Mouse genome-wide association and systems genetics identify Asxl2 as a regulator of bone mineral density and osteoclastogenesis

Significant advances have been made in the discovery of genes affecting bone mineral density (BMD); however, our understanding of its genetic basis remains incomplete. In the current study, genome-wide association (GWA) and co-expression network analysis were used in the recently described Hybrid Mouse Diversity Panel (HMDP) to identify and functionally characterize novel BMD genes. In the HMDP, a GWA of total body, spinal, and femoral BMD revealed four significant associations (-log10P>5.39) affecting at least one BMD trait on chromosomes (Chrs.) 7, 11, 12, and 17. The associations implicated a total of 163 genes with each association harboring between 14 and 112 genes. This list was reduced to 26 functional candidates by identifying those genes that were regulated by local eQTL in bone or harbored potentially functional non-synonymous (NS) SNPs. This analysis revealed that the most significant BMD SNP on Chr. 12 was a NS SNP in the additional sex combs like-2 (Asxl2) gene that was predicted to be functional. The involvement of Asxl2 in the regulation of bone mass was confirmed by the observation that Asxl2 knockout mice had reduced BMD. To begin to unravel the mechanism through which Asxl2 influenced BMD, a gene co-expression network was created using cortical bone gene expression microarray data from the HMDP strains. Asxl2 was identified as a member of a co-expression module enriched for genes involved in the differentiation of myeloid cells. In bone, osteoclasts are bone-resorbing cells of myeloid origin, suggesting that Asxl2 may play a role in osteoclast differentiation. In agreement, the knockdown of Asxl2 in bone marrow macrophages impaired their ability to form osteoclasts. This study identifies a new regulator of BMD and osteoclastogenesis and highlights the power of GWA and systems genetics in the mouse for dissecting complex genetic traits.     

A Genome-Wide Association Study of the Maize Hypersensitive Defense Response Identifies Genes That Cluster in Related Pathways

Much remains unknown of molecular events controlling the plant hypersensitive defense response (HR), a rapid localized cell death that limits pathogen spread and is mediated by resistance (R-) genes. Genetic control of the HR is hard to quantify due to its microscopic and rapid nature. Natural modifiers of the ectopic HR phenotype induced by an aberrant auto-active R-gene (Rp1-D21), were mapped in a population of 3,381 recombinant inbred lines from the maize nested association mapping population. Joint linkage analysis was conducted to identify 32 additive but no epistatic quantitative trait loci (QTL) using a linkage map based on more than 7000 single nucleotide polymorphisms (SNPs). Genome-wide association (GWA) analysis of 26.5 million SNPs was conducted after adjusting for background QTL. GWA identified associated SNPs that colocalized with 44 candidate genes. Thirty-six of these genes colocalized within 23 of the 32 QTL identified by joint linkage analysis. The candidate genes included genes predicted to be in involved programmed cell death, defense response, ubiquitination, redox homeostasis, autophagy, calcium signalling, lignin biosynthesis and cell wall modification. Twelve of the candidate genes showed significant differential expression between isogenic lines differing for the presence of Rp1-D21. Low but significant correlations between HR-related traits and several previously-measured disease resistance traits suggested that the genetic control of these traits was substantially, though not entirely, independent. This study provides the first system-wide analysis of natural variation that modulates the HR response in plants.     

New loci from New Zealand Black and New Zealand White mice on chromosomes 4 and 12 contribute to lupus-like disease in the context of BALB/c

New Zealand Black (NZB) and New Zealand White (NZW) mice are genetically predisposed to a lupus-like autoimmune syndrome. To further define the loci linked to disease traits in NZB and NZW mice in the context of the BALB/c genetic background, linkage analyses were conducted in two crosses: (NZW x BALB/c.H2(z))F(1) x NZB and (NZB x BALB/c)F(2). Novel loci linked to autoantibody production and glomerulonephritis, present in both NZB and NZW mice, were identified on proximal chromosomes 12 and 4. The chromosome 12 locus showed the strongest linkage to anti-nuclear Ab production. Additionally, a number of other novel loci linked to lupus traits derived from both the New Zealand and non-autoimmune BALB/c genomes were identified. Furthermore, we confirm the linkage of disease to a number of previously described lupus-associated loci, demonstrating that they are relatively background independent. These data provide a number of additional candidate gene regions in murine lupus, and highlight the powerful effect the non-autoimmune background strain has in influencing the genetic loci linked to disease.     

