Biology subjects

Ortega, A.

Publications and source records attributed to Ortega, A..

23 records · Page 2Linked to original sources

bioRxiv2022

Different transcriptional responses by the CRISPRa system in distinct types of heterochromatin in Drosophila melanogaster

Transcription factors (TFs) activate gene expression by binding to elements close to promoters or enhancers. Some TFs can bind to heterochromatic regions to initiate gene activation, suggesting that if a TF is able to bind to any type of heterochromatin, it can activate transcription. To investigate this possibility, we used the CRISPRa system based on dCas9-VPR as an artificial TF in Drosophila. dCas9-VPR was targeted to the TAHRE subtelomeric element, an example of constitutive heterochromatin, and to promoters and enhancers of the HOX Ultrabithorax (Ubx) and Sex Combs Reduced (Scr) genes in the context of facultative heterochromatin. dCas9-VPR robustly activated TAHRE transcription, showing that although this element is heterochromatic, dCas9-VPR was sufficient to activate its expression. In the case of HOX gene promoters, although these genes are epigenetically silenced by Polycomb complexes, both were ectopically activated. When the artificial TF was directed to enhancers, we found that the expression pattern was different compared to the effect on the promoters. In the case of the Scr upstream enhancer, dCas9-VPR activated the gene ectopically but with less expressivity; however, ectopic activation also occurred in different cells. In the case of the bxI enhancer located in the third intron of Ubx, the presence of dCas9-VPR is capable of increasing transcription initiation while simultaneously blocking transcription elongation, generating a lack of functional phenotype. Our results show that transcription can be activated in any type of heterochromatin by CRISPRa; nevertheless, its effect on transcription is subject to the intrinsic characteristics of each gene or regulatory element. SignificanceWhether transcription only depends on activating factors binding to chromatin, even though it is found in a silent state as heterochromatin, remains an open question. In this work, we addressed this question using the CRISPRa system via dCas9-VPR as a synthetic transcriptional activator in Drosophila. This activator was directed to a constitutive heterochromatin element and to promoters and enhancers of two HOX genes, which in the tissues where they are not expressed, are present as facultative heterochromatin. In all cases, the CRISPRa system was able to activate transcription, showing that its sole presence is sufficient for this to occur. Although transcription in constitutive heterochromatin was very robust, in the case of promoters and enhancers of HOX genes, the degree of expressivity, penetrance and ectopic effect was different between promoters and enhancers. These results indicate that the presence of a synthetic activator can activate transcription by binding to transcriptional regulatory elements; however, its effect depends on the particular characteristics of each one. These results show how artificial transcription factors can be used to understand transcription regulation at the organismal level.

genetics↗

bioRxiv2021

DcPAR1 Is Required For Development And Carotenoid Synthesis In The Dark-Grown Carrot Taproot

Light stimulates carotenoid synthesis in plants during photomorphogenesis through the expression of PHYTOENE SYNTHASE (PSY), a key gene in carotenoid biosynthesis. The orange Daucus carota (carrot) synthesizes and accumulates high amounts of carotenoids in the taproot that grows underground. Contrary to other organs, light impairs carrot taproot development and represses the expression of carotenogenic genes such as DcPSY1 and DcPSY2 reducing carotenoid accumulation. By means of an RNA-seq, in previous analysis we observed that carrot PHYTOCHROME RAPIDLY REGULATED 1 (DcPAR1) is more expressed in the underground grown taproot respect to those grown in light. PAR1 is a transcriptional cofactor with a negative role in the shade avoidance syndrome regulation in Arabidopsis thaliana through the dimerization with PHYTOCHROME INTERACTING FACTORs (PIFs), allowing a moderate synthesis of carotenoids. Here we show that overexpressing AtPAR1 in carrot produces an increment of carotenoids in taproots grown underground as well as higher DcPSY1 expression. The high identity of AtPAR1 and DcPAR1 let us to suggest a functional role of DcPAR1 that was verified through the in vivo binding to AtPIF7 and the overexpression in Arabidopsis, where it increments AtPSY expression and carotenoid accumulation together with a photomorphogenic phenotype. Finally, DcPAR1 antisense carrot lines presented a dramatic decrease in carotenoids levels and in the relative expression of key carotenogenic genes as well as impairment in taproot development. These results let us to propose that DcPAR1 is a key factor for secondary root development, plastid differentiation and carotenoid synthesis in carrot taproot grown underground. One-sentence summaryDcPAR1 is a key factor for secondary root development, plastid differentiation and carotenoid synthesis in carrot taproot grown underground.

