Phenotypic Traits Research Articles

Phenotypic Diversity Analysis in the Sect. Tuberculate (Camellia L.) Population, an Endemic Taxon in China

Sect. Tuberculate Chang belongs to the genus Camellia, which is an endemic group in China and has high research value. However, the phenotypic patterns of this taxon are complex and diverse, and the phenotypic variation in key traits is still unclear. In this study, a total of 212 samples from 18 populations of sect. Tuberculate plants were studied for 30 phenotypic traits of flowers, fruits, and leaves using analysis of variance, correlation analysis, principal component analysis, and cluster analysis. The results showed the following. (1) The plants in sect. Tuberculate were rich in phenotypic trait variation and possessed rich phenotypic diversity. The differentiation of phenotypic traits mainly came from among populations, with leaves (66.804%) being the largest and flowers (53.476%) being the smallest. Qualitative traits (70.264%) were greater than quantitative traits (57.608%). (2) Correlation analyses showed close and complex relationships among the phenotypic traits of flowers, fruits, and leaves. (3) The cumulative contribution of the first 10 principal components was up to 73.49%, which screened out 12 major traits contributing to the phenotypic differences in plants of sect. Tuberculate. (4) Q-type analysis showed that they were classified into 18 taxa at a Euclidean distance of 7.5 and 11 taxa at a Euclidean distance of 10. The 18 populations were not fully clustered according to the geographic distance of the plants, and there was an overlap between some of the populations. In summary, the degree of variation in phenotypic traits among populations of sect. Tuberculate plants is high, which is affected by the climatic environment. The 12 major phenotypic traits screened can be used as the basis for the classification of sect. Tuberculate plants. There are trait overlaps among some populations, which may be affected by the stochastic influence of the geographic climate and gene flow. This study will provide important references for interspecific identification, classification system construction, genetic mechanism, germplasm resource conservation, and exploitation of plants in sect. Tuberculate.

Identification of trait-associated microRNA modules in liver transcriptome of pig fed with PUFAs-enriched supplementary diet.

Dietary lipids provide energy, are cellular structural components, and are involved in physiological processes. Lipids are the dietary source in supplementary diet experiments in pigs. This study aims to investigate the dietary effects of PUFAs on the hepatic transcriptome and physiological pathways of two diets on two pig breeds. Polish Landrace (PL: n = 6) and six PLxDuroc (PLxD: n = 6) pigs were fed with a normal diet (n = 3) or PUFAs-enriched healthy diet (n = 3), and the hepatic miRNA profiles were studied for weighted gene co-expression network analysis biological interactions between gene networks and metabolic pathways of DE miRNA genes. The study identified trait-associated modules that were significantly associated with four phenotypic traits in the dietary groups of PL and PLxD: meat colour (a*), shoulder subcutaneous fat thickness, conductivity 24h post-mortem (PE24), and ashes. Trait-wise, a large set of co-expressed miRNAs of porcine liver were identified in these trait-associated significant modules (9, 7, 2, and 8) in PL and PLxD. Each module is represented by a module eigengene (ME). Forty-four miRNAs out of 94 miRNAs interacted with 6719 statistically significant target genes with a target score > 90. The GO/pathway analysis showed association with pathways including regulation of metallopeptidase activity, sebaceous gland development, collagen fibril organization, WNT signalling, epithelial tube morphogenesis, etc. The study showed the differences in miRNA expression between the dietary groups of PL and PLxD breeds. Hub genes of discovered miRNA clusters can be considered predicted miRNA genes associated with PE24, meat colour, shoulder subcutaneous fat thickness, and ashes. Discovered target genes for miRNA clusters play significant roles in biological functions such as (i) muscle and body growth development, (ii) different cellular processes and developments, (iii) system development, and (iv) metabolic processes.

Multimodal Data Fusion for Precise Lettuce Phenotype Estimation Using Deep Learning Algorithms

Effective lettuce cultivation requires precise monitoring of growth characteristics, quality assessment, and optimal harvest timing. In a recent study, a deep learning model based on multimodal data fusion was developed to estimate lettuce phenotypic traits accurately. A dual-modal network combining RGB and depth images was designed using an open lettuce dataset. The network incorporated both a feature correction module and a feature fusion module, significantly enhancing the performance in object detection, segmentation, and trait estimation. The model demonstrated high accuracy in estimating key traits, including fresh weight (fw), dry weight (dw), plant height (h), canopy diameter (d), and leaf area (la), achieving an R2 of 0.9732 for fresh weight. Robustness and accuracy were further validated through 5-fold cross-validation, offering a promising approach for future crop phenotyping.

Extent and patterns of morphological and molecular genetic diversity and population structure of Nigerian Taro cultivars.

Genetic diversity is crucial for conservation efforts as well as breeding programs targeted at the development of improved varieties. Taro, a climate-resilient crop, plays a vital role in the nutritional and economic livelihoods of many households in Nigeria, but its yield is very low due to inadequate genetic improvement efforts. A diversity assessment of Nigerian taro is therefore required to create a premise for its improvement in yield, quality and disease tolerance. In this study, the genetic diversity and population structure of 490 taro cultivars comprising two main gene pools: Dasheen (215) and Eddoe (275), collected from farmers and marketers across seven states in Nigeria was assessed using 3047 Diversity Array Technology single nucleotide polymorphism (DArT-SNP) markers. A subset of 114 taro cultivars, comprising 30 Dasheens and 84 Eddoes were further phenotyped using 24 agro-morphological descriptors. Both phenotypic and molecular characterization revealed higher genetic diversity among the Eddoes than Dasheens. Estimates of gene flow (Nm = 0.353) revealed intermixing of cultivars among the States of collection, with the highest gene flow occurring between cultivars from Anambra and Ondo states and the lowest between Anambra and Kwara states. Population structure and Ward's minimum variance hierarchical cluster based on DArT-SNPs identified four groups, one comprising Dasheen and three comprising Eddoe cultivars. Hierarchical clustering based on phenotypic traits delineated three clusters. Variation between gene pools (49%) was higher than within gene pools (32%). Variation among States of collection was high (41%), while variation among individuals within gene pools (18%) and States of collection (19%) was relatively low. Correlation between phenotypic and genotypic diversity assessments was low (r = 0.01), indicating that both approaches were necessary for assessing genetic diversity in taro. However, genotypic assessment provided better information about genetic diversity of the taro cultivars. This is the first study that represented germplasm collection across the major taro growing regions of Nigeria. The findings from this study based on agro-morphological characterization and DArT-SNP genotyping are critical for genetic characterization, conservation and breeding of taro in Nigeria, mainly initiating hybridization between the two genepools after careful assessment of ploidy levels of the accessions collected in this study. This will facilitate in developing improved taro varieties with desirable traits, such as higher yield, better disease resistance, and improved nutritional quality.

On the large time behaviour of the solutions of an evolutionary-epidemic system with spatial dispersal.

This paper investigates some properties of the large time behaviour of the solutions of a spatially distributed system of equations modelling the evolutionary epidemiology of a plant-pathogen system. The model takes into account the phenotypic trait and the mutation of the pathogen, which is described by a non-local operator. We roughly speaking prove that the solutions separate the phenotype trait from the spatio-temporal evolution in the large time asymptotic. This feature is obtained by investigating the positive and bounded entire solutions of the problem, that are shown to exhibit such a separation of the variables property, by reformulating them as the positive solutions of suitable integral equations in some ordered Banach space. In addition, some numerical simulations are performed to support our theoretical results.

DNA barcoding, micromorphology and metabolic traits of selected Ficus L. (Moraceae) species from Egypt.

The genus Ficus of the family Moraceae, is one of the largest genera of angiosperms, with diverse pharmaceutical applications and biological activities. The traditional approaches based on the morphological traits have been frequently implemented for taxonomical identification of the different taxa of Ficus, however, encompassing these features are quite laborious, due to the dependence of these phenotypic traits on the environmental conditions. So, authenticating the taxonomical identity of the Ficus taxa with molecular barcoding and metabolic profiling, as relatively stable traits, could be a relevant approach for confirming the traditional phenotypic traits of this genus. Nine species of the genus Ficus namely F. amplissima Sm., F. benjamina L. F. binnendijkii, F. drupacea var. pubescens, F. elastica Roxb., F. microcarpa L., F. religiosa L., F. tinctoria subsp. gibbosa and F. virens var. sublancelata in Egypt, were selected for this study. From the anatomical features, three species of subsection Urostigma, F. religiosa, F. virens var. sublanceolata have cystoliths on the abaxial layer, whereas in F. amplissima it was on the adaxial layer. The UPGMA dendrogram of the studied Ficus taxa has been generated from the 21 anatomical characters, categorized the studied taxa into two clusters (I and II) of average distance ~ 3.5, each cluster has been further divided into subclusters I and II. The sub-cluster I includes F. religiosa, F. virens var. sublanceolata and F. tinctoria subsp. gibbosa were grouped together to subsection Urostigma, while the sub-cluster II of the cluster I includes F. benjamina and F. amplissima. From the DNA barcoding analysis, three clusters I, II and III were emerged, the cluster I includes F. benjamina, F. binnendjikee, and F. amplissima. The cluster II, F. virens var. sublanceolata and F. religiosa that belong to subsection Urostigma, while, the cluster III includes F. elastica and F. drupacea var. pubescens, F. microcarpa that belongs to subsection Conosycea. From the metabolic profiling of Ficus species, the major compounds; H-cycloprop-azulen-7-ol, 3,7,11,15-Tetramethyl-2-hexadecen-1-ol, 2-(9-octadecenyloxy), pentadecanoic acid, phytol, sitosterol and 9,12-octadecadienoic acid were the common among the taxa, with an obvious fluctuation, that could be a chemotaxonomic markers for these species of Ficus. Based on the metabolic profiling, two distinct clusters I and II were evolved, the cluster I involve F. elastica, F. benjamina, F. drupacea var. pubescens, F. amplissima, while, the cluster II had F. tinctoria subsp. gibbosa and F. religiosa. The fluctuation on the metabolites of the tested Ficus species could be a metabolic fingerprint for each species. So, the delamination of the tested plants based on their anatomical traits was typically matched to the separation based on the ITS sequence analysis.

Shaping root system architecture: holobiont-based phenotyping for root traits

Shaping root system architecture: holobiont-based phenotyping for root traits

Structural variations in livestock genomes and their associations with phenotypic traits: a review

Genomic structural variation (SV) refers to differences in gene sequences between individuals on a genomic scale. It is widely distributed in the genome, primarily in the form of insertions, deletions, duplications, inversions, and translocations. Due to its characterization by long segments and large coverage, SVs significantly impact the genetic characteristics and production performance of livestock, playing a crucial role in studying breed diversity, biological evolution, and disease correlation. Research on SVs contributes to an enhanced understanding of chromosome function and genetic characteristics and is important for understanding hereditary diseases mechanisms. In this article, we review the concept, classification, main formation mechanisms, detection methods, and advancement of research on SVs in the genomes of cattle, buffalo, equine, sheep, and goats, aiming to reveal the genetic basis of differences in phenotypic traits and adaptive genetic mechanisms through genomic research, which will provide a theoretical basis for better understanding and utilizing the genetic resources of herbivorous livestock.

A path integral approach for allele frequency dynamics under polygenic selection.

Many phenotypic traits have a polygenic genetic basis, making it challenging to learn their genetic architectures and predict individual phenotypes. One promising avenue to resolve the genetic basis of complex traits is through evolve-and-resequence experiments, in which laboratory populations are exposed to some selective pressure and trait-contributing loci are identified by extreme frequency changes over the course of the experiment. However, small laboratory populations will experience substantial random genetic drift, and it is difficult to determine whether selection played a role in a given allele frequency change. Predicting allele frequency changes under drift and selection, even for alleles contributing to simple, monogenic traits, has remained a challenging problem. Recently, there have been efforts to apply the path integral, a method borrowed from physics, to solve this problem. So far, this approach has been limited to genic selection, and is therefore inadequate to capture the complexity of quantitative, highly polygenic traits that are commonly studied. Here we extend one of these path integral methods, the perturbation approximation, to selection scenarios that are of interest to quantitative genetics. We derive analytic expressions for the transition probability (i.e., the probability that an allele will change in frequency from x to y in time t) of an allele contributing to a trait subject to stabilizing selection, as well as that of an allele contributing to a trait rapidly adapting to a new phenotypic optimum. We use these expressions to characterize the use of allele frequency change to test for selection, as well as explore optimal design choices for evolve-and-resequence experiments to uncover the genetic architecture of polygenic traits under selection.

