Fused Graphical Lasso Recovers Flowering Time Mutation Genes in Arabidopsis thaliana Academic Article

abstract

• Conventional breeding approaches that focus on yield under highly favorable nutrient conditions have resulted in reduced genetic and trait diversity in crops. Under the growing threat from climate change, the mining of novel genes in more resilient varieties can help dramatically improve trait improvement efforts. In this work, we propose the use of the joint graphical lasso for discovering genes responsible for desired phenotypic traits. We prove its efficiency by using gene expression data for wild type and delayed flowering mutants for the model plant. Arabidopsis thaliana shows that it recovers the mutation causing genes LNK1 and LNK2. Some novel interactions of these genes were also predicted. Observing the network level changes between two phenotypes can also help develop meaningful biological hypotheses regarding the novel functions of these genes. Now that this data analysis strategy has been validated in a model plant, it can be extended to crop plants to help identify the key genes for beneficial traits for crop improvement.

authors

• Datta, Aniruddha
• Thomson, Michael

published proceedings

• INVENTIONS

author list (cited authors)

• Kapoor, R., Datta, A., & Thomson, M.

citation count

• 2

complete list of authors

• Kapoor, Rajan||Datta, Aniruddha||Thomson, Michael

publication date

• 2021

publisher

• MDPI  Publisher

published in

• Inventions  Journal

keywords

• Arabidopsis Thaliana
• Flowering Time
• Fused Lasso Penalty
• Gaussian Graphical Models
• Joint Graphical Lasso

Digital Object Identifier (DOI)

• 10.3390/inventions6030052

start page

• 52

end page

• 52

volume

• 6

issue

• 3

URL

• http://dx.doi.org/10.3390/inventions6030052