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10.1186/s12864-025-12417-9 http://scihub22266oqcxt.onion/10.1186/s12864-025-12417-9 41382026!?!41382026 Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=41382026&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215       BMC+Genomics 2025 ; ? (?): ? Nephropedia Template TP {{tp|p=41382026|t=2025. Integrated genomic analysis of a diverse maize population reveals novel genes and superior predictive models for ear diameter |pdf=|usr=}}{{41382026}} gab.com Text Integrated genomic analysis of a diverse maize population reveals novel genes and superior predictive models for ear diameter JO: BMC Genomics http://www.kidney.de/pget.php?&tw=1&pmid=41382026 #FOAvip BACKGROUND: Ear diameter (ED) is a key agronomic trait that significantly influences maize yield and is regulated by both genetic and environmental factors. RESULTS: We systematically dissected the genetic basis of ED using a diverse multi-parent population of 858 recombinant inbred lines (RILs). Through an integrated approach combining quantitative trait locus (QTL) mapping and genome-wide association study (GWAS), we identified multiple stable loci associated with ED. Notably, we pinpointed two novel and significant loci on chromosomes 5 and 7, which harbor key candidate genes: Zm00001d020000, encoding a phosphatidate cytidylyltransferase involved in membrane biosynthesis, and Zm00001d016356, a putative Kinesin-like protein potentially regulating cell division. Functional annotation, haplotype, and protein structural analyses support their roles in regulating ear development. A comprehensive comparison of 13 genomic selection (GS) models, which demonstrated that the non-linear support vector regression (SVR) model achieved superior predictive accuracy. This highlights the substantial contribution of non-additive genetic effects, such as epistasis, to ED. Furthermore, we identified 45 elite RILs with stable performance across environments, providing valuable breeding materials. CONCLUSIONS: Our study unveils novel SNPs and candidate genes, elucidated the complex genetic architecture underlying maize ear diameter. We demonstrate that integrating GWAS and linkage mapping with advanced GS models provides a powerful strategy to dissect complex traits and deliver practical resources for accelerating yield improvement in maize breeding programs. The candidate genes identified represent promising targets for future functional validation. Twit Text FOAVip Integrated genomic analysis of a diverse maize population reveals novel genes and superior predictive models for ear diameter ????BMC Genomics http://www.kidney.de/pget.php?&tw=1&pmid=41382026 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=41382026 #FOAvip English Wikipedia <ref>{{Cite pmid|41382026}}</ref> Integrated genomic analysis of a diverse maize population reveals novel genes and superior predictive models for ear diameter #MMPMID41382026 Wu X; Jiang F; Ijaz B; Hong X; Ye F; Dai T; Fan X BMC Genomics 2025[Dec]; ? (?): ? PMID41382026show ga BACKGROUND: Ear diameter (ED) is a key agronomic trait that significantly influences maize yield and is regulated by both genetic and environmental factors. RESULTS: We systematically dissected the genetic basis of ED using a diverse multi-parent population of 858 recombinant inbred lines (RILs). Through an integrated approach combining quantitative trait locus (QTL) mapping and genome-wide association study (GWAS), we identified multiple stable loci associated with ED. Notably, we pinpointed two novel and significant loci on chromosomes 5 and 7, which harbor key candidate genes: Zm00001d020000, encoding a phosphatidate cytidylyltransferase involved in membrane biosynthesis, and Zm00001d016356, a putative Kinesin-like protein potentially regulating cell division. Functional annotation, haplotype, and protein structural analyses support their roles in regulating ear development. A comprehensive comparison of 13 genomic selection (GS) models, which demonstrated that the non-linear support vector regression (SVR) model achieved superior predictive accuracy. This highlights the substantial contribution of non-additive genetic effects, such as epistasis, to ED. Furthermore, we identified 45 elite RILs with stable performance across environments, providing valuable breeding materials. CONCLUSIONS: Our study unveils novel SNPs and candidate genes, elucidated the complex genetic architecture underlying maize ear diameter. We demonstrate that integrating GWAS and linkage mapping with advanced GS models provides a powerful strategy to dissect complex traits and deliver practical resources for accelerating yield improvement in maize breeding programs. The candidate genes identified represent promising targets for future functional validation. ?Integrated genomic analysis of a diverse maize population reveals nove(epmc).pdf DeepDyve Pubget Overpricing