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Tiling array

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Introduction

Tiling Arrays are a subtype of microarray chips. They function on a similar principle to traditional microarrays in that labeled target molecules are hybridized to unlabeled probes fixed on to a solid surface. Tiling arrays differ in the nature of the probes. Short fragments are designed to cover the entire genome or contigs of the genome. Depending on the probe lengths and spacing different degrees of resolution can be achieved. Number of features on a single array can range from 10,000 to greater than 6,000,000, with each feature containing millions of copies of one probe[1]. Traditional DNA microarrays designed to look at gene expression use a few probes for each known or predicted gene. In contrast, tilling arrays can produce an unbiased look at gene expression because previously unidentified genes can still be incorporated. On top of individual gene expression analysis, other tiling arrays can be used in transcriptome mapping, ChIP-chip, MeDIP-chip and DNase Chip studies, Array CGH among others[2]. Tiling arrays are quickly becoming one of the most powerful tools in genome-wide investigations.


Synthesis and Manufacturers

There are two main ways of synthesizing tiling arrays, the first is photolithographic manufacturing and the second is mechanically spotting or printing. The first method involves in situ synthesis where probes, approximately 25bp, are built on the surface of the chip. These arrays can hold up to 6 million discrete features, each of which contains millions of copies of one probe. The other way of synthesizing tiling array chips is via mechanically printing probes onto the chip. This is done by using automated machines with pins that place the previously synthesized probes onto the surface. Due to the size restriction of the pins, these chips can hold between 10,000 and 30,000 features[3]. Three manufacturers of tiling arrays are Affymetrix, NimbleGen and Agilent. Their products vary in probe length and spacing.


Applications and types

ChIP-chip

ChIP-chip is one of the most popular usages of tiling arrays. Chromatin immunoprecipitation is the technique whereby binding sites of proteins can be identified. A genome-wide variation of this is known as ChIP-on-chip. Proteins that bind to chromatin are cross-linked in vivo, usually via fixation with formaldehyde. The chromatin is then fragmented and exposed to antibodies specific to the protein of interest. These complexes are then precipitated. The DNA is then isolated and purified. With traditional DNA microarrays, the immunoprecipitated DNA is hybridized to the chip, which contains probes, designed to cover regions representative of the genome. However, with tiling arrays, overlapping probes or probes in very close proximity can be used and therefore, giving an unbiased analysis with higher resolution. Besides these advantages, tiling arrays show high reproducibility, and with overlapping probes spanning large segments of the genome, tiling arrays can still interrogate protein binding sites, which harbor repeats. ChIP-chip experiments have been done to identify binding sites of transcription factors across the genome in yeast, drosophila and mammalian cells[4][5].

Transcriptome mapping

Another popular use of tiling arrays is in finding expressed genes. Traditional methods of gene prediction for annotation of genomic sequences have had several problems when used to map the transcriptome, such as not producing an accurate structure of the genes and also miss transcripts. The method of sequencing cDNA to find transcribed genes also run into problems like not being able to detect rare RNA molecules, RNA that are not polyadenylated, and would not detect genes that are only active in response to signals or specific to a time frame. Tiling arrays can solve these issues in mapping the transcriptome. Due to the high resolution and sensitivity, even small and rare molecules can be detected. The overlapping nature of the probes, also allow detection of non-polyadenylated RNA and can produce a more precise picture of the gene structure[6][7]. Earlier studies done on chromosome 21 and 22 showed the power of tiling arrays for identifying transcription units[8][9][10]. The authors used 25-mer probes that were 35bp apart, spanning the entire chromosomes. Labeled targets were made from polyadenylated RNA. The results found many more genes than predicted and 90% of which were outside of annotated exons. Another study done in Arabidopsis used high-density oligonucleotide arrays that cover the entire genome. More than 10 times more genes were found than predicted by ESTs and other prediction tools[11][12]. Also found were novel transcripts in the centromeric regions where it was thought that no genes are actively expressed. Many noncoding and natural antisense RNA have also been identified using tiling arrays[13].

MeDIP-chip

Methyl-DNA immunoprecipitation followed by tiling array allows DNA methylation mapping and measurement across the genome. DNA is methylated on cytosine in CG di-nucleotides in many places in the genome. This modification is one of the best-understood inherited epigenetic changes and is shown to affect gene expression. Mapping these sites can add to the knowledge of expressed genes and also epigenetic regulation on a genome-wide level. Studies have been done, utilizing tiling arrays, to generate high-resolution methylation maps for the Arabidopsis genome to generate the first “methylome”.

DNase-chip

DNase chip is an application of tiling arrays to identify hypersensitive sites, which are segments of open chromatin that are more readily cleaved by DNaseI. DNaseI cleaving produces larger fragments of around 1.2kb in size. These hypersensitive sites have been shown to be an accurate way of predicting regulatory elements such as promoter regions, enhancers and silencers[14]. Historically, the method uses Southern blotting to find digested fragments; however, tiling arrays have been used in its place for applying the technique to a genome-wide scale.

