Exploration des approches pangénomiques en amélioration variétale chez l'orge à six rangs dans l'Est du Canada

L’émergence du génotypage à haut débit et le développement de méthodes statistiques reliant le génotype au phénotype ont donné lieu à des approches pangénomiques, c’est-à-dire à l’échelle du génome entier, exploitables en sélection des plantes. Ces approches ont d’abord permis d’examiner l'association entre génotype et phénotype via des analyses d'association pangénomique (GWAS en anglais) afin d’identifier des loci de caractères quantitatifs (« quantitative trait loci », QTL) utiles en sélection assistée par marqueurs (SAM). Plus récemment, ces approches ont été explorées pour la prédiction génomique, laquelle vise, d’une part, à identifier les croisements les plus prometteurs (la sélection des croisements), et d’autre part, à identifier les individus les plus prometteurs au sein d’une descendance (la sélection génomique). Dans les deux cas, ces prédictions reposent sur un modèle statistique reliant le génotype et le phénotype au sein d’une population de référence. Ces approches pangénomiques offrent un grand potentiel, mais sont encore émergentes et de nombreuses questions se posent encore chez l’orge. Notre étude s’intéresse à certaines de ces interrogations et elle est divisée en quatre volets de recherche. Les approches pangénomiques nécessitent un nombre important de marqueurs moléculaires de type SNP (« single nucleotide polymorphism »). Ainsi dans le premier volet nous avons optimisé le protocole de génotypage par séquençage. Ce volet détaille tout le processus, de la préparation des librairies de séquençage jusqu’à la production d’un catalogue de SNP de haute qualité. À titre d’illustration, nous avons généré un catalogue de 30 000 SNP ayant une distribution chromosomique intéressante et une grande exactitude des génotypes. Dans le deuxième volet, en utilisant les données phénotypiques et génotypiques d’une population d’amélioration, nous avons comparé l’efficacité de trois approches GWAS (Uni-SNP, Multi-SNP et Haplotypique) pour détecter des QTL pour des caractères agronomiques importants. Les approches Multi-SNP et Haplotypique ont identifié plus de QTL que l’approche Uni-SNP. Le chevauchement entre les approches était limité, chaque approche découvrant un sous-ensemble différent de QTL.Dans le cadre du troisième volet, nous avons étudié l’impact de trois facteurs sur la justesse de la sélection génomique : (1) la performance de différents modèles statistiques (incluant ou non l’épistasie), (2) le nombre de marqueurs employés ainsi que (3) leur localisation (génique/nongénique). Le modèle qui intègre les effets additifs et épistatiques a montré les meilleures performances même si les différences entre les modèles étaient modestes. Jusqu’à 2K SNP, la justesse de la sélection génomique est restée comparable à celle basée sur le catalogue entier (35K), mais une diminution significative été observée à 500 SNP. Dans la plupart des cas, l’utilisation de SNP présents dans les régions géniques, voire codantes, n’a pas apporté une amélioration significative. Enfin, dans le quatrième volet, nous avons exploré la sélection génomique et la sélection des croisements. En premier lieu, nous avons constitué une population de référence pour bâtir un modèle de sélection génomique et prédire les performances de 350 descendants développés dans un programme d’amélioration. A partir des prédictions, 35 lignées ont été sélectionnées et testées au champ afin d’examiner la corrélation entre les performances prédites et observées. Les corrélations étaient satisfaisantes pour la résistance à la fusariose et le rendement. Ensuite, sur la base de ce modèle, nous avons prédit la moyenne (μ) ela variance génétique (Vg) de chacune des descendances simulées issues de tous les croisements possibles (30 000). La validation de ces prédictions a été réalisée rétrospectivement sur un sous-ensemble de croisements précédemment réalisés, en examinant leur persistance dans le processus de sélection. Tel qu’attendu les croisements les plus persistants (>F9) ont présenté des μ supérieures, mais des Vg modérées. Même si la résistance à la fusariose et le rendement sont corrélés défavorablement, nous avons pu identifier des croisements (650) où cette corrélation était rompue. Parmi ces croisements, certains (40) auraient un réel potentiel avec des performances égales ou supérieures à des lignées témoins performantes. Au terme de ce projet, nous avons démontré l'efficacité d'une procédure GWAS combinant des approches uni- et multi-locus à disséquer des caractères complexes et à détecter des QTL clés