Phenotypic Distance Research Articles

Genetic and phenotypic differentiation in functional traits of Iris pseudacorus L. in native and introduced Mediterranean climate ranges

Intraspecific variation in functional traits between native and introduced plant species may underlie resilience and invasiveness of introduced species. We explored if observed phenotypic variation of Iris pseudacorus L. between populations in the native vs. introduced ranges results from genetic differentiation and/or phenotypic plasticity. Seeds were collected from populations along estuarine stress gradients within populations in both Guadalquivir Estuary (Andalusia, Spain) and San Francisco Bay-Delta Estuary (California, USA). Genetic analysis was performed on leaf tissue from plants in each seed donor population. Germinants (n = 48: 6 plants × 4 populations × 2 ranges) were grown for 12 months in a common garden experiment (CGE). We then evaluated 25 traits including growth, biomass allocation, morphological and biochemical responses. Geographic range explained relative intraspecific trait variation segregating native from introduced phenotypes. Native plants had lower specific leaf area (− 34%) and carbohydrate concentrations in rhizomes (− 63%) than introduced plants, providing evidence of genetic differentiation. Higher genetic diversity and 27% higher phenotypic variation (CGE) of native vs. introduced plants indicated longer-term adaptive processes in the native range. Genetic distance of introduced populations (field) increased along with their phenotypic distance (CGE), suggesting rapid genetic differentiation. Phenotypic plasticity also explained some observed inter-range differences under field conditions not expressed by plants in the CGE. Management of the introduced I. pseudacorus populations should be established urgently since they represent novel genotypes with key functional traits that can support invasiveness through increased competitive ability and physiological stress tolerances to sea level rise.

Demographic inference from the mt-DNA COI gene and wing geometry of Culex gelidus (Diptera: Culicidae), an important vector of Japanese encephalitis in Thailand

Culex gelidus (Diptera: Culicidae), an important vector of the Japanese encephalitis virus (JEV), contributes to human viral encephalitis in many Asian countries, including Thailand. This study represents the first investigation of the demographic patterns of Cx. gelidus populations in Thailand using cytochrome c oxidase subunit I (COI) gene analysis and wing geometric morphometrics (GM). Mosquitoes were collected from 10 provinces across six regions of Thailand in 2022. Analysis of the COI sequences (n = 182) indicated high haplotype diversity (0.882) and low nucleotide diversity (0.006), with 72 haplotypes identified. The haplotype network demonstrated no profound splits among the geographic populations. Neutral tests, including Tajima's D and Fu's Fs, displayed negative values, with a significant result observed for Fu's Fs (−33.048, p < 0.05). The mismatch distribution analysis indicated that the population does not statistically deviate from a model of sudden population expansion (SSD = 0.010, p > 0.05; Rg = 0.022, p > 0.05). The estimations suggest that the Cx. gelidus population in Thailand began its expansion approximately between 459,243 and 707,011 years ago. The Mantel test showed no significant relationship between genetic and geographic distances (r = 0.048, p > 0.05). Significant phenotypic differences (based on wing shape) were observed among most populations. Additionally, in this study, we found no significant relationships between phenotypic and genetic distances (r = 0.250, p > 0.05). Understanding the genetic and morphological dynamics of Cx. gelidus is vital for developing targeted surveillance and vector control measures. This knowledge will also help to predict how future environmental changes might affect these populations, thereby informing long-term vector management strategies.

