Computable species descriptions and nanopublications: applying ontology-based technologies to dung beetles (Coleoptera, Scarabaeinae).

Background: Taxonomy has long struggled with analysing vast amounts of phenotypic data due to computational and accessibility challenges. Ontology-based technologies provide a framework for modelling semantic phenotypes that are understandable by computers and compliant with FAIR principles. In this paper, we explore the use of Phenoscript, an emerging language designed for creating semantic phenotypes, to produce computable species descriptions. Our case study centers on the application of this approach to dung beetles (Coleoptera, Scarabaeinae). New information: We illustrate the effectiveness of Phenoscript for creating semantic phenotypes. We also demonstrate the ability of the Phenospy python package to automatically translate Phenoscript descriptions into natural language (NL), which eliminates the need for writing traditional NL descriptions. We introduce a computational pipeline that streamlines the generation of semantic descriptions and their conversion to NL. To demonstrate the power of the semantic approach, we apply simple semantic queries to the generated phenotypic descriptions. This paper addresses the current challenges in crafting semantic species descriptions and outlines the path towards future improvements. Furthermore, we discuss the promising integration of semantic phenotypes and nanopublications, as emerging methods for sharing scientific information. Overall, our study highlights the pivotal role of ontology-based technologies in modernising taxonomy and aligning it with the evolving landscape of big data analysis and FAIR principles.

Cypermethrin exposure: Implications for growth, phenotypic attributes, and biochemical responses in monosex tilapia (Oreochromis niloticus).

The present study was conducted to evaluate the effects of exposure to sublethal concentrations of cypermethrin on growth, phenotypic traits, and metabolic and antioxidant enzymes activities of monosex tilapia (Oreochromis niloticus). The median lethal concentration (LC50) of cypermethrin was initially ascertained to be 0.04 ppm after 12 h of exposure to three concentrations (0.04, 0.20, and 1.0 ppm) via the Probit analysis method. The sublethal exposures were obtained for 3 months at 0.0016, 0.008, and 0.04 ppm of cypermethrin. The growth performance, phenotypic traits, and enzymatic activity were analyzed. The research findings revealed a notable impact of cypermethrin on the growth performance of monosex tilapia, with a significant (p < 0.05) decrease in weight observed as the concentration increased. The experiment documented a significant change (p < 0.05) in the phenotypic traits of standard length, total length, tail length, trunk length, eye diameter, body area, and color patterns, but not dressing percentage. Furthermore, it was observed that the activities of amylase and protease in both the intestine and muscle decreased significantly (p < 0.05) with increasing concentrations of cypermethrin, except for amylase in the muscle, where no significant change was noted (p > 0.05). The results also demonstrated significant reductions (p < 0.05) in the activity of metabolic enzymes, specifically superoxide dismutase and catalase, following exposure to sublethal levels of cypermethrin. The study suggested that sublethal exposure of pyrethroid alters the growth, phenotypic traits, metabolic enzymes activities, and immunity of monosex tilapia.

Transcriptomic and metabolomic profiling reveals molecular regulatory network involved in flower development and phenotypic changes in two Lonicera macranthoides varieties.

Due to the medicinal importance of the flowers of Xianglei type (XL) Lonicera macranthoides, it is important to understand the molecular mechanisms that underlie their development. In this study, we elucidated the transcriptomic and metabolomic mechanisms that underlie the flower development mechanism of two L. macranthoides varieties. In this study, 3435 common differentially expressed unigenes (DEGs) and 1138 metabolites were identified. These common DEGs were mainly enriched in plant hormone signal transduction pathways. Metabolomic analysis showed that amino acids were the main metabolites of differential accumulation in wild-type (WT) L. macranthoides, whereas in XL, they were flavonoids and phenylalanine metabolites. Genes and transcription factors (TFs), such as MYB340, histone deacetylase 1 (HDT1), small auxin-up RNA 32 (SAUR32), auxin response factor 6 (ARF6), PIN-LIKES 7 (PILS7), and WRKY6, likely drive metabolite accumulation. Plant hormone signals, especially auxin signals, and various TFs induce downstream flower organ recognition genes, resulting in a differentiation of the two L. macranthoides varieties in terms of their developmental trajectories. In addition, photoperiodic, autonomous, and plant hormone pathways jointly regulated the L. macranthoides corolla opening. SAUR32, Arabidopsis response regulator 9 (ARR9), Gibberellin receptor (GID1B), and Constans-like 10 (COL10) were closely related to the unfolding of the L. macranthoides corolla. These findings offer valuable understanding of the flower growth process of L. macranthoides and the excellent XL phenotypes at the molecular level. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-024-04019-1.

