WRKY Transcription Factors in Medicago sativa L.: Genome-Wide Identification and Expression Analysis Under Abiotic Stress

2020 ◽  
Vol 39 (12) ◽  
pp. 2212-2225
Author(s):  
Pei Mao ◽  
Xiaoyu Jin ◽  
Qinyan Bao ◽  
Cuo Mei ◽  
Qiang Zhou ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Abiotic Stress ◽  
Medicago Sativa ◽  
Expression Analysis ◽  
Wrky Transcription Factors ◽  
Genome Wide ◽  
Medicago Sativa L

scholarly journals Strategies to Increase Prediction Accuracy in Genomic Selection of Complex Traits in Alfalfa (Medicago sativa L.)

Cells ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 3372
Author(s):  
Cesar A. Medina ◽  
Harpreet Kaur ◽  
Ian Ray ◽  
Long-Xi Yu
Keyword(s):  
Salt Stress ◽  
Abiotic Stress ◽  
Medicago Sativa ◽  
Genomic Selection ◽  
Complex Traits ◽  
Prediction Accuracy ◽  
Breeding Value ◽  
Phenotypic Traits ◽  
Genome Wide ◽  
Medicago Sativa L

Agronomic traits such as biomass yield and abiotic stress tolerance are genetically complex and challenging to improve through conventional breeding approaches. Genomic selection (GS) is an alternative approach in which genome-wide markers are used to determine the genomic estimated breeding value (GEBV) of individuals in a population. In alfalfa (Medicago sativa L.), previous results indicated that low to moderate prediction accuracy values (<70%) were obtained in complex traits, such as yield and abiotic stress resistance. There is a need to increase the prediction value in order to employ GS in breeding programs. In this paper we reviewed different statistic models and their applications in polyploid crops, such as alfalfa and potato. Specifically, we used empirical data affiliated with alfalfa yield under salt stress to investigate approaches that use DNA marker importance values derived from machine learning models, and genome-wide association studies (GWAS) of marker-trait association scores based on different GWASpoly models, in weighted GBLUP analyses. This approach increased prediction accuracies from 50% to more than 80% for alfalfa yield under salt stress. Finally, we expended the weighted GBLUP approach to potato and analyzed 13 phenotypic traits and obtained similar results. This is the first report on alfalfa to use variable importance and GWAS-assisted approaches to increase the prediction accuracy of GS, thus helping to select superior alfalfa lines based on their GEBVs.

scholarly journals Genome-wide identification of the MADS-box transcription factor family in autotetraploid cultivated alfalfa (Medicago sativa L.) and expression analysis under abiotic stress

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Xueming Dong ◽  
Hao Deng ◽  
Wenxue Ma ◽  
Qiang Zhou ◽  
Zhipeng Liu
Keyword(s):  
Phylogenetic Analysis ◽  
Transcription Factors ◽  
Abiotic Stress ◽  
Medicago Sativa ◽  
Expression Analysis ◽  
Expression Profiles ◽  
Pcr Analysis ◽  
Type I ◽  
Segmental Duplications ◽  
Mads Box

Abstract Background Alfalfa, the “queen of forage”, is the most extensively cultivated forage legume in the world. The development and yield of alfalfa are seriously limited by abiotic stress. MADS-box transcription factors are one of the largest gene families and play a pivotal role in plant development and abiotic stress. However, little is known regarding the MADS-box transcription factors in autotetraploid cultivated alfalfa. Results In the present study, we identified 120 MsMADS-box genes in the alfalfa genome. Phylogenetic analysis indicated that 75 type-I MsMADS-box genes were classified into the Mα, Mβ, and Mγ subgroups, and 45 type-II MsMADS-box genes were classified into 11 subgroups. The promoter region of MsMADS-box genes containing several hormone and stress related elements. Chromosomal location analysis revealed that 117 MsMADS-box genes were unevenly distributed on 32 chromosomes, and the remaining three genes were located on unmapped scaffolds. A total of nine pairs of segmental duplications and four groups of tandem duplications were found. Expression analysis showed that MsMADS-box genes were differentially expressed in various tissues and under abiotic stresses. qRT-PCR analysis revealed that the expression profiles of eight selected MsMADS-box genes were distinct under various stresses. Conclusions In this study, MsMADS-box genes were identified in the cultivated alfalfa genome based on autotetraploid level, and further confirmed by Gene Ontology (GO) analysis, phylogenetic analysis, sequence features and expression analysis. Taken together, these findings will provide clues for further study of MsMADS-box functions and alfalfa molecular breeding. Our study is the first to systematically identify and characterize the MADS-box transcription factors in autotetraploid cultivated alfalfa (Medicago sativa L.), and eight MsMADS-box genes were significantly involved in response to various stresses.

Sign in / Sign up

Export Citation Format

Share Document