Quantitative trait loci for physical activity traits in mice.

The genomic locations and identities of the genes that regulate voluntary physical activity are presently unknown. The purpose of this study was to search for quantitative trait loci (QTL) that are linked with daily mouse running wheel distance, duration, and speed of exercise. F(2) animals (n = 310) derived from high active C57L/J and low active C3H/HeJ inbred strains were phenotyped for 21 days. After phenotyping, genotyping with a fully informative single-nucleotide polymorphism panel with an average intermarker interval of 13.7 cM was used. On all three activity indexes, sex and strain were significant factors, with the F(2) animals similar to the high active C57L/J mice in both daily exercise distance and duration of exercise. In the F(2) cohort, female mice ran significantly farther, longer, and faster than male mice. QTL analysis revealed no sex-specific QTL but at the 5% experimentwise significance level did identify one QTL for duration, one QTL for distance, and two QTL for speed. The QTL for duration (DUR13.1) and distance (DIST13.1) colocalized with the QTL for speed (SPD13.1). Each of these QTL accounted for approximately 6% of the phenotypic variance, whereas SPD9.1 (chromosome 9, 7 cM) accounted for 11.3% of the phenotypic variation. DUR13.1, DIST13.1, SPD13.1, and SPD9.1 were subsequently replicated by haplotype association mapping. The results of this study suggest a genetic basis of voluntary activity in mice and provide a foundation for future candidate gene studies.     

Quantitative trait loci for electrical seizure threshold mapped in C57BLKS/J and C57BL/10SnJ mice

We mapped the quantitative trait loci (QTL) that contribute to the robust difference in maximal electroshock seizure threshold (MEST) between C57BLKS/J (BKS) and C57BL10S/J (B10S) mice. BKS, B10S, BKS × B10S F1 and BKS × B10S F2 intercross mice were tested for MEST at 8-9 weeks of age. Results of F2 testing showed that, in this cross, MEST is a continuously distributed trait determined by polygenic inheritance. Mice from the extremes of the trait distribution were genotyped using microarray technology. MEST correlated significantly with body weight and sex; however, because of the high correlation between these factors, the QTL mapping was conditioned on sex alone. A sequential series of statistical analyses was used to map QTLs including single-point, multipoint and multilocus methods. Two QTLs reached genome-wide levels of significance based upon an empirically determined permutation threshold: chromosome 6 (LOD = 6.0 at ～69 cM) and chromosome 8 (LOD = 5.7 at ～27 cM). Two additional QTLs were retained in a multilocus regression model: chromosome 3 (LOD = 2.1 at ～68 cM) and chromosome 5 (LOD = 2.7 at ～73 cM). Together the four QTLs explain one third of the total phenotypic variance in the mapping population. Lack of overlap between the major MEST QTLs mapped here in BKS and B10S mice and those mapped previously in C57BL/6J and DBA/2J mice (strains that are closely related to BKS and B10S) suggest that BKS and B10S represent a new polygenic mouse model for investigating susceptibility to seizures.     

Independent quantitative trait loci influence ventral and dorsal hippocampal volume in recombinant inbred strains of mice

Anatomical and functional studies support segregation of the hippocampus into ventral and dorsal components along its septotemporal axis. However, it is unknown whether the development of these two components of the hippocampus is influenced by common or separate genetic factors. In this study, we used recombinant inbred strains of mice to determine whether the same or different quantitative trait loci (QTL) influence ventral and dorsal hippocampal volume. Using two sets of strains of recombinant inbred mice (BXD and AXB/BXA), we identified separate QTLs for ventral and dorsal hippocampal volume. In BXD mice, suggestive QTLs for ventral hippocampus were identified on chromosomes 2, 8 and 13, and a significant QTL for dorsal hippocampal volume was identified on chromosome 15. There was also a suggestive QTL for dorsal hippocampal volume on chromosome 13. In AXB/BXA mice, there were no significant or suggestive QTLs for ventral hippocampal volume, but a significant QTL for dorsal hippocampus was identified on chromosome 5. These findings suggest that the development of the ventral and dorsal components of the hippocampus is influenced by separate genetic loci.     

A genome scan for Loci associated with aerobic running capacity in rats

Aerobic capacity is a complex trait that defines the efficiency to use atmospheric oxygen as an electron acceptor in energy transfer. Copenhagen (COP) and DA inbred rat strains show a wide difference in a test for aerobic treadmill running and serve as contrasting genetic models for aerobic capacity. A genome scan was carried out on an F(2)(COP x DA) segregating population (n=224) to detect quantitative trait loci (QTLs) associated with aerobic running capacity. Linkage analysis revealed a significant QTL on chromosome 16 (lod score, 4.0). A suggestive linkage was found near the p-terminus of chromosome 3 (lod score, 2.2) with evidence of an interaction with another QTL on chromosome 16 (lod score, 2.9). All three QTLs showed a dominant mode of inheritance in which the presence of at least one DA allele was associated with a greater distance run. These results represent the first aerobic capacity QTLs identified in genetic models.     

