Oral Exam Flashcards
What are the two major disciplines within Behavioural Genetics?
Behavioural genetics is interested in uncovering the relative contribution of genes and environmental factors contribute to the development of certain traits. This can be subdivided into Molecular Genetics and Quantitative Genetics. Molecular Genetics searches for specific DNA variances or polymorphisms which are involved in human behaviours or traits. It uses methods such as DNA microarrays in order to identify specific genes that are connected to or directly influence a particular phenotype. Quantitative Genetics does not specifically look for DNA variances but tries to estimate the relative contribution of genetic and environmental factors in particular traits within a population and operates using methods such as twin, adoptive, sibling and IVF designs. It can also include genome complex trait analysis/GCTA.
What is an Association Study?
Genetic Association studies test for a correlation between disease status and genetic variation to identify candidate genes or genome regions that contribute to a specific disease. They do this by looking at affected and unaffected individuals for specific traits or diseases. A higher frequency of a single-nucleotide polymorphism (SNP) allele or genotype in a series of individuals affected with a disease can be interpreted as meaning that the tested variant increases the risk of a specific disease. SNPs are the most widely tested markets in association studies but copy-number variants/CNVs and microsatellite markers are amongst others that are also used. Association studies are a major tool in identifying genes conferring susceptibility to complex disorders. The traits and diseases are termed complex because both genetic and environmental factors contribute to the susceptibility risk. Association studies design require large sample sizes and large numbers of genetic markers.
Is Heritability fixed at birth?
Heritability is a population statistic that looks at variability between individual differences. As such it is interested in explaining how much of individual differences within a particular population is explained by genetic variability within their DNA. We then argue that the proportion of variability explained for by genetic influences vary greatly across our development. We can then talk about differences in height and weight as explained for by genetic influences across the lifespan. No, the developmental course of a genetic expression can vary through age, for example, weight has been shown to have a stronger influence in later life. Furthermore, one’s environment can affect the expression of a gene. For example, short allele may make an individual more susceptible to depression when an individual experiences a stressful life event. (Caspi et al, 2003)
What are the aims of Molecular Genetics?
Searches for specific gene variances (DNA polymorphisms) which are involved in human behaviours, traits, and disorders. It does this through linkage, association and knocking out studies in animals. Linkage studies track genotypes within families and pinpoints specific polymorphisms that are found only in affected individuals. This type of pedigree study is not widely used as it requires major effects. Allelic association studies compare cases vs controls. It does this by looking at specific populations (e.g. musical geniuses) and then comparing them to normal populations. This method also requires us to genotype each populations DNA and then we compare the frequency of one allele in one group as compare to another group. The disadvantage of this method is that we have over 10million types of SNPs amongst other types of genetic variations, therefore how do we know which gene is important? Moreover, each polymorphism might also have a small effect onto that population thus it may lack power. Knocking out works by supressing the expression of a particular gene via chemical or radiation methods. This method is very aggressive and is thus only used on animal models.
What are the aims of Quantitative Genetics?
Quantitative Genetics aims to link phenotypic variation to its underlying genetic basis in order to better understand and predict genetic composition and long term change within natural, agricultural, and human populations.
Define A
‘A’ stands for additive genetics or heritability and is a contributing factor in determining the variance within individual differences, along with common or shared environments, known as ‘C’, and non-share environments, known as ‘E’. The contribution of ‘A’ or genes is usually explored via twin studies using monozygotic and dizygotic twin pairs. As MZ twins are genetically identical, being that they share roughly 100% of their segregating genes and DZ twins share roughly 50% of their segregating genes, studying these twin pairs allows us to estimate the genetic contribution to the variance of a specific phenotype. We know that the concordance (or similarity) rates for any given phenotype in MZ twins is a combination of ‘A’ (genes) and ‘C’ (shared environments) and for DZ twins a combination of ‘.5A’ (as they share half the same genes) and ‘C’ (shared environments). Therefore, when studying twin pairs for a particular phenotype, we can subtract the concordance rate value for DZ twins for that phenotype from the concordance rate for the same phenotype in MZ twins in order to determine the value of .5A. For example, if when studying the variability of height, MZ twins were found to have a concordance rate of 0.8 and DZ twins a concordance rate of 0.6, the resulting value of .5A would be 0.2. This can then by multiplied by 2 to give us a value for ‘A’, which in this case would be 0.4. This gives us an estimate that 0.4 or 40% of the variance in a population for this specific phenotype is due to genetics, meaning the remaining 0.6 or 60% of the variance is due to shared and non-shared environments. It is important to note that heritability is a population statistic and cannot be applied to an individual person, for example, it is not possible to say that 40% of somebody’s height is due to their genes. It is only applicable to populations and thus, may vary between different groups of people.
