Targeted Chromatin Capture (T2C): A novel high resolution high throughput method to detect genomic interactions and regulatory elements.

Background: Significant efforts have recently been put into the investigation of the spatial organization and the chromatin-interaction networks of genomes. Chromosome conformation capture (3C) technology and its derivatives are important tools used in this effort. However, many of these have limitations, such as being limited to one viewpoint, expensive with moderate to low resolution, and/or requiring a large sequencing effort. Techniques like Hi-C provide a genome-wide analysis. However, it requires massive sequencing effort with considerable costs. Here we describe a new technique termed Targeted Chromatin Capture (T2C), to interrogate large selected regions of the genome. T2C provides an unbiased view of the spatial organization of selected loci at superior resolution (single restriction fragment resolution, from 2 to 6 kbp) at much lower costs than Hi-C due to the lower sequencing effort. Results: We applied T2C on well-known model regions, the mouse β-globin locus and the human H19/IGF2 locus. In both cases we identified all known chromatin interactions. Furthermore, we compared the human H19/IGF2 locus data obtained from different chromatin conformation capturing methods with T2C data. We observed the same compartmentalization of the locus, but at a much higher resolution (single restriction fragments vs. the common 40 kbp bins) and higher coverage. Moreover, we compared the β-globin locus in two different biological samples (mouse primary erythroid cells and mouse fetal brain), where it is either actively transcribed or not, to identify possible transcriptional dependent interactions. We identified the known interactions in the β-globin locus and the same topological domains in both mouse primary erythroid cells and in mouse fetal brain with the latter having fewer interactions probably due to the inactivity of the locus. Furthermore, we show that interactions due to the important chromatin proteins, Ldb1 and Ctcf, in both tissues can be analyzed easily to reveal their role on transcriptional interactions and genome folding. Conclusions: T2C is an efficient, easy, and affordable with high (restriction fragment) resolution tool to address both genome compartmentalization and chromatin-interaction networks for specific genomic regions at high resolution for both clinical and non-clinical research

Constraints on the Nucleon Strange Form Factors at Q^2 ~ 0.1 GeV^2

We report the most precise measurement to date of a parity-violating asymmetry in elastic electron-proton scattering. The measurement was carried out with a beam energy of 3.03 GeV and a scattering angle =6 degrees, with the result A_PV = -1.14 +/- 0.24 (stat) +/- 0.06 (syst) parts per million. From this we extract, at Q^2 = 0.099 GeV^2, the strange form factor combination G_E^s + 0.080 G_M^s = 0.030 +/- 0.025 (stat) +/- 0.006 (syst) +/- 0.012 (FF) where the first two errors are experimental and the last error is due to the uncertainty in the neutron electromagnetic form factor. This result significantly improves current knowledge of G_E^s and G_M^s at Q^2 ~0.1 GeV^2. A consistent picture emerges when several measurements at about the same Q^2 value are combined: G_E^s is consistent with zero while G_M^s prefers positive values though G_E^s=G_M^s=0 is compatible with the data at 95% C.L.Comment: minor wording changes for clarity, updated references, dropped one figure to improve focu

Common variants near MC4R are associated with fat mass, weight and risk of obesity.

To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

A Newton-like Method based on Model Reduction Techniques for Implicit Numerical Methods

In this paper, we present a Newton-like method based on model reduction techniques, which can be used in implicit numerical methods for approximating the solution to ordinary differential equations. In each iteration, the Newton-like method solves a reduced order linear system in order to compute the Newton step. This reduced system is derived using a projection matrix, obtained using proper orthogonal decomposition, which is updated in each time step of the numerical method. We demonstrate that the method can be used together with Euler's implicit method to simulate CO2 injection into an oil reservoir, and we compare with using Newton's method. The Newton-like method achieves a speedup of between 39% and 84% for systems with between 4,800 and 52,800 state variables