Coexpression gene network analysis of cold‐tolerant Solanum commersonii reveals new insights in response to low temperatures

Abstract

Among abiotic stressors, cold is one of the most harmful for the cultivated potato (Solanum tuberosum L.), a frost-sensitive crop. RNA sequencing (RNA-seq) profiling of two different clones of wild potato (S. commersonii Dun.) contrasting in their capacity to withstand low temperatures revealed a higher number of differentially expressed genes (DEGs) under nonacclimated conditions (NAC) in tolerant clone cmm1T vs. the susceptible cmm6-6 (1,002 and 8,055 DEGs, respectively). By contrast, the number of DEGs was much more comparable when both genotypes were under acclimated conditions (AC). Indeed, a total of 5,650 and 8,936 DEGs were detected in the tolerant genotype vs. the susceptible. Gene ontology (GO) classification under NAC showed a significant role for transcription regulation, lignin catabolic genes, and regulation of plant type secondary cell wall in the cold-tolerant genotypes, suggesting an important role in conferring tolerance response. By contrast, response to stress and response to stimuli were enriched GO categories in both clones under AC. Unsigned weighted correlation networks analysis (WGCNA) allowed identification of coexpressed hub genes with possible main regulatory functions and major impacts on the phenotype. Among those identified, we clarified the role of CBF4. This gene showed contrasting expression profiles in the two clones under NAC, being induced in cold-tolerant cmm1T but suppressed in susceptible cmm6-6. By contrast, under AC, CBF4 was upregulated in both clones. Our study provides a global understanding of mechanisms involved following exposure to NAC and AC in S. commersonii. The mechanisms described here will inform future investigations for detailed validation in studies regarding cold tolerance in plants.

LncRNA‐mediatedceRNAregulatory network provides new insight into chlorogenic acid synthesis in sweet potato

“…Weighted gene co-expression network analysis (WGCNA) is widely used in key gene or module screening (Esposito et al, 2021;Zhu et al, 2019). By this method, the DEmRNAs and DElncRNAs were further narrowed to modules highly-related to CGA content.…”

“…Selecting important genes or pathways from a large number of DEGs is a large challenge in transcriptomics analysis. Weighted gene co‐expression network analysis (WGCNA) is widely used in key gene or module screening (Esposito et al, 2021; Zhu et al, 2019). By this method, the DEmRNAs and DElncRNAs were further narrowed to modules highly‐related to CGA content.…”

Feedback Inhibition Might Dominate the Accumulation Pattern of BR in the New Shoots of Tea Plants (Camellia sinensis)

“…After the preliminary module division, the modules with similar expression patterns were combined according to the module similarity to form a dynamic tree. Subsequent analyses were carried out according to the combined module ( Esposito et al, 2021 ). The KEGG pathway enrichment analysis was performed using the KEGG database ( http://www.genome.jp/kegg/ ) ( Minoru et al, 2008 ).…”

Gene Co-Expression Network Tools and Databases for Crop Improvement

“…A previous study has found that WGCNA is more sensitive to noise in datasets and outperforms other clustering methods in detecting non-overlapping clusters or modules [39]. The WGCNA has been reported in several publications related to crop improvement [40][41][42][43][44].…”