Gene Editing: The Role of Oligonucleotide Chips

Gene Editing: The Role of Oligonucleotide Chips

Curators: Larry H Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN



  • 2015 Breakthrough Prize: Jennifer Doudna, Emmanuelle Charpentier, Dick Costolo, Cameron Diaz

  • 2015 Breakthrough Prize Symposium Welcome Panel (Part 2)

  • Creator Space™ Science Symposium – Jennifer Doudna

  • Jennifer A. Doudna, PhD | UCLA School of Medicine 56th Annual Lectureship

  • Jennifer Doudna (UC Berkeley / HHMI): Genome Engineering with CRISPR-Cas9

  • Genome Engineering: Genome Editing with CRISPR-Cas9 – How the Editing is done at the nucleotide level and animation from MIT

More Videos on Note:

  • Davos 2015 – Rewriting Human Genes:

Greg Mello, 2006 Nobel Prize on Interference RNA and Jeniffer Doudna

  • RNA Therapeutics and DNA Editing, Jeniffer Doudna

  • Jennifer Doudna, Rosalind Franklin Society –

  • 2015 Life Sciences Panel with Allis, Ambros, Benabid, Charpentier, Doudna and Gary Ruvkun

  • Emmanuelle Charpentier – Alexander von Humboldt Professorship 2014 (EN)

  • 2015 Massry Prize Laureate: Emmanuelle Charpentier

  • Prix Louis-Jeantet de médecine 2015 – Emmanuelle Charpentier

  • Deux chercheuses lauréates du prix Princesse des Asturies pour leurs avancées sur la génétique

  • CSHL 2015 Symposium Interview Series with Emmanuelle Charpentier

  • CSHL 2015 Symposium Interview Series with Jennifer Doundna – 21th Century Genetics Engineering




Gene editing is a method that has several revisions over the last decade, and in the current form has used an enzyme from a bacteria that breaks the DNA of an attacking virus. Thus, it is an evolutionary method for cellular defense. The discovery and development of the method has been recognized by

SCIENCE Selects CRISPR-Cas9 as

2015 Annual Breakthrough

2015 Breakthrough Prize: Jennifer Doudna, Emmanuelle Charpentier, Dick Costolo, Cameron Diaz

2015 Breakthrough Prize Symposium Welcome Panel (Part 2)


The method has been recently expanded by Zhang et al. @MIT

to the extent that errors in code reading have been minimized.

Ethical Issues in Editing Human Germ-line

have been raised about the use of the method, which has application to the food market, and it has uncertain pitfalls in translational medicine.

International Summit on Human Gene Editing: A Global Discussion, National Academy of Sciences, WashDC, December 1-3, 2015


To what end do we do gene editing?

We use the method to remove a part of the genetic material that is tied to expression of an unwanted phenotypic expression. This is more complicated than it may appear. The main problem is how accurately the portion of the genomic target reflects the phenome expressed. This assumes that common diseases, which might be attributed to both genomic expression and environmental conditions, can be easily reduced.

1. Classic view of genetics is that gene expression follows a predictable pathway that is as follows:

DNA—>>> RNA—>>> Protein

This is not the case when we consider the numerous interactions that we call feedback regulatory mechanisms.


Pictograph of the DNA strands

The slide illustrates the double stranded helical DNA strands that are made of linear paired nucleotides linked at 3’ and 5’ positions. The strands separate and unwind and each strand is replicated as “bases” are paired forming a replicated strand, and the new strands combine and rewind.

2. The Challenge of DNA Replication

a.  Enzymatic breaking of DNA strands

b.  New nucleotides pair with unwound strand

c.  Two copies of DNA strand

DNA replication


SOURCE: Google Images

This concept has undergone many challenges that has been mentioned and will not be addressed.

3. Types of RNA

a. There are many RNAs – mRNA, tRNA, cRNA, ncRNA, siRNA, mtRNA

b. The RNA role in gene expression has an impact on DNA regulation

c. The protein that is produced in the endoplasmic reticulum has modifiable action on the DNA function through action on chromatin, and through pathway activation or inactivation by protein folding and related “allostericity”

 3.1. RNA Medicine

3a Sarepta’s phosphorodiamidate morpholino oligomer—or PMO—chemistry platform

Sarepta Therapeutics Headquarters, Cambridge, MA


Phosphorodiamidate morpholino oligomers – or PMOs – are assembled in precise sequences that correspond to the specific target RNA. These therapeutics bind selectively to the target RNA and modulate its function to increase or decrease the production of a protein involved in a disease.


3b. Exon-Skipping for Duchenne (DMD)

3c. Drug Development – eteplirsen

PMO-based drug development has the potential to address countless diseases, including serious and life-threatening diseases that otherwise could not be treated with traditional small molecule or biologic drugs. The human genome of about 22,000 genes is the basis for more than 250,000 RNA transcripts and about 150,000 proteins, a universe rich with potential targets for PMO-based therapies.

Sarepta Therapeutics Announces FDA Has Filed Eteplirsen NDA for the Potential Treatment of Duchenne Muscular Dystrophy for Patients Amenable to Exon 51 Skipping

  • FDA Grants Priority Review Status
  • PDUFA Date is February 26, 2016
August 25, 2015 05:17 PM Eastern Daylight Time

CAMBRIDGE, Mass.–(BUSINESS WIRE)–Sarepta Therapeutics, Inc. (NASDAQ:SRPT), a developer of innovative RNA-targeted therapeutics, today announced that the U.S. Food and Drug Administration (FDA) has filed the New Drug Application (NDA) for eteplirsen for the treatment of Duchenne muscular dystrophy (DMD) amenable to exon 51 skipping. Approximately 13% of people with Duchenne muscular dystrophy are estimated to have a mutation addressable by Eteplirsen/exon 51 skipping.

The FDA has completed its filing review and has determined that our application is sufficiently complete to permit a substantive review. The Prescription Drug User Fee Act (PDUFA) action date for a decision on the application is February 26, 2015. The FDA has granted eteplirsen Priority Review status, which is designated to drugs that offer benefit over existing therapies, or provide a treatment where no adequate therapy exists.

3d. Why CRISPR might be better than exon skipping for DMD

By Lauren Martz, Senior Writer
Published on Thursday, January 21, 2016

As if to preempt the regulatory setbacks in Duchenne muscular dystrophy (DMD) that last week disappointed the field, a trio of preclinical studies emerged two weeks earlier showing that cutting out DMD mutations with gene editing might offer a viable alternative to the exon-skipping strategies that have dominated the pipeline. Now, the question is whether there’s reason to believe the mouse studies will translate any better to the clinic.

The studies, published Dec. 31 in Science, provide in vivo proof of concept for the first time that CRISPR-Cas9 used postnatally can have a disease-modifying effect. Despite the hype around its therapeutic promise, the technology has so far proved itself primarily in research applications, for example, in modifying cells for in vitro screening or creating animal models of disease.


3.2 Sarepta Therapeutics, Corvallis, Oregon, has been assigned a patent (9,238,042) – “antisense modulation of interleukins 17 and 23 signaling.”

01/21/2016 | 07:08am US/Eastern
By Targeted News Service

ALEXANDRIA, Va., Jan. 21 — Sarepta Therapeutics, Corvallis, Oregon, has been assigned a patent (9,238,042) developed by four co-inventors for “antisense modulation of interleukins 17 and 23 signaling.” The co-inventors are Frederick J. Schnell, Corvallis, Oregon, Patrick L. Iversen, Corvallis, Oregon, Dan V. Mourich, Albany, Oregon, and Gunnar J. Hanson, Bothell, Washington.

The patent application was filed on May 13, 2011 (13/107,528). The full-text of the patent can be found at,38,042.PN.&OS=PN/92,38,042&RS=PN/92,38,042

Written by Deviprasad Jena; edited by Jaya Anand.

