1. QTLs for murine red blood cell parameters in LG/J and SM/J F(2) and advanced intercross lines
- Author
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Thomas B. Bartnikas, Abraham A. Palmer, Riyan Cheng, Mark D. Fleming, Clarissa C. Parker, Jackie E. Lim, and Dean R. Campagna
- Subjects
Nonsynonymous substitution ,Male ,Candidate gene ,Erythrocytes ,Molecular Sequence Data ,Quantitative Trait Loci ,Mean corpuscular hemoglobin ,Single-nucleotide polymorphism ,Mice, Inbred Strains ,Quantitative trait locus ,Biology ,Polymorphism, Single Nucleotide ,Article ,Mice ,Genetics ,medicine ,Animals ,Humans ,Inbreeding ,Amino Acid Sequence ,Crosses, Genetic ,Red Cell ,medicine.diagnostic_test ,Oxygen transport ,Proteins ,Red blood cell ,medicine.anatomical_structure ,Female ,Sequence Alignment - Abstract
Red blood cells are essential for oxygen transport and other physiologic processes. Red cell characteristics are typically determined by complete blood counts which measure parameters such as hemoglobin levels and mean corpuscular volumes; these parameters reflect the quality and quantity of red cells in the circulation at any particular moment. To identify the genetic determinants of red cell parameters, we performed genome-wide association analysis on LG/J × SM/J F2 and F34 advanced intercross lines using single nucleotide polymorphism genotyping and a novel algorithm for mapping in the combined populations. We identified significant quantitative trait loci for red cell parameters on chromosomes 6, 7, 8, 10, 12, and 17; our use of advanced intercross lines reduced the quantitative trait loci interval width from 1.6- to 9.4-fold. Using the genomic sequences of LG/J and SM/J mice, we identified nonsynonymous coding single nucleotide polymorphisms in candidate genes residing within quantitative trait loci and performed sequence alignments and molecular modeling to gauge the potential impact of amino acid substitutions. These results should aid in the identification of genes critical for red cell physiology and metabolism and demonstrate the utility of advanced intercross lines in uncovering genetic determinants of inherited traits.
- Published
- 2011