Define C
‘C’ stands for common or shared environments, which refers to environments that are experienced by family members that are perceived in the same way in order to contribute to similarity between members. ‘C’ is a contributing factor in determining the variance within individual differences, along with additive genetics, known as ‘A’, and non-shared environments, known as ‘E’. The contribution of ‘C’ or shared environments is usually explored with twin studies and adoption studies. In twin studies which use monozygotic twins who share roughly 100% of their segregating genes, and dizygotic twins who share roughly 50% of their segregating genes, we can estimate the contribution of ‘C’ or shared environments as we know that the similarity in twin pairs is due to a combination of shared genes and shared environments. For MZ twins who are genetically identical, we say that their similarity is explained by ‘A + C’, whereas for DZ twins who share roughly 50% of their segregating genes, we say that their similarity is explained by ‘.5A + C’. Therefore, when studying twin pairs for a particular phenotype, we can calculate the value of ‘C’ by calculating the value of ‘A’ first and then subtracting ‘A’ from the concordance or similarity rate in MZ twins, whose similarity is explained by ‘A + C’. For example, if MZ twins were found to have a concordance rate of 0.8 for height, and DZ twins a concordance rate of 0.6, we can calculate the value of ‘A’ by subtracting the DZ concordance value from the MZ concordance value to give us .5A and then multiply it by 2. In this case, that would mean that the value of ‘A’ is 0.4. As said previously, the MZ concordance rate is made up of ‘A + C’, therefore if ‘A’ is 0.4 then ‘C’ will also be 0.4 in this example to equal the 0.8 MZ concordance rate. The remaining 0.2 would be explained by ‘E’ or non-shared environments. Adoption designs are also useful in helping us understand the contribution of shared environments because they allow a more explicit examination of shared environments. An adoption design would include a sibling pair, one biological and one adoptive whose similarities could only be explained by ‘C’ or shared environments as they would share none of their segregating genes. In these studies, any concordance rates for a phenotype between the sibling pairs are solely explained by shared environments. This is important for understanding variance as twin studies are based on a series of assumptions that may lead to an over estimation of the contribution of ‘A’ or genes if they have been violated. Studying a particular phenotype using both twin designs and adoption designs allows us to be more confident in the estimation of the contribution of ‘C’ to that phenotype. The difficulty however with shared environments is that they are difficult to define. Parenting styles often differ from child to child (REFERENCE!), making this a non-shared environment or something that contributes to the dissimilarity in twins or siblings, rather than a shared environment. Specific events, e.g. a divorce, may also be interpreted or perceived differently by each child and hold different meaning for them, again contributing to their dissimilarity even though both are experiencing the same event.
Define E
‘E’ stands for non-shared environments, which refers to either differing environments that are experienced by family members, or the same environments that are perceived in different ways and thus contribute to dissimilarity between family members. An example of a non-shared environment may be friendship groups or chance factors, such as accidents and illnesses. ‘E’ is a contributing factor in determining the variance within individual differences, along with additive genetics, known as ‘A’, and shared or common environments, known as ‘C’. The contribution of ‘E’ or non-shared environments can be explored in twin studies and adoption studies, but can also be looked at in family design studies as in all situations there will be the presence of non-shared environments. In twin studies which use monozygotic twins who share roughly 100% of their segregating genes, and dizygotic twins who share roughly 50% of their segregating genes, the concordance or similarity rates found for a particular phenotype are due to a combination of shared genes and shared environments. For MZ twins who are genetically identical, we say their similarity is a result of ‘A + C’ as their genes and shared environments are exactly the same, meaning we can make the assumption that any discordance in MZ twin pairs for a phenotype is due to ‘E’ or non-shared environments. When calculating variance, we can subtract the concordance rate for MZ twins from 1 to give us a value for ‘E’. For example, if for a particular phenotype the MZ concordance rate was 0.8, then we would know the value of ‘E’ is 0.2 suggesting that 20% of the variance in this phenotype within a population is due to non-shared environments. Understanding what constitutes a non-shared environment and what effect it may have on an individual is important in understanding why MZ twins with the same genes and are raised in the same environments may show different behaviours.
