INV SUPERIOR JUBILADO
SEILICOVICH Adriana
congresos y reuniones científicas
Título:
Hunting Mutations, Targeting Disease
Autor/es:
M.I.PEREZ MILLAN; I.BERGADA; D.BRASLAVSKY; A.KESELMAN; J.KITZMAN; S.CAMPER; A. SEILICOVICH
Lugar:
Mar del Plata
Reunión:
Congreso; LXI Reunión de la Sociedad Argentina de Investigación Clínica; 2016
Resumen:
Congenital multiple pituitary hormone deficiency (MPHD) arises from defects in pituitary development and is sometimes associated with craniofacial abnormalities. Our objectives are to understand this disease pathophysiology and to improve molecular diagnosis and treatment of MPHD. Mutations in at least 8 genes have been found to cause hypopituitarism and up to 20 genes have been implicated but there is not yet enough evidence to prove pathogenicity.The overwhelming majority of patients do not have identified mutations in any of these genes. Our hypothesis is that the genetic factors that cause hormone deficiency are oligogenic and represent a collection of genes expressed in the developing embryonic pituitary, midline, and hypothalamus.We are setting up a new approach based on Molecular inversion probe (MIP) capture. We developed a refined version of the single-molecule molecular inversion probe (smMIP) capture assay. In this assay, a mixed pool of MIP capture probes is added to individual genomic DNA samples in a single-well reaction. Each probe is designed with two arms flanking a targeted region, such that when a probe anneals to its targeted genomic fragment, a polymerase copies the sequence between the flanking arms, and a ligase joins this copied sequence to the probe backbone. We established a panel of 67genes associated with MPHD in humans and mice. This panel targets 693 coding exons. In pilot MIP experiments, we obtained deep coverage over targeted regions, with approximately 2.1 million reads per individual, 97.6% of targeted bases reach ≥ 8X read depth coverage and 95.1% of bases reach ≥ 40X, such that up to 125 individuals could be readily pooled for sequencing on a single HiSeq lane. We believe that identifying these potential variants will make it feasible to predict clinical outcomes from genetic data, which is necessary for patient diagnosis and prognosis, and for assessing the risk of future affected individuals.