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== Synthesis and Manufacturers ==
== 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 up to nearly 400,000 features.<ref>{{cite journal|last=Liu|first=XS|title=Getting started in tiling microarray analysis.|journal=PLoS computational biology|date=2007 Oct|volume=3|issue=10|pages=1842-4|pmid=17967045|accessdate=28 May 2011}}</ref>
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 up to nearly 400,000 features.<ref>{{cite journal|last=Liu|first=XS|title=Getting started in tiling microarray analysis.|journal=PLoS computational biology|date=2007 Oct|volume=3|issue=10|pages=1842-4|pmid=17967045|accessdate=28 May 2011}}</ref>
Three manufacturers of tiling arrays are Affymetrix, NimbleGen and Agilent. Their products vary in probe length and spacing.
Three manufacturers of tiling arrays are Affymetrix, NimbleGen and Agilent. Their products vary in probe length and spacing.


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[[Image:transcriptome fig 3.png|thumb|left|235px|Overview of transcriptome mapping procedure.]]
[[Image:transcriptome fig 3.png|thumb|left|235px|Overview of transcriptome mapping procedure.]]
=== Transcriptome mapping ===
=== 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 the missing of transcripts. The method of sequencing cDNA to find transcribed genes also runs into problems like not being able to detect rare RNA molecules, RNA that are not polyadenylated, and very short 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 allows detection of non-polyadenylated RNA and can produce a more precise picture of gene structure.<ref>{{cite journal|last=Bertone|first=P|coauthors=Gerstein, M, Snyder, M|title=Applications of DNA tiling arrays to experimental genome annotation and regulatory pathway discovery.|journal=Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology|date=2005|volume=13|issue=3|pages=259-74|pmid=15868420|accessdate=28 May 2011}}</ref> Earlier studies done on chromosome 21 and 22 showed the power of tiling arrays for identifying transcription units.<ref>{{cite journal|last=Cawley|first=S|coauthors=Bekiranov, S, Ng, HH, Kapranov, P, Sekinger, EA, Kampa, D, Piccolboni, A, Sementchenko, V, Cheng, J, Williams, AJ, Wheeler, R, Wong, B, Drenkow, J, Yamanaka, M, Patel, S, Brubaker, S, Tammana, H, Helt, G, Struhl, K, Gingeras, TR|title=Unbiased mapping of transcription factor binding sites along human chromosomes 21 and 22 points to widespread regulation of noncoding RNAs.|journal=Cell|date=2004 Feb 20|volume=116|issue=4|pages=499-509|pmid=14980218|accessdate=28 May 2011}}</ref><ref>P. Kapranov, et al.: Large-scale transcriptional activity in chromosome 21 and 22. Science (2002) 296:916-919</ref><ref>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</ref> The authors used 25-mer probes that were 35bp apart, spanning the entire chromosomes. Labeled targets were made from polyadenylated RNA. They found many more transcripts than predicted and 90% 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 transcripts were found than predicted by ESTs and other prediction tools.<ref>K. Yamada, et al.: Empirical analysis of transcriptional activity in the Arabidopsis genome. Science (2003) 302: 842 846</ref><ref>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</ref> 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.<ref>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</ref>
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 the missing of transcripts. The method of sequencing cDNA to find transcribed genes also runs into problems like not being able to detect rare RNA molecules, RNA that are not polyadenylated, and very short 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 allows detection of non-polyadenylated RNA and can produce a more precise picture of gene structure.<ref>{{cite journal|last=Bertone|first=P|coauthors=Gerstein, M, Snyder, M|title=Applications of DNA tiling arrays to experimental genome annotation and regulatory pathway discovery.|journal=Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology|date=2005|volume=13|issue=3|pages=259-74|pmid=15868420|accessdate=28 May 2011}}</ref> Earlier studies done on chromosome 21 and 22 showed the power of tiling arrays for identifying transcription units.<ref>{{cite journal|last=Cawley|first=S|coauthors=Bekiranov, S, Ng, HH, Kapranov, P, Sekinger, EA, Kampa, D, Piccolboni, A, Sementchenko, V, Cheng, J, Williams, AJ, Wheeler, R, Wong, B, Drenkow, J, Yamanaka, M, Patel, S, Brubaker, S, Tammana, H, Helt, G, Struhl, K, Gingeras, TR|title=Unbiased mapping of transcription factor binding sites along human chromosomes 21 and 22 points to widespread regulation of noncoding RNAs.|journal=Cell|date=2004 Feb 20|volume=116|issue=4|pages=499-509|pmid=14980218|accessdate=28 May 2011}}</ref><ref>{{cite journal|last=Kapranov|first=P|coauthors=Cawley, SE, Drenkow, J, Bekiranov, S, Strausberg, RL, Fodor, SP, Gingeras, TR|title=Large-scale transcriptional activity in chromosomes 21 and 22.|journal=Science (New York, N.Y.)|date=2002 May 3|volume=296|issue=5569|pages=916-9|pmid=11988577|accessdate=28 May 2011}}</ref><ref name="Kam04">{{cite journal|last=Kampa|first=D|coauthors=Cheng, J, Kapranov, P, Yamanaka, M, Brubaker, S, Cawley, S, Drenkow, J, Piccolboni, A, Bekiranov, S, Helt, G, Tammana, H, Gingeras, TR|title=Novel RNAs identified from an in-depth analysis of the transcriptome of human chromosomes 21 and 22.|journal=Genome research|date=2004 Mar|volume=14|issue=3|pages=331-42|pmid=14993201|accessdate=28 May 2011}}</ref> The authors used 25-mer probes that were 35bp apart, spanning the entire chromosomes. Labeled targets were made from polyadenylated RNA. They found many more transcripts than predicted and 90% 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 transcripts were found than predicted by ESTs and other prediction tools. <ref>{{cite journal|last=Yamada|first=K|coauthors=Lim, J, Dale, JM, Chen, H, Shinn, P, Palm, CJ, Southwick, AM, Wu, HC, Kim, C, Nguyen, M, Pham, P, Cheuk, R ''et al.''|title=Empirical analysis of transcriptional activity in the Arabidopsis genome.|journal=Science (New York, N.Y.)|date=2003 Oct 31|volume=302|issue=5646|pages=842-6|pmid=14593172|accessdate=28 May 2011}}</ref><ref>{{cite journal|last=Stolc|first=V|coauthors=Samanta, MP, Tongprasit, W, Sethi, H, Liang, S, Nelson, DC, Hegeman, A, Nelson, C, Rancour, D, Bednarek, S, Ulrich, EL, Zhao, Q, Wrobel, RL, Newman, CS, Fox, BG, Phillips GN, Jr, Markley, JL, Sussman, MR|title=Identification of transcribed sequences in Arabidopsis thaliana by using high-resolution genome tiling arrays.|journal=Proceedings of the National Academy of Sciences of the United States of America|date=2005 Mar 22|volume=102|issue=12|pages=4453-8|pmid=15755812|accessdate=28 May 2011}}</ref> 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.<ref name="Kam04" />