Sarepta Therapeutics Corvallis

United States Patent 9,238,042
Schnell ,   et al. January 19, 2016

Antisense modulation of interleukins 17 and 23 signaling

AbstractProvided are antisense oligonucleotides and other agents that target and modulate IL-17 and/or IL-23 signaling activity in a cell, compositions that comprise the same, and methods of use thereof. Also provided are animal models for identifying agents that modulate 17 and/or IL-23 signaling activity.,38,042.PN.&OS=PN/92,38,042&RS=PN/92,38,042


4. Principle of complementarity in linking of oligonucleotide pairs.

Two pictographs show the principle of complementarity in linking of oligonucleotide pairs.

  • The first identifies the obligatory pairing of guanine-cytosine (G-C) and adenine-thymine (A-T)
  • The second is a model the exact complementary base pairing of oligonucleotide sequences.



SOURCE: Google Images


DNA Molecule:  Two Views in One – Bases and Phosphate Groups

Notice the role of phosphate groups in the bonding.

DNA Molecule


base and backbone



5. Oligonucleotide sequence composed of introns and exons

Pictograph of an oligonucleotide sequence composed of introns and exons (sequences) from which the introns are removed, creating a new sequence of exons that are translated into AA chain


DNA Transcription



The picture shows a DNA sequence composed of two types of oligonucleotide sequences colored red and blue (introns and exon). The splicing removes the red colored introns from the nucleotide chain, leaving a chain composed of recombined blue exons. The resulting chain is translated into an amino acid chain based on an obligatory pairing of nucleotide to amino acid. The resulting chain, a posttranslational modification, is the primary sequence of a protein. The finished protein has secondary and tertiary structure.

6. Gene editing to change a value in a linear sequence in an oligonucleotide

Then it is safe to say that we do gene editing to change a value in a linear sequence in an oligonucleotide that is translated into an amino acid through RNA which may be expected to have functional significance. A sequence of 3 nucleotides codes for each of 23 amino acids. However, there have been constructs proposed for a triplex model that might account for three additional metabolites.

7. Mutation and Transcription Errors

  • There are many mutations that occur having no functional significance, which results in our not needing to pay attention to the change.
  • There are mutations that have functional significance as a result of expression that we identify as pathological.

8. Gene Expression

A pictorial image of gene expression is shown with a structural translation and a functional portion. The functional portion is really a diversity of methods involving proteomics and metabolomics.

Struc-Func genomics

SOURCE: Google Images

The genome function directly addressed by editing is in the structure – the oligonucleotide sequence.

The pictograph show major aspects of functional genomics, which is largely dictated by 3-D structure built on amino acid sequencing, and acts through subtrates and cofactors. The amino acid sequence of a protein is determined by triplet oligonucleotide portions.

9. Phenotypic Variation

  • amino acid nucleotide sequences are related to phenotypic variation
  • Most of human genetic variation is represented by SNPs (Single Nucleotide Polymorphisms) and many of them are believed to cause phenotypic differences between human individuals.
  • PolyPhen (= Polymorphism Phenotyping) is an automatic tool for prediction of possible impact of an amino acid substitution on the structure and function of a human protein. This prediction is based on straightforward empirical rules which are applied to the sequence, phylogenetic and structural information characterizing the substitution.
  • oligonucleotide triplets define amino acids in sequence

10. Codons specify which amino acid will be added next during protein synthesis.

The code defines how sequences of nucleotide triplets, called codons, specify which amino acid will be added next during protein synthesis.

A series of codons in part of a messenger RNA (mRNA) molecule. Each codon consists of three nucleotides, usually corresponding to a single amino acid. The nucleotides are abbreviated with the letters A, U, G and C.

  • mRNA, which uses U (uracil). This mRNA molecule will instruct a ribosome to synthesize a protein according to this code
  • DNA uses T (thymine) instead.



