Eggplant (; 2 = 24) is an economically important fruit crop of the family Solanaceae that was domesticated in India and Southeast Asia. Construction of a high-resolution genetic map and map-based gene mining in eggplant have lagged behind other crops within the family such as tomato and potato. In this study, we conducted high-throughput single nucleotide polymorphism (SNP) discovery in the eggplant genome using specific length amplified fragment (SLAF) sequencing and constructed a high-density genetic map for the quantitative trait locus (QTL) analysis of multiple traits. An interspecific F population of 121 individuals was developed from the cross between cultivated eggplant "1836" and the wild relative "1809." Genomic DNA extracted from parental lines and the F population was subjected to high-throughput SLAF sequencing. A total of 111.74 Gb of data and 487.53 million pair-end reads were generated. A high-resolution genetic map containing 2,122 SNP markers and 12 linkage groups was developed for eggplant, which spanned 1530.75 cM, with an average distance of 0.72 cM between adjacent markers. A total of 19 QTLs were detected for stem height and fruit and leaf morphology traits of eggplant, explaining 4.08-55.23% of the phenotypic variance. These QTLs were distributed on nine linkage groups (LGs), but not on LG2, 4, and 9. The number of SNPs ranged from 2 to 11 within each QTL, and the genetic interval varied from 0.15 to 10.53 cM. Overall, the results establish a foundation for the fine mapping of complex QTLs, candidate gene identification, and marker-assisted selection of favorable alleles in eggplant breeding.
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http://dx.doi.org/10.3389/fgene.2020.00178 | DOI Listing |
BMC Public Health
December 2024
Upstream Lab, MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, Unity Health Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada.
Background: Machine learning (ML) is increasingly used in population and public health to support epidemiological studies, surveillance, and evaluation. Our objective was to conduct a scoping review to identify studies that use ML in population health, with a focus on its use in non-communicable diseases (NCDs). We also examine potential algorithmic biases in model design, training, and implementation, as well as efforts to mitigate these biases.
View Article and Find Full Text PDFBMC Plant Biol
December 2024
Hami-melon Research Center, Xinjiang Academy of Agricultural Sciences, Urumqi, Xinjiang, 830091, China.
Fruit diameter is one of important agronomy traits that has greatly impacts fruit yield and commercial value in cucumber (Cucumis sativus L.). Hence, we preliminary mapping of fruit diameter was conducted to refine its genetic locus.
View Article and Find Full Text PDFSci Rep
December 2024
Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, 818 Fenghua Road, Jiangbei District, Ningbo, China.
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by limited effective treatments, underscoring the critical need for early detection and diagnosis to improve intervention outcomes. This study integrates various bioinformatics methodologies with interpretable machine learning to identify reliable biomarkers for AD diagnosis and treatment. By leveraging differentially expressed genes (DEGs) analysis, weighted gene co-expression network analysis (WGCNA), and construction of Protein-Protein Interaction (PPI) Networks, we meticulously analyzed the AD dataset from the GEO database to pinpoint Hub genes.
View Article and Find Full Text PDFPLoS One
December 2024
Department of Biotechnology and Food Science, NTNU - Norwegian University of Science and Technology, Trondheim, Norway.
Disease networks offer a potential road map of connections between diseases. Several studies have created disease networks where diseases are connected either based on shared genes or Single Nucleotide Polymorphism (SNP) associations. However, it is still unclear to which degree SNP-based networks map to empirical, co-observed diseases within a different, general, adult study population spanning over a long time period.
View Article and Find Full Text PDFCirc Res
December 2024
Cardiovascular Research Center, Massachusetts General Hospital, Boston. (C.C., P.X., Z.Y., Y.S., E.S.L., J.D.R., M.C.H.).
Background: Preeclampsia is a hypertensive disorder of pregnancy characterized by systemic endothelial dysfunction. The pathophysiology of preeclampsia remains incompletely understood. This study used human venous endothelial cell (EC) transcriptional profiling to investigate potential novel mechanisms underlying EC dysfunction in preeclampsia.
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