Effect of population stratification on the identification of significant single-nucleotide polymorphisms in genome-wide association studies

The North American Rheumatoid Arthritis Consortium case-control study collected case participants across the United States and control participants from New York. More than 500,000 single-nucleotide polymorphisms (SNPs) were genotyped in the sample of 2000 cases and controls. Careful adjustment for the confounding effect of population stratification must be conducted when analyzing these data; the variance inflation factor (VIF) without adjustment is 1.44. In the primary analyses of these data, a clustering algorithm in the program PLINK was used to reduce the VIF to 1.14, after which genomic control was used to control residual confounding. Here we use stratification scores to achieve a unified and coherent control for confounding. We used the first 10 principal components, calculated genome-wide using a set of 81,500 loci that had been selected to have low pair-wise linkage disequilibrium, as risk factors in a logistic model to calculate the stratification score. We then divided the data into five strata based on quantiles of the stratification score. The VIF of these stratified data is 1.04, indicating substantial control of stratification. However, after control for stratification, we find that there are no significant loci associated with rheumatoid arthritis outside of the HLA region. In particular, we find no evidence for association of TRAF1-C5 with rheumatoid arthritis

The GB4.0 Platform, an All-In-One Tool for CRISPR/Cas-Based Multiplex Genome Engineering in Plants

CRISPR/Cas ability to target several loci simultaneously (multiplexing) is a game-changer in plant breeding. Multiplexing not only accelerates trait pyramiding but also can unveil traits hidden by functional redundancy. Furthermore, multiplexing enhances dCas-based programmable gene expression and enables cascade-like gene regulation. However, the design and assembly of multiplex constructs comprising tandemly arrayed guide RNAs (gRNAs) requires scarless cloning and is still troublesome due to the presence of repetitive sequences, thus hampering a more widespread use. Here we present a comprehensive extension of the software-assisted cloning platform GoldenBraid (GB), in which, on top of its multigene cloning software, we integrate new tools for the Type IIS-based easy and rapid assembly of up to six tandemly-arrayed gRNAs with both Cas9 and Cas12a, using the gRNA-tRNA-spaced and the crRNA unspaced approaches, respectively. As stress tests for the new tools, we assembled and used for Agrobacterium-mediated stable transformation a 17 Cas9-gRNAs construct targeting a subset of the Squamosa-Promoter Binding Protein-Like (SPL) gene family in Nicotiana tabacum. The 14 selected genes are targets of miR156, thus potentially playing an important role in juvenile-to-adult and vegetative-to-reproductive phase transitions. With the 17 gRNAs construct we generated a collection of Cas9-free SPL edited T plants harboring up to 9 biallelic mutations and showing leaf juvenility and more branching. The functionality of GB-assembled dCas9 and dCas12a-based CRISPR/Cas activators and repressors using single and multiplexing gRNAs was validated using a Luciferase reporter with the Solanum lycopersicum Mtb promoter or the Agrobacterium tumefaciens nopaline synthase promoter in transient expression in Nicotiana benthamiana. With the incorporation of the new web-based tools and the accompanying collection of DNA parts, the GB4.0 genome edition turns an all-in-one open platform for plant genome engineering

DNA methylation epi-signature is associated with two molecularly and phenotypically distinct clinical subtypes of Phelan-McDermid syndrome

Background: Phelan-McDermid syndrome is characterized by a range of neurodevelopmental phenotypes with incomplete penetrance and variable expressivity. It is caused by a variable size and breakpoint microdeletions in the distal long arm of chromosome 22, referred to as 22q13.3 deletion syndrome, including the SHANK3 gene. Genetic defects in a growing number of neurodevelopmental genes have been shown to cause genome-wide disruptions in epigenomic profiles referred to as epi-signatures in affected individuals. Results: In this study we assessed genome-wide DNA methylation profiles in a cohort of 22 individuals with Phelan-McDermid syndrome, including 11 individuals with large (2 to 5.8 Mb) 22q13.3 deletions, 10 with small deletions (\u3c 1 Mb) or intragenic variants in SHANK3 and one mosaic case. We describe a novel genome-wide DNA methylation epi-signature in a subset of individuals with Phelan-McDermid syndrome. Conclusion: We identified the critical region including the BRD1 gene as responsible for the Phelan-McDermid syndrome epi-signature. Metabolomic profiles of individuals with the DNA methylation epi-signature showed significantly different metabolomic profiles indicating evidence of two molecularly and phenotypically distinct clinical subtypes of Phelan-McDermid syndrome

SHANK proteins limit integrin activation by directly interacting with Rap1 and R-Ras

