Weighted Gene Co-expression Network Analysis (WGCNA) Reveals the Hub Role of Protein Ubiquitination in the Acquisition of Desiccation Tolerance in Boea hygrometrica.

Boea hygrometrica can survive extreme drought conditions and has been used as a model to study desiccation tolerance. A genome-wide transcriptome analysis of B. hygrometrica showed that the plant can survive rapid air-drying after experiencing a slow soil-drying acclimation phase. In addition, a weighted gene co-expression network analysis was used to study the transcriptomic datasets. A network comprising 22 modules was constructed, and seven modules were found to be significantly related to desiccation response using an enrichment analysis. Protein ubiquitination was observed to be a common process linked to hub genes in all the seven modules. Ubiquitin-modified proteins with diversified functions were identified using immunoprecipitation coupled with mass spectrometry. The lowest level of ubiquitination was noted at the full soil drying priming stage, which coincided the accumulation of dehydration-responsive gene BhLEA2. The highly conserved RY motif (CATGCA) was identified from the promoters of ubiquitin-related genes that were downregulated in the desiccated samples. An in silico gene expression analysis showed that the negative regulation of ubiquitin-related genes is potentially mediated via a B3 domain-containing transcription repressor VAL1. This study suggests that priming may involve the transcriptional regulation of several major processes, and the transcriptional regulation of genes in protein ubiquitination may play a hub role to deliver acclimation signals to posttranslational level in the acquisition of desiccation tolerance in B. hygrometrica.

Haplotypes Phased from Population Transcriptomes Detecting Selection in the Initial Adaptation of Miscanthus lutarioriparius to Stressful Environments.

Adaptation is a characteristic that enhances the survival or reproduction of organisms; selection is the critical process leading to adaptive evolution. Therefore, detecting selection is important in studying evolutionary biology. Changes in allele frequency are fundamental to adaptive evolution. The allele frequency of entire genes at the genomic scale is more intensive and precise for analyzing selection effects, compared with simple sequence repeat and single nucleotide polymorphism (SNP) alleles from nuclear gene fragments. Here, we analyzed 29,094 SNPs derived from 80 individuals of 14 L. Liou ex S.L. Chen & Renvoize populations planted near their native habitat (Jiangxia, Hubei Province, JH) and a stressful environment (Qingyang, Gansu Province, QG) to detect selection during initial adaptation. The nucleotide diversity of over 60% of genes was decreased in QG compared with JH, suggesting that most genes were undergoing selection in the stressful environment. We explored a new approach based on haplotype data inferred from RNA-seq data to analyze the change in frequency between two sites and to detect selection signals. In total, 402 and 51 genes were found to be targets of positive and negative selection, respectively. Among these candidate genes, the enrichment of abiotic stress-response genes and photosynthesis-related genes might have been responsible for establishment in the stressful environment. This is the first study assessing the change in allele frequency at the genomic level during adaptation. The method in which allele frequency detects selection during initial adaptation using population RNA-seq data would be useful for developing evolutionary biology.