title: Systems mapping for hematopoietic progenitor cell heterogeneity.
abstract: Cells with the same genotype growing under the same conditions can show different phenotypes, which is known as "population heterogeneity". The heterogeneity of hematopoietic progenitor cells has an effect on their differentiation potential and lineage choices. However, the genetic mechanisms governing population heterogeneity remain unclear. Here, we present a statistical model for mapping the quantitative trait locus (QTL) that affects hematopoietic cell heterogeneity. This strategy, termed systems mapping, integrates a system of differential equations into the framework for systems mapping, allowing hypotheses regarding the interplay between genetic actions and cell heterogeneity to be tested. A simulation approach based on cell heterogeneity dynamics has been designed to test the statistical properties of the model. This model not only considers the traditional QTLs, but also indicates the methylated QTLs that can illustrate non-genetic individual differences. It has significant implications for probing the molecular, genetic and epigenetic mechanisms of hematopoietic progenitor cell heterogeneity.
authors.affiliation: Center for Computational Biology, Beijing Forestry University, Beijing, People's Republic of China.
authors.forename: Linghua
authors.initials: L
authors.lastname: Zhou
authors.affiliation: Center for Computational Biology, Beijing Forestry University, Beijing, People's Republic of China.
authors.forename: Yong
authors.initials: Y
authors.lastname: Shen
authors.affiliation: Center for Computational Biology, Beijing Forestry University, Beijing, People's Republic of China.
authors.forename: Libo
authors.initials: L
authors.lastname: Jiang
authors.affiliation: Center for Computational Biology, Beijing Forestry University, Beijing, People's Republic of China.
authors.forename: Danni
authors.initials: D
authors.lastname: Yin
authors.affiliation: Center for Computational Biology, Beijing Forestry University, Beijing, People's Republic of China.
authors.forename: Jingxin
authors.initials: J
authors.lastname: Guo
authors.affiliation: CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, Guangdong, People's Republic of China.
authors.forename: Hui
authors.initials: H
authors.lastname: Zheng
authors.affiliation: CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, Guangdong, People's Republic of China.
authors.forename: Hao
authors.initials: H
authors.lastname: Sun
authors.affiliation: Center for Computational Biology, Beijing Forestry University, Beijing, People's Republic of China; Center for Statistical Genetics, Pennsylvania State University, Hershey, Pennsylvania, United States of America.
authors.forename: Rongling
authors.initials: R
authors.lastname: Wu
authors.affiliation: Center for Computational Biology, Beijing Forestry University, Beijing, People's Republic of China.
authors.forename: Yunqian
authors.initials: Y
authors.lastname: Guo
mesh_terms: D000465:Algorithms; D002874:Chromosome Mapping; D019175:DNA Methylation; D044127:Epigenesis, Genetic; D005838:Genotype; D006412:Hematopoietic Stem Cells / Q000502:physiology*; D006801:Humans; D008957:Models, Genetic; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci