Evolution, Genetics, and the Scientific Method - Vocabulary Flashcards
I. The Process of Science and Learning Context
The plan for today centers on the Process of Science: why we learn science, what science is and how we study it, and an introduction to an evolution experiment. Reminders include a Background Quiz on ELMS/Canvas due tonight at midnight and starting next week’s SimBiotic assignment on Evolution, due Friday. The material emphasizes moving beyond memorization to thinking like a scientist: evaluating evidence, understanding context, and recognizing that scientists can disagree.
A. Theory vs. Fact
A fact is an observable phenomenon known to be true, while a theory is a well-substantiated explanation acquired through the scientific method and repeatedly tested through observation and experimentation.
B. The Scientific Method
Outlined in six steps:
Define a problem
Research what is known
Hypothesize a cause
Test your hypothesis
Analyze your results
Support or refute your hypothesis
Emphasis is on testing ideas, interpreting data with awareness of context, and distinguishing correlation from causation.
C. Hypotheses Structure
A key note discusses hypotheses as a structured sequence: Question -> BECAUSE of this reason -> Methods -> IF I do this -> THEN this will happen.
D. Observational vs. Experimental Designs
Observational studies collect data without manipulation.
Experimental designs manipulate one or more variables to test cause-and-effect relationships.
E. Addressing Big Questions
Systematic reviews and meta-analyses are strategies for addressing big questions by summarizing and reanalyzing existing studies.
F. Valuing Negative Data and Mathematics in Ecology
Negative data is valued as a useful part of science because science is iterative and can lead to new hypotheses.
The role of mathematics in ecology is highlighted, including variability and data interpretation across multiple factors such as count data, environmental factors, and temporal variation.
G. Growth Mindset
A growth mindset is encouraged: failure is an opportunity to grow, challenges help learning, effort and attitude matter, feedback is constructive, and success of others can be a source of inspiration.
II. Core Concepts of Evolution
A. Why Evolution Matters
Evolution is foundational to understanding biology because it explains how populations change over time in response to genetic variation and environmental pressures.
The material emphasizes that evolution operates on allele frequencies in populations, not on individuals.
The plan for today covers the terminology of evolution, sources of genetic variation, and the mechanisms by which evolution occurs.
B. The Genetic Basis of Evolution: Variation, Heredity, and Selection
Variation in a population is essential for evolution. Variation can arise from mutation (new alleles), gene flow (movement of alleles between populations), and recombination during meiosis.
Genetic drift (random changes in allele frequencies) and non-random mating also shape genetic variation.
Natural selection acts on heritable variation, favoring traits that increase reproductive success in a given environment.
C. Darwin’s Theory of Natural Selection
Darwin’s theory of natural selection rests on four main principles:
Heritable variation in populations;
Struggle/competition for limited resources;
Differential reproductive success;
Change in allele frequency over time.
The idea of descent with modification underpins Darwin’s view that species are related through common ancestry and that adaptations arise as populations evolve.
Fitness is a measure of reproductive success. Beneficial traits increase an individual’s chances of surviving to reproduce and passing on genes.
Ecology and environmental conditions act as selecting forces that shape traits in populations (e.g., soil moisture, temperature, growing season, mutualists, competition, predators, parasites).
D. Evidence for Evolution
Evolution can be traced using multiple lines of evidence:
Direct observation and strong inference (e.g., artificial selection experiments like dogs from wolves, natural observations like Darwin’s finches).
The fossil record demonstrates the ordering of fossils in rock layers, with deeper layers being older.
Homologous structures reveal shared ancestry, while analogous features illustrate convergent evolution. Vestigial structures reveal relatedness to ancestral forms.
Biogeography and geology support patterns of descent with modification.
Genetics provides a molecular basis for inheritance and variation.
E. Mechanisms of Evolution (Adaptive and Non-adaptive)
Evolution can occur via non-adaptive processes (mutation, gene flow, genetic drift, non-random mating) and adaptive processes (natural selection).
The Red Queen hypothesis and Tangled Bank hypothesis are highlighted as theories for why sex and genetic variation are maintained in populations under environmental variability and co-evolution with parasites.
III. Molecular and Genetic Foundations
A. Information Storage: DNA and RNA
Living organisms store information in nucleic acids (DNA and RNA) built from nucleotides.
