Multi-environment association study highlights candidate genes for robust agronomic quantitative trait loci in a novel worldwide Capsicum core collection.

Investigating crop diversity through genome-wide association studies (GWAS) on core collections helps in deciphering the genetic determinants of complex quantitative traits. Using the G2P-SOL project world collection of 10 038 wild and cultivated Capsicum accessions from 10 major genebanks, we assembled a core collection of 423 accessions representing the known genetic diversity. Since complex traits are often highly dependent upon environmental variables and genotype-by-environment (G × E) interactions, multi-environment GWAS with a 10 195-marker genotypic matrix were conducted on a highly diverse subset of 350 Capsicum annuum accessions, extensively phenotyped in up to six independent trials from five climatically differing countries. Environment-specific and multi-environment quantitative trait loci (QTLs) were detected for 23 diverse agronomic traits. We identified 97 candidate genes potentially implicated in 53 of the most robust and high-confidence QTLs for fruit flavor, color, size, and shape traits, and for plant productivity, vigor, and earliness traits. Investigating the genetic architecture of agronomic traits in this way will assist the development of genetic markers and pave the way for marker-assisted selection. The G2P-SOL pepper core collection will be available upon request as a unique and universal resource for further exploitation in future gene discovery and marker-assisted breeding efforts by the pepper community.

Genetic diversity and population structure of wheat landraces in Southern Winter Wheat Region of China.

BACKGROUND: Wheat landraces are considered a valuable source of genetic diversity for breeding programs. It is useful to evaluate the genetic diversity in breeding studies such as marker-assisted selection (MAS), genome-wide association studies (GWAS), and genomic selection. In addition, constructing a core germplasm set that represents the genetic diversity of the entire variety set is of great significance for the efficient conservation and utilization of wheat landrace germplasms. RESULTS: To understand the genetic diversity in wheat landrace, 2,023 accessions in the Jiangsu Provincial Crop Germplasm Resource Bank were used to explore the molecular diversity and population structure using the Illumina 15 K single nucleotide polymorphism (SNP) chip. These accessions were divided into five subpopulations based on population structure, principal coordinate and kinship analysis. A significant variation was found within and among the subpopulations based on the molecular variance analysis (AMOVA). Subpopulation 3 showed more genetic variability based on the different allelic patterns (Na, Ne and I). The M strategy as implemented in MStratv 4.1 software was used to construct the representative core collection. A core collection with a total of 311 accessions (15.37%) was selected from the entire landrace germplasm based on genotype and 12 different phenotypic traits. Compared to the initial landrace collections, the core collection displayed higher gene diversity (0.31) and polymorphism information content (PIC) (0.25), and represented almost all phenotypic variation. CONCLUSIONS: A core collection comprising 311 accessions containing 100% of the genetic variation in the initial population was developed. This collection provides a germplasm base for effective management, conservation, and utilization of the variation in the original set.

Transcriptome-based prediction for polygenic traits in rice using different gene subsets.

BACKGROUND: Transcriptome-based prediction of complex phenotypes is a relatively new statistical method that links genetic variation to phenotypic variation. The selection of large-effect genes based on a priori biological knowledge is beneficial for predicting oligogenic traits; however, such a simple gene selection method is not applicable to polygenic traits because causal genes or large-effect loci are often unknown. Here, we used several gene-level features and tested whether it was possible to select a gene subset that resulted in better predictive ability than using all genes for predicting a polygenic trait. RESULTS: Using the phenotypic values of shoot and root traits and transcript abundances in leaves and roots of 57 rice accessions, we evaluated the predictive abilities of the transcriptome-based prediction models. Leaf transcripts predicted shoot phenotypes, such as plant height, more accurately than root transcripts, whereas root transcripts predicted root phenotypes, such as crown root length, more accurately than leaf transcripts. Furthermore, we used the following three features to train the prediction model: (1) tissue specificity of the transcripts, (2) ontology annotations, and (3) co-expression modules for selecting gene subsets. Although models trained by a gene subset often resulted in lower predictive abilities than the model trained by all genes, some gene subsets showed improved predictive ability. For example, using genes expressed in roots but not in leaves, the predictive ability for crown root diameter was improved by more than 10% (R2 = 0.59 when using all genes; R2 = 0.66, using 1,554 root-specifically expressed genes). Similarly, genes annotated as "gibberellic acid sensitivity" showed higher predictive ability than using all genes for root dry weight. CONCLUSIONS: Our results highlight both the possibility and difficulty of selecting an appropriate gene subset to predict polygenic traits from transcript abundance, given the current biological knowledge and information. Further integration of multiple sources of information, as well as improvements in gene characterization, may enable the selection of an optimal gene set for the prediction of polygenic phenotypes.

