engleski

Computational long range analyses of human pericentromeric regions

The aim of this study is to develop a model that would help enlighten in more details the general compositional and organizational principles of repetitive DNA in the eukaryotic genomes. The so called "haeven for repetitive sequences" is the centromeric region of the chromosome that represents the most rapidly evolving compartment of the eukaryotic genome. DNA structures involved in the centromeric functions have not been characterized yet. In human, the most prominent and most recently amplified centromeric sequences are those belonging to the new alpha satellite families. These DNA families are composed of 10-40% diverged ~171 bp monomers (basic units) tandemly reiterated within a higher order repeat (HORs) units. HORs themselves, are also tandemly repeated up to several thousand times with 95-99% identity between copies. Repeated HORs form chromosome-specific arrays 250-5000 kb long. From the available data that are rather poor and approximate, similar evolutionary trend in the large-scale organization of alpha satellite can be discerned when followed from lower primates to human and also from the edges of pericentromeric regions towards the centromere. Old alpha satellite families present in lower primats, as well as in regions peripheral to human centromere are generaly characterized by irregular monomeric organization, high interspersionwith other classes of tandem and interspersed sequences, appearance of satellite blocks in both - forward and inverted orientation and coexistence of the same sequences on different chromosomes of the complement. On the contrary, new families are characterized by regular higher order repeat organization, continuity, independent evolution and extensive individual variability. In this work, large scale organization of human chromosome 7 pericentromeric region was analysed using repeat finding strategy based on sequence relatedness.

Computational biology, satellite DNA, centromere, human chromosome 7, evolution, DNA mapping, pattern visualisation

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