pengfeil

Pengfei Liu, Ph.D.

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Pengfei Liu, Ph.D.

Assistant Professor

Email

pengfeil@bcm.edu

Positions

Assistant Professor: Molecular and Human Genetics
Baylor College of Medicine

Director: ACGME/ABMGG Laboratory Genetics and Genomics Fellowship Program
Baylor College of Medicine
Houston, Texas United States

Associate Clinical Director: NGS/Molecular
Baylor Genetics

Education

PhD from Baylor College of Medicine: 01/2012 - Houston, TX

Certifications

Clinical Molecular Genetics: #2015130; American Board of Medical Genetics and Genomics

Honors & Awards

C. W. Cotterman Award: The American Society of Human Genetics (01/2012)

The 10 most significant advances in genomic medicine for 2019, by NHGRI: https://www.cell.com/ajhg/pdf/S0002-9297(19)30427-6.pdf

Dr. Michael S. Watson Genetic and Genomic Medicine Innovation Award: The ACMG Foundation for Genetic and Genomic Medicine (03/2022)

Professional Interests

Clinical whole genome sequencing
Medical genetics
Genomic disorders

Professional Statement

The ultimate research goals of the Liu lab are to (1) develop novel approaches to improve the implementation of genomic medicine, and to (2) utilize clinical diagnostic big data to generate knowledge that advances genomic science.

In the Undiagnosed Diseases Network (UDN) sequencing core, I have been leading the development and implementation of clinical whole genome sequencing (cWGS) for the diagnostics of Mendelian disorders. We have been working to establish a robust analytical pipeline with automation to perform reanalysis of cWGS data. To streamline interpretation of intronic variants revealed by cWGS, we have focused on neurological diseases, aiming to develop a fast, low-cost protocol that enables RNAseq profiling of patient-specific induced neurons trans-differentiated from clinically accessible tissues. Our group has also been investigating on various sequencing modalities beyond the currently widely used short-read based WGS technology for their potential in clinical diagnostics.

In another project, we seek to use the unique selection of patients with recurrent genomic deletions to elucidate the impact and mechanisms of genetic modifiers. We propose to integrate patient-based genomic analysis with cell-based genetic engineering and functional characterization to enhance the detection power of disease-risk alleles. Findings from this project are expected to bridge the gap between our understanding of highly penetrant, rare Mendelian variants and variants with higher population frequencies and association with complex diseases.