11. Codon Table and 21 Amino Acids (AA)

Inverse table (compressed using IUPAC notation)
Amino acid Codons Compressed Amino acid Codons Compressed


11. Amino acid composition of proteins and Amino acid frequency

Genetic information contained in mRNA is in the form of codons, sequences of three nucleotides, which are translated into amino acids which then combine to form proteins. At certain sites in a protein’s structure, amino acid composition is not critical. Yet certain amino acids occur at such sites up to six times more often than other amino acids.


12. Amino acid composition and protein dimension

Oliviero Carugo

The amino acid composition of a nonredundant set of about 550,000 proteins was determined and it was observed that, in the range of 50–200 residues, the percentage of occurrence of most of the residue types significantly depends on protein dimension.

The percentage of occurrence pcaa,i of the amino acid aa in the ith protein was computed for each of the 20 types of amino acids in each protein as

where naa,i and nresi are the number of residues of type aa observed in protein I and the total number of residues in protein i, respectively. Then, the pcaa,i values were averaged for all protein that contains the same number of residues R, by computing



13. Frequency of a particular codon

The frequencies of DNA bases in nature are 22.0% uracil, 30.3% adenine, 21.7% cytosine, and 26.1% guanine. The expected frequency of a particular codon can then be calculated by multiplying the frequencies of each DNA base comprising the codon. The expected frequency of the amino acid can then be calculated by adding the frequencies of each codon that codes for that amino acid.

By plotting the expected frequency against the observed frequency, we can see if some amino acids are occurring more or less often than expected by chance. If the observed and expected frequencies are close to equal, we would expect a line with a slope = 1


14. Amino acid composition of proteins reduces deleterious impact of mutations

protein composition works alongside the genetic code to minimize impact of mutations on protein structure

15. Evolution of amino acid frequencies

Evolution of Amino Acid Frequencies in Proteins Over Deep Time: Inferred Order of Introduction of Amino Acids into the Genetic Code

Dawn J. Brooks*Jacques R. Fresco*Arthur M. Lesk and Mona Singh

It is proposed that the inferred amino acid composition of proteins in the LUA probably reflects historical events in the establishment of the genetic code


16. 1:1 relationship between genetic codons and amino acid composition

The classical dogma infers that there is a 1:1 relationship between genetic codons and amino acid composition. However, …..

the regulation of cellular pathways and of gene expression is also dependent on the functional portion, which accounts for the activities of pathways and interactions with the environment. These interactions are very fast. The posttranslational results interact with one another defining specific pathways and also are affected by pathway omissions that may be a result of interactions between mRNA or protein and chromatin of the DNA.


17. The Importance of Gene Editing

is the critical need to change the code for which there are 3 nucleotide combinations for each of 21 amino acids that form the primary protein structure. Critical mutant changes may cause the deletion of a vital amino acid in a key functional location. Most notable is a sulfhydryl group, as in methionine or in cysteine, which is involved in disulfide bonds, necessary for protein folding. Other changes may be in a histidyl residue – a ring structure that has importance


18. Predicting the Genetic Code

The genetic code used by a genome can be predicted by identifying the genes encoded on that genome, and comparing the codons on the DNA to the amino acids in homologous proteins in other genomes. The evolutionary conservation of protein sequences makes it possible to predict the amino acid translation for each codon as the one that is most often aligned to that codon. The program FACIL[41] allows the automated prediction of the genetic code, searching which amino acids in homologous protein domains are most often aligned to every codon. The resulting amino acid probabilities for each codon are displayed in a genetic code logo, that also shows the support for a stop codon.


19. Amino Acids and Proteins

Which of the following has the most significant influence on the characteristics of an individual protein?