Complex nitrogen sources from agro-industrial byproducts: impact on production, multi-stress tolerance, virulence, and quality of Beauveria bassiana blastospores.

We investigated the impact of various complex organic nitrogen sources on the submerged liquid fermentation of Beauveria bassiana, a versatile entomopathogenic fungus known for producing hydrophilic yeast-like single cells called blastospores. Specifically, we examined yeast extract, autolyzed yeast, inactive yeast, cottonseed flour, corn bran, and corn gluten meal as nitrogen compounds with different carbon-to-nitrogen (C:N) ratios. Our comprehensive analysis encompassed blastospore production, tolerance to abiotic stresses, shelf stability after drying, and virulence against mealworm larvae, crucial attributes for developing effective blastospore-based biopesticides. Notably, cottonseed flour emerged as the optimal nitrogen source, yielding up to 2.5 × 109 blastospores/mL within 3 days in a bioreactor. These blastospores exhibited the highest tolerance to heat stress and UV-B radiation exposure. The endogenous C:N ratio in blastospore composition was also impacted by nitrogen sources. Bioassays with mealworm larvae demonstrated that blastospores from cottonseed flour were the most virulent, achieving faster lethality (lower LT50) and requiring a lower inoculum (LC50). Importantly, blastospores produced with cottonseed flour displayed extended viability during storage, surpassing the retention of viability compared to those from autolyzed yeast over 180 days at 4°C. Despite differences in storage viability, both nitrogen sources conferred similar long-term blastospore bioactivity against mealworms. In summary, this research advances our understanding of the crucial impact of complex organic nitrogen selection on the phenotypic traits of blastospores in association with their intracellular C:N ratio, contributing to the production of ecologically fit, shelf-stable, and virulent propagules for effective pest biocontrol programs. IMPORTANCE: Biological control through entomopathogenic fungi provides essential ecological services in the integrated management of agricultural pests. In the context of submerged liquid fermentation, the nutritional composition significantly influences the ecological fitness, virulence and quality of these fungi. This study specifically explores the impact of various complex organic nitrogen sources derived from agro-industrial byproducts on the submerged liquid fermentation of Beauveria bassiana, a versatile entomopathogenic fungus known for producing hydrophilic yeast-like blastospores. Notably, manipulating the nitrogen source during submerged cultivation can influence the quality, fitness, and performance of blastospores. This research identifies cottonseed flour as the optimal low-cost nitrogen source, contributing to increased production yields, enhanced multi-stress tolerance, heightened virulence with extended shelf life and long-term bioactivity. These findings deepen our understanding of the critical role of nitrogen compound selection in liquid media formulation, facilitating the production of ecologically fit and virulent blastospores for more effective pest biocontrol programs.

The diversity of endophytic fungi in Tartary buckwheat (Fagopyrum tataricum) and its correlation with flavonoids and phenotypic traits.

Tartary buckwheat (Fagopyrum tataricum) is a significant medicinal crop, with flavonoids serving as a crucial measure of its quality. Presently, the artificial cultivation of Tartary buckwheat yields low results, and the quality varies across different origins. Therefore, it is imperative to identify an effective method to enhance the yield and quality of buckwheat. Endophytic fungi reside within plants and form a mutually beneficial symbiotic relationship, aiding plants in nutrient absorption, promoting host growth, and improving secondary metabolites akin to the host. In this study, high-throughput sequencing technology was employed to assess the diversity of endophytic fungi in Tartary buckwheat. Subsequently, a correlation analysis was performed between fungi and metabolites, revealing potential increases in flavonoid content due to endophytic fungi such as Bipolaris, Hymenula, and Colletotrichum. Additionally, a correlation analysis between fungi and phenotypic traits unveiled the potential influence of endophytic fungi such as Bipolaris, Buckleyzyma, and Trichosporon on the phenotypic traits of Tartary buckwheat. Notably, the endophytic fungi of the Bipolaris genus exhibited the potential to elevate the content of Tartary buckwheat metabolites and enhance crop growth. Consequently, this study successfully identified the resources of endophytic fungi in Tartary buckwheat, explored potential functional endophytic fungi, and laid a scientific foundation for future implementation of biological fertilizers in improving the quality and growth of Tartary buckwheat.

