Development of a next generation SNP genotyping array for wheat

High-throughput genotyping arrays have provided a cost-effective, reliable and interoperable system for genotyping hexaploid wheat and its relatives. Existing, highly cited arrays including our 35K Wheat Breeder's array and the Illumina 90K array were designed based on a limited amount of varietal sequence diversity and with imperfect knowledge of SNP positions. Recent progress in wheat sequencing has given us access to a vast pool of SNP diversity, whilst technological improvements have allowed us to fit significantly more probes onto a 384-well format Axiom array than previously possible. Here we describe a novel Axiom genotyping array, the ‘Triticum aestivum Next Generation’ array (TaNG), largely derived from whole genome skim sequencing of 204 elite wheat lines and 111 wheat landraces taken from the Watkins ‘Core Collection’. We used a novel haplotype optimization approach to select SNPs with the highest combined varietal discrimination and a design iteration step to test and replace SNPs which failed to convert to reliable markers. The final design with 43 372 SNPs contains a combination of haplotype-optimized novel SNPs and legacy cross-platform markers. We show that this design has an improved distribution of SNPs compared to previous arrays and can be used to generate genetic maps with a significantly higher number of distinct bins than our previous array. We also demonstrate the improved performance of TaNGv1.1 for Genome-wide association studies (GWAS) and its utility for Copy Number Variation (CNV) analysis. The array is commercially available with supporting marker annotations and initial genotyping results freely available

Port Sunlight's Star: Sophie Somers

Port Sunlight Village Trust Blog Pos

Data from: Stochastic character mapping, Bayesian model selection, and biosynthetic pathways shed new light on the evolution of habitat preference in cyanobacteria

Cyanobacteria are the only prokaryotes to have evolved oxygenic photosynthesis paving the way for complex life. Studying the evolution and ecological niche of cyanobacteria and their ancestors is crucial for understanding the intricate dynamics of biosphere evolution. These organisms frequently deal with environmental stressors such as salinity and drought, and they employ compatible solutes as a mechanism to cope with these challenges. Compatible solutes are small molecules that help maintain cellular osmotic balance in high-salinity environments, such as marine waters. Their production plays a crucial role in salt tolerance, which, in turn, influences habitat preference. Among the five known compatible solutes produced by cyanobacteria (sucrose, trehalose, glucosylglycerol, glucosylglycerate, and glycine betaine), their synthesis varies between individual strains. In this study, we work in a Bayesian stochastic mapping framework, integrating multiple sources of information about compatible solute biosynthesis in order to predict the ancestral habitat preference of Cyanobacteria. Through extensive model selection analyses and statistical tests for correlation, we identify glucosylglycerol and glucosylglycerate as the most significantly correlated with habitat preference, while trehalose exhibits the weakest correlation. Additionally, glucosylglycerol, glucosylglycerate, and glycine betaine show high loss/gain rate ratios, indicating their potential role in adaptability, while sucrose and trehalose are less likely to be lost due to their additional cellular functions. Contrary to previous findings, our analyses predict that the last common ancestor of Cyanobacteria (living at around 3180 Ma) had a 97% probability of a high salinity habitat preference and was likely able to synthesize glucosylglycerol and glucosylglycerate. Nevertheless, cyanobacteria likely colonized low-salinity environments shortly after their origin, with an 89% probability of the first cyanobacterium with low-salinity habitat preference arising prior to the Great Oxygenation Event (2460 Ma). Stochastic mapping analyses provide evidence of cyanobacteria inhabiting early marine habitats, aiding in the interpretation of the geological record. Our age estimate of ~2590 Ma for the divergence of two major cyanobacterial clades (Macro- and Microcyanobacteria) suggests that these were likely significant contributors to primary productivity in marine habitats in the lead-up to the Great Oxygenation Event, and thus played a pivotal role in triggering the sudden increase in atmospheric oxygen

NMR metabolomic modeling of age and lifespan:A multicohort analysis

Metabolomic age models have been proposed for the study of biological aging, however, they have not been widely validated. We aimed to assess the performance of newly developed and existing nuclear magnetic resonance spectroscopy (NMR) metabolomic age models for prediction of chronological age (CA), mortality, and age-related disease. Ninety-eight metabolic variables were measured in blood from nine UK and Finnish cohort studies (N ≈31,000 individuals, age range 24-86 years). We used nonlinear and penalized regression to model CA and time to all-cause mortality. We examined associations of four new and two previously published metabolomic age models, with aging risk factors and phenotypes. Within the UK Biobank (N ≈102,000), we tested prediction of CA, incident disease (cardiovascular disease (CVD), type-2 diabetes mellitus, cancer, dementia, and chronic obstructive pulmonary disease), and all-cause mortality. Seven-fold cross-validated Pearson's r between metabolomic age models and CA ranged between 0.47 and 0.65 in the training cohort set (mean absolute error: 8-9 years). Metabolomic age models, adjusted for CA, were associated with C-reactive protein, and inversely associated with glomerular filtration rate. Positively associated risk factors included obesity, diabetes, smoking, and physical inactivity. In UK Biobank, correlations of metabolomic age with CA were modest (r = 0.29-0.33), yet all metabolomic model scores predicted mortality (hazard ratios of 1.01 to 1.06/metabolomic age year) and CVD, after adjustment for CA. While metabolomic age models were only moderately associated with CA in an independent population, they provided additional prediction of morbidity and mortality over CA itself, suggesting their wider applicability.</p

"I Am Not Taking Sides as a Female At All":Co-Facilitation and Gendered Positioning in a Domestic Abuse Perpetrator Program

The facilitation of domestic abuse perpetrator programs (DAPPs) by mixed gender co-facilitation pairs brings different facilitator perspectives and enables the modeling of egalitarian and respectful male-female relationships. This study analyzed 22 video and audio recordings of community-based DAPP groups featuring male participants, and male and female facilitators. Using thematic analysis, we aimed to understand how facilitators engaged participants and whether the facilitator's gender affected this. We found an asymmetry in the positioning of the facilitators. Group participants challenged both facilitators, but especially the female facilitators. Facilitator strategies toward behavior change included softening direct challenges (female facilitators) and mobilizing the shared category of men (male facilitators). Implications from this study are for reflective practice in facilitator management and supervision specifically focused on gendered power dynamics. Skilled facilitation is key to behavior change and the gendered interplay within groups may be a crucial element in the reduction of interpersonal violence and abuse.</p

Data from Rogmann & Dubrovinsky 2024

Supplementary information for: 'A Raman spectroscopic study of CS_2 with paraffin up to 25 GPa' by E.-M. Rogmann and L.S. Dubrovinsk

A Bi-CMOS electronic photonic integrated circuit quantum light detector

Complimentary metal-oxide semiconductor (CMOS) integration of quantum technology provides a route to manufacture at volume, simplify assembly, reduce footprint, and increase performance. Quantum noise–limited homodyne detectors have applications across quantum technologies, and they comprise photonics and electronics. Here, we report a quantum noise–limited monolithic electronic-photonic integrated homodyne detector, with a footprint of 80 micrometers by 220 micrometers, fabricated in a 250-nanometer lithography bipolar CMOS process. We measure a 15.3-gigahertz 3-decibel bandwidth with a maximum shot noise clearance of 12 decibels and shot noise clearance out to 26.5 gigahertz, when measured with a 9–decibel-milliwatt power local oscillator. This performance is enabled by monolithic electronic-photonic integration, which goes below the capacitance limits of devices made up of separate integrated chips or discrete components. It exceeds the bandwidth of quantum detectors with macroscopic electronic interconnects, including wire and flip chip bonding. This demonstrates electronic-photonic integration enhancing quantum photonic device performance