A NEW WORKFLOW OF FETAL DNA PREDICTION FROM CELL-FREE DNA IN MATERNAL PLASMA by

نویسندگان

  • Yerkebulan Talzhanov
  • Michael Barmada
  • Eleanor Feingold
  • David Peters
  • Aleksandar Rajkovic
چکیده

Prediction of fetal DNA allows diagnosing known/passed mutations before child’s birth. Public health significance of such early testing is that it can reassure parents who have negative results and offers timely information for those with abnormal results. My dissertation work presents a new approach of reconstructing fetal DNA from maternal plasma. The method works because plasma from pregnant women, which contains “cell-free DNA”, has been noted to contain fetal DNA as well as maternal DNA. I developed and tested a workflow that implements my suggested approach. The workflow was broken into several parts, each fully documented in this dissertation. Each step we have taken was supported with explanation of the logic driving the step. The approach works through the examination of sequencing data sets generated by short-read sequencing (also known as next-generation sequencing), by calling variation (single nucleotide polymorphisms, or SNPs) within those samples vis-à-vis a reference sequence. I developed and introduced a series of quality control criteria applied to SNPs to improve overall prediction. A novel single individual haplotyping method was developed and applied to haplotype the parental samples. The obtained parental haplotypes were incorporated into the workflow and along with parental genotypes were used to A NEW WORKFLOW OF FETAL DNA PREDICTION FROM CELL-FREE DNA IN MATERNAL PLASMA Yerkebulan Talzhanov, PhD University of Pittsburgh, 2015

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تاریخ انتشار 2015