Does testosterone underly the interplay between male traits and territorial behavior in neotropical poison frogs?

The ability of individual animals to defend a territory as well as various phenotypic and behavioral traits may be targets of sexual selection used by males to evaluate their competitors or by females to choose males. A frequent question in animal behavior is whether male traits and characteristics of their territory are correlated and what are the mechanisms that may mediate such associations when they exist. Because hormones link phenotype to behavior, by studying the role of testosterone in territoriality one may come closer to understanding the mechanisms mediating correlations or lack thereof between characteristics of territories and of males. We evaluated whether variation in characteristics of territories (size and quality) are correlated with variation in morphology, coloration, testosterone, heterozygosity, and calls in two species of poison frogs. The Amazonian frog Allobates aff. trilineatus exhibits male care and defends territories only during the breeding season, while the endangered frog Oophaga lehmanni displays maternal care and defends territories throughout the year. We found that morphological traits (body length, weight, thigh size), call activity, and testosterone levels correlated with size and various indicators of quality of the territory. However, the direction of these correlations (whether positive or negative) and which specific morphological, acoustic traits or testosterone level variables covaried depended on the species. Our findings highlight an endocrine pathway as part of the physiological machinery that may underlie the interplay between male traits and territorial behavior. We were able to identify some male traits related to territory attributes, but whether females choose males based on these traits requires further research.

Characterization of phenotypic traits associated with anthracnose resistance in selected common bean (Phaseolus vulgaris L.) breeding material.

Anthracnose caused by Colletotrichum lindemuthianum is the major common bean disease worldwide causing complete yield loss under favourable disease conditions. This study aimed to determine phenotypic traits associated with anthracnose resistance for future use in breeding programmes. Twenty-two common bean varieties (CBVs) were selected basing on susceptibility to anthracnose, advanced breeding lines, improved variety resembling advanced breeding lines and the farmer variety widely grown in Tanzania. Selected varieties were planted in anthracnose hotspot fields and the same CBVs were planted in a screen house to validate resistance to anthracnose. Anthracnose infection score, leaf length, leaf width, length of fifth internode, length of petiole, plant vigour, canopy height and canopy width were recorded. Data on number of plants emerging; days to flowering; days to maturity; plant stands at harvest; and grain yield were also collected and analysed using R software. Phenotypic traits evaluated differed significantly among genotypes, environment and genotype by environment interaction. Seventy-five percent of phenotypic traits evaluated were positively correlated to anthracnose resistance. Highly-strong correlations to anthracnose were observed on number of days to maturity, plant stands at harvest, plant vigour and grain yield. Leaf length, leaf width, length of fifth internode, length of petiole and number of stands emerging were strongly correlated to anthracnose resistance. Additive main effects and multiplicative interaction analysis (AMMI) revealed highest contribution of environment on anthracnose infection-58.9% and grain yield -84.9% compared to genotype effects on anthracnose infection -32.7% and grain yield-15.7%. Based on these results, four traits - plant vigour, number of days to maturity, number of plant stands at harvest and grain yield - are recommended for selecting anthracnose-resistant varieties. NUA 48, NUA 64 and RWR 2154 were superior varieties, resistant to anthracnose and high yielding, while Sweet Violet and VTT 923-23-10 were most stable varieties across environments. Further on-farm research is suggested to assess their performance and identify traits preferred by farmers.

Advanced deep learning models for phenotypic trait extraction and cultivar classification in lychee using photon-counting micro-CT imaging.

Introduction: In contemporary agronomic research, the focus has increasingly shifted towards non-destructive imaging and precise phenotypic characterization. A photon-counting micro-CT system has been developed, which is capable of imaging lychee fruit at the micrometer level and capturing a full energy spectrum, thanks to its advanced photon-counting detectors. Methods: For automatic measurement of phenotypic traits, seven CNN-based deep learning models including AttentionUNet, DeeplabV3+, SegNet, TransUNet, UNet, UNet++, and UNet3+ were developed. Machine learning techniques tailored for small-sample training were employed to identify key characteristics of various lychee species. Results: These models demonstrate outstanding performance with Dice, Recall, and Precision indices predominantly ranging between 0.90 and 0.99. The Mean Intersection over Union (MIoU) consistently falls between 0.88 and 0.98. This approach served both as a feature selection process and a means of classification, significantly enhancing the study's ability to discern and categorize distinct lychee varieties. Discussion: This research not only contributes to the advancement of non-destructive plant analysis but also opens new avenues for exploring the intricate phenotypic variations within plant species.

Demographic patterns of walleye (Sander vitreus) reproductive success in a Wisconsin population.

Harvest in walleye Sander vitreus fisheries is size-selective and could influence phenotypic traits of spawners; however, contributions of individual spawners to recruitment are unknown. We used parentage analyses using single nucleotide polymorphisms to test whether parental traits were related to the probability of offspring survival in Escanaba Lake, Wisconsin. From 2017 to 2020, 1339 adults and 1138 juveniles were genotyped and 66% of the offspring were assigned to at least one parent. Logistic regression indicated the probability of reproductive success (survival of age-0 to first fall) was positively (but weakly) related to total length and growth rate in females, but not age. No traits analyzed were related to reproductive success for males. Our analysis identified the model with the predictors' growth rate and year for females and the models with year and age and year for males as the most likely models to explain variation in reproductive success. Our findings indicate that interannual variation (i.e., environmental conditions) likely plays a key role in determining the probability of reproductive success in this population and provide limited support that female age, length, and growth rate influence recruitment.

An Evaluation of the Crop Preference and Phenotypic Characteristics of Ceracris kiangsu Tsai (Orthoptera: Arcypteridae) under Different Temperatures.

The yellow-spined bamboo locust (YSBL), Ceracris kiangsu Tsai, has historically had a significant impact on different bamboo varieties in East Asia and Southeast Asia. Since 2014, there have been many outbreaks of YSBL populations in Laos, and YSBLs subsequently invaded Southwest China in 2020 and 2023. However, there was limited information about the damage to staple crops. Life table parameters and fitness parameters were assessed using wheat, rice, waxy maize, and sweet maize under three different temperatures (25 °C, 30 °C, and 35 °C) in the laboratory. The results indicated that the YSBLs feeding on wheat seedlings displayed a significantly higher survival rate, a shorter developmental time, and a higher adult emergence rate compared to YSBLs feeding on the other host species at 30 °C. The developmental durations of 1st and 3rd instar YSBLs on wheat (1st: 8.21 ± 0.35 d; 3rd: 6.32 ± 0.34 d) and rice (1st: 7.19 ± 0.23 d; 3rd: 9.00 ± 0.66 d) were significantly shorter than those of 1st and 3rd instar YSBLs on waxy maize (1st: 13.62 ± 1.22 d; 3rd: 13.67 ± 6.33 d) and sweet maize (1st: 16.00 ± 1.79 d; 3rd: 18.00 ± 3.49 d) at 30 °C. The body lengths of male and female YSBLs on wheat (male: 29.52 ± 0.40 mm, female: 34.97 ± 0.45 mm) and rice (male: 28.85 ± 0.68 mm, female: 34.66 ± 0.35 mm) were significantly longer than those observed when they were fed on sweet maize (male: 25.64 ± 1.60 mm, female: 21.93 ± 6.89 mm). There were only male adults obtained on waxy maize. The phenotypic characteristics of the YSBLs feeding on rice seedlings were very close to those of the YSBLs feeding on wheat seedlings. A relatively slower decline was observed in the survival rates of YSBL nymphs on wheat and rice compared to those on waxy maize and sweet maize at 25 °C, 30 °C, and 35 °C. In short, this study implied that YSBLs prefer wheat and rice. This study is the first report of direct damage caused by the YSBL to wheat in the laboratory, and its results could be useful in improving our understanding of the host preference of the YSBL and providing strategies for the management of this pest in field crops.

Construction of a High-Density Paulownia Genetic Map and QTL Mapping of Important Phenotypic Traits Based on Genome Assembly and Whole-Genome Resequencing.

