RESUMO
Crop wild relatives (CWR) provide a valuable resource for improving crops. They possess desirable traits that confer resilience to various environmental stresses. To fully utilize crop wild relatives in breeding and conservation programs, it is important to understand the genetic basis of their adaptation. Landscape genomics associates environments with genomic variation and allows for examining the genetic basis of adaptation. Our study examined the differences in allele frequency of 15,416 single nucleotide polymorphisms (SNPs) generated through genotyping by sequencing approach among 153 accessions of 15 wild eggplant relatives and two cultivated species from Africa, the principal hotspot of these wild relatives. We also explored the correlation between these variations and the bioclimatic and soil conditions at their collection sites, providing a comprehensive understanding of the genetic signals of environmental adaptation in African wild eggplant. Redundancy analysis (RDA) results showed that the environmental variation explained 6% while the geographical distances among the collection sites explained 15% of the genomic variation in the eggplant wild relative populations when controlling for population structure. Our findings indicate that even though environmental factors are not the main driver of selection in eggplant wild relatives, it is influential in shaping the genomic variation over time. The selected environmental variables and candidate SNPs effectively revealed grouping patterns according to the environmental characteristics of sampling sites. Using four genotype-environment association methods, we detected 396 candidate SNPs (2.5% of the initial SNPs) associated with eight environmental factors. Some of these SNPs signal genes involved in pathways that help adapt to environmental stresses such as drought, heat, cold, salinity, pests, and diseases. These candidate SNPs will be useful for marker-assisted improvement and characterizing the germplasm of this crop for developing climate-resilient eggplant varieties. The study provides a model for applying landscape genomics to other crops' wild relatives.
RESUMO
Introduction: Over the last 12 years, there has been a consistent decline in the cases of typhoid/paratyphoid fever in China. Studying the epidemiological patterns of these diseases in various provincial-level administrative divisions (PLADs) and examining potential influencing factors can provide crucial information for implementing successful control strategies. Methods: In this study, we analyzed the cases and incidence rates of typhoid/paratyphoid fever reported in various PLADs of China from 2011 to 2022, along with exploring potential influencing factors. We initially studied spatial shifts in the incidence rates through centroid shift analysis. Seasonal variations in typhoid/paratyphoid fever onset were examined using heatmaps. Spatial autocorrelation analysis was utilized to understand the spatial correlations among different PLADs. To assess potential factors, we utilized a generalized estimating equations model that integrated spatial lag effects and sequence comparison analysis. Results: The study identified significant geographical clustering of typhoid/paratyphoid fever cases in southwestern China. A decrease in incidence rates in the west resulted in a movement of the disease center towards the east. Higher incidence occurred during warmer seasons, highlighting the seasonal pattern of the diseases. Factors such as meteorological conditions and socioeconomic status were probable influencers of typhoid/paratyphoid fever. Conclusions: The geographical and temporal spread of typhoid/paratyphoid fever can be impacted by meteorological and socioeconomic factors. Enhancing economic conditions, particularly in regions with high disease prevalence, could aid in the prevention and management of these fevers.