Comparative Genomics of Gossypium spp. through GBS and Candidate Genes – Delving into the Controlling Factors behind Photoperiodic Flowering

Cotton has been a world-wide economic staple in textiles and oil production. There has been a concerted effort for cotton improvement to increase yield and quality to compete with non-natural man-made fibers. Unfortunately, cultivated cotton has limited genetic diversity; therefore finding new marketable traits within cultivated cotton has reached a plateau. To alleviate this problem, traditional breeding programs have been attempting to incorporate practical traits from wild relatives into cultivated lines. This incorporation has presented a new problem: uncultivated cotton hampered by photoperiodism. Traditionally, due to differing floral times, wild and cultivated cotton species were unable to be bred together in many commercial production areas world-wide. This worldwide breeding problem has inhibited new trait incorporation. Before favorable traits from undomesticated cotton could be integrated into cultivated elite lines using marker-assisted selection breeding, the markers associated with photoperiod independence needed to be discovered. In order to increase information about this debilitating trait, we set out to identify informative markers associated with photoperiodism. This study was segmented into four areas. First, we reviewed the history of cotton to highlight current problems in production. Next, we explored cotton’s floral development through a study of floral transition candidate genes. The third area was an in-depth analysis of Phytochrome C (previously linked to photoperiod independence in other crops). In the final area of study, we used Genotype-By-Sequencing (GBS), in a segregating population, was used to determine photoperiod independence associated with single nucleotide polymorphisms (SNPs). In short, this research reported SNP differences in thirty-eight candidate gene homologs within the flowering time network, including photoreceptors, light dependent transcripts, circadian clock regulators, and floral integrators. Also, our research linked other discrete SNP differences, in addition to those contained within candidate genes, to photoperiodicity within cotton. In conclusion, the SNP markers that our study found may be used in future marker assisted selection (MAS) breeding schemas to incorporate desirable traits into elite lines without the introgression of photoperiod sensitivity

Duplication, divergence and persistence in the Phytochrome photoreceptor gene family of cottons (Gossypium spp.)

<p>Abstract</p> <p>Background</p> <p>Phytochromes are a family of red/far-red photoreceptors that regulate a number of important developmental traits in cotton (<it>Gossypium </it>spp.), including plant architecture, fiber development, and photoperiodic flowering. Little is known about the composition and evolution of the phytochrome gene family in diploid (<it>G. herbaceum</it>, <it>G. raimondii</it>) or allotetraploid (<it>G. hirsutum</it>, <it>G. barbadense</it>) cotton species. The objective of this study was to obtain a preliminary inventory and molecular-evolutionary characterization of the phytochrome gene family in cotton.</p> <p>Results</p> <p>We used comparative sequence resources to design low-degeneracy PCR primers that amplify genomic sequence tags (GSTs) for members of the <it>PHYA</it>, <it>PHYB/D</it>, <it>PHYC </it>and <it>PHYE </it>gene sub-families from A- and D-genome diploid and AD-genome allotetraploid <it>Gossypium </it>species. We identified two paralogous <it>PHYA </it>genes (designated <it>PHYA1 </it>and <it>PHYA2</it>) in diploid cottons, the result of a Malvaceae-specific <it>PHYA </it>gene duplication that occurred approximately 14 million years ago (MYA), before the divergence of the A- and D-genome ancestors. We identified a single gene copy of <it>PHYB</it>, <it>PHYC</it>, and <it>PHYE </it>in diploid cottons. The allotetraploid genomes have largely retained the complete gene complements inherited from both of the diploid genome ancestors, with at least four <it>PHYA </it>genes and two genes encoding <it>PHYB</it>, <it>PHYC </it>and <it>PHYE </it>in the AD-genomes. We did not identify a <it>PHYD </it>gene in any cotton genomes examined.</p> <p>Conclusions</p> <p>Detailed sequence analysis suggests that phytochrome genes retained after duplication by segmental duplication and allopolyploidy appear to be evolving independently under a birth-and-death-process with strong purifying selection. Our study provides a preliminary phytochrome gene inventory that is necessary and sufficient for further characterization of the biological functions of each of the cotton phytochrome genes, and for the development of 'candidate gene' markers that are potentially useful for cotton improvement via modern marker-assisted selection strategies.</p

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p&lt;0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5–5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p&lt;0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4–10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p&lt;0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32–4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP &gt;5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification

Time to Peak Glucose and Peak C-Peptide During the Progression to Type 1 Diabetes in the Diabetes Prevention Trial and TrialNet Cohorts

OBJECTIVE To assess the progression of type 1 diabetes using time to peak glucose or C-peptide during oral glucose tolerance tests (OGTTs) in autoantibody-positive relatives of people with type 1 diabetes. RESEARCH DESIGN AND METHODS We examined 2-h OGTTs of participants in the Diabetes Prevention Trial Type 1 (DPT-1) and TrialNet Pathway to Prevention (PTP) studies. We included 706 DPT-1 participants (mean ± SD age, 13.84 ± 9.53 years; BMI Z-score, 0.33 ± 1.07; 56.1% male) and 3,720 PTP participants (age, 16.01 ± 12.33 years; BMI Z-score, 0.66 ± 1.3; 49.7% male). Log-rank testing and Cox regression analyses with adjustments (age, sex, race, BMI Z-score, HOMA-insulin resistance, and peak glucose/C-peptide levels, respectively) were performed. RESULTS In each of DPT-1 and PTP, higher 5-year diabetes progression risk was seen in those with time to peak glucose >30 min and time to peak C-peptide >60 min (P < 0.001 for all groups), before and after adjustments. In models examining strength of association with diabetes development, associations were greater for time to peak C-peptide versus peak C-peptide value (DPT-1: χ2 = 25.76 vs. χ2 = 8.62; PTP: χ2 = 149.19 vs. χ2 = 79.98; all P < 0.001). Changes in the percentage of individuals with delayed glucose and/or C-peptide peaks were noted over time. CONCLUSIONS In two independent at-risk populations, we show that those with delayed OGTT peak times for glucose or C-peptide are at higher risk of diabetes development within 5 years, independent of peak levels. Moreover, time to peak C-peptide appears more predictive than the peak level, suggesting its potential use as a specific biomarker for diabetes progression

DUNE Offline Computing Conceptual Design Report

International audienceThis document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on $10^3$ pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

DUNE Offline Computing Conceptual Design Report

This document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment

DUNE Offline Computing Conceptual Design Report

This document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment

DUNE Offline Computing Conceptual Design Report

This document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment