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Background And Aims: The symmetry of venation patterning in leaves is highly conserved within a plant species. Auxins are involved in this process and also in xylem vasculature development. Studying transgenic Arabidopsis plants ectopically expressing the sunflower transcription factor HaHB4, it was observed that there was a significant lateral-vein asymmetry in leaves and in xylem formation compared to wild type plants. To unravel the molecular mechanisms behind this phenotype, genes differentially expressed in these plants and related to auxin influx were investigated.
Methods: Candidate genes responsible for the observed phenotypes were selected using a co-expression analysis. Single and multiple mutants in auxin influx carriers were characterized by morphological, physiological and molecular techniques. The analysis was further complemented by restoring the wild type (WT) phenotype by mutant complementation studies and using transgenic soybean plants ectopically expressing HaHB4 .
Key Results: LAX2 , down-regulated in HaHB4 transgenic plants, was bioinformatically chosen as a candidate gene. The quadruple mutant aux1 lax1 lax2 lax3 and the single mutants, except lax1, presented an enhanced asymmetry in venation patterning. Additionally, the xylem vasculature of the lax2 mutant and the HaHB4 -expressing plants differed from the WT vasculature, including increased xylem length and number of xylem cell rows. Complementation of the lax2 mutant with the LAX2 gene restored both lateral-vein symmetry and xylem/stem area ratio in the stem, showing that auxin homeostasis is required to achieve normal vascular development. Interestingly, soybean plants ectopically expressing HaHB4 also showed an increased asymmetry in the venation patterning, accompanied by the repression of several GmLAX genes.
Conclusions: Auxin influx carriers have a significant role in leaf venation pattering in leaves and, in particular, LAX2 is required for normal xylem development, probablt controlling auxin homeostasis.
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http://dx.doi.org/10.1093/aob/mcx091 | DOI Listing |
Accurate honey bee subspecies identification is vital for biodiversity conservation and pollination resilience, yet current methods face critical limitations. Classical morphometric techniques, reliant on manual wing vein measurements, suffer from subjectivity and poor scalability across hybrid populations, while deep learning approaches demand extensive labeled datasets and exhibit limited interpretability in noisy field conditions. Crucially, existing methods fail to reconcile scalability with the ability to analyze phenotypic gradients in hybrid specimens.
View Article and Find Full Text PDFPhys Rev Lett
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University of Copenhagen, University of Copenhagen, Niels Bohr Institute, Denmark and Department of Computer Science, Copenhagen, Denmark.
Biological transport networks are highly optimized structures that ensure power-efficient distribution of fluids across various domains, including animal vasculature and plant venation. Theoretically, these networks can be described as space-embedded graphs, and rich structures that align well with observations emerge from optimizing their hydrodynamic energy dissipation. Studies on these models typically use regular grids and focus solely on edge width optimization.
View Article and Find Full Text PDFData Brief
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Department of Computer Science and Engineering, Daffodil International University, Daffodil Smart City, Birulia, Dhaka 1216, Bangladesh.
This corpus contains 3173 high-quality images of leaves of ten commonly found fruit species in Bangladesh, namely Lotkon (306), Lychee (312), Mango (330), Black plum (304), Custard apple (304), Guava (325), Jackfruit (311), Aegle marmelos (336), Star Fruit (343), Plum (302). It is captured with Realme 7-Pro (64 MP primary camera) and Realme 8-Pro (108 MP primary camera) smartphones at nurseries near to Daffodil International University, Bangladesh. This dataset addresses the scarcity of high-quality, region-specific agricultural image datasets in South Asia, offering a unique combination of standardized smartphones-based imaging and controlled lighting to ensure consistant high-resolution visual data compared to existiong datasets.
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Department of Statistics, Columbia University, 1255 Amsterdam Ave, New York, NY 10027, United States.
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View Article and Find Full Text PDFFront Plant Sci
June 2025
Laboratorio de Dendrocronología, Universidad Continental, Huancayo, Junín, Peru.
Introduction: Tropical montane cloud forests (TMCFs) host specialized plant species reliant on persistent atmospheric humidity, including fog immersion obligates and relict assemblages. Understanding anatomical and morphological adaptations in TMCF woody angiosperms is critical for elucidating their acclimation strategies to hydric stress under shifting fog regimes. This study investigates interspecific variability in wood and leaf traits among 10 TMCF tree species in Mexico's Medio Monte Natural Protected Area, hypothesizing that distinct anatomical strategies emerge in response to climatic stressors.
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