Genomic deletion and promoter methylation status of Hypermethylated in Cancer 1 (HIC1) in mantle cell lymphoma

Mantle cell lymphomas (MCL), characterized by the t(11;14)(q13;q32), frequently carry secondary genetic alterations such as deletions in chromosome 17p involving the TP53 locus. Given that the association between TP53-deletions and concurrent mutations of the remaining allele is weak and based on our recent report that the Hypermethylated in Cancer 1 (HIC1) gene, that is located telomeric to the TP53 gene, may be targeted by deletions in 17p in diffuse large B-cell lymphoma (DLBCL), we investigated whether HIC1 inactivations might also occur in MCL. Monoallelic deletions of the TP53 locus were detected in 18 out of 59 MCL (31%), while overexpression of p53 protein occurred in only 8 out of 18 of these MCL (44%). In TP53-deleted MCL, the HIC1 gene locus was co-deleted in 11 out of 18 cases (61%). However, neither TP53 nor HIC1 deletions did affect survival of MCL patients. In most analyzed cases, no hypermethylation of the HIC1 exon 1A promoter was observed (17 out of 20, 85%). However, in MCL cell lines without HIC1-hypermethylation, the mRNA expression levels of HIC1 were nevertheless significantly reduced, when compared to reactive lymph node specimens, pointing to the occurrence of mechanisms other than epigenetic or genetic events for the inactivation of HIC1 in this entity

Polysomal mRNA Association and Gene Expression in <i>Trypanosoma brucei</i>

Background: The contrasting physiological environments of Trypanosoma brucei procyclic (insect vector) and bloodstream (mammalian host) forms necessitates deployment of different molecular processes and, therefore, changes in protein expression. Transcriptional regulation is unusual in T. brucei because the arrangement of genes is polycistronic; however, genes which are transcribed together are subsequently cleaved into separate mRNAs by trans-splicing. Following pre-mRNA processing, the regulation of mature mRNA stability is a tightly controlled cellular process. While many stage-specific transcripts have been identified, previous studies using RNA-seq suggest that changes in overall transcript level do not necessarily reflect the abundance of the corresponding protein. Methods: To better understand the regulation of gene expression in T. brucei, we performed a bioinformatic analysis of RNA-seq on total, sub-polysomal, and polysomal mRNA samples. We further cross-referenced our dataset with a previously published proteomics dataset to identify new protein coding sequences. Results: Our analyses showed that several long non-coding RNAs are more abundant in the sub-polysome samples, which possibly implicates them in regulating cellular differentiation in T. brucei. We also improved the annotation of the T.brucei genome by identifying new putative protein coding transcripts that were confirmed by mass spectrometry data. Conclusions: Several long non-coding RNAs are more abundant in the sub-polysome cellular fractions and might pay a role in the regulation of gene expression. We hope that these data will be of wide general interest, as well as being of specific value to researchers studying gene regulation expression and life stage transitions in T. brucei