Modelling the transmission and control of COVID-19 in Yangzhou city with the implementation of Zero-COVID policy

In the fight against the COVID-19 pandemic, China has long adhered to the "Dynamic Zero COVID-19" strategy till the end of 2022. To understand the mechanism of this strategy, we used the case of the Yangzhou summer outbreak in 2021 and a multi-stage dynamical model incorporating city-wide and key area testing-trace-isolation (TTI) strategies. We defined two time-varying indexes for measuring the disease transmission risk and the public health prevention and control force, respectively, which allowed us to explore the mechanisms of TTI policies. Integrating with the historical data and literature parameter values, we first estimated the parameters and then quantified the relevant indexes over time. The findings showed that multiple rounds of rapid testing were one of the critical measures to overcome the outbreak in Yangzhou within one month. In addition, we compared the impact of the duration of the free transmission stage, tracking rate, testing interval and precise division of key areas on the epidemiological indicators, including the final sizes of infections and isolations, peak value, peak arrival time and epidemic duration and the minimum round of testing. Our results suggest that the early detection of the epidemic, an improved efficiency of tracking, and a reduced duration of each test play a positive role in restraining COVID-19; however, a considerable investment of resources was essential to achieve a significant effect quickly

Graph pangenome captures missing heritability and empowers tomato breeding

Missing heritability in genome-wide association studies defines a major problem in genetic analyses of complex biological traits(1,2). The solution to this problem is to identify all causal genetic variants and to measure their individual contributions(3,4). Here we report a graph pangenome of tomato constructed by precisely cataloguing more than 19 million variants from 838 genomes, including 32 new reference-level genome assemblies. This graph pangenome was used forgenome-wide association study analyses and heritability estimation of 20,323 gene-expression and metabolite traits. The average estimated trait heritability is 0.41 compared with 0.33 when using the single linear reference genome. This 24% increase in estimated heritability is largely due to resolving incomplete linkage disequilibrium through the inclusion of additional causal structural variants identified using the graph pangenome. Moreover, by resolving allelic and locus heterogeneity, structural variants improve the power to identify genetic factors underlying agronomically important traits leading to, for example, the identification of two new genes potentially contributing to soluble solid content. The newly identified structural variants will facilitate genetic improvement of tomato through both marker-assisted selection and genomic selection. Our study advances the understanding of the heritability of complex traits and demonstrates the power of the graph pangenome in crop breeding

Free boundary models for mosquito range movement driven by climate warming

As vectors, mosquitoes transmit numerous mosquito-borne diseases. Among the many factors affecting the distribution and density of mosquitoes, climate change and warming have been increasingly recognized as major ones. In this paper, we make use of three diffusive logistic models with free boundary in one space dimension to explore the impact of climate warming on the movement of mosquito range. First, a general model incorporating temperature change with location and time is introduced. In order to gain insights of the model, a simplified version of the model with the change of temperature depending only on location is analyzed theoretically, for which the dynamical behavior is completely determined and presented. The general model can be modified into a more realistic one of seasonal succession type, to take into account of the seasonal changes of mosquito movements during each year, where the general model applies only for the time period of the warm seasons of the year, and during the cold season, the mosquito range is fixed and the population is assumed to be in a hibernating status. For both the general model and the seasonal succession model, our numerical simulations indicate that the long-time dynamical behavior is qualitatively similar to the simplified model, and the effect of climate warming on the movement of mosquitoes can be easily captured. Moreover, our analysis reveals that hibernating enhances the chances of survival and successful spreading of the mosquitoes, but it slows down the spreading speed

Genomic insights into the origin, domestication and genetic basis of agronomic traits of castor bean

BACKGROUND: Castor bean (Ricinus communis L.) is an important oil crop, which belongs to the Euphorbiaceae family. The seed oil of castor bean is currently the only commercial source of ricinoleic acid that can be used for producing about 2000 industrial products. However, it remains largely unknown regarding the origin, domestication, and the genetic basis of key traits of castor bean.RESULTS: Here we perform a de novo chromosome-level genome assembly of the wild progenitor of castor bean. By resequencing and analyzing 505 worldwide accessions, we reveal that the accessions from East Africa are the extant wild progenitors of castor bean, and the domestication occurs ~ 3200 years ago. We demonstrate that significant genetic differentiation between wild populations in Kenya and Ethiopia is associated with past climate fluctuation in the Turkana depression ~ 7000 years ago. This dramatic change in climate may have caused the genetic bottleneck in wild castor bean populations. By a genome-wide association study, combined with quantitative trait locus analysis, we identify important candidate genes associated with plant architecture and seed size.CONCLUSIONS: This study provides novel insights of domestication and genome evolution of castor bean, which facilitates genomics-based breeding of this important oilseed crop and potentially other tree-like crops in future.</p

