequence content is heterogeneous throughout genomes. Therefore, genome-wide next-generation sequencing (NGS) reads biased towards specific nucleotide profiles are affected by the genome-wide heterogeneous nucleotide distribution. Boquila generates sequences that mimic the nucleotide profile of true reads, which can be used to correct the nucleotide-based bias of genome-wide distribution of NGS reads. Boquila can be configured to generate reads from only specified regions of the reference genome. It also allows the use of input DNA sequencing to correct the bias due to the copy number variations in the genome. Boquila uses standard file formats for input and output data, and it can be easily integrated into any workflow for high-throughput sequencing applications.

SARS-CoV-2 Variants of Concern and Variations within Their Genome Architecture: Does Nucleotide Distribution and Mutation Rate Alter the Functionality and Evolution of the Virus?

SARS-CoV-2 virus pathogenicity and transmissibility are correlated with the mutations acquired over time, giving rise to variants of concern (VOCs). Mutations can significantly influence the genetic make-up of the virus. Herein, we analyzed the SARS-CoV-2 genomes and sub-genomic nucleotide composition in relation to the mutation rate. Nucleotide percentage distributions of 1397 in-house-sequenced SARS-CoV-2 genomes were enumerated, and comparative analyses (i) within the VOCs and of (ii) recovered and mortality patients were performed. Fisher's test was carried out to highlight the significant mutations, followed by RNA secondary structure prediction and protein modeling for their functional impacts. Subsequently, a uniform dinucleotide composition of AT and GC was found across study cohorts. Notably, the N gene was observed to have a high GC percentage coupled with a relatively higher mutation rate. Functional analysis demonstrated the N gene mutations, C29144T and G29332T, to induce structural changes at the RNA level. Protein secondary structure prediction with N gene missense mutations revealed a differential composition of alpha helices, beta sheets, and coils, whereas the tertiary structure displayed no significant changes. Additionally, the N gene CTD region displayed no mutations. The analysis highlighted the importance of N protein in viral evolution with CTD as a possible target for antiviral drugs.

Preliminary identification and analysis of differential RNA editing between higher and lower backfat thickness pigs using DNA-seq and RNA-seq data.

RNA editing is an essential post-transcriptional regulatory mechanism. However, few studies have investigated the functional RNA edits in the economic traits of livestock on a genome-wide scale. Pigs are one of the most important livestock species and their fat is the principal organ involved in the regulation of adipose deposition. Here, we used three full-sibling pairs, with each pair comprising a pig with higher backfat (BF) thickness and lower backfat thickness, to identify RNA editing events based on whole-genome and transcriptome sequencing data. A total of 60,903 non-redundant RNA editing sites with 59,472 (97.7%) A-to-G edits were detected using a revised bioinformatics pipeline. A specific sequence context with G preference was found one base downstream of the edited site, and the editing level was associated with the distribution of nucleotides across nearly sites. Moreover, the A-to-G editing sites mostly occurred in the pig-special short interspersed nuclear elements, Pre0_SS. Comparing the difference between pigs with higher BF and lower BF, we found 211 differentially edited sites (DESites). Functional enrichment analyses revealed a significant enrichment of genes containing DESites in terms of adipose deposition. The DESites located in the six adipose-related genes (SKP1, GSK3B, COL5A3, MDM4, NT5C2, and DENND2A) were selected as candidate RNA editing sites associated with adipose deposition, and thus require further evaluation. This study mined the potentially functional RNA editing sites in pig adipose tissue and indicated that RNA editing may play an important role in adipose deposition, which provides a new insight into the post-transcriptionally mediated regulation mechanism of fat development.

IDDLncLoc: Subcellular Localization of LncRNAs Based on a Framework for Imbalanced Data Distributions.

Long non-coding RNAs play a crucial role in many life processes of cell, such as genetic markers, RNA splicing, signaling, and protein regulation. Considering that identifying lncRNA's localization in the cell through experimental methods is complicated, hard to reproduce, and expensive, we propose a novel method named IDDLncLoc in this paper, which adopts an ensemble model to solve the problem of the subcellular localization. In the proposal model, dinucleotide-based auto-cross covariance features, k-mer nucleotide composition features, and composition, transition, and distribution features are introduced to encode a raw RNA sequence to vector. To screen out reliable features, feature selection through binomial distribution, and recursive feature elimination is employed. Furthermore, strategies of oversampling in mini-batch, random sampling, and stacking ensemble strategies are customized to overcome the problem of data imbalance on the benchmark dataset. Finally, compared with the latest methods, IDDLncLoc achieves an accuracy of 94.96% on the benchmark dataset, which is 2.59% higher than the best method, and the results further demonstrate IDDLncLoc is excellent on the subcellular localization of lncRNA. Besides, a user-friendly web server is available at http://lncloc.club .

Full Chromosomal Relationships Between Populations and the Origin of Humans.

A comprehensive description of human genomes is essential for understanding human evolution and relationships between modern populations. However, most published literature focuses on local alignment comparison of several genes rather than the complete evolutionary record of individual genomes. Combining with data from the 1,000 Genomes Project, we successfully reconstructed 2,504 individual genomes and propose Divided Natural Vector method to analyze the distribution of nucleotides in the genomes. Comparisons based on autosomes, sex chromosomes and mitochondrial genomes reveal the genetic relationships between populations, and different inheritance pattern leads to different phylogenetic results. Results based on mitochondrial genomes confirm the “out-of-Africa” hypothesis and assert that humans, at least females, most likely originated in eastern Africa. The reconstructed genomes are stored on our server and can be further used for any genome-scale analysis of humans (http://yaulab.math.tsinghua.edu.cn/2022_1000genomesprojectdata/). This project provides the complete genomes of thousands of individuals and lays the groundwork for genome-level analyses of the genetic relationships between populations and the origin of humans.

Context dependency of nucleotide probabilities and variants in human DNA

BackgroundGenomic DNA has been shaped by mutational processes through evolution. The cellular machinery for error correction and repair has left its marks in the nucleotide composition along with structural and functional constraints. Therefore, the probability of observing a base in a certain position in the human genome is highly context-dependent.ResultsHere we develop context-dependent nucleotide models. We first investigate models of nucleotides conditioned on sequence context. We develop a bidirectional Markov model that use an average of the probability from a Markov model applied to both strands of the sequence and thus depends on up to 14 bases to each side of the nucleotide. We show how the genome predictability varies across different types of genomic regions. Surprisingly, this model can predict a base from its context with an average of more than 50% accuracy. For somatic variants we show a tendency towards higher probability for the variant base than for the reference base. Inspired by DNA substitution models, we develop a model of mutability that estimates a mutation matrix (called the alpha matrix) on top of the nucleotide distribution. The alpha matrix can be estimated from a much smaller context than the nucleotide model, but the final model will still depend on the full context of the nucleotide model. With the bidirectional Markov model of order 14 and an alpha matrix dependent on just one base to each side, we obtain a model that compares well with a model of mutability that estimates mutation probabilities directly conditioned on three nucleotides to each side. For somatic variants in particular, our model fits better than the simpler model. Interestingly, the model is not very sensitive to the size of the context for the alpha matrix.ConclusionsOur study found strong context dependencies of nucleotides in the human genome. The best model uses a context of 14 nucleotides to each side. Based on these models, a substitution model was constructed that separates into the context model and a matrix dependent on a small context. The model fit somatic variants particularly well.

Identification of HIV Rapid Mutations Using Differences in Nucleotide Distribution over Time.

Mutation is the driving force of species evolution, which may change the genetic information of organisms and obtain selective competitive advantages to adapt to environmental changes. It may change the structure or function of translated proteins, and cause abnormal cell operation, a variety of diseases and even cancer. Therefore, it is particularly important to identify gene regions with high mutations. Mutations will cause changes in nucleotide distribution, which can be characterized by natural vectors globally. Based on natural vectors, we propose a mathematical formula for measuring the difference in nucleotide distribution over time to investigate the mutations of human immunodeficiency virus. The studied dataset is from public databases and includes gene sequences from twenty HIV-infected patients. The results show that the mutation rate of the nine major genes or gene segment regions in the genome exhibits discrepancy during the infected period, and the Env gene has the fastest mutation rate. We deduce that the peak of virus mutation has a close temporal relationship with viral divergence and diversity. The mutation study of HIV is of great significance to clinical diagnosis and drug design.