Genetic diversity and population structure of superior shea trees (Vitellaria paradoxa subsp. paradoxa) using SNP markers for the establishment of a core collection in Côte d'Ivoire.

BACKGROUND: The shea tree is a well-known carbon sink in Africa that requires a sustainable conservation of its gene pool. However, the genetic structure of its population is not well studied, especially in Côte d'Ivoire. In this study, 333 superior shea tree genotypes conserved in situ in Côte d'Ivoire were collected and genotyped with the aim of investigating its genetic diversity and population structure to facilitate suitable conservation and support future breeding efforts to adapt to climate change effects. RESULTS: A total of 7,559 filtered high-quality single nucleotide polymorphisms (SNPs) were identified using the genotyping by sequencing technology. The gene diversity (HE) ranged between 0.1 to 0.5 with an average of 0.26, while the polymorphism information content (PIC) value ranged between 0.1 to 0.5 with an average of 0.24, indicating a moderate genetic diversity among the studied genotypes. The population structure model classified the 333 genotypes into three genetic groups (GP1, GP2, and GP3). GP1 contained shea trees that mainly originated from the Poro, Tchologo, and Hambol districts, while GP2 and GP3 contained shea trees collected from the Bagoué district. Analysis of molecular variance (AMOVA) identified 55% variance within populations and 45% variance within individuals, indicating a very low genetic differentiation (or very high gene exchange) between these three groups (FST = 0.004, gene flow Nm = 59.02). Morphologically, GP1 displayed spreading tree growth habit, oval nut shape, higher mean nut weight (10.62 g), wide leaf (limb width = 4.63 cm), and small trunk size (trunk circumference = 133.4 cm). Meanwhile, GP2 and GP3 showed similar morphological characteristics: erect and spreading tree growth habit, ovoid nut shape, lower mean nut weight (GP2: 8.89 g; GP3: 8.36 g), thin leaf (limb width = 4.45 cm), and large trunk size ( GP2: 160.5 cm, GP3: 149.1 cm). A core set of 100 superior shea trees, representing 30% of the original population size and including individuals from all four study districts, was proposed using the "maximum length sub-tree function" in DARwin v. 6.0.21. CONCLUSION: These findings provide new knowledge of the genetic diversity and population structure of Ivorian shea tree genetic resources for the design of effective collection and conservation strategies for the efficient use of inbreeding.

Capitalizing on genebank core collections for rare and novel disease resistance loci to enhance barley resilience.

In the realm of agricultural sustainability, the utilization of plant genetic resources for enhanced disease resistance is paramount. Preservation efforts in genebanks are justified by their potential contributions to future crop improvement. To capitalize on the potential of plant genetic resources, we focused on a barley core collection from the German ex situ genebank and contrasted it with a European elite collection. The phenotypic assessment included 812 plant genetic resources and 298 elites, with a particular emphasis on four disease traits (Puccinia hordei, Blumeria graminis hordei, Ramularia collo-cygni, and Rhynchosporium commune). An integrated genome-wide association study, employing both Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK) and a linear mixed model, was performed to unravel the genetic underpinnings of disease resistance. A total of 932 marker-trait associations were identified and assigned to 49 quantitative trait loci. The accumulation of novel and rare resistance alleles significantly bolstered the overall resistance level in plant genetic resources. Three plant genetic resources donors with high counts of novel/rare alleles and exhibiting exceptional resistance to leaf rust and powdery mildew were identified, offering promise for targeted pre-breeding goals and enhanced resilience in future varieties. Our findings underscore the critical contribution of plant genetic resources to strengthening crop resilience and advancing sustainable agricultural practices.

SUnSeT: spectral unmixing of hyperspectral images for phenotyping soybean seed traits.

KEY MESSAGE: Hyperspectral features enable accurate classification of soybean seeds using linear discriminant analysis and GWAS for novel seed trait genes. Evaluating crop seed traits such as size, shape, and color is crucial for assessing seed quality and improving agricultural productivity. The introduction of the SUnSet toolbox, which employs hyperspectral sensor-derived image analysis, addresses this necessity. In a validation test involving 420 seed accessions from the Korean Soybean Core Collections, the pixel purity index algorithm identified seed- specific hyperspectral endmembers to facilitate segmentation. Various metrics extracted from ventral and lateral side images facilitated the categorization of seeds into three size groups and four shape groups. Additionally, quantitative RGB triplets representing seven seed coat colors, averaged reflectance spectra, and pigment indices were acquired. Machine learning models, trained on a dataset comprising 420 accession seeds and 199 predictors encompassing seed size, shape, and reflectance spectra, achieved accuracy rates of 95.8% for linear discriminant analysis model. Furthermore, a genome-wide association study utilizing hyperspectral features uncovered associations between seed traits and genes governing seed pigmentation and shapes. This comprehensive approach underscores the effectiveness of SUnSet in advancing precision agriculture through meticulous seed trait analysis.

Mapping trends in hemifacial spasm research: bibliometric and visualization-based analyses of the Web of Science Core Collection.

Hemifacial spasm (HFS) is a common cranial nerve disease. In HFS research, we conducted a bibliometric analysis to examine the development and research trends. A retrieval of HFS studies published between 2011 and 2022 was performed from the Web of Science Core Collection in September 2022. Two scientometric tools were used to perform bibliometric and visualization-based analyses: VOSviewer and CiteSpace. Bibliometric analysis of 1461 studies published between 2011 and 2022 was carried out using data from 444 journals, 6021 authors, 1732 institutions, and 76 countries/regions. China, the USA, Japan, and South Korea were four key contributors to this study. Shanghai Jiaotong University was the major institution with the larger number of publications. Li Shiting was the most prolific author. Jannetta PJ was the most co-cited author. World Neurosurgery was the top prolific journal. Journal of Neurosurgery was the top co-cited journal. The top five keywords were hemifacial spasm, microvascular decompression, trigeminal neuralgia, surgery, and neurovascular compression. This study examines the research trends in global scientific research on HFS over the last decade. Researchers interested in learning more about current trends and novel research frontiers in this area can benefit from the study.

Global performance and trends of research on emerging contaminants in sewage sludge: A Bibliometric Analysis from 1990 to 2023.

The pervasive occurrence of emerging contaminants (ECs) in sewage sludge (SWS) poses significant safety challenges concerning the processing, disposal, and secure application, ultimately jeopardizing both human health and the ecological environment. To comprehensively comprehend the evolutionary trajectories, present state, and research advancements in the field of ECs in SWS, a systematic was conducted, scrutinizing the annual publication quantity, disciplinary distribution, core authors, involved nations/regions, pertinent keywords, and citation status of 2082 research publications related to ECs in SWS from 1990 to 2023. The results indicate a substantial upward trajectory in the research literature pertaining to ECs in SWS. The study of ECs in SWS encompasses 78 disciplines, including Environmental Sciences, Environmental Engineering, and Water Resources. China, Spain, and the USA ranked among the top three countries in terms of both total publications and citation frequency. The majority of publications were published in reputable high-impact journals such as Science of the Total Environment, Chemosphere, and Bioresource Technology. Based on high-frequency keywords, co-occurrence networks of keywords, and keywords burst analysis, it is found that the occurrence and environment behavior of ECs in SWS (ARGs, microplastics, PPCPs, and POPs), the detection and analytical methods, the impact on SWS treatment and disposal processes, and the accumulation and ecological risks in plants and soil during SWS land utilization, are the main research directions and hot topics in this field. In the future, the study of the impact of SWS treatment technologies on ECs removal is expected to receive increased research attention.

Genome-Wide Association Study of Cuticle and Lipid Droplet Properties of Cucumber (Cucumis sativus L.) Fruit.

The fruit surface is a critical first line of defense against environmental stress. Overlaying the fruit epidermis is the cuticle, comprising a matrix of cutin monomers and waxes that provides protection and mechanical support throughout development. The epidermal layer of the cucumber (Cucumis sativus L.) fruit also contains prominent lipid droplets, which have recently been recognized as dynamic organelles involved in lipid storage and metabolism, stress response, and the accumulation of specialized metabolites. Our objective was to genetically characterize natural variations for traits associated with the cuticle and lipid droplets in cucumber fruit. Phenotypic characterization and genome-wide association studies (GWAS) were performed using a resequenced cucumber core collection accounting for >96% of the allelic diversity present in the U.S. National Plant Germplasm System collection. The collection was grown in the field, and fruit were harvested at 16-20 days post-anthesis, an age when the cuticle thickness and the number and size of lipid droplets have stabilized. Fresh fruit tissue sections were prepared to measure cuticle thickness and lipid droplet size and number. The collection showed extensive variation for the measured traits. GWAS identified several QTLs corresponding with genes previously implicated in cuticle or lipid biosynthesis, including the transcription factor SHINE1/WIN1, as well as suggesting new candidate genes, including a potential lipid-transfer domain containing protein found in association with isolated lipid droplets.

Bibliometric analysis and systematic review of fluoride-containing wastewater treatment: Development, hotspots and future perspectives.

Water pollution with fluoride can cause dental fluorosis, skeletal deformities, and other diseases, posing serious harm to human health. To understand the development status, research hotspots, and frontier trends in fluoride-containing wastewater (FCW) treatment, this study employed bibliometric methods to visually analyze 2840 publications related to FCW treatment from the Web of Science Core Collection (WOSCC) database. The "bibliometrix" package in R language, VOSviewer, and CiteSpace visualization software were utilized for the analysis. The results revealed a fluctuating upward trend in the annual number of publications, indicating ongoing deepening and development of research in this field. India and China exhibited the strongest research capacity, forming a cooperation network centered around these two countries. High-impact journals such as Desalination and Water Treatment, Journal of Hazardous Materials, and Chemical Engineering Journal frequently publish research related to FCW treatment. Keyword co-occurrence and burst analysis revealed that the current research hotspots in FCW treatment primarily focus on treatment methods (ion exchange, chemical coagulation/precipitation, adsorption, electrochemical, membrane separation, and fluidized bed crystallization), adsorption mechanism, and adsorbent design and optimization. Future research will likely focus on developing efficient treatment technologies and adsorption materials for FCW, as well as the recovery of fluoride resources from FCW, highlighting a dual approach to environmental sustainability and resource management. By employing bibliometrics, this study outlines the development status of FCW treatment and predicts the field's future trends, providing insights for understanding the development trajectory of this field.

Global research trends of uranium-containing wastewater treatment based on bibliometric review.

The generation of uranium-containing wastewater (UCW) during different stages of uranium mining, processing, and utilization presents a significant ecological and biospheric threat. Consequently, it is crucial for both sustainable development and the protection of human health to adopt appropriate methods for the treatment of UCW as well as the separation and enrichment of uranium. This study conducted a comprehensive search of the Web of Science Core Collection (WOSCC) database for publications related to UCW treatment between 1990 and 2022 to gain insight into current trends in the field. Subsequently, the annual publications, WOSCC categories, geographical distribution, major collaborations, prolific authors, influential journals, and highly cited publications were the subjects of a biliometric analysis that was subsequently carried out. The study findings indicate a significant rise in the overall number of publications in the research field between 1990 and 2022. China, India, and the USA emerged as the primary contributors in terms of publication count. The Chinese Academy of Sciences, the East China University of Technology, and the University of South China were identified as the key research institutions in this field. Furthermore, a majority of the publications in this field were distributed through prestigious journals with high impact factors, such as the Journal of Radioanalytical and Nuclear Chemistry. The top 3 journals were Radioanalytical and Nuclear Chemistry, Chemical Engineering Journal, and Journal of Hazardous Materials. The keyword co-occurrence and burst analysis revealed that the current research on UCW treatment mainly focuses on adsorption-based treatment methods, environmentally functional materials, uranium recovery, etc. Furthermore, the study of the adsorption efficiency of different adsorbent materials, as well as the strengthening and improvement of adsorbent material selectivity and capacity for the recovery of uranium, represents a research hotspot in the field of UCW treatment in the future. This study conducts a comprehensive overview of the current status and prospects of the UCW treatment, which can provide a valuable reference for gaining insights into the development trajectory of the UCW treatment.

Global bibliometric mapping of dental development research for the period 2012-2021.

BACKGROUND: Dental development is a complex long-term biological process, significant attention should be paid to the dental development and health of this critical time window in childhood for the oral health of the whole life cycle. AIM: This study aimed to conduct bibliometric studies on the scientific outputs of global dental development research by the CiteSpace software. DESIGN: The global scientific outputs about dental development between January 1, 2012, and December 31, 2021, retrieved from Web of Science Core Collection, CiteSpace, and Microsoft Excel were applied for this bibliometric study. RESULTS: A total of 3746 reviews and articles were obtained from the Web of Science core database for exploring the basic publication characteristics, hotspots, and frontiers of this research field. The results showed that dental development is gaining more researcher's attention over time. In terms of countries, the USA and China were the major contributors to this research area. At the institutional level, Sichuan University ranked first. Meanwhile, international cooperation across regions was quite active. The Journal of Dental Research has exerted a broad and far-reaching influence on dental development research in both publications and citations. James P Simmer, Jungwook Kim, Charles E Smith, and Jan CC Hu are among the most influential scholars in this field. Finally, the future hotspots were proposed, covering three directions: dental analysis, tooth development, and post-translational phosphorylation of histones. CONCLUSION: In the past decade, the field of dental development has developed rapidly, and the cooperation between scholars, institutions, and researchers has become increasingly close.

Bibliometric analysis of global performance and trends of research on combined sewer overflows (CSOs) from 1990 to 2022.

Combined sewer overflows (CSOs) are one of the main sources of pollution in urban water systems and significantly impede the restoration of water body functionalities within urban rivers and lakes. To understand the research and frontier trends of CSOs comprehensively and systematically, a visual statistical analysis of the literature related to CSOs in the Web of Science core database from 1990 to 2022 was conducted using the bibliometric method using HistCite Pro and VOSviewer. The results reveal a total of 1,209 pertinent publications related to CSOs from 1990 to 2022, and the quantity of CSOs-related publications indicated an increasing trend. Investigations of the distribution and fate of typical pollutants in CSOs and their ecological effects on receiving waters and studies on pollution control technologies (source reduction, process control, and end-of-pipe treatment) are the current focus of CSOs research. CSOs pollution control technologies based on source reduction and the monitoring and control of emerging contaminants are at the forefront of scientific investigations on CSOs. This study systematically and comprehensively summarized current research topics and future research directions of CSOs, thus providing a reference for CSOs control and water environment management research.

The chemotype core collection of genus Nicotiana.

Sustainable production of chemicals and improving these biosources by engineering metabolic pathways to create efficient plant-based biofactories relies on the knowledge of available chemical/biosynthetic diversity present in the plant. Nicotiana species are well known for their amenability towards transformation and other new plant breeding techniques. The genus Nicotiana is primarily known through Nicotiana tabacum L., the source of tobacco leaves and all respective tobacco products. Due to the prevalence of the latter, N. tabacum and related Nicotiana species are one of the most extensively studied plants. The majority of studies focused solely on N. tabacum or other individual species for chemotyping. The present study analysed a diversity panel including 17 Nicotiana species and six accessions of Nicotiana benthamiana and created a data set that effectively represents the chemotype core collection of the genus Nicotiana. The utilisation of several analytical platforms and previously published libraries/databases enabled the identification and measurement of over 360 metabolites of a wide range of chemical classes as well as thousands of unknowns with dedicated spectral and chromatographic properties.

Construction of a strawberry breeding core collection to capture and exploit genetic variation.

BACKGROUND: Genetic diversity is crucial for the success of plant breeding programs and core collections are important resources to capture this diversity. Many core collections have already been constructed by gene banks, whose main goal is to obtain a panel of a limited number of genotypes to simplify management practices and to improve shareability while retaining as much diversity as possible. However, as gene banks have a different composition and goal than plant breeding programs, constructing a core collection for a plant breeding program should consider different aspects. RESULTS: In this study, we present a novel approach for constructing a core collection by integrating both genomic and pedigree information to maximize the representation of the breeding germplasm in a minimum subset of genotypes while accounting for future genetic variation within a strawberry breeding program. Our stepwise approach starts with selecting the most important crossing parents of advanced selections and genotypes included for specific traits, to represent also future genetic variation. We then use pedigree-genomic-based relationship coefficients combined with the 'accession to nearest entry' criterion to complement the core collection and maximize its representativeness of the current breeding program. Combined pedigree-genomic-based relationship coefficients allow for accurate relationship estimation without the need to genotype every individual in the breeding program. CONCLUSIONS: This stepwise construction of a core collection in a strawberry breeding program can be applied in other plant breeding programs to construct core collections for various purposes.

Diversity and genetic architecture of agro-morphological traits in a core collection of European traditional tomato.

European traditional tomato varieties have been selected by farmers given their consistent performance and adaptation to local growing conditions. Here we developed a multipurpose core collection, comprising 226 accessions representative of the genotypic, phenotypic, and geographical diversity present in European traditional tomatoes, to investigate the basis of their phenotypic variation, gene×environment interactions, and stability for 33 agro-morphological traits. Comparison of the traditional varieties with a modern reference panel revealed that some traditional varieties displayed excellent agronomic performance and high trait stability, as good as or better than that of their modern counterparts. We conducted genome-wide association and genome-wide environment interaction studies and detected 141 quantitative trait loci (QTLs). Out of those, 47 QTLs were associated with the phenotype mean (meanQTLs), 41 with stability (stbQTLs), and 53 QTL-by-environment interactions (QTIs). Most QTLs displayed additive gene actions, with the exception of stbQTLs, which were mostly recessive and overdominant QTLs. Both common and specific loci controlled the phenotype mean and stability variation in traditional tomato; however, a larger proportion of specific QTLs was observed, indicating that the stability gene regulatory model is the predominant one. Developmental genes tended to map close to meanQTLs, while genes involved in stress response, hormone metabolism, and signalling were found within regions affecting stability. A total of 137 marker-trait associations for phenotypic means and stability were novel, and therefore our study enhances the understanding of the genetic basis of valuable agronomic traits and opens up a new avenue for an exploitation of the allelic diversity available within European traditional tomato germplasm.

The elite variations in germplasms for soybean breeding.

The genetic base of soybean cultivars (Glycine max (L.) Merr.) has been narrowed through selective domestication and specific breeding improvement, similar to other crops. This presents challenges in breeding new cultivars with improved yield and quality, reduced adaptability to climate change, and increased susceptibility to diseases. On the other hand, the vast collection of soybean germplasms offers a potential source of genetic variations to address those challenges, but it has yet to be fully leveraged. In recent decades, rapidly improved high-throughput genotyping technologies have accelerated the harness of elite variations in soybean germplasm and provided the important information for solving the problem of a narrowed genetic base in breeding. In this review, we will overview the situation of maintenance and utilization of soybean germplasms, various solutions provided for different needs in terms of the number of molecular markers, and the omics-based high-throughput strategies that have been used or can be used to identify elite alleles. We will also provide an overall genetic information generated from soybean germplasms in yield, quality traits, and pest resistance for molecular breeding.