Genome evolution and diversity of wild and cultivated potatoes

Potato (Solanum tuberosum L.) is the world’s most important non-cereal food crop, and the vast majority of commercially grown cultivars are highly heterozygous tetraploids. Advances in diploid hybrid breeding based on true seeds have the potential to revolutionize future potato breeding and production1–4. So far, relatively few studies have examined the genome evolution and diversity of wild and cultivated landrace potatoes, which limits the application of their diversity in potato breeding. Here we assemble 44 high-quality diploid potato genomes from 24 wild and 20 cultivated accessions that are representative of Solanum section Petota, the tuber-bearing clade, as well as 2 genomes from the neighbouring section, Etuberosum. Extensive discordance of phylogenomic relationships suggests the complexity of potato evolution. We find that the potato genome substantially expanded its repertoire of disease-resistance genes when compared with closely related seed-propagated solanaceous crops, indicative of the effect of tuber-based propagation strategies on the evolution of the potato genome. We discover a transcription factor that determines tuber identity and interacts with the mobile tuberization inductive signal SP6A. We also identify 561,433 high-confidence structural variants and construct a map of large inversions, which provides insights for improving inbred lines and precluding potential linkage drag, as exemplified by a 5.8-Mb inversion that is associated with carotenoid content in tubers. This study will accelerate hybrid potato breeding and enrich our understanding of the evolution and biology of potato as a global staple food crop

Phylogenomic discovery of deleterious mutations facilitates hybrid potato breeding

Hybrid potato breeding will transform the crop from a clonally propagated tetraploid to a seed-reproducing diploid. Historical accumulation of deleterious mutations in potato genomes has hindered the development of elite inbred lines and hybrids. Utilizing a whole-genome phylogeny of 92 Solanaceae and its sister clade species, we employ an evolutionary strategy to identify deleterious mutations. The deep phylogeny reveals the genome-wide landscape of highly constrained sites, comprising ∼2.4% of the genome. Based on a diploid potato diversity panel, we infer 367,499 deleterious variants, of which 50% occur at non-coding and 15% at synonymous sites. Counterintuitively, diploid lines with relatively high homozygous deleterious burden can be better starting material for inbred-line development, despite showing less vigorous growth. Inclusion of inferred deleterious mutations increases genomic-prediction accuracy for yield by 24.7%. Our study generates insights into the genome-wide incidence and properties of deleterious mutations and their far-reaching consequences for breeding.ISSN:0092-8674ISSN:1097-417

Genome architecture and tetrasomic inheritance of autotetraploid potato

Potato (Solanum tuberosum) is the most consumed non-cereal food crop. Most commercial potato cultivars are autotetraploids with highly heterozygous genomes, severely hampering genetic analyses and improvement. By leveraging the state-of-the-art sequencing technologies and polyploid graph binning, we achieved a chromosome-scale, haplotype-resolved genome assembly of a cultivated potato, Cooperation-88 (C88). Intra-haplotype comparative analyses revealed extensive sequence and expression differences in this tetraploid genome. We identified haplotype-specific pericentromeres on chromosomes, suggesting a distinct evolutionary trajectory of potato homologous centromeres. Furthermore, we detected double reduction events that are unevenly distributed on haplotypes in 1021 of 1034 selfing progeny, a feature of autopolyploid inheritance. By distinguishing maternal and paternal haplotype sets in C88, we simulated the origin of heterosis in cultivated tetraploid with a survey of 3110 tetra-allelic loci with deleterious mutations, which were masked in the heterozygous condition by two parents. This study provides insights into the genomic architecture of autopolyploids and will guide their breeding

Graph pangenome captures missing heritability and empowers tomato breeding

Missing heritability in genome-wide association studies defines a major problem in genetic analyses of complex biological traits(1,2). The solution to this problem is to identify all causal genetic variants and to measure their individual contributions(3,4). Here we report a graph pangenome of tomato constructed by precisely cataloguing more than 19 million variants from 838 genomes, including 32 new reference-level genome assemblies. This graph pangenome was used forgenome-wide association study analyses and heritability estimation of 20,323 gene-expression and metabolite traits. The average estimated trait heritability is 0.41 compared with 0.33 when using the single linear reference genome. This 24% increase in estimated heritability is largely due to resolving incomplete linkage disequilibrium through the inclusion of additional causal structural variants identified using the graph pangenome. Moreover, by resolving allelic and locus heterogeneity, structural variants improve the power to identify genetic factors underlying agronomically important traits leading to, for example, the identification of two new genes potentially contributing to soluble solid content. The newly identified structural variants will facilitate genetic improvement of tomato through both marker-assisted selection and genomic selection. Our study advances the understanding of the heritability of complex traits and demonstrates the power of the graph pangenome in crop breeding.ISSN:0028-0836ISSN:1476-468