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Genetics
Published in Cathy Laver-Bradbury, Margaret J.J. Thompson, Christopher Gale, Christine M. Hooper, Child and Adolescent Mental Health, 2021
More recently, agnostic approaches, such as array comparative genomic hybridisation (aCGH) or genotyping microarrays, have been used to identify structural variants across the whole genome. Genotyping microarrays can be used to identify single nucleotide polymorphisms. This technology allows millions of SNPs to be assayed simultaneously at relatively low cost. Next-generation sequencing (whole-genome or exome) is now available and can be used to decipher an individual’s genetic code at the level of single base pairs.
Mind–Body Medicine
Published in Aruna Bakhru, Nutrition and Integrative Medicine, 2018
Jacqueline Proszynski, Darshan H. Mehta
Genomics-based investigations of MBTs have revolutionized the understanding of their mechanistic pathways and effects on human physiology. The developing field of functional genomics unites genomics, epigenomics, transcriptomics, proteomics, and metabolomics to uncover molecular pathways and determinants involved in the changes brought about, in this context, by MBTs. The vast majority of functional genomic studies use methods in transcriptomics, such as assessing gene expression by partially or fully sequencing the transcriptome of peripheral white and red blood cells. Other commonly used genomic analyses involve microarray technologies that measure the expression levels of many genes simultaneously or to genotype multiple regions of a genome. Table 16.5 describes frequently used genomic biomarkers in MBT studies.
Two-Dimensional Microfluidic Bioarray for Nucleic Acid Analysis
Published in Iniewski Krzysztof, Integrated Microsystems, 2017
DNA microarray hybridization has been an important technique in genomic research. Because of their flexibility and low production cost, microarrays with low-density probes have been used in SNP detection as well as nucleic acid diagnostic applications. Recently, microfluidic technology was combined with the DNA microarray method through covering the spotted probe area with chambers or microchannels for sample hybridization. As summarized in this chapter, the microfluidic microarray method shows the advantages of less sample usage, fast reaction kinetics, as well as multiple sample capabilities for high-throughput analysis.
Genetic variations as molecular diagnostic factors for idiopathic male infertility: current knowledge and future perspectives
Published in Expert Review of Molecular Diagnostics, 2021
Mohammad Karimian, Leila Parvaresh, Mohaddeseh Behjati
Microarray technology that evaluates males regarding copy number variation, gene expression level, and SNPs, is a promising approach for identification of very sensitive and specific biomarkers. Comparative genomic hybridization is a method that is applied for assessment of relative DAN ratios between samples and could be applied for whole-genome evaluation using microarray-based method or array comparative genomic hybridization. In the case of factors related to male infertility, array comparative genomic hybridization has identified Y-chromosomal microdeletion and other copy number variations outside of the identified AZF regions [189]. The additional candidate genes related to infertility are identified using array comparative genomic hybridization, although their roles are not yet clarified [190]. SNP analysis-based microarray has also recognized numerous candidate genes and potential biomarkers related to male infertility. This technique could also be a suitable alternative for reassessment of represented polymorphisms in this article with male infertility on wider scales.
Genes in treatment: Polygenic risk scores for different psychopathologies, neuroticism, educational attainment and IQ and the outcome of two different exposure-based fear treatments
Published in The World Journal of Biological Psychiatry, 2021
André Wannemüller, Robert Kumsta, Hans-Peter Jöhren, Thalia C. Eley, Tobias Teismann, Dirk Moser, Christopher Rayner, Gerome Breen, Jonathan Coleman, Svenja Schaumburg, Simon E. Blackwell, Jürgen Margraf
DNA from most participants (n = 364) was extracted from blood, with the rest (n = 68) obtained from saliva samples by routine desalting methods. Saliva samples were taken from patients who refused to have blood drawn due to high levels of blood-injury-injection fear. In order to avoid that blood drawing would have an influence on fear ratings, completion of questionnaires and blood drawings took place on different days. Genotyping of the participants was performed using the Illumina PsychChip microarray (Illumina, USA), see (Rayner et al. 2019) for a detailed description. In brief, variants were excluded if they were missing in >1% of participants, if they had a minor allele frequency <.05, or if they deviated substantially from Hardy–Weinberg equilibrium (p < 10−5). Individuals were included only if they had genotype calls for <99% of variants, had concordant phenotypic and genotypic sex (X chromosome heterozygosity F statistic: males >.8 and females <.2), were unrelated to other individuals (identity by descent: IBD >.1875) and showed no evidence of contamination (pairwise IBD and genome-wide heterozygosity F statistic <3 SD from the cohort means).
Gut microbiota regulate tumor metastasis via circRNA/miRNA networks
Published in Gut Microbes, 2020
Zhuxian Zhu, Jianguo Huang, Xu Li, Jun Xing, Qiang Chen, Ruilin Liu, Feng Hua, Zhongmin Qiu, Yuanlin Song, Chunxue Bai, Yin-Yuan Mo, Ziqiang Zhang
In this study, we have used both microarray and next-generation sequencing (NGS) for gene profiling. While microarray technology was developed early days, NGS is a relatively new technology. Based on a comparative study,45 there is a high correlation between gene expression profiles generated by these two platforms. The advantages of microarray technology are high throughput, relatively quick, and sensitive at low cost. However, limitations for microarrays include a need for predesigned probes on the chip and thus it can only detect known genes. Other limitations associated with microarrays are cross-hybridization, nonspecific hybridization, and limited detection range of individual probes. On the other hand, NGS does not need predesigned probes, which would be able to identify new genes. In particular, NGS is better in detecting low abundance transcripts, differentiating biologically critical isoforms, and allowing the identification of genetic variants. Finally, NGS is capable of detecting a broader dynamic range than microarrays. Because of these features, NGS has become a predominant platform. That is why we adopted NGS for the experiments at the later stage of our study.