Abstract

The development of genetically modified crops (GM) includes the discovery of candidate genes through bioinformatics analysis using genomics data, gene expression, and others. Proteins of unknown function (PUFs) are interesting targets for GM crops breeding pipelines for the novelty associated with such targets and also to avoid copyright protection. One method of inferring the putative function of PUFs is by relating them to factors of interest such as abiotic stresses using orthology and co-expression networks, in a guilt-by-association manner. In this regard, we have downloaded, analyzed, and processed genomics data of 53 angiosperms, totaling 1,862,010 genes and 2,332,974 RNA. Diamond and InterproScan were used to discover 72,266 PUFs for all organisms. RNA-seq datasets related to abiotic stresses were downloaded from NCBI/GEO. The RNA-seq data was used as input to the LSTrAP software to construct co-expression networks. LSTrAP also created clusters of transcripts with correlated expression, whose members are more probably related to the molecular mechanisms associated with abiotic stresses in the plants. Orthologous groups were created (OrhtoMCL) using all 2,332,974 proteins in order to associate PUFs to abiotic stress-related clusters of co-expression and therefore infer their function in a guilt-by-association manner. A freely available web resource named “Plant Co-expression Annotation Resource” (https://www.machado.cnptia.embrapa.br/plantannot), Plantannot, was created to provide indexed queries to search for PUF putatively associated with abiotic stresses. The web interface also allows browsing, querying, and retrieving of public genomics data from 53 plants. We hope Plantannot to be useful for researchers trying to obtain novel GM crops resistant to climate change hazards.

Highlights

  • In the last decades, the ability to genetically engineer plants demonstrated the potential to create genetically modified (GM) crops with favorable economic outcomes [1].The main achievement in this area was the development of improved plants tolerant to herbicide and resistant to insects, nutritional composition improvements are about to happen [2]

  • The RNA-seq data was used as input to the LSTrAP software to construct coexpression networks

  • We present a web resource named “Plant co-expression annotation resource” which uses plant genomics data, RNA sequencing data, orthology, and co-expression networks to enable the identification of proteins of unknown function (PUF) as abiotic stress-related candidates to enter GM crop breeding pipelines

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Summary

Background

The ability to genetically engineer plants demonstrated the potential to create genetically modified (GM) crops with favorable economic outcomes [1]. The first phase for creating GM crops is the candidate gene discovery, which relies on bioinformatics analyses of huge volumes of genomics data available on public resources [8, 9] These proteins of unknown function (PUF) are very prevalent in eukaryotic genomes and may play a role in determining the differences between species [10] and may be related to resistance to abiotic stresses [11]. We present a web resource named “Plant co-expression annotation resource” (https://www.machado.cnptia.embrapa.br/plantannot) which uses plant genomics data, RNA sequencing data, orthology, and co-expression networks to enable the identification of PUFs as abiotic stress-related candidates to enter GM crop breeding pipelines.

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