The Affymetrix Medicago GeneChip® array is applicable for transcript analysis of alfalfa (Medicago sativa)

2006 ◽  
Vol 33 (8) ◽  
pp. 783 ◽  
Author(s):  
Mesfin Tesfaye ◽  
Kevin A. T. Silverstein ◽  
Bruna Bucciarelli ◽  
Deborah A. Samac ◽  
Carroll P. Vance
Keyword(s):  
Medicago Sativa ◽  
Transcript Analysis ◽  
Crop Species ◽  
Trifoliate Leaf ◽  
Model Legume ◽  
Genome Wide ◽  
Medicago Sativa L ◽  
Genome Array ◽  
Medicago Species ◽  
Medicago Genechip

The recently released Affymetrix GeneChip® Medicago Genome Array contains approximately 52 700 probe sets representing genes in both the model legume Medicago truncatula Gaertn. and the closely related crop species Medicago sativa L. (alfalfa). We evaluated the utility of the Medicago GeneChip® for monitoring genome-wide expression of M. truncatula and alfalfa seedlings grown to the first trifoliate leaf stage. We found that approximately 40–54% of the Medicago probes were detected in leaf or root samples of alfalfa or M. truncatula. Approximately 45–59% of the detected Medicago probes were called ‘present’ in all replicate GeneChips of Medicago species, indicating a considerable overlap in the number and type of Medicago probes detected between root and leaf organs. Nevertheless, gene expression differences between roots and leaf organs accounted for approximately 17% of the total variation, regardless of the Medicago species from which the samples were harvested. The result shows that the Medicago GeneChip® is applicable for transcript analysis for both alfalfa and M. truncatula.

Artificial microRNA (amiRNA) induced gene silencing in alfalfa (Medicago sativa)

Botany ◽  
2013 ◽  
Vol 91 (2) ◽  
pp. 117-122 ◽  
Author(s):  
Julian C. Verdonk ◽  
Michael L. Sullivan
Keyword(s):  
Gene Silencing ◽  
Medicago Sativa ◽  
Target Gene ◽  
Target Genes ◽  
Mirna Precursor ◽  
Crop Species ◽  
Forage Crop ◽  
Ribonucleic Acids ◽  
Endogenous Gene ◽  
Medicago Sativa L

Gene silencing is a powerful technique that allows the study of the function of specific genes by selectively reducing their transcription. Several different approaches can be used, however they all have in common the artificial generation of single stranded small ribonucleic acids (RNAs) that are utilized by the endogenous gene silencing machinery of the organism. Artificial microRNAs (amiRNA) can be used to very specifically target genes for silencing because only a short sequence of 21 nucleotides of the gene of interest is used. Gene silencing via amiRNA has been developed for Arabidopsis thaliana (L.) Heynh. and rice using endogenous microRNA (miRNA) precursors and has been shown to also work effectively in other dicot species using the arabidopsis miRNA precursor. Here, we demonstrate that the arabidopsis miR319 precursor can be used to silence genes in the important forage crop species alfalfa (Medicago sativa L.) by silencing the expression of a transgenic beta-glucuronidase (GUSPlus) target gene.

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.

Genome-Wide Identification and Expression Profiling of the ERF Gene Family in Medicago sativa L. Under Various Abiotic Stresses

2019 ◽  
Vol 38 (10) ◽  
pp. 1056-1068 ◽  
Author(s):  
Xiaoyu Jin ◽  
Xiaofan Yin ◽  
Boniface Ndayambaza ◽  
Zhengshe Zhang ◽  
Xueyang Min ◽  
...  
Keyword(s):  
Gene Family ◽  
Medicago Sativa ◽  
Expression Profiling ◽  
Abiotic Stresses ◽  
Genome Wide ◽  
Medicago Sativa L
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