The Impact of Nathan Mantel's "The Detection of Disease Clustering and a Generalized Regression Approach"

Effect of genetic distances of different genotypes of maize on the authenticity of single seeds detected by NIR spectroscopy

Introduction

NIR spectroscopy combined with chemometric algorithms has been widely used for seed authenticity detection. However, the study of seed genetic distance, an internal feature that affects the discriminative performance of classification models, has rarely been reported.

Methods

Therefore, maize seed samples of different genotypes were selected to investigate the effect of genetic distance on the authenticity of single seeds detected by NIR spectroscopy. Firstly, the Support vector machine (SVM) model was established using spectral information combined with a preprocessing algorithm, and then the DNA of the samples was extracted to study the correlation between genetic and relative spectral distances, the model identification performance, and finally to compare the similarities and differences between the results of genetic clustering and relative spectral clustering.

Results

The results were as follows: the average accuracy of the models was 93.6% (inbred lines) and 93.7% (hybrids), respectively; Genetic distance and correlation spectral distance exhibited positive correlation significantly (inbred lines: r=0.177, p<0.05; hybrids: r=0.238, p<0.05), likewise genetic distance and model accuracy also showed positive correlation (inbred lines: r=0.611, p<0.01; hybrids: r=0.6158, p<0.01); Genetic clustering and spectral clustering results were essentially uniform for 94.3% (inbred lines) and 93.9% (hybrids), respectively.

Discussion

This study reveals the relationship between the genetic and relative spectral distances of seeds and the accuracy of the model, which provides theoretical basis for the establishment of the standardized system for detecting the authenticity of seeds by NIR spectroscopic techniques.

Comparative mitogenomics elucidates the population genetic structure of Amblyomma testudinarium in Japan and a closely related Amblyomma species in Myanmar

Ticks are the second most important vector capable of transmitting diseases affecting the health of both humans and animals. Amblyomma testudinarium Koch 1844 (Acari: Ixodidae), is a hard tick species having a wide geographic distribution in Asia. In this study, we analyzed the composition of A. testudinarium whole mitogenomes from various geographical regions in Japan and investigated the population structure, demographic patterns, and phylogeographic relationship with other ixodid species. In addition, we characterized a potentially novel tick species closely related to A. testudinarium from Myanmar. Phylogeographic inference and evolutionary dynamics based on the 15 mitochondrial coding genes supported that A. testudinarium population in Japan is resolved into a star‐like haplogroup and suggested a distinct population structure of A. testudinarium from Amami island in Kyushu region. Correlation analysis using Mantel test statistics showed that no significant correlation was observed between the genetic and geographic distances calculated between the A. testudinarium population from different localities in Japan. Finally, demographic analyses, including mismatch analysis and Tajima’s D test, suggested a possibility of recent population expansion occurred within Japanese haplogroup after a bottleneck event. Although A. testudinarium has been considered widespread and common in East and Southeast Asia, the current study suggested that potentially several cryptic Amblyomma spp. closely related to A. testudinarium are present in Asia.

Rhizosphere Soil Fungal Communities of Aluminum-Tolerant and -Sensitive Soybean Genotypes Respond Differently to Aluminum Stress in an Acid Soil

Different soybean genotypes can differ in their tolerance toward aluminum stress depending on their rhizosphere-inhabiting microorganisms. However, there is limited understanding of the response of fungal communities to different aluminum concentrations across different genotypes. Here, we used metabarcoding of fungal ribosomal markers to assess the effects of aluminum stress on the rhizosphere fungal community of aluminum-tolerant and aluminum-sensitive soybean genotypes. Shifts in fungal community structure were related to changes in plant biomass, fungal abundance and soil chemical properties. Aluminum stress increased the difference in fungal community structure between tolerant and sensitive genotypes. Penicillium, Cladosporium and Talaromyces increased with increasing aluminum concentration. These taxa associated with the aluminum-tolerant genotypes were enriched at the highest aluminum concentration. Moreover, complexity of the co-occurrence network associated with the tolerant genotypes increased at the highest aluminum concentration. Collectively, increasing aluminum concentrations magnified the differences in fungal community structure between the two studied tolerant and sensitive soybean genotypes. This study highlights the possibility to focus on rhizosphere fungal communities as potential breeding target to produce crops that are more tolerant toward heavy metal stress or toxicity in general.