5.5: Functional Genomics

Gene expression analysis: RNA Sequencing

Techniques such as RNA sequencing (RNA-seq) can measure gene expression levels across the genome, helping scientists understand when, where, and under what conditions genes are active. Figure \(\PageIndex{1}\) below summarizes the major steps of RNA-seq. In contrast to genome sequencing, in RNA-seq, it isn't the genome that is sequenced, but the transcriptome - the complete range of mRNA molecules made through gene expression. Thanks to techniques like next-generation sequencing (NGS), the transcriptome of a biological sample can be determined in a matter of hours. Using RNA-seq, researchers can examine alternatively spliced transcripts, post-transcriptional modifications, gene mutations and changes in gene expression over time, or measure differences in gene expression in different groups or treatments. RNA-seq can also look at different populations of RNA, including total RNA, mRNA, microRNA (miRNA), and transfer RNA (tRNA). For more information about next-generation sequencing, go to Chapter 10.2 Diagnostic Biotechnology.

Gene expression analysis: Gene Silencing and RNA Interference

By inhibiting or "silencing" the expression of specific genes in organisms or cells, researchers can observe the resulting changes, providing insights into a gene's role in various biological processes and diseases. There are several mechanisms that can be used in the laboratory to inhibit the expression of a specific gene. One mechanism is based on a cell's natural defense mechanism and is known as RNA interference (RNAi). RNAi mechanisms within a cell target specific mRNA molecules for degradation or inhibit their expression into proteins. As such, RNAi may be a powerful tool in the discovery of drugs and their treatment of many diseases, such as cancer.

Two types of RNAi mechanisms are used in laboratories:

1. small interfering RNA (siRNA)
2. microRNA (miRNA)

siRNA and miRNA molecules are known as non-coding RNA molecules. Non-coding RNA is not translated into polypeptides. An siRNA molecule is a short, double-stranded RNA (dsRNA) molecule of 20 to 24 nucleotides long. miRNA is also single stranded RNA that is 21 nucleotides in length. The mechanism that siRNA and miRNA use to silence gene expression is very similar (Figure \(\PageIndex{2}\)). siRNA genes are transcribed in the nucleus as either a long piece of double-stranded RNA (dsRNA) or as a piece of "hairpin" RNA - a section of dsDNA (i.e., the "stem") with a "loop" at the end. An miRNA gene is also transcribed in the nucleus as a long piece of dsRNA with several hairpin sections. This long piece is cut into smaller pieces known as pre-miRNA. Both the siRNA and pre-miRNA are exported into the cytoplasm for processing by an enzyme Dicer. Dicer is an RNA-specific enzyme that removes the loops from siRNA and miRNA molecules, leaving the double-stranded section. The double-stranded siRNA or miRNA molecules are then denatured into single strands through a mechanism not fully understood, but involves a protein called Ago2. The single stranded piece of siRNA or miRNA associates with several proteins to form an RNA-Induced Silencing Complex (RISC). The bound siRNA or miRNA in the RISC complex then binds to its complementary mRNA sequence which leads to eventual silencing of the gene by the RISC.

How the siRNA and miRNA molecules result in gene silencing differs. The binding of siRNA to its complementary sequence is "perfect", with no mismatches. This leads to degradation of the bound mRNA by the RISC and silencing of the corresponding gene. However, the match between the miRNA and its complementary sequence does not have to be 100%. In fact, in animal cells, the base pairing between miRNA and mRNA is not a perfect match. This mismatch leads to an inhibition of translation because the RISC prevents the binding of the small ribosomal subunit to the mRNA. The gene is silenced as a result. Eventually, the poly-A tail is degraded which leads to the eventual degradation of the entire mRNA molecule. In contrast to animal cells, the binding of the miRNA-RISC complex is perfect in plant cells, with no mismatches. Like the siRNA mechanism, this perfect match between the miRNA sequence and its mRNA leads to direct degradation of the bound mRNA.

Gene silencing in the lab using siRNA or miRNA is based on their naturally-occurring mechanisms. For siRNA silencing, an siRNA sequence is designed against the target gene and then cloned into an expression vector that can be introduced into mammalian cells either through transfection or by using an expression system that incorporates the siRNA sequence into a viral vector. The effect of silencing that gene can then be determined. As with siRNA, miRNA sequences can be cloned and introduced into mammalian cells to learn how the silenced gene functions. Anti-mRNA oligonucleotides can be designed to bind and inhibit miRNA function without the need for cloning. Finally, other compounds that inhibit miRNA function can also be considered.

Confirmation of gene silencing involves downstream protein analysis techniques, such as SDS-PAGE electrophoresis and Western Blotting. Through these techniques, researchers can detect expression of a specific protein and quantify its expression level. To learn more about SDS-PAGE, go to Chapter 13.11: SDS-PAGE. To learn about Western Blotting, go to Chapter 13.12: Western Blotting.

Mutational Analysis

Mutational analysis is used in laboratories to identify mutations in the DNA sequence of a gene so that researchers can understand how genetic alterations contribute to diseases, disorders, and even certain infections. It is a critical part of the process known as genetic testing. In mutational analysis, DNA is extracted from tissues such as blood, tissue, saliva, or even tumor biopsies. The gene of interest is amplified using Polymerase Chain Reaction (PCR) and the mutation confirmed using DNA sequencing methods, like Sanger sequencing and next generation sequencing (NGS). The use of NGS has become popular owing to its ability to detect a range of mutations, including single nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations. However, additional sequencing methods like Sanger sequencing are often used to confirm the NGS results. Bioinformatics tools align the sequenced DNA to the reference genome to confirm and identify the mutation(s). Functional studies can then be performed in order to assess how the mutation affects protein function, cellular pathways, or affects the phenotype of the organism. Well known genes identified using mutational analysis include the BRCA1 and BRCA2 genes involved in breast and ovarian cancer. To learn more about PCR, go to Chapter 13.2: Polymerase Chain Reaction (PCR). To learn about DNA sequencing, go to Chapter 13.9: DNA sequencing.

One of the most common mutations studied through mutational analysis is the single nucleotide polymorphism (SNP). A SNP is a substitution of a single nucleotide at a specific position in the genome. SNPs can occur in both coding and non-coding regions of a gene, in addition to regions of the genome outside of a protein-coding gene (Figure \(\PageIndex{3}\)). SNPs within a coding region of a gene can be classified as synonymous (not affecting the protein sequence - i.e., a "silent" mutation) and non-synonymous (affecting the protein sequence). While the synonymous mutation does not affect the sequence of the protein, it may still affect the function of the protein. The non-synonymous SNPs are known as missense and nonsense mutations. These mutations can have significant effects on protein function depending on what domain of the protein the mutation can be found. SNPs that are not in protein-coding regions may still affect gene expression through their effects on splicing, transcription factor binding, or mRNA stability.

Over 600 million SNPs have been identified in the human genome across the world's population. Within a single human genome, close to 4 million SNPs can be found. Many of these SNPs are found associated within protein-coding sequences. However, most SNPs are located outside protein-coding regions. These SNPs may be unique to the individual or may be found within individuals who share a similar racial profile or geographic origin. This finding is the basis for many commercial ancestry companies.

Measurement of Molecular Activities: The "Omics" Approach

In genomics, the measurement of molecular activities involves the quantitation of various molecules within a cell, like RNA transcripts or proteins. Through this work different "omics" have emerged, including including transcriptomics (for RNA expression), proteomics (for protein expression), and metabolomics (for studying metabolite levels). Each "omic" is related to one another and is a part of a critical flow of information in the cell (Figure \(\PageIndex{4}\)).

Transcriptomics studies and quantifies the transcriptome, the complete set of RNA transcripts, produced by the genome in a specific cell type, under particular conditions, or at specific points in time. The transcriptome includes all RNA, such as mRNA and the other non-coding RNAs like rRNA, tRNA, miRNA and snRNA. Because the transcriptome is dynamic, constantly changing based on the condition of the cell, studying it through transcriptomics can provide a detailed view of gene expression patterns. These patterns may help researchers understand how genes are regulated and function within complex biological processes, such as diseases like cancer. Transcriptome analysis can be done through microarray analysis. However, most transcriptomics is now done through RNA sequencing (RNA-seq).

Proteomics studies and quantifies the proteome, the complete set of proteins expressed in a cell, tissue, or organism. Proteomics uses techniques such as mass spectroscopy, two-dimensional gel electrophoresis and protein-protein interaction studies to understand how proteins function within complex biological pathways, in addition to identifying biomarkers associated with diseases, and those drugs which may be used for treatments. Finally, metabolomics studies and measures the metabolome, the complete set of metabolites in a biological system. Metabolites are small molecules produced or modified by metabolic processes. They include carbohydrates, amino acids, fatty acids, nucleotides, and signaling molecules. Metabolomics provides insights into the biochemical state of a cell or organism and is often used in combination with genomics, transcriptomics, and proteomics to gain a more holistic understanding of biological processes and disease mechanisms. To read more about proteomics, go to Chapter 5.6 Proteomics.

Other Techniques

Scientists studying functional genomics have additional techniques available to them. Studying protein-protein interactions other using methods like yeast two-hybrid screening or co-immunoprecipitation, may help identify metabolic pathways that are critical for cellular function. Epigenomics, the study of chemical modifications on DNA and histones (e.g. methylation) provides insight into gene regulation mechanisms beyond that of DNA sequences.