olecular cytogenetic and cytopostgenomic analysis of the human genome
Authors:   Mental Health Research Center, Iourov Ivan Y. ,   Pirogov Russian National Research Medical University,   Russian Medical Academy of Continuous Postgraduate Education, Vorsanova Svetlana G. ,   Mental Health Research Center,   Pirogov Russian National Research Medical University, Kurinnaia Oksana S. ,   Mental Health Research Center,   Pirogov Russian National Research Medical University, Zelenova Maria A. ,   Mental Health Research Center,   Pirogov Russian National Research Medical University, Vasin Kirill S. ,   Mental Health Research Center,   Pirogov Russian National Research Medical University, Demidova Irina A. ,   Mental Health Research Center,   Pirogov Russian National Research Medical University, Kolotii Alexey D. ,   Mental Health Research Center,   Pirogov Russian National Research Medical University, Kravets Victor S. ,   Mental Health Research Center,   Pirogov Russian National Research Medical University, Iuditskaia Maria E. ,   Mental Health Research Center,   Pirogov Russian National Research Medical University, Iakushev Nikita S. ,   Mental Health Research Center,   Pirogov Russian National Research Medical University, Soloviev Ilia V. ,   Mental Health Research Center, Yurov Yuri B. ,   Mental Health Research Center,   Pirogov Russian National Research Medical University
Published: December 2022

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.