RESUMO
Human umbilical cord blood is a rich source of hematopoietic stem and progenitor cells. CD34+ cells in umbilical cord blood are more primitive than those in peripheral blood or bone marrow, and can proliferate at a high rate and differentiate into multiple cell types. In this protocol, a dependable method is described for the isolation of fetal CD34+ cells from umbilical cord blood and expanding these cells in culture. The cells can then be in vitro differentiated along an erythroid pathway, while simultaneously performing knockdown of a gene of choice. The use of lentiviral vectors that express small hairpin RNA (shRNA) is an efficient method to downregulate genes. Flow cytometric analyses are used to enrich for erythroid cells. Using these methods, one can generate in vitro differentiated cells to use for quantitative reverse transcriptase PCR and other purposes.
Assuntos
Diferenciação Celular/genética , Sangue Fetal/citologia , Técnicas de Silenciamento de Genes , Vetores Genéticos/genética , Células-Tronco Hematopoéticas/citologia , Células-Tronco Hematopoéticas/metabolismo , Lentivirus/genética , Antígenos CD34/metabolismo , Técnicas de Cultura de Células , Separação Celular , Células Eritroides/citologia , Células Eritroides/metabolismo , Citometria de Fluxo , Expressão Gênica , Células HEK293 , Humanos , TransfecçãoRESUMO
The impact of structural variants (SVs) on a variety of organisms and diseases like cancer has become increasingly evident. Methods for SV detection when studying genomic differences across cells, individuals or populations are being actively developed. Currently, just a few methods are available to compare different SVs callsets, and no specialized methods are available to annotate SVs that account for the unique characteristics of these variant types. Here, we introduce SURVIVOR_ant, a tool that compares types and breakpoints for candidate SVs from different callsets and enables fast comparison of SVs to genomic features such as genes and repetitive regions, as well as to previously established SV datasets such as from the 1000 Genomes Project. As proof of concept we compared 16 SV callsets generated by different SV calling methods on a single genome, the Genome in a Bottle sample HG002 (Ashkenazi son), and annotated the SVs with gene annotations, 1000 Genomes Project SV calls, and four different types of repetitive regions. Computation time to annotate 134,528 SVs with 33,954 of annotations was 22 seconds on a laptop.