Unknown

Dataset Information

0

Identification of immunity-related genes in Arabidopsis and cassava using genomic data.


ABSTRACT: Recent advances in genomic and post-genomic technologies have provided the opportunity to generate a previously unimaginable amount of information. However, biological knowledge is still needed to improve the understanding of complex mechanisms such as plant immune responses. Better knowledge of this process could improve crop production and management. Here, we used holistic analysis to combine our own microarray and RNA-seq data with public genomic data from Arabidopsis and cassava in order to acquire biological knowledge about the relationships between proteins encoded by immunity-related genes (IRGs) and other genes. This approach was based on a kernel method adapted for the construction of gene networks. The obtained results allowed us to propose a list of new IRGs. A putative function in the immunity pathway was predicted for the new IRGs. The analysis of networks revealed that our predicted IRGs are either well documented or recognized in previous co-expression studies. In addition to robust relationships between IRGs, there is evidence suggesting that other cellular processes may be also strongly related to immunity.

SUBMITTER: Leal LG 

PROVIDER: S-EPMC4357831 | biostudies-other | 2013 Dec

REPOSITORIES: biostudies-other

altmetric image

Publications

Identification of immunity-related genes in Arabidopsis and cassava using genomic data.

Leal Luis Guillermo LG   Perez Álvaro Á   Quintero Andrés A   Bayona Ángela Á   Ortiz Juan Felipe JF   Gangadharan Anju A   Mackey David D   López Camilo C   López-Kleine Liliana L  

Genomics, proteomics & bioinformatics 20131206 6


Recent advances in genomic and post-genomic technologies have provided the opportunity to generate a previously unimaginable amount of information. However, biological knowledge is still needed to improve the understanding of complex mechanisms such as plant immune responses. Better knowledge of this process could improve crop production and management. Here, we used holistic analysis to combine our own microarray and RNA-seq data with public genomic data from Arabidopsis and cassava in order to  ...[more]

Similar Datasets

| S-EPMC2762073 | biostudies-literature
| S-EPMC3434191 | biostudies-literature
| S-EPMC5765366 | biostudies-literature
| S-EPMC7289146 | biostudies-literature
| S-EPMC5961004 | biostudies-literature
| S-EPMC3701084 | biostudies-literature
| S-EPMC5004182 | biostudies-literature
| S-EPMC2383967 | biostudies-literature
| S-EPMC5860558 | biostudies-other
| S-EPMC6355707 | biostudies-literature