utilisables en SAM. Nous avons aussi démontré que la prédiction génomique peut être optimisée et efficacement intégrée en sélection génétique chez l’orge à six rangs pour identifier les meilleurs descendants, mais surtout pour identifier des croisements prometteurs.Finally, in the fourth part, we explored genomic selection and genomic mating in a breeding program. First, we established a training population to build a genomic selection model and to predict the performance of 350 progeny developed in a breeding program. Based on these predictions, 35 lines were selected and tested in the field to examine the correlation between predicted and observed performances. The correlations were satisfactory for Fusarium head blight (FHB) resistance and yield. Then, based on this model, we predicted the mean (μ) and the genetic variance (VG) of each simulated progeny from all possible crosses (n = 30,000) between lines of the training population. The validation of these predictions was carried out retrospectively on a subset of previously performed crosses by examining their persistence in the selection process. As expected, the most persistent crosses (> F9) displayed high μ but moderate VG. Although resistance to FHB and yield are unfavorably correlated, we could identify crosses (650) where this correlation was weakened. Among these crosses, some (40) are predicted to offer equal or better performance than current checks. Through this project, we demonstrated the efficiency of a GWAS procedure combining single- and multi-locus approaches to dissect complex characters and to detect key QTLs that can be used in MAS. We also demonstrated that genomic prediction can be optimized and efficiently integrated in genetic improvement of six-row barley to identify the best progeny but also to identify promising crosses.The emergence of high-throughput genotyping and the development of statistical methods linking genotype to phenotype have led to pangenomic approaches, performed on a genome-wide scale, exploitable in plant breeding. First, these approaches were used to examine the association between genotype and phenotype in genome-wide association studies (GWAS) in order to identify quantitative trait loci (QTLs) useful in marker-assisted selection (MAS). More recently, these approaches have been explored in genomic prediction which aims, on the one hand, to identify the most promising crosses (genomic mating), and on the other hand, to identify the most promising lines within a set of progeny (genomic selection). In both cases, these predictions are based on a statistical model linking genotype to phenotype in a training population. These genome-wide approaches offer great potential but are still emerging and many questions remain unanswered in barley. Our study focuses on some of these questions and is divided into four areas of research. Genome-wide approaches require a large number of single nucleotide polymorphism (SNP) markers. Thus, in the first part of this project, we optimized the protocol of genotyping by sequencing (GBS). This part details the entire process, from the preparation of GBS libraries until the production of a high-quality SNP catalog. As an illustration, we generated a catalog of 30,000 SNPs with a broad chromosome distribution and high genotype accuracy. In the second part, using phenotypic and genotypic data from a breeding population, we compared the effectiveness of three GWAS approaches (Single-SNP, Multi-SNP and Haplotype-based) to detect QTLs for important agronomic traits. The Multi-SNP and Haplotype-based approaches identified more QTLs than the Single-SNP approach. The overlap between the approaches was limited, as each approach uncovered a different subset of previously validated QTLs. In the third part we studied the impact of three factors on the accuracy of genomic selection: (1) the performance of different statistical models (including epistasis or not), (2) the number of SNP markers included in the model as well as (3) their localization (genic/non-genic regions). The model that incorporates both the additive and epistatic effects of SNPs showed the best performance even though the differences between the models were modest. With as few as 2K SNP, the accuracy of genomic selection remained comparable to that based on the entire catalog (35K), while a significant decrease in accuracy was observed at 500 SNPs. In most cases, the use of SNPs located in genic regions, even coding regions, did not provide a significant improvement

Polycystic ovary syndrome: A disorder of reproductive age, its pathogenesis, and a discussion on the emerging role of herbal remedies

