Part 1: Biological Operators ~ Genomic-Level Perturbations and Their Downstream Effects in Transcription

Nature is modular and multi-scale. While natural systems exhibit chaos and complexity in the codomain with high variability, the natural phenomena itself can be captured by countably finite foundational operators. Getting lost in the variability and chaos of the range and codomain is not much helpful when capturing governing functions.

Understanding the nuanced impact of genomic aberrations is essential for unraveling the complexities of gene expression and regulation. The beauty of genomics lies in the fact that almost every change must pass through transcription processes before exerting any downstream effects.

By thoroughly understanding foundational aspects of transcription dynamics, such as gene expression, RNA splicing, 5' capping, polyadenylation, transcription regulation, and ribosome profiling, we can cover a broad base for comprehending how aberrations affect downstream molecular machinery. Each of this can be considered a foundational biological operator. This does not have to be innumerable operators. Biology can be considered as infinite variations of dynamic state of the foundational operators.

In this article, I provide a framework (among many) for thinking through various genomic perturbations and their downstream consequences, emphasizing how a few well-designed assays based on the foundational biological operator can capture the broadest effects and offer comprehensive insights into genomic regulation.

Series

• Part 1: Biological Operators ~ Genomic-Level Perturbations and Their Downstream Effects in Transcription
• Part 2: Biological Operators ~ Capturing the Effects of Synonymous SNPs Using Genomic Assays
• Part 3: Biological Operators to Math Operators~ Mixture of Operators Genomic Aberrations

What Is A Biological Operator?

I use the term “Biological Operator” with both humility and a significant influence from the mathematical and physical sciences’ use of “operator.” This shift in perspective is necessary to address two critical points.

First, in my opinion, there is a prevalent notion in biology that capturing the underlying dynamics requires consideration of an overwhelming number of variables. This perception may not be entirely accurate. While the state space in biological systems may exhibit infinite dynamics, these can often be described by a countably finite number of operators at a given scale. These operators can effectively capture the infinite variabilities of the system. (Activities in the transcription layer from genome to isoform is an example of a scale).

Second, at a later stage in this series, I will demonstrate how to mathematically model biological operators as function-to-function mappings. This approach aligns with the true essence of operators in mathematics and physics.

The Thought Framework

In the following sections, we will first explore the state space of gene aberrations, which has infinite unknowns. Then, we will examine how these aberrations affect transcriptions, narrowing the state space to countable finite states. We will also address an important question: what is the minimal number of ‘capture’ mechanisms needed to cover the broadest range of transcription changes that affect the gene product?

Gene Aberrations

Promoter and Enhancer Mutations

Promoter Mutations:
Promoter regions are critical for the precise initiation of transcription, serving as docking sites for RNA polymerase II and an array of transcription factors (TFs). Mutations within promoter sequences can significantly alter the binding affinity and specificity of these TFs, thus modulating transcription initiation rates. For instance, a single nucleotide polymorphism (SNP) in the TATA box or other core promoter elements can decrease TF binding affinity, leading to reduced transcriptional activity. Conversely, gain-of-function mutations can enhance TF binding, resulting in aberrant overexpression of target genes, a hallmark of oncogenic transformations.

Enhancer Mutations:
Enhancers are distal cis-regulatory elements that augment the transcription of target genes through the formation of DNA loops, bringing enhancers into close proximity with promoters. Mutations within enhancer sequences can disrupt these critical enhancer-promoter interactions, thereby diminishing transcriptional activation. Given the modular and tissue-specific nature of enhancers, such mutations can have pleiotropic effects, altering the expression of multiple genes within a regulatory network.

Polyadenylation Signal Mutations

Polyadenylation Signal Mutations:
The polyadenylation signal (PAS), typically characterized by the hexamer sequence AAUAAA, is essential for the 3' end processing of pre-mRNA, leading to the addition of a poly(A) tail. Mutations within the PAS can impede proper cleavage and polyadenylation, resulting in unstable or improperly processed mRNA transcripts. This can markedly reduce mRNA half-life and translation efficiency, as seen in diseases like β-thalassemia, where a single nucleotide mutation in the PAS leads to ineffective mRNA maturation and reduced hemoglobin synthesis.

microRNA Binding Site Mutations

microRNA Binding Site Mutations:
microRNAs (miRNAs) are key post-transcriptional regulators that bind to complementary sequences within the 3' untranslated regions (UTRs) of target mRNAs, leading to mRNA degradation or translational repression. Mutations in miRNA binding sites can abrogate these interactions, resulting in dysregulated gene expression. For instance, mutations in the 3' UTR of the KRAS oncogene can prevent miRNA binding, thereby stabilizing the mRNA and enhancing translation, which contributes to tumorigenesis.

