No evidence that protein truncating variants in BRIP1 are associated with breast cancer risk: implications for gene panel testing.

BACKGROUND: BRCA1 interacting protein C-terminal helicase 1 (BRIP1) is one of the Fanconi Anaemia Complementation (FANC) group family of DNA repair proteins. Biallelic mutations in BRIP1 are responsible for FANC group J, and previous studies have also suggested that rare protein truncating variants in BRIP1 are associated with an increased risk of breast cancer. These studies have led to inclusion of BRIP1 on targeted sequencing panels for breast cancer risk prediction. METHODS: We evaluated a truncating variant, p.Arg798Ter (rs137852986), and 10 missense variants of BRIP1, in 48 144 cases and 43 607 controls of European origin, drawn from 41 studies participating in the Breast Cancer Association Consortium (BCAC). Additionally, we sequenced the coding regions of BRIP1 in 13 213 cases and 5242 controls from the UK, 1313 cases and 1123 controls from three population-based studies as part of the Breast Cancer Family Registry, and 1853 familial cases and 2001 controls from Australia. RESULTS: The rare truncating allele of rs137852986 was observed in 23 cases and 18 controls in Europeans in BCAC (OR 1.09, 95% CI 0.58 to 2.03, p=0.79). Truncating variants were found in the sequencing studies in 34 cases (0.21%) and 19 controls (0.23%) (combined OR 0.90, 95% CI 0.48 to 1.70, p=0.75). CONCLUSIONS: These results suggest that truncating variants in BRIP1, and in particular p.Arg798Ter, are not associated with a substantial increase in breast cancer risk. Such observations have important implications for the reporting of results from breast cancer screening panels.The COGS project is funded through a European Commission's Seventh Framework Programme grant (agreement number 223175 - HEALTH-F2-2009-223175). BCAC is funded by Cancer Research UK [C1287/A10118, C1287/A12014] and by the European Community´s Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH-F2-2009-223175) (COGS). Funding for the iCOGS infrastructure came from: the European Community's Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565), the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 16 CA148065 and 1U19 CA148112 - the GAME-ON initiative), the Department of Defense (W81XWH-10-1- 0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. This study made use of data generated by the Wellcome Trust Case Control consortium. Funding for the project was provided by the Wellcome Trust under award 076113. The results published here are in part based upon data generated by The Cancer Genome Atlas Project established by the National Cancer Institute and National Human Genome Research Institute.This is the author accepted manuscript. The final version is available from BMJ Group at http://dx.doi.org/10.1136/jmedgenet-2015-103529

FireWorks: A dynamic workflow system designed for high-throughput applications

This paper introduces FireWorks, a workflow software for running high-throughput calculation workflows atsupercomputing centers. FireWorks has been used to complete over 50 million CPU-hours worth of compu-tational chemistry and materials science calculations at the National Energy Research Supercomputing Center.It has been designed to serve the demanding high-throughput computing needs of these applications, with ex-tensive support for (i) concurrent execution through job packing, (ii) failure detection and correction, (iii) prov-enance and reporting for long-running projects, (iv) automated duplicate detection, and (v) dynamic workflows(i.e., modifying the workflow graph during runtime). We have found that these features are highly relevant toenabling modern data-driven and high-throughput science applications, and we discuss our implementationstrategy that rests on Python and NoSQL databases (MongoDB). Finally, we present performance data andlimitations of our approach along with planned future work. Copyright © 2015 John Wiley & Sons, Ltd

High-Throughput Computational Search for new Li-ion Battery Cathode Materials

This is the author accepted manuscript. The final version is available from Oxford University Press via the DOI in this record.Data accessibility Analyses reported in this article can be reproduced using the data provided by Marjamäki et al. (2018).Movement of individuals, or their genes, can influence eco-evolutionary processes in structured populations. We have limited understanding of the extent to which spatial behaviour varies among groups and individuals within populations. Here we use genetic pedigree reconstruction in a long-term study of European badgers (Meles meles) to characterise the extent of extra-group paternity, occurring as a consequence of breeding excursions, and to test hypothesised drivers of variation at multiple levels. We jointly estimate parentage and paternity distance (PD; distance between a cub’s natal and its father’s social group), and test whether population density and sex ratio influence mean annual PD. We also model cub level PD and extra-group paternity (EGP) to test for variation among social groups and parental individuals. Mean PD varied among years but was not explained by population density or sex ratio. However, cub-level analysis shows strong effects of social group, and parental identities, with some parental individuals being consistently more likely to produce cubs with extra-group partners. Group effects were partially explained by local sex ratio. There was also a strong negative correlation between maternal and paternal social group effects on cub paternity distance, indicating source-sink dynamics. Our analyses of paternity distance and EGP indicate variation in extra-group mating at multiple levels – among years, social groups and individuals. The latter in particular is a phenomenon seldom documented and suggests that gene flow among groups may be disproportionately mediated by a non-random subset of adults, emphasising the importance of the individual in driving eco-evolutionary dynamics.This work was supported by Natural Environment Research Council. P.H.M. was funded by a NERC industrial Case Studentship awarded to A.J.W., R.D. and R.A.M. (grant numbers NE/L009897/1, NE/M004546/1). (grant numbers NE/L009897/1, NE/M004546/1)