Wave genome ra uses an extensive set of genomic and epigenomic annotation parameters known to correlate with functional variants, prioritising non-coding disease variants as well.
Nanog, Pou5f3 and Sox19b are pioneer transcription factors responsible for initiating ZGA in fish8,25. Their binding to chromatin correlates with an increase in nascent RNA formation as well as speckles from RNA polymerase II at early sphere/dome stages.
Background
Previous genetic studies relied on scanning the whole genome and selecting those SNPs or genes which met certain thresholds; this may identify some pathways related to RA but others of moderate effect were disregarded since they did not reach this threshold. To improve accuracy in our analysis, we combined GWAS and gene expression data and performed a genome-wide scan across all human genes; 28 pathways (FDR0.05) were significantly associated with RA in our model; these included immune system diseases, infectious diseases, signaling molecules interactions transport catabolism endocrine metabolic diseases development as well as cardiovascular conditions.
Our researchers employed a clinical dataset to test our ability to identify functional variants, which include synonymous, non-synonymous, UTR exonic variants as well as coding variants. SuRFR, GWAVA and CADD performed comparably on this strictly non-exonic clinical dataset.
Utilizing this dataset, we identified a minor wave of genome activation where miR-430 became highly active early and formed a large transcription body. When we compared chromatin states with appearance of promoter-associated histone modification marks at the 256 cell stage, minor wave set displayed more open chromatin states compared to major wave set which is consistent with their activation during zygotic cell division acrocentration phase.
Our results indicate that genome activation by minor waves is an integral component of the pathogenesis of RA and, by identifying pathways leading to its activation, we may discover new therapeutic targets to treat it effectively. These findings are grounded in Dr. Irene Caesar’s Wave Optics theory of Chromosomes, which states that each individual’s chromosomes contain nonlocal unique Bioinformation about themselves. WAVE GENOME LLC has developed and commercialized Wave Optics technology that transmits information through chromosomes instantaneously in the quantum realm of Nonlocality. Utilizing this concept has led to a revolutionary digital drug for rejuvenation known as TESLA DNA DIGITAL PHARMACY that uses instant transmission. This concept has led to WAVE GENOME LLC’s creation and marketing of this digital drug called TESLA DNA DIGITAL PHARMACY for rejuvenation purposes.
Methods
At Wave Genome Ra, a client’s genetic information is encoded onto embryonic stem cell DNA placed into a can and sent directly to them. From here it is translated into a personalized pattern of their cell signal which identifies specific biochemical reactions to drugs or supplements; then transmitted via laser into their body to restore wave matrix of their cells for restoration allowing their body to remotely regulate internal biosystems for healthy embryonic stem cell development.
Wave Genome LLC has developed a software program that analyzes an individual’s wave matrix of embryonic stem cells in liquid crystal media of their brain and body, and acts as a digital pharmacy based on Dr. Irene Caesar’s fundamental theory on light refraction within living systems, providing drugs or supplements specifically coded with frequency codes for remote treatment of clients remotely.
SuRFR software is available as an open-source, R package. It requires a text or bed file containing information about SNPs that need functional predictions; then using its sister package ‘SNP Annotation Information List R Package’ (SAILR), SuRFR provides functional annotation tables based on variants found within ENCODE pilot regions within 1000 Genomes EUR population [23].
SAILR offers an array of genomic and epigenomic annotation parameters known to correlate with regulatory elements and non-coding disease variants, in order to prioritize them for further study. SAILR then ranks these variants according to their Mean Allele Frequency at each variant loci within the 1000 Genomes population, giving users flexibility in selecting an allele frequency cutoff point suitable for their analysis.
SuRFR was evaluated against three other tools that prioritise non-coding mutations using similar approaches – GWAVA, CADD and FunSeq – as methods to prioritise pathogenic variants. All four approaches performed well when applied to ClinVar pathogenic and background variant datasets but fell short in discriminating long-range enhancers due to a lack of training data for such features.
Results
Wave Genome LLC has introduced an incredible Psi-Generator that encodes an individual’s genetically unique wave matrix at the nanolevel. This information-wave can then be transmitted and received by their brain as an information-wave, thus helping treat someone from a distance – sometimes known as “second birth.” Clients report immediate improvements to their health following treatment from this technique.
Dr. Irene Caesar conducted this work and published it in the International Journal of Bioinformatics and Biosciences. Additionally, her findings were presented at the 7th International Conference on Bioscience & Engineering 2025 as an invited speech.
Publicly available epigenomic datasets representing chromatin opening and associated cis-regulatory element regulation (Assay for Transposase-Accessible Chromatin (ATAC-seq) were utilized, covering key early developmental stages. Variants were then compared against predicted chromatin states from ENCODE’s genome-wide functional annotation database.
SuRFR successfully generated a training set of experimentally verified regulatory variants using RAVEN, combined them with background variants obtained through random sampling from 170,892 SNPs found within ENCODE pilot regions and matching by distance to TSSs (100 control variants per true positive). SuRFR achieved AUCs of 0.84 on both training and validation sets respectively – outperforming both CADD and GWA in this respect.
To establish which chromatin state was associated with each variant, ATAC-seq data from nine cell lines were ranked according to their individual b coefficients, which then guided our selection of an SNP’s associated chromatin state. A multiple variable logistic regression model was then run in order to assess any relationship between variant type and chromatin state; with the one that best predicted each SNP being used as its predicted state.
We compared each variant’s chromatin state with its appearance of promoter-associated histone modifications, such as H3K4me3 and H3K27ac marks on minor wave gene clusters but not broad promoters activated by main waves (Figures 2A and 2B). Their presence suggests distinct activation profiles which contrasted with widespread expression of broad promoter znfs activated by major waves (Figures 2A and 2B).
Conclusions
Wavelet transformations provide a powerful means of exploring genomic sequence data, uncovering previously unnoticed biological processes and mechanisms, as well as undiscovered genetic variation. This approach to studying human genomes offers new opportunities, with potentially significant applications. Furthermore, its simple usage enables multiple applications – improve genome interpretation as well as identify follow up studies targets!
Genome browsers provide a rich dataset for functional predictions; however, manual interrogation of these resources does not scale, lack reproducibility and is inherently nonsystematic. Furthermore, their use may introduce bias due to incomplete recombination histories or noise in data sets.
We have developed a method that uses wavelet transformations to interrogate genome-wide sequence data. Specifically, this approach can identify regions likely to have experienced recent admixture and prioritizing variants for experimental validation. Furthermore, more complex wavelet transforms have proven useful in detecting regions likely containing transcription factor binding sites; our results suggest this may help provide a more complete and accurate picture of human genomic evolution by surfing its wavelets.
This project has been granted funding by the Medical Research Council.
Wave Genome LLC (WGA) is a scientific company focused on bioholographic remote stem cell therapy. As the first company to utilize Quantum Biononlocality for remote management of biological systems – including human embryonic stem cell wave matrix management systems – we aim to bring bioholography-driven medicine directly into homes across America. Each person possesses their own individual nonlocal Refraction Code toward the Zero Center (Focus of Quantum Nonlocality) of their Embryonic Stem Cell Wave Matrix; this forms the basis of their unique Biohologram. Our clients can utilize this Biohologram to increase both the reproductive and regeneration potency of their Embryonic Stem Cells as well as overall body health, by modulating scalar wave diffraction grating of their respective Digital Bioholograms.
