Application and development trends in gene chip technology (Author: Shanghai Biochip National Engineering Research Center Tengxiao Kun, Xiao Huasheng)
As gene chip technology matures, it has been widely used in functional genomes, disease genomes, systems biology, and other fields.It has published tens of thousands of research papers, and the number of papers published every year shows a growing trend.
Chip preparation technology has greatly promoted the development of biochips, from laboratory manual or mechanical spot-made chips to industrialized in-situ synthesis preparation, from hundreds of dots to millions of high-density chips. Science has become a technology and is widely used by more and more researchers. Various laboratories continue to generate massive amounts of hybridization data. Researchers in the same field need to compare the data generated by different experimental platforms as high-throughput based on the principle of molecular hybridization. Technology, standardization, reliability, reproducibility of chip experiments, and whether chip results can be used as quantitative data have become issues of concern to all chip users. The Miami Principles and Microarray Quality Control series of studies answered these two questions.
The Miami Principle (Minimum Information About a Micro-Array Experiment, MIAME, minimum information amount) puts forward the concept of biochip standardization.The establishment of this principle enables the chip experiment data of laboratories around the world to be shared by all researchers. At the same time, the National Center for Bioinformatics (NCBI) and the European Institute of Bioinformatics (EBI) in the United Kingdom have also established GEO (http: //) and ArryExpress (http: //;) public databases to accept and store global According to the biochip data submitted by the researchers according to the Miami principle, researchers interested in a certain research can download the raw chip data of the relevant subject for analysis.
In 2006, the US FDA conducted a series of MAQC experiments (micro array quality control, MAQC) with multiple independent laboratories, aiming to study the quality control of the currently used chip platform. The 12 series of articles of this study were published in September 2006 On Nature Biotechnology, the rigorous experiment was used to analyze the current mainstream chip platform data quality, the correlation between chip data and quantitative PCR results, the method of chip data homogenization, and the reproducibility between different chip platforms. The data generated by the chip platform is comparable and reproducible. The systematic errors between the various chip platforms are much smaller than the differences between human operations and biological samples, which confirms the credibility of the chip data and eliminates the past. All kinds of suspicions about the chip data, it is clear that the chip based on the principle of hybridization can also be used as a quantitative method. It has promoted the wider application of biochip technology in the field of molecular biology.
Bioinformatics and statistics are indispensable tools for processing the massive data generated by gene chips. With the advancement of chip applications, new theories and new algorithms for chip data analysis have been continuously developed. These methods help biologists Quickly screen out differentially expressed genes from massive amounts of data. One chip experiment obtains the expression information of thousands of genes. It is difficult for any single analysis method to contain all the biological information contained in the data. Extracted, from the trend of bioinformatics research in recent years, the focus of current research has begun to shift to chip data storage, management, sharing and deep information mining, aiming to obtain more biological explanations from chip data instead of Stay on the simple screening of differentially expressed genes.
At present, the preparation of gene chips is developing in two main directions. First, high density, which is manifested by the increase in chip density. The density of chips synthesized in situ has reached tens of millions of probes per square centimeter. One chip It is enough to analyze the genomic information of a species. Second, microquantization, microarray detection of samples, the current detection limit of microarray can reach the level of nanogram total RNA, which is the expression of single cells in stem cell research, especially IPS stem cells Spectral research provides the possibility. On the other hand, micro-quantization also reflects the miniaturization of the chip matrix area, that is, the parallel hybridization of multiple matrices on the same chip carrier, greatly reducing the differences that may be brought by the system and batch, while Reduce experiment costs.
Microarray technology has changed the methods of biological research, making the rapid and high-throughput analysis of trace samples possible, from the rapid expansion of single gene research to whole-genome systems biology research. Microarray technology has helped biological research into the post-genomic era , Endless research results.