  • the amino-acid sequence
  • the amino-acid composition
  • the location of its encoding gene within the genome
  • the stereochemistry at the α-carbon




20. Types of Microarrays

Types of microarrays

SOURCE: Google Images

  • The microarrays that are now necessary to break down gene expression are not limited to DNA microarrays. The discussion here is limited to DNA microarrays for gene editing.
  • The remarkable advances in oligonucleotides analysis, proteomics and metabolomics are large advances in science analytics, but they are disjointed steps in dissecting the large puzzle that we wish to realize as life shaping.
  • A missing portion of explaining life may not ever be known by the static methods we own because there is a time dimension that we have no comprehension of. This was predicted by the Nobel Physicist Irwin Schroedinger in his seminal book “What is Life?”


21. Chip for Detection of Reverse Transcribed cDNA to labelled cRNA

This is a pictograph of the sequence of steps in biotinylation of the reverse transcribed cDNA to labelled cRNA, and detection on the chip.


SOURCE: Google Images

22. DNA microarray: Table


SOURCE: Google Images


23. The CRISPR-Cas9 Mechanism



24. Diseases that can be attacked using the genome editing method.

Consider –

  • multiple organ mutant neonatal disorders
  • single organ mutant inborn errors
  • chronic adult onset disorders (not necessarily mutational)
  • cancer – stage II or less
  • neurological/cognitive
  1. schizophrenia
  2. MS
  3. AML
  4. Alzheimer’s
  • Immunological disease
  • B-cell
  • Amyloidosis
  • T-cell

Priority would be to bacterial, virus, and insect borne parasites

  • Malaria
  • River bed fever
  • Antibiotic resistant bacteria (S. aureus, E. coli, C. difficile, …
  • Recent virus strains



The bacterial enzyme Cas9 is the engine of RNA-programmed genome engineering in human cells. Graphic by Jennifer Doudna/UC Berkeley.

“The ability to modify specific elements of an organism’s genes has been essential to advance our understanding of biology, including human health,” said Doudna, a professor of molecular and cell biology and of chemistry and a Howard Hughes Medical Institute Investigator at UC Berkeley. “However, the techniques for making these modifications in animals and humans have been a huge bottleneck in both research and the development of human therapeutics.

“This is going to remove a major bottleneck in the field, because it means that essentially anybody can use this kind of genome editing or reprogramming to introduce genetic changes into mammalian or, quite likely, other eukaryotic systems.”

“I think this is going to be a real hit,” said George Church, professor of genetics at Harvard Medical School and principal author of one of the Science Express papers. “There are going to be a lot of people practicing this method because it is easier and about 100 times more compact than other techniques.”

“Based on the feedback we’ve received, it’s possible that this technique will completely revolutionize genome engineering in animals and plants,” said Doudna, who also holds an appointment at Lawrence Berkeley National Laboratory. “It’s easy to program and could potentially be as powerful as the Polymerase Chain Reaction (PCR).”

The latter technique made it easy to generate millions of copies of small pieces of DNA and permanently altered biological research and medical genetics.



Diagnosing Diseases & Gene Therapy: Precision Genome Editing and Cost-effective microRNA Profiling


An RNA-based complex guides the DNA-cutting enzyme Cas9 to specific sites in the genome. The natural RNA-programmed DNA cleavage system is shown on the left, with the engineered system on the right.

Image: H. Adam Steinberg,


double strand

Illustration by KC Roeyer


CRISPR/Cas9, a defense system that bacteria use to protect against invading genetic elements, was adapted by scientists in 2012 as tool to edit genomes in the lab. The new technology has been adopted enthusiastically by the research community because of its ability to cleave target sequences of DNA with remarkable precision and efficiency. Now, after directly watching individual Cas9 enzymes explore DNA inside living cells, Howard Hughes Medical Institute (HHMI) scientists report that they have a better understanding of how Cas9 speeds through this task, testing out potential targets but quickly moving on from those that are not an exact match.

The research, published November 13, 2015, in the journal Science, was co-led by Robert Tjian, president of HHMI; Zhe Liu, a group leader at the Janelia Research Campus; and Jennifer Doudna, an HHMI investigator at the University of California, Berkeley, who is one of the inventors of the CRISPR-Cas9 genome-editing tool.

