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    Large-scale integration of meta-QTL and genome-wide association study discovers the genomic regions and candidate genes for yield and yield-related traits in bread wheat. TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik KEY MESSAGE:Based on the large-scale integration of meta-QTL and Genome-Wide  Association Study, 76 high-confidence MQTL regions and 237 candidate genes that affected wheat yield and yield-related traits were discovered. Improving yield and yield-related traits are key goals in wheat breeding program. The integration of accumulated wheat genetic resources provides an opportunity to uncover important genomic regions and candidate genes that affect wheat yield. Here, a comprehensive meta-QTL analysis was conducted on 2230 QTL of yield-related traits obtained from 119 QTL studies. These QTL were refined into 145 meta-QTL (MQTL), and 89 MQTL were verified by GWAS with different natural populations. The average confidence interval (CI) of these MQTL was 2.92 times less than that of the initial QTL. Furthermore, 76 core MQTL regions with a physical distance less than 25 Mb were detected. Based on the homology analysis and expression patterns, 237 candidate genes in the MQTL involved in photoperiod response, grain development, multiple plant growth regulator pathways, carbon and nitrogen metabolism and spike and flower organ development were determined. A novel candidate gene TaKAO-4A was confirmed to be significantly associated with grain size, and a CAPS marker was developed based on its dominant haplotype. In summary, this study clarified a method based on the integration of meta-QTL, GWAS and homology comparison to reveal the genomic regions and candidate genes that affect important yield-related traits in wheat. This work will help to lay a foundation for the identification, transfer and aggregation of these important QTL or candidate genes in wheat high-yield breeding. 10.1007/s00122-021-03881-4
    Genome-Wide Association Study Identifies Candidate Genes Related to the Linoleic Acid Content in Soybean Seeds. Di Qin,Piersanti Angela,Zhang Qi,Miceli Cristina,Li Hui,Liu Xiaoyi International journal of molecular sciences Soybean ( (L.) Merrill) oil is a complex mixture of five fatty acids (palmitic, stearic, oleic, linoleic, and linolenic). The high content of linoleic acid (LA) contributes to the oil having poor oxidative stability. Therefore, soybean seed with a lower LA content is desirable. To investigate the genetic architecture of LA, we performed a genome-wide association study (GWAS) using 510 soybean cultivars collected from China. The phenotypic identification results showed that the content of LA varied from 36.22% to 72.18%. The GWAS analysis showed that there were 37 genes related to oleic acid content, with a contribution rate of 7%. The candidate gene () on chromosome 4 was detected in three consecutive years. The showed a negative correlation with the LA content and the correlation coefficient was -0.912. To test whether can lead to a lower LA content in soybean, we introduced into the soybean genome. Matrix-assisted laser desorption/ionization time-of-flight imaging mass spectrometry (MALDI-TOF IMS) showed that the overexpression of leads to a lower LA content in soybean seeds. Meanwhile, RNA-seq verified that -overexpressed soybean lines showed a lower accumulation of and than control lines. Our results indicate that the down-regulation of the gene triggered by the transcription factor is the underlying mechanism reducing the LA level of seed. Our results provide novel insights into the genetic architecture of LA and pinpoint potential candidate genes for further in-depth studies. 10.3390/ijms23010454