Genetic diversity and population structure of core watermelon (Citrullus lanatus) genotypes using DArTseq-based SNPs

Watermelon [Citrullus lanatus (Thunb.) Matsum. & Nakai var. lanatus] is an economically important vegetable belonging to the Cucurbitaceae family. Genotypes that exhibit agronomically important traits are selected for the development of elite cultivars. Understanding the genetic diversity and the genotype population structure based on molecular markers at the genome level can speed up the utilization of diverse genetic resources for varietal improvement. In the present study, we carried out an analysis of genetic diversity based on 3882 SNP markers across 37 core watermelon genotypes, including the most widely used watermelon varieties and wild watermelon. Based on the SNP genotyping data of the 37 watermelon genotypes screened, gene diversity and polymorphism information content values across chromosomes varied between 0.03–0.5 and 0.02–0.38, with averages of 0.14 and 0.13, respectively. The two wild watermelon genotypes were distinct from cultivated varieties and the remaining 35 cultivated genotypes were differentiated into three major clusters: 20 genotypes were grouped in cluster I; 11 genotypes were grouped in cluster II; three advanced breeding lines of yellow fruit flesh and genotype SW043 were grouped in cluster III. The results from neighbour-joining dendrogram, principal coordinate analysis and STRUCTURE analysis approaches were consistent, and the grouping of genotypes was generally in agreement with their origins. Here we reveal the genetic relationships among the core watermelon genotypes maintained at the Jiangsu Academy of Agricultural Sciences, China. The molecular and phenotypic characterization of the existing core watermelon genotypes, together with specific agronomic characteristics, can be utilized by researchers and breeders for future watermelon improvement

Rapid and Sensitive Detection of Didymella bryoniae by Visual Loop-Mediated Isothermal Amplification Assay

Didymella bryoniae is a pathogenic fungus that causes gummy stem blight (GSB) in Cucurbitaceae crops (e.g. cantaloupe, muskmelon, cucumber, and watermelon). GSB produces lesions on the stems and leaves, and can also be spread by seeds. Here, we developed a rapid, visual, and sensitive loop-mediated amplification (LAMP) assay for D. bryoniae detection based on sequence-characterized amplified regions (GenBank accession nos GQ872461 and GQ872462) common to the two random amplification of polymorphic DNA group genotypes (RGI and RGII) of D. bryoniae; ideal conditions for detection were optimized for completion in 45 min at 63°C. The sensitivity and specificity of the LAMP assay were further analyzed in comparison with those of a conventional polymerase chain reaction (PCR). The sensitivity of the LAMP assay was 1000-fold higher than that of conventional PCR with a detection limit of 0.1 fg μL−1 of targeted DNA. The LAMP assay could be accomplished in about 45 min, with the results visible to the naked eye. The assay showed high specificity in discriminating all D. bryoniae isolates from seven other fungal pathogens that occur in Cucurbitaceae crops. The LAMP assay also detected D. bryoniae infection in young muskmelon leaves with suspected early symptoms of GSB disease. Hence, the technique has great potential for developing rapid and sensitive visual detection methods for the D. bryoniae pathogen in crops and seeds. This method has potential application in early prediction of disease and reducing the risk of epidemics

Construction of a high-density DArTseq SNP-based genetic map and identification of genomic regions with segregation distortion in a genetic population derived from a cross between feral and cultivated-type watermelon

Watermelon [Citrullus lanatus (Thunb.) Matsum. & Nakai] is an economically important vegetable crop grown extensively worldwide. To facilitate the identification of agronomically important traits and provide new information for genetic and genomic research on this species, a high-density genetic linkage map of watermelon was constructed using an F2 population derived from a cross between elite watermelon cultivar K3 and wild watermelon germplasm PI 189225. Based on a sliding window approach, a total of 1,161 bin markers representing 3,465 SNP markers were mapped onto 11 linkage groups corresponding to the chromosome pair number of watermelon. The total length of the genetic map is 1,099.2cM, with an average distance between bins of 1.0cM. The number of markers in each chromosome varies from 62 in chromosome 07 to 160 in chromosome 05. The length of individual chromosomes ranged between 61.8cM for chromosome 07 and 140.2cM for chromosome 05. A total of 616 SNP bin markers showed significant (P<0.05) segregation distortion across all 11 chromosomes, and 513 (83.3%) of these distorted loci showed distortion in favor of the elite watermelon cultivar K3 allele and 103 were skewed toward PI 189225. The number of SNPs and InDels per Mb varied considerably across the segregation distorted regions (SDRs) on each chromosome, and a mixture of dense and sparse SNPs and InDel SDRs coexisted on some chromosomes suggesting that SDRs were randomly distributed throughout the genome. Recombination rates varied greatly among each chromosome, from 2.0 to 4.2 centimorgans per megabase (cM/Mb). An inconsistency was found between the genetic and physical positions on the map for a segment on chromosome 11. The high-density genetic map described in the present study will facilitate fine mapping of quantitative trait loci, the identification of candidate genes, map-based cloning, as well as marker-assisted selection (MAS) in watermelon breeding programs

Non-traditional cognitive brain network involvement in insulo-Sylvian gliomas: a case series study and clinical experience using Quicktome

Abstract Background Patients with insulo-Sylvian gliomas continue to present with severe morbidity in cognitive functions primarily due to neurosurgeons’ lack of familiarity with non-traditional brain networks. We sought to identify the frequency of invasion and proximity of gliomas to portions of these networks. Methods We retrospectively analyzed data from 45 patients undergoing glioma surgery centered in the insular lobe. Tumors were categorized based on their proximity and invasiveness of non-traditional cognitive networks and traditionally eloquent structures. Diffusion tensor imaging tractography was completed by creating a personalized brain atlas using Quicktome to determine eloquent and non-eloquent networks in each patient. Additionally, we prospectively collected neuropsychological data on 7 patients to compare tumor-network involvement with change in cognition. Lastly, 2 prospective patients had their surgical plan influenced by network mapping determined by Quicktome. Results Forty-four of 45 patients demonstrated tumor involvement (< 1 cm proximity or invasion) with components of non-traditional brain networks involved in cognition such as the salience network (SN, 60%) and the central executive network (CEN, 56%). Of the seven prospective patients, all had tumors involved with the SN, CEN (5/7, 71%), and language network (5/7, 71%). The mean scores of MMSE and MOCA before surgery were 18.71 ± 6.94 and 17.29 ± 6.26, respectively. The two cases who received preoperative planning with Quicktome had a postoperative performance that was anticipated. Conclusions Non-traditional brain networks involved in cognition are encountered during surgical resection of insulo-Sylvian gliomas. Quicktome can improve the understanding of the presence of these networks and allow for more informed surgical decisions based on patient functional goals