DNA Arrays …DNA systematically arrayed at high density, –virtual genomes for expression studies, RNA hybridization to DNA for expression studies, –comparative.
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DNA Arrays …DNA systematically arrayed at high density, –virtual genomes for expression studies, RNA hybridization to DNA for expression studies, –comparative genomics, DNA hybridization to DNA, –inter- and intra-species comparisons, etc. –potential yet to be developed.
DNA Arrays …or, why did my home-brew beer blow up? http://www.bio.davidson.edu/courses/genomics/chip/chip.html
Probes/Targets...Probes: are the tethered nucleic acids with known sequence, –the DNA on the chip,...Target: is the free nucleic acid sample whose identity/abundance is being detected, –the labeled nucleic acid that is washed over the chip.
DNA Chip Photolithography in situ probe synthesis
Circadian Rhythms Relating to, or exhibiting approximately 24-hour periodicity, –circa (latin), around + dies (latin), day. Circadian clocks –Internal Biochemical Oscillators, found in all eukaryotes, eubacteria as well.
Humans? Details of mammalian clocks were elucidated by classical and genomic work, first accomplished in Drosophila.
The Experiment? …in Arabidopsis DNA representing > 8000 Arabidopsis genes (out of nearly 26,000 total) has been arrayed by Affymetrix, the chip is available for purchase, –mRNA from whole tissue* is extracted and labeled, –hybridized to the chip, –fluorescence is measured for each gene. Then…mass data analysis.
Gene Expression Technologies DNA Chips (Affymetrix) and MicroArrays can measure mRNA concentration of thousands of genes simultaneously General scheme: Extract RNA, synthesize labeled cDNA or cRNA, Hybridize with DNA on chip.
The Experiment After hybridization, –Scan the Chip and obtain an image file, –Image Analysis (find spots, measure signal and noise). Output File, –Affymetrix chips: Measure each gene’s signal and make a present/absent call. –cDNA MicroArrays: competing hybridization of target and control. For each gene the log ratio of target and control.
Preprocessing: From one experiment to many Chip and Channel Normalization –Aim: bring readings of all experiments to the same scale, –Cause: different RNA amounts, labeling efficiency and image acquisition parameters, –Method: Multiply readings of each array/channel by a scaling factor such that: The sum of the scaled readings will be the same for all arrays Find scaling factor by a linear fit of the highly expressed genes.
Preprocessing: From one experiment to many Filtering of Genes –Remove genes that are absent in most experiments –Remove genes that are constant in all experiments –Remove genes with low readings which are not reliable.
We can ask many questions? Supervised Methods (directed analysis), –which genes are expressed differently in two known types of conditions? –what is the minimal set of genes needed to distinguish one type of condition from the others? Unsupervised Methods (undirected analysis), –what set of genes behave similarly in the experiments? –how many different types of conditions are there? Generally, limited number of significant genes are arrayed. Generally, as many genes as possible are arrayed.
Goal A: Find groups of genes that have correlated expression profiles, –these genes are believed to belong to the same biological process and/or are co-regulated. Goal B: Divide conditions to groups with similar gene expression profiles, –example: define drugs according to their effect on gene expression. Unsupervised Analysis Clustering Methods