METHODS OF KINSHIP ANALYSIS IN FOSSIL POPULATIONS

Introduction. Identifying kinship relationships from skeletal remains is among the various objectives of bioarchaeological studies. This article focuses on reviewing the methods used to analyze biological kinship in human fossil populations through non-metric traits. Methods. Since direct molecular-genetic analysis of kinship is often highly challenging due to the poor preservation of ancient DNA, special attention in such studies is given to nonmetric phenotypic traits. Results. Research with osteological samples that have been documented provides compelling evidence that the level of morphological similarity between individuals is directly related to their degree of biological kinship. In cases where the pedigrees of osteological materials are fully or partially known, phenotypic data can be effectively used in lieu of genetic information. Discussion. The methodology developed for kinship analysis depends on the internal spatial structure of the cemetery being studied. When analyzing small burial sites, the aim is to determine if the people buried there are close relatives. Various methods are used in these analyses, including different techniques for determining the likelihood of kinship, cluster analysis, and correlation coefficients. Identifying kinship is most promising in burial sites where archaeological or historical indicators of biological relationships are present. Kinship analysis in spatially structured cemeteries is aimed at identifying families or social groups. The analysis of uniformly distributed cemeteries focuses on identifying closely related individuals in large burials without clearly defined subgroups. This involves spatial correlation analysis, which tests for significant correlation between the matrix of spatial distances and the matrix of phenotypic distances; various counting methods to test for non-random clustering of traits; the nearest neighbor method; and a non-spatial block search procedure that simultaneously identifies presumed relatives and the traits that indicate the degree of their kinship. Conclusion. Many problems in establishing kinship can be overcome with the availability of skeletal material accompanied by verified genealogical data. Unfortunately, skeletal remains with preserved documentation are quite rare, limiting the opportunities to study the inheritance of non-metric traits and the morphological similarity of biologically related individuals.

Molecular and Phenotypic Markers from Many Okra Genotypes were Used to Estimate the Genetic and Phenotypic Distances

The experiment was conducted in the spring of 2021 in an open field in the Al-Mahmudiya district/Baghdad to study the genetic and phenotypic distance of a number of genotypes in okra using a randomized complete block design (RCBD) and three replications. As replication contained 18 genotypes of okra, distributed randomly on 18 experimental units, with ten cultivars giving the symbols (O1-O10) and eight hybrids giving the symbols (O11-O18), and at the third true leaf Samples were taken from (18 genotypes) extract DNA and the ISSR method was used to estimate the genetic distance, and the plants agricultural service operations continued and traits of vegetative, flowering and yield growth of genotypes were studied to study the phenotypic distance between them. The results of the genetic distance based on ISSR technology demonstrated that there is a genetic distance between the genotypes of okra under study, with the highest genetic distance between the two genotypes O6 and O15 reaching 0.735. The O6 cultivar displayed a high genetic distance with the most of the other genotypes, as the O10 cultivar which displayed a high genetic distance with most of the other genotypes, which advises plant breeders to use them to create development single hybrids. The hybrids O11, O12, O13, O14, O15, O16, and O17 also demonstrated a high genetic distance with the cultivars O6, O7, O8, O9, and O10, which plant breeders can use it in breeding program to development three-way hybrids. The ISSR results divided into two groups A and B in the genetic Cluster dendogram. the findings of the statistical analysis of the phenotypic variables also revealed that there were significant differences between the genotypes in the measured traits. As the O4 cultivar produced the greatest values for plant height and leaf number, flowers number, pods number (169 pods ) and pod set percentage, The O10 cultivar produced the highest pod weight (5.29 g) and yield per plant (691 g), and the results of the genetic distance based on phenotypic traits demonstrated that there is a phenotypic distance between the genotypes, with the two genotypes O10 and O15 exhibiting the highest genetic distance based on phenotypic traits (371.96 ).as The genotypes were divided into two groups within the cluster analysis depended on phenotypic traits.

Omicron breakthrough infections in vaccinated or previously infected hamsters.

The ongoing SARS-CoV-2 epidemic was marked by the repeated emergence and replacement of "variants" with genetic and phenotypic distance from the ancestral strains, the most recent examples being viruses of the Omicron lineage. Here, we describe a hamster direct contact exposure challenge model to assess protection against reinfection conferred by either vaccination or prior infection. We found that two doses of self-amplifying RNA vaccine based on the ancestral Spike ameliorated weight loss following Delta infection and decreased viral loads but had minimal effect on Omicron BA.1 infection. Prior vaccination followed by Delta or BA.1 breakthrough infections led to a high degree of cross-reactivity to all tested variants, suggesting that repeated exposure to antigenically distinct Spikes, via infection and/or vaccination drives a cross-reactive immune response. Prior infection with ancestral or Alpha variant was partially protective against BA.1 infection, whereas all animals previously infected with Delta and exposed to BA.1 became reinfected, although they shed less virus than BA.1-infected naive hamsters. Hamsters reinfected with BA.1 after prior Delta infection emitted infectious virus into the air, indicating that they could be responsible for onwards airborne transmission. We further tested whether prior infection with BA.1 protected from reinfection with Delta or later Omicron sublineages BA.2, BA.4, or BA.5. BA.1 was protective against BA.2 but not against Delta, BA.4, or BA.5 reinfection. These findings suggest that cohorts whose only immune experience of COVID-19 is Omicron BA.1 infection may be vulnerable to future circulation of reemerged Delta-like derivatives, as well as emerging Omicron sublineages.

Weak Genetic Isolation and Putative Phenotypic Selection in the Wild Carnation Dianthus virgineus (Caryophyllaceae).

By relating genetic divergence at neutral loci, phenotypic variation, and geographic and environmental distances, it is possible to dissect micro-evolutionary scenarios involving natural selection and neutral evolution. In this work, we tested the patterns of intraspecific genetic and phenotypic variation along an elevational gradient, using Dianthus virgineus as study system. We genotyped genome-wide SNPs through ddRAD sequencing and quantified phenotypic variation through multivariate morphological variation. We assessed patterns of variation by testing the statistical association between genetic, phenotypic, geographic, and elevational distances and explored the role of genetic drift and selection by comparing the Fst and Pst of morphometric traits. We revealed a weak genetic structure related to geographic distance among populations, but we excluded the predominant role of genetic drift acting on phenotypic traits. A high degree of phenotypic differentiation with respect to genetic divergence at neutral loci allowed us to hypothesize the effect of selection, putatively fuelled by changing conditions at different sites, on morphological traits. Thus, natural selection acting despite low genetic divergence at neutral loci can be hypothesized as a putative driver explaining the observed patterns of variation.

Heterosis of quality protein maize inbred lines for agronomic traits and association with genetic distances based on SSR and phenotypic markers

Due to high cost, limited labour, and longer time required in hybrid development, identifying promising hybrids at an early stage without large-scale yield trials is crucial. Therefore this study estimated heterosis of quality protein maize hybrids for grain yield (GY) and other agronomic traits and investigated relationship of genetic and phenotypic distances (GD, PD) of inbreds with hybrid performance (HP) and mid-and-better parent heterosis (MPH, BPH). Forty-five hybrids generated by half-diallel with 10 inbreds were evaluated for GY and other agronomic traits at three locations. The yield trials were conducted for two years (2017 and 2018 cropping seasons). The GD and PD were 0.45 and 0.40 based on SSR and phenotypic data, respectively, this shows moderate genetic variation existed among inbreds. GY had highest MPH (77.55%) and BPH (53.96%) with hybrid TZEEQI-9 × TZEEQI-16 having highest MPH (382.8%) and BPH (331.7%), across locations. Positive and significant association existed between SSR-GD with HP, MPH and BPH for ear length, kernels/row and 100-seed weight (r = 0.31** to 0.41**), this suggests these traits can be predicted from SSR-based GD of parents. These traits could be used for indirect selection for yield improvement. However, negative correlation was obtained between SSR-GD with HP, MPH and BPH for anthesis and silking (r = −0.29 to −0.03), this indicates the dominance for earliness to flowering and silking than their parental lines. The two distance measures can be used to differentiate between maize inbreds and assigned them to different heterotic groups and Breeders can therefore prioritize crosses with high heterosis and desirable phenotypic traits, saving time, resources, and field space.

Core Collection Formation in Guatemalan Wild Avocado Germplasm with Phenotypic and SSR Data

Guatemala’s wild avocado germplasm holds vital genetic value, but lacking conservation strategies imperils it. Studying its diversity is pivotal for conservation and breeding. The study aimed to comprehensively assess the wild avocado germplasm in Guatemala by combining phenotypic and genotypic data and to create a core collection for conservation and future breeding programs. A total of 189 mature avocado trees were sampled across Guatemala’s northern, southern, and western regions. Morphological characteristics were documented, and genetic diversity was assessed using 12 SSR loci. The investigated germplasm revealed three distinct genetic clusters, exhibiting an average gene diversity of 0.796 and a 7.74% molecular variation among them. The samples showed various morphological characteristics that indicate the presence of three avocado races in Guatemala. The weak correlation between phenotypic and genotypic distances highlighted their independence and complementary nature. The joint matrix effectively integrated and captured genotypic and phenotypic data for comprehensive genetic diversity analysis. A core collection comprising 20% of total accessions that captured maximum genetic diversity was formed. This study exposed wild Guatemalan avocados’ genetic diversity, morphological traits, and conservation significance. Integrated data capture via clustering validates holistic genetic insight for conservation and breeding strategies.

Microsatellite markers’ based molecular divergence among the breeding lines of aromatic marigold (Tagetes minuta L.)

Aromatic marigold (Tagetes minuta L.) is an essential oil-bearing plant of industrial value. The essential oil obtained from the plant has high demand in the flavor and perfume industry. The present study investigates the molecular diversity patterns using microsatellite markers in 126 breeding lines representing three groups (higher, intermediate, and lower biomass) based on phenotypic characterization. These lines are being maintained through repeated selfing. A total of 503 alleles with an average of 16.23 alleles per locus were detected at 31 SSR loci over all the genotypes. The average most common and rare alleles were 3.35 and 12.87, respectively, over all the studied loci. The high polymorphic information content (0.88) and genetic diversity (0.89) indicate high allelic diversity among the genotypes studied. Ten genotype-specific markers were identified. Significant molecular variances have been observed among the groups (3 %), among individuals (72 %), and within individuals (26 %). The unweighted neighbor-joining clustering based on a simple matching dissimilarity index grouped all 126 genotypes into five major clusters. The clustering pattern primarily follows the biomass-specific distribution of populations. The principle coordinate analysis depicts considerable variations and again confirms the biomass-specific grouping of genotypes. The highly significant positive association between genotypic and phenotypic distances indicates the importance of these marker loci for future marker-assisted selection and association mapping studies.

Convergence in sympatric swallowtail butterflies reveals ecological interactions as a key driver of worldwide trait diversification

Ecological interactions can promote phenotypic diversification in sympatric species. While competition can enhance trait divergence, other ecological interactions may promote convergence in sympatric species. Within butterflies, evolutionary convergences in wing color patterns have been reported between distantly related species, especially in females of palatable species, where mimetic color patterns are promoted by predator communities shared with defended species living in sympatry. Wing color patterns are also often involved in species recognition in butterflies, and divergence in this trait has been reported in closely related species living in sympatry as a result of reproductive character displacement. Here, we investigate the effect of sympatry between species on the convergence vs. divergence of their wing color patterns in relation to phylogenetic distance, focusing on the iconic swallowtail butterflies (family Papilionidae). We developed an unsupervised machine learning-based method to estimate phenotypic distances among wing color patterns of 337 species, enabling us to finely quantify morphological diversity at the global scale among species and allowing us to compute pairwise phenotypic distances between sympatric and allopatric species pairs. We found phenotypic convergence in sympatry, stronger among distantly related species, while divergence was weaker and restricted to closely related males. The convergence was stronger among females than males, suggesting that differential selective pressures acting on the two sexes drove sexual dimorphism. Our results highlight the significant effect of ecological interactions driven by predation pressures on trait diversification in Papilionidae and provide evidence for the interaction between phylogenetic proximity and ecological interactions in sympatry, acting on macroevolutionary patterns of phenotypic diversification.

Migration and biological continuity in central Mexico during the Classic-Epiclassic transition.

The role of migration in the cultural development of central Mexico has long been debated. Archaeological models suggest that central Mexico likely experienced increased migration during the Epiclassic period (600-900 CE) and that migrants may have originated in northwestern Mexico. While previous biodistance analyses of Classic and Postclassic populations have come to similar conclusions, none have incorporated Epiclassic skeletal populations. This study uses multi-scalar biodistance analyses to directly evaluate archaeological Epiclassic migration models within central Mexico. This study uses finite mixture and relationship (R) matrix analyses of cervicometric tooth dimensions to reconstruct patterns of biological affinity among Classic and Epiclassic Mesoamerican populations (n = 333), including at the central Mexican Epiclassic shrine site of Non-Grid 4 where the remains of at least 180 individuals were interred. Estimated inter-site phenotypic distances demonstrate support for some degree of both biological continuity and extra-local gene flow within central Mexican populations during the Classic-Epiclassic transition. Furthermore, estimated phenotypic distances and finite mixture posterior probabilities indicate central Mexican Epiclassic populations were biologically diverse, originating from various source populations throughout Mesoamerica, including the Bajío region, the Malpaso Valley, and the Oaxaca Valley. Results suggest that emphasizing both local and extra-local gene flow rather than population replacement may be more appropriate to understand central Mexican population structure during the Classic-Epiclassic transition. Moreover, analyses support previous archaeological migration models positing that Epiclassic migrants into central Mexico originated in northwestern Mexico, but also find evidence of Epiclassic migrants originating from previously unanticipated locales like southern Mexico.

841-P: Phenomapping-Derived Tool to Personalize Chiglitazar Treatment in Type 2 Diabetes—A Post Hoc Analysis of Randomised Clinical Trials

Chiglitazar is a peroxisome proliferator-activated receptor (PPAR) pan-agonist showing comparable glucose-lowering efficacy with sitagliptin in patients with type 2 diabetes. To identify the subgroup with higher benefits with chiglitazar thus personalizes drug therapy, a post-hoc analysis using a machine learning algorithm was applied in ChiglitAzar Monotherapy with Placebo (CAMP) and ChiglitAzar Monotherapy with Sitagliptin (CAMS) study. We constructed a phenomap based on 13 baseline variables from 1069 patients with diabetes assigned to chiglitazar (32mg or 48mg, n=822) and sitagliptin (n=247). Personalized HbA1c decline at week 24 was estimated using least squares regression weighted for phenotypic distances between each participant. High-benefit group (HBG) was defined as patients with estimated HbA1c decline higher in chiglitazar than sitagliptin, and low-benefit group (LBG) was defined as the opposite.677 (63.3%) patients were allocated to the HBG and 392 (36.7%) were allocated to the LBG. Chiglitazar showed higher HbA1c decline than sitagliptin In the HBG and lower HbA1c decline in the LBG (relative decline 0.67%, 95%CI [0.50, 0.83] in HBG and -0.93% [-1.18, -0.68] in LBG, p for interaction&amp;lt;0.001). There was no significant inter-group heterogeneity in changes in HOMA-IR, HDL, triglyceride and body weight. Dosage analysis suggested the majority (n=635, 77.3%) would gain more glucose-lowering benefits from chiglitazar 48mg than 32mg. To facilitate efficient identification of HBG in the clinic, we developed ML-PANPPAR, a machine learning model based on extreme gradient boosting algorithm (XGBoost). The model showed robust performance (AUC=0.933 in the internal testing subset) to recognise HBG with five simple variables including sex, BMI, HbA1c, HDL and fasting insulin.Our phenomapping-derived tool provides support to select specific patients to receive chiglitazar for better glucose-lowering efficacy. Disclosure Q.Huang: None. X.Zou: None. W.Jia: None. L.Ji: Other Relationship; Eli Lilly and Company, Novo Nordisk, Merck &amp; Co., Inc., Bayer Inc., Sanofi-Aventis U.S., Roche Pharmaceuticals, MSD Life Science Foundation, AstraZeneca, Boehringer Ingelheim Inc., Abbott, Metronics. Funding Beijing Nova Cross Program (Z211100002121169); Beijing Nova Program of Science and Technology (Z191100001119026 to X.Z.)

The Limits of Evolutionary Convergence in Sympatry: Reproductive Interference and Historical Constraints Leading to Local Diversity in Warning Traits.