DNA is a double helix with a sugar-phosphate backbone and nucleobases: Adenine (A), Thymine (T), Cytosine (C), and Guanine (G).
RNA uses Uracil (U) in place of T.
Base pairing rules in DNA are A-T (with two hydrogen bonds) and C-G (with three hydrogen bonds). In RNA, A pairs with U, and C with G.
B. Central Dogma: DNA to Protein
The central dogma describes how DNA is transcribed into RNA, which is translated into a polypeptide (protein).
DNA replication, transcription, and translation are the core steps of gene expression.
DNA is replicated before cell division.
Transcription copies DNA into messenger RNA (mRNA).
Translation uses the mRNA sequence to assemble a polypeptide chain from amino acids.
Proteins fold into functional three-dimensional structures (primary, secondary, tertiary, and quaternary structures), directly influenced by the sequence and chemical properties of their amino acids.
The 20 canonical amino acids have varying properties (nonpolar, polar, charged) that influence folding and function.
Protein function includes transporters, receptors, enzymes, antibodies, and structural roles (e.g., muscle tissue, pigment transport).
C. Genes, Alleles, Genotype, and Phenotype
Genes are segments of DNA that provide information to make proteins. A gene is a locus on a chromosome.
Alleles are variants of a gene.
The genotype is the combination of alleles an individual carries for a gene, while the phenotype is the observable trait influenced by gene expression and the environment.
Organisms have two alleles for most genes (except sex chromosomes in males for X-linked genes).
Dominant alleles mask recessive alleles in heterozygotes, though there are exceptions (incomplete dominance, codominance).
D. Mutations: Types and Impact
Mutations create new alleles through changes in DNA sequences.
Types of mutations:
Point mutations (single nucleotide changes)
Frameshift mutations (insertions or deletions that shift the reading frame)
Chromosomal mutations (deletions, insertions, translocations, inversions)
Point mutations can alter one amino acid, change function, or introduce stop codons.
Frameshift mutations can drastically alter the protein sequence.
Chromosomal mutations affect larger genomic segments and can have substantial phenotypic consequences.
Mutations can be heritable when they occur in germline cells (sperm/egg) and thus can be passed to offspring; somatic mutations are not inherited.
E. Non-Coding Regions and Gene Regulation
Non-coding regions of genes (introns, promoters, regulatory sequences) influence gene expression and genome structure.
Exons encode the amino acid sequence, while introns are spliced out during processing of pre-mRNA.
Regulation and expression determine when and where genes are active, contributing to cellular differentiation.
F. Chromosomes and Linkage
The organization of chromosomes and genes includes the concept of homologous chromosomes (same genes, different alleles).
Crossing over during meiosis I can create recombinant chromosomes, increasing genetic diversity.
Linkage (genes close together on a chromosome) can reduce recombination, while genetic distance corresponds to recombination frequency.
Recombination rates can be translated into map units (centiMorgans), with 1 map unit corresponding to 1% recombination.
IV. Cell Division and the Generation of Genetic Diversity
A. Mitosis
Mitosis produces two genetically identical diploid daughter cells from a single diploid parent.
Ensures equal chromosome distribution and maintains chromosome number through somatic cell divisions.
The process includes DNA replication, followed by prophase, metaphase, anaphase, telophase, and cytokinesis.
B. Meiosis: Generation of Genetic Diversity
Meiosis reduces chromosome number from diploid to haploid, creating genetic diversity.
Diversity arises via crossing over (recombination) during prophase I, independent assortment of homologous chromosome pairs during metaphase I, and random fertilization.
Meiosis consists of two rounds of division (Meiosis I and Meiosis II) with interphase in between and results in four haploid gametes.
Homologous chromosomes pair and exchange genetic material at chiasmata during prophase I, producing recombinant chromatids.
The law of segregation ensures that alleles separate into gametes.
The law of independent assortment states that the orientation of chromosome pairs during meiosis I is random, producing many possible gamete combinations.
When meiosis is coupled with fertilization, genetic diversity arises in offspring due to segregation, recombination, and fertilization randomness.
V. Mendelian Inheritance and Genetic Variation
A. Mendel’s Laws of Inheritance
Mendel’s experiments with pea plants established particulate inheritance: traits are inherited as discrete units (now called genes) rather than blended in offspring.
The locus is the gene’s position on the chromosome.
The Law of Segregation states that alleles separate randomly into gametes, so an offspring inherits one allele from each parent.
The Law of Independent Assortment states that the way alleles of different genes line up in metaphase I is random, producing many allele combinations in offspring.
B. Genotypes and Phenotypes
The concepts of homozygous (two identical alleles) and heterozygous (two different alleles) genotypes are introduced.
Distinction between genotype (allele composition) and phenotype (expressed trait).
Dominant alleles mask recessive alleles in heterozygotes, but there are exceptions (incomplete dominance and codominance; e.g., codominant or incompletely dominant forms can exist for a given gene).
C. Punnett Squares and Crosses
A Punnett square is a tool to predict offspring genotypes and phenotypes based on parental genotypes.
For a single gene with two alleles (A and a) and complete dominance, the genotype frequencies in the F1 and F2 generations often follow a 1:2:1 genotype ratio and a 3:1 phenotype ratio.
For a dihybrid cross with two independently assorting genes (AaBb x AaBb), the classic phenotype ratio is 9:3:3:1 under independent assortment assumptions.
Test crosses (crossing a dominant phenotype with a homozygous recessive) reveal genotypes and help determine dominance patterns.
D. Pleiotropy and Epistasis
Pleiotropy: one gene affecting multiple traits (e.g., sickle cell disease exhibits pleiotropy and shows heterozygote advantage with malaria resistance).
Epistasis: one gene’s effect depends on another gene (e.g., coat color in Labrador retrievers, where one gene affects pigment production and another affects pigment deposition).
E. Sex-linked Inheritance
X-linked genes (on the X chromosome) show distinctive inheritance patterns in males (who have only one X) and females (two Xs).
Practice problems show how to determine the proportion of daughters and sons affected by X-linked traits and how pedigrees can reveal carrier statuses.
F. Genetic Linkage and Recombination
Linkage and recombination are discussed using Morgan’s work with fruit flies as a gateway to understanding how genes on the same chromosome can be linked and how crossing over in meiosis creates recombinants.
The concept of recombination frequency as a measure of genetic distance is introduced, with the formula: r = \frac{\text{number of recombinant offspring}}{\text{total offspring}}
Mapping distance in map units (1% recombination = 1 map unit).
Morgan’s work demonstrated that when genes are linked, the expected 9:3:3:1 ratio can deviate, depending on distance and recombination frequency. Testcross data lead to conclusions about linkage and recombination for constructing genetic maps.
VI. Population Genetics: The Hardy-Weinberg Framework
A. Hardy-Weinberg Equilibrium (HWE)
The Hardy-Weinberg Equilibrium describes a non-evolving population, assuming an infinitely large population, no mutation, random mating, no gene flow, and no natural selection.
Under these conditions, allele and genotype frequencies remain constant across generations.
B. Key Hardy-Weinberg Equations
Allele frequencies satisfy p + q = 1 where p is the frequency of the dominant allele and q is the frequency of the recessive allele.
Genotype frequencies satisfy p^2 + 2pq + q^2 = 1 corresponding to genotypes AA, Aa, and aa, respectively.
These equations allow us to estimate allele frequencies from genotype data or to test whether a population is evolving by comparing observed genotype frequencies to Hardy-Weinberg expectations.
The probability rules underpinning Hardy-Weinberg calculations include the multiplication rule for independent events and the decomposition of p^2, 2pq, q^2 into genotypic frequencies.
C. Applications and Deviations from HWE
Stepwise examples show how to compute p and q from genotype counts, convert to expected numbers, and compare to observed numbers to assess HW equilibrium.
Practice problems cover multiple scenarios: calculating allele and genotype frequencies from genotype counts, differentiating among homozygous and heterozygous frequencies, and applying the p^2, 2pq, q^2 framework to real data (e.g., PKU carrier calculations, cat coat color, cattle roan genotype frequencies).
In real data, deviations from HW expectations indicate that evolutionary forces may be acting (mutation, migration, selection, drift, non-random mating).
The population genetics framework also addresses the construction of random mating assumptions, the interpretation of phenotypes vs. genotypes, and the limits of Hardy-Weinberg in natural populations where evolution is occurring.
D. The Mechanisms of Evolution: Forces that violate HWE
Mutation: Introduces new genetic variation by altering DNA sequences. Heritable mutations provide novel alleles. Mutation alone is not adaptive but provides raw material.