QTL analysis of white blood cell, platelet and red blood cell-related traits in an F2 intercross between Landrace and Korean native pigs

Haematological traits play important roles in disease resistance and defence functions. The objective of this study was to locate quantitative trait loci (QTL) and the associated positional candidate genes influencing haematological traits in an F₂ intercross between Landrace and Korean native pigs. Eight blood‐related traits (six erythrocyte traits, one leucocyte trait and one platelet trait) were measured in 816 F₂ progeny. All experimental animals were genotyped with 173 informative microsatellite markers located throughout the pig genome. We report that nine chromosomes harboured QTL for the baseline blood parameters: genomic regions on SSC 1, 4, 5, 6, 8, 9, 11, 13 and 17. Eight of twenty identified QTL reached genome‐wide significance. In addition, we evaluated the KIT locus, an obvious candidate gene locus affecting variation in blood‐related traits. Using dense single nucleotide polymorphism marker data on SSC 8 and the marker‐assisted association test, the strong association of the KIT locus with blood phenotypes was confirmed. In conclusion, our study identified both previously reported and novel QTL affecting baseline haematological parameters in pigs. Additionally, the positional candidate genes identified here could play an important role in elucidating the genetic architecture of haematological phenotype variation in swine and in humans.     

QTLs for murine red blood cell parameters in LG/J and SM/J F2 and advanced intercross lines

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.     

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 and candidate genes underlying genotype by environment interaction in the response of Arabidopsis thaliana to drought

Drought stress was imposed on two sets of Arabidopsis thaliana genotypes grown in sand under short‐day conditions and analysed for several shoot and root growth traits. The response to drought was assessed for quantitative trait locus (QTL) mapping in a genetically diverse set of Arabidopsis accessions using genome‐wide association (GWA) mapping, and conventional linkage analysis of a recombinant inbred line (RIL) population. Results showed significant genotype by environment interaction (G×E) for all traits in response to different watering regimes. For the RIL population, the observed G×E was reflected in 17 QTL by environment interactions (Q×E), while 17 additional QTLs were mapped not showing Q×E. GWA mapping identified 58 single nucleotide polymorphism (SNPs) associated with loci displaying Q×E and an additional 16 SNPs associated with loci not showing Q×E. Many candidate genes potentially underlying these loci were suggested. The genes for RPS3C and YLS7 were found to contain conserved amino acid differences when comparing Arabidopsis accessions with strongly contrasting drought response phenotypes, further supporting their candidacy. One of these candidate genes co‐located with a QTL mapped in the RIL population.     

Association Mapping for Fruit,Plant and Leaf Morphology Traits in Eggplant

An eggplant (Solanum melongena) association panel of 191 accessions, comprising a mixture of breeding lines, old varieties and landrace selections was SNP genotyped and phenotyped for key breeding fruit and plant traits at two locations over two seasons. A genome-wide association (GWA) analysis was performed using the mixed linear model, which takes into account both a kinship matrix and the sub-population membership of the accessions. Overall, 194 phenotype/genotype associations were uncovered, relating to 30 of the 33 measured traits. These associations involved 79 SNP loci mapping to 39 distinct chromosomal regions distributed over all 12 eggplant chromosomes. A comparison of the map positions of these SNPs with those of loci derived from conventional linkage mapping showed that GWA analysis both validated many of the known controlling loci and detected a large number of new marker/trait associations. Exploiting established syntenic relationships between eggplant chromosomes and those of tomato and pepper recognized orthologous regions in ten eggplant chromosomes harbouring genes influencing breeders’ traits.     

