|SHARIATIPOUR, NIKWAN - Shiraz University|
|HEIDARI, BAHRAM - Shiraz University|
|TAHMASEBI, AHMAD - Shiraz University|
Submitted to: Frontiers in Plant Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/6/2021
Publication Date: 10/12/2021
Citation: Shariatipour, N.A., Heidari, B.M., Tahmasebi, A.M., Richards, C.M. 2021. Comparative genomic analysis of QTLs associated with micronutrient contents, grain quality and agronomic traits in wheat (Triticum aestivum L.). Frontiers in Plant Science. 12. Article e709817. https://doi.org/10.3389/fpls.2021.709817.
Interpretive Summary: This study extends our understanding of the genetic architecture of grain yield, quality and micronutrient content in wheat by first improving the mapping precision using meta-QTL analysis and then leveraging comparative genomic methods to locate homologous regions from wheat within the genomes of rice and corn. Using these methods, we were able to identify 16 conserved regions (orthologs) that are present in all three species. By exploiting the more advanced sequence characterization of these related species, the data supports the identification of several gene candidates. This research helps us move from genetic and physical mapping to causative genes and prospects for understanding the genetic mechanisms for these important agronomic traits.
Technical Abstract: Comparative genomics and meta-QTL (MQTL) analysis are important tools for identification of reliable and stable QTLs and functional genes controlling quantitative traits. We conducted a meta-analysis to identify the most stable QTLs for grain yield, grain quality traits and micronutrient contents in wheat. A total of 735 QTLs retrieved from 27 independent mapping populations reported in the last 13 years were used for meta-analysis. The results showed that 449 QTLs were successfully projected on to the genetic consensus map which condensed to 100 MQTLs distributed on wheat chromosomes. This consolidation of MQTLs resulted in a 3-fold reduction in the confidence interval (CI) compared with CI for the initial QTLs. Projection of QTLs revealed that the majority of QTLs and MQTLs were in non-telomeric regions of chromosomes. The majority of micronutrients MQTLs located on the A and D genome. The QTLs for thousand kernel weights were frequently associated with QTLs for grain yield and grain protein content with co-localization occurring at 55 % and 63%, respectively. The co-localization of QTLs for grain yield/grain Fe and QTLs for grain Fe/grain Zn were 52% and 66%, respectively. The genomic collinearity within Poaceae allowed us to identify 16 orthologous (OrMQTLs) QTLs in wheat, rice and maize. Annotation of promising candidate genes (CGs) located in the genomic intervals of the stable MQTLs indicated that several CG’s (e.g. TraesCS2A02G141400, TraesCS3B02G040900, TraesCS4D02G323700, TraesCS3B02G077100, TraesCS4D02G290900) had effects on micronutrients contents, yield and yield related traits. The mapping refinements leading to the identification of these CG’s provide an opportunity to understand the genetic mechanisms.