plant biology↗

bioRxiv2021

A general deep learning model for bird detection in high resolution airborne imagery

Advances in artificial intelligence for computer vision hold great promise for increasing the scales at which ecological systems can be studied. The distribution and behavior of individuals is central to ecology, and computer vision using deep neural networks can learn to detect individual objects in imagery. However, developing supervised models for ecological monitoring is challenging because it needs large amounts of human-labeled training data, requires advanced technical expertise and computational infrastructure, and is prone to overfitting. This limits application across space and time. One solution is developing generalized models that can be applied across species and ecosystems. Using over 250,000 annotations from 13 projects from around the world, we develop a general bird detection model that achieves over 65% recall and 50% precision on novel aerial data without any local training despite differences in species, habitat, and imaging methodology. Fine-tuning this model with only 1000 local annotations increase these values to an average of 84% recall and 69% precision by building on the general features learned from other data sources. Retraining from the general model improves local predictions even when moderately large annotation sets are available and makes model training faster and more stable. Our results demonstrate that general models for detecting broad classes of organisms using airborne imagery are achievable. These models can reduce the effort, expertise, and computational resources necessary for automating the detection of individual organisms across large scales, helping to transform the scale of data collection in ecology and the questions that can be addressed.

ecology↗

bioRxiv2020

A high-quality genome assembly and annotation of the gray mangrove, Avicennia marina

The gray mangrove [Avicennia marina (Forsk.) Vierh.] is the most widely distributed mangrove species, ranging throughout the Indo-West Pacific. It presents remarkable levels of geographic variation both in phenotypic traits and habitat, often occupying extreme environments at the edges of its distribution. However, subspecific evolutionary relationships and adaptive mechanisms remain understudied, especially across populations of the West Indian Ocean. High-quality genomic resources accounting for such variability are also sparse. Here we report the first chromosome-level assembly of the genome of A. marina. We used a previously release draft assembly and proximity ligation libraries Chicago and Dovetail HiC for scaffolding, producing a 456,526,188 bp long genome. The largest 32 scaffolds (22.4 Mb to 10.5 Mb) accounted for 98 % of the genome assembly, with the remaining 2% distributed among much shorter 3,759 scaffolds (62.4 Kb to 1 Kb). We annotated 23,331 protein-coding genes using tissue-specific RNA-seq data, from which 13,312 were associated to GO terms. Genome assembly and annotated set of genes yield a 96.7% and 92.3% completeness score, respectively, when compared with the eudicots BUSCO dataset. Furthermore, an FST survey based on resequencing data successfully identified a set of candidate genes potentially involved in local adaptation, and revealed patterns of adaptive variability correlating with a temperature gradient in Arabian mangrove populations. Our A. marina genomic assembly provides a highly valuable resource for genome evolution analysis, as well as for identifying functional genes involved in adaptive processes and speciation.

genomics↗

bioRxiv2016

Identifying the diamond in the rough: a study of allelic diversity underlying flowering time adaptation in maize landraces

Landraces (traditional varieties) of crop species are a reservoir of useful genetic diversity, yet remain untapped due to the genetic linkage between the few useful alleles with hundreds of undesirable alleles1. We integrated two approaches to characterize the genetic diversity of over 3000 maize landraces from across the Americas. First, we mapped the genomic regions controlling latitudinal and altitudinal adaptation, identifying 1498 genes. Second, we developed and used F-One Association Mapping (FOAM) to directly map genes controlling flowering time across 22 environments, identifying 1,005 genes. In total 65% of the SNPs associated with altitude were also associated with flowering time. In particular, we observed many of the significant SNPs were contained in large structural variants (inversions, centromeres, and pericentromeric regions): 29.4% for flowering time, 58.4% for altitude and 13.1% for latitude. The combined mapping results indicate that while floral regulatory network genes contribute substantially to field variation, over 90% of contributing genes likely have indirect effects. Our strategy can be used to harness the diversity of maize and other plant and animal species.

genetics↗