Microarray blob-defect removal improves array analysis

MOTIVATION: New generation Affymetrix oligonucleotide microarrays often have blob-like image defects that will require investigators to either repeat their hybridization assays or analyze their data with the defects left in place. We investigated the effect of analyzing a spike-in experiment on Affymetrix ENCODE tiling arrays in the presence of simulated blobs covering between 1 and 9% of the array area. Using two different ChIP-chip tiling array analysis programs (Affymetrix tiling array software, TAS, and model-based analysis of tiling arrays, MAT), we found that even the smallest blob defects significantly decreased the sensitivity and increased the false discovery rate (FDR) of the spike-in target prediction. RESULTS: We introduced a new software tool, the microarray blob remover (MBR), which allows rapid visualization, detection and removal of various blob defects from the .CEL files of different types of Affymetrix microarrays. It is shown that using MBR significantly improves the sensitivity and FDR of a tiling array analysis compared to leaving the affected probes in the analysis. AVAILABILITY: The MBR software and the sample array .CEL files used in this article are available at: http://liulab.dfci.harvard.edu/Software/MBR/MBR.htm     

Error-pooling-based statistical methods for identifying novel temporal replication profiles of human chromosomes observed by DNA tiling arrays

Statistical analysis on tiling array data is extremely challenging due to the astronomically large number of sequence probes, high noise levels of individual probes and limited number of replicates in these data. To overcome these difficulties, we first developed statistical error estimation and weighted ANOVA modeling approaches to high-density tiling array data, especially the former based on an advanced error-pooling method to accurately obtain heterogeneous technical error of small-sample tiling array data. Based on these approaches, we analyzed the high-density tiling array data of the temporal replication patterns during cell-cycle S phase of synchronized HeLa cells on human chromosomes 21 and 22. We found many novel temporal replication patterns, identifying about 26% of over 1 million tiling array sequence probes with significant differential replication during the four 2-h time periods of S phase. Among these differentially replicated probes, 126941 sequence probes were matched to 417 known genes. The majority of these genes were found to be replicated within one or two consecutive time periods, while the others were replicated at two non-consecutive time periods. Also, coding regions found to be more differentially replicated in particular time periods than noncoding regions in the gene-poor chromosome 21 (25% differentially replicated among genic probes versus 18.6% among intergenic probes), while such a phenomenon was less prominent in gene-rich chromosome 22. A rigorous statistical testing for local proximity of differentially replicated genic and intergenic probes was performed to identify significant stretches of differentially replicated sequence regions. From this analysis, we found that adjacent genes were frequently replicated at different time periods, potentially implying the existence of quite dense replication origins. Evaluating the conditional probability significance of identified gene ontology terms on chromosomes 21 and 22, we detected some over-represented molecular functions and biological processes among these differentially replicated genes, such as the ones relevant to hydrolase, transferase and receptor-binding activities. Some of these results were confirmed showing >70% consistency with cDNA microarray data that were independently generated in parallel with the tiling arrays. Thus, our improved analysis approaches specifically designed for high-density tiling array data enabled us to reliably and sensitively identify many novel temporal replication patterns on human chromosomes.     

Optimized design and assessment of whole genome tiling arrays

MOTIVATION: Recent advances in microarray technologies have made it feasible to interrogate whole genomes with tiling arrays and this technique is rapidly becoming one of the most important high-throughput functional genomics assays. For large mammalian genomes, analyzing oligonucleotide tiling array data is complicated by the presence of non-unique sequences on the array, which increases the overall noise in the data and may lead to false positive results due to cross-hybridization. The ability to create custom microarrays using maskless array synthesis has led us to consider ways to optimize array design characteristics for improving data quality and analysis. We have identified a number of design parameters to be optimized including uniqueness of the probe sequences within the whole genome, melting temperature and self-hybridization potential. RESULTS: We introduce the uniqueness score, U, a novel quality measure for oligonucleotide probes and present a method to quickly compute it. We show that U is equivalent to the number of shortest unique substrings in the probe and describe an efficient greedy algorithm to design mammalian whole genome tiling arrays using probes that maximize U. Using the mouse genome, we demonstrate how several optimizations influence the tiling array design characteristics. With a sensible set of parameters, our designs cover 78% of the mouse genome including many regions previously considered 'untilable' due to the presence of repetitive sequence. Finally, we compare our whole genome tiling array designs with commercially available designs. AVAILABILITY: Source code is available under an open source license from http://www.ebi.ac.uk/~graef/arraydesign/.     

