Biology subjects

Penson, A. V.

Publications and source records attributed to Penson, A. V..

2 recordsLinked to original sources

bioRxiv2019

Nbs1 Mediates Assembly and Activity of the Mre11 complex

We derived a mouse model in which a mutant form of Nbs1 (Nbs1mid8) exhibits severely impaired binding to the Mre11-Rad50 core of the Mre11 complex. The Nbs1mid8 allele was expressed exclusively in hematopoietic lineages (in Nbs1-/mid8vav mice). Unlike Nbs1flox/floxvav mice, which are Nbs1 deficient in the bone marrow, Nbs1-/mid8vav mice were viable. Nbs1-/mid8vav hematopoiesis was profoundly defective, exhibiting reduced cellularity of thymus and bone marrow, and stage specific blockage of B cell development. Within six months, Nbs1-/mid8 mice developed highly penetrant T cell leukemias. Nbs1-/mid8vav leukemias recapitulated mutational features of human T-ALL, containing mutations in Notch1, Trp53, Bcl6, Bcor, and Ikzf1, suggesting that Nbs1mid8 mice may provide a venue to examine the relationship between the Mre11 complex and oncogene activation in the hematopoietic compartment. Genomic analysis of Nbs1-/mid8vav malignancies showed focal amplification of 9qA2, causing overexpression of MRE11 and CHK1. We propose that overexpression compensates for the meta-stable Mre11-Nbs1mid8 interaction, and that selection pressure for overexpression reflects the essential role of Nbs1 in promoting assembly and activity of the Mre11 complex.

cancer biology↗

bioRxiv2017

Enabling cross-study analysis of RNA-Sequencing data

Driven by the recent advances of next generation sequencing (NGS) technologies and an urgent need to decode complex human diseases, a multitude of large-scale studies were conducted recently that have resulted in an unprecedented volume of whole transcriptome sequencing (RNA-seq) data. While these data offer new opportunities to identify the mechanisms underlying disease, the comparison of data from different sources poses a great challenge, due to differences in sample and data processing. Here, we present a pipeline that processes and unifies RNA-seq data from different studies, which includes uniform realignment and gene expression quantification as well as batch effect removal. We find that uniform alignment and quantification is not sufficient when combining RNA-seq data from different sources and that the removal of other batch effects is essential to facilitate data comparison. We have processed data from the Genotype Tissue Expression project (GTEx) and The Cancer Genome Atlas (TCGA) and have successfully corrected for study-specific biases, enabling comparative analysis across studies. The normalized data are available for download via GitHub (at https://github.com/mskcc/RNAseqDB).

bioinformatics↗