Genome wide identification of the trihelix transcription factors and overexpression of Gh_A05G2067 (GT‐2), a novel gene contributing to increased drought and salt stresses tolerance in cotton

Abstract

We identified 102, 51 and 51 proteins encoded by the trihelix genes in Gossypium hirsutum, Gossypium arboreum and Gossypium raimondii, respectively. RNA sequence data and real‐time quantitative polymerase chain reaction analysis showed that Gh_A05G2067 (GT‐2) was highly upregulated under drought and salt stress conditions. Transient expression of GT‐2‐green fluorescent protein fusion protein in protoplast showed that GT‐2 was localized in the nucleus. The overexpression of GT‐2 conferred an enhanced drought tolerance to cotton, with lower malondialdehyde, hydrogen peroxide contents and higher reactive oxygen scavenging enzyme activities. Moreover, chlorophyll content, relative leaf water content (RLWC), excised leaf water loss (ELWL) and cell membrane stability (CMS) were relatively stable in the GT‐2‐overexpressed lines compared to wild‐type (WT). Similarly, stress‐responsive genes RD29A, SOS1, ABF4 and CBL1 were highly upregulated in the GT‐2‐overexpressed lines but were significantly downregulated in WT. In addition, the GT‐2‐silenced cotton plants exhibited a high level of oxidation injury, due to high levels of oxidant enzymes, in addition to negative effects on CMS, ELWL, RLWC and chlorophyll content. These results mark the foundation for future exploration of the trihelix genes in cotton, with an aim of developing more resilient, versatile and highly tolerant cotton genotypes.

Genome-wide identification of OSCA gene family and their potential function in the regulation of dehydration and salt stress in Gossypium hirsutum

“…The higher concentration levels of the MDA in the leaf tissues of VIGS plants showed that the plants suffered more of oxidative stress compared with the wild types and the positively controlled plant under drought and salt stress conditions. The results obtained were in agreement with the previous findings in which the Gh_A05G2067 (GT-2) knocked out plants registered higher concentration levels of MDA, hydrogen peroxide and significant reduction on the concentration level of catalase (CAT), peroxidase (POD) (Magwanga et al 2019a). Therefore, these results suggested that GhOSCA1.1 gene may improve salt and drought tolerance of cotton.…”

Genetic regulatory networks for salt-alkali stress in Gossypium hirsutum with differing morphological characteristics

“…1b), an indication that CRI12 and MAR85 were less affected under salt stress compared to LAT40. Furthermore, Malondialdehyde (MDA) concentrations levels within the plants is an indication that the plants are suffering from oxidative stress, being MDA is a byproduct of lipid peroxidation [22]. The results obtained were in agreement to previous findings in which the knockdown of trihelix transcription factor in cotton reduced drought and salt stress tolerance and in turn accelerated the accumulation of various oxidants and MDA levels under drought and salt stress exposure [22].…”

Genetic Regulatory Networks for Salt-Alkali Stress in Gossypium hirsutum With Differing Morphological Characteristics

“…showed significantly higher concentrations of proline and superoxide dismutase (SOD) compared to LAT40 ( Figure 1B), an indication that CRI12 and MAR85 were less affected under salt stress compared to LAT40. Furthermore, Malondialdehyde (MDA) concentrations levels within the plants is an indication that the plants are suffering from oxidative stress, being MDA is a byproduct of lipid peroxidation [22]. The results obtained were in agreement to previous findings in which the knockdown of trihelix transcription factor in cotton reduced drought and salt stress tolerance and in turn accelerated the accumulation of various oxidants and MDA levels under drought and salt stress exposure [22].…”

“…To investigate the gene regulatory network of alkali-salt stress response in upland cotton, we identified co-expressed gene sets via weighted gene co-expression network analysis (WGCNA) which can be used to find networks (modules) of highly correlated genes [30]. In the present study, 22,359 DEGs were used for WGCNA. In order to ensure a scale-free network, the power of β= 12 (scale free R2= 0.8740) was accurately selected by determination of soft-thresholding power ( Figure S3A orange red1 (Gene number: 1836, r= 0.95) module-SS3 stage in root).…”