Scienziati crescono: Deciphering the Code for Retroviral Integration Target Site Selection of Santoni, Federico Andrea, Hartley, Oliver, Luban, and Jeremy

parco scientifico a Pula

Non si tratta di un abstract di un articolo divulgativo, ma del riassunto di uan ricerca sul DNA. Potrebbero anche non interessarci, perché non molto alfabetizzati in proposito, ma è giusto anche dare divulgazione al lavoro, che giovani scienziati che crescono, portano avanti con impegno e passione, se poi tra questi c’è un sassarese come Federico Andrea Santoni, che conosciamo e stimiamo ci fa davvero un piacere immenso. A tutti i nostri fervidi auguri di buona e fruttuosa ricerca.

(A. T.)

Abstract

Upon cell invasion, retroviruses generate a DNA copy of their RNA genome and integrate retroviral cDNA within host chromosomal DNA. Integration occurs throughout the host cell genome, but target site selection is not random. Each subgroup of retrovirus is distinguished from the others by attraction to particular features on chromosomes. Despite extensive efforts to identify host factors that interact with retrovirion components or chromosome features predictive of integration, little is known about how integration sites are selected. We attempted to identify markers predictive of retroviral integration by exploiting Precision-Recall methods for extracting information from highly skewed datasets to derive robust and discriminating measures of association. ChIPSeq datasets for more than 60 factors were compared with 14 retroviral integration datasets. When compared with MLV, PERV or XMRV integration sites, strong association was observed with STAT1, acetylation of H3 and H4 at several positions, and methylation of H2AZ, H3K4, and K9. By combining peaks from ChIPSeq datasets, a supermarker was identified that localized within 2 kB of 75\\% of MLV proviruses and detected differences in integration preferences among different cell types. The supermarker predicted the likelihood of integration within specific chromosomal regions in a cell-type specific manner, yielding probabilities for integration into proto-oncogene LMO2 identical to experimentally determined values. The supermarker thus identifies chromosomal features highly favored for retroviral integration, provides clues to the mechanism by which retrovirus integration sites are selected, and offers a tool for predicting cell-type specific proto-oncogene activation by retroviruses.

Reference and download information

Santoni, Federico Andrea, Hartley, Oliver, Luban, and Jeremy. Deciphering the Code for Retroviral Integration Target Site Selection. Technical Report 10/100. CRS4, Center for Advanced Studies, Research and Development in Sardinia. Cagliari, Italy, nov 2010.

Bibtex citation record

@TechReport{Santoni:2010:DCRb,

author = {Santoni and Federico Andrea and Hartley and Oliver and Luban and Jeremy},

title = {Deciphering the Code for Retroviral Integration Target Site Selection},

institution = {CRS4, Center for Advanced Studies, Research and Development in Sardinia},

number = {10/100},

address = {Cagliari, Italy},

month = {nov},

year = {2010},

abstract = {Upon cell invasion, retroviruses generate a DNA copy of their RNA genome and integrate retroviral cDNA within host chromosomal DNA. Integration occurs throughout the host cell genome, but target site selection is not random. Each subgroup of retrovirus is distinguished from the others by attraction to particular features on chromosomes. Despite extensive efforts to identify host factors that interact with retrovirion components or chromosome features predictive of integration, little is known about how integration sites are selected. We attempted to identify markers predictive of retroviral integration by exploiting Precision-Recall methods for extracting information from highly skewed datasets to derive robust and discriminating measures of association. ChIPSeq datasets for more than 60 factors were compared with 14 retroviral integration datasets. When compared with MLV, PERV or XMRV integration sites, strong association was observed with STAT1, acetylation of H3 and H4 at several positions, and methylation of H2AZ, H3K4, and K9. By combining peaks from ChIPSeq datasets, a supermarker was identified that localized within 2 kB of 75\\% of MLV proviruses and detected differences in integration preferences among different cell types. The supermarker predicted the likelihood of integration within specific chromosomal regions in a cell-type specific manner, yielding probabilities for integration into proto-oncogene LMO2 identical to experimentally determined values. The supermarker thus identifies chromosomal features highly favored for retroviral integration, provides clues to the mechanism by which retrovirus integration sites are selected, and offers a tool for predicting cell-type specific proto-oncogene activation by retroviruses.},

url = {http://dx.doi.org/10.1371/journal.pcbi.1001008},

idxproject = {?},

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