人类基因组的分子细胞遗传学和细胞后基因组学分析

I. Iourov, S. Vorsanova, O. S. Kurinnaia, M. Zelenova, K. Vasin, I. Demidova, Alexey D. Kolotii, V. S. Kravets, Maria E. Iuditskaia, Nikita S. Iakushev, I. V. Soloviev, Y. Yurov
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引用次数: 1

摘要

尽管人类基因组学取得了成就,但全面的基因组分析,包括在(亚)染色体/细胞基因组水平上获取细胞间和个体间变异的知识,仍然是一项艰巨的任务。这主要是由于缺乏启发式算法来揭示(细胞)基因组和/或体细胞基因组变异和功能结果。然而,目前分子细胞遗传学和“细胞原位基因组学”的发展可能为这个问题提供解决方案。本研究的目的:提出一种启发式算法,用于人类基因组的分子细胞遗传学和细胞原位基因组学分析,以揭示遗传(脑/神经发育)疾病的机制。材料和方法:利用原始分子细胞遗传学技术处理的细胞遗传学和(细胞)基因组变异(染色体异常、染色体/基因组不稳定、拷贝数变异(CNV)等)数据,并通过原始生物信息学(细胞基因组学)方法进行处理,开发算法。对8556人进行了核型分析。必要时应用FISH分析(体细胞嵌合体/染色体不稳定的情况)。600例(约7%)进行了分子核型分析。结果:利用我们长期研究神经发育障碍中染色体和基因组变异/不稳定性的经验以及(细胞)基因组数据处理的原始发展,我们成功地提出了一种启发式算法,用于人类基因组的分子细胞遗传学和细胞原位基因组学分析,以揭示脑部疾病的机制。建立了算法的估计效率达到84%。通过对35年来应用细胞遗传学和细胞基因组学技术的动态分析,我们发现诊断效率从7%(仅通过核型诊断)提高到80%以上(通过分子细胞遗传学和细胞原位基因组学分析)。结论:在这里,我们提出了一种启发式算法,用于人类基因组的分子细胞遗传学和细胞原位基因组学分析,以揭示遗传疾病的机制。揭示染色体不稳定性机制的效率和能力使我们得出结论,该算法可能在基础和诊断基因组/细胞(后)基因组研究中具有高度竞争力。
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olecular cytogenetic and cytopostgenomic analysis of the human genome
Despite the achievements of human genomics, comprehensive genome analysis, including acquiring the knowledge about intercellular and interindividual variations at (sub)chromosomal/ cytogenomic level, remains a difficult task. This basically results from a lack of heuristic algorithms for uncovering (cyto)genomic and/or somatic genome variations and the functional outcomes. However, current developments in molecular cytogenetics and “cytopostgenomics” may offer a solution of the problem. The aim of the study: To present a heuristic algorithm for molecular cytogenetic and cytopostgenomic analysis of the human genome to uncover mechanisms of genetic (brain/neurodevelopmental) diseases. Materials and methods: Data on cytogenetic and (cyto)genomic variations (chromosome abnormalities, chromosome/genome instability, copy number variation (CNV) etc.) addressed by original molecular cytogenetic techniques and processed by original bioinformatic (cytopostgenomic) methods were used to develop the algorithm. Karyotyping was performed in 8556 individuals. FISH analysis was applied when required (cases of somatic mosaicism/ chromosome instability). Molecular karyotyping by SNP-array was performed in 600 (~7%) cases. Results: Using our long-term experience of studying chromosomal and genomic variations/instability in neurodevelopmental disorders as well as original developments in (cyto) genomic data processing, we managed to present a heuristic algorithm for molecular cytogenetic and cytopostgenomic analysis of the human genome to uncover mechanisms for brain diseases. Estimated efficiency of the algorithm was established to achieve 84%. Analyzing the dynamics of applying cytogenetic and cytogenomic techniques throughout ~35 years of our diagnostic research we found that the diagnostic efficiency had been increasing from ~7% (exclusive diagnosis by karyotyping) to more than 80% (molecular cytogenetic and cytopostgenomic analysis). Conclusion: Here, we propose a heuristic algorithm for molecular cytogenetic and cytopostgenomic analysis of the human genome to uncover mechanisms for genetic diseases. The efficiency and ability to uncover mechanisms of chromosome instability allows us to conclude that the algorithm may be highly competitive for basic and diagnostic genomic/cyto(post)genomic research.
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