Quantitative trait locus (QTL) mapping based on a genetic map is a very effective method of marker-assisted selection in breeding, and whole-genome resequencing is one of the useful methods to obtain high-density genetic maps. In this study, the hybrid assembly of Illumina, PacBio, and chromatin interaction mapping data was used to construct high-quality chromosomal genome sequences of Paulownia fortunei, with a size of 476.82 Mb, a heterozygosity of 0.52%, and a contig and scaffold N50s of 7.81 Mb and 21.81 Mb, respectively. Twenty scaffolds with a total length of 437.72 Mb were assembled into 20 pseudochromosomes. Repeat sequences with a total length of 243.96 Mb accounted for 51.16% of the entire genome. In all, 26,903 protein-coding gene loci were identified, and 26,008 (96.67%) genes had conserved functional motifs. Further comparative genomics analysis preliminarily showed that the split of P. fortunei with Tectona grandis likely occurred 38.8 (33.3-45.1) million years ago. Whole-genome resequencing was used to construct a merged genetic map of 20 linkage groups, with 2993 bin markers (3,312,780 SNPs), a total length of 1675.14 cm, and an average marker interval of 0.56 cm. In total, 73 QTLs for important phenotypic traits were identified (19 major QTLs with phenotypic variation explained ≥ 10%), including 10 for the diameter at breast height, 7 for the main trunk height, and 56 for branch-related traits. These results not only enrich P. fortunei genomic data but also form a solid foundation for fine QTL mapping and key marker/gene mining of Paulownia, which is of great significance for the directed genetic improvement of these species.

Exploring Genetic Markers: Mitochondrial DNA and Genomic Screening for Biodiversity and Production Traits in Donkeys.

Donkeys (Equus asinus) play a pivotal role as essential livestock in arid and semi-arid regions, serving various purposes such as transportation, agriculture, and milk production. Despite their significance, donkey breeding has often been overlooked in comparison to other livestock species, resulting in limited genetic improvement programs. Preserving donkey genetic resources within each country necessitates the establishment of breed conservation programs, focusing on managing genetic diversity among populations. In recent years, significant strides have been made in sequencing and analyzing complete mitochondrial DNA (mtDNA) molecules in donkeys. Notably, numerous studies have honed in on the mitochondrial D-loop region, renowned for its remarkable variability and higher substitution rate within the mtDNA genome, rendering it an effective genetic marker for assessing genetic diversity in donkeys. Furthermore, genetic markers at the RNA/DNA level have emerged as indispensable tools for enhancing production and reproduction traits in donkeys. Traditional animal breeding approaches based solely on phenotypic traits, such as milk yields, weight, and height, are influenced by both genetic and environmental factors. To overcome these challenges, genetic markers, such as polymorphisms, InDel, or entire gene sequences associated with desirable traits in animals, have achieved widespread usage in animal breeding practices. These markers have proven increasingly valuable for facilitating the selection of productive and reproductive traits in donkeys. This comprehensive review examines the cutting-edge research on mitochondrial DNA as a tool for assessing donkey biodiversity. Additionally, it highlights the role of genetic markers at the DNA/RNA level, enabling the informed selection of optimal production and reproductive traits in donkeys, thereby driving advancements in donkey genetic conservation and breeding programs.

Phenotypic evolution in durum wheat (Triticum durum Desf.) based on SNPs, morphological traits, UPOV descriptors and kernel-related traits.

Durum wheat is a worldwide staple crop cultivated mainly in the Mediterranean basin. Progress in durum wheat breeding requires the exploitation of genetic variation among the gene pool enclosed in landraces, old cultivars and modern cultivars. The aim of this study was to provide a more comprehensive view of the genetic architecture evolution among 123 durum wheat accessions (41 landraces, 41 old cultivars and 41 modern cultivars), grown in replicated randomized complete block in two areas, Metaponto (Basilicata) and Foggia (Apulia), using the Illumina iSelect 15K wheat SNP array and 33 plant and kernel traits including the International Union for the Protection of new Varieties of Plants (UPOV) descriptors. Through DAPC and Bayesian population structure five groups were identified according to type of material data and reflecting the genetic basis and breeding strategies involved in their development. Phenotypic and genotypic coefficient of variation were low for kernel width (6.43%) and for grain protein content (1.03%). Highly significant differences between environments, genotypes and GEI (Genotype x Environment Interaction) were detected by mixed ANOVAs for agro-morphological-quality traits. Number of kernels per spike (h2 = 0.02) and grain protein content (h2 = 0.03) were not a heritability character and highly influenced by the environment. Nested ANOVAs revealed highly significant differences between DAPC clusters within environments for all traits except kernel roundness. Ten UPOV traits showed significant diversity for their frequencies in the two environments. By PCAmix multivariate analysis, plant height, heading time, spike length, weight of kernels per spike, thousand kernel weight, and the seed related traits had heavy weight on the differentiation of the groups, while UPOV traits discriminated moderately or to a little extent. The data collected in this study provide useful resources to facilitate management and use of wheat genetic diversity that has been lost due to selection in the last decades.

