Jaikham, J. | Search bioRxiv

bioRxiv2025

Constitutive expression of full-length or partial of SOC1 genes for yield enhancement in tomato

Manipulating the expression of flowering pathway genes holds potential for regulating tomato fruit productivity. SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 (SOC1) is a MADS-box gene that serves as a key integrator in the flowering pathway. In this study, two full-length SOC1 genes cloned from maize (ZmSOC1) and soybean (GmSOC1), along with a partial SOC1 gene from blueberry (VcSOC1K, containing the K-domain), were individually transformed into tomato for constitutive expression. Phenotypically, the expression of VcSOC1K and ZmSOC1, but not GmSOC1, led to early flowering. Most transgenic lines for all three constructs exhibited a significant increase in fruit number per plant. More importantly, compared to non-transgenic plants, all three constructs resulted in varying degrees of increased fruit production per plant, primarily through enhanced branching. At the transcriptomic level, comparative analysis of GmSOC1 revealed the broader impact of the transformed genes. The increased expression of CLF and EZA1 appears to explain the unchanged flowering time of the GmSOC1 transgenic plants, while the repressed expression of DWARF genes likely contributes to enhanced branching. Additionally, numerous genes associated with biotic and abiotic stress tolerance displayed differential expression. These findings demonstrate that constitutive expression of either full-length or partial SOC1 has the potential to enhance tomato fruit production by modulating multiple pathways, at least at the transcript levels.

plant biology↗

bioRxiv2024

A high resolution model of the grapevine leaf morphospace predicts synthetic leaves

O_LIGrapevine leaves are a model morphometric system. Sampling over ten thousand leaves using dozens of landmarks, the genetic, developmental, and environmental basis of leaf shape has been studied and a morphospace for the genus Vitis predicted. Yet, these representations of leaf shape fail to capture the exquisite features of leaves at high resolution. C_LIO_LIWe measure the shapes of 139 grapevine leaves using 1672 pseudo-landmarks derived from 90 homologous landmarks with Procrustean approaches. From hand traces of the vasculature and blade, we have derived a method to automatically detect landmarks and place pseudo-landmarks that results in a high-resolution representation of grapevine leaf shape. Using polynomial models, we create continuous representations of leaf development in 10 Vitis spp. C_LIO_LIWe visualize a high-resolution morphospace in which genetic and developmental sources of leaf shape variance are orthogonal to each other. Using classifiers, V. vinifera, Vitis spp., rootstock and dissected leaf varieties as well as developmental stages are accurately predicted. Theoretical eigenleaf representations sampled from across the morphospace that we call synthetic leaves can be classified using models. C_LIO_LIBy predicting a high-resolution morphospace and delimiting the boundaries of leaf shapes that can plausibly be produced within the genus Vitis, we can sample synthetic leaves with realistic qualities. From an ampelographic perspective, larger numbers of leaves sampled at lower resolution can be projected onto this high-resolution space; or, synthetic leaves can be used to increase the robustness and accuracy of machine learning classifiers. C_LI Societal Impact StatementGrapevine leaves are emblematic of the strong visual associations people make with plants. At a glance, leaf shape is immediately recognizable, and it is because of this reason it is used to distinguish grape varieties. In an era of computationally-enabled, machine learning-derived representations of reality, we can revisit how we view and use the shapes and forms that plants display to understand our relationship with them. Using computational approaches combined with time-honored methods, we can predict theoretical leaves that are possible to understand the genetics, development, and environmental responses of plants in new ways.

plant biology↗