Seminario 24xan2019. Amplificacion do xenoma completo

 

foto Nuria Estevez     logo-Phylogenomics-lab-uvigo-300x116

O seminario será o xoves 24 de xaneiro 2019, as 10 h., na Sala de Conferencias CACTI (Torre CACTI-Planta 0)

Tito da charla:  Whole-genome amplification of cancer and healthy human single cells”. 

Ponente:  Nuria Estévez Gómez do grupo Phylogenomics Lab

A conferencia estará en español e inglés. No es necesario rexistro.

Resumo:

Single-cell genomics is an alluring area that holds the potential to change the way we understand cell populations. Due to the small amount of DNA within a single cell, whole-genome amplification becomes a mandatory step in many single-cell applications. Unfortunately, single-cell whole-genome amplification (scWGA) strategies suffer from several technical biases that complicate the posterior interpretation of the data. Here we compared the performance of six different scWGA methods (GenomiPhi, REPLIg, TruePrime, Ampli1, MALBAC, and PicoPLEX) after amplifying and low-pass sequencing the complete genome of 230 healthy/tumoral human cells. Overall, REPLIg outperformed competing methods regarding DNA yield, amplicon size, amplification breadth, amplification uniformity –being the only method with a random amplification bias–, and false single-nucleotide variant calls. On the other hand, non Multiple Displacement Amplification (non-MDA) methods, and in particular Ampli1, showed less allelic imbalance and allelic dropout (ADO), more reliable copy-number profiles and less chimeric amplicons. While no single scWGA method showed optimal performance for every aspect, they clearly have distinct advantages. Our results provide a convenient guide for selecting a scWGA method depending on the question of interest while revealing relevant weaknesses that should be considered during the analysis and interpretation of single-cell sequencing data.

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07/02/2019 Applied Physics Group
21/02/2019 Analytical & Food Chemistry. Biotoxins.
07/03/2019 Biomass and Sustainable Development
21/03/2019 Neuroscience