Multi-index fuzzy comprehensive evaluation model with information entropy of alfalfa salt tolerance based on LiDAR data and hyperspectral image data.

Rapid, non-destructive and automated salt tolerance evaluation is particularly important for screening salt-tolerant germplasm of alfalfa. Traditional evaluation of salt tolerance is mostly based on phenotypic traits obtained by some broken ways, which is time-consuming and difficult to meet the needs of large-scale breeding screening. Therefore, this paper proposed a non-contact and non-destructive multi-index fuzzy comprehensive evaluation model for evaluating the salt tolerance of alfalfa from Light Detection and Ranging data (LiDAR) and HyperSpectral Image data (HSI). Firstly, the structural traits related to growth status were extracted from the LiDAR data of alfalfa, and the spectral traits representing the physical and chemical characteristics were extracted from HSI data. In this paper, these phenotypic traits obtained automatically by computation were called Computing Phenotypic Traits (CPT). Subsequently, the multi-index fuzzy evaluation system of alfalfa salt tolerance was constructed by CPT, and according to the fuzzy mathematics theory, a multi-index Fuzzy Comprehensive Evaluation model with information Entropy of alfalfa salt tolerance (FCE-E) was proposed, which comprehensively evaluated the salt tolerance of alfalfa from the aspects of growth structure, physiology and biochemistry. Finally, comparative experiments showed that: (1) The multi-index FCE-E model based on the CPT was proposed in this paper, which could find more salt-sensitive information than the evaluation method based on the measured Typical Phenotypic Traits (TPT) such as fresh weight, dry weight, water content and chlorophyll. The two evaluation results had 66.67% consistent results, indicating that the multi-index FCE-E model integrates more information about alfalfa and more comprehensive evaluation. (2) On the basis of the CPT, the results of the multi-index FCE-E method were basically consistent with those of Principal Component Analysis (PCA), indicating that the multi-index FCE-E model could accurately evaluate the salt tolerance of alfalfa. Three highly salt-tolerant alfalfa varieties and two highly salt-susceptible alfalfa varieties were screened by the multi-index FCE-E method. The multi-index FCE-E method provides a new method for non-contact non-destructive evaluation of salt tolerance of alfalfa.

Phenotypic Variation Analysis and Excellent Clone Selection of Alnus cremastogyne from Different Provenances.

Alnus cremastogyne is a rapidly growing broad-leaved tree species that is widely distributed in southwest China. It has a significant economic and ecological value. However, with the expansion of the planting area, the influence of phenotypic variation and differentiation on Alnus cremastogyne has increased, resulting in a continuous decline in its genetic quality. Therefore, it is crucial to investigate the phenotypic variation of Alnus cremastogyne and select excellent breeding materials for genetic improvement. Herein, four growth-related phenotypic traits (diameter at breast height, the height of trees, volume, height under the branches) and twelve reproductive-related phenotypic traits (fresh weight of single cone, dry weight of single cone, seed weight per plant, thousand kernel weight, cone length, cone width, cone length × cone width, fruit shape index, seed rate, germination rate, germination potential, germination index) of 40 clones from four provenances were measured and analyzed. The phenotypic variation was comprehensively evaluated by correlation analysis, principal component analysis and cluster analysis, and excellent clones were selected as breeding materials. The results revealed that there were abundant phenotypic traits variations among and within provenances. Most of the phenotypic traits were highly significant differences (p < 0.01) among provenances. The phenotypic variation among provenances (26.36%) was greater than that of within provenances clones (24.80%). The average phenotypic differentiation coefficient was accounted for 52.61% among provenances, indicating that the phenotypic variation mainly came from among provenances. The coefficient of variation ranged from 9.41% (fruit shape index) to 97.19% (seed weight per plant), and the repeatability ranged from 0.36 (volume) to 0.77 (cone width). Correlation analysis revealed a significantly positive correlation among most phenotypic traits. In principal component analysis, the cumulative contribution rate of the first three principal components was 79.18%, representing the main information on the measured phenotypic traits. The cluster analysis revealed four groups for the 40 clones. Group I and group II exhibited better performance phenotypic traits as compared with group III and group IV. In addition, the four groups are not clearly clustered following the distance from the provenance. Employing the multi-trait comprehensive evaluation method, 12 excellent clones were selected, and the average genetic gain for each phenotypic trait ranged from 4.78% (diameter at breast height) to 32.05% (dry weight of single cone). These selected excellent clones can serve as candidate materials for the improvement and transformation of Alnus cremastogyne seed orchards. In addition, this study can also provide a theoretical foundation for the genetic improvement, breeding, and clone selection of Alnus cremastogyne.

