Cosuppression of AtGELP22 and AtGELP23, two ubiquitinated target proteins of RING E3 ligase AtAIRP5, increases tolerance to drought stress in Arabidopsis

Utilizing machine learning and bioinformatics analysis to identify drought-responsive genes affecting yield in foxtail millet

Drought stress is a major constraint on crop development, potentially causing huge yield losses and threatening global food security. Improving Crop's stress tolerance is usually associated with a yield penalty. One way to balance yield and stress tolerance is modification specific gene by emerging precision genome editing technology. However, our knowledge of yield-related drought-tolerant genes is still limited. Foxtail millet (Setaria italica) has a remarkable tolerance to drought and is considered to be a model C4 crop that is easy to engineer. Here, we have identified 46 drought-responsive candidate genes by performing a machine learning-based transcriptome study on two drought-tolerant and two drought-sensitive foxtail millet cultivars. A total of 12 important drought-responsive genes were screened out by principal component analysis and confirmed experimentally by qPCR. Significantly, by investigating the haplotype of these genes based on 1844 germplasm resources, we found two genes (Seita.5G251300 and Seita.8G036300) exhibiting drought-tolerant haplotypes that possess an apparent advantage in 1000 grain weight and main panicle grain weight without penalty in grain weight per plant. These results demonstrate the potential of Seita.5G251300 and Seita.8G036300 for breeding drought-tolerant high-yielding foxtail millet. It provides important insights for the breeding of drought-tolerant high-yielding crop cultivars through genetic manipulation technology.

Identification, evolution, and expression of GDSL-type Esterase/Lipase (GELP) gene family in three cotton species: a bioinformatic analysis

BACKGROUND

GDSL esterase/lipases (GELPs) play important roles in plant growth, development, and response to biotic and abiotic stresses. Presently, an extensive and in-depth analysis of GELP family genes in cotton is still not clear enough, which greatly limits the further understanding of cotton GELP function and regulatory mechanism.

RESULTS

A total of 389 GELP family genes were identified in three cotton species of Gossypium hirsutum (193), G. arboreum (97), and G. raimondii (99). These GELPs could be classified into three groups and eight subgroups, with the GELPs in same group to have similar gene structures and conserved motifs. Evolutionary event analysis showed that the GELP family genes tend to be diversified at the spatial dimension and certain conservative at the time dimension, with a trend of potential continuous expansion in the future. The orthologous or paralogous GELPs among different genomes/subgenomes indicated the inheritance from genome-wide duplication during polyploidization, and the paralogous GELPs were derived from chromosomal segment duplication or tandem replication. GELP genes in the A/D subgenome underwent at least three large-scale replication events in the evolutionary process during the period of 0.6-3.2 MYA, with two large-scale evolutionary events between 0.6-1.8 MYA that were associated with tetraploidization, and the large-scale duplication between 2.6-9.1 MYA that occurred during diploidization. The cotton GELPs indicated diverse expression patterns in tissue development, ovule and fiber growth, and in response to biotic and abiotic stresses, combining the existing cis-elements in the promoter regions, suggesting the GELPs involvements of functions to be diversification and of the mechanisms to be a hormone-mediated manner.

CONCLUSIONS

Our results provide a systematic and comprehensive understanding the function and regulatory mechanism of cotton GELP family, and offer an effective reference for in-depth genetic improvement utilization of cotton GELPs.