Paper Analysis: Microarray technology: beyond transcript profiling and genotype analysis

Microarray technology: beyond transcript profiling and genotype analysis
Nature Reviews Genetics 7, 200-210 (March 2006) | doi:10.1038/nrg1809

I have spent nearly three days reading this review on microarray. It is partly because this paper involves too many new concepts for me to digest, partly because, I have to admit, I have wasted too much time on BBS, films and music ^_^. Even until now I still cannot declare to absorb all materials in this paper, but i think it is better to take some notes here for it may urge me to concentrate on research.

This paper describe the following microarray development

Process	Status*
*From most to least developed: mature, in progress, under development, early stages, pilot phase, idea. CGH, comparative genomic hybridization; ChIP-on-chip, on-chip chromatin immunoprecipitation.
Transcriptional profiling	Mature, but still to be improved
Genotyping	Mature, but still to be improved
Splice-variant analysis	In progress
Identification of unknown exons	Early stages
DNA-structure analysis	Pilot phase
ChIP-on-chip	In progress
Protein binding	Under development
Protein–RNA interaction	Idea
Chip-based CGH	In progress
Epigenetic studies	Under development
DNA mapping	Mature
Resequencing	In progress
Large-scale sequencing	Under development
Gene/genome synthesis	Early stages
RNA/RNAi synthesis	Pilot phase
Protein–DNA interaction	Under development
On-chip translation	Under development
Universal microarray	Under development

He thoughts transcriptional profiling is relative in technique but the data analysis and interpretation. Some organization are take effect in this path, such as Microarray Gene Expression Data (MGED) Society, Gene Ontology Consortium and Bioconductor.

Expanding RNA studies the transcried RNA profile is a mixture of pre-mRNA, various form of alternative spliced mature mRNA, non-coding RNA and regualatory RNA. If we think about the effect of alternative splicing, it is possible that we may ignorant other forms and exons in the genome sequence which is not seen in our experiement samples. Then how to know other exons and what condition they are retained in mature mRNA, we can built an array consisting of oligonucleotide representing all known exons from genome annotation analysis. This array can then be used for the above condition.

Another question arising is that how can we find exons that escape the notice of genome annotation analysis. "One option is to synthesize oligonucleotides that correspond to the sequences at the exon–intron boundaries with their 5' ends attached to the chip surface "

Another approach is the entire genome microarray (tiling path), but the fragment is rather long which may miss some active sites of interest.

ChIP-on-chip on-chip chromatin immunoprecipitation. But, how this technique get high throughput if only one kind of protein can be precipitated due to the specificity of antibody binding? Needs more reading to understand this technique.

The author also predicted that " all analyses that are carried out with DNA are feasible at the level of RNA also."

comparative genomic hybridization (CGH), a method that is used to analyse variations in DNA copy number

The following part of this paper describes on demand sythesis based on microfluidic microarray, such as probe production (parallel production of large amount of different of oligomers), gene synthesis, RNAi production and protein in situ synthesis. Finally he introduced universal microarray platform based on L-DNA with great enthusiasm.

Conclusions:
1. To some extent, microarray technique means a new data-driven method e.g placing data production before intellectual concepts. This method is different from traditional hypothesis driven research in biology but is successful in physics.
2. The global view obtained by microarray approaches might lead researchers to appreciate more complexity of biological systems.
3. Experimental multiplexing by analysing different processes on a single system platform will become important. The in vitro systems biology will emerge competing (or complementing) in silico systems biology.

Here is a list of notable research project about microarray analysis http://filtr.blogspot.com/2007/02/research-projects-on-microarray.html

Xianghong Zhou's Papers

If you know the enemy and know yourself, you need not fear the result ofa hundred battles.

--Sun Tze, the Art of War

Comments on Zhou's papers:
1. Gene Aging Nexus: A Web Database and Data Mining Platform for Microarray Data on Aging
keywords:
meta-analysis: by first extracting expression patterns form individual microarray datasets and then identifying recurrent signals, these approaches may enhance signal-noise separation.
differential expression analysis:
co-expression analysis: Zhou proposed a new method to mine regulatory modules in previous papers Mining dense subgraphs across massive biological networks for functional discovery.
no major biological breakthrough.

2. Integrative missing value estimation for microarray data
Question Answered:
Due to the inherent noise and the limitation of experimental systems, a microarray dataset on average has more than 5% missing values, affecting more than 60% of the genes. Such missing values made some subsequent analysis methods inapplicable or greatly decrease their performance. Thus the question of missing value estimation.

Basic Idea:
How to choose neighboring genes when not enough information is available in internal microarray dataset. Intuitively, if a set of genes frequently show expression similarity to the target gene over multiple data sets, they constitute a robust neighborhood which tend to show expression co-variations with the target gene.

other concepts:
LLS Local Least Square
Bayesian principle component analysis
singular value decomposition
support vector machines