Quantitative trait loci associated with blood pressure of metabolic syndrome in the progeny of NZO/HILtJ × C3H/HeJ intercrosses

In a previous study in 15 inbred mouse strains, we found highest and lowest systolic blood pressures in NZO/HILtJ mice (metabolic syndrome) and C3H/HeJ mice (common lean strain), respectively. To identify the loci involved in hypertension in metabolic syndrome, we performed quantitative trait locus (QTL) analysis for blood pressure with direction of cross as a covariate in segregating F₂ males derived from NZO/HILtJ and C3H/HeJ mice. We detected three suggestive main-effect QTLs affecting systolic and diastolic blood pressures (SBP and DBP). We analyzed the first principle component (PC1) generated from SBP and DBP to investigate blood pressure. In addition to all the suggestive QTLs (Chrs 1, 3, and 8) in SBP and DBP, one suggestive QTL on Chr 4 was found in PC1 in the main scan. Simultaneous search identified two significant epistatic locus pairs (Chrs 1 and 4, Chrs 4 and 8) for PC1. Multiple regression analysis revealed three blood pressure QTLs (Bpq10, 100 cM on Chr 1; Bpq11, 6 cM on Chr 4; Bpq12, 29 cM on Chr 8) accounting for 29.4% of blood pressure variance. These were epistatic interaction QTLs constructing a small network centered on Chr 4, suggesting the importance of genetic interaction for development of hypertension. The blood pressure QTLs on Chrs 1, 4, and 8 were detected repeatedly in multiple studies using common inbred nonobese mouse strains, implying substantial QTL independent of development of obesity and insulin resistance. These results enhance our understanding of complicated genetic factors of hypertension in metabolic diseases. Eri Nishihara, Shirng-Wern Tsaih, Chieko Tsukahara and Sarah Langley contributed equally to this work.     

Exercise Capacity and Response to Training Quantitative Trait Loci in a NZW X 129S1 Intercross and Combined Cross Analysis of Inbred Mouse Strains

Genetic factors determining exercise capacity and the magnitude of the response to exercise training are poorly understood. The aim of this study was to identify quantitative trait loci (QTL) associated with exercise training in mice. Based on marked differences in training responses in inbred NZW (-0.65 ± 1.73 min) and 129S1 (6.18 ± 3.81 min) mice, a reciprocal intercross breeding scheme was used to generate 285 F₂ mice. All F₂ mice completed an exercise performance test before and after a 4-week treadmill running program, resulting in an increase in exercise capacity of 1.54 ± 3.69 min (range = -10 to +12 min). Genome-wide linkage scans were performed for pre-training, post-training, and change in run time. For pre-training exercise time, suggestive QTL were identified on Chromosomes 5 (57.4 cM, 2.5 LOD) and 6 (47.8 cM, 2.9 LOD). A significant QTL for post-training exercise capacity was identified on Chromosome 5 (43.4 cM, 4.1 LOD) and a suggestive QTL on Chromosomes 1 (55.7 cM, 2.3 LOD) and 8 (66.1 cM, 2.2 LOD). A suggestive QTL for the change in run time was identified on Chromosome 6 (37.8 cM, 2.7 LOD). To identify shared QTL, this data set was combined with data from a previous F₂ cross between B6 and FVB strains. In the combined cross analysis, significant novel QTL for pre-training exercise time and change in exercise time were identified on Chromosome 12 (54.0 cM, 3.6 LOD) and Chromosome 6 (28.0 cM, 3.7 LOD), respectively. Collectively, these data suggest that combined cross analysis can be used to identify novel QTL and narrow the confidence interval of QTL for exercise capacity and responses to training. Furthermore, these data support the use of larger and more diverse mapping populations to identify the genetic basis for exercise capacity and responses to training.     

GBS-SNP and SSR based genetic mapping and QTL analysis for drought tolerance in upland cotton

A recombinant inbred line mapping population of intra-species upland cotton was generated from a cross between the drought-tolerant female parent (AS2) and the susceptible male parent (MCU13). A linkage map was constructed deploying 1,116 GBS-based SNPs and public domain-based 782 SSRs spanning a total genetic distance of 28,083.03 cM with an average chromosomal span length of 1,080.12 cM with inter-marker distance of 10.19 cM.A total of 19 quantitative trait loci (QTLs) were identified in nine chromosomes for field drought tolerance traits. Chromosomes 3 and 8 harbored important drought tolerant QTLs for chlorophyll stability index trait while for relative water content trait, three QTLs on chromosome 8 and one QTL each on chromosome 4, 12 were identified. One QTL on each chromosome 8, 5, and 7, and two QTLs on chromosome 15 linking to proline content were identified. For the nitrate reductase activity trait, two QTLs were identified on chromosome 3 and one on each chromosome 8, 13, and 26. To complement our QTL study, a meta-analysis was conducted along with the public domain database and resulted in a consensus map for chromosome 8. Under field drought stress, chromosome 8 harbored a drought tolerance QTL hotspot with two in-house QTLs for chlorophyll stability index (qCSI01, qCSI02) and three public domain QTLs (qLP.FDT_1, qLP.FDT_2, qCC.ST_3). Identified QTL hotspot on chromosome 8 could play a crucial role in exploring abiotic stress-associated genes/alleles for drought trait improvement.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12298-021-01041-y.     

Quantitative trait loci influencing hepatic copper in rats

Significant differences in liver copper content have been observed between rat inbred strains. To define loci controlling this trait, the offspring (n = 190) from an (LEW/OlaHsd x BC/CpbU) F(2)-intercross was genetically analyzed. From each F(2) animal, liver copper content was determined and genomic DNA was screened with polymorphic DNA markers. We found a major quantitative trait locus (QTL) for liver copper content in females on chromosome 2 and in males on chromosome 10. Both QTLs accounted for approximately 20% of the genetic variance. In addition, suggestive linkage for liver copper content was found on rat chromosomes 1, 8, 10, 12, 14, and 19. The regions on these chromosomes contain genes that are responsible for 9.0-15.5% of the genetic variance of liver copper content.     

The genetic contribution to heart rate and heart rate variability in quiescent mice

Recent studies have suggested a genetic component to heart rate (HR) and HR variability (HRV). However, a systematic examination of the genetic contribution to the variation in HR and HRV has not been performed. This study investigated the genetic contribution to HR and HRV using a wide range of inbred and recombinant inbred (RI) mouse strains. Electrocardiogram data were recorded from 30 strains of inbred mice and 29 RI strains. Significant differences in mean HR and total power (TP) HRV were identified between inbred strains and RI strains. Multiple significant differences within the strain sets in mean low-frequency (LF) and high-frequency (HF) power were also found. No statistically significant concordance was found between strain distribution patterns for HR and HRV phenotypes. Genomewide interval mapping identified a significant quantitative trait locus (QTL) for HR [LOD (likelihood of the odds) score = 3.763] on chromosome 6 [peak at 53.69 megabases (Mb); designated HR 1 (Hr1)]. Suggestive QTLs for TP were found on chromosomes 2, 4, 5, 6, and 14. A suggestive QTL for LF was found on chromosome 16; for HF, we found one significant QTL on chromosome 5 (LOD score = 3.107) [peak at 53.56 Mb; designated HRV-high-frequency 1 (Hrvhf1)] and three suggestive QTLs on chromosomes 2, 11 and 15. In conclusion, the results demonstrate a strong genetic component in the regulation of resting HR and HRV evidenced by the significant differences between strains. A lack of correlation between HR and HRV phenotypes in some inbred strains suggests that different sets of genes control the phenotypes. Furthermore, QTLs were found that will provide important insight to the genetic regulation of HR and HRV at rest.     

Quantitative trait loci linked to thalamus and cortex gray matter volumes in BXD recombinant inbred mice

To investigate whether there are separate or shared genetic influences on the development of the thalamus and cerebral cortex, we identified quantitative trait loci (QTLs) for relevant structural volumes in BXD recombinant inbred (RI) strains of mice. In 34 BXD RI strains and two parental strains (C57BL/6J and DBA/2J), we measured the volumes of the entire thalamus and cortex gray matter using point counting and Cavalieri's rule. Heritability was calculated using analysis of variance (ANOVA), and QTL analysis was carried out using WebQTL (http://www.genenetwork.org). The heritability of thalamus volume was 36%, and three suggestive QTLs for thalamus volume were identified on chromosomes 10, 11 and 16. The heritability of cortical gray matter was 43%, and four suggestive QTLs for cortex gray matter volume were identified on chromosomes 2, 8, 16 and 19. The genetic correlation between thalamus and cortex gray matter volumes was 0.64. Also, a single QTL on chromosome 16 (D16Mit100) was identified for thalamus volume, cortex gray matter volume and Morris water maze search-time preference (r=0.71). These results suggest that there are separate and shared genetic influences on the development of the thalamus and cerebral cortex.     

Genetic analysis of tongue size and taste papillae number and size in recombinant inbred strains of mice

Quantitative trait loci (QTLs) analysis has been used to examine natural variation of phenotypes in the mouse somatosensory cortex, hippocampus, cerebellum, and amygdala. QTL analysis has also been utilized to map and identify genes underlying anatomical features such as muscle, organ, and body weights. However, this methodology has not been previously applied to identification of anatomical structures related to gustatory phenotypes. In this study, we used QTL analysis to map and characterize genes underlying tongue size, papillae number, and papillae area. In a set of 43 BXD recombinant inbred (RI) mice (n = 111) and 2 parental strains (C57BL/6J and DBA/2J; n = 7), we measured tongue length, width, and weight. In a subset of 23 BXD RI mice and the parental mice, we measured filiform and fungiform papillae number and fungiform papillae area. Using QTL linkage analysis (through WebQTL), we detected 2 significant and noninteracting QTLs influencing tongue length on chromosomes 5 and 7. We also found a significant QTL on chromosome 19 underlying fungiform papillae area and a suggestive QTL on chromosome 2 linked to fungiform papillae number. From these QTLs, we identified a number of candidate genes within the QTL intervals that include SRY-box containing gene, nebulin-related anchoring protein, and actin-binding LIM protein 1. This study is an important first step in identifying genetic factors underlying tongue size, papillae size, and papillae number using QTL analysis.     

Quantitative trait loci that regulate plasma lipid concentration in hereditary obese KK and KK-Ay mice

To identify quantitative trait loci (QTLs) responsible for regulating plasma lipid concentration associated with obesity, linkage analysis was carried out on the 190 F2 progeny of a cross between C57BL/6J female and KK-Ay (Ay allele at the agouti locus congenic) male. In F2 a/a (agouti locus genotype) mice, two QTLs were identified on chromosome 1 and a QTL on chromosome 3 for total-cholesterol. A QTL for HDL-cholesterol was identified on chromosome 1 and a QTL for NEFA on chromosome 9. In F2 Ay/a mice, two QTLs for HDL-cholesterol were found on chromosome 1. Loci for other lipids with suggestive linkage were also identified. In both F2 mice, one QTL on chromosome 1 for total- and HDL-cholesterol was mapped near D1Mit150, in the vicinity of the apolipoprotein A-II (Apoa2) locus. Seven nucleotide substitutions out of 309 nucleotide apolipoprotein A-II cDNA sequences were identified between KK and C57BL/6J. The Ay allele may be an indication of the plasma lipid levels, but its influence was less apparent than in the case of weight control. The loci for lipids were not on identical chromosomes with those previously identified for obesity, suggesting that hyperlipidemia in KK does not coincidentally occur with obesity.     

A genome scan for loci affecting pork quality in a Duroc-Landrace F population

A genome scan was conducted on 370 F2 Duroc-Landrace pigs. Microsatellite markers (n = 182) were genotyped across the entire F2 population, all F1 parents and the paternal grandparents. Breed of origin of all chromosomal segments inherited in F2 progeny were predicted using GenoProb, where genotypic data, genetic maps and extended pedigrees were used as inputs. Statistical tests for quantitative trait loci (QTL) associations were conducted on 41 phenotypes with SAS using output from GenoProb for genotypic data. Fixed effects included sex and age at slaughter. For certain analyses carcass weight, RYR1 genotype and/or PRKAG3 genotype were also included as covariates. Subjective and objective measures of pork colour, marbling and tenderness were recorded, as well as measures of carcass fatness and muscularity. Test results were adjusted to a genome-wide level of significance. Five genomic regions presented significant evidence for QTL at chromosome 1 positions 6 cM (intramuscular fat) and 67 cM (Hunter L*), chromosome 2 position 62 cM (taste panel tenderness), chromosome 17 position 50 (loineye area and image analysis estimated loineye area) and X position 87 cM (carcass weight). Sixty-six suggestive associations were detected. Fourteen of these associations were within the regions with significant QTL on chromosomes 2, 17 and X, and the remaining 52 associations resided in 29 other regions on 13 different chromosomes of the porcine genome. The chromosome 2 region of 60-66 cM was associated with all measures of pork tenderness and the region on chromosome 17 (32-39 cM) was associated with both measures of intramuscular fat and loineye area. After verification, the QTL for marbling and tenderness should be useful in commercial production to improve pork quality as the population was developed from two of the three most utilized breeds of swine in the USA.     

Genetic Analysis of Ligation-Induced Neointima Formation in an F2 Intercross of C57BL/6 and FVB/N Inbred Mouse Strains

Objective

Proliferation and migration of vascular smooth muscle cells (SMCs) are central for arterial diseases including atherosclerosis and restenosis. We hypothesized that the underlying mechanisms may be modeled by carotid ligation in mice. In FVB/N inbred mice, ligation leads to abundant neointima formation with proliferating media-derived SMCs, whereas in C57BL/6