Engineering structural variants to interrogate genome function.

Structural variation, such as deletions, duplications, inversions and complex rearrangements, can have profound effects on gene expression, genome stability, phenotypic diversity and disease susceptibility. Structural variants can encompass up to millions of bases and have the potential to rearrange substantial segments of the genome. They contribute considerably more to genetic diversity in human populations and have larger effects on phenotypic traits than point mutations. Until recently, our understanding of the effects of structural variants was driven mainly by studying naturally occurring variation. New genome-engineering tools capable of generating deletions, insertions, inversions and translocations, together with the discovery of new recombinases and advances in creating synthetic DNA constructs, now enable the design and generation of an extended range of structural variation. Here, we discuss these tools and examples of their application and highlight existing challenges that will need to be overcome to fully harness their potential.

Genome-Wide Scan for Selective Sweeps Reveals Novel Loci Associated with Prolificacy in Iranian Sheep Breeds in Comparison with Highly Prolific Exotic Breed

Domestication and selection significantly changed phenotypic traits in modern domestic animals. To identify the genomic regions associated with prolificacy in this study, 837 ewes from three Iranian indigenous sheep breeds, consisting of Baluchi, Lori-Bakhtiari, and Zandi uniparous breeds, and one Greek highly prolific dairy sheep, namely Chios, were genotyped using OvineSNP50K arrays. Statistical tests were then performed using different and complementary methods based on either site frequency (FST) and haplotype (hapFLK) between populations, followed by a pathway analysis of the genes contained in the selected regions. The results revealed that for the top 0.01 percentile of the obtained FST values, 16 genomic regions on chromosomes 2, 3, 4, 7, 8, 9, 13, 14, 16, 18, 19, and 20, and for hapFLK values, 3 regions located on chromosomes 3, 7, and 13, were under selection. A bioinformatic analysis of these genomic regions showed that these loci overlapped with potential candidate genes associated with prolificacy in sheep including GNAQ, COL5A2, COL3A1, HECW1, FBN1, COMMD3, RYR1, CCL28, SERPINA14, and HSPA2. These regions also overlapped with some quantitative trait loci (QTLs) linked to prolificacy traits, milk yield, and body weight. These findings suggest that future research could further link these genomic regions to prolificacy traits in sheep.

Improving the Characteristics of Fruiting Bodies in Lentinus edodes: The Impact of Rolipram-Induced cAMP Modulation

Background: Strains XG04 and XGT2 of Lentinus edodes (Berk.) Singer demonstrate a high degree of genomic similarity, with XGT2 representing a systematic selection of XG04 and exhibiting enhanced phenotypic traits. Methods: An investigation into the differences between these strains was conducted using untargeted metabolomics to identify potential causal factors. Five exogenous inducers were assessed for their relationship with the observed phenotypes, and their impacts on fruiting body characteristics were analyzed. Results: Notably, the exogenous inducer rolipram, at a concentration of 0.4%, was found to increase cAMP expression levels in L. edodes primordia, which subsequently affected gill development, leading to the formation of gill-free fruiting bodies. Morphological differences between the two strains were evident; XG04 exhibited a spherical morphology with absent gills, rendering it commercially unviable, whereas XGT2 displayed a thicker cap and a more robust stipe, maintaining its characteristic umbrella shape. Conclusions: As the concentration of rolipram increased, both cap retraction and gill reduction in XGT2 occurred in a dose-dependent manner. The endogenous cAMP levels in the fruiting bodies were measured before and after rolipram treatment, revealing that the cap retraction and gill reduction in XGT2 progressed in a dose-dependent manner alongside increasing cAMP expression levels. Furthermore, a positive correlation was observed between cAMP levels and rolipram concentration. This study provides a foundation for improving the quality and productivity of mushroom cultivation by manipulating fruiting body characteristics through external stimuli.