AbstractMutualistic interactions between defended species represent a striking case of evolutionary convergence in sympatry, driven by the increased protection against predators brought by mimicry in warning traits. However, such convergence is often limited: sympatric defended species frequently display different or imperfectly similar warning traits. The phylogenetic distance between sympatric species may indeed prevent evolution toward the exact same signal. Moreover, warning traits are also involved in mate recognition, so trait convergence might result in heterospecific courtship and mating. Here, we develop a mathematical model to investigate the strength and direction of the evolution of warning traits in defended species with different ancestral traits. Specifically, we determine the effect of phenotypic distances between ancestral trait states of sympatric defended species and of the costs of heterospecific sexual interactions on imperfect mimicry and trait divergence. Our analytical results confirm that reproductive interference and historical constraints limit the convergence of warning traits, leading to either complete divergence or imperfect mimicry. Our model reveals that imperfect mimicry evolves only when ancestral trait values differ between species because of historical constraints and highlights the importance of female and predator discrimination in the evolution of such imperfect mimicry. Our study thus provides new predictions on how reproductive interference interacts with historical constraints and may promote the emergence of novel warning traits, enhancing mimetic diversity.

Individualising intensive systolic blood pressure reduction in hypertension using computational trial phenomaps and machine learning: a post-hoc analysis of randomised clinical trials

The cardiovascular benefits of intensive systolic blood pressure control vary across clinical populations tested in large randomised clinical trials. We aimed to evaluate the application of machine learning to clinical trials of patients without and with type 2 diabetes to define the personalised cardiovascular benefit of intensive control of systolic blood pressure. In SPRINT, a trial of intensive (systolic blood pressure <120 mm Hg) versus standard (systolic blood pressure <140 mm Hg) systolic blood pressure control in patients without type 2 diabetes, we defined a phenotypic representation of the study population using 59 baseline variables. We extracted personalised treatment effect estimates for the primary outcome, time-to-first major adverse cardiovascular event (MACE; cardiovascular death, myocardial infarction or acute coronary syndrome, stroke, and acute decompensated heart failure), through iterative Cox regression analyses providing average hazard ratio (HR) estimates weighted for the phenotypic distance of each participant from the index patient of each iteration. Next, we trained an extreme gradient boosting algorithm (known as XGBoost) to predict the personalised effect of intensive systolic blood pressure control using features most consistently linked to increased personalised benefit, before evaluating its performance in the ACCORD BP trial of patients with type 2 diabetes randomly assigned to receive intensive versus standard systolic blood pressure control. We stratified patients based on their predicted treatment effect, and key demographic groups (age, sex, cardiovascular disease, and smoking). We assessed the presence of heterogeneity with an interaction test, and assessed the performance of the algorithm in a simulation analysis of SPRINT in the presence or absence of an artificially introduced heterogeneous treatment effect. From SPRINT, we included all 9361 study participants (mean age 67·9 years [SD 9·4], 3332 [35·6%] female) who underwent randomisation to either intensive (n=4678) or standard (n=4683) treatment. The median individualised HR for MACE was 0·63 (IQR 0·53-0·78). An eight-feature tool built for this analysis to predict personalised benefit in SPRINT was externally tested in ACCORD BP (4733 participants (mean age 62·7 years [SD 6·7], 2258 [47·7%] female), wherein it successfully identified individuals with differential benefit from intensive versus standard systolic blood pressure control (adjusted HR for MACE of 0·70 [95% CI 0·55-0·90] in individuals with above-median MACE benefit versus 1·05 [95% CI 0·84-1·32] for below-median predicted benefit; pinteraction=0·0184). Subgroup analysis based on age (<65 years: HR 0·89 [95% CI 0·71-1·12]; ≥65 years: 0·85 [0·67-1·09]), sex (male: 0·89 [0·72-1·10]; female: 0·85 [0·65-1·10]), established cardiovascular disease (no: 0·89 [0·70-1·14]; yes: 0·84 [0·67-1·06]), or active smoking (no: 0·85 [0·71-1·02]; yes: 1·01 [0·64-1·60]) did not identify groups with heterogeneity of treatment effect. In a simulation analysis of SPRINT, the proposed algorithm detected groups with heterogeneous treatment effects in the presence, but not absence, of simulated subgroup differences. By use of machine learning to define an individual's personalised benefit through phenotypic representations of clinical trials, we created a practical tool for individualising the selection of intensive versus standard systolic blood pressure control in patients without and with type 2 diabetes. National Heart, Lung, and Blood Institute of the US National Institutes of Health.