“CRISPR-based genome engineering offers exciting prospects for curing human disease as well as for advancing agriculture and synthetic biology,” said Doudna. “These studies provide a detailed mechanistic picture of the CRISPR machinery as it operates in living cells, helping to advance both fundamental understanding as well as application of the technology in mammalian cells.”

In both the naturally occurring bacterial defense system and in the CRISPR genome-editing tool, the DNA-cutting Cas9 enzyme is guided to its target by a 20-letter piece of RNA that matches a sequence of DNA embedded within the genome. When Cas9 and its guide find the complementary sequence, they bind to the target and cut. In the laboratory, Knight says, target sites are cut within a few hours of introducing the Cas9 complex to cells.

Previous experiments had demonstrated that Cas9 doesn’t bind exclusively to its true targets, however. A match of just 5-8 letters of genetic code is enough to cause what the scientists call off-target Cas9 binding. Off-target cutting, however, is much rarer. If a sequence that Cas9 binds to does not fully match its 20-letter guide, the enzyme almost always releases the DNA and renews its search.

“A longstanding question was how can Cas9 scan vast eukaryotic genomes, which have billions of DNA bases, and find a target in a timely manner if it’s binding at every off target?” says Spencer Knight, a graduate student in the Doudna and Tjian labs who is the first author of the Science paper.


25. Genomics Engineering Technologies for Detection of Mismatched complementarity in linking of oligonucleotide pairs.


SOURCE: Google Images


Two Types of DNA Chips

(a) cDNA based microarrays

(b) Oligonucleutides based microarrays


Type dna

SOURCE: Google Images



Lab Process of Gene Analysis using Gene Chip Expression Array: Biotin Labeled cRNA





SOURCE: Google Images


Probes arranged in array structure on a Chip


SOURCE: Google Images






SOURCE: Google Images


Gene Editing & Statistical Modeling:

Detection of Mismatches using Affymetrix Software

DNA arrays

It is for many biological investigation very desirable to analyse the protein status of a cell. Today the common approach is to separate all the proteins by 2D gel electrophoresis, to stain the proteins and to analyze the obtained spots by mass spectrometry. This give not only the molecular weight but also a fragmentation pattern can be obtained that goes towards mass spec sequencing. This approach called proteomics is still difficult and requires sophisticated mass spectrometry equipment. A way around is to analyze not the proteins but the mRNA content of the cell, although this may be only a rough approximation of the protein content. In any case, already a comparison of the mRNA status of a healthy cell with the status of a cell featuring a disorder may be very informative. These difference allow in some cases to recognize genes which are up or down regulated.

The massively parallel analysis of the mRNA content of cells is today performed with DNA arrays (DNA chips), These are mostly glass plates which are devided in small segments. Each segment contains a specific oligonucleotide attached to the surface either covalently or by absorption. A typical chip is 2.5 x 2.5 cm large and may contain up to 50’000 segments with different oligonucleotide sequences.

The mRNA of the cells to be analysed is first reverse transcribed into cDNA. Then the DNA is amplified using PCR. The DANN is afterwards cut into smaller pieces using hydrolytic enzymes. A ligase such as the RNA ligase which attached unspecifically nucleotides to DNA and RNA is used to attach to each piece of DNA a fluorophore. The so prepared DNA is finally added onto the chip. If the fluorescence labelled oligonucleotide pieces find a complementary piece of DNA on the chip they will form the double strand. The conditions for these hybridizations are carefully controlled so that not matching oligonucleotides are not binding. Under certain conditions one can discriminate between a fully complementary oligonucleotide (binding) and one having a single mismatch (not binding). All the segment were matching oligonucleotides formed a double strand will fluoresce. This can be analyzed so that in a single experiment 50’000 DNA sequences can be checked.

