@article {Abkallo078451, author = {Hussein M. Abkallo and Axel Martinelli and Megumi Inoue and Abhinay Ramaprasad and Phonepadith Xangsayarath and Jesse Gitaka and Jianxia Tang and Kazuhide Yahata and Augustin Zoungrana and Hayato Mitaka and Paul Hunt and Richard Carter and Osamu Kaneko and Ville Mustonen and Christopher J. R. Illingworth and Arnab Pain and Richard Culleton}, title = {Quantitative Seq-LGS {\textendash} Genome-Wide Identification of Genetic Drivers of Multiple Phenotypes in Malaria Parasites}, elocation-id = {078451}, year = {2016}, doi = {10.1101/078451}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Identifying the genetic determinants of phenotypes that impact on disease severity is of fundamental importance for the design of new interventions against malaria. Traditionally, such discovery has relied on labor-intensive approaches that require significant investments of time and resources. By combining Linkage Group Selection (LGS), quantitative whole genome population sequencing and a novel mathematical modeling approach (qSeq-LGS), we simultaneously identified multiple genes underlying two distinct phenotypes, identifying novel alleles for growth rate and strain specific immunity (SSI), while removing the need for traditionally required steps such as cloning, individual progeny phenotyping and marker generation. The detection of novel variants, verified by experimental phenotyping methods, demonstrates the remarkable potential of this approach for the identification of genes controlling selectable phenotypes in malaria and other apicomplexan parasites for which experimental genetic crosses are amenable.}, URL = {https://www.biorxiv.org/content/early/2016/09/30/078451}, eprint = {https://www.biorxiv.org/content/early/2016/09/30/078451.full.pdf}, journal = {bioRxiv} }