Review Slides on Genetics - PDF

Submit to me your own favorite organism fun fact https://tinyurl.com/StolafBio150 Cat Office Hours Today till ~12:45 The DNA Ladder The sides of the “ladder” of DNA are made up of the phosphate group and the deoxyribose sugar These molecules link together and provide overall struc...

Submit to me your own favorite organism fun fact https://tinyurl.com/StolafBio150 Cat Office Hours Today till ~12:45 The DNA Ladder The sides of the “ladder” of DNA are made up of the phosphate group and the deoxyribose sugar These molecules link together and provide overall structure for the DNA molecule Bases There are 2 groups of nitrogenous bases: Purines (adenine and guanine) Pyrimidines (cytosine and thymine). The one-ring Pyrimidines are always paired with their counterpart 6 member 1 ring 9 member 2 rings two-ring Purines. Base Pairs If the phosphates and sugars make up the ladder sides, then the base pairs make up the rungs Adenine is always paired up with Thymine Guanine is always paired up with Cytosine However more DNA doesn’t necessarily mean more genes or a more complex organism The human genome includes approximately 20,000 genes The average gene has ~400 base pairs This means ~8 million out of 3.2 billion base pairs are part of genes in the human body Paris japonica has a similar number of genes despite having 150 billion base pairs Genes Of the 20,000 genes in the human genome, approximately 3,800 are used in almost every cell in the body These are called house-keeping genes and they code for structures that are integral to the basic functions of the cell This includes proteins like RNA polymerase (which makes mRNA), actin (which forms much of the structure of a cell), or transferrin receptors (which are critical for iron uptake in the cell) Genes That leaves the majority of genes as important for only certain types of cell or certain processes in an organism All cells within a body contain all the information needed for any part of the body So, how can we have muscle cells or eye cells that have such different structures and purposes? DNA Expression The process by which the information in DNA is used is called Expression Mechanisms within the cell of an organism use genes encoded in DNA to create proteins, RNA, or regulate the expression of other genes Transcription, Translation DNA to RNA to Protein Gene Expression First, RNA polymerase identifies the gene to be expressed and creates an mRNA mirror image of it: Second, the mRNA is taken to the Ribosome where tRNA is transcribed onto it to create proteins based on the codons in the mRNA More on Gene Regulation The process by which certain genes are expressed only in certain cells or at certain times is called “Gene Regulation” Gene regulation can occur during any phase of gene expression: Pre-transcription Transcription Post-transcription Translation Post-translation The specific mechanisms of gene regulation differ during each of these steps We covered cis-regulatory elements and gene expression during transcription Promoter regions provide a site for polymerase to bind to and begin replicating a gene Silencer regions provide a site for proteins that repress transcription to bind to, preventing the function of polymerase Enhancer regions provide a site for proteins that increase the likelihood of a gene being replicated to bind so a gene is expressed a disproportionate amount Terminator regions triggers the release of the transcribed RNA and frees the RNA polymerase All of these are regions are just another part of the DNA strand Non-Coding DNA (NOT JUNK!) and Transcription: Cis-regulatory elements (CREs) Transcription doesn’t start and end at a random location along a strand of DNA Promoter regions provide a site for polymerase to bind to and begin replicating a gene Silencer regions provide a site for proteins that repress transcription to bind to, preventing the function of polymerase Enhancer regions provide a site for proteins that increase the likelihood of a gene being replicated to bind so a gene is expressed a disproportionate amount Terminator regions triggers the release of the transcribed RNA and frees the RNA polymerase All of these are regions are just another part of the DNA strand  More Transcription Gene Regulation Transcription factor (TF) are those proteins are what bind to the cis regulatory regions to attract DNA polymerase and activate DNA transcription Each TF has a portion of DNA sequence (usually of a promoter region) that it readily binds to In the human genome there are ~1400 kinds of TFs, but they often work in combination with one another In eukaryotes, without a TF, polymerase enzymes generally cannot bind to a promoter region Thetech.com  Pre-transcription Gene Regulation Essentially this is where the structure of the DNA is somehow modified to alter the “ease” of