Soil biological health assessment based on nematode communities under maize and peanut intercropping

Abstract Background Cereal/legume intercropping can enhance crop productivity and improve soil health in dryland farming. However, little is known about soil biological health under maize/peanut intercropping. The aim of this study was to assess soil biological health based on nematode communities in a maize/peanut intercropping system. Methods We conducted a field experiment with different planting patterns, including monoculture maize (M), monoculture peanut (P), and maize intercropped with peanut (IM, intercropped maize; IP, intercropped peanut) to determine the influence on soil biological health. We measured soil physicochemical properties and nematode communities, and employed exploratory factor analysis combined with cumulative normal distribution curve scoring to identify potential soil biological health traits. Results The intercropped maize gave the highest plant parasitic nematode abundance, trophic diversity index, evenness index, and structure index. The monoculture peanut gave the highest enrichment index and least plant parasitic nematode abundance, trophic diversity index, Shannon diversity index, evenness index, structure index, and channel index. We identified four soil biological health traits, including basic nutrients and biodiversity, food web complexity, slow energy channel, and fast energy channel, mainly represented by soil ammonium nitrogen and Shannon diversity index, structural index and omnivore-predator nematode abundance, fungivorous nematode abundance and plant parasitic nematode abundance, microbial biomass carbon and bacterivorous nematode abundance, respectively. The intercropping systems improved the comprehensive score of soil biological health, especially maize intercropping soil. Intercropping maize and intercropping peanut significantly improved oil biological health traits representing the food web complexity compared with the corresponding monoculture soils. Conclusions Our results indicate that soil nematode and physicochemical indicators reflect different soil biological health traits. Among those traits, the improvement of basic nutrients and biodiversity and the complexity of the food web were the main reasons for improving soil biological health through the intercropping system.

Foliar application of silver (Ag-NPs) and copper (Cu-NPs) nanoparticles enhances phenotypic traits and oil quality in Brassica napus L.

Nanotechnology represents a burgeoning field of science that enables advanced research across various domains. In recent years, there has been a notable increase in the utilization of silver nanoparticles (AgNPs) for diverse agricultural and industrial applications. Similarly, copper nanoparticles (CuNPs) have significant attention in agriculture due to their cost-effectiveness and practicality. This study aimed to investigate the potential impact of silver and copper nanoparticles on enhancing both the yield and quality of Brassica napus L. cultivar CON-1. The combined foliar application of green synthesized silver and copper nanoparticles at varying concentrations (0, 5, 10, 15, 20, 25, 30, and 35mg/L) resulted in notable improvements in the growth, yield and quality of Brassica napus L. compared to untreated plants. Particularly, the concentration of 25mg/L for both silver and copper nanoparticles demonstrated superior outcomes in terms of plant height, number of primary and secondary branches/plant, number of siliques /plant, number of seeds/silique, siliqua length, 1000-seed weight, biological yield/plant, seed yield/plant, oil yield/plant, and harvest index. Furthermore, the nanoparticles effectively reduced the accumulation of erucic acid in the oil, thereby enhancing the overall oil quality of canola. In summary, the application of silver and copper nanoparticles shows promising potential in improving the productivity and quality of Brassica napus L., highlighting their role as beneficial agricultural additives in modern farming practices.

Past and recent drivers of extinction risk in endemic New Zealand birds

AbstractLand‐cover change is a major driver of species extinction risk and the overarching loss of biodiversity. However, the impact of such change is nuanced, varying among species due to the mediation of life‐history traits and the timing of land transformation. While diverse studies have pinpointed ecological and life‐history attributes linked to the decline of bird species, the combined effects of past and recent land‐cover change often present a complex picture. In this study, we undertook a modelling approach to assess extinction risk in New Zealand's endemic birds based on life‐history traits and past (1996–2008) and recent (2008–2018) land‐cover change. Our results suggested specific variables driving extinction risk in endemic New Zealand birds. Notably, incubation length emerged as the most influential factor, trailed by past land‐cover change, body size and clutch size. This indicates that past land‐cover change in combination with large body sizes and slow life histories, characterized by low fecundity and extended incubation periods, collectively elevates the extinction risk of endemic birds in New Zealand. These results shed light on the conservation priorities for species with specific biological traits potentially exposed to the negative effects of land‐cover change.

Phosphorus-Mediated Transition from Vegetative to Reproductive Growth in Dwarf Coconut (Cocos nucifera L.)

Reducing the time before the flowering stage in coconut (Cocos nucifera L.) trees greatly influences yield, yet the mechanisms driving the switch from vegetative to reproductive growth are not well understood, especially the role of phosphorus in this transition. In this study, dwarf coconut plants of the same cultivation age were selected and categorized into the vegetative phase (VP) or the reproductive phase (RP). By examining the phenotypic traits, nutrient variations in the roots and soil, and the transcriptional expression of relevant genes in the roots across both phases, we investigated the potential mechanisms driving the transition from the VP to the RP in coconuts. The shoots of coconuts in the RP were significantly taller compared to those in the VP. Moreover, the phosphorus concentration in the roots of coconuts during the RP was 1.31 times higher than in the VP, which may be linked to the significant upregulation of the PT1 genes AZ11G0219160 and AZ02G0034860 in the roots of coconuts in the RP. In addition, all phosphorus-containing metabolites in the roots during the RP showed a significant increase, particularly those related to long-chain fatty acids and ribonucleotide metabolites. This suggests that coconut roots may facilitate the progression from vegetative to reproductive growth by enhancing phosphorus uptake via PT1s and promoting the synthesis and accumulation of phosphorus-containing metabolites.

Phenotypic Trait Analysis of Tomato (Solanum lysopersicum) Genotypes in Qatar and Indian Agro-climatic Conditions

Background: The study included four genotypes of tomato (EC620378, EC620380, EC620383, EC620534) which were cultivated to find out their similarities and differences based on phenotypic traits when they were grown under different soil zones of Doha (Qatar) and Meerut (India) to find out that which of the genotypes can be cultivated better in Qatar and India. Methods: The experiment was laid out in Randomized Complete Block Design (RBCD) with two replications. Statistical analysis for variation in quantitative characteristics among genotypes was done by collecting data in 15 qualitative and quantitative traits. Data showed great variation for almost all the traits. The principal component analysis involved plant height and days to marketable maturity as the most discriminating trait that accounted for greater variability in genotypes in both zones, and they should be considered in tomato improvement programs. The correlation analysis showed that fruit yield per plant was positively and significantly correlated with number of fruits per plant and fruit width. Present findings suggest that the identified superior genotypes may be utilized by different farms to further improve their breeding and cultivation strategies. Result: In Indian soil zone, genotype EC620534 performed extremely well in terms of maximum yield per plant. Similarly, in Qatar soil zone, EC620534 and EC620380 performed well. The phenotypic coefficient of variation (PCV) was higher than its corresponding genotypic counterpart (GCV) for all characters studied showing environmental influence. High broad-sense heritability were recorded for days to marketable maturity, fruit shape index and fruit weight in both agro-climatic zones, they were associated with low genetic advance indicating non-additive gene action and environmental influence, hence, heterosis breeding is recommended.

Flight initiation distance differs among eumelanin‐based color morphs in feral pigeons

AbstractOrganisms facing anthropogenic activities usually exhibit phenotypic responses assumed to enhance coping with disturbance. These responses include a decreasing degree of reaction toward potentially risky situations (“behavioral tolerance”) with increasing disturbance. Though melanin is associated with many phenotypic traits, including pigmentation and behavior, the potential relationship between behavioral tolerance and melanin has never been explored. Such relationship may potentially result from either direct association between melanin and behavior (e.g., genetic correlation) or indirectly through a coloration‐dependent behavior‐modulating factor (e.g., differential predation or human preferences in cities toward color morphs). Feral pigeons (Columba livia) represent an ideal biological system to test for these hypotheses, due to their presence in cities worldwide, their considerable variation in eumelanin‐based coloration, ranging from white to black plumage, and their close proximity to humans. We measured Flight Initiation Distance (FID, classically used for behavioral tolerance assessment) of feral pigeons of 4 different eumelanin‐based color morphs in sites differing in their urbanization rate and pedestrian traffic within the restricted scale of a city center (Paris). Urbanization rate and pedestrian traffic had no effect on FID, maybe because of the small spatial scale considered. FID varied with eumelanin‐based coloration: white pigeons had lower FID (104.6 cm; i.e., higher behavioral tolerance) than darker morphs (232.3 cm for Blue bar, 184.4 cm for T‐pattern & Checker, and 181.8 cm for Spread color morphs). Though the exact underlying causes remain to be identified, we propose different possible mechanisms for this relationship that remain to be investigated in future work.

