Single-cell Transcriptomics Reveals Inter-ethnic Variation in Immune Response to Falciparum Malaria. [Batch1]
Africa's environmental, cultural and genetic diversity can significantlygreatly influences how the populations' respondse to infectious diseases, including malaria, caused by Plasmodium falciparum. Differences in susceptibility to malaria between populations are documented but the underlying mechanisms are poorly understood. The Fulani ethnic group in Africa was reported to be less susceptible to malaria compared to other sympatric groups, such as the Mossi., They exhibit with lower disease rates and parasite load, as well as higher levels of serological protection. Unraveling the underlying genetic, molecular and cellularimmunological basis of this protection remains challenging, in part due to a lack of in-depth immunological characterization at the cellular level. Therefore, to address this question, we performed single cell transcriptomic RNA sequencing analysis ofon peripheral blood mononuclear cells from 126 infected and non-infected Fulani and Mossi children in rural Burkina Faso., This analysis generateding > 70,000 single-cell RNA-Seq profiles and identifiedying 30 cell subtypes. By performing cell subtype proportion analysis, we report an increased abundance of ?d T cells in infected Fulani samples compared to the Mossi counterpart. Moreover, cell-type specific differential expression analysis revealed ethnic-specific immune signatures in both infection states, and highlighted lower pro-inflammatory responses in the monocytes and T cell subtypes of the Fulani in both infection states, with a stronger activation and inflammatory profile in their B cell subtypes. Single-cell expression quantitative trait loci (eQTL) analysis in monocytes of infected samples revealed several significant regulatory variants with ethnic-specific effects. Overall, the results demonstrate the power of single cell transcriptomics in identifying ethnic, cell-type specific and genetic regulatory effects in the host immune response to malaria and provide valuable single-cell eQTL and transcriptomic data from populations underrepresented in genomic studies. Overall design: Expression profiling by high throughput sequencing.