Two independent approaches converge to the cloning of a new Leptosphaeria maculans avirulence effector gene, AvrLmS-Lep2.

Brassica napus (oilseed rape, canola) seedling resistance to Leptosphaeria maculans, the causal agent of blackleg (stem canker) disease, follows a gene-for-gene relationship. The avirulence genes AvrLmS and AvrLep2 were described to be perceived by the resistance genes RlmS and LepR2, respectively, present in B. napus 'Surpass 400'. Here we report cloning of AvrLmS and AvrLep2 using two independent methods. AvrLmS was cloned using combined in vitro crossing between avirulent and virulent isolates with sequencing of DNA bulks from avirulent or virulent progeny (bulked segregant sequencing). AvrLep2 was cloned using a biparental cross of avirulent and virulent L. maculans isolates and a classical map-based cloning approach. Taking these two approaches independently, we found that AvrLmS and AvrLep2 are the same gene. Complementation of virulent isolates with this gene confirmed its role in inducing resistance on Surpass 400, Topas-LepR2, and an RlmS-line. The gene, renamed AvrLmS-Lep2, encodes a small cysteine-rich protein of unknown function with an N-terminal secretory signal peptide, which is a common feature of the majority of effectors from extracellular fungal plant pathogens. The AvrLmS-Lep2/LepR2 interaction phenotype was found to vary from a typical hypersensitive response through intermediate resistance sometimes towards susceptibility, depending on the inoculation conditions. AvrLmS-Lep2 was nevertheless sufficient to significantly slow the systemic growth of the pathogen and reduce the stem lesion size on plant genotypes with LepR2, indicating the potential efficiency of this resistance to control the disease in the field

Targeted mutagenesis in wheat microspores using CRISPR/Cas9

Abstract CRISPR/Cas9 genome editing is a transformative technology that will facilitate the development of crops to meet future demands. However, application of gene editing is hindered by the long life cycle of many crop species and because desired genotypes generally require multiple generations to achieve. Single-celled microspores are haploid cells that can develop into double haploid plants and have been widely used as a breeding tool to generate homozygous plants within a generation. In this study, we combined the CRISPR/Cas9 system with microspore technology and developed an optimized haploid mutagenesis system to induce genetic modifications in the wheat genome. We investigated a number of factors that may affect the delivery of CRISPR/Cas9 reagents into microspores and found that electroporation of a minimum of 75,000 cells using 10–20 µg DNA and a pulsing voltage of 500 V is optimal for microspore transfection using the Neon transfection system. Using multiple Cas9 and sgRNA constructs, we present evidence for the seamless introduction of targeted modifications in an exogenous DsRed gene and two endogenous wheat genes, including TaLox2 and TaUbiL1. This study demonstrates the value and feasibility of combining microspore technology and CRISPR/Cas9-based gene editing for trait discovery and improvement in plants

Rapid identification of the Leptosphaeria maculans avirulence gene AvrLm2 using an intraspecific comparative genomics approach

Five avirulence genes from Leptosphaeria maculans, the causal agent of blackleg of canola (Brassica napus), have been identified previously through map-based cloning. In this study, a comparative genomic approach was used to clone the previously mapped AvrLm2. Given the lack of a presence-absence gene polymorphism coincident with the AvrLm2 phenotype, 36 L.maculans isolates were resequenced and analysed for single-nucleotide polymorphisms (SNPs) in predicted small secreted protein-encoding genes present within the map interval. Three SNPs coincident with the AvrLm2 phenotype were identified within LmCys1, previously identified as a putative effector-coding gene. Complementation of a virulent isolate with LmCys1, as the candidate AvrLm2 allele, restored the avirulent phenotype on Rlm2-containing B.napus lines. AvrLm2 encodes a small cysteine-rich protein with low similarity to other proteins in the public databases. Unlike other avirulence genes, AvrLm2 resides in a small GC island within an AT-rich isochore of the genome, and was never found to be deleted completely in virulent isolates

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BackgroundEstimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period.Methods22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution.FindingsGlobal all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations.InterpretationGlobal adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic