Molecular basis of genetic polymorphisms - comprehensive notes

From Mendel’s traits to genes

  • Allele = variant at a genetic locus; concept of antagonistic pairs as Mendel studied traits.

  • Alleles underlie phenotypic variation; mutations create new alleles and allelic diversity.

Mutation and inheritance

  • Mutation is the process whereby genes change from one allelic form to another; new alleles can arise.

  • Mutations occur randomly, at any time and in any cell of an organism.

  • Mutations can arise spontaneously during normal DNA replication or be induced by a mutagen.

  • Only mutations in germline cells can be transmitted to progeny; somatic mutations cannot.

  • Inherited mutations appear as alleles in populations of individuals; mutations are the source of allelic variation.

Germline vs somatic mutations

  • Germline mutations: in germinal tissue; passed to offspring; contribute to inherited variation.

  • Somatic mutations: in somatic tissue; can create a mutant sector within an organism but are not inherited by progeny.

  • Conceptual representation: germline mutations in germinal tissue lead to mutant progeny; somatic mutations affect only the individual.

Allele frequency and polymorphism

  • Allele frequency = percentage of the total number of gene copies represented by one allele.

  • Wild-type allele – frequency ≥ 1%.

  • Mutant allele – frequency < 1%.

  • Monomorphic – gene with only one wild-type allele.

  • Polymorphic – gene with more than one wild-type allele.

  • Forward mutation – changes wild-type allele to a different allele.

  • Reverse mutation – reversion to wild-type allele (novel mutation).

  • Mutations are the source of allelic variation.

Mutation rates and dynamics

  • Mutation rate varies from 1 in 1,000 to 1 in 1,000,000,000 per gene per gamete.

  • The forward mutation rate is almost always higher than the reverse rate.

  • Mutations can occur during normal DNA replication.

  • The mutation rate can increase after exposure to a mutagen (e.g., UV light, certain chemicals).

  • Quantitative reference:

    • Forward vs reverse mutation rates: extmutationsforwardmutations reverseext{mutations forward} \gg \text{mutations reverse}

    • Typical range: bc \in [10^{-3}, 10^{-9}] \text{ per gene per gamete} (varies by gene and context).

Types of DNA mutations

  • Substitution – a base is replaced by one of the other three bases.

  • Deletion – loss of a block of one or more DNA base pairs.

  • Insertion – addition of a block of one or more DNA base pairs.

  • Inversion – rotation of a piece of DNA.

  • Reciprocal translocation – parts of nonhomologous chromosomes exchange places.

  • Chromosomal rearrangements – affect many genes at once.

Single nucleotide polymorphisms (SNPs) and polymorphism

  • SNPs are alleles differing at a single nucleotide position.

  • Polymorphism = detectable difference at a given locus/gene; this difference is what defines an allele.

  • DNA sequence differences can be used to infer allelic variation.

From DNA to phenotype: central dogma and alleles

  • Mendel’s traits are encoded in DNA; organismal traits arise from gene expression.

  • DNA -> mRNA -> protein; allelic differences at the DNA level can influence mRNA expression and/or protein function, thereby affecting phenotype.

  • Flow: DNA sequence variations can alter transcription, RNA processing, translation, and protein function.

Gene structure

  • Prokaryotic/bacterial genes: promoters regulate transcription of one region or more genes; transcription produces mRNA and translation yields proteins.

  • Eukaryotic genes: contain introns and exons that are transcribed; promoters regulate transcription initiation; splicing removes introns to produce mature mRNA.

  • Key features in gene architecture:

    • Promoter

    • Coding sequence

    • Start codon (ATG) and stop codon (TGA)

    • Exons (coding segments) and introns (intervening sequences)

  • Transcriptional and post-transcriptional processing yields mature RNA that is translated into protein.

Gene expression and alleles: examples

  • Start codon: ATG; stop codon: TGA.

  • Transcription produces mRNA; splicing produces mature RNA (exons joined, introns removed).

  • Translation produces nascent protein, which folds into functional protein.

  • Wild-type allele vs mutant allele: mutations can affect transcription, splicing, translation, or protein folding, leading to altered or nonfunctional proteins.

Allelic variation and disease: PKU (phenylketonuria)

  • PKU overview: buildup of phenylalanine; lack of tyrosine; potential seizures and mental/mood disorders.

  • Enzymatic cause: Phenylalanine hydroxylase deficiency; leads to phenylalanine buildup and downstream tyrosine depletion.

  • Biochemical consequence: accumulation of phenylpyruvic acid affecting nervous system development.

  • Genetic basis: mutations can occur in PAH gene; mutations can be in exons or introns (affecting splicing) and inactivate the gene.

BRCA1 and disease risk

  • BRCA1: tumor-suppressor gene involved in repairing DNA damage.

  • Mutations in BRCA1 can disrupt DNA repair and increase cancer risk, particularly breast and ovarian cancer.

  • Population data: hundreds of BRCA1 mutations identified; common risk figures include ~12% baseline risk in general population vs ~60% risk for those with harmful BRCA1 mutations.

Functional consequences of mutations

  • Wild-type phenotype arises when two copies of the wild-type allele are present.

  • Mutant alleles can have several effects:

    • Loss-of-function (null/amorph) – little or no functional gene product.

    • Gain-of-function (hypermorphic) – increased function or new function.

    • Gain-of-function (neomorphic) – introduces a new function/structure.

    • Leaky/hypomorphic – partial loss of function; reduced but not abolished activity.

    • Haploinsufficiency – one wild-type allele is not enough for normal function.

    • Dominant-negative – mutant allele produces a product that interferes with normal product from the wild-type allele.

Haploinsufficiency and dominance concepts

  • Haplosufficiency: one wild-type allele provides enough gene product for normal function (e.g., 50% activity can be sufficient).

  • Haploinsufficiency: one WT allele not enough to maintain normal function.

  • Dominant-negative: mutant product disrupts function of the normal product in heterozygotes, often seen with multimeric proteins.

Practical inheritance patterns with enzyme activity examples

  • Example: recessive loss-of-function in enzyme activity

    • WT allele (R+) yields active enzyme (e.g., 50 units).

    • Mutant allele (r) yields little/no active enzyme (0 units).

    • WT phenotype when total activity ≥ threshold (e.g., 40+ units).

    • Genotypes: R+R+ (WT), R+r (WT/haplosufficient), rr (mutant phenotype).

  • Example: dominant loss-of-function and haploinsufficiency

    • T1T1 (20 units) may be WT; T1T2 (15 units) and T2T2 (10 units) show mutant phenotype.

    • The T2 allele is dominant; the WT T1 allele is haploinsufficient (one copy not enough for normal function).

  • Example: haploinsufficiency and dominance illustrated with dosage of protein products.

  • Example: dominant negative mutations – interactions between mutant and normal gene products cause abnormal phenotypes.

More on mutation outcomes

  • (e) Loss of function – haplosufficiency vs haploinsufficiency; 50% protein can be enough or not depending on system.

  • (f) Gain of function – neomorphic mutation introduces a new function or novel structure.

Detection of allelic polymorphism at the molecular level

  • Techniques: PCR and DNA sequencing; new technologies enable visualization of allelic polymorphism.

  • Ultimate detection resides at DNA sequence level; polymorphism can be detected from DNA to protein levels.

  • Analyses performed on the diploid nuclear genome.

PCR and DNA sequencing: workflow and interpretation

  • PCR amplification provides a comprehensive picture of the region of interest.

  • DNA sequencing reveals the exact nucleotide sequence across the amplified region.

  • Sequencing data supports detection of SNPs, insertions/deletions, and more complex variants.

