Week 10: functional genomics

Functional genomics

the study of the relationship between genes and their function

Levels of focus of functional genomics

DNA level - genomics and epigenomics
RNA level - transcriptomics
Protein level - proteomics
Metabolite level - metabolomics

Various technologies for functional genomics

DNA microarrays
Mass spectrometry
Next generation sequencing

DNA microarrays

Measure expression of thousands of genes at a time

Inkjet printer technology

Can use photolithography

Photolithography in microarrays

By selectively using light and masks to unblock specific spots on a glass slide, scientists can add one nucleotide at a time and build millions of different DNA sequences in parallel, creating a DNA microarray.

mass spectrometry

Measures the abundance of proteins in the cells and tissues

Next generation sequencing

Measures DNA sequences and the abundance of RNAs

Transcriptome

All transcripts an organism makes at any given time

Transcriptomics

Part of functional genomic studies that measure the levels of RNAs produced from many genes at a time

genomic functional profiling

the use of genomic information to try to determine the pattern of expression of all the genes in an organism at all stages of the organisms life

Genome-wide association study

Compare many individuals genomes to find significant differences and link this to phenotype

Single nucleotide polymorphisms (SNPs)
Chromosomal structural variations (SVs) - including inversions, deletions, duplications

Beginning of the microarray technology

To enhance the reliability of the chips - included multiple oligonucleotides designed to hybridize to single transcripts

Using a microarray to identify differentailly expressed genes (DEGs)

Red > more active in the presence of serum
Green > more active in the absence of serum
Yellow > equally active in presence and absence of serum

Seeing which genes are being transcribed

Another application of microarray for the functional genomics project

DNA microarrays allow functional genomics studies by comparing labeled RNAs hybridized to thousands of gene probes, revealing differentially expressed genes under different biological conditions.

Microarray functionality during development

Can reveal temporal patterns of gene regulation during development

Drosophila experiments
Embryonic vs pupal development

SAGE (serial analysis of gene expression)

A method of analyzing the range of genes expressed in a given cell

• genes follow distinct expressions patterns during development
• similar genetic programs are reused at different developmental stages

CAGE (cap analysis of gene expression)

Because it focuses on the 5'-ends of mRNAs, it also allows the identification of transcription start sites (TSS) >>> it helps locate promoters

Procedure starts with reverse transcription

Transcriptional mapping

Map the transcripts with great accuracy to sites in whole chromosomes

TUFs

Transcripts of Unknown Function; role in the cell is unknown

human cells produce far more RNA than expected from protein-coding genes alone

Explains the great differences between species

The large proportion of transcript regions outside the exon

• genomes of eukaryotes are larger and more complex
• complex eukaryotes have large amounts of noncoding sequences

Deletion analysis

Take off pieces bit by bit to see if gene is still expressed
Mutant analysis by replacement

RNA interference (RNAi)

A technique used to silence the expression of selected genes.

RNAi uses synthetic double-stranded RNA molecules that match the sequence of a particular gene to trigger the breakdown of the gene's messenger RNA.

Tissue specific down regulation by miRNAs

MiRNAs regulate gene expression by down-regulating target mRNAs by binding to 3´utrs >>> proved by MEME (consensus sequence of CAUUCC)

Used to reveal how gene regulation differs between tissues

Motif Discovery

Identifying recurring patterns in DNA sequences.
Done by MEME (its a tool)

Effects of transcription factors

Identifying the genes and DNA sequences directly controlled by a TF by examining cells that overexpress certain transcription factors and which genes get activated by them

Limitations of testing for transcription factors

1) the genes that are turned on may not be direct targets of the activator, but may be targets of other activators whose genes were stimulated by the first activator

2) Their might be difference between in vivo and in vitro situation

Genome-wide search for DNA-protein interactions in yeast by ChIP analysis

Using ChIP and ChIP on chip to identify the binding sites for TF (transcription factor) GAL4 throughout the yeast genome

PROBLEM: finding TF binding sites is limited to the sequences placed on the chip (human genome is too big)

Mapping a transcription factor binding sites by ChIP-seq

1. DNA and proteins are first cross-linked in living cells, and the DNA is fragmented.
2. Ab specific to the TF of interest is then used to immunoprecipitate the TF along with the DNA fragments it is bound to.
3. The purified DNA fragments are amplified and sequenced using next-generation sequencing (NGS).
4. The resulting short sequence reads are mapped back to the genome.
5. Clusters of overlapping reads (peaks) indicate regions where the TF binds.

• improvement over ChIP-chip (suitable for large genomes such as humans)
• powerful and unbiased

CRMs

Cis regulatory modules

A different approach to finding TF binding sites in the human genome

Looks for clusters of binding sites

Lie in regions thought to be devoid of genes

Locating enhancers that bind unknown proteins

Looking for highly conserved noncoding DNA regions in other species

Functionally important regulatory elements such as enhancers are under strong evolutionary constraint and therefore remain conserved

Finding promoters

Some promoters lie hundreds of bps from their genes

Over 1600 genes have multiple promoters

Expression of two genes in mouse embryos

Mice can be used as human surrogates

Expression of all the mouse orthologs have been studied on human chromosome 21

Down syndrome genes identified this way

MALDI-TOF mass spectrometry

evaluation of protein spectrum of each microorganism (looking at mass)
matrix-assisted laser desorption/ionization - time of flight
replaces biochemical testing

Proteome

The properties and activities of all the proteins that organism makes in its lifetime

Sequencing a peptide by mass spectronomy (MS/MS)

Principle: the higher the mass, the longer the time of flight of the ion

Masses reveal the exact chemical compositions of the peptides

Collision Induced Dissociation (CID)

collision of molecule and fragment to produce more fragments

Can break peptide bonds

Comparing the masses of ions differing by one aa leads to determining a sequence of the peptide

Quantitative proteomics

measurement of abundance of proteins across multiple conditions

Isotope-Coded Affinity Tags (ICAT)

A method that involves labeling proteins with isotopic tags, which allows for quantification and identification of proteins via mass spectrometry.

Using ICATs to measure the change in protein concentrations upon shift in growth conditions

Labeling the sample under condition 1 with a light isotope and a sample under condition 2 with a heavy iosotope

Proteins appear as peaks separated by the masses difference in the tags
The ratio of the heavy to light area tells us the change in protein concentration as the growth conditions change

Methods to detect protein-protein interactions

Yeast two-hybrid assay
Protein microarrays
Immunoaffinity chromatography Followed by mass spectrometry
Protein microchip

Allow for the discovery of functions of new proteins

Protein microchip to detect pro-pro and pro-lip interactions

The intensity of the red fluorescence indicates the amount of protein in each spot

Each pair of green spots on the microarray corresponds to a protein that binds to the protein or lipid probe

Bioinformatics

A scientific subdiscipline that involves using computer technology to collect, store, analyze, and disseminate biological data and information (DNA; aa sequences)