Question

Think about the many recent technological advances in the field of genetics. Choose the one that you think might be the most influential over the next ten years and explain the reasons for your choice. DO NOT USE GENE THERAPY

Answer 1

Epigenetics (including epigenetic techniques)

A relatively new area of research based on the science of epigenetics is uncovering how our environment interacts with certain genes to switch them on or off permanently, or alter their expression—much like a light-switch dimmer.

Epigenetics is the study of changes in gene activity that do not involve alterations to the genetic code, yet are heritable. These patterns of gene expression are governed by the cellular material— the epigenome —that overlies the genome.

For example, epigenetic changes include DNA methylation and histone modification, both of which serve to regulate gene expression without altering the underlying DNA sequence.

DNA methylation, for example, is a naturally occurring process that can cause a potentially reversible change in the activity of a gene. It helps to determine which genes are turned ‘on’ or ‘off’ in each cell—and at what level or intensity of expression—thus influencing the cells’ functions. DNA methylation is the process in which enzymes (methylases) add methyl groups onto specific cytosine nucleotides in genes and in so doing block their activity. Many cancer biologists agree that methylation and other so-called epigenetic changes may be as important as genetic mutations in causing and promoting cancer.

Histone modification does not change the chemistry of DNA but does affect the protein platforms around which DNA is “spooled” (i.e., the core histones). These proteins condense DNA and provide an initial level of gene organization. Histones can be modified by methylation, acetylation and phosphorylation. These changes are dynamic, reversible and can act to recruit specific protein factors that are important for regulating gene expression. The combined interactions of the different types of modification yield a “histone code,” which influences the likelihood that associated DNA will be transcribed (or not).

Various techniques are used to identify epigenetic modifications to DNA. These may include:

• mapping locus-specific differences in DNA modification by using enzymes that recognize the same target sequence in the DNA but were either sensitive or insensitive to its modification;
• exposing DNA to bisulphites and then sequencing, in effect allowing methylated sites to be identified;
• using chemical approaches or antibodies targeted to specific modifications (e.g., cytosine modification). Antibody-based approaches are also widely applied to identify the various types of histone protein modification in chromatin.

These techniques can be amplified by using DNA microarrays or next-generation (high-throughput) sequencing techniques to analyze the entire epigenome.

Genome-wide association studies

Genome-wide association studies (GWAS) enable researchers to identify genes involved in human illnesses and thereby test for the association between genetic polymorphisms (the recurrence within a population of two or more discontinuous genetic variants of a specific trait, such as blood type) spread evenly over the entire genome. GWAS search the genome for small variations, called single nucleotide polymorphisms (SNPs) that occur more frequently in people with a particular illness versus those without.

Once new genetic associations are identified for a particular illness, researchers can use the information to develop better strategies to detect, treat and prevent the disease. Such studies are particularly useful in finding genetic variations that contribute to common, complex illnesses such as arthritis, cancer, diabetes, heart disease and psychiatric illnesses.
If certain genetic variations are found to be significantly more frequent in people with the disease compared to those without, the variations are said to be “associated” with the disease. The associated genetic variations can thereby indicate the region of the human genome where the disease-causing mutations reside.
An analysis of GWAS data requires the performance of thousands of statistical tests. Some adjustment for the multiple testing issues is required to declare a genetic variant significantly associated with the outcome of interest. Researchers often consider that a p-value of the magnitude 5.10-8 (before adjustment for multiple testing) is necessary to achieve genome-wide significance.
However, the associated variants themselves may not directly cause the disease. Therefore, researchers often take additional steps, such as fine-mapping by imputation (i.e., substitution) of dense SNPs or by sequencing DNA base pairs in that particular region of the genome, to identify the exact genetic change involved in the disease.
Some researchers are now moving away from GWAS, which was originally motivated by the “common variants, common diseases” hypothesis. For many diseases and complex traits, GWAS have not been able to identify genetic variants that could explain a large proportion of heritability. Therefore, many investigators are now searching for novel rare variants through next-generation sequencing techniques (described below) that could explain this “missing heritability.”

When using family data, linkage analysis can be a powerful approach to find rare variants that segregate through families. A linkage signal can be detected at markers up to 20 Mb away from the disease or trait locus of interest.