Array CGH

Array based comparative genomic hybridization is a technique often used in diagnostics to compare differences between types of DNA, such as normal cells vs. cancer cells. There are two types of tilling arrays commonly used for array CGH, which are the whole genome and fine tiled. The whole genome approach would be useful in identifying copy number variations with high resolution. On the other hand, the fine tiled array CGH would produce ultrahigh resolution to find other abnormalities such as breakpoints[15].


Procedure

There are several different methods for conducting a tiling arraying. One protocol for analyzing gene expression involves first isolating total RNA. This is then purified of rRNA molecules. The RNA is copied into double stranded DNA, which is subsequently amplified and in vitro transcribed to cRNA. The product is split into triplicates to produce dsDNA, which is then fragmented and labeled. Finally, the samples are hybridized to the tiling array chip. The signals from the chip is scanned and interpreted by computers[16].


Various software and algorithms are available for data analysis and vary in benefits depending on the manufacturer of the array chip. For Affymetrix chips, the model-based analysis of tiling array (MAT) is the most effective peak-seeking algorithm. For NimbleGen chips, TAMAL is more suitable for locating binding sites. Alternative algorithms include MA2C and TileScope, which are less complicated to operate. The Joint binding deconvolution algorithm is commonly used for the Aglient chips. If sequence analysis of binding site or annotation of the genome is required then programs like MEME, Gibbs Motif Sampler, Cis-regulatory element annotation system and Galaxy are used[17].


Advantage and Disadvantage

The obvious advantages of tiling array are that they provide an unbiased tool to investigate protein binding, gene expression and gene structure on a genome-wide scope. They allow a new level of insight in studying the transcriptome and methylome.

However, there are also certain drawbacks. First and foremost is the issue of expense. Although the cost of purchasing tiling array kits have reduced in price in the last several years, at the moment, the price makes it impractical to actually use genome wide tiling arrays for larger genomes like mammalian. Another issue is to do with the ultra sensitive detection of this technology. For looking at gene expression, an argument against a study in Arabidopsis, which found ten times more genes in the genome than traditional prediction tools, is that the results were confounded by “transcriptional noise”[18].


External Links

http://www.affymetrix.com/index.affx http://www.nimblegen.com/ http://www.chem.agilent.com/Scripts/PCol.asp?lPage=494References


References

  1. ^ Mockler,T, Ecker,J: Applications of DNA tiling arrays for whole-genome analysis. Genomics, 85 (2005) 1-15
  2. ^ Yazaki, J, Gregory, B, Ecker, J: Mapping the genome landscape using tiling array technology. Current Opinion in Plant Biology, (2007) 10:534-542
  3. ^ Mockler,T, Ecker,J: Applications of DNA tiling arrays for whole-genome analysis. Genomics, 85 (2005) 1-15
  4. ^ O’geen, H, Squazzo, S, Iyengar, S, Blahnik, K, Rinn, J, Chang, H, Green, R, Farnham, P: Genome-Wide Analysis of KAP1 Binding Suggests Autoregulation of KRAB-ZNFs. PLoS Genetics (2007) 6:e89
  5. ^ Lander, E: Array of hope. Nature Genetics Supplement (1999) volume 21
  6. ^ Bertpme, P, Gerstein, M, Snyder, M: Applications of DNA tiling arrays to experimental genome annotation and regulatory pathway discover. Chromosome Research (2005) 13:259-274
  7. ^ Liu, S: Getting Started in Tiling Microarray Analysis. PLoS Computational Biology (2007) Volume 3, Issue 10, e183
  8. ^ S. Cawley, et al.: Unbiased Mapping of transcription factor binding sites along human chromosomes 21 and 22 points to widespread regulation of noncoding RNAs. Cell (2004) 116: 499-509
  9. ^ P. Kapranov, et al: Large-scale transcriptional activity in chromosome 21 and 22. Science (2002) 296:916-919
  10. ^ D. Kampa, et al.: Novel RNAs identified from an in-depth analysis of the transcriptome of human chromosomes 21 and 22. Genome Res. (20040 14:331-342
  11. ^ K. Yamada, et al: Empirical analysis of transcriptional activity in the Arabidopsis genome. Science (2003) 302: 842 – 846
  12. ^ V. Stolc et al.: Identification of transcribed sequences in Arabidopsis thaliana by using high-resolution genome tiling arrays. PNAS (2005) vol. 102, no.12: 4453-4458
  13. ^ D. Kampa, et al.: Novel RNAs identified from an in-depth analysis of the transcriptome of human chromosomes 21 and 22. Genome Res. (20040 14:331-342
  14. ^ G. Crawford et al.: DNase-chip: A High Resolution Method to Identify DNaseI Hypersensitive Sites using Tiled Microarrays. Nature Methods (2006) 3:503-509
  15. ^ M. Heidenblad et al.: Tiling resolution array CGH and high density expression profiling of urothelial carcinomas delineate genomic amplicons and candidate target genes specific for advanced tumors. BMC Medical Genomiocs (2008) 1:3
  16. ^ Affymetrix website
  17. ^ Liu, S: Getting Started in Tiling Microarray Analysis. PLoS Computational Biology (2007) Volume 3, Issue 10, e183
  18. ^ Mockler,T, Ecker,J: Applications of DNA tiling arrays for whole-genome analysis. Genomics, 85 (2005) 1-15
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