Literature DB >> 22322356

QTLs for murine red blood cell parameters in LG/J and SM/J F(2) and advanced intercross lines.

Thomas B Bartnikas1, Clarissa C Parker, Riyan Cheng, Dean R Campagna, Jackie E Lim, Abraham A Palmer, Mark D Fleming.   

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.

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Year:  2012        PMID: 22322356      PMCID: PMC3358495          DOI: 10.1007/s00335-012-9393-3

Source DB:  PubMed          Journal:  Mamm Genome        ISSN: 0938-8990            Impact factor:   2.957


  46 in total

1.  Quantitative trait loci for baseline white blood cell count, platelet count, and mean platelet volume.

Authors:  Luanne L Peters; Weidong Zhang; Amy J Lambert; Carlo Brugnara; Gary A Churchill; Orah S Platt
Journal:  Mamm Genome       Date:  2005-10-29       Impact factor: 2.957

2.  Evidence for linkage of red blood cell size and count: genome-wide scans in the Framingham Heart Study.

Authors:  Jing-Ping Lin; Christopher J O'Donnell; Li Jin; Caroline Fox; Qiong Yang; L Adrienne Cupples
Journal:  Am J Hematol       Date:  2007-07       Impact factor: 10.047

Review 3.  When does Parkinson disease start?

Authors:  Rodolfo Savica; Walter A Rocca; J Eric Ahlskog
Journal:  Arch Neurol       Date:  2010-07

4.  Quantitative trait loci regulating relative lymphocyte proportions in mouse peripheral blood.

Authors:  Jichun Chen; David E Harrison
Journal:  Blood       Date:  2002-01-15       Impact factor: 22.113

5.  Sequence variation at multiple loci influences red cell hemoglobin concentration.

Authors:  Luanne L Peters; Jordan A Shavit; Amy J Lambert; Shirng-Wern Tsaih; Qian Li; Zhiguang Su; Magalie S Leduc; Beverly Paigen; Gary A Churchill; David Ginsburg; Carlo Brugnara
Journal:  Blood       Date:  2010-09-10       Impact factor: 22.113

6.  Quantitative trait loci for baseline erythroid traits.

Authors:  Luanne L Peters; Amy J Lambert; Weidong Zhang; Gary A Churchill; Carlo Brugnara; Orah S Platt
Journal:  Mamm Genome       Date:  2006-04-04       Impact factor: 2.957

7.  Identification of quantitative trait loci that modify the severity of hereditary spherocytosis in wan, a new mouse model of band-3 deficiency.

Authors:  Luanne L Peters; Rebecca A Swearingen; Sabra G Andersen; Babette Gwynn; Amy J Lambert; Renhua Li; Samuel E Lux; Gary A Churchill
Journal:  Blood       Date:  2003-12-30       Impact factor: 22.113

8.  Red blood cells are the major source of alpha-synuclein in blood.

Authors:  Robin Barbour; Kristin Kling; John P Anderson; Kelly Banducci; Tracy Cole; Linnea Diep; Michael Fox; Jason M Goldstein; Ferdie Soriano; Peter Seubert; Tamie J Chilcote
Journal:  Neurodegener Dis       Date:  2008-01-04       Impact factor: 2.977

9.  MARCH ubiquitin ligases alter the itinerary of clathrin-independent cargo from recycling to degradation.

Authors:  Craig A Eyster; Nelson B Cole; Shariska Petersen; Kasinath Viswanathan; Klaus Früh; Julie G Donaldson
Journal:  Mol Biol Cell       Date:  2011-07-14       Impact factor: 4.138

10.  The MPI Bioinformatics Toolkit for protein sequence analysis.

Authors:  Andreas Biegert; Christian Mayer; Michael Remmert; Johannes Söding; Andrei N Lupas
Journal:  Nucleic Acids Res       Date:  2006-07-01       Impact factor: 16.971

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  6 in total

Review 1.  Fine-mapping QTLs in advanced intercross lines and other outbred populations.

Authors:  Natalia M Gonzales; Abraham A Palmer
Journal:  Mamm Genome       Date:  2014-06-07       Impact factor: 2.957

2.  High-resolution genetic mapping of complex traits from a combined analysis of F2 and advanced intercross mice.

Authors:  Clarissa C Parker; Peter Carbonetto; Greta Sokoloff; Yeonhee J Park; Mark Abney; Abraham A Palmer
Journal:  Genetics       Date:  2014-09       Impact factor: 4.562

3.  Identification and characterization of a novel murine allele of Tmprss6.

Authors:  Thomas B Bartnikas; Andrea U Steinbicker; Dean R Campagna; Sherika Blevins; Lanette S Woodward; Carolina Herrera; Kenneth D Bloch; Monica J Justice; Mark D Fleming
Journal:  Haematologica       Date:  2013-01-08       Impact factor: 9.941

4.  Using whole-genome sequences of the LG/J and SM/J inbred mouse strains to prioritize quantitative trait genes and nucleotides.

Authors:  Igor Nikolskiy; Donald F Conrad; Sung Chun; Justin C Fay; James M Cheverud; Heather A Lawson
Journal:  BMC Genomics       Date:  2015-05-28       Impact factor: 3.969

5.  Fine-mapping and genetic analysis of the loci affecting hepatic iron overload in mice.

Authors:  Xin Guo; Zhuzhen Zhang; Fan Zhang; Yunlong Tao; Peng An; Qian Wu; Chia-Yu Wang; Mitchell D Knutson; Fudi Wang
Journal:  PLoS One       Date:  2013-05-10       Impact factor: 3.240

6.  Genome-Wide Association Study in Two Cohorts from a Multi-generational Mouse Advanced Intercross Line Highlights the Difficulty of Replication Due to Study-Specific Heterogeneity.

Authors:  Xinzhu Zhou; Celine L St Pierre; Natalia M Gonzales; Jennifer Zou; Riyan Cheng; Apurva S Chitre; Greta Sokoloff; Abraham A Palmer
Journal:  G3 (Bethesda)       Date:  2020-03-05       Impact factor: 3.154

  6 in total

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