Genome‐wide association studies for hematological traits in swine

Improving immune capacity may increase the profitability of animal production if it enables animals to better cope with infections. Hematological traits play pivotal roles in animal immune capacity and disease resistance. Thus far, few studies have been conducted using a high‐density swine SNP chip panel to unravel the genetic mechanism of the immune capability in domestic animals. In this study, using mixed model‐based single‐locus regression analyses, we carried out genome‐wide association studies, using the Porcine SNP60 BeadChip, for immune responses in piglets for 18 hematological traits (seven leukocyte traits, seven erythrocyte traits, and four platelet traits) after being immunized with classical swine fever vaccine. After adjusting for multiple testing based on permutations, 10, 24, and 77 chromosome‐wise significant SNPs were identified for the leukocyte traits, erythrocyte traits, and platelet traits respectively, of which 10 reached genome‐wise significance level. Among the 53 SNPs for mean platelet volume, 29 are located in a linkage disequilibrium block between 32.77 and 40.59 Mb on SSC6. Four genes of interest are located within the block, providing genetic evidence that this genomic segment may be considered a candidate region relevant to the platelet traits. Other candidate genes of interest for red blood cell, hemoglobin, and red blood cell volume distribution width also have been found near the significant SNPs. Our genome‐wide association study provides a list of significant SNPs and candidate genes that offer valuable information for future dissection of molecular mechanisms regulating hematological traits.     

Confirmation and fine‐mapping of clinical mastitis and somatic cell score QTL in Nordic Holstein cattle

A genome‐wide association study of 2098 progeny‐tested Nordic Holstein bulls genotyped for 36 387 SNPs on 29 autosomes was conducted to confirm and fine‐map quantitative trait loci (QTL) for mastitis traits identified earlier using linkage analysis with sparse microsatellite markers in the same population. We used linear mixed model analysis where a polygenic genetic effect was fitted as a random effect and single SNPs were successively included as fixed effects in the model. We detected 143 SNP‐by‐trait significant associations (P < 0.0001) on 20 chromosomes affecting mastitis‐related traits. Among them, 21 SNP‐by‐trait combinations exceeded the genome‐wide significant threshold. For 12 chromosomes, both the present association study and the previous linkage study detected QTL, and of these, six were in the same chromosomal locations. Strong associations of SNPs with mastitis traits were observed on bovine autosomes 6, 13, 14 and 20. Possible candidate genes for these QTL were identified. Identification of SNPs in linkage disequilibrium with QTL will enable marker‐based selection for mastitis resistance. The candidate genes identified should be further studied to detect candidate polymorphisms underlying these QTL.     

Genome-wide association: a promising start to a long race

A recent study by Cheung et al. demonstrates how to identify expression quantitative trait loci (eQTLs) underlying gene expression phenotypes through a combination of genome-wide linkage analysis and subsequent fine mapping or by genome-wide association (GWA) analysis. This study emphasizes the complexity of human traits, highlighting the challenges faced by investigators--in particular, insufficient linkage disequilibrium between the trait and marker variant, genetic heterogeneity and correcting for multiple testing will all adversely impact the power to detect loci by association. These issues must be considered carefully if the GWA approach is to succeed in mapping complex phenotypes.     

Large-scale in silico mapping of complex quantitative traits in inbred mice

Understanding the genetic basis of common disease and disease-related quantitative traits will aid in the development of diagnostics and therapeutics. The processs of gene discovery can be sped up by rapid and effective integration of well-defined mouse genome and phenome data resources. We describe here an in silico gene-discovery strategy through genome-wide association (GWA) scans in inbred mice with a wide range of genetic variation. We identified 937 quantitative trait loci (QTLs) from a survey of 173 mouse phenotypes, which include models of human disease (atherosclerosis, cardiovascular disease, cancer and obesity) as well as behavioral, hematological, immunological, metabolic, and neurological traits. 67% of QTLs were refined into genomic regions <0.5 Mb with approximately 40-fold increase in mapping precision as compared with classical linkage analysis. This makes for more efficient identification of the genes that underlie disease. We have identified two QTL genes, Adam12 and Cdh2, as causal genetic variants for atherogenic diet-induced obesity. Our findings demonstrate that GWA analysis in mice has the potential to resolve multiple tightly linked QTLs and achieve single-gene resolution. These high-resolution QTL data can serve as a primary resource for positional cloning and gene identification in the research community.     