The major problem is to prepare the chips and to deposite the oligonucleotides onto the chips. This is currently achieved in two different ways:

Synthesis of the 50’000 oligonucleotudes using a photolithographic approach directly on the chip (the known phosphoramidite DNA synthesis with light sensitive protecting groups is used)

Synthesis of the oligonucleotides in solution and printing of the DNA strand onto the surface using a modified ink jet printer.

Schematic representation of the DNA array technology

Schematic representation of the DNA array technology



Course Chemical Biology I Nucleic Acids, Established 2004 in Haifa at the Technion

Modern Methods Start Chapter 3


Oligonucleotide chips[edit]

Oligonucleotide chips are microarrays of oligonucleotides.[3] They can be used for detection of mutations and expression monitoring, and gene discovery and mapping.[22]The main methods for creating an oligonucleotide microarray are by gel pads (Motorola), microelectrodes (Nanogen), photolithography (Affymetrix), and inkjet technology (Agilent).[22]

  • Using gel pads, prefabricated oligonucleotides are attached to patches of activatedpolyacrylamide[22]
  • Using microelectrodes, negatively charged DNA and molecular probes can be concentrated on energized electrodes for interaction[23]
  • Using photolithography, a light exposure pattern is created on the substrate using a photomask or virtual photomask projected from a digital micromirror device.[3][6] The light removes photoliabile protecting groups from the selected exposure areas.[6] Following de-protection, nucleotides with a photolabile protecting group are exposed to the entire surface and the chemical coupling process only occurs where light was exposed in the previous step.[6] This process can be repeated to synthesize oligonucleotides of relatively short lengths on the surface, nucleotide by nucleotide.[6]
  • Using inkjet technology, nucleotides are printed onto a surface drop by drop to form oligonucleotides[22]

cDNA microarray[edit]

Differential comparison in cDNA microarray

cDNA microarrays are often used for large-scale screening and expression studies.[22] In cDNA microarrays, mRNA from cells are collected and converted into cDNA by reverse transcription.[3] Subsequently, cDNA molecules (each corresponding to one gene) are immobilized as ~100 µm diameter spots on a membrane, glass, or silicon chip by metallic pins.[3][22] For detection, fluorescently-labelled single strand cDNA from cells hybridize to the molecules on the microarray and a differential comparison between a treated sample (labelled red, for example) and an untreated sample (labelled in another color such as green) is used for analysis.[3] Red dots mean that the corresponding gene was expressed at a higher level in the treated sample. Conversely, green dots mean that the corresponding gene was expressed at a higher level in the untreated sample. Yellow dots, as a result of the overlap between red and green dots, mean that the corresponding gene was expressed at relatively the same level in both samples, whereas dark spots indicate no or negligible expression in either sample.


Structure and Analysis of Affymetrix Arrays

Monnie McGee Department of Statistical Science Southern Methodist University

Other Sources of Variation

  • Systematic

Amount of RNA in biopsy extraction, Efficiencies of RNA extraction, reverse transcription, labeling, photodetection, GC content of probes Similar effect on many measurements Corrections can be estimated from data Calibration corrections

  • Stochastic

PCR yield, DNA quality, Spotting efficiency, spot size, Non-specific hybridization, Stray signal Too random to be explicitly accounted for in a model Noise components

Why Normalize ?

Ensure that differences in intensities are truly due to differential expression, not printing, hybridization, or scanning artifacts Must be done before an analysis which involves comparison of intensities within or between slides Procedures depend on the array technology

Analysis Tasks

Identify up- and down-regulated genes. Find groups of genes with similar expression profiles. Find groups of experiments (tissues) with similar expression profiles. Find genes that explain observed differences among tissues (feature selection)

The “Big Four” algorithms for correcting, normalizing, and summarizing probe level data for analysis of Gene Expression and identification of Over Expressed Genes