[[Image:ChIP fig 4.png|thumb|250px|Overview of MeDIP-chip procedure.]]
[[Image:ChIP fig 4.png|thumb|250px|Overview of MeDIP-chip procedure.]]

Revision as of 11:53, 28 May 2011

Comparison of methods for genomic coverage within tiling array applications.

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 contiguous regions 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, tiling 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 uses of tiling arrays are in transcriptome mapping, ChIP-chip, MeDIP-chip and DNase Chip studies and 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 up to nearly 400,000 features.[3] Three manufacturers of tiling arrays are Affymetrix, NimbleGen and Agilent. Their products vary in probe length and spacing.

Applications and types

Overview of ChIP-chip procedure.

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 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. This gives an unbiased analysis with high 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 a few mammalian species.[4]

Overview of transcriptome mapping procedure.

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 the missing of transcripts. The method of sequencing cDNA to find transcribed genes also runs into problems like not being able to detect rare RNA molecules, RNA that are not polyadenylated, and very short 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 allows detection of non-polyadenylated RNA and can produce a more precise picture of gene structure.[5] Earlier studies done on chromosome 21 and 22 showed the power of tiling arrays for identifying transcription units.[6][7][8] The authors used 25-mer probes that were 35bp apart, spanning the entire chromosomes. Labeled targets were made from polyadenylated RNA. They found many more transcripts than predicted and 90% 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 transcripts were found than predicted by ESTs and other prediction tools. [9][10] 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.[8]

Overview of MeDIP-chip procedure.

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”.

Overview of DNase-chip procedure.

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.[11] 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.

