DNA sequence diversity in a 9.7-kb region of the human lipoprotein lipase gene

• Published in: Nature genetics Vol. 19; no. 3; pp. 233 - 240
• Main Authors: Nickerson, Deborah A, Taylor, Scott L, Weiss, Kenneth M, Clark, Andrew G, Hutchinson, Richard G, Stengård, Jari, Salomaa, Veikko, Vartiainen, Erkki, Boerwinkle, Eric, Sing, Charles F
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group 01.07.1998
• Subjects: Base Sequence; Biological and medical sciences; Classical genetics, quantitative genetics, hybrids; DNA, Complementary; Fundamental and applied biological sciences. Psychology; Genetic Variation; Genetics of eukaryotes. Biological and molecular evolution; Human; Humans; Lipoprotein Lipase - genetics; Molecular Sequence Data; Sequence Analysis, DNA; Human; Genetic variability; Enzyme; Genetic variant; Cardiovascular disease; Lipids; Esterases; Lipoprotein lipase; Metabolism; Population genetics; Carboxylic ester hydrolases; Association; Gene; Hydrolases; Polymorphism
• ISSN: 1061-4036; 1546-1718
• DOI: 10.1038/907

Lipoprotein lipase plays a central role in lipid metabolism and the gene that encodes this enzyme (LPL) is a candidate susceptibility gene for cardiovascular disease. Here we report the complete sequence of a fraction of the LPL gene for 71 individuals (142 chromosomes) from three populations that may have different histories affecting the organization of the sequence variation. Eighty-eight sites in this 9.7 kb vary among individuals from these three populations. Of these, 79 were single nucleotide substitutions and 9 sites involved insertion-deletion variations. The average nucleotide diversity across the region was 0.2% (or on average 1 variable site every 500 bp). At 34 of these sites, the variation was found in only one of the populations, reflecting the differing population and mutational histories. If LPL is a typical human gene, the pattern of sequence variation that exists in introns as well as exons, even for the small number of samples considered here, will present challenges for the identification of sites, or combinations of sites, that influence variation in risk of disease in the population at large.