A generalized framework for AMOVA with multiple hierarchies and ploidies

Population Genetic Analysis of Phytophthora colocasiae from Taro in Japan Using SSR Markers

Phytophthora colocasiae is an important pathogen that causes great economic losses in taro production in tropical and subtropical regions, especially in Japan. Understanding the genetic variations in P. colocasiae populations and their transmission patterns in Japan is essential for effective disease control. Here, the genetic diversity of 358 P. colocasiae isolates, including 348 from Japan, 7 from China, and 3 from Indonesia, was assessed using 11 simple sequence repeat (SSR) primer pairs with high polymorphism. The phylogenetic tree of the SSR locus showed that the isolates from Japan could be divided into 14 groups, with group A being the dominant group. Among foreign isolates, only six from mainland China were similar to those from Japan and clustered in groups B and E. Analysis of molecular variance (AMOVA), principal components analysis (PCA), and cluster analysis (K = 3) results revealed a moderate level of genetic diversity, mainly within individuals. Populations showed high heterozygosity, a lack of regional differentiation, and frequent gene flow. Analysis of mating types and ploidy levels revealed that A2 and self-fertile (SF) A2 types and tetraploids were dominant across populations. Explanations and hypotheses for the results can provide more effective strategies for disease management of taro leaf blight.

Population Genomic Analysis of Diploid-Autopolyploid Species

This chapter outlines an empirical analysis of genome-wide single-nucleotide polymorphism (SNP) variation and its underlying drivers among multiple natural populations within a diploid-autopolyploid species. The aim is to reconstruct the genetic structure among natural populations of varying ploidy and infer footprints of selection in these populations, framed around specific questions that are typically encountered when analyzing a mixed-ploidy data set,e.g., addressing the relevance of natural whole-genome duplication for speciation and adaptation. We briefly review the options for the analysis of polyploid population genomic data involving variant calling, population structure, demographic history inference, and selection scanning approaches. Further, we provide suggestions for methods and associated software, possible caveats, and examples of their application to mixed-ploidy and autopolyploid data sets.

vcfpop: Performing population genetics analyses for autopolyploids and aneuploids based on next-generation sequencing data sets

Polyploids are cells or organisms with a genome consisting of more than two sets of homologous chromosomes. Polyploid plants have important traits that facilitate speciation and are thus often model systems for evolutionary, molecular ecology and agricultural studies. However, due to their unusual mode of inheritance and double-reduction, diploid models of population genetic analysis cannot properly be applied to autopolyploids. To overcome this problem, we developed a software package entitled vcfpop to perform a variety of population genetic analyses for autopolyploids, such as parentage analysis, analysis of molecular variance, principal coordinates analysis, hierarchical clustering analysis and Bayesian clustering. We used three data sets to evaluate the capability of vcfpop to analyse large data sets on a desktop computer. This software is freely available at http://github.com/huangkang1987/vcfpop.

Different coding characteristics between flight and freezing in dorsal periaqueductal gray of mice during exposure to innate threats

BACKGROUND

Flight and freezing are two vital defensive behaviors that mice display to avoid natural enemies. When they are exposed to innate threats, visual cues are processed and transmitted by the visual system into the emotional nuclei and finally transmitted to the periaqueductal gray (PAG) to induce defensive behaviors. However, how the dorsal PAG (dPAG) encodes the two defensive behaviors is unclear.

METHODS

Multi-array electrodes were implanted in the dPAG nuclei of C57BL/6 mice. Two kinds of visual stimuli (looming and sweeping) were used to induce defensive behaviors in mice. Neural signals under different defense behaviors were recorded, and the encoding characteristics of the two behaviors were extracted and analyzed from spike firing and frequency oscillations. Finally, synchronization of neural activity during the defense process was analyzed.

RESULTS

The neural activity between flight and freezing behaviors showed different firing patterns, and the differences in the inter-spike interval distribution were mainly reflected in the 2-10 ms period. The frequency band activities under both defensive behaviors were concentrated in the theta band; the active frequency of flight was ~8 to 10 Hz, whereas that of freezing behavior was ~6 to 8 Hz. The network connection density under both defense behaviors was significantly higher than the period before and after defensive behavior occurred, indicating that there was a high synchronization of neural activity during the defense process.

CONCLUSIONS

The dPAG nuclei of mice have different coding features between flight and freezing behaviors; during strong looming stimulation, fast neuro-instinctive decision making is required while encountering weak sweeping stimulation, and computable planning late behavior is predicted in the early stage. The frequency band activities under both defensive behaviors were concentrated in the theta band. There was a high synchronization of neural activity during the defense process, which may be a key factor triggering different defensive behaviors.

Long-Term Exposure and Effects of rGO-nZVI Nanohybrids and Their Parent Nanomaterials on Wastewater-Nitrifying Microbial Communities

Single nanomaterials and nanohybrids (NHs) can inhibit microbial processes in wastewater treatment, especially nitrification. While existing studies focus on short-term and acute exposures of single nanomaterials on wastewater microbial community growth and function, long-term, low-exposure, and emerging NHs need to be examined. These NHs have distinctly different physicochemical properties than their parent nanomaterials and, therefore, may exert previously unknown effects onto wastewater microbial communities. This study systematically investigated long-term [∼6 solid residence time [(SRT)] exposure effects of a widely used carbon-metal NH (rGO-nZVI = 1:2 and 1:0.2, mass ratio) and compared these effects to their single-parent nanomaterials (i.e., rGO and nZVI) in nitrifying sequencing batch reactors. nZVI and NH-dosed reactors showed relatively unaffected microbial communities compared to control, whereas rGO showed a significantly different (p = 0.022) and less diverse community. nZVI promoted a diverse community and significantly higher (p < 0.05) biomass growth under steady-state conditions. While long-term chronic exposure (10 mg·L^-1) of single nanomaterials and NHs had limited impact on long-term nutrient recovery, functionally, the reactors dosed with higher iron content, that is, nZVI and rGO-nZVI (1:2), promoted faster NH₄⁺-N removal due to higher biomass growth and upregulation of amoA genes at the transcript level, respectively. The transmission electron microscopy images and scanning electron microscopy─energy-dispersive X-ray spectroscopy analysis revealed high incorporation of iron in nZVI-dosed biomass, which promoted higher cellular growth and a diverse community. Overall, this study shows that NHs have unique effects on microbial community growth and function that cannot be predicted from parent materials alone.