As one of the largest transcription factor families in plants, MYB genes play an important role in resisting stress. The MYB transcription factor GhMYB108 was cloned and analyzed to verify its role in drought stress response, which laid a foundation for further study on the molecular mechanism of GhMYB108 regulating drought tolerance in G. hirsutum.

Through the analysis of unpublished drought transcriptome data, GhMYB108 was identified to drought response. The target gene was amplified from the root cDNA by polymerase chain reaction (PCR). Through bioinformatics analysis of gene structure characteristics, the sequence information and phylogenetic relationship of these genes were predicted. The obtained gene promoter sequences were analyzed by Plant Care website. The genes expression characteristics under different stress conditions were analyzed using Real time fluorescence quantitative PCR (qRT-PCR). The location of GhMYB108 protein was determined by subcellular localization. The transcriptional activity was tested in yeast cell; The GhMYB108 gene was silenced using Virus induced gene silencing (VIGS), and the gene silencing efficiency was detected by qRT-PCR. The phenotypic changes before and after drought treatment were observed and the survival rate was counted. The relevant physiological and biochemical indexes were measured by Solarbio Kit; The relationship between GhMYB108 and ABA was analyzed by spraying ABA and Fluridone on cotton leaves.

GhMYB108 (Gh_A10G1563) was cloned from G. hirsutum, with 879 bp length and 292 amino acids. Its protein relative molecular weight and isoelectric point is 33.288 kD and 6.037, respectively. Multiple sequence alignment and conserved domain analysis showed that GhMYB108 contains two highly conserved MYB binding domains, which belongs to a typical R2R3 MYB transcription factor. Phylogenetic analysis of different species showed that GhMYB108 was highly homology with ATMYB108, ATMYB78 and ATMYB2, belonging to the same subfamily. Previous studies found that ATMYB108, ATMYB78 and ATMYB2 were related to drought and ABA signaling pathway. GhMYB108 located in the nucleus and had transcriptional activation activity. The expression level of GhMYB108 was the highest in roots and the lowest in stems, and was induced by abiotic stresses including natural drought, 18% PEG 6000 simulated drought, salt stress and low temperature. The GhMYB108 silenced plants showed a critical phenotype under natural drought conditions. Compared with the control, the silenced plants showed more serious wilting and decreased survival rate. Some physiological and biochemical indexes also changed significantly, such as accelerated leaf water loss rate, increased malondialdehyde content, decreased leaf relative water content and proline content, and decreased CAT and POD activities. Through DAB and NBT staining, the hydrogen peroxide (H₂O₂) and superoxide anion (O₂^-) were significantly accumulated in plants. By spraying the hormone ABA or Fluridone on cotton leaves, we found that GhMYB108 could be positively regulated by ABA signal.

GhMYB108 positively regulates cotton drought resistance and is positively regulated by ABA signal.

In this study, the purpose was to comprehensively evaluate the cold tolerance of cotton varieties (lines) at seedling emergence stage, establish a reliable evaluation model, screen and identify indicators, and provide a simple and effective evaluation method for the selection and identification of cold-tolerant varieties in cotton.

200 upland cotton varieties (lines) were used to test hypocotyl length, root length and 100-grain weight, etc. under three treatments of constant chilling (CC), diurnal variation of chilling (DVC) and normal conditions. A combination of integrated cold tolerance coefficient difference analysis, frequency analysis, drop analysis, principal component analysis, cluster analysis, and multiple regression analysis were used to classify their cold tolerance types, establish cold tolerance prediction models, and screen evaluation parameters.

The variation of each parameters at normal conditions were minor fluctuations ranging from 3.12% to 18.89%. The seedling emergence rate was above 85.00%, which had high viability and could be used for subsequent cold tolerance analysis. The variability of each parameter within the accessions increased under chilling stress, ranging from 7.14%-108.33%, and the most variable parameter were root length under CC condition and germination index under DVC condition. Principal component analysis converted the 14 parameters under chilling stress and 100-grain weight measured into six mutually independent composite indicators, representing 74.98% of the total data information. The comprehensive cold tolerance evaluation value (D) was calculated by the affiliation function method and then clustering analysis was performed. 200 cotton varieties (lines) were divided into five categories according to their cold tolerance, with 2 of the group Ⅰ being strongly cold tolerant, 42 of the group Ⅱ being cold tolerant, 69 of the group Ⅲ being medium cold tolerant, 83 of the group Ⅳ being more sensitive, and 4 of the group Ⅴ being sensitive, of which Xinluzhong 16 was the most cold-tolerant material. A multiple regression analysis was applied to establish a prediction model for cold tolerance of cotton at seedling emergence as Y=-4.10+0.58X4+0.40X14+0.32X1+0.22X5 (R²=0.92), and four parameters for cold resistance evaluation were confirmed, namely total length of seedling, emergence rate, and dry weight under CC stress, germination rate under DVC stress. The cold-tolerant varieties (lines) had higher seedling emergence rates of early sowing experiment in the field, which were basically consistent with the results of the indoor results.

It is feasible to use CC and DVC stress combined with multivariate statistical analysis to evaluate the cold tolerance of cotton at seeding stage, and total length of seedling, emergence rate, and dry weight under CC stress, germination rate under DVC stress can be used as evaluation parameters.