Gene Flow (Migration): Introduces or removes alleles from a population through movement of individuals. Tends to homogenize allele frequencies and is not inherently adaptive.
Genetic Drift: Random fluctuations in allele frequencies due to chance events, which can cause alleles to become fixed or lost in small populations (bottlenecks, founder effects). Strength of drift is inversely related to population size; smaller populations experience stronger drift.
Non-random Mating: Includes assortative mating and inbreeding, where mate choice or geographic proximity biases mating patterns. Changes genotype frequencies without directly changing allele frequencies, and can influence evolutionary trajectories.
Natural Selection: Acts on heritable variation, leading to differential reproductive success. There are four main principles: heritable variation, struggle for resources, differential reproductive success, and changes in allele frequency over time. In addition to directional, stabilizing, and disruptive selection, other dynamics include frequency-dependent selection and sexual selection. Ecology acts as the selecting force, as environmental factors (soil moisture, temperature, predation, mutualisms, competition) influence advantageous traits.
E. The Evolution of Reproductive Strategies and Sexual Selection
Sexual reproduction introduces genetic diversity through meiosis, recombination, and fertilization.
The biological imperative to reproduce drives the evolution of mating systems and sexual selection, which can involve male-male competition and female choice.
Sexual selection can operate strongly on males, where relative mating success drives trait evolution (e.g., elaborate plumage, weaponry, vocalization). Trade-offs can exist where traits that maximize mating success reduce survival.
Female choice exerts control over male reproductive success and can drive rapid evolution of secondary sexual traits through direct benefits, good genes, or sexy sons/runaway selection dynamics.
Various examples illustrate sexual selection: male-male competition (combat, sperm competition), female choice (direct benefits like nuptial gifts, good genes, or runaway selection where female preference and male trait co-evolve), and phenomena such as sexual cannibalism or elaborate ornamentation.
The concept of pleiotropy and epistasis can influence trait expression and the evolutionary trajectory of sexually selected characteristics.
The notes discuss the genetic architecture of complex traits, where multiple genes (polygenic) and environmental factors contribute to phenotypes like coloration, size, or reproductive traits. Epistasis can produce non-additive effects where one gene alters the expression of another, while linkage can constrain the independent mapping of alleles across loci.
VII. Real-World Applications and Case Studies
A. Coral Reefs as a Model: Defining Problems, Hypotheses, and Data Interpretation
A case study introduced is coral bleaching, where bleaching is driven by high water temperatures.
The problem definition centers on understanding how environmental stressors such as temperature and light intensity affect zooxanthellae abundance and pigment content within coral tissues.
Hypotheses are isolated in a structured way. For example: If we grow corals at normal and hot temperatures, then the number of zooxanthellae will be lower in corals grown at hot temperatures because bleaching is driven by high water temperatures.
These hypotheses are tested using experiments that measure zooxanthellae abundance and pigment content under different temperature and light conditions. The data include figures showing the effects of temperature (27°C vs 32°C) on zooxanthellae abundance and chlorophyll a pigment per zooxanthellae, and how light intensity influences these same variables.
Error bars on graphs reflect the variation around the mean and are used to assess statistical significance. When error bars overlap substantially, differences may not be statistically significant; when they do not, there is a hint of significance, but formal statistical tests are required.
Beyond the lab, satellite imagery and observational strategies are proposed to monitor coral bleaching and ocean temperatures.
Questions are posed about causation vs correlation: Does high temperature cause bleaching, and does observational data alone prove causation? The discussion emphasizes considering alternative causes (light intensity, salinity, pollution, etc.).
B. Evolution in Real Populations
Galápagos Finches: The Galápagos finches example (Grant & Grant) demonstrates how drought-induced shifts in resource availability can drive selection on beak size, producing measurable differences in survival and beak morphology between survivors and non-survivors. Boxplots are used to summarize distributions of numerical traits (e.g., beak size, body mass) and capture central tendency and variability.
Human AMY1 gene: Another example examines human variation in salivary amylase gene (AMY1) copy number and enzyme activity across populations with different starch diets, highlighting how gene copy number variation can contribute to phenotypic differences and potential local adaptation.
Poaching and Elephants: Poaching and elephant populations are used as case studies to show how human-caused selective pressures can influence trait distributions (e.g., tusk length and circumference) and how long-term data can reveal shifts in populations under strong selective forces.