A(H3N2) antigenic variation of influenza is associated with low vaccine efficacy in the early 2018 influenza season in Mexico City

ObjectivesWe evaluated the VE and the mutations of the viruses present in the Mexican population at the beginning of 2018. MethodsWe diagnosed influenza in outpatients with a high-performance Rapid Influenza Diagnostic Test (RIDT) qRT–PCR. Descriptive statistics were used to describe the study population, while the chi-square test was used to determine clinical variables. VE was analyzed through a negative test design. We sequenced the hemagglutinin (HA) gene, performed a phylogenetic analysis, and analyzed the nonsynonymous substitutions both in and outside antigenic sites. ResultsOf the 240 patients analyzed, 42.5% received the trivalent vaccine, and 37.5% were positive for influenza. The VE for the general population for any influenza virus type or subtype was 37.0%, while the VE for the predominant influenza A(H3N2) subtype was the lowest (19.7%). The phylogenetic analysis of HA showed the co-circulation of clades and subclades 3C.2a1, 3C.2a1b, 3C.2a2, 3C.2a2re, 3C.2a3, and 3C.3a with identities approximately 97-98% similar to the vaccine composition. ConclusionLow VE was related to the co-circulation of multiple clades and subclades of influenza A(H3N2), with sufficient genetic and phenotypic distance to allow for the infection of vaccinated individuals.

Whole Genome Sequencing and Morphological Trait-Based Evaluation of UPOV Option 2 for DUS Testing in Rice.

To evaluate the application potential of high-density SNPs in rice distinctness, uniformity, and stability (DUS) testing, we screened 37,929 SNP loci distributed on 12 rice chromosomes based on whole-genome resequencing of 122 rice accessions. These SNP loci were used to analyze the DUS testing of rice varieties based on the correlation between the molecular and phenotypic distances of varieties according to UPOV option 2. The results showed that statistical algorithms and the number of phenotypic traits and SNP loci all affected the correlation between the molecular and phenotypic distances of rice varieties. Relative to the other nine algorithms, the Jaccard similarity algorithm had the highest correlation of 0.6587. Both the number of SNPs and the number of phenotypes had a ceiling effect on the correlation between the molecular and phenotypic distances of varieties, and the ceiling effect of the number of SNP loci was more obvious. To overcome the correlation bottleneck, we used the genome-wide prediction method to predict 30 phenotypic traits and found that the prediction accuracy of some traits, such as the basal sheath anthocyanin color, glume length, and intensity of the green color of the leaf blade, was very low. In combination with group comparison analysis, we found that the key to overcoming the ceiling effect of correlation was to improve the resolution of traits with low predictive values. In addition, we also performed distinctness testing on rice varieties by using the molecular distance and phenotypic distance, and we found that there were large differences between the two methods, indicating that UPOV option 2 alone cannot replace the traditional phenotypic DUS testing. However, genotype and phenotype analysis together can increase the efficiency of DUS testing.

Speciation in a metapopulation model upon environmental changes

We propose a metapopulation model to investigate the role of environmental changes in shaping species diversity. The model is studied under the framework of the Fisher geometric model, which assumes the existence of an optimal phenotype in each patch. The phenotypic distance rules out the survivorship of the individuals in a patch to the optimal phenotype. Additionally, we provide our model a genetic ground, such that changes in phenotype are associated with mutational events. One simulates environmental changes as shifts of the optimum phenotype. Quite surprisingly, we find that the pattern of speciation depends only on the net effect of the environmental disturbances in a given time interval, no matter the rate at which the events occur. We also observe that migration has a pivotal role in shaping diversity due to its substantial effects on the genetic distance among individuals at small and intermediate values of the strength of selection.

