Quantitative trait loci for steady-state platelet count in mice

Genome-wide association study identifies candidate Loci associated with platelet count in koreans

Platelets are derived from the fragments that are formed from the cytoplasm of bone marrow megakaryocytes-small irregularly shaped anuclear cells. Platelets respond to vascular damage, contracts blood vessels, and attaches to the damaged region, thereby stopping bleeding, together with the action of blood coagulation factors. Platelet activation is known to affect genes associated with vascular risk factors, as well as with arteriosclerosis and myocardial infarction. Here, we performed a genome-wide association study with 352,228 single-nucleotide polymorphisms typed in 8,842 subjects of the Korea Association Resource (KARE) project and replicated the results in 7,861 subjects from an independent population. We identified genetic associations between platelet count and common variants nearby chromosome 4p16.1 (p = 1.46 × 10^-10, in the KIAA0232 gene), 6p21 (p = 1.36 × 10^-7, in the BAK1 gene), and 12q24.12 (p = 1.11 × 10^-15, in the SH2B3 gene). Our results illustrate the value of large-scale discovery and a focus for several novel research avenues.

Genetic analysis of hematological parameters in incipient lines of the collaborative cross

Hematological parameters, including red and white blood cell counts and hemoglobin concentration, are widely used clinical indicators of health and disease. These traits are tightly regulated in healthy individuals and are under genetic control. Mutations in key genes that affect hematological parameters have important phenotypic consequences, including multiple variants that affect susceptibility to malarial disease. However, most variation in hematological traits is continuous and is presumably influenced by multiple loci and variants with small phenotypic effects. We used a newly developed mouse resource population, the Collaborative Cross (CC), to identify genetic determinants of hematological parameters. We surveyed the eight founder strains of the CC and performed a mapping study using 131 incipient lines of the CC. Genome scans identified quantitative trait loci for several hematological parameters, including mean red cell volume (Chr 7 and Chr 14), white blood cell count (Chr 18), percent neutrophils/lymphocytes (Chr 11), and monocyte number (Chr 1). We used evolutionary principles and unique bioinformatics resources to reduce the size of candidate intervals and to view functional variation in the context of phylogeny. Many quantitative trait loci regions could be narrowed sufficiently to identify a small number of promising candidate genes. This approach not only expands our knowledge about hematological traits but also demonstrates the unique ability of the CC to elucidate the genetic architecture of complex traits.

Quantitative trait loci analysis for peripheral blood parameters in a (BALB/cW × C57BL/6J-Mpl (hlb219)/J) F(2) mice

The genetic basis of the peripheral blood cell parameters is not fully elucidated. Thus, it is essential to research the correlation between blood cell counts levels and the genome in laboratory animals and subsequently in humans. In the present study, we examined 288 F(2) mice from a cross between BALB/cW and C57BL/6J-Mpl(hlb219)/J. The C57BL/6J-Mpl (hlb219)/J strain is a mouse model of thrombocytopenia. We found very strong correlations for PLT counts and revealed some highly significant correlations for RBC counts. On the basis of the obtained results, we presume that genetic control of erythrocyte parameters is divided into two pathways: first, the morphological determinants responsible for the red blood cell count (RBC), hematocrit (HCT), and mean corpuscular volume (MCV), and second, the functional pathway determining the hemoglobin content (HGB). The locus on Chromosome 4 is the only detected quantitative trait locus (QTL) influencing the analyzed platelets parameters. We also detected highly significant correlations for erythrocyte parameters on Chromosome 1 (RBC, MCV, MCH), Chr 7 (HGB), Chr 9 (MCHC), Chr 11 (RBC), and Chr 17 (MCH). Finally, with regards to the given correlations, using the Mouse Genome Database resource, we proposed candidate genes with possible meaning for the level of these parameters: cytokine receptor genes (e.g., Mpl), transcription factor genes (e.g., Xbp1, Ikzf1), hemoglobin chain genes (e.g., Hbb-b1, Hbb-ar), and many others localized in the confidence intervals of found QTLs.

Evolutionary conservation of metabolism explains howDrosophila nutrigenomics can help us understand human nutrigenomics

While large populations in the third world are enduring famine, much of the developed world is undergoing an obesity epidemic. In addition to reflecting an unbalanced distribution of food, the "epidemic of overabundance" is ironically leading to a decrease in the health and longevity of the obese and improperly nourished in the first world. International consortia, such as the European Nutrigenomics Organization (NuGO), are increasing our knowledge of nutrientgene interactions and the effects of diet and obesity on human health. In this review, we summarize both previous and ongoing nutrigenomics studies in Drosophila and we explain how these studies can be used to provide insights into molecular mechanisms underlying nutrigenomics in humans. We will discuss how quantitative trait locus (QTL) experiments have identified genes that affect triglyceride levels in Drosophila, and how microarray analyses show that hundreds of genes have altered gene expression under different dietary conditions. Finally, we will discuss ongoing combined microarray-QTL studies, termed "genetical genomics," that promise to identify "master modulatory loci" that regulate global responses of potentially hundreds of genes under different dietary conditions. When "master modulatory loci" are identified in Drosophila, then experiments in mammalian models can be used to determine the relevance of these genes to human nutrition and health.

The genetics of common variation affecting platelet development, function and pharmaceutical targeting

Common variant effects on human platelet function and response to anti-platelet treatment have traditionally been studied using candidate gene approaches involving a limited number of variants and genes. These studies have often been undertaken in clinically defined cohorts. More recently, studies have applied genome-wide scans in larger population samples than prior candidate studies, in some cases scanning relatively healthy individuals. These studies demonstrate synergy with some prior candidate gene findings (e.g., GP6, ADRA2A) but also uncover novel loci involved in platelet function. Here, I summarise findings on common genetic variation influencing platelet development, function and therapeutics. Taken together, candidate gene and genome-wide studies begin to account for common variation in platelet function and provide information that may ultimately be useful in pharmacogenetic applications in the clinic. More than 50 loci have been identified with consistent associations with platelet phenotypes in ≥ 2 populations. Several variants are under further study in clinical trials relating to anti-platelet therapies. In order to have useful clinical applications, variants must have large effects on a modifiable outcome. Regardless of clinical applications, studies of common genetic influences, even of small effect, offer additional insights into platelet biology including the importance of intracellular signalling and novel receptors. Understanding of common platelet-related genetics remains behind parallel fields (e.g., lipids, blood pressure) due to challenges in phenotype ascertainment. Further work is necessary to discover and characterise loci for platelet function, and to assess whether these loci contribute to disease aetiologies or response to therapeutics.

Serious limitations of the QTL/microarray approach for QTL gene discovery

BACKGROUND

It has been proposed that the use of gene expression microarrays in nonrecombinant parental or congenic strains can accelerate the process of isolating individual genes underlying quantitative trait loci (QTL). However, the effectiveness of this approach has not been assessed.

RESULTS

Thirty-seven studies that have implemented the QTL/microarray approach in rodents were reviewed. About 30% of studies showed enrichment for QTL candidates, mostly in comparisons between congenic and background strains. Three studies led to the identification of an underlying QTL gene. To complement the literature results, a microarray experiment was performed using three mouse congenic strains isolating the effects of at least 25 biometric QTL. Results show that genes in the congenic donor regions were preferentially selected. However, within donor regions, the distribution of differentially expressed genes was homogeneous once gene density was accounted for. Genes within identical-by-descent (IBD) regions were less likely to be differentially expressed in chromosome 2, but not in chromosomes 11 and 17. Furthermore, expression of QTL regulated in cis (cis eQTL) showed higher expression in the background genotype, which was partially explained by the presence of single nucleotide polymorphisms (SNP).

CONCLUSIONS

The literature shows limited successes from the QTL/microarray approach to identify QTL genes. Our own results from microarray profiling of three congenic strains revealed a strong tendency to select cis-eQTL over trans-eQTL. IBD regions had little effect on rate of differential expression, and we provide several reasons why IBD should not be used to discard eQTL candidates. In addition, mismatch probes produced false cis-eQTL that could not be completely removed with the current strains genotypes and low probe density microarrays. The reviewed studies did not account for lack of coverage from the platforms used and therefore removed genes that were not tested. Together, our results explain the tendency to report QTL candidates as differentially expressed and indicate that the utility of the QTL/microarray as currently implemented is limited. Alternatives are proposed that make use of microarray data from multiple experiments to overcome the outlined limitations.

Detection of quantitative trait loci affecting haematological traits in swine via genome scanning

BACKGROUND

Haematological traits, which consist of mainly three components: leukocyte traits, erythrocyte traits and platelet traits, play extremely important role in animal immune function and disease resistance. But knowledge of the genetic background controlling variability of these traits is very limited, especially in swine.

RESULTS

In the present study, 18 haematological traits (7 leukocyte traits, 7 erythrocyte traits and 4 platelet traits) were measured in a pig resource population consisting of 368 purebred piglets of three breeds (Landrace, Large White and Songliao Black Pig), after inoculation with the swine fever vaccine when the pigs were 21 days old. A whole-genome scan of QTL for these traits was performed using 206 microsatellite markers covering all 18 autosomes and the X chromosome. Using variance component analysis based on a linear mixed model and the false discovery rate (FDR) test, 35 QTL with FDR < 0.10 were identified: 3 for the leukocyte traits, 28 for the erythrocyte traits, and 4 for the platelet traits. Of the 35 QTL, 25 were significant at FDR < 0.05 level, including 9 significant at FDR < 0.01 level.

CONCLUSIONS

Very few QTL were previously identified for hematological traits of pigs and never in purebred populations. Most of the QTL detected here, in particular the QTL for the platelet traits, have not been reported before. Our results lay important foundation for identifying the causal genes underlying the hematological trait variations in pigs.

Quantitative trait loci for porcine white blood cells and platelet-related traits in a White Duroc x Erhualian F resource population

White blood cell count and platelets are implicated as risk factors for common complex diseases. Genetic factors substantially affect these traits in humans and mice. However, little is known about the genetic architecture of these traits in pigs. To identify quantitative trait loci (QTL) for leucocyte- and platelet-related traits in pigs, the total leucocyte number and differential leucocyte counts including the fraction of basophils, eosinophils, lymphocytes, monocytes, neutrophils, and a series of platelet parameters including platelet count, mean platelet volume, platelet distribution width and plateletcrit were measured in 1033 F(2) animals on 240 days from a White Duroc x Erhualian intercross resource population. A total of 183 informative microsatellites distributed across 19 pig chromosomes (SSC) were genotyped across the entire resource population. Thirty-three QTL were identified for the examined traits, including eight genome-wide significant QTL for white blood cells and differential leucocyte counts on SSC2, 7, 8, 12 and 15 and six significant QTL for platelet-related traits on SSC2, 8, 13 and X. Erhualian or White Duroc alleles were not systematically associated with increased phenotypic values. These results not only confirmed many QTL identified previously in the mouse and swine, but also revealed a number of novel QTL for the traits recorded. Moreover, it is the first time that QTL for platelet-related traits in pigs have been reported.

Interspecific recombinant congenic strains between C57BL/6 and mice of the Mus spretus species: a powerful tool to dissect genetic control of complex traits

Complex traits are under the genetic control of multiple genes, often with weak effects and strong epistatic interactions. We developed two new collections of mouse strains to improve genetic dissection of complex traits. They are derived from several backcrosses of the Mus spretus SEG/Pas or STF/Pas strains on the C57BL/6J background. Each of the 55 interspecific recombinant congenic strains (IRCSs) carries up to eight SEG/Pas chromosomal segments with an average size of 11.7 Mb, totalizing 1.37% of the genome. The complete series covers 39.7% of the SEG/Pas genome. As a complementary resource, six partial or complete interspecific consomic strains were developed and increased genome coverage to 45.6%. To evaluate the usefulness of these strains for QTL mapping, 16 IRCSs were compared with C57BL/6J for seven hematological parameters. Strain 66H, which carries three SEG/Pas chromosomal segments, had lower red blood cell volume and higher platelet count than C57BL/6J. Each chromosomal segment was isolated in a congenic strain to evaluate individual effects. Congenic strains were combined to assess epistasis. Our data show that both traits were controlled by several genes with complex epistatic interactions. IRCSs are therefore useful to unravel QTL with small effects and gene-by-gene interactions.

Quantitative trait loci for peripheral blood cell counts: a study in baboons

Increasingly, baseline peripheral blood cell counts are implicated as risk factors for common complex diseases. While genetic influences on these hematologic parameters are firmly established, the genetic architecture of the blood counts is still poorly understood. In this article we used data from 582 healthy pedigreed baboons and variance components methods to localize quantitative trait loci (QTLs) influencing complete blood count variables. Besides performing genome-wide linkage scans for each trait individually, we conducted bivariate linkage analyses for all pairwise trait combinations to also identify pleiotropic QTLs influencing several blood counts. While significant and suggestive QTLs were localized throughout the genome (LOD range: 1.5-3.5), chromosomal regions associated with the expression of various hematologic parameters stand out. In particular, our results provide significant and consistent evidence for a QTL on the orthologous human chromosome 1p that is shared by several blood counts, mainly erythrocyte parameters. In addition, multiple suggestive evidence of linkage was detected on the orthologous human chromosomes 10 (near the q-terminus) and 19 (centromeric section). Future studies should help identify the genes responsible for these QTL and elucidate their role on baseline variation in hematologic indicators of health and disease.

Quantitative trait loci for baseline erythroid traits

A substantial genetic contribution underlies variation in baseline peripheral blood counts. We performed quantitative trait locus/loci (QTL) analyses to identify chromosome (Chr) regions harboring genes influencing the baseline erythroid parameters in F2 intercrosses between NZW/LacJ, SM/J, and C57BLKS/J inbred mice. We identified multiple significant QTL for red blood cell (RBC) count, hemoglobin (Hgb) and hematocrit (Hct) levels, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean cell hemoglobin concentration (CHCM). We identified four RBC count QTL: Rbcq1 (Chr 1, peak LOD score at 62 cM,), Rbcq2 (Chr 4, 60 cM), Rbcq3 (Chr 11, 34 cM), and Rbcq4 (Chr 10, 60 cM). Three MCV QTL were identified: Mcvq1 (Chr 7, 30 cM), Mvcq2 (Chr 11, 6 cM), and Mcvq3 (Chr 10, 60 cM). Single significant loci for Hgb (Hgbq1, Chr 16, 32 cM), Hct (Hctq1, Chr 3, 42 cM), and MCH (Mchq1, Chr 10, 60 cM) were identified. The data support the existence of a common RBC/MCH/MCV locus on Chr 10. Two QTL for CHCM (Chcmq1, Chr 2, 48 cM; Chcmq2, Chr 9, 44 cM) and an interaction between Chcmq2 with a locus on Chr 19 were identified. These analyses emphasize the genetic complexity underlying the regulation of erythroid peripheral blood traits in normal populations and suggest that genes not previously recognized as significantly impacting normal erythropoiesis exist.

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

A substantial genetic contribution to baseline peripheral blood counts has been established. We performed quantitative trait locus/loci (QTL) analyses to identify chromosome (Chr) regions harboring genes influencing the baseline white blood cell (WBC) count, platelet (Plt) count, and mean platelet volume (MPV) in F(2) intercrosses between NZW/LacJ, SM/J, and C57BLKS/J inbred mice. We identified six significant WBC QTL: Wbcq1 (peak LOD score at 38 cM, Chr 1), Wbcq2 (42 cM, Chr 3), Wbcq3 (0 cM, Chr 15), Wbcq4 (58 cM, Chr 1), Wbcq5 (82 cM, Chr 1), and Wbcq6 (8 cM, Chr 14). Three significant Plt QTL were identified: Pltq1 (24 cM, Chr 2), Pltq2 (36 cM, Chr 7), and Pltq3 (10 cM, Chr 12). Two significant MPV QTL were identified, Mpvq1 (62 cM, Chr 15) and Mpvq2 (44 cM, Chr 8). In total, the WBC QTL accounted for up to 31% of the total variance in baseline WBC count, while the Plt and MPV QTL accounted for up to 30% and 49% of the total variance, respectively. These analyses underscore the genetic complexity underlying these traits in normal populations and provide the basis for future studies to identify novel genes involved in the regulation of mammalian hematopoiesis.

Development of a highly fecund inbred strain of mice

A highly fecund inbred mouse line has been established from the Quackenbush Swiss (QS) outbred strain by full-sib inbreeding combined with selection for high number of pups born alive (NBA) and low interlitter interval (ILI). After more than 50 generations of inbreeding and selection, this line, named QSi5, has an NBA of 13.4 and an ILI of 29 days, averaged over the first four parities, and a total productivity of 50.7 NBA. With its exceptional reproductive performance, this line will be very useful in the creation of resources (including advanced intercross lines) for analysis of quantitative trait loci for a wide range of traits, and for the cost-effective creation of congenic lines.