List 5 facts about DNA
DNA or deoxyribonucleic acid codes for your genetic makeup and is found inside every cell in our bodies, apart from red blood cells. Human beings share high proportions of their DNA with other species, including around 92% with mice and 98% with chimpanzees. DNA is a double stranded molecule, in the form of a helix, held together by weak bonds between base pairs of nucleotides. There approximately 3 billion chemical letters or base pairs in the DNA code, which are comprised of 4 nucleotides – Adenine (A), Guanine (G), Cytosine (C) and Thymine (T). Due to their molecular structures, Adenine always pairs with Thymine and Guanine always pairs with Cytosine to form the base pairs. Thus, the base sequence of each single strand can be deducted from that of its partner. The backbone of each strand consists of sugar and phosphate molecules. The specific pairing of nucleotide bases allows DNA to carry out its functions which is to replicate itself and to direct the synthesis of proteins, according to the genetic information that resides in the particular sequence of bases. Approximately 2% of DNA is made up of sections that code for amino acids, which are called genes. The combination of the base pair letters within the DNA sequence determine which amino acid is produced and more than one combination can produce the same amino acid. For example, GTT and GTC both code for the production of the amino acid Glutamine. Only this 2% of our DNA is transcribed into RNA and therefore translated into proteins, whilst the other 98% of our DNA is non-coding in that it is transcribed but not translated. DNA replication is the process by which DNA makes a copy of itself during cell division. The first step in DNA replication is to ‘unzip’ the double helix structure, this is carried out by an enzyme called helicase which breaks the hydrogen bonds which hold the complimentary bases of DNA together. The separation of the two single strands of DNA creates a ‘Y’ shape called a replication ‘fork’. The two separated strands will act as templates for making the new strands of DNA. The leading strand is orientated towards the replication fork and the lagging strand is orientated away from the replication fork and as a result, the two strands are replicated differently. The result of DNA replication is that two double helix’s are created, half of the chain being part of the original DNA molecule and the other half brand new, where previously there was only one.
What are microarrays?
DNA Microarrays are collections of microscopic DNA spots attached to a solid surface that can be used to measure the expression levels of large numbers of genes simultaneously or to genotype multiple regions of a genome. Microarrays measure the changes in mRNA expression which is responsible for the production of proteins. Microarrays can be used to look at the differences in expression in different types of tissues, for example, liver or lung tissues or to look at the differences in the same type of tissues that are behaving differently, for example, healthy and cancerous skin tissue. To do this, tissue samples are collected and then dissolved in a solvent in order to separate the RNA from the other cell components. There are different types of RNA within the samples, so the messenger RNA or mRNA molecules are separated from the transfer RNA/tRNA and ribosomal RNA/rRNA molecules by washing the samples over a column of beads that will only attach to RNA strands with sequences of adenines at the end, known as a ‘poly-A tail’ which are only found in mRNA molecules. A buffer solution is then used to detach the mRNA from the beads. A labelling mix is then added to each sample in order to assemble a complementary DNA or cDNA strand and to colour code the different samples for easy identification when they are added to the microarray, usually in green and red. Stuck to the microarray are little piles of single-stranded synthetic DNA molecules. A single spot contains many identical copies of the same gene and each spot on the microarray represents a different gene, which is recorded in a computer database. When two complementary DNA strands are mixed together, they will find and base pair with each other reforming a double-stranded DNA molecule. It doesn’t matter where they come from – they’ll do that even if they were not originally paired. This process is called hybridisation and is the key to how DNA microarrays work. When the samples are added, most of the cDNA molecules will hybridise to their complementary DNA standards on the microarray while a few will remain stray. The microarray is then washed to clear any extra cDNAs that didn’t bind to the slide and then placed in a scanner to analyse. Spots with a combination of the two colours (usually shown as yellow), means that that gene was expressed in cells in both the healthy and cancerous samples. For example, if a microarray was used to examine skin cells with healthy and cancerous samples, a yellow spot on the microarray would suggest that that gene may not be particularly helpful as the activity of that gene doesn’t change when the cells becomes cancerous, as both healthy and cancerous cDNA attached to that gene spot. This means that the amount of mRNA produced was the same in both samples. Cancerous spots, let’s say coloured red, show genes that produce more mRNA in cancer cells than in healthy cells, so they’re more active in cancer. Healthy or green spots show genes that produce less mRNA in cancer cells. This is useful in studying complex diseases as some genes are responsible for producing protein products whose role is to reduce or ‘turn down’ the expression of several other genes – i.e. some of the green spots. However, there are some limitations to microarray technology because it is still possible for defective genes to still produce mRNA, but the defect prevents the mRNA from being translated into protein. In the cancer example, these genes would show as yellow on the microarray, as the mRNA was found in both healthy (green) and cancerous (red) cells. There is no way to tell using microarray technology whether mRNA expression is resulting in translation and protein production, which is considered a major limitation of the technology. DNA microarray analysis on its own cannot identify the defective genes which cause a disease or identify every gene that is behaving inappropriately.
What is a SNP?
