Sexual transfer of the CRISPR/Cas genome-editing system to targeted cotton cultivars could bypass their recalcitrance to regeneration from tissue culture. We used sexual hybridization to transmit a CRISPR/LbCas12a system from a regenerable Gossypium hirsutum donor to a nonregenerable G. barbadense recipient. We knocked out the GbCLA and GbPGF genes in the recipient, generating respectively albino and glandless phenotypes. Focusing on GbPGF, we detected novel mutations in the progeny across generations, and developed a set of nearly isogenic lines. The average editing efficiency of the target gene at crRNA1 exceeded 70% in the BC₃F₁ generation, yielding plants with agronomic traits or fiber quality nearly identical to those of the recurrent parent but lacking glands or gossypol. We introduced the CRISPR/LbCas12a system into three other nonregenerable G. hirsutum genotypes and one diploid cotton by hybridization and edited three more genes in two recipients.

Plant height (PH) is a key agronomic trait influencing plant architecture. Suitable PH values for cotton are important for lodging resistance, high planting density, and mechanized harvesting, making it crucial to elucidate the mechanisms of the genetic regulation of PH. However, traditional field PH phenotyping largely relies on manual measurements, limiting its large-scale application. In this study, a high-throughput phenotyping platform based on UAV-mounted RGB and light detection and ranging (LiDAR) was developed to efficiently and accurately obtain time series PHs of 419 cotton accessions in the field. Different strategies were used to extract PH values from two sets of sensor data, and the extracted values were used to train using linear regression and machine learning methods to obtain PH predictions. These predictions were consistent with manual measurements of the PH for the LiDAR (R² ​= ​0.934) and RGB (R² ​= ​0.914) data. The predicted PH values were used for GWAS analysis, and 34 ​PH-related genes, two of which have been demonstrated to regulate PH in cotton, namely, GhPH1 and GhUBP15, were identified. We further identified significant differences in the expression of a new gene named GhPH_UAV1 in the stems of the G. hirsutum cultivar ZM24 harvested on the 15th, 35th, and 70th days after sowing compared with those from a dwarf mutant (pag1), which presented shortened stem and internode phenotypes. The overexpression of GhPH_UAV1 significantly promoted cotton stem development, whereas its knockout by CRISPR-Cas9 dramatically inhibited stem growth, suggesting that GhPH_UAV1 plays a positive regulatory role in cotton PH. This field-scale high-throughput phenotype monitoring platform significantly improves the ability to obtain high-quality phenotypic data from large populations, which helps overcome the imbalance between massive genotypic data and the shortage of field phenotypic data and facilitates the integration of genotype and phenotype research for crop improvement.

Global warming is limiting availability of water resources in arid and semi-arid regions, and so understanding water use efficiency (WUE) is increasingly important for agricultural production in those areas. As China is the largest cotton producing area, the problem of balancing WUE and efficient cotton production is a major issue. In this study, we used a natural population of 517 Upland cotton accessions to conduct a water-controlled trial in south and north of Xinjiang over two years. A total of 18 traits including agronomic traits, fiber yield indices and fiber quality indices, were investigated for broad-sense heritability and coefficient of variation. Appropriate water limitation was found to promote the establishment of favorable agronomic traits in cotton, associated with an increased cotton yield of 8.46% in Xinjiang, at the expense of a certain degree of fiber quality, such as decreased fiber length and an over-higher micronaire value. We detected 33 QTL related to response to water limitation using a drought resistance coefficient (DRC), and 6 QTL were found using a comprehensive indicator of CIDT (comprehensive index of drought tolerance) at the genetic level by integrating resequencing data. Two novel QTL-hotspots including six differentially expressed genes (DEGs) were further identified related to the drought response of cotton. These findings not only suggested a new approach to irrigation of cotton fields in Xinjiang, but also provided abundant genetic evidence for genetic breeders to study drought improvement of crops.