The EU self-surplus puzzle: an indication of VAT fraud?

The world runs a trade surplus with itself: the reported values of exports exceed the reported values of imports. This is logically impossible but a well-known empirical fact. Less well-known is the fact that, in recent years, the EU has a trade surplus with itself that amounts to more than 80% of the global surplus. In this paper, we show that this EU self-surplus is worth a striking 307 billion Euro in 2018, equaling 1.9% of the Union’s GDP, which persists both in goods and services trade accounts. We further examine discrepancies in goods and services trade accounts at the country and country pair level. These are strongest between neighboring countries and exist for members of the Euro Area as well as non-members. Around the 2004 Eastern Enlargement, the EU self-surplus quadrupled. Our estimations suggest that Cyprus, Ireland, Luxembourg, and Sweden are EU Members with the most inaccurate statistical regimes. We observe systematic biases which unlikely root in random measurement error. By contrast, we suspect that a large fraction of the EU’s self-surplus puzzle seems related to fraud in value added tax (VAT). VAT exemptions for exporters provide strong incentives for the over-declaration of true export values. The resulting loss in tax income could amount to as much as 64 billion Euro per year.

Genetic Genealogy Uncovers a Founder Deletion Mutation in the Cerebral Cavernous Malformations 2 Gene

Cerebral cavernous malformations (CCM) are vascular malformations consisting of collections of enlarged capillaries occurring in the brain or spinal cord. These vascular malformations can occur sporadically or susceptibility to develop these can be inherited as an autosomal dominant trait due to mutation in one of three genes. Over a decade ago, we described a 77.6 Kb germline deletion spanning exons 2-10 in the CCM2 gene found in multiple affected individuals from seemingly unrelated families. Segregation analysis using linked, microsatellite markers indicated that this deletion may have arisen at least twice independently. In the ensuing decades, many more CCM patients have been identified with this deletion. In this present study we examined 27 reportedly unrelated affected individuals with this deletion. To investigate the origin of the deletion at base pair level resolution, we sequenced approximately 10 Kb upstream and downstream from the recombination junction on the deleted allele. All patients showed the identical SNP haplotype across this combined 20 Kb interval. In parallel, genealogical records have traced 11 of these individuals to five separate pedigrees dating as far back as the 1600-1700’s. These haplotype and genealogical data suggest that these families and the remaining “unrelated” samples converge on a common ancestor due to a founder mutation occurring centuries ago on the North American continent. We also note that another gene, NACAD, is included in this deletion. Although patient self-reporting does not indicate an apparent phenotypic consequence for heterozygous deletion of NACAD, further investigation is warranted for these patients.

Joint disease-specificity at the regulatory base-pair level

Given the pleiotropic nature of coding sequences and that many loci exhibit multiple disease associations, it is within non-coding sequence that disease-specificity likely exists. Here, we focus on joint disorders, finding among replicated loci, that GDF5 exhibits over twenty distinct associations, and we identify causal variants for two of its strongest associations, hip dysplasia and knee osteoarthritis. By mapping regulatory regions in joint chondrocytes, we pinpoint two variants (rs4911178; rs6060369), on the same risk haplotype, which reside in anatomical site-specific enhancers. We show that both variants have clinical relevance, impacting disease by altering morphology. By modeling each variant in humanized mice, we observe joint-specific response, correlating with GDF5 expression. Thus, we uncouple separate regulatory variants on a common risk haplotype that cause joint-specific disease. By broadening our perspective, we finally find that patterns of modularity at GDF5 are also found at over three-quarters of loci with multiple GWAS disease associations.

A molecular view of DNA flexibility

DNA dynamics can only be understood by taking into account its complex mechanical behavior at different length scales. At the micrometer level, the mechanical properties of single DNA molecules have been well-characterized by polymer models and are commonly quantified by a persistence length of 50 nm (~150 bp). However, at the base pair level (~3.4 Å), the dynamics of DNA involves complex molecular mechanisms that are still being deciphered. Here, we review recent single-molecule experiments and molecular dynamics simulations that are providing novel insights into DNA mechanics from such a molecular perspective. We first discuss recent findings on sequence-dependent DNA mechanical properties, including sequences that resist mechanical stress and sequences that can accommodate strong deformations. We then comment on the intricate effects of cytosine methylation and DNA mismatches on DNA mechanics. Finally, we review recently reported differences in the mechanical properties of DNA and double-stranded RNA, the other double-helical carrier of genetic information. A thorough examination of the recent single-molecule literature permits establishing a set of general ‘rules’ that reasonably explain the mechanics of nucleic acids at the base pair level. These simple rules offer an improved description of certain biological systems and might serve as valuable guidelines for future design of DNA and RNA nanostructures.