  • Microarray Analysis Suite 5.0 (MAS5 – Affymetrix, 2001, 2003)
  • Model Based Expression Index (MBEI – Li and Wong, 2001a,b)
  • Robust Multichip Analysis (RMA – Irizarry et. al., 2003)
  • Significance Analysis of Microarrays (SAM – Tusher, Tibshirani, and Chu, 2001)


Content of the CHP file Data

analysis output for a Single Array Analysis includes the following:

  • List of probes (transcripts)
  • Stat Pairs: Number of probe pairs to interrogate each gene
  • Stat Pairs Used: Number of pairs used to calculate signal
  • Signal: Raw Adjusted Intensity
  • Detection Call: presence or absence of transcript
  • Detection P-value: p-value used to determine presence or absence of transcript

Significance Analysis of Microarrays

Algorithm to determine “significantly” expressed genes

  • Original article mentions use of GeneChip Analysis Suite software for background correction, normalization and summarization.
  • Assigns a score to each gene on the basis of change in gene expression relative to the standard deviation of repeated measurements.
  • If the score exceeds a threshold, use permutations of repeated measurements to estimate the percentage of genes identified by chance.

More Information: tibs/SAM/

Microarray Software

  • Open Source

Bioconductor: Calculates RMA, MBEI, MAS5, dChip (MBEI only, Significance Analysis of Microarrays (SAM) Generalized Probe Model (GPM – Fan, et. al.2005,

  • Commerical

GCOS, MAS 5.0 (Affymetrix) S-Plus ArrayAnalyzer: Calculates RMA, MBEI, MAS5* Iobion GeneTraffic: RMA, MBEI, MAS5*


Protein Microarrays for Studies in Biomarkers and Post Translational Modification

Joshua LaBaer, M.D., Ph.D., Director, Virginia G. Piper Center for Personalized Diagnostics, The Biodesign Institute, Arizona State University

Self-assembling protein microarrays can be used to study protein-protein interactions, protein-drug interactions, search for enzyme substrates, and as tools to search for disease biomarkers. In particular, recent experiments have focused on using these protein microarrays to search for autoantibody responses in cancer patients. These experiments show promise in finding antibody responses that appear in only cancer patients. New methods using click chemistry-based reagents also allow the application of these arrays for discovering new substrates of post translational modification.

Dr. LaBaer was an early initiator and leader of the effort to build fully sequence-verified recombination-based clone sets for human genes and other model organisms now managed in an automated repository with more than 250,000 samples, which are openly shared with the scientific community. His laboratory has developed a number of methods to employ these clones, including HT protein expression and purification, and HT screens of ectopic protein expression in mammalian cells for relevant phenotypes. In addition, his group invented a novel protein microarray technology, Nucleic Acid Programmable Protein Array, which has been used widely for biomedical research, including the recent discovery of a panel of 28 autoantibody biomarkers that may aid the early diagnosis of breast cancer. Formerly founder and director of the Harvard Institute of Proteomics, LaBaer was recruited to ASU’s Biodesign Institute as the first Piper Chair in Personalized Medicine in 2009.

Protein Expression System Engineering is part of the Expression Stream which also includes Difficult to Express Proteins and Optimizing Protein Expression. Register for a Premium Package to maximize your savings and learning opportunities while gaining access to all the PEGS conferences!


From: Protein Expression <>

Date: Monday, January 11, 2016 at 3:10 PM

To: Aviva Lev-Ari <>

Subject: Learn How Protein Microarrays Can Find Antibody Response in Cancer Patients Only

Other related articles published in this Open Access Online Scientific Journal include the following:


Gene Editing by creation of a complement without transcription error

Curator: Larry H. Bernstein, MD, FCAP


UPDATED – Medical Interpretation of the Genomics Frontier – CRISPR – Cas9:  Gene Editing Technology for New Therapeutics

Authors and Curators: Larry H Bernstein, MD, FCAP and Stephen J Williams, PhD and Curator: Aviva Lev-Ari, PhD, RN


DNA Structure and Oligonucleotides

Curator: Larry H Bernstein, MD, FCAP


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