SNPs and Their Effects

Synonymous Single Nucleotide Polymorphisms (SNPs): Synonymous SNPs, while not altering the amino acid sequence of proteins, can have significant regulatory effects at the molecular level. These mutations can impact mRNA stability, translation efficiency, and splicing by altering codon usage and mRNA secondary structures. Codon bias introduced by synonymous SNPs can affect translation kinetics, leading to variations in protein folding and function. Additionally, these SNPs can modulate the binding affinity of regulatory proteins or miRNAs to the mRNA, affecting post-transcriptional regulation and mRNA decay rates.

Non-Synonymous SNPs

Missense SNPs: Missense SNPs result in the substitution of one amino acid for another in the protein product. This alteration can have a range of effects depending on the properties of the amino acids involved and their position within the protein. Such mutations can:

• Disrupt protein structure and function by altering active sites, binding domains, or structural stability.
• Lead to gain-of-function or loss-of-function effects, which can be pathogenic or, in some cases, beneficial.
• Affect protein-protein interactions and signaling pathways, potentially causing downstream regulatory effects.

Nonsense SNPs: Nonsense SNPs introduce a premature stop codon in the coding sequence, leading to the production of truncated proteins. These incomplete proteins are usually nonfunctional and can:

• Be rapidly degraded by nonsense-mediated decay (NMD), reducing the overall protein levels.
• Lead to haploinsufficiency if the protein is essential and not compensated by the other allele.
• Cause dominant-negative effects if the truncated protein interferes with the function of the normal protein.

Non-Coding SNPs

Regulatory SNPs: Non-coding SNPs occur outside of protein-coding regions but can influence gene expression and regulation. These include SNPs in:

• Promoter Regions: Affect transcription factor binding, altering transcription initiation rates.
• Enhancer Regions: Disrupt interactions between enhancers and promoters, affecting gene activation.
• Introns: Influence splicing by creating or abolishing splice sites, leading to alternative splicing patterns.
• 3' and 5' Untranslated Regions (UTRs): Affect mRNA stability, localization, and translation efficiency by altering miRNA binding sites and other regulatory elements.

Epigenetic Modifications

DNA Methylation and Histone Modifications:
Epigenetic modifications, including DNA methylation and various histone modifications, play pivotal roles in chromatin architecture and gene accessibility. DNA methylation typically occurs at CpG islands within promoter regions, leading to transcriptional repression through chromatin condensation. Histone modifications, such as methylation, acetylation, and phosphorylation, can either activate or repress transcription depending on the specific modification and context. Aberrant epigenetic modifications are often associated with cancers and other diseases, exemplified by hypermethylation of tumor suppressor gene promoters leading to their silencing.

Chromosomal Rearrangements

Translocations, Inversions, and Deletions:
Chromosomal rearrangements, including translocations, inversions, and deletions, can profoundly impact gene function and regulation. Such structural alterations can disrupt coding sequences or regulatory elements, or alter the three-dimensional genome organization. For example, the BCR-ABL fusion gene, resulting from a translocation between chromosomes 9 and 22 (the Philadelphia chromosome), leads to constitutive tyrosine kinase activity and chronic myeloid leukemia.

Copy Number Variations (CNVs)

Duplications or Deletions of Genomic Segments:
Copy number variations (CNVs) involve the duplication or deletion of large genomic segments, significantly affecting gene dosage. For instance, duplication of the MYC oncogene is frequently observed in cancers, leading to its overexpression and uncontrolled cellular proliferation. Conversely, deletions encompassing tumor suppressor genes, such as PTEN or TP53, can lead to haploinsufficiency and contribute to tumorigenesis.

Transposable Element Insertions

Transposable Element Insertions:
Transposable elements (TEs) are mobile genetic elements capable of inserting themselves into various genomic loci, thereby disrupting gene function or regulation. Insertions of TEs within coding regions can lead to frameshift mutations, while insertions in regulatory regions can alter gene expression. The insertion of a TE in the APC gene disrupts its function, leading to familial adenomatous polyposis, a condition predisposing individuals to colorectal cancer.

Repeat Expansion Mutations

Repeat Expansion Mutations:
Repeat expansion mutations involve the abnormal increase in the number of tandem repeats of short DNA sequences. Such expansions can interfere with normal gene function through mechanisms like gene silencing, RNA toxicity, or protein aggregation. These mutations are implicated in several neurodegenerative diseases, such as Huntington’s disease, where CAG repeat expansions in the HTT gene lead to toxic protein aggregates.