Wide-scale identification of novel/eliminated genes responsible for evolutionary transformations.

BACKGROUND: It is generally accepted that most evolutionary transformations at the phenotype level are associated either with rearrangements of genomic regulatory elements, which control the activity of gene networks, or with changes in the amino acid contents of proteins. Recently, evidence has accumulated that significant evolutionary transformations could also be associated with the loss/emergence of whole genes. The targeted identification of such genes is a challenging problem for both bioinformatics and evo-devo research. RESULTS: To solve this problem we propose the WINEGRET method, named after the first letters of the title. Its main idea is to search for genes that satisfy two requirements: first, the desired genes were lost/emerged at the same evolutionary stage at which the phenotypic trait of interest was lost/emerged, and second, the expression of these genes changes significantly during the development of the trait of interest in the model organism. To verify the first requirement, we do not use existing databases of orthologs, but rely purely on gene homology and local synteny by using some novel quickly computable conditions. Genes satisfying the second requirement are found by deep RNA sequencing. As a proof of principle, we used our method to find genes absent in extant amniotes (reptiles, birds, mammals) but present in anamniotes (fish and amphibians), in which these genes are involved in the regeneration of large body appendages. As a result, 57 genes were identified. For three of them, c-c motif chemokine 4, eotaxin-like, and a previously unknown gene called here sod4, essential roles for tail regeneration were demonstrated. Noteworthy, we established that the latter gene belongs to a novel family of Cu/Zn-superoxide dismutases lost by amniotes, SOD4. CONCLUSIONS: We present a method for targeted identification of genes whose loss/emergence in evolution could be associated with the loss/emergence of a phenotypic trait of interest. In a proof-of-principle study, we identified genes absent in amniotes that participate in body appendage regeneration in anamniotes. Our method provides a wide range of opportunities for studying the relationship between the loss/emergence of phenotypic traits and the loss/emergence of specific genes in evolution.

Study on the Phenotypic Diversity of 33 Ornamental Xanthoceras sorbifolium Cultivars.

Xanthoceras sorbifolium, belonging to the family Sapindaceae, has a beautiful tree shape, elegant leaves, large and many brightly colored flowers, and a long flowering duration. This plant is widely applied in gardens. In this study, 33 cultivars of Xanthoceras sorbifolium were selected from the perspective of ornamental properties, and their phenotypic traits, such as leaves, flowers, and branches, were measured and analyzed, and their phenotypic diversity was comprehensively evaluated using principal component analysis, in order to investigate the phenotypic diversity characteristics of Xanthoceras sorbifolium. The results showed that the genetic diversity index of the qualitative traits varied from 0.14 to 1.50, and that of quantitative traits varied from 1.76 to 2.05. The quantitative traits were more diverse than the qualitative traits. The coefficient of variation of the qualitative traits ranged from 16.90% to 57.96%, and that of quantitative traits ranged from 12.92% to 32.87%. The phenotypic traits of the tested cultivars had relatively rich variation. Furthermore, the level of the phenotypic diversity index of Xanthoceras sorbifolium was not consistent with the level of coefficient of variation, indicating large variation and uneven distribution of variation. Through principal component analysis, 17 quantitative characters were extracted into five principal components, with a cumulative contribution rate of 79.82%, representing the primary information on the quantitative characters of ornamental Xanthoceras sorbifolium cultivars. The F value of the 33 samples ranged from -2.79 to 1.93, and the comprehensive scores of seven cultivars were greater than 1, indicating that these cultivars had rich phenotypic diversity. Therefore, the screening, development, and utilization of fine germplasm resources of Xanthoceras sorbifolium should focus on these cultivars. The 33 cultivars were subsequently clustered into five categories through systematic clustering. The cluster analysis provided references for breeding ornamental Xanthoceras sorbifolium cultivars with different utilization values, such as large white flowers, small red flowers, large red flowers, large orange flowers, and double-petaled flowers.