  • Example visualization challenges include handling fragment bases and reads; real data often includes multiple reads and alignment considerations.

SNP detection and disease

  • SNP-based screening can identify carriers or affected individuals.

  • Example: recessive disease screening using SNP profiles (e.g., AA no disease, AG carrier, GG diseased).

How to screen for BRCA1-related breast cancer risk

  • Gene sequencing is the most comprehensive approach but expensive; BRCA1 > ~80,000 bp.

  • SNP detection for common mutations can be cheaper but less comprehensive.

  • A suggested strategy: screen the affected individual using gene sequencing to identify causal mutation; if a causal SNP is found, use targeted SNP detection to screen at-risk relatives (full gene sequencing not required for relatives if the causal SNP is known).

New technologies in genetics

  • Next-generation sequencing (NGS) enables massive parallel sequencing at much lower costs; Illumina is a common platform.

  • Visualization tools (e.g., IGV) help inspect read alignments, coverage, and variant calls across the genome.

  • Example data: scaffold coordinates; read coverage across genomic regions; long-read vs short-read strategies.

Probability rules in genetics

  • Product rule (multiplication rule): P(A and B) = P(A) × P(B) for independent events.

  • Sum rule (addition rule): P(A or B) = P(A) + P(B) − P(A and B).

  • Conditional probability and binomial probability concepts are used to infer genotype/phenotype proportions in crosses and samples.

  • Example: independent loci in a dihybrid cross yield probabilities calculated by multiplying individual locus probabilities.

Applying product rule: worked example (as in slides)

  • For a genotype with loci A, B, C, S, use:

    • P(RRYYTTSS) × P(rrYYttss) to compute the combined probability of a multi-locus genotype.

  • Example calculation shown in slides: product of individual locus probabilities, e.g., 2/4 × 2/4 × 2/4 × 1/4 = 8/256 = 1/32 for a multi-locus genotype.

Mutually exclusive events and sum rule in genetics

  • When events are mutually exclusive, probabilities add directly: P(A or B) = P(A) + P(B).

Practice problems (overview of questions given in the slides)

  • Practice problem #1: Determine the type of individual given a genotype A/A; B/B; c/c; D/d.

    • Options: A) monohybrid B) dihybrid C) trihybrid D) tetrahybrid

  • Practice problem #2: Cross genotype with multiple traits; compute proportion of progeny phenotypically identical to the first parent.

  • Practice problem #3–#4: Similar multi-trait genotype crosses and identically/identically to a parent calculations.

  • Practice problem #5: Classical inheritance problem involving a new mutation and penetrance/homozygosity; interpret allele type from F2 phenotypic ratios.

  • Practice problem #6: Pedigree-style question about a dihybrid cross for two traits with different dominance relationships; calculate probabilities for specific phenotypes.

Summary of key concepts to remember

  • Allele and mutation concepts; germline vs somatic inheritance.

  • Definitions: wild-type, mutant, monomorphic, polymorphic; forward vs reverse mutations; allele frequency.

  • Mutation rates across genes; effects of mutagens; general patterns of forward > reverse.

  • Types of DNA mutations and their consequences on gene function and phenotype.

  • SNPs and polymorphisms; detection methods from DNA to protein level.

  • Gene structure in eukaryotes vs prokaryotes; transcription, splicing, and translation; regulatory elements.

  • Allelic variation and disease: PKU and BRCA1 as examples of how mutations cause disease.

  • Functional consequences of mutations: loss-of-function, gain-of-function, haploinsufficiency, haplosufficiency, dominant-negative, neomorphic.

  • Central dogma and how mutations can alter gene expression and protein function.

  • Detection technologies: PCR, DNA sequencing, and emerging high-throughput sequencing; practical screening strategies.

  • Probability rules in genetics: product rule, sum rule, independent events, conditional probability, and basic binomial concepts.

  • Practice problems illustrate the application of these concepts to real-world genetic questions.