Population Evolution, Genetic Diversity and Structure of the Medicinal Legume, Glycyrrhiza uralensis and the Effects of Geographical Distribution on Leaves Nutrient Elements and Photosynthesis

Glycyrrhiza uralensis is a valuable medicinal legume, which occurs widely in arid and semi-arid regions. G. uralensis demand has risen steeply due to its high medical and commercial value. Interpret genome-wide information can stimulate the G. uralensis development as far as its increased bioactive compound levels, and plant yield are concerned. In this study, leaf nutrient concentration and photosynthetic chlorophyll index of G. uralensis were evaluated to determine the G. uralensis growth physiology in three habitats. We observed that G. uralensis nutrient levels and photosynthesis differed significantly in three regions (p < 0.05). Whole-genome re-sequencing of the sixty G. uralensis populations samples from different habitats was performed using an Illumina HiSeq sequencing platform to elucidate the distribution patterns, population evolution, and genetic diversity of G. uralensis. 150.06 Gb high-quality clean data was obtained after strict filtering. The 895237686 reads were mapped against the reference genome, with an average 89.7% mapping rate and 87.02% average sample coverage rate. A total of 6985987 SNPs were identified, and 117970 high-quality SNPs were obtained after filtering, which were subjected to subsequent analysis. Principal component analysis (PCA) based on interindividual SNPs and phylogenetic analysis based on interindividual SNPs showed that the G. uralensis samples could be categorized into central, southern, and eastern populations, which reflected strong genetic differentiation due to long periods of geographic isolation. In this study, a total of 131 candidate regions were screened, and 145 candidate genes (such as Glyur001802s00036258, Glyur003702s00044485, Glyur001802s00036257, Glyur007364s00047495, Glyur000028s00003476, and Glyur000398s00034457) were identified by selective clearance analysis based on Fst and θπ values. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed significant enrichment of 110 GO terms including carbohydrate metabolic process, carbohydrate biosynthetic process, carbohydrate derivative biosynthetic process, and glucose catabolic process (p < 0.05). Alpha-linolenic acid metabolism, biosynthesis of unsaturated fatty acids, and fatty acid degradation pathways were significantly enriched (p < 0.05). This study provides information on the genetic diversity, genetic structure, and population adaptability of the medicinal legumes, G. uralensis. The data obtained in this study provide valuable information for plant development and future optimization of breeding programs for functional genes.

Surnames in south-eastern France: structure of the rural population during the 19th century through isonymy

An analysis of the distribution of surnames through time and space allows us to understand the structure of human groups, their exchanges or even their possible isolation. The French population has already been studied through surnames and it has been shown that the Sud-Provence-Alpes-Côte d’Azur region differed from the rest of France in both the 20th and 21st centuries (Mourrieras et al., 1995; Scapoli et al., 2005). The objective of this study was to understand the population evolution and particularities of the Sud-Provence-Alpes-Côte d’Azur region through an analysis of the distribution of surnames over an earlier period: the 19th century. For this work, 806,069 birth records from 521 communes between 1810 and 1890 were recorded and a total of 23,340 surnames were collected. The estimation of various isonymic parameters has allowed a description of this corpus never exploited before. In order to appreciate the population evolution, the data set was divided into three periods of 25 years. The canton was the geographical unit of this study, and similarities and differences between each of them were evaluated using Lasker distances, which allow the construction of dendrograms. A positive and significant correlation (p<0.0001) was found between Lasker distances and geographical distances using the Mantel test. The lowest inbreeding estimates were found in the Durance Valley. Migration, estimated from the v-index of Karlin and McGregor (1967), showed higher values in the south-western quarter of the region. The decrease in Rst values across the three periods is consistent with a homogenization of the patronymic between the cantons. This three-period approach showed a population evolution influenced by linguistic, cultural, historical and migratory phenomena since the Middle Ages, disrupted by the socioeconomic changes of the 19th century.

Frequency of CYP2D6*3 and *4 and metabolizer phenotypes in three mestizo Peruvian populations

Wild type genotypes (CYP2D6) and their allelic variants have been described in a sample of a Peruvian mestizo population. The global allele frequency was 0.015 for CYP2D6*3 and 0.051 for CYP2D6*4. The percentages of genotypes described were 97% CYP2D6*1/*1 and 3.0% CYP2D6*1/*3; 90.60% for CYP2D6*1/*1, 8.55% CYP2D6*1/*4 and 0.85% CYP2D6*4/*4. The allelic frequencies of CYP2D6*3 in the Lima subpopulations were 0.022 and 0.010 for Junin; CYP2D6*4 of 0.048, 0.060, and 0.050 for residents of Lima, Junín, and Tacna, respectively. The Hardy-Weinberg equilibrium test for the studied population showed that both frequencies are in equilibrium, p &lt;.05. The metabolizer phenotype was inferred according to the genotypes: 11.54% were classified as intermediate metabolizers (*1/*3 or *1/*4) and 0.85% as poor metabolizers (*4/*4). It is concluded that the frequencies of the CYP2D6*3 and CYP2D6*4 alleles are low for the Peruvian mestizo population compared to the Latin American and tricontinental population, due to their natural population evolution, which is manifested by their decreased metabolic activity, the same that is relevant in clinical practice.

ANFIS soft sensing model of SMB chromatographic separation process based on new adaptive population evolution particle swarm optimization algorithm

Aiming at predicting the purity of the extract and raffinate components in the simulated moving bed (SMB) chromatographic separation process, a soft-sensor modeling method was proposed by adoptig the hybrid learning algorithm based on an improved particle swarm optimization (PSO) algorithm and the least means squares (LMS) method to optimize the adaptive neural fuzzy inference system (ANFIS) parameters. The hybrid learning algorithm includes a premise parameter learning phase and a conclusion parameter learning phase. In the premise parameter learning stage, the input data space division of the SMB chromatographic separation process and the initialization of the premise parameters are realized based on the fuzzy C-means (FCM) clustering algorithm. Then, the improved PSO algorithm is used to calculate the excitation intensity and normalized excitation intensity of all the rules for each individual in the population. In the conclusion parameter learning phase, these linear parameters are identified by the LMS method. In order to improve population diversity and convergence accuracy, the population evolution rate function was defined. According to the relationship between population diversity, population fitness function and particle position change, a new adaptive population evolution particle swarm optimization (NAPEPSO) algorithm was proposed. The inertia weight is adaptively adjusted according to the evolution of the population and the change of the particle position, thereby improving the diversity of the particle swarm and the ability of the algorithm to jump out of the local optimal solution. The simulation results show that the proposed soft-sensor model can effectively predict the key economic and technical indicators of the SMB chromatographic separation process so as to meet the real-time and efficient operation of the SMB chromatographic separation process.

No Correlation Between Pollen Fertility and Viability: Differential Measures of Male Gametophytic Fitness in Cannabis sativa L.

Pollen grains are male gametophytes, an ephemeral haploid generation of plants, commonly engaging in competition for a limited supply of ovules. Since differential male fertility may influence the direction and pace of population evolution, the relative fitness of pollen is regularly estimated as either pollen viability, the proportion of pollen containing intact cytoplasm's and regenerative nuclei, or pollen fertility, the frequency of pollen germinating under standardized conditions. Here, we estimated the relative fitness of pollen in a dioecious, wind-pollinated model system, Cannabis sativa, by characterizing pollen fertility and viability from multiple sires. Pollen fertility quickly declined within two weeks of anther dehiscence, and pollen stored under freezer conditions did not germinate regardless of storage time. In contrast, pollen viability declined slowly and persisted longer than the lifetime of a sporophyte plant under both room temperature and freezer conditions. Pollen samples that underwent both fertility and viability analysis displayed no significant correlation, implying researchers cannot predict pollen fertility from pollen viability, nor infer male gametophytic fitness from a single measure. Our work demonstrates two approaches to measure proxies of male fitness in C. sativa, and identifies new questions around what are valuable estimates of male fitness in plants.

Desarrollo local y vaciamiento demográfico en Moratalla (Murcia, España): ¿un proceso reversible a través de la promoción turística?

Resumen: El municipio de Moratalla, ubicado en la comarca del NO de Murcia (España) presenta por sus datos respecto a la evolución poblacional una de las pocas excepciones en el conjunto regional, ya que pierde población desde al menos cuatro décadas. Esta situación significa un progresivo deterioro en la actividad económica, el envejecimiento de la población y un importante abandono del casco histórico de la ciudad, así como en una serie de pedanías localizadas en un amplio término municipal de 954,82 km2, el tercero más extenso de la Región de Murcia que está compuesta por cuarenta y cinco términos municipales. Los análisis estadísticos, cuestionario tabulados y entrevistas de carácter cualitativo a expertos locales señalan un escenario para esta ciudad y su término municipal preocupante, que en caso de que no se consiga frenar podría desembocar a medio y largo plazo en una aguda regresión social y económica de este municipio. A través de la herramienta DAFO aplicada básicamente a la promoción turística de interior se harán propuestas que contribuyan a detener la sangría demográfica, diversificando la económica local basada en el sector primario y en la salida diaria de muchos vecinos a otras localidades, donde desarrollan sus puestos de trabajo. Palabras clave: Despoblación, vaciamiento, desarrollo local, Moratalla, estrategia territorial. Abstract: The municipality of Moratalla, located in the NW region of Murcia (Spain) presents, due to its data regarding population evolution, one of the few exceptions in the regional set, since it has lost population for at least four decades. This situation means a progressive deterioration in economic activity, the aging of the population and a significant abandonment of the historic center of the city, as well as in a series of districts located in a large municipal area of 954.82 km2, the third largest of the Murcia Region, which is made up of forty-five municipalities. Statistical analyzes, tabulated questionnaires and qualitative interviews with local experts indicate a worrying scenario for this city and its municipal area, which in the event of failure to stop could lead in the medium and long term into an acute social and economic regression of this municipality. Through the SWOT tool applied basically to inland tourism promotion, proposals will be made that help to stop demographic bleeding, diversifying the local economy based on the primary sector and the daily departure of many residents to other locations, where they develop their jobs of work. Key words: Depopulation, emptying, local development, Moratalla, territorial strategy.

Simplified Phasmatodea population evolution algorithm for optimization

This work proposes a population evolution algorithm to deal with optimization problems based on the evolution characteristics of the Phasmatodea (stick insect) population, called the Phasmatodea population evolution algorithm (PPE). The PPE imitates the characteristics of convergent evolution, path dependence, population growth and competition in the evolution of the stick insect population in nature. The stick insect population tends to be the nearest dominant population in the evolution process, and the favorable evolution trend is more likely to be inherited by the next generation. This work combines population growth and competition models to achieve the above process. The implemented PPE has been tested and analyzed on 30 benchmark functions, and it has better performance than similar algorithms. This work uses several engineering optimization problems to test the algorithm and obtains good results.

Dynamics of bacterial adaptation

Determining pattern in the dynamics of population evolution is a long-standing focus of evolutionary biology. Complementing the study of natural populations, microbial laboratory evolution experiments have become an important tool for addressing these dynamics because they allow detailed and replicated analysis of evolution in response to controlled environmental and genetic conditions. Key findings include a tendency for smoothly declining rates of adaptation during selection in constant environments, at least in part a reflection of antagonism between accumulating beneficial mutations, and a large number of beneficial mutations available to replicate populations leading to significant, but relatively low genetic parallelism, even as phenotypic characteristics show high similarity. Together, there is a picture of adaptation as a process with a varied and largely unpredictable genetic basis leading to much more similar phenotypic outcomes. Increasing sophistication of sequencing and genetic tools will allow insight into mechanisms behind these and other patterns.