Efficient oligonucleotide probe selection for pan-genomic tiling arrays

Background  

Array comparative genomic hybridization is a fast and cost-effective method for detecting, genotyping, and comparing the genomic sequence of unknown bacterial isolates. This method, as with all microarray applications, requires adequate coverage of probes targeting the regions of interest. An unbiased tiling of probes across the entire length of the genome is the most flexible design approach. However, such a whole-genome tiling requires that the genome sequence is known in advance. For the accurate analysis of uncharacterized bacteria, an array must query a fully representative set of sequences from the species' pan-genome. Prior microarrays have included only a single strain per array or the conserved sequences of gene families. These arrays omit potentially important genes and sequence variants from the pan-genome.     

Global single-cell cDNA amplification to provide a template for representative high-density oligonucleotide microarray analysis

We describe here a protocol for the representative amplification of global mRNAs from typical single mammalian cells to provide a template for high-density oligonucleotide microarray analysis. A single cell is lysed in a tube without purification and first-strand cDNAs are synthesized using a poly(dT)-tailed primer. Unreacted primer is specifically eliminated by exonuclease treatment and second strands are generated with a second poly(dT)-tailed primer after poly(dA) tailing of the first-strand cDNAs. The cDNAs are split into four tubes, which are independently directionally amplified by PCR, and then recombined. The amplified products (approximately 100 ng) show superior representation and reproducibility of original gene expression, especially for genes expressed in more than 20 copies per cell, compared with those obtained by a conventional PCR protocol, and can effectively be used for quantitative PCR and EST analyses. The cDNAs are then subjected to another PCR amplification with primers bearing the T7 promoter sequence. The resultant cDNA products are gel purified, amplified by one final cycle and used for isothermal linear amplification by T7 RNA polymerase to synthesize cRNAs for microarray hybridization. This protocol yields cDNA templates sufficient for more than 80 microarray hybridizations from a single cell, and can be completed in 5-6 days.     

Properties of signal intensities observed with individual probes of GeneChip Rat Gene 1.0 ST Array, an affymetric microarray system

For proper evaluation of the results of microarray experiments, it is important to understand how the signal intensities of individual probes are determined. Our previous studies revealed that signal intensities of individual probes in the Agilent array system (code G4131F) are largely dependent upon the location of the probes in the mRNA. In the present study, we examined the properties of signal intensities of individual probes in an Affymetrix array system (GeneChip Rat Gene 1.0 ST Array), in which a random primer fused to the T7 promoter sequence is employed. Distinct from the Agilent array system, individual probes used in this Affymetrix array system did not show the probe-location effects, but gave relatively diverse signal intensities. However, the diversities of the signal intensities of these individual probes were not due to experimental error.     

Efficiency clustering for low-density microarrays and its application to QPCR

Background  

Pathway-targeted or low-density arrays are used more and more frequently in biomedical research, particularly those arrays that are based on quantitative real-time PCR. Typical QPCR arrays contain 96-1024 primer pairs or probes, and they bring with it the promise of being able to reliably measure differences in target levels without the need to establish absolute standard curves for each and every target. To achieve reliable quantification all primer pairs or array probes must perform with the same efficiency.     

勒氏笛鲷微卫星位点的筛选及特征分析

采用PCR法快速筛选勒氏笛鲷(Lutjanus russelli)基因组文库, 以获得(CA)_n微卫星位点。勒氏笛鲷基因组DNA经限制性内切酶HaeⅢ+ DraⅠ双酶切后, 连接T-载体克隆, 构建基因组文库。以通用引物M13+/-与重复序列引物(CA)15对基因组文库进行筛选, 二次筛选后得到121个可能含有微卫星位点的阳性克隆。进行序列测定, 共获得53个CA(n≥7)重复序列, 重复次数主要分布于7~15(80.77%)。在所得微卫星序列中, 重复单元除CA外, 还观察到单碱基、三碱基、四碱基、五碱基重复单元。根据侧翼序列设计48对引物, 通过优化PCR反应条件, 可获得清晰可重复的目的条带。研究旨在为勒氏笛鲷遗传多样性研究及遗传图谱的构建等奠定基础, 为勒氏笛鲷资源的合理开发利用提供参考。