M icroRNA expression and sequence analysis database ( http://konulab.fen.bilkent.edu.tr/mirna/ ) (mESAdb) is a regularly updated database for the multivariate analysis of sequences and expression of microRNAs from multiple taxa. mESAdb is modular and has a user interface implemented in PHP and JavaScript and coupled with statistical analysis and visualization packages written for the R language. The database primarily comprises mature microRNA sequences and their target data, along with selected human, mouse and zebrafish expression data sets. mESAdb analysis modules allow (i) mining of microRNA expression data sets for subsets of microRNAs selected manually or by motif; (ii) pair-wise multivariate analysis of expression data sets within and between taxa; and (iii) association of microRNA subsets with annotation databases, HUGE Navigator, KEGG and GO. The use of existing and customized R packages facilitates future addition of data sets and analysis tools. Furthermore, the ability to upload and analyze user-specified data sets makes mESAdb an interactive and expandable analysis tool for microRNA sequence and expression data.

A virtual database system is software that provides unified access to multiple information sources. If the sources are overlapping in their contents and independently maintained, then the likelihood of inconsistent answers is high. Solutions are often based on ranking (which sorts the different answers according to recurrence) and on fusion (which synthesizes a new value from the different alternatives according to a specific formula). In this paper we argue that both methods are flawed, and we offer alternative solutions that are based on knowledge about the performance of the source data; including features such as recentness, availability, accuracy and cost. These features are combined in a flexible utility function that expresses the overall value of a data item to the user. Utility allows us to (1) define meaningful ranking on the inconsistent set of answers, and offer the topranked answer as a preferred answer; (2) determine whether a fusion value is indeed better than the initial values, by calculating its utility and comparing it to the utilities of the initial values; and (3) discover the best fusion: the fusion formula that optimizes the utility. The advantages of such performance-based and utility-driven ranking and fusion are considerable.

Lamina-associated polypeptide 1 (LAP1) is a ubiquitously expressed inner nuclear membrane protein encoded by TOR1AIP1, and presents as two isoforms in humans, LAP1B and LAP1C. While loss of both isoforms results in a multisystemic progeroid-like syndrome, specific loss of LAP1B causes muscular dystrophy and cardiomyopathy, suggesting that LAP1B has a critical role in striated muscle. To gain more insight into the molecular pathophysiology underlying muscular dystrophy caused by LAP1B, we established a patient-derived fibroblast line that was transdifferentiated into myogenic cells using inducible MyoD expression. Compared to the controls, we observed strongly reduced myogenic differentiation and fusion potentials. Similar defects were observed in the C2C12 murine myoblasts carrying loss-of-function LAP1A/B mutations. Using RNA sequencing, we found that, despite MyoD overexpression and efficient cell cycle exit, transcriptional reprogramming of the LAP1B-deficient cells into the myogenic lineage is impaired with delayed activation of MYOG and muscle-specific genes. Gene set enrichment analyses suggested dysregulations of protein metabolism, extracellular matrix, and chromosome organization. Finally, we found that the LAP1B-deficient cells exhibit nuclear deformations, such as an increased number of micronuclei and altered morphometric parameters. This study uncovers the phenotypic and transcriptomic changes occurring during myoconversion of patient-derived LAP1B-deficient fibroblasts and provides a useful resource to gain insights into the mechanisms implicated in LAP1B-associated nuclear envelopathies.