1 Fall 2006 – 7.03 7.05, 2006, Lecture 23 Eukaryotic Genes and Genomes IV In the last three lectures we have thought a lot about analyzing a regulatory system in S. cerevisiae, namely Gal regulation that involved a hand full of genes. These studies monitored the increased transcription of Gal genes in the presence of galactose (and the absence of glucose); we saw that this regulation is achieved by particular proteins, or multiprotein complexes that bind to specific sequences in the promoter region upstream from their target genes. What if I told you that it is now possible to do the following in S. cerevisiae: ! Monitor mRNA expression level for every gene in S. cerevisiae, in one single experiment. ! Monitor all the binding sites in the S. cerevisiae genome for each transcription factor in a single experiment. ! Determine all possible pair-wise interactions for every S. cerevisiae protein. Obviously I wouldn’t mention these possibilities if they weren’t already happening. What I want to do today is to introduce you to the idea of carrying out genetic analyses on a global, genome-wide scale, and hopefully give you some examples that are relevant to what we have already learned along the way. So, this will be a technology oriented lecture, but with some application to what we have already learned about gene regulation in eukaryotes. It should also be mentioned that what will be described for S. cerevisiae, is theoretically possible for any organism whose genome has been completely sequenced and the location of all the genes in that genome have been established. So, what we will learn today is being, or will be, applied to higher eukaryotes and mammals. ! Monitor mRNA expression level for every gene in S. cerevisiae, in one single experiment: Global transcriptional profiling. Before we consider how it is possible to measure the levels of thousands of mRNA species, we will have to step back to consider how the levels of one or two mRNA species can be measured by Northern Blot analysis….and I know you must have learned this in 7.01 if not in high school. Northern blot analysis is based upon the fact that DNA and RNA molecules that possess complementary base sequences will hybridize together to form a double stranded molecule. If the complementarity is perfect the duplex molecule is stable, if it is imperfect (with base pair mismatches) !"#$%&' )* +%,%' -%& .a-l)12 +%,)#%34866144666194666 ::4366::4366!"#$%&' )* +%,%' -%& .a-l)12 +%,)#%34866144666194666 ::4366::43662 Fall 2006 – 7.03 it is relatively less stable. This provides the specificity needed to identify perfectly matched DNA:RNA duplexes (on Northern Blots) and DNA:DNA duplexes (on Southern Blots). This specificity is needed to be sure we are measuring the level of one particular transcript and that this is not contaminated with signal from closely related transcripts. RNA is isolated from cells, size fractionated on a gel; the thousands of mRNAs species form a smear on the gel which is punctuated by the strong ribosomal RNA bands (28S and 18S) that do not interfere with the analysis. The breakthrough in developing microarrays for analyzing mRNA levels was to reverse the logic – instead of immobilizing the mRNAs for hybridization with one or two labeled complementary DNA (cDNA) probes, all possible cDNA probes are immobilized on a solid surface (usually glass slides). The spoting of probes is achieved robotically; the DNA probes are designed to specifically hybridize to only one nucleic acid sequence that represents a single mRNA species. The thousands of DNA probes are dispensed from 96-well, or 384-well plates to an addressable site on the solid surface. The mRNA population from each cell type purified and then copied such that the copy is fluorescently labeled. This fluorescent population is hybridized to the immobilized probes, and the intensity of the fluorescence at each probe spot is proportional to the number of copies of that specific mRNA species in the original mRNA population. !he immobili*ed m,N. population is probed 6hybridi*ed89ith :2<=labeled se>uen?es spe?ifi? for one or t9o gene produ?ts;ll #<!;' '%-a&a=%2 $> '1?% !he immobili*ed m,N. population is probed 6hybridi*ed89ith :2<=labeled se>uen?es spe?ifi? for one or t9o gene produ?ts;ll #<!;' '%-a&a=%2 $> '1?% Northern Blots@##)$1l1?%2 #<!; -)-"la=1), .>$&121?%2 A1=. la$%l%2 B!; -&)$% &%-&%'%,=1,+ ),% )& =A) +%,%'DN. Di?roarrays@##)$1l1?%2 B!; -&)$%' &%-&%'%,=1,+ all-)''1$l% +%,%'.>$&121?%2 A1=. la$%l%2 #<!; -)-"la=1),3 Fall 2006 – 7.03 So let’s look at how this would actually work in a real experiment. mRNA is isolated from yeast cells in state A (e.g., minus galactose) and from yeast cells in state B (e.g., plus galactose), and copies of each population is made such that one fluoresces red and the other fluoresces green. After mixing, these fluorescent molecules are hybridized to the slides containing ~5,800 DNA probes, each one specific for detecting hybridization of many copies of an individual mRNA species. The location and identity of each probe on the microarray slide is known, and each probe is specific for a single mRNA. The color and intensity of the fluorescence is measured by scanning the slide with lasers, and the relative abundance of each mRNA in the cells of State A vs State B can be calculated from the emitted fluorescence, i.e., the relative level of 5,800 mRNAs can be compared between two populations of yeast cells. Presenting data for thousands of mRNA transcripts is clearly a challenge. You could present endless tables of data, but our brains are much more adept at recognizing shapes, patterns and colors. Colored representations of up and down regulation of transcripts levels is the preferred way to present data. C%a'= 1, '=a=% ;;;;;;;;;;;;;;;;;;;;;DDDDDDDDDDDDDDDDDDDDC%a'= 1, '=a=% E;;;;;;;;;;;;;;;;;;;;DDDDDDDDDDDDDDDDDDDDEabel c)-1%' )* #<!; '-%c1%' A1=. <GB )& G<GG! @')la=% #<!; -)-"la=1),'I@JDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDFybridi*e =) =.% #1c&)a&&a>C%a'= 1, '=a=%
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