Building a Portuguese Coalition for Biodiversity Genomics

The diverse physiography of the Portuguese land and marine territory, spanning from continental Europe to the Atlantic archipelagos, has made it an important repository of biodiversity throughout the Pleistocene glacial cycles, leading to a remarkable diversity of species and ecosystems. This rich biodiversity is under threat from anthropogenic drivers, such as climate change, invasive species, land use changes, overexploitation or pathogen (re)emergence. The inventory, characterization and study of biodiversity at inter- and intra-specific levels using genomics is crucial to promote its preservation and recovery by informing biodiversity conservation policies, management measures and research. The participation of researchers from Portuguese institutions in the European Reference Genome Atlas (ERGA) initiative, and its pilot effort to generate reference genomes for European biodiversity, has reinforced the establishment of Biogenome Portugal. This nascent institutional network will connect the national community of researchers in genomics. Here, we describe the Portuguese contribution to ERGA’s pilot effort, which will generate high-quality reference genomes of six species from Portugal that are endemic, iconic and/or endangered, and include plants, insects and vertebrates (fish, birds and mammals) from mainland Portugal or the Azores islands. In addition, we outline the objectives of Biogenome Portugal, which aims to (i) promote scientific collaboration, (ii) contribute to advanced training, (iii) stimulate the participation of institutions and researchers based in Portugal in international biodiversity genomics initiatives, and (iv) contribute to the transfer of knowledge to stakeholders and engaging the public to preserve biodiversity. This initiative will strengthen biodiversity genomics research in Portugal and fuel the genomic inventory of Portuguese eukaryotic species. Such efforts will be critical to the conservation of the country’s rich biodiversity and will contribute to ERGA’s goal of generating reference genomes for European species.info:eu-repo/semantics/publishedVersio

Study of the Marbled Newt (Triturus (m.) marmoratus and T. (m.) pygmaeus) hybrid zone by genetic markers . [Estudo da Zona Híbrida entre Triturus marmoratus e T. pygmaeus por Marcadores Genéticos]

Dissertação de Mestrado em Ecologia Aplicada, área de especialização em Genética Populacional, apresentada à Faculdade de Ciências da Universidade do Port

DNA sequences in IMa2 format of marbled newts from the Iberian Peninsula

IMa2 input files for four different areas of the T. marmoratus / T. pygmaeus hybrid zone (Coastal Portugal, Tejo river, Idanha-a-Nova and Sierra da Gata). BF = beta-Fibrinogen intron 7 ; CALC = Calreticulin intron 3 ; PDGFRA = Platelet-derived growth factor receptor alpha intron 11 and ND4 = mitochondrial NADH dehydrogenase subunit 4

Locality data of sampling location of Triturus marmoratus and T. pygmaeus

Locality data of sampled populations of T. marmoratus and T. pygmaeus, including Locality name and order number, country, hybrid zone area as described in the paper, and GPS coordinates

Metabolic signature of the pathogenic 22q11.2 deletion identifies carriers and provides insight into systemic dysregulation

Large deletions at chromosome 22q11.2 are known to cause severe clinical conditions collectively known as 22q11.2 deletion syndrome. Notwithstanding the pathogenicity of these deletions, affected individuals are typically diagnosed in late childhood or early adolescence, and little is known of the molecular signaling cascades and biological consequences immediately downstream of the deleted genes. Here, we used targeted metabolomics to compare neonatal dried blood spot samples from 203 individuals clinically identified as carriers of a deletion at chromosome 22q11.2 with 203 unaffected individuals. A total of 173 metabolites were successfully identified and used to inform on systemic dysregulation caused by the genomic lesion and to discriminate carriers from non-carriers. We found 84 metabolites to be differentially abundant between carriers and non-carriers of the 22q11.2 deletion. A predictive model based on all 173 metabolites achieved high Accuracy (89%), Area Under the Curve (93%), F1 (88%), Positive Predictive Value (94%), and Negative Predictive Value (84%) with tyrosine and proline having the highest individual contributions to the model as well as the highest interaction strength. Targeted metabolomics provides insight into the molecular consequences possibly contributing to the pathology underlying the clinical manifestations of the 22q11 deletion and is an easily applicable approach to first-pass screening for carrier status of the 22q11 to prompt subsequent verification of the genomic diagnosis.info:eu-repo/semantics/publishedVersio