Xue Li, Ph.D., is a bioinformatic scientist studying malaria parasites. Using powerful computational approaches and genetic crosses, Dr. Li seeks to identify the genetic basis of biomedically important traits in malaria parasites, including drug resistance, parasite fitness, and nutritional genetics. Dr. Li also focuses on using large scale whole-genome sequencing data to study parasite population genomics, such as spread of drug resistance alleles and patterns of parasite transmission, which are extremely valuable during malaria elimination programs.
Dr. Li earned a Ph.D. in 2016 from Ocean University of China. Her expertise is in statistical, bioinformatic and population genetic data processing and analysis. She joined Texas Biomed in 2017.
Inside the Lab
Malaria infects around 200 million people and kills over 400,000 each year. With the absence of commercially available vaccine, malaria treatment largely depends on clinical antimalarial drugs. However, resistances to almost all antimalarial drugs currently in use, have been reported in the most lethal human malaria parasite, Plasmodium falciparum.
Working with Dr. Tim Anderson, Dr. Li focuses on using genetic crosses to study the basis of important traits for malaria parasite biology and epidemiology, as well as using population genetic tools to understand the dynamics of parasite transmission during malaria elimination.
Malaria parasite genetics
Classical genetic crosses in malaria parasites requires isolation, genotyping and phenotyping of multiple progeny parasites, which is time consuming and laborious. Dr. Li coordinated with wet-lab members to explore a powerful approach that overcomes these problems to identify loci underlying complex traits in the human malaria parasite, Plasmodium falciparum. This approach combines experimental genetic crosses using humanized mice, with selective whole genome amplification and pooled sequencing. Dr. Li has used this method to identify genomic regions that determine parasite fitness across the whole life cycle, genes underlying drug resistance and loci involved with parasite nutritional genetics.
Dynamics of parasite transmission during malaria elimination
Genomic surveillance of malaria parasites, which can be used to monitor the spread of drug resistant alleles and to examine patterns of parasite transmission, is extremely valuable during malaria elimination programs. Dr. Li established a systematic approach for surveillance of parasite population genomics in a region of intense parasite control. The P. falciparum genome is highly repetitive and the most AT-rich genome sequenced to date, complicating genomic analysis. To access genetic variations for this population genetic analysis, Dr. Li has also developed methods for accurate genotyping P. falciparum genome from next generation sequencing data, as well as from long-read third generation sequencing data.
Artemisinin resistance in malaria parasites
Artemisinin is currently the global front-line treatment for malaria infections. Resistance has rapidly spread through South-East Asia and has reached Africa. Fitness costs are key determinants of whether drug resistance alleles establish and how fast they spread within populations. Dr. Li developed an amplicon sequencing analysis pipeline to examine the fitness consequences of different kelch13 alleles. Her study concludes that fitness costs alone are not able to explain the population dynamics of artemisinin resistance alleles spread in South-East Asia. Compensatory mutations that restore parasite fitness in nature may be involved.
Main Technologies and Methods Used
- Next-generation sequencing
- Long-read Nanopore sequencing
- Amplicon sequencing
- Population genomics
- Linkage mapping with genetic crosses
- Genome-wide association studies
- CRISPR/Cas9 gene editing
- Whole genome amplification
- Transcriptome analysis