Biology subjects

Monfort, A.

Publications and source records attributed to Monfort, A..

3 recordsLinked to original sources

bioRxiv2024

TILLCANN: A TILLING platform in Cannabis sativa for mutation discovery and crop improvement

Cultivation of Cannabis sativa is increasing because of its therapeutic value and recognition as a multi-purpose and sustainable crop. Targeting Induced Local Lesions in Genomes (TILLING) is a versatile reverse genetics approach that unlocks induced variation through mutagenesis to accelerate the development of new cultivars and contribute to the functional validation of genes. Increasingly efficient next-generation sequencing technologies and genomic resources have combined to make TILLING by sequencing (TbyS) an attractive technique that can be applied in cannabis. Here we describe the development of a mutagenesis protocol for C. sativa and the development of the TILLCANN platform composed of 1,633 M2 families. As a demonstration of the functionality of the platform, we used TbyS to perform a high throughput screening of novel mutations in amplicons for genes associated with important agronomic and biochemical traits in a set of 512 M2 families. We confirmed 14 of the identified mutations and calculated an average mutation frequency range of 1/263 to 1/320 kb. We found that heterozygous mutants in the cannabis homologue of Class II TEOSINTE BRANCHED 1/CYCLOIDEA/PCF (TCP4) are linked to alterations in leaf number and morphology. We expect that the novel genetic variability unlocked in the TILLCANN platform for performing forward or reverse genetic screens can significantly boost breeding programs geared toward both medicinal cannabis and industrial hemp. Gene & accession numbersRaw sequencing data generated in this study was deposited at the European Nucleotide Archive with accession numbers xxx and xxx. Genes and accession numbers discussed within this manuscript correspond to the Cannabis sativa cs10 genome assembly deposited in National Center for Biotechnology Information with accession number GCA_900626175.2.

plant biology↗

bioRxiv2020

Automatic fruit morphology phenome and genetic analysis: An application in the octoploid strawberry

Automatizing phenotype measurement is needed to increase plant breeding efficiency. Morphological traits are relevant in many fruit breeding programs, as appearance influences consumer preference. Often, these traits are manually or semi-automatically obtained. Yet, fruit morphology evaluation can be boosted by resorting to fully automatized procedures and digital images provide a cost-effective opportunity for this purpose. Here, we present an automatized pipeline for comprehensive phenomic and genetic analysis of morphology traits extracted from internal and external strawberry images. The pipeline segments, classifies and labels the images, extracts conformation features, including linear (area, perimeter, height, width, circularity, shape descriptor, ratio between height and width) and multivariate (Fourier Elliptical components and Generalized Procrustes) statistics. Internal color patterns are obtained using an autoencoder to smooth out the image. In addition, we develop a variational autoencoder to automatically detect the most likely number of underlying shapes. Bayesian modeling is employed to estimate both additive and dominant effects for all traits. As expected, conformational traits are clearly heritable. Interestingly, dominance variance is higher than the additive component for most of the traits. Overall, we show that fruit shape and color can be quickly and automatically evaluated and is moderately heritable. Although we study the strawberry species, the algorithm can be applied to other fruits, as shown in the GitHub repository https://github.com/lauzingaretti/DeepAFS.

plant biology↗

bioRxiv2020

Tmed2 regulates Smoothened trafficking and Hedgehog signalling

Hedgehog (HH) signalling plays a key role in embryonic pattering and stem cell differentiation. Compounds that selectively bind Smoothened (SMO) can induce cell death in mouse embryonic stem cells (ESCs). Here we perform a genetic screen in haploid ESCs and discover that SMO inhibits a cell death pathway that resembles dissociation induced death of human ESCs and Anoikis. In mouse ESCs, SMO acts through a G-protein coupled mechanism that is independent of GLI activation. Our screen also identifies the Golgi proteins Tmed2 and Tmed10. We show that TMED2 binds SMO and controls its abundance at the plasma membrane. In neural differentiation and neural tube pattering Tmed2 acts as a repressor of HH signalling strength. We demonstrate that the interaction between SMO and TMED2 is regulated by HH signalling suggesting SMO release form the ER-Golgi is critical for controlling G-protein and GLI mediated functions of mammalian HH signalling.

cell biology↗