The reanalysis of existing GWAS data represents a powerful and cost-effective opportunity to gain insights into the genetics of complex diseases. By reanalyzing publicly available type 2 diabetes (T2D) genome-wide association studies (GWAS) data for 70,127 subjects, we identify seven novel associated regions, five driven by common variants (LYPLAL1, NEUROG3, CAMKK2, ABO, and GIP genes), one by a low-frequency (EHMT2), and one driven by a rare variant in chromosome Xq23, rs146662075, associated with a twofold increased risk for T2D in males. rs146662075 is located within an active enhancer associated with the expression of Angiotensin II Receptor type 2 gene (AGTR2), a modulator of insulin sensitivity, and exhibits allelic specific activity in muscle cells. Beyond providing insights into the genetics and pathophysiology of T2D, these results also underscore the value of reanalyzing publicly available data using novel genetic resources and analytical approaches.

SUMMARYIn today's Grids, files are usually managed by Grid data management systems that are superimposed on existing file and storage systems. In this paper, we analyze this predominant approach and argue that object-based file systems can be an alternative when adapted to the characteristics of a Grid environment. We describe how we are solving the challenge of extending the object-based storage architecture for the Grid in XtreemFS, an object-based file system for federated infrastructures.

In the Big Data era, both the academic community and industry agree that a crucial point to obtain the maximum benefits from the explosive data growth is integrating information from different sources, and also combining methodologies to analyze and process it. For this reason, sharing data so that third parties can build new applications or services based on it is nowadays a trend. Although most data sharing initiatives are based on public data, the ability to reuse data generated by private companies is starting to gain importance as some of them (such as Google, Twitter, BBC or New York Times) are providing access to part of their data. However, current solutions for sharing data with third parties are not fully convenient to either or both data owners and data consumers. Therefore we present dataClay, a distributed data store designed to share data with external players in a secure and flexible way based on the concepts of identity and encapsulation. We also prove that dataClay is comparable in terms of performance with trendy NoSQL technologies while providing extra functionality, and resolves impedance mismatch issues based on the Object Oriented paradigm for data representation.This work has been supported by the Spanish Government (grant SEV2015-0493 of the Severo Ochoa Program), by the Spanish Ministry of Science and Innovation (contract TIN2015-65316) and by Generalitat de Catalunya (contract 2014-SGR-1051). Special thanks go to Dr. Oscar Romero (Universitat Politècnica de Catalunya) for providing helpful feedback on the paper.Peer ReviewedPostprint (published version

A lease is a token which grants its owner exclusive access to a resource for a defined span of time. In order to be able to tolerate failures, leases need to be coordinated by distributed processes. We present FaTLease, an algorithm for faulttolerant lease negotiation in distributed systems. It is built on the Paxos algorithm for distributed consensus, but avoids Paxos' main performance bottleneck of requiring persistent state. This property makes our algorithm particularly useful for applications that can not dispense any disk bandwidth. Our experiments show that FaTLease scales up to tens of thousands of concurrent leases and can negotiate thousands of leases per second in both LAN and WAN environments.

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