Mouse Genome-Wide Association Mapping Needs Linkage Analysis to Avoid False-Positive Loci

We carried out genome-wide association (GWA) studies in inbred mouse strains characterized for their lung tumor susceptibility phenotypes (spontaneous or urethane-induced) with panels of 12,959 (13K) or 138,793 (140K) single-nucleotide polymorphisms (SNPs). Above the statistical thresholds, we detected only SNP rs3681853 on Chromosome 5, two SNPs in the pulmonary adenoma susceptibility 1 (Pas1) locus, and SNP rs4174648 on Chromosome 16 for spontaneous tumor incidence, urethane-induced tumor incidence, and urethane-induced tumor multiplicity, respectively, with the 13K SNP panel, but only the Pas1 locus with the 140K SNP panel. Haplotype analysis carried out in the latter panel detected four additional loci. Loci reported in previous GWA studies failed to replicate. Genome-wide genetic linkage analysis in urethane-treated (BALB/c×C3H/He)F2, (BALB/c×SWR/J)F2, and (A/J×C3H/He)F2 mice showed that Pas1, but none of the other loci detected previously or herein by GWA, had a significant effect. The Lasc1 gene, identified by GWA as a functional element (Nat. Genet., 38:888–95, 2006), showed no genetic effects in the two independent intercross mouse populations containing both alleles, nor was it expressed in mouse normal lung or lung tumors. Our results indicate that GWA studies in mouse inbred strains can suffer a high rate of false-positive results and that such an approach should be used in conjunction with classical linkage mapping in genetic crosses.     

Genome-wide association study of porcine hematological parameters in a Large White × Minzhu F2 resource population

Hematological traits, which are important indicators of immune function in animals, have been commonly examined as biomarkers of disease and disease severity in humans and animals. Genome-wide significant quantitative trait loci (QTLs) provide important information for use in breeding programs of animals such as pigs. QTLs for hematological parameters (hematological traits) have been detected in pig chromosomes, although these are often mapped by linkage analysis to large intervals making identification of the underlying mutation problematic. Single nucleotide polymorphisms (SNPs) are the common form of genetic variation among individuals and are thought to account for the majority of inherited traits. In this study, a genome-wide association study (GWAS) was performed to detect regions of association with hematological traits in a three-generation resource population produced by intercrossing Large White boars and Minzhu sows during the period from 2007 to 2011. Illumina PorcineSNP60 BeadChip technology was used to genotype each animal and seven hematological parameters were measured (hematocrit (HCT), hemoglobin (HGB), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), mean corpuscular volume (MCV), red blood cell count (RBC) and red blood cell volume distribution width (RDW)). Data were analyzed in a three step Genome-wide Rapid Association using the Mixed Model and Regression-Genomic Control (GRAMMAR-GC) method. A total of 62 genome-wide significant and three chromosome-wide significant SNPs associated with hematological parameters were detected in this GWAS. Seven and five SNPs were associated with HCT and HGB, respectively. These SNPs were all located within the region of 34.6-36.5 Mb on SSC7. Four SNPs within the region of 43.7-47.0 Mb and fifty-five SNPs within the region of 42.2-73.8 Mb on SSC8 showed significant association with MCH and MCV, respectively. At chromosome-wide significant level, one SNP at 29.2 Mb on SSC1 and two SNPs within the region of 26.0-26.2 Mb were found to be significantly associated with RBC and RDW, respectively. Many of the SNPs were located within previously reported QTL regions and appeared to narrow down the regions compared with previously described QTL intervals. In current research, a total of seven significant SNPs were found within six candidate genes SCUBE3, KDR, TDO, IGFBP7, ADAMTS3 and AFP. In addition, the KIT gene, which has been previously reported to relate to hematological parameters, was located within the region significantly associated with MCH and MCV and could be a candidate gene. These results of this study may lead to a better understanding of the molecular mechanisms of hematological parameters in pigs.     