SNPs or single nucleotide polymorphisms are the most common type of genetic variation. In human beings, our DNA sequences are more than 99% identical with only very small sections producing the many differences between us. SNPs are points in the DNA sequence at which there is a single difference in the nucleotide present. For example, a SNP may replace the nucleotide cytosine (C) with the nucleotide thymine (T) in a certain stretch of DNA. SNPs occur normally throughout a person’s DNA. They occur once in every 300 nucleotides on average, which means there are roughly 10 million SNPs in the human genome. Most commonly, these variations are found in the DNA between genes. They can act as biological markers, helping researchers locate genes that are associated with disease. When SNPs occur within a gene or in a regulatory region near a gene, they may play a more direct role in disease by affecting the gene’s function. Most SNPs have no effect on health or development. Some of these genetic differences, however, have proven to be very important in the study of human health. Researchers have found SNPs that may help predict an individual’s response to certain drugs, susceptibility to environmental factors such as toxins, and risk of developing particular diseases. SNPs can also be used to track the inheritance of disease genes within families. Future studies will work to identify SNPs associated with complex diseases such as heart disease, diabetes, and cancer. Single nucleotide polymorphisms (SNPs) are the most common type of genetic variation among people. 90% of DNA sequence variability is SNPs. They represent a change in a single DNA base (A, C, G or T) in the DNA code. SNPs occur throughout the genome and, on average, there is a SNP every 300 bases. SNPs may fall within coding sequences of genes, non-coding regions of genes, or in inter-genic region between genes. Most SNPs within a coding sequence will not produce a change in an amino acid sequence as the SNP will be involved in one of the alternate DNA codes for the same amino acid, these are referred to as synonymous (or known as a silent mutation). SNPs which produce a change in an amino acid sequence are referred to as non-synonymous and are therefore functional as the resulting protein will contain a different amino acid. SNPs that are not in protein coding regions may still have consequences for gene splicing, transcription factor binding, or the sequence of non-coding RNA. Many genetic changes associated with complex diseases have been identified by looking to see if there are SNPs that occur more, or less frequently in people with a disease, than people without the disease. This type of study is called a genome-wide association study (GWAS). Identifying SNPs associated with particular diseases will enable scientists to predict an individual’s likelihood of developing the disease and how it runs in families. These ‘risk SNPs’ can also help scientists to identify biological pathways underlying these diseases which can help with the development of treatments.
What is the ‘QTL method’?
A QTL or quantitative trait locus is a region of DNA that correlates with variation in a phenotype. The QTL is typically linked to, or contains, the genes that control that phenotype. QTLs are mapped by identifying which molecular markers, such as SNPs, correlate with an observed trait and are often found on different chromosomes. Knowing the number of QTLs that explains variation in the phenotype tells us about the genetic architecture of a trait. It may tell us that a phenotype is controlled by many genes of small effect, or by a few genes of large effect.
Describe the Twin Method
The Twin Method is a commonly used method is Quantitative Genetics that helps us to determine the contribution of genes, shared environment and non-shared environment to a particular phenotype within a population. The Twin Method design takes advantage of the fact that monozygotic twins share around 100% of their genes and shared environment, meaning we can assume that any differences in monozygotic twin pairs in a particular phenotype are due to non-shared environments. Dizygotic twins share only around 50% of their genes and 100% of their shared environment. Therefore, by comparing DZ twin concordance rates and MZ twin concordance rates we are able to estimate how much contribution each of the three factors of variance makes to individual differences. The Twin Method does have some limitations as it is based on a number of assumptions.
Describe the Adoption Method
The adoption methods that’s advantage of the fact that adoptees have the genes of their bio parents but the environment of the adopted families, thus by looking at the similarities between the adoptee and the adoptive parents we are able to examine the influence that environment has over ID, whereas the similarities between the adoptee and the biological parents are due to genes. Problems: not all adoptees are adopted out at birth, thus early environment may have an impact. Children are also usually adopted into similar families thus environments may not be so dissimilar. Used by quantitative genetics. STUDY
How can we estimate the influence of non-shared environment?
Non-shared environment or ‘E’ The contribution of ‘E’ or non-shared environments can be explored in twin studies and adoption studies, but can also be looked at in family design studies as in all situations there will be the presence of non-shared environments. In twin studies which use monozygotic twins who share roughly 100% of their segregating genes, and dizygotic twins who share roughly 50% of their segregating genes, the concordance or similarity rates found for a particular phenotype are due to a combination of shared genes and shared environments. For MZ twins who are genetically identical, we say their similarity is a result of ‘A + C’ as their genes and shared environments are exactly the same, meaning we can make the assumption that any discordance in MZ twin pairs for a phenotype is due to ‘E’ or non-shared environments. When calculating variance, we can subtract the concordance rate for MZ twins from 1 to give us a value for ‘E’. For example, if for a particular phenotype the MZ concordance rate was 0.8, then we would know the value of ‘E’ is 0.2 suggesting that 20% of the variance in this phenotype within a population is due to non-shared environments. Understanding what constitutes a non-shared environment and what effect it may have on an individual is important in understanding why MZ twins with the same genes and are raised in the same environments may show different behaviours.