Remotely Sensed Phenotypic Traits for Heritability Estimates and Grain Yield Prediction of Barley Using Multispectral Imaging from UAVs.

This study tested the potential of parametric and nonparametric regression modeling utilizing multispectral data from two different unoccupied aerial vehicles (UAVs) as a tool for the prediction of and indirect selection of grain yield (GY) in barley breeding experiments. The coefficient of determination (R2) of the nonparametric models for GY prediction ranged between 0.33 and 0.61 depending on the UAV and flight date, where the highest value was achieved with the DJI Phantom 4 Multispectral (P4M) image from 26 May (milk ripening). The parametric models performed worse than the nonparametric ones for GY prediction. Independent of the retrieval method and UAV, GY retrieval was more accurate in milk ripening than dough ripening. The leaf area index (LAI), fraction of absorbed photosynthetically active radiation (fAPAR), fraction vegetation cover (fCover), and leaf chlorophyll content (LCC) were modeled at milk ripening using nonparametric models with the P4M images. A significant effect of the genotype was found for the estimated biophysical variables, which was referred to as remotely sensed phenotypic traits (RSPTs). Measured GY heritability was lower, with a few exceptions, compared to the RSPTs, indicating that GY was more environmentally influenced than the RSPTs. The moderate to strong genetic correlation of the RSPTs to GY in the present study indicated their potential utility as an indirect selection approach to identify high-yield genotypes of winter barley.

Genomic and Phenotypic Udder Evaluation for Dairy Cattle Selection: A Review.

The traditional point of view regarding dairy cattle selection has been challenged by recent genomic studies indicating that livestock productivity prediction can be redefined based on the evaluation of genomic and phenotypic data. Several studies that included different genomic-derived traits only indicated that interactions among them or even with conventional phenotypic evaluation criteria require further elucidation. Unfortunately, certain genomic and phenotypic-derived traits have been shown to be secondary factors influencing dairy production. Thus, these factors, as well as evaluation criteria, need to be defined. Owing to the variety of genomic and phenotypic udder-derived traits which may affect the modern dairy cow functionality and conformation, a definition of currently important traits in the broad sense is indicated. This is essential for cattle productivity and dairy sustainability. The main objective of the present review is to elucidate the possible relationships among genomic and phenotypic udder evaluation characteristics to define the most relevant traits related to selection for function and conformation in dairy cattle. This review aims to examine the potential impact of various udder-related evaluation criteria on dairy cattle productivity and explore how to mitigate the adverse effects of compromised udder conformation and functionality. Specifically, we will consider the implications for udder health, welfare, longevity, and production-derived traits. Subsequently, we will address several concerns covering the application of genomic and phenotypic evaluation criteria with emphasis on udder-related traits in dairy cattle selection as well as its evolution from origins to the present and future prospects.

Whole-genome selective scans detect genes associated with important phenotypic traits in goat (Capra hircus).

Goats with diverse economic phenotypic traits play an important role in animal husbandry. However, the genetic mechanisms underlying complex phenotypic traits are unclear in goats. Genomic studies of variations provided a lens to identify functional genes. In this study, we focused on the worldwide goat breeds with outstanding traits and used whole-genome resequencing data in 361 samples from 68 breeds to detect genomic selection sweep regions. We identified 210-531 genomic regions with six phenotypic traits, respectively. Further gene annotation analysis revealed 332, 203, 164, 300, 205, and 145 candidate genes corresponding with dairy, wool, high prolificacy, poll, big ear, and white coat color traits. Some of these genes have been reported previously (e.g., KIT, KITLG, NBEA, RELL1, AHCY, and EDNRA), while we also discovered novel genes, such as STIM1, NRXN1, LEP, that may be associated with agronomic traits like poll and big ear morphology. Our study found a set of new genetic markers for genetic improvement in goats and provided novel insights into the genetic mechanisms of complex traits.