Temperature Affects Antagonism Among Coral-Associated Bacteria

Reef-building corals are invertebrate animals that associate with diverse microorganisms, including Symbiodiniaceae, bacteria, fungi, and archaea. This symbiotic consortium, called the holobiont, is a dynamic system and rapidly responds to environmental temperatures. At present, the effects of temperature on bacteria-bacteria interactions in the coral-associated bacterial community are not clear. Antagonism is considered one of the potential structuring forces in coral microbial communities. Here, we examined the antagonistic interactions among 32 coral-associated bacteria and the physiological and biochemical characteristics of these isolates at different temperatures. The results showed that the antagonism breadth (i.e. the total number of antagonistic interactions) increased but antagonism intensity (i.e. the size of the inhibition zone) decreased at 32°C. The antagonistic interaction network was nested and sender-determined both at 25°C and 32°C, suggesting that the competition networks of coral-associated bacteria were more influenced by the antagonist strains than sensitive strains. Furthermore, we found that the elevated temperature increased the complexity of the antagonistic network. By evaluating the correlations between antagonism and the phylogenetic and phenotypic distances, we demonstrated that the antagonism probability correlated with the phylogenetic distance rather than phenotypic distance. Moreover, the antagonist strains have a wider metabolic niche space, i.e., grew on more carbon sources, than the antagonized strains at 25°C, while there was no difference at 32°C, suggesting the trade-off between antagonism and resource exploitation shifted in the antagonistic interactions under the higher temperature. These findings will be helpful for understanding the bacterial interactions in coral holobionts and the assembly of bacterial community in altered environments, especially under heat stress.

Морфологическое разнообразие лиственницы Каяндера (Larix сajanderi Mayr) по форме семенных чешуй шишек в пенжинской популяции (Северная Корякия)

The diversity in the shape of cone scales of Larix cajanderi Mayr in the Penzhina population (North of Koryakia) was estimated using geometric morphometry methods. The study aimed in comparing the Penzhina population with other larch populations in Northeast Asia by the shape of cone scales and in identifying its geographical connections. A sample of 360 cones, collected from 36 larch trees in the middle reaches of the Penzhina River, was analyzed. Scales taken from the middle part of the cones were scanned, and outline points were placed with the screen digitizer using angular algorithm. Fourteen morphotypes of cone scales were distinguished by pairwise comparison of samples from each tree using Bootstrap resampling-based Goodall\'s F-test. These morphotypes were compared with those previously determined in the larch populations from Yakutia, Magadan Oblast, and the Kamchatka Peninsula. The morphotypes composition and frequency were used to determine phenotypic distances between populations. Cluster analysis and multidimensional scaling of the phenotypic distances were applied for ordination of the larch populations. All Penzhina morphotypes corresponded to the morphotypes of cone scales previously identified in the Yakutia and Magadan Cajander larch populations; two morphotypes were found earlier in the Kamchatka populations. By the shape of cone scales, the larch of the Penzhina population is close to the Yakutia populations of L. cajanderi. One can assume that the formation of larch forests in the Penzhina River valley mainly occurred due to the settlement of the larch from the Yakutia Pleistocene refugia. The Kamchatka cone scale morphotypes identical to those found in the Penzhina and Kolyma larch populations may indicate the migration of larch from the continent to the peninsula.

Association between Phenotypic and Genotypic Distance Matrices of Advanced Breeding Lines of Lowland Rice (Oryza sativa L.) from Diverse Parents

Background: The major staple food of the world, rice, is known for preferences in dietary diversification among the communities. Evaluation of advanced breeding lines developed from a set of diverse parents involved in different cross combination facilitates selection of promising genotypes, resource management and planning further breeding activities.&#x0D; Methods: Totally, 22 advanced breeding lines of lowland rice in F7 were evaluated based on agro-morphologically and genotypically with molecular markers. Here we report correspondence between different distance matrices subjected to correlation based on Mantel test.&#x0D; Results: Non significant (p-value &gt; 0.05) correlation was observed between the matrices due to causal factors such as data type, markers used and genetic properties of lines as explained in the text. However, certain promising lines were selected from phenotypic performance as well as molecular fingerprints and grain quality evaluation relative to checks (CAUR1 and Shasarang) with specific context to north eastern hill region.