SHANK3, a synaptic scaffold protein and actin regulator, is widely expressed outside of the central nervous system with predominantly unknown function. Solving the structure of the SHANK3 N-terminal region revealed that the SPN domain is an unexpected Ras-association domain with high affinity for GTP-bound Ras and Rap G-proteins. The role of Rap1 in integrin activation is well established but the mechanisms to antagonize it remain largely unknown. Here, we show that SHANK1 and SHANK3 act as integrin activation inhibitors by sequestering active Rap1 and R-Ras via the SPN domain and thus limiting their bioavailability at the plasma membrane. Consistently, SHANK3 silencing triggers increased plasma membrane Rap1 activity, cell spreading, migration and invasion. Autism-related mutations within the SHANK3 SPN domain (R12C and L68P) disrupt G-protein interaction and fail to counteract integrin activation along the Rap1-RIAM-talin axis in cancer cells and neurons. Altogether, we establish SHANKs as critical regulators of G-protein signalling and integrin-dependent processes

Exact solution of the Falicov-Kimball model with dynamical mean-field theory

The Falicov-Kimball model was introduced in 1969 as a statistical model for metal-insulator transitions; it includes itinerant and localized electrons that mutually interact with a local Coulomb interaction and is the simplest model of electron correlations. It can be solved exactly with dynamical mean-field theory in the limit of large spatial dimensions which provides an interesting benchmark for the physics of locally correlated systems. In this review, we develop the formalism for solving the Falicov-Kimball model from a path-integral perspective, and provide a number of expressions for single and two-particle properties. We examine many important theoretical results that show the absence of fermi-liquid features and provide a detailed description of the static and dynamic correlation functions and of transport properties. The parameter space is rich and one finds a variety of many-body features like metal-insulator transitions, classical valence fluctuating transitions, metamagnetic transitions, charge density wave order-disorder transitions, and phase separation. At the same time, a number of experimental systems have been discovered that show anomalies related to Falicov-Kimball physics [including YbInCu4, EuNi2(Si[1-x]Gex)2, NiI2 and TaxN].Comment: 51 pages, 40 figures, submitted to Reviews of Modern Physic

Cured meat, vegetables, and bean-curd foods in relation to childhood acute leukemia risk: A population based case-control study

<p>Abstract</p> <p>Background</p> <p>Consumption of cured/smoked meat and fish leads to the formation of carcinogenic <it>N-</it>nitroso compounds in the acidic stomach. This study investigated whether consumed cured/smoked meat and fish, the major dietary resource for exposure to nitrites and nitrosamines, is associated with childhood acute leukemia.</p> <p>Methods</p> <p>A population-based case-control study of Han Chinese between 2 and 20 years old was conducted in southern Taiwan. 145 acute leukemia cases and 370 age- and sex-matched controls were recruited between 1997 and 2005. Dietary data were obtained from a questionnaire. Multiple logistic regression models were used in data analyses.</p> <p>Results</p> <p>Consumption of cured/smoked meat and fish more than once a week was associated with an increased risk of acute leukemia (OR = 1.74; 95% CI: 1.15–2.64). Conversely, higher intake of vegetables (OR = 0.55; 95% CI: 0.37–0.83) and bean-curd (OR = 0.55; 95% CI: 0.34–0.89) was associated with a reduced risk. No statistically significant association was observed between leukemia risk and the consumption of pickled vegetables, fruits, and tea.</p> <p>Conclusion</p> <p>Dietary exposure to cured/smoked meat and fish may be associated with leukemia risk through their contents of nitrites and nitrosamines among children and adolescents, and intake of vegetables and soy-bean curd may be protective.</p

The Medical Segmentation Decathlon

International challenges have become the de facto standard for comparative assessment of image analysis algorithms given a specific task. Segmentation is so far the most widely investigated medical image processing task, but the various segmentation challenges have typically been organized in isolation, such that algorithm development was driven by the need to tackle a single specific clinical problem. We hypothesized that a method capable of performing well on multiple tasks will generalize well to a previously unseen task and potentially outperform a custom-designed solution. To investigate the hypothesis, we organized the Medical Segmentation Decathlon (MSD) - a biomedical image analysis challenge, in which algorithms compete in a multitude of both tasks and modalities. The underlying data set was designed to explore the axis of difficulties typically encountered when dealing with medical images, such as small data sets, unbalanced labels, multi-site data and small objects. The MSD challenge confirmed that algorithms with a consistent good performance on a set of tasks preserved their good average performance on a different set of previously unseen tasks. Moreover, by monitoring the MSD winner for two years, we found that this algorithm continued generalizing well to a wide range of other clinical problems, further confirming our hypothesis. Three main conclusions can be drawn from this study: (1) state-of-the-art image segmentation algorithms are mature, accurate, and generalize well when retrained on unseen tasks; (2) consistent algorithmic performance across multiple tasks is a strong surrogate of algorithmic generalizability; (3) the training of accurate AI segmentation models is now commoditized to non AI experts