Unraveling the genetic and physiological potential of donkeys: insights from genomics, proteomics, and metabolomics approaches.

Donkeys (Equus asinus) have played a vital role in agriculture, transportation, and companionship, particularly in developing regions where they are indispensable working animals. The domestication of donkeys marked a significant turning point in human history, as they became essential for transportation, agriculture, and trade, especially in arid and semi-arid areas where their resilience and endurance were highly valued. In modern society, donkeys are indispensable due to their diversified applications, including meat, dairy, medicine, and functional bioproducts, supporting economic, cultural, and medical industries. Despite their critical importance, research on donkeys has historically been overshadowed with studies on horses. However, recent advancements in high-throughput sequencing and bioinformatics have significantly deepened our understanding of the molecular landscape of donkey genome, uncovering their unique adaptations, genetic diversity, and potential therapeutic applications. Microsatellite and mitochondrial DNA (mtDNA) markers have proven effective in assessing the genetic diversity of donkeys across various regions of the world. Additionally, significant strides have been made in characterizing differentially abundant genes, proteins, and metabolic profiles in donkey milk, meat, and skin, and in identifying specific genes/proteins/metabolites associated with sperm quality, motility, and reproduction. Advanced genomic technologies, such as genome-wide association studies and the identification of selection signatures, have also been instrumental in delineating genomic regions associated with phenotypic and adaptive traits. This review integrates data from diverse studies, including those on genetic diversity, transcriptomics, whole genome sequencing, protein analysis, and metabolic profiling, to provide a comprehensive overview of donkey biology. It underscores the unique characteristics of donkeys and emphasizes the importance of continued research to improve their genetic management, conservation, and agricultural use, ensuring their ongoing contribution to human societies.

Construction of a high-density genetic map using specific-locus amplified fragment sequencing and quantitative trait loci analysis for tillering related traits in Psathyrostachys juncea perennial grass.

Russian wildrye (RWR, Psathyrostachys juncea) is an outcrossing perennial grass that plays a crucial role in foragaing and rangeland restoration due to its tiller producing capabilities, nevertheless, a genetic map has yet to be constructed due to a shortage of efficient and reliable molecular markers. This also limits the identification, localization, and cloning of economically important traits related to tiller density during breeding. Therefore, this study aimed to create a F1 mapping population with 147 individual lines and their two parents, which were selected based on varying tiller densities. We then used this mapping population to conduct specific-locus amplified fragment sequencing (SLAF-seq) to generate SLAF markers and discover single nucleotide polymorphisms (SNPs). Initially, we generated a total of 1,438.38 million pair-end reads with an average sequencing depth of 84.92 in the maternal line, 79.34 in the parental line, and 27.05 in each F1 individual line, respectively. Following the filtering of low-depth SLAF tags, a total of 558,344 high-quality SLAFs were identified. A total of 1,519,903 SNP markers were obtained, and 62,424 polymorphic SNPs were discovered. From these, 4,644 polymorphic SNPs were selected and used for the construction of a genetic map encompassing seven linkage groups. The genetic map spanned 1,416.60 cM with an average distance of 0.31 cM between adjacent markers. Comparative analysis between the seven linkage groups of RWR SLAF tag and the whole-genome sequences in barley (Hordeum vulgare L.) revealed homology values ranging from 17.5% to 34.6%, and the collinearity between the RWR linkage groups and the barley homology groups ranged from 0.6787 to 0.9234, with an average value of 0.8158. Additionally, 143 significant quantitative trait locus (QTLs) with Logarithm of Odds (LOD) value greater than 2.5 for five tiller related traits were detected using three consecutive years of phenotypic trait data from the F1 population, further verifying the map's reliability.