Evaluation of Malus Germplasm Identifies Genetic Sources of Powdery Mildew and Frogeye Leaf Spot Resistance for Apple Breeding.

Apple is an important fruit crop of temperate regions. The narrow genetic base of commercially cultivated apples has resulted in its vulnerability to a large number of fungal, bacterial, and viral pathogens. Apple breeders are always seeking new sources of resistance within the cross-compatible Malus species that can be deployed into elite genetic backgrounds. We have evaluated resistance to two major fungal diseases of apples: powdery mildew and frogeye leaf spot, using a germplasm collection of 174 Malus accessions to identify novel sources of genetic resistance. In 2020 and 2021, we evaluated these accessions for the incidence and severity of powdery mildew and frogeye leaf spot diseases at Cornell AgriTech, Geneva, New York, in a partially managed orchard. The severity and incidence of powdery mildew and frogeye leaf spot, as well as weather parameters were recorded in June, July, and August. Total incidence of powdery mildew and frogeye leaf spot infections increased from 33 to 38%, and 56 to 97% in 2020 and 2021, respectively. Our analysis showed that relative humidity and precipitation correlate with powdery mildew and frogeye leaf spot susceptibility. The predictor variables with highest impact to the variability of powdery mildew were accessions and relative humidity in May. A total of 65 Malus accessions were found to be resistant to powdery mildew, and only one accession showed moderate resistance to frogeye leaf spot. Several of these accessions belong to Malus hybrid species and domesticated apples and can therefore be potential sources of novel resistance alleles for apple breeding.

Elucidation of genetic variation and population structure of melon genetic resources in the NARO Genebank, and construction of the World Melon Core Collection.

Numerous genetic resources of major crops have been introduced from around the world and deposited in Japanese National Agriculture and Food Research Organization (NARO) Genebank. Understanding their genetic variation and selecting a representative subset ("core collection") are essential for optimal management and efficient use of genetic resources. In this study, we conducted genotyping-by-sequencing (GBS) to characterize the genetic relationships and population structure in 755 accessions of melon genetic resources. The GBS identified 39,324 single-nucleotide polymorphisms (SNPs) that are distributed throughout the melon genome with high density (one SNP/10.6 kb). The phylogenetic relationships and population structure inferred using this SNP dataset are highly associated with the cytoplasm type and geographical origin. Our results strongly support the recent hypothesis that cultivated melon was established in Africa and India through multiple independent domestication events. Finally, we constructed a World Melon Core Collection that covers at least 82% of the genetic diversity and has a wide range of geographical origins and fruit morphology. The genome-wide SNP dataset, phylogenetic relationships, population structure, and the core collection provided in this study should largely contribute to genetic research, breeding, and genetic resource preservation in melon.

Genetic Diversity and Population Structure of a Wide Pisum spp. Core Collection.

Peas (Pisum sativum) are the fourth most cultivated pulses worldwide and a critical source of protein in animal feed and human food. Developing pea core collections improves our understanding of pea evolution and may ease the exploitation of their genetic diversity in breeding programs. We carefully selected a highly diverse pea core collection of 325 accessions and established their genetic diversity and population structure. DArTSeq genotyping provided 35,790 polymorphic DArTseq markers, of which 24,279 were SilicoDArT and 11,511 SNP markers. More than 90% of these markers mapped onto the pea reference genome, with an average of 2787 SilicoDArT and 1644 SNP markers per chromosome, and an average LD50 distance of 0.48 and 1.38 Mbp, respectively. The pea core collection clustered in three or six subpopulations depending on the pea subspecies. Many admixed accessions were also detected, confirming the frequent genetic exchange between populations. Our results support the classification of Pisum genus into two species, P. fulvum and P. sativum (including subsp. sativum, arvense, elatius, humile, jomardii and abyssinicum). In addition, the study showed that wild alleles were incorporated into the cultivated pea through the intermediate P. sativum subsp. jomardii and P. sativum subsp. arvense during pea domestication, which have important implications for breeding programs. The high genetic diversity found in the collection and the high marker coverage are also expected to improve trait discovery and the efficient implementation of advanced breeding approaches.