Downstream Effects Of The Aberrations

The result of all the stated aberrations are some form of transcription affects. The biological operators can be attuned to “keeping an eye” on the transcriptional changes to makes sense of what may happen during translation. The downstream transcription effects due to the stated aberrations are as follows:

During Transcription

Gene Expression:
Gene expression encompasses the entire process of transcribing DNA into RNA and translating RNA into proteins. Genomic aberrations can impact gene expression at multiple levels:

• Transcriptional Level: Mutations in promoter regions, enhancers, or transcription factor binding sites can alter the rate of gene transcription.
• Post-Transcriptional Level: Changes in RNA splicing, mRNA stability, and RNA transport can affect the availability and functionality of mRNA.

Transcription Factor Binding:
Mutations that alter TF binding sites can affect the rate and fidelity of transcription. Enhanced or diminished TF binding can lead to inappropriate levels of gene expression, contributing to pathological conditions like cancer and genetic disorders.

Chromatin Structure:
Epigenetic modifications influence chromatin accessibility, significantly impacting transcriptional regulation. Open chromatin regions are generally associated with active transcription, while condensed chromatin regions are repressive.

DNA Sequence:
Direct mutations within the DNA sequence can alter transcription rates and accuracy, impacting mRNA production and subsequent protein synthesis.

RNA Processing

RNA Splicing:
Mutations in splice sites or splicing regulatory elements can disrupt the splicing process, leading to the production of aberrant mRNA isoforms. For instance, mutations that create or abolish splice sites can result in exon skipping or the inclusion of intronic sequences, producing non-functional proteins or triggering nonsense-mediated decay.

mRNA Stability:
Changes in polyadenylation signals and miRNA binding sites can significantly impact mRNA stability and localization. These alterations influence the availability of mRNA for translation, thereby affecting protein synthesis and cellular function.

Comprehensive Assays for Capturing Genomic Effects

The question now is to choose the smallest number of assay types to capture the broadest effects caused by genomic aberrations, several key assays are particularly effective:

RNA-Seq: RNA-Seq provides a comprehensive view of mRNA abundance, splicing patterns, and allele-specific expression. This high-throughput sequencing technology can identify differential gene expression, detect alternative splicing events, and measure the relative expression of alleles, making it an invaluable tool for studying the impacts of genomic perturbations.

Cap Analysis of Gene Expression (CAGE): CAGE maps transcription start sites (TSSs) and quantifies their usage, providing insights into promoter activity and alternative TSS selection. This assay can reveal shifts in TSS usage caused by mutations near TSS regions and measure changes in promoter activity, offering a detailed view of transcriptional regulation and its disruption by genomic mutations.

Chromatin Immunoprecipitation (ChIP):

• ChIP-Seq for Transcription Factors (ChIP-TF): This assay identifies the binding sites of transcription factors across the genome, providing insights into transcriptional regulation and how mutations in promoter or enhancer regions can alter TF binding and gene expression.
• ChIP-Seq for Histone Modifications (ChIP-Histone): ChIP-Seq for histone modifications maps the distribution of histone marks, revealing changes in chromatin state and how epigenetic modifications influence gene expression.

Assay for Transposase-Accessible Chromatin using Sequencing (ATAC-Seq) / DNase I Hypersensitive Sites Sequencing (DNase-Seq): These assays identify regions of open chromatin, providing a global view of chromatin accessibility. Changes in chromatin structure detected by these assays can indicate how mutations and epigenetic modifications alter chromatin states, affecting transcriptional regulation.

Ribosome Profiling: Ribosome profiling provides a snapshot of active translation by mapping ribosome positions on mRNA. This technique allows researchers to study translation dynamics, identify which mRNAs are being actively translated, and detect changes in translation efficiency caused by genomic aberrations. Ribosome profiling is crucial for understanding how mutations affect the final stage of gene expression.

Given these assay types, now we can imagine modeling a system that can capture the underlying operators that maps a function in genomic aberration to the assay types. More on this in next articles.

Future Directions

The future of research into genomic transcription and isoforms lies in probably understanding biological operators and capturing them as governing functions through mathematical operators. The underlying phenomena can be effectively captured by a countably finite set of foundational operators. The key is to choose the smallest number of assay types to capture the broadest effects caused by genomic aberrations.

By integrating high-throughput sequencing technologies like RNA-Seq, CAGE, and ribosome profiling with advanced computational models, we can accurately map how genomic aberrations influence transcription dynamics and isoform diversity. These foundational biological operators provide a framework for understanding the intricate dynamics of gene regulation. Single-cell sequencing will offer insights into cell-specific transcriptional variations and alternative splicing events, while CRISPR/Cas9 and other gene-editing tools will allow us to experimentally validate the roles of specific SNPs and regulatory elements.

Ultimately, by focusing on capturing the governing functions of biological operators, we can achieve a deeper understanding of how transcriptional regulation and isoform generation contribute to cellular function and disease. This approach will possibly pave the way for targeted therapeutic strategies and precision medicine, advancing our grasp of genetic regulation and its implications for human health.