MegaPlate Antibiotic Resistance: The MegaPlate antibiotic resistance experiment is revisited as a vivid demonstration of rapid adaptation to strong selection, where bacterial populations evolve resistance under exposure to antibiotics. This example emphasizes the speed of evolution in microbial systems and the role of selection.
C. Real-World Implications and Study Practices
Evolutionary thinking applies to medicine, agriculture, conservation, and ecology. Antibiotic resistance demonstrates rapid evolution in microbial populations under strong selection.
Human activities influence evolutionary trajectories in wildlife (e.g., poaching effects on tusk size in elephants, selection on beak depth in Galápagos finches during drought, and dietary effects on amylase gene copy number).
Understanding population genetics helps interpret data from pedigrees, cross-breeding experiments, and population surveys. Pedigree analysis can reveal dominant vs. recessive inheritance in humans and help identify carriers of genetic diseases.
The concept of phenotypic plasticity highlights how genotype-environment interactions shape observed traits. Twin studies illustrate how genetics and environment contribute to phenotypes, such as susceptibility to complex conditions like schizophrenia or obesity.
Finally, the material emphasizes creative and critical thinking in science: formulating hypotheses, designing tests, evaluating data with appropriate statistical tools, and recognizing that multiple evolutionary processes can act simultaneously to shape populations.
VIII. Synthesis and Key Tools
A. Integrating Concepts
The course integrates process of science with evolution, genetics, and population biology.
It emphasizes thinking like a scientist, understanding how data support or refute hypotheses, and recognizing the roles of different mechanisms of evolution (mutation, gene flow, genetic drift, natural selection, non-random mating).
It also highlights the difference between observational data and experimental manipulation, the importance of statistical interpretation (e.g., error bars and significance), and how to use models like Hardy-Weinberg as baseline comparisons.
The study of evolution is connected to real-world phenomena to illustrate how theory translates into empirical evidence.
The content also covers ethical and societal implications of science, such as public trust in science and the role of science in policy decisions.
Finally, the notes underscore that evolution is the change in allele frequency over time, and that the ultimate product of evolution is populations that are better adapted to their environments.
B. Key Equations and Notation
Hardy-Weinberg allele frequency relation: p + q = 1
Hardy-Weinberg genotype frequencies: p^2 + 2pq + q^2 = 1
Recombination frequency (genetic distance): r = \frac{\text{number of recombinant offspring}}{\text{total offspring}}
Map distance units: 1\% \text{ recombination} = 1 \text{ map unit (centiMorgan)}
Probability rule (independence): P(A\text{ and }B) = P(A) \times P(B)
Two-allele genotype frequencies: p^2,\ 2pq,\ q^2\; (\text{for genotypes } AA,\ Aa,\ aa)
Central dogma summary: DNA -> RNA -> Protein; base pairing rules: A\text{(DNA)}-T, C-G; A\text{(RNA)}-U, C-G; and the role of transcription and translation in producing polypeptides from mRNA.
Other core relationships: genotype vs phenotype, dominance/recessiveness, homozygous vs heterozygous, incomplete dominance, codominance, epistasis, and pleiotropy.
C. Practice and Review Prompts (Representative Examples)
What is the difference between a theory and a fact? How do scientists use the scientific method to test theories?
Define a problem in coral bleaching and outline a testable hypothesis. How would you design an experiment to isolate the effects of temperature and light on zooxanthellae abundance?
Explain the four main principles of natural selection and provide an example for each.
What are the key differences between benign, neutral, and deleterious mutations? How do frameshift mutations differ from point mutations in terms of their impact on proteins?
Describe how meiosis generates genetic diversity via segregation, independent assortment, and recombination. What is the role of chiasmata in crossing over?
Compare and contrast Hardy-Weinberg equilibrium with real populations. What factors can violate HW assumptions, and how would you test for deviations?
Explain pleiotropy and epistasis with examples. How can these interactions influence evolutionary outcomes?
Discuss sex-linked inheritance and provide an example problem involving X-linked traits in humans or Drosophila.
Interpret a dihybrid cross and a test cross. What would you expect for phenotypic ratios if two genes assort independently? What if they are linked?
How does natural selection differ from genetic drift and gene flow? In what scenarios might drift overpower selection, and vice versa?