Genomic structural variation is the variation in structure of an organism's chromosome. It consists of many kinds of variation in the genome of one species, and usually includes microscopic and submicroscopic types, such as deletions, duplications, copy-number variants, insertions, inversions and translocations. Originally, a structure variation affects a sequence length about 1kb to 3Mb, which is larger than SNPs and smaller than chromosome abnormality (though the definitions have some overlap). However, the operational range of structural variants has widened to include events > 50bp. The definition of structural variation does not imply anything about frequency or phenotypical effects. Many structural variants are associated with genetic diseases, however many are not. Recent research about SVs indicates that SVs are more difficult to detect than SNPs. Approximately 13% of the human genome is defined as structurally variant in the normal population, and there are at least 240 genes that exist as homozygous deletion polymorphisms in human populations, suggesting these genes are dispensable in humans. Rapidly accumulating evidence indicates that structural variations can comprise millions of nucleotides of heterogeneity within every genome, and are likely to make an important contribution to human diversity and disease susceptibility.
Microscopic means that it can be detected with optical microscopes, such as aneuploidies, marker chromosome, gross rearrangements and variation in chromosome size. The frequency in human population is thought to be underestimated due to the fact that some of these are not actually easy to identify. These structural abnormalities exist in 1 of every 375 live births by putative information.
Sub-microscopic structural variants are much harder to detect owing to their small size. The first study in 2004 that used DNA microarrays could detect tens of genetic loci that exhibited copy number variation, deletions and duplications, greater than 100 kilobases in the human genome.
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Bioinformatics (ˌbaɪ.oʊˌɪnfɚˈmætɪks) is an interdisciplinary field of science that develops methods and software tools for understanding biological data, especially when the data sets are large and complex. Bioinformatics uses biology, chemistry, physics, computer science, computer programming, information engineering, mathematics and statistics to analyze and interpret biological data. The subsequent process of analyzing and interpreting data is referred to as computational biology.
Explores personalized medicine, genetic variability, and drug response, emphasizing tailoring treatments based on individual genetic and metabolic profiles.
BackgroundAging in postmitotic tissues is associated with clonal expansion of somatic mitochondrial deletions, the origin of which is not well understood. Such deletions are often flanked by direct nucleotide repeats, but this alone does not fully explain ...
Contemporary genomic approaches allow us to seek answers to biological questions that were previously out of reach. Genome-wide association studies (GWAS) have identified numerous genetic polymorphisms associated with human diseases, providing new insight ...
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BackgroundLarge-scale datasets of protein structures and sequences are becoming ubiquitous in many domains of biological research. Experimental approaches and computational modelling methods are generating biological data at an unprecedented rate. The deta ...