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Communication Dans Un Congrès Année : 2022

Sentiment Analysis Decision System for Tracking Climate Change Opinion in Twitter

Résumé

Unlabelled - Yield and quality are two crucial breeding objects of wheat therein grain weight and grain protein content (GPC) are two key relevant factors correspondingly. Investigations of their genetic mechanisms represent special significance for breeding. In this study, 199 F plants and corresponding F families derived from Nongda3753 (ND3753) and its EMS-generated mutant 564 (M564) were used to investigate the genetic basis of larger grain and higher GPC of M564. QTL analysis identified a total of 33 environmentally stable QTLs related to thousand grain weight (TGW), grain area (GA), grain circle (GC), grain length (GL), grain width (GW), and GPC on chromosomes 1B, 2A, 2B, 4D, 6B, and 7D, respectively, among which , , , and shared overlap confidence interval on chromosome 6B. This interval contained the gene playing the same role as the QTLs, so was cloned and sequenced. Sequence alignment revealed two G/A SNPs between two parents, among which the SNP in the seventh exon led to a premature termination in M564. A KASP marker was developed based on the SNP, and single-marker analysis on biparental populations showed that the mutant allele could significantly increase GW and TGW, but had no effect on GPC. Distribution detection of the mutant allele through KASP marker genotyping and sequence alignment against databases ascertained that no materials harbored this allele within natural populations. This allele was subsequently introduced into three different varieties through molecular marker-assisted backcrossing, and it was revealed that the allele had a significant effect on simultaneously increasing GW, TGW, and even GPC in all of three backgrounds. Summing up the above, it could be concluded that a novel elite allele of was artificially created and might play an important role in wheat breeding for high yield and quality. Supplementary information - The online version contains supplementary material available at 10.1007/s11032-024-01455-y.
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Dates et versions

hal-04217816 , version 1 (26-09-2023)

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Mustapha Lydiri, Youssef El Habouz, Hicham Zougagh. Sentiment Analysis Decision System for Tracking Climate Change Opinion in Twitter. 7th International Conference on Business Intelligence, CBI 2022, May 2022, Khouribga, Morocco. pp.188-196, ⟨10.1007/978-3-031-06458-6_15⟩. ⟨hal-04217816⟩
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