Comparative Genomic Hybridization (CGH)

Array-based CGH 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 tiling 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.[12]

Procedure

Workflow of tiling array 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.[13]

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 Agilent 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.[14]

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 sp., which found ten times more genes in the genome than traditional prediction tools, is that the results were confounded by “transcriptional noise”.[15] Furthermore there is an analysis challenge, as there is no clearly defined start or stop to your region of interest once identified on the array. Also, the arrays usually only give chromosome and position numbers, necessitating the need to sequence your region of interest (if required) as a separate step (although some modern arrays also give sequence information [citation needed]).

External links

References

  1. ^ Mockler, TC (2005 Jan). "Applications of DNA tiling arrays for whole-genome analysis". Genomics. 85 (1): 1–15. PMID 15607417. {{cite journal}}: |access-date= requires |url= (help); Check date values in: |date= (help); Unknown parameter |coauthors= ignored (|author= suggested) (help)
  2. ^ Yazaki, J (2007 Oct). "Mapping the genome landscape using tiling array technology". Current opinion in plant biology. 10 (5): 534–42. PMID 17703988. {{cite journal}}: |access-date= requires |url= (help); Check date values in: |date= (help); Unknown parameter |coauthors= ignored (|author= suggested) (help)
  3. ^ Liu, XS (2007 Oct). "Getting started in tiling microarray analysis". PLoS computational biology. 3 (10): 1842–4. PMID 17967045. {{cite journal}}: |access-date= requires |url= (help); Check date values in: |date= (help)
  4. ^ O'Geen, H (2007 Jun). "Genome-wide analysis of KAP1 binding suggests autoregulation of KRAB-ZNFs". PLoS genetics. 3 (6): e89. PMID 17542650. {{cite journal}}: |access-date= requires |url= (help); Check date values in: |date= (help); Unknown parameter |coauthors= ignored (|author= suggested) (help)
  5. ^ Bertone, P (2005). "Applications of DNA tiling arrays to experimental genome annotation and regulatory pathway discovery". Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology. 13 (3): 259–74. PMID 15868420. {{cite journal}}: |access-date= requires |url= (help); Unknown parameter |coauthors= ignored (|author= suggested) (help)
  6. ^ Cawley, S (2004 Feb 20). "Unbiased mapping of transcription factor binding sites along human chromosomes 21 and 22 points to widespread regulation of noncoding RNAs". Cell. 116 (4): 499–509. PMID 14980218. {{cite journal}}: |access-date= requires |url= (help); Check date values in: |date= (help); Unknown parameter |coauthors= ignored (|author= suggested) (help)
  7. ^ Kapranov, P (2002 May 3). "Large-scale transcriptional activity in chromosomes 21 and 22". Science (New York, N.Y.). 296 (5569): 916–9. PMID 11988577. {{cite journal}}: |access-date= requires |url= (help); Check date values in: |date= (help); Unknown parameter |coauthors= ignored (|author= suggested) (help)
  8. ^ a b Kampa, D (2004 Mar). "Novel RNAs identified from an in-depth analysis of the transcriptome of human chromosomes 21 and 22". Genome research. 14 (3): 331–42. PMID 14993201. {{cite journal}}: |access-date= requires |url= (help); Check date values in: |date= (help); Unknown parameter |coauthors= ignored (|author= suggested) (help)
  9. ^ Yamada, K (2003 Oct 31). "Empirical analysis of transcriptional activity in the Arabidopsis genome". Science (New York, N.Y.). 302 (5646): 842–6. PMID 14593172. {{cite journal}}: |access-date= requires |url= (help); Check date values in: |date= (help); Unknown parameter |coauthors= ignored (|author= suggested) (help)
  10. ^ Stolc, V (2005 Mar 22). "Identification of transcribed sequences in Arabidopsis thaliana by using high-resolution genome tiling arrays". Proceedings of the National Academy of Sciences of the United States of America. 102 (12): 4453–8. PMID 15755812. {{cite journal}}: |access-date= requires |url= (help); Check date values in: |date= (help); Unknown parameter |coauthors= ignored (|author= suggested) (help)
  11. ^ G. Crawford et al.: DNase-chip: A High Resolution Method to Identify DNaseI Hypersensitive Sites using Tiled Microarrays. Nature Methods (2006) 3:503-509
  12. ^ 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
  13. ^ Affymetrix website
  14. ^ Liu, S: Getting Started in Tiling Microarray Analysis. PLoS Computational Biology (2007) Volume 3, Issue 10, e183
  15. ^ Mockler,T, Ecker,J: Applications of DNA tiling arrays for whole-genome analysis. Genomics, 85 (2005) 1-15