Financial Integration and the Co-Movement of Economic Activity: Evidence from U.S. States

We analyze the effect of the geographic expansion of banks across U.S. states on the comovement of economic activity between states. Exploiting the removal of interstate banking restrictions to construct time-varying instrumental variables at the state-pair level, we find that bilateral banking integration increases output co-movement between states. The effect of financial integration depends on the nature of the idiosyncratic shocks faced by states and is stronger for more financially dependent industries. Finally, we show that integration (1) increases the similarity of bank lending fluctuations between states and (2) contributes to the transmission of deposit shocks across states.

unCOVERApp: an interactive graphical application for clinical assessment of sequence coverage at the base-pair level

Motivation Next-generation sequencing is increasingly adopted in the clinical practice largely thanks to concurrent advancements in bioinformatic tools for variant detection and annotation. However, the need to assess sequencing quality at the base-pair level still poses challenges for diagnostic accuracy. One of the most popular quality parameters is the percentage of targeted bases characterized by low depth of coverage (DoC). These regions potentially ‘hide’ clinically relevant variants, but no annotation is usually returned with them. However, visualizing low-DoC data with their potential functional and clinical consequences may be useful to prioritize inspection of specific regions before re-sequencing all coverage gaps or making assertions about completeness of the diagnostic test. To meet this need, we have developed unCOVERApp, an interactive application for graphical inspection and clinical annotation of low-DoC genomic regions containing genes. Results unCOVERApp interactive plots allow to display gene sequence coverage down to the base-pair level, and functional and clinical annotations of sites below a user-defined DoC threshold can be downloaded in a user-friendly spreadsheet format. Moreover, unCOVERApp provides a simple statistical framework to evaluate if DoC is sufficient for the detection of somatic variants. A maximum credible allele frequency calculator is also available allowing users to set allele frequency cut-offs based on assumptions about the genetic architecture of the disease. In conclusion, unCOVERApp is an original tool designed to identify sites of potential clinical interest that may be ‘hidden’ in diagnostic sequencing data. Availabilityand implementation unCOVERApp is a free application developed with Shiny packages and available in GitHub (https://github.com/Manuelaio/uncoverappLib). Supplementary information Supplementary data are available at Bioinformatics online.

unCOVERApp: an interactive graphical application for clinical assessment of sequence coverage at the base-pair level

MotivationNext Generation Sequencing (NGS) is increasingly adopted in the clinical practice largely thanks to concurrent advancements in bioinformatic tools for variant detection and annotation. Despite improvements in available approaches, the need to assess sequencing quality down to the base-pair level still poses challenges for diagnostic accuracy. One of the most popular quality parameters of diagnostic NGS is the percentage of targeted bases characterized by low depth of coverage (DoC). These regions potentially hide a clinically-relevant variant, but no annotation is usually returned for them.However, visualizing low-DoC data with their potential functional and clinical consequences may be useful to prioritize inspection of specific regions before re-sequencing all coverage gaps or making assertions about completeness of the diagnostic test.To meet this need we have developed unCOVERApp, an interactive application for graphical inspection and clinical annotation of low-DoC genomic regions containing genes.ResultsunCOVERApp is a suite of graphical and statistical tools to support clinical assessment of low-DoC regions. Its interactive plots allow to display gene sequence coverage down to the base-pair level, and functional and clinical annotations of sites below a user-defined DoC threshold can be downloaded in a user-friendly spreadsheet format. Moreover, unCOVERApp provides a simple statistical framework to evaluate if DoC is sufficient for the detection of somatic variants, where the usual 20x DoC threshold used for germline variants is not adequate. A maximum credible allele frequency calculator is also available allowing users to set allele frequency cut-offs based on assumptions about the genetic architecture of the disease instead of applying a general one (e.g. 5%). In conclusion, unCOVERApp is an original tool designed to identify sites of potential clinical interest that may be hidden in diagnostic sequencing data.AvailabilityunCOVERApp is a freely available application written in R and developed with Shiny packages and available in GitHub.

The Genetic Architecture of Kidney Disease

The kidney is subject to a wide range of abnormalities, many of which have a significant hereditable component. Next generation sequencing is increasingly bringing the genetic drivers of Mendelian disease into focus at the base pair level, whereas inexpensive genotyping arrays have surveyed hundreds of thousands of individuals to identify common variants that predispose to kidney dysfunction. In this first article in a CJASN series on kidney genomics, we review how both rare and common variants contribute to kidney disease, explore how evolution may influence the genetic variants that affect kidney function, consider how genetic information is and will be used in the clinic, and identify some of the most important future directions for kidney disease research. Forthcoming articles in the series will elaborate on many of these themes.

Self-limiting aggregation of phospholipid vesicles

Aggregation of lipid vesicles can be limited to the pair level and is reversible depending on the linker type.