transcription Often this means that portions of the DNA remains highly coiled around a histone preventing polymerase from acting on that portion of the DNA Mechanisms of pre-transcription regulation include phosphorylation and methylation of promoter regions Methylation can result in the longer term “epigenetic” changes in gene expression Post-transcription Gene Regulation In Post-transcription regulation, the expression of genes is regulated by modification of the mRNA molecule Frequently, RNA molecules are cut/spliced with proteins that either alter the expression of the gene or prevent it entirely Post-transcription regulation can also occur when the nuclear export pathway is interrupted, preventing mRNA from leaving the nucleus Translation Gene Regulation Translational Gene Regulation occurs as the protein is being created by tRNA in the Ribosomes Translation GR occurs through binding of proteins to the Ribosome or mRNA that alter the amount or type of proteins being synthesized MicroRNA (small pieces of RNA that can bind to mRNA) can also block translation entirely at this phase Post-translation Gene Regulation Post-translation Gene Regulation affects the amino acid chain produced by the ribosome, rather than the DNA or mRNA Typically this process involves proteins that are specifically designed to alter specific proteins Some of this regulation is activating (the original protein was useless, but the altered version is useable by the cell) and some is silencing (altering the original useful protein to no longer work for its intended purpose) Genome-wide Association Crossing studies obviously aren’t practical in many system. GWA take many different individuals from a single, broad population Individuals are categorized into differing phenotypes The entire genome is mapped for these individuals Genetic markers that consistently differ between phenotypes are identified as being associated with the trait in question  Manhattan Plots: The X axis shows SNPs from genes being expressed on each chromosome in a population. Anything below the red line is being expressed is being expressed at about the same amount as the population as a whole. Anything above the red line is being expressed more in the group being examined than the overall population. I.e. – any dots above the red line are genes probably coding for the trait Morgan et al. 2018 GWA is to study inherited risk of disease in humans However, finding markers associated with disease is not always finding the “gene” for that disease Many diseases are associated with many genetic markers and the interaction between genes and the environment is complex Heart Disease There are dozens of markers associated with coronary heart disease How many of these do you need before you worry? Should you not worry if you have none? Environmental factors may completely change the picture Harihan and Dupis 2021 Finding Genes for Quantitative Traits using Quantitative Trait Locus Analysis One of the most important tools to understand the relationship between quantitative traits and the genetic makeup of an organism is a Quantitative Trait Locus Analysis A Locus (plural loci) is the location of a single gene on a chromosome This analysis compares the genotypes of different phenotypes to identify where on the chromosomes (which loci), alleles associated with a particular quantitative trait are being expressed Quantitative Trait Locus Analysis There is a multi-generational process to perform this analysis Researchers breed two phenotypes using disruptive selection The goal is to produce individuals that are homozygous for as many genes that effect the phenotype as possible  Quantitative Trait Locus Analysis So, let’s say you’re studying a phenotype with 10 genes: AaBbCcDdEeFfGgHhIiJj The alleles of each of those specific genes (e.g., Aa) can change the overall phenotype slightly one way or the other The goal is to have two different populations after many generations of selection, each of them homozygous for the alleles that maximize or minimize the quantitative trait Quantitative Trait Locus Analysis So, we’ve got our breeding AAbbCCddeeffGGhhII experiment going on fish Theoretically, if you select for each extreme, you end up with two true breeding, homozygous lineages for all relevant genes The goal is to create two populations: one homozygous for all the large-phenotype alleles and one homozygous for all the small- aaBBccDDEEFFggHHii phenotype alleles Think of this like Mendel's True-breeding Peas… with a lot of genes at once Quantitative Trait Locus Analysis In these strains of fish a bunch of genetic markers (spots on the genome) are different These differences are marked by triangles Location on the Genome But which of those locations actually have to do with size? Quantitative Trait Locus Analysis After many generations, we then cross these two populations Then we cross the first generation of offspring with itself, and end up with a second generation with heterozygous alleles for many of the traits Why don’t we use the first generation for analyses? (Hint: Think back to Mendelian inheritance) Quantitative Trait Locus Analysis So, you now have a 2nd generation with a huge amount of variation in alleles present and phenotypes expressed You can go back to the parent generation (the big and small fish) and comb their genomes for unique DNA sequences that are different from each other These genetic markers are potential locations where the genes for the trait being investigated exist Quantitative Trait Locus Analysis In the second generation of individuals, you can then look for the presence of those genetic markers across the genome If a particular gene is associated The triangles indicate genetic markers where with the trait being studied, its the original big and small populations differ prevalence in certain phenotypes The purple line is how closely associated the will be higher marker is with the trait in the F2 (second generation offspring) This shows which of these genes are related to bigness Non-Mendelian Inheretance Incomplete Dominance – the phenotype of the heterozygous genotype is distinct (and typically intermediate) from either homozygous genotype Co-dominance – both alleles are expressed simultaneously In tortoise shell cats, one X chromosome (which has the allele associated with pigment) is inactivated at random People with AB blood types produce both A and B antigens Multiple Alleles – there can be more than two alleles controlling a single trait at a single loci with different levels of dominance Pleiotropy: One Gene Affecting Multiple Traits Example: “Lethal white” in horses. The allele for coat color is also responsible for aspects of intestinal development. Horses with the pure white gene also have improperly developed intestines and die soon after birth. Relative Fitness – Calculating Selection Determining the strength of selection Strength of Selection (S) is the difference between the mean trait of the entire population and the mean trait of reproducing individuals Determining the effect of selection Response to selection is how much the next generation changes to reflect the characteristics of the breeding population You can quantify a population’s Response to Selection (R) by multiplying it’s Strength of Selection with a trait’s heritability: R = h2 * S If heritability is low, selection will have little effect; if it is high, it will be a relatively strong effect Visualizing Selection and Heritability S (selection) and R (response) can be used to calculate h2 (hereitability) usinging the equation: h2 = R / S In a low heritability system, strength of selection (S) will be much greater than the response to selection (R) In a high heritability system, S and R will be very close to one another  h2 = R / S is an expression of the three elements needed for evolution. Heritability, variation in traits and variable fitness conferred by traits h2 refers to the heritability of the trait S describes the mean values of a trait in “fit” (reproducing) individuals R is how much that trait changed in the next generation (evolution) If h2 is 0, there is no heritability and no population change If the trait has no variation than the mean of S in reproducing and not reproducing is identical and the population doesn’t change If the mean value of that trait is the same between breeding and non- breeding individuals, then there is no difference in fitness and no population change Relative Fitness of a Phenotype w = (S * R) / max(S * R) S is the average survival to reproduction R is the average reproductive output Relative Fitness Practice Question Let’s calculate relative fitness (w) for two phenotypes of snakes, Striped and Spotted (Spotted is dominant to Striped). The calculation for w is: w = (S * R) / max(S * R) Spotted snakes have an annual survival of 0.8 and produce 23 young per year on average. Striped snakes have an annual survival of 0.65 and produce 42 young per year on average. What is w for each phenotype? Relative Fitness Practice Question What is w for each? Spotted S*R = 18.4 Striped S*R = 27.3 Spotted w = 18.4 / 27.3 = 0.674 Striped w = 27.3 / 27.3 = 1 Hardy-Weinberg p2+ 2pq+ q2= 1 & p+q = 1 p is the proportion of the population with the dominant allele q is the proportion of the population with the recessive  These equations can be smooshed together to show changes in allele frequency when phenotypes have different levels of fitness This will provide an average fitness of the population and can be used to calculate changes in allele frequency through time w̅ = (p2 * wphenotype-pp) + (2pq * wphenotype-pq) + (q2 * wphenotype-qq)  If a phenotype associated with a dominant allele is selected against (w