Genome-wide identification of Aux/IAA gene family in white clover (Trifolium repens L.) and functional verification of TrIAA18 under different abiotic stress.

BACKGROUND: White clover (Trifolium repens L.) is an excellent leguminous cool-season forage with a high protein content and strong nitrogen-fixing ability. Despite these advantages, its growth and development are markedly sensitive to environmental factors. Indole-3-acetic acid (IAA) is the major growth hormone in plants, regulating plant growth, development, and response to adversity. Nevertheless, the specific regulatory functions of Aux/IAA genes in response to abiotic stresses in white clover remain largely unexplored. RESULTS: In this study, we identified 47 Aux/IAA genes in the white clover genome, which were categorized into five groups based on phylogenetic analysis. The TrIAAs promoter region co-existed with different cis-regulatory elements involved in developmental and hormonal regulation, and stress responses, which may be closely related to their diverse regulatory roles. Collinearity analysis showed that the amplification of the TrIAA gene family was mainly carried out by segmental duplication. White clover Aux/IAA genes showed different expression patterns in different tissues and under different stress treatments. In addition, we performed a yeast two-hybrid analysis to investigate the interaction between white clover Aux/IAA and ARF proteins. Heterologous expression indicated that TrIAA18 could enhance stress tolerance in both yeast and transgenic Arabidopsis thaliana. CONCLUSION: These findings provide new scientific insights into the molecular mechanisms of growth hormone signaling in white clover and its functional characteristics in response to environmental stress.

Pricing for a basket of LCDS under fuzzy environments.

This paper looks at both the prepayment risks of housing mortgage loan credit default swaps (LCDS) as well as the fuzziness and hesitation of investors as regards prepayments by borrowers. It further discusses the first default pricing of a basket of LCDS in a fuzzy environment by using stochastic analysis and triangular intuition-based fuzzy set theory. Through the 'fuzzification' of the sensitivity coefficient in the prepayment intensity, this paper describes the dynamic features of mortgage housing values using the One-factor copula function and concludes with a formula for 'fuzzy' pricing the first default of a basket of LCDS. Using analog simulation to analyze the sensitivity of hesitation, we derive a model that considers what the LCDS fair premium is in a fuzzy environment, including a pure random environment. In addition, the model also shows that a suitable pricing range will give investors more flexible choices and make the predictions of the model closer to real market values.