Development and identification of molecular markers of GhHSP70-26 related to heat tolerance in cotton

The novel chaperonin 10 like protein (SbCPN10L) from Salicornia brachiata (Roxb.) augment the heat stress tolerance in transgenic tobacco

The heat stress is a significant environmental challenge and impede the plant growth, development and productivity. The characterization and utilization of novel genes for improving stress tolerance represents a paramount approach in crop breeding. In the present study, we report on cloning of a novel heat-induced chaperonin 10-like gene (SbCPN10L) from Salicornia brachiata and elucidation of its in-planta role in conferring the heat stress endurance. The transgenic tobacco over-expressing SbCPN10L gene exhibited enhanced growth attributes such as higher rate of seed germination, germination and vigor index at elevated (35 ± 1 °C) temperature (eT). The SbCPN10L tobacco exhibited greenish and healthy seedling growth under stress. Compared with control tobacco at eT, the transgenic tobacco had higher water contents, membrane stability index, stress tolerance index and photosynthetic pigments. Lower electrolyte leakage and less accumulation of malondialdehyde, hydrogen peroxide and reactive oxygen species indicated better heat stress tolerance in transgenic tobacco over-expressing SbCPN10L gene. Transgenic tobacco accumulated higher contents of sugars, starch, amino acids and polyphenols at eT. The negative solute potential observed in transgenic tobacco contributed to maintain water content and support improved growth under stress. The up-regulation of NtAPX, NtPOX and NtSOD in transgenic tobacco under stress indicated higher ROS scavenging ability and better physiological conditioning. The results recommend the SbCPN10L gene as a potential candidate gene with an ability to confer heat stress tolerance for climate resilient crops.

KASP-IEva: an intelligent typing evaluation model for KASP primers

KASP marker technology has been used in molecular marker-assisted breeding because of its high efficiency and flexibility, and an intelligent evaluation model of KASP marker primer typing results is essential to improve the efficiency of marker development on a large scale. To this end, this paper proposes a gene population delineation method based on NTC identification module and data distribution judgment module to improve the accuracy of K-Means clustering, and introduces a decision tree to construct the KASP-IEva primer typing evaluation model. The model firstly designs the NTC identification module and data distribution judgment module to extract four types of data, grouping and categorizing to achieve the improvement of the distinguishability of amplification product signals; secondly, the K-Means algorithm is used to aggregate and classify the data, to visualize the five aggregated clusters and to obtain the morphology location eigenvalues; lastly, the evaluation criteria for the typing effect level are constructed, and the logical decision tree is used to make conditional discrimination on the eigenvalues in order to realize the score prediction. The performance of the model was tested by the KASP marker typing test results of 2519 groups of cotton varieties, and the following conclusions were obtained: the model is able to visualize the aggregation and classification effects of the amplification products of NTC, pure genotypes, heterozygous genotypes, and untyped genotypes, enabling rapid and accurate KASP marker typing evaluation. Comparing and analyzing the model evaluation results with the expert evaluation results, the average accuracy rate of the four grades evaluated by the model was 87%, and the overall evaluation results showed an uneven distribution of the grades with significant differential characteristics. When evaluating 2519 KASP fractal maps, the expert evaluation consumes 15 hours, and the model evaluation only uses 8min27.45s, which makes the model intelligent evaluation significantly better than the expert evaluation from the perspective of time. The establishment of the model will further enhance the application of KASP markers in molecular marker-assisted breeding and provide technical support for the large-scale screening and identification of excellent genotypes.