Novel Genes Affecting the Interaction between the Cabbage Whitefly and Arabidopsis Uncovered by Genome-Wide Association Mapping

Plants have evolved a variety of ways to defend themselves against biotic attackers. This has resulted in the presence of substantial variation in defense mechanisms among plants, even within a species. Genome-wide association (GWA) mapping is a useful tool to study the genetic architecture of traits, but has so far only had limited exploitation in studies of plant defense. Here, we study the genetic architecture of defense against the phloem-feeding insect cabbage whitefly (Aleyrodes proletella) in Arabidopsis thaliana. We determined whitefly performance, i.e. the survival and reproduction of whitefly females, on 360 worldwide selected natural accessions and subsequently performed GWA mapping using 214,051 SNPs. Substantial variation for whitefly adult survival and oviposition rate (number of eggs laid per female per day) was observed between the accessions. We identified 39 candidate SNPs for either whitefly adult survival or oviposition rate, all with relatively small effects, underpinning the complex architecture of defense traits. Among the corresponding candidate genes, i.e. genes in linkage disequilibrium (LD) with candidate SNPs, none have previously been identified as a gene playing a role in the interaction between plants and phloem-feeding insects. Whitefly performance on knock-out mutants of a number of candidate genes was significantly affected, validating the potential of GWA mapping for novel gene discovery in plant-insect interactions. Our results show that GWA analysis is a very useful tool to gain insight into the genetic architecture of plant defense against herbivorous insects, i.e. we identified and validated several genes affecting whitefly performance that have not previously been related to plant defense against herbivorous insects.     

Novel quantitative trait loci controlling development of experimental autoimmune encephalomyelitis and proportion of lymphocyte subpopulations

The B10.RIII mouse strain (H-2(r)) develops chronic experimental autoimmune encephalomyelitis (EAE) upon immunization with the myelin basic protein 89-101 peptide. EAE was induced and studied in a backcross between B10.RIII and the EAE-resistant RIIIS/J strain (H-2(r)), and a complete genome scan with microsatellite markers was performed. Five loci were significantly linked to different traits and clinical subtypes of EAE on chromosomes 1, 5, 11, 15, and 16, three of the loci having sex specificity. The quantitative trait locus on chromosome 15 partly overlapped with the Eae2 locus, previously identified in crosses between the B10.RIII and RIIIS/J mouse strains. The loci on chromosomes 11 and 16 overlapped with Eae loci identified in other mouse crosses. By analyzing the backcross animals for lymphocyte phenotypes, the proportion of B and T cells in addition to the levels of CD4(+)CD8(-) and CD4(-)CD8(+) T cells and the CD4(+)/CD8(+) ratio in spleen were linked to different loci on chromosomes 1, 2, 3, 5, 6, 11, and 15. On chromosome 16, we found significant linkage to spleen cell proliferation. Several linkages overlapped with the quantitative trait loci for disease phenotypes. The identification of subphenotypes that are linked to the same loci as disease traits could be most useful in the search for candidate genes and biological pathways involved in the pathological process.     