In 2001, the National Human Genome South Research Center Dr. Han Zeguang's research team used cDNA chips to screen expression profiles of 12393 genes and EST sequences in liver cancer and normal tissues. Among them, 2253 genes and EST were found to be differentially expressed in liver cancer , And analyzed the signaling pathways of these differential genes, and found that the WNT signaling pathway was abnormally expressed in the occurrence of liver cancer. In 2002, the research team of Dr. Zhang Xu of the Institute of Neurosciences, Chinese Academy of Sciences used the expression profile chip to damage peripheral nerves in rats The gene expression of the dorsal root ganglion of the model was studied. By screening the expression profiles of 7523 genes, a group of genes and potential drug targets related to nerve injury and pain were found, and the clinical use of Gabapentin treatment was explained. The molecular mechanism of pain. In the same year, the research team of the Netherlands Cancer Institute published by Nature used the expression profiling chip to carry out molecular typing of breast cancer patients' metastasis within 5 years. The results show that the difference in gene expression profiles can be used to predict tumors. Prognosis. This work becomes the use of expression profiling The classic case of molecular typing and prognosis research. The expression profile chip produced based on this research result in 2006 became the first expression profile chip approved by the FDA for clinical use, taking the first step of the chip from the laboratory to the clinic .
The International Rational Hapmap Project, launched in 2003, used five different high-throughput platforms for genotyping, of which the chip completed more than 50% of the workload. In 2005, Gunderson et al. Used The DNA chip detects SNP sites in the human genome. The results of the chip have a very good correlation with traditional PCR-based genotyping. Roch's Amplichip CYP450 test chip was approved by the FDA in 2005 for clinical use. In order to detect the polymorphic sites that determine the activity of cytochrome oxidase in patients and predict the level of drug metabolism in patients, this is also the first SNP chip to enter clinical examination. In 2007, Burton et al. Used microarray to detect 1000 cases of four There are more than 14,000 SNP loci in 1500 healthy people in patients with various diseases and the control group, and differences in genomic SNP loci in autoimmunity between patients and healthy people have been found.
In 2006, the National Human Genome South Research Center and the Biochip Shanghai National Engineering Research Center collaborated to use comparative genomic hybridization (aCGH) and expression profiling chips to jointly analyze the correlation between genomic copy number variation and gene expression in liver cancer samples. The study of the mechanism of liver cancer from the perspective of genomic structure variation provides a basis for research. In 2007 Carter et al. Reported the use of SNP chips to detect genome copy number variation and found that about 12% copy number variation exists in the human genome. It is far beyond the previous prediction of the diversity of the human genome. In 2008, Lee et al. Reported the use of comparative genomic hybridization (aCGH) to classify genetic diseases, and found a region in the chromosome 15q13.3 region of mental retardation patients. Missing, Nature Genetics published this result.
Small RNA or non-coding RNA (ncRNA) is an emerging research field. This type of small molecule RNA plays a role as a regulatory molecule in physiological processes and plays a very important role in development and human diseases, especially tumorigenesis. These small molecule nucleic acids are highly homologous, and the sequence difference is often one base, and the length is between 21 and 35 bases, which is a great challenge for chip detection, requiring that both low molecular weight target fragments can be detected, It can also distinguish one base difference. The development of chip technology has partially solved these problems. The use of chips to detect the expression profile of small molecule RNA has become another way of tumor typing. In breast cancer, lung cancer, prostate cancer and other disease molecules Very good results were obtained in typing and molecular marker search.
DNA modification and DNA-protein interaction are the ways in which cells regulate gene expression. In 2007, Meier et al. Used the ChIP-chip experimental method to detect the distribution of corresponding repair factors on DNA when DNA damage occurred. In the same year, Guenther et al. Humans have used ChIP-chip experiments to find that gene transcription initiation may not be specific. Most human genes, including coding genes that have been proven to be transcriptionally inactive, can initiate transcription. Cells modify the genome to control the extension of transcription. In order to achieve the purpose of regulating gene transcription. In 2008, Lupien et al. Used ChIP-chip and a series of experiments to confirm that epigenetic modification of the genome can regulate FoxA1, and change the structure of chromatin through FoxA1, thereby controlling the tissue specificity of the gene. expression.
The application of gene chips has accelerated the progress of life science research, and micro-quantization and parallel analysis have helped scientists discover useful information from massive data.
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