Abiotic Stress Responses in Plants: Unraveling the Complexity of Genes and Networks to Survive - Abiotic Stress: Plant Responses and Applications in Agriculture - page 71

Most of the plant system biology approaches relied on three main axes: transcriptomics,
proteomics and metabolomics (see Figure 1).
In addition to these previous studies, interaction between DNA-proteins and Proteins-proteins
- interactomes - are being also used with success to identify regulatory proteins involved in
complex whole plant responses [282]. Bioinformatics has been crucial in every aspect of Omics-
based research to manage various types of genome-scale data sets effectively and extract
valuable information and facilitate knowledge exchange with other model organisms [278,
283]. A comprehensive list of the analytical bioinformatics platforms available constituting an
essential infrastructure for systems analysis can be found in [278].
5.1. Transcriptomics
Transcriptomics, also referred as expression profiling, captures spatial and temporal gene
expression within plant tissues or cell populations on a specific biological context (e.g.
genotype, growth or environmental condition). In many instances transcriptomic analysis is
used to screen for candidate genes for abiotic stress improvement programs [280] or to predict
the tentative gene function by the association of differently expressed or co-expressed genes
with the plant phenotype alteration [284]. Transcriptomic approaches should incorporate
highly specific, sensitive and quantitative measurements over a large dynamic range with a
flexibility to identify unanticipated novelties in transcript structures and sequences [285].
Determination of large scale transcript profiles or identification of differentially regulated
genes in plants can be performed by various techniques, such as DNA microarrays, serial
analysis of gene expression (SAGE) or more recently Digital Gene Expression (DGE) profiling
taking advantage of next-generation sequencing (NGS) based tools such as RNA sequencing
(RNA-seq) [279, 280, 285]. The hybridization-based method, such as that used in microarray
analyses, together with the availability of completed genomes sequences and increasing public
repositories of available microarray data and data analysis tools have opened new avenues to
genome-wide analysis of plant stress responses [278, 280].
Cassava ( Manihot esculenta Crantz) is an important tropical root crop adapted to a wide range
of environmental stimuli, such as drought and acid soils, but it is an extremely cold-sensitive
species [286]. A transcriptome profiling of cassava apical shoots, that were submitted to a
progressive cold stress, was conducted using a dedicated 60-mer oligonucleotide microarray
representing 20,840 cassava genes has identified a total of 508 transcripts [287]. Those differ‐
entially expressed transcripts were identified as early cold-responsive genes in which 319
sequences had functional descriptions when aligned with Arabidopsis proteins. Various
stress-associated genes with a wide range of biological functions were found, such as signal
transduction components (e.g., MAP kinase 4), transcription factors (TFs, e.g., RAP2.11 and
AP2-EREBP), and active oxygen species scavenging enzymes (e.g., catalase 2), as well as
photosynthesis-related genes (e.g., PsaL). This work provided useful candidate genes for
genetic improvement in this species and suggested that the dynamic expression changes
observed reflect the integrative controlling and transcriptome regulation of the networks in
the cold stress response of this important tropical root crop.