Competition for Light Interception in Different Plant Canopy Characteristics of Diverse Cotton Cultivars.

Identifying the ideal plant nature and canopy structure is of great importance for improving photosynthetic production and the potential action of plants. To address this challenge, an investigation was accomplished in 2018 and 2019 at the Institute of Cotton Research (ICR) of the Chinese Academy of Agricultural Science (CAAS), Henan Province, China. Six cotton varieties with diverse maturities and plant canopy structures were used to evaluate the light interception (LI) in cotton, the leaf area index (LAI), the biomass, and the yield throughout the two years of study. The light spatial distribution in the plant canopy was evaluated using a geographic statistical method, following the increasing quantity of radiation intercepted, which was determined using the rules of Simpson. Compared to the cotton plants with a compact structure, varieties with both a loose and tower design captured a comparatively higher amount of light (average 31.3%) and achieved a higher LAI (average 32.4%), eventually achieving a high yield (average 10.1%). Furthermore, the polynomial correlation revealed a positive relationship between the biomass accumulation in the reproductive parts and canopy-accrued light interception (LI), signifying that light interception is critical for the yield development of cotton. Furthermore, when the leaf area index (LAI) was peaked, radiation interception and biomass reached the highest during the boll-forming stage. These findings will provide guidance on the light distribution in cotton cultivars with an ideal plant structure for light capture development, providing an important foundation for researchers to better manage light and canopies.

Differential seedling growth and tolerance indices reflect drought tolerance in cotton.

BACKGROUND: Cotton production is adversely effected by drought stress. It is exposed to drought stress at various critical growth stages grown under a water scarcity environment. Roots are the sensors of plants; they detect osmotic stress under drought stress and play an important role in plant drought tolerance mechanisms. The seedling stage is very sensitive to drought stress, and it needed to explore the methods and plant characteristics that contribute to drought tolerance in cotton. RESULTS: Initially, seedlings of 18 genotypes from three Gossypium species: G. hirsutum, G. barbadense, and G. arboreum, were evaluated for various seedling traits under control (NS) and drought stress (DS). Afterward, six genotypes, including two of each species, one tolerant and one susceptible, were identified based on the cumulative drought sensitivity response index (CDSRI). Finally, growth rates (GR) were examined for shoot and root growth parameters under control and DS in experimental hydroponic conditions. A significant variation of drought stress responses was observed across tested genotypes and species. CDSRI allowed here to identify the drought-sensitive and drought-resistant cultivar of each investigated species. Association among root and shoots growth traits disclosed influential effects of enduring the growth under DS. The traits including root length, volume, and root number were the best indicators with significantly higher differential responses in the tolerant genotypes. These root growth traits, coupled with the accumulation of photosynthates and proline, were also the key indicators of the resistance to drought stress. CONCLUSION: Tolerant genotypes have advanced growth rates and the capacity to cop with drought stress by encouraging characteristics, including root differential growth traits coupled with physiological traits such as chlorophyll and proline contents. Tolerant and elite genotypes of G. hirsutum were more tolerant of drought stress than obsolete genotypes of G. barbadense and G. arboreum. Identified genotypes have a strong genetic basis of drought tolerance, which can be used in cotton breeding programs.

Integrating Genome-wide association and whole transcriptome analysis to reveal genetic control of leaf traits in Gossypium arboreum L.

Leaves are important organs for crop photosynthesis and transpiration, and their morphological characteristics can directly reflect the growth state of plants. Accurate measurement of leaf traits and mining molecular markers are of great significance to the study of cotton growth. Here, we performed a Genome-wide association study on 7 leaf traits in 213 Asian cotton accessions. 32 significant SNPs and 44 genes were identified. A field experiment showed significant difference in leaf hair and leaf area between DPL971 and its natural mutant DPL972. We also compared the leaf transcriptome difference between DPL971 and DPL972, and found a batch of differentially expressed genes and non-coding RNAs (including lncRNAs, microRNAs, and circRNAs). After integrating the GWAS and transcriptome results, we finally selected two coding genes (Ga03G2383 and Ga05G3412) and two microRNAs (hbr-miR156, unconservative_Chr03_contig343_2364) as the candidate for leaf traits. Those findings will provide important genomic resources for cotton leaf improvement breeding.

Genome-wide association and transcriptome analysis of root color-related genes in Gossypium arboreum L.

MAIN CONCLUSION: The significant number loci and candidate genes of root color in Gossypium arboreum are identified and provide a theoretical basis of root color for cotton. A stimulating phenomenon was observed on the 4th day of sowing in the root color of some G. arboreum accessions that turned red. To disclose the genetic mechanisms of root color formation via genome and transcript levels, we identified the significant number of SNPs and candidate genes that are related to root color through genome-wide association study (GWAS) and RNAseq analysis in G. arboreum. Initially, 215 no. of G. arboreum accessions was collected, and the colors of root on the 4th, 6th and 9th day of germination were recorded. The GWAS demonstrated that 225 significant SNPs and 47 candidate genes have been identified totally. The strongest signal SNP A04_91824 could greatly distinguish the root color with most "C" allele accessions have displayed white and "T" allele accessions displayed red. RNAseq was performed on accessions having the white and red root, and results revealed that 12 and 138 DEGs were detected on 2nd and 4th day, respectively. ACD6, UFGT, and LYM2 were the most related genes of root color, later, verified by qRT-PCR. The mature zone of red and the white roots was observed by the histological section method, and results shown that cells were more closely arranged in the white root, and both average cell length and cell width were longer in the red root. This study will be helpful to cotton breeders for utilization of several elite genes and related SNPs related to root color, in addition to find linkage with economically important traits of interests.