Polycystic ovary syndrome (PCOS) is a very common, complex, and heterogeneous endocrine disorder of women that involves a combination of environmental and genetic factors. PCOS affects women of growing age particularly at the early to late reproductive stage (15-35 years). Currently, PCOS affects 1 in every 10 women worldwide. It is characterized majorly by a raised level of androgens such as testosterone and a large number of ovarian cysts (more than 10) that cause anovulation, infertility, and irregular menstrual cycle. PCOS is also related to other endocrine and metabolic abnormalities, such as obesity, hirsutism, acne, diabetes, insulin resistance, and glucose impairment. PCOS can be treated with allopathic, ayurvedic, and natural or herbal medications along with lifestyle modifications. Herbal medicines remained in demand for numerous reasons such as high cost and side effects associated with the use of allopathic medicine and our traditional norms, which have helped humans to use more herbal products for their health benefits. Estrogenic and nonestrogenic phytochemicals present in various plant species such as Glycyrrhiza glabra L. [Fabaceae], Aloe vera (L.) Burm. f. [Asphodelaceae], Silybum marianum (L.). Gaertn. [Asteraceae], Serenoa repens (W.Bartram) Small [Arecaceae], Actaea racemosa L. [Ranunculaceae], and Angelica sinensis (Oliv.) Diels [Apiaceae] are effective and harmless. Herbal medicines are found to be cost-effective, efficacious, and a highly esteemed source of management/treatment for PCOS than allopathic medicines. In this literature review, diagnosis, signs, and symptoms of PCOS; causes of hormonal imbalance; and risk factors associated with PCOS and their management are discussed briefly, and the focus was to find out the role of herbal remedies in PCOS management

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Time for a paradigm shift in the use of plant genetic resources

For all major crops, sizeable genebanks are maintained across the world and serve as repositories of genetic diversity and key sources of novel traits used in breeding. Although molecular markers have been used to characterize diversity in a broad sense, the most common approach to exploring these resources has been through phenotypic characterization of subsets of these large collections. With the advent of affordable large-scale genotyping technologies and the increasing body of candidate genes for traits of interest, we argue here that it is time for a paradigm shift in the way that we explore and exploit these considerable and highly useful resources. By combining dense genotypic information in and around candidate genes, it is possible to classify accessions based on their haplotype, something approximating the actual alleles at these genes of interest.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

An Innovative Approach for Evaluating the Quality of Recycled Concrete Aggregate Mixes

The objective of this research is to develop an innovative methodology for evaluating the quality of coarse aggregate mixes that incorporate recycled concrete aggregate for use in structural concrete. The proposed approach consists of three steps: measuring the packing density, quantifying the adhered mortar, and characterizing the mechanical resistance of the aggregate mixes containing both natural and recycled concrete aggregate. Comprehensive practical recommendations for each step are discussed in detail to facilitate the broader future utilization of recycled concrete aggregate in structural concrete. The mechanical resistance of aggregate mixes is significantly influenced by both packing density and the quantity of adhered mortar. Predictive models are used to illustrate the mechanical resistance of aggregate mixes based on packing density and adhered mortar amount, recognizing the direct correlation between these properties

A TEMPLATE MATCHING-BASED METHOD FOR IDENTIFYING THE SEPARATION POINT OF BUOYANT WALL JETS

International audienceA cold air jet introduced just below a horizontal wall attaches to the wall and then separates from it. The distance between the separation point and the inlet nozzle is an important design parameter for air conditioning systems. Using laser-light sheet visualization, the separation point can be located by either visual observation or image processing. Nevertheless, the unsteadiness of the separation point, induced by the turbulence of the jet, requires tens or hundreds of readings for one determination, making visual measurement tedious and hardly reproducible. As an alternative, the separation point of the jet from the wall may be numerically located where the highest correlation between the image of the jet edges and the template representing the characteristic separation pattern is found in the image. The correlation, calculated using the Discrete Fourier Transform, also gives a measure of the separation point location clarity