Genomics II: Functional Genomics, Proteomics, and Bioinformatics Quiz

Omics

• In biology, the word "omics" refers to the sum of constituents within a cell at all levels.
• There are several types of omics, including:
  • Epigenomics: deals with chemicals that can tell the genome what to do
  • Proteomics: studies the entire collection of proteins that an organism can make
  • Bioinformatics: analyzes biological information using a mathematical/computational approach
  • Transcriptomics: analyzes the complete set of gene expression
  • Metabolomics: is the large-scale study of small molecules, commonly known as metabolites, within cells, biofluids, tissues, or organisms

Functional Genomics

• The goal of functional genomics is to elucidate the roles of genetic sequences in a given species.
• It aims to understand gene function and the interplay among many different genes.
• Recent genome-sequencing projects have enabled the study of gene function at a more complex level.
• We can now examine groups of many genes simultaneously.

DNA Microarrays

• DNA microarrays (also called gene chips) are a technology that makes it possible to monitor thousands of genes simultaneously.
• A DNA microarray is a small silica, glass, or plastic slide that is dotted with many sequences of DNA.
• Each of these sequences corresponds to a known gene.
• The DNA fragments on a microarray can be either amplified by PCR and then spotted onto the microarray or synthesized directly on the microarray itself.
• A single slide contains tens of thousands of different spots in an area the size of a postage stamp.
• The technology for making DNA microarrays is quite amazing, involving spotting technologies that are quite similar to the way that an inkjet printer works.

Applications of DNA Microarrays

• DNA microarrays can be used to:
  • Compare microarray data using cDNAs derived from RNA of different cell types to identify genes that are expressed in a cell-specific manner.
  • Identify genes that are expressed in a cell-specific manner.
  • Probe the function of proteins.

Bioinformatics

• The computer has become an important tool in genetic studies.
• The marriage between genetics and biocomputing has yielded an important branch of science: bioinformatics.
• Computer analysis of genetic sequences usually relies on three basic components: a computer, a computer program, and some type of data.
• A computer program is a defined series of operations that can analyze data in a desired way.
• A first step in the computer analysis of genetic data is the generation of a computer data file.
• The genetic sequence can be analyzed in many ways, including:
  • Does a sequence contain a gene?
  • Where are functional sequences, such as promoters and splice sites?
  • Does a sequence encode a polypeptide?
  • Is a sequence homologous to other sequences?
  • What is the evolutionary relationship between two or more genetic sequences?

Approaches to Identify Genes

• Gene prediction refers to the process of identifying regions of genomic DNA that encode genes.
• Computer programs can employ different strategies to locate genes, including:
  • Search by signal: looking for an organization of known sequence elements that are normally found within a gene.
  • Search by content: looking for sequences that differ significantly from a random distribution due to codon bias within protein-encoding genes.

Open Reading Frames

• Another way to locate coding regions within a DNA sequence is to examine reading frames.
• In a DNA sequence, the reading of codons could begin with the first, second, or third nucleotide.
• These are called reading frame 1, 2, and 3, respectively.
• An open reading frame (ORF) is a nucleotide sequence that does not contain any stop codons.
• In prokaryotes, long ORFs are contained within the chromosomal gene sequences.
• In eukaryotes, however, the chromosomal coding sequences may be interrupted by introns.

Homologous Genes

• When comparing genetic sequences, researchers sometimes find two or more similar sequences.
• Homology between genetic sequences can be identified by computer programs and databases.
• A strong correlation is typically found between homology and function.
• Homologous genes are derived from the same ancestral gene.

BLAST

• BLAST (Basic Local Alignment Search Tool) is a program that starts with a genetic sequence and then locates homologous sequences in a large database.
• Homology among protein sequences is easier to identify than is DNA sequence homology.
• The relationship between the query sequence and each matching sequence is given an E-value (Expect value).
• The E-value represents the number of times that the match or a better one would be expected to occur purely by random chance in the entire database.

Proteomics

• Proteomics is the study of the functional roles of proteins in a species.
• The entire collection of proteins in a species is known as the proteome.
• Genomic data can provide insights into the proteome, but may not accurately measure protein abundance.

The Proteome is Larger than the Genome

• The proteome is larger than the genome due to cellular processes such as:
  • Alternative splicing
  • RNA editing
  • Post-translational covalent modification

Alterations that Affect the Proteome

• Alternative splicing:
  • Occurs in eukaryotes
  • A single pre-mRNA is spliced into multiple versions
  • Splicing is often cell-specific or related to environmental conditions
• RNA editing:
  • Less common than alternative splicing
  • Leads to changes in the coding sequence of mRNA after it is made

DNA Microarrays

• A DNA microarray is a technology that allows for the simultaneous monitoring of thousands of genes.
• It consists of a small silica, glass, or plastic slide dotted with many DNA sequences, each corresponding to a known gene.
• The DNA fragments on the microarray can be:
  • Amplified by PCR and then spotted onto the microarray
  • Synthesized directly on the microarray
• A single slide can contain tens of thousands of different spots, with the relative location of each spot known.

Applications of DNA Microarrays

• Cell-specific gene expression: Comparing microarray data using cDNAs derived from RNA of different cell types can identify genes that are expressed in a cell-specific manner.
• Functional microarrays: Consist of many different cellular proteins, used to probe the function of proteins.

Bioinformatics

• The computer has become an important tool in genetic studies, combining genetics and biocomputing to form the field of bioinformatics.
• Computer analysis of genetic sequences relies on three basic components:
  • A computer
  • A computer program
  • Some type of data

Sequence Files and Computer Programs

• A computer program is a defined series of operations that can analyze data in a desired way.
• A computer data file is a collection of information in a form suitable for storage and manipulation by a computer.
• Entering data into a computer file can be done manually or by instruments that read data directly from a sequencing ladder.

Analyzing Genetic Sequences

• Computer analysis of genetic sequences can answer questions such as:
  • Does a sequence contain a gene?
  • Where are functional sequences, such as promoters and splice sites?
  • Does a sequence encode a polypeptide?
  • Is a sequence homologous to other sequences?
  • What is the evolutionary relationship between two or more genetic sequences?

Homologous Genes

• Homologous genes are genes that have evolved from a common ancestral gene.
• Orthologs: Homologous genes found in different species.
• Paralogs: Homologous genes found in a single organism.
• A gene family consists of two or more copies of homologous genes within the genome of a single organism.

Computer Databases

• Computer databases store large amounts of genetic information generated by researchers.
• Databases contain annotations, including the genetic sequence and a concise description of it, as well as other features of significance.
• Examples of major computer databases include GenBank, EMBL, and DDBJ.

Multiple Sequence Alignment

• This approach compares homologous genes to identify conserved sites and understand their structure and function.
• It was originally proposed by Saul Needleman and Christian Wunsch in 1970.
• The globin gene family in humans is an example of multiple sequence alignment.

Globin Gene Family

• The globin gene family consists of 9 paralogs that are functionally expressed in humans.
• The 9 paralogs fall into two categories: α-chains and β-chains.
• The composition of hemoglobin changes during development, with different genes expressed during early embryonic development and in the adult.
• Comparing the sequences of the hemoglobin chains can give insight into their structure and function.