RESUMEN
The vegetative-to-floral transition is a dramatic developmental change of the shoot apical meristem, promoted by the systemic florigen signal. However, poor molecular temporal resolution of this dynamic process has precluded characterization of how meristems respond to florigen induction. Here, we develop a technology that allows sensitive transcriptional profiling of individual shoot apical meristems. Computational ordering of hundreds of tomato samples reconstructed the floral transition process at fine temporal resolution and uncovered novel short-lived gene expression programs that are activated before flowering. These programs are annulled only when both florigen and a parallel signalling pathway are eliminated. Functional screening identified genes acting at the onset of pre-flowering programs that are involved in the regulation of meristem morphogenetic changes but dispensable for the timing of floral transition. Induced expression of these short-lived transition-state genes allowed us to determine their genetic hierarchies and to bypass the need for the main flowering pathways. Our findings illuminate how systemic and autonomous pathways are integrated to control a critical developmental switch.
Asunto(s)
Flores/genética , Perfilación de la Expresión Génica/métodos , Meristema/genética , Proteínas de Plantas/genética , Solanum lycopersicum/genética , Simulación por Computador , Florigena/metabolismo , Flores/crecimiento & desarrollo , Regulación de la Expresión Génica de las Plantas , Solanum lycopersicum/citología , Solanum lycopersicum/crecimiento & desarrollo , Meristema/citología , Meristema/crecimiento & desarrollo , Meristema/metabolismo , Microscopía Electrónica de Rastreo , Mutación , Proteínas de Plantas/metabolismo , Plantas Modificadas GenéticamenteRESUMEN
Structural variants (SVs) underlie important crop improvement and domestication traits. However, resolving the extent, diversity, and quantitative impact of SVs has been challenging. We used long-read nanopore sequencing to capture 238,490 SVs in 100 diverse tomato lines. This panSV genome, along with 14 new reference assemblies, revealed large-scale intermixing of diverse genotypes, as well as thousands of SVs intersecting genes and cis-regulatory regions. Hundreds of SV-gene pairs exhibit subtle and significant expression changes, which could broadly influence quantitative trait variation. By combining quantitative genetics with genome editing, we show how multiple SVs that changed gene dosage and expression levels modified fruit flavor, size, and production. In the last example, higher order epistasis among four SVs affecting three related transcription factors allowed introduction of an important harvesting trait in modern tomato. Our findings highlight the underexplored role of SVs in genotype-to-phenotype relationships and their widespread importance and utility in crop improvement.
Asunto(s)
Productos Agrícolas/genética , Regulación de la Expresión Génica de las Plantas , Variación Estructural del Genoma , Solanum lycopersicum/genética , Alelos , Sistema Enzimático del Citocromo P-450/genética , Ecotipo , Epistasis Genética , Frutas/genética , Duplicación de Gen , Genoma de Planta , Genotipo , Endogamia , Anotación de Secuencia Molecular , Fenotipo , Fitomejoramiento , Sitios de Carácter Cuantitativo/genéticaRESUMEN
Despite the importance of complex phenotypes, an in-depth understanding of the combined molecular and genetic effects on a phenotype has yet to be achieved. Here, we introduce InPhenotype, a novel computational approach for complex phenotype prediction, where gene-expression data and genotyping data are integrated to yield quantitative predictions of complex physiological traits. Unlike existing computational methods, InPhenotype makes it possible to model potential regulatory interactions between gene expression and genomic loci without compromising the continuous nature of the molecular data. We applied InPhenotype to synthetic data, exemplifying its utility for different data parameters, as well as its superiority compared to current methods in both prediction quality and the ability to detect regulatory interactions of genes and genomic loci. Finally, we show that InPhenotype can provide biological insights into both mouse and yeast datasets.
Asunto(s)
Variación Biológica Poblacional , Estudio de Asociación del Genoma Completo/métodos , Fenotipo , Programas Informáticos , Animales , Genotipo , Ratones , Herencia Multifactorial , LevadurasRESUMEN
Despite incremental improvements in the field of tissue engineering, no technology is currently available for producing completely autologous implants where both the cells and the scaffolding material are generated from the patient, and thus do not provoke an immune response that may lead to implant rejection. Here, a new approach is introduced to efficiently engineer any tissue type, which its differentiation cues are known, from one small tissue biopsy. Pieces of omental tissues are extracted from patients and, while the cells are reprogrammed to become induced pluripotent stem cells, the extracellular matrix is processed into an immunologically matching, thermoresponsive hydrogel. Efficient cell differentiation within a large 3D hydrogel is reported, and, as a proof of concept, the generation of functional cardiac, cortical, spinal cord, and adipogenic tissue implants is demonstrated. This versatile bioengineering approach may assist to regenerate any tissue and organ with a minimal risk for immune rejection.