IBYME   02675
INSTITUTO DE BIOLOGIA Y MEDICINA EXPERIMENTAL
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
Whole genome jaguar (Panthera onca) population structure analysis
Autor/es:
PEGUEROLES QUERALT, CINTA; GABALDÓN, TONI; TARIFA, INTI; JULCA CHAVEZ, IRENE CONSUELO; PISCIOTTANO, FRANCISCO; WILLIS, JESSE R. ; SARAGÜETA, PATRICIA
Lugar:
Mar del Plata, Buenos Aires
Reunión:
Congreso; 9no Congreso Argentino de Bioinformática y Biología Computacional; 2018
Institución organizadora:
Asociación Argentina de Bioinformática y Biología Computacional (A2B2C)
Resumen:
The jaguar (Panthera onca) is the largest felid in America and the most emblematic South American predator. This carnivore species holds a high environmental importance in all ecosystems it inhabits for its apex predator role. However, jaguar populations have suffered an important decline over the last century and today this species is considered as critically endangered in our country. Not only furtive hunting, habitat destruction and deforestation have strongly reduced jaguar individuals number, but also habitat fragmentation due to human activity and urbanization have rendered small and isolated subsisting populations that may not endure inbreeding effects (Galetti et al. 2013). Ensuring the sustainability of the remaining jaguar populations demands a high degree ofknowledge about the current state of their genetic variability levels and a description of population structure is essential, especially to allow rational translocation and reintroduction actions. The first jaguar reference genome was released in 2017 (Figueiro et al. 2017) by the Jaguar Genome Project, a consortium we integrate. Moreover, we carried out the whole genome sequencing of 9 jaguar samples using Illumina 2500 NSG technology. Here we present the first results obtained from these 9 genomes compared to the reference. We performed a population structure analysis in order to estimate the optimal number of populations present in our data and a Multiple Correspondece Analysis (MCA) clustering of our samples based on over 280.000 homozygous variable positions in their genomes.