Association between the ABO locus and hematological traits in Korean

ABSTRACT: BACKGROUND: Recently, genomewide association studies identified a pleiotropic gene locus, ABO, as being significantly associated with hematological traits. To confirm the effects of ABO on hematological traits, we examined the link between the ABO locus and hematological traits in Korean population-based cohorts. RESULTS: Six tagging SNPs for ABO were analyzed with regard to their effects on hematological traits [white blood cell count (WBC), red blood cell count (RBC), platelet (Plat), mean corpuscular volume (MCV), and mean corpuscular haemoglobin concentration (MCHC)]. Linear regression analyses were performed, controlling for recruitment center, sex, and age as covariates. Of the 6 tagging SNPs, 3 (rs2073823, rs8176720, and rs495828) and 3 (rs2073823, rs8176717, and rs687289) were significantly associated with RBC and MCV, respectively (Bonferroni correction p-value criteria < 0.05/6 = 0.008). rs2073823 and a reported SNP (rs8176746), as well as rs495828 and a reported SNP (rs651007), showed perfect linkage disequilibrium status (r2s = 0.99). Of the remaining 3 SNPs (rs8176720, rs8176717 and rs687289), rs8176717 generated an independent signal with moderate p-value (= 0.045) when it was adjusted for by rs2073823 (the most significant SNP). We also identified a copy number variation (CNV) that was tagged by the SNP rs8176717, the minor allele of which correlated with the deletion allele of CNV. Our haplotype analysis indicated that the haplotype that contained the CNV deletion was significantly associated with MCV (beta +/- se = 0.363 +/- 0.118, p =2.09 x 10-3). CONCLUSIONS: Our findings confirm that ABO is one of the genetic factors that are associated with hematological traits in the Korean population. This result is notable, because GWASs fail to evaluate the link between a CNV and phenotype traits.     

Quantitative trait loci for porcine baseline erythroid traits at three growth ages in a White Duroc × Erhualian F<Subscript>2</Subscript> resource population

Baseline erythroid indices are increasingly involved as risk factors for common complex diseases in humans. However, little is known about the genetic architecture of baseline erythroid traits in pigs. In this study, hematocrit (Hct), hemoglobin (Hgb), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), mean corpuscular volume (MCV), red blood cell (RBC), and red cell distribution width (RDW) were measured in 1420 (day 18), 1410 (day 46), and 1033 (day 240) F(2) pigs from a White Duroc x Erhualian intercross resource population. The entire resource population was genotyped for 183 microsatellite loci across the pig genome, and the quantitative trait loci (QTL) analysis was performed for all erythroid-related traits measured with QTL Express based on a least-squares method. A total of 101 QTL, including 46 genome-wide significant QTL and 55 chromosome-wide significant QTL, regulating erythroid traits were found on all pig chromosomes (SSC) except for SSC15 and SSC18. The genome-wide significant QTL were mainly localized on SSC1, 7, 8, 10, and X. These results confirmed most of QTL previously identified in the swine. More importantly, this study detected age-specific QTL for baseline erythroid traits in pigs for the first time. Notably, the QTL for MCV and MCH on day 18 on SSC8 with small intervals of 3 and 4 cM, respectively, provided a good starting point for identifying causal genes underlying MCV and MCH in the future.     

猪2、7和8号染色体上影响血常规指标的数量性状基因座(QTL)检测

以3个品种（长白猪、大白猪、松辽黑猪）16个公猪家系共计368头仔猪组成资源群体,在猪2、7和8号染色体上共选取35个微卫星标记,采用基于线性混合模型的方差组分分析方法,对影响与猪白细胞、红细胞和血小板相关的共计18项血常规指标的数量性状基因座（quantitative trait loci,QTL）进行了检测．通过似然比检验,并以自由度为2的卡方分布作为检验统计量的分布,共发现22个在P〈5％水平下显著的QTL,其中在2号染色体上有9个,分别影响白细胞总数、中性粒细胞数、平均红细胞体积、血红蛋白含量、平均红细胞血红蛋白浓度、血小板总数、平均血小板体积、血小板分布宽度和血小板压积,在7号染色体有7个,分别影响白细胞总数、中性粒细胞数、平均红细胞血红蛋白浓度、血红蛋白含量、血小板总数、平均红细胞体积和红细胞分布宽度变异,在8号染色体上有6个,分别影响中性粒细胞百分比、淋巴细胞百分比、平均红细胞血红蛋白浓度、血小板总数、血小板压积和平均红细胞体积．为尽可能地避免由于多重检验所造成的假阳性率的升高,我们采用了控制假检出率（false discovery rate,FDR）的方法来对这22个QTL进行进一步检验,发现有14个达到FDR〈5％显著水平,其中又有9个达到FDR〈1％显著水平．