Abstract
The decade passed after publishing the Human Genome first draft faced an enormous growth at the understanding of the genomic variation among different subjects, populations, and groups of patients. Single nucleotide polymorphisms (SNPs) and insertion or deletions (INDELs) have been increasingly recognized as a major type of genetic variations, with potential impact in protein activities and gene expression changes observed in complex genetic traits, like neuropsychiatric diseases. INDELs represent the second most common class of variations after SNPs, but there is still an important gap between the number of INDELs reported and the actual knowledge about the functional implications of such variations. There are approximately 10 million SNPs already reported, and the human populations are expected to collectively harbor at least 1.6–2.5 million INDELs. One of the major challenges is to find better platforms to screen for INDELs in a high throughput manner. The discordance in between the data from different studies might be explained by the diverse approaches employed to sequence the genomes with variable platforms. Short INDEL variations increased the scope of genetic markers in human genetic diseases, and various studies showed that common microdeletions and smaller INDELs might be highly associated with neuropsychiatric diseases such as schizophrenia, autism, mental retardation, and Alzheimer disease. The rapidly increasing amount of resequencing, genotyping, and personal genome data generated by large-scale genetic human projects require the development of integrated bioinformatics tools able to efficiently manage and analyze these genetic data. Our group is currently dealing with different approaches that might optimize sequencing and bioinformatics analyses of short INDELs to broaden our research capabilities of identifying those intriguing genetic variations. Hopefully, INDELs might become a new trend in association studies in neuropsychiatric genetics since so far the level of significant and positive associations with the standard SNPs reported presents limited predictive application.
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Acknowledgments
We are greatly indebted to José Luiz de Lima Filho and Henrique Castelletti. This study received financial support from the following Brazilian funding agencies and academic bureaus: LIKA-JIKA, PROPESQ-UFPE, CAPES, CNPq, and FACEPE.
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Lemos, R.R., Souza, M.B.R. & Oliveira, J.R.M. Exploring the Implications of INDELs in Neuropsychiatric Genetics: Challenges and Perspectives. J Mol Neurosci 47, 419–424 (2012). https://doi.org/10.1007/s12031-012-9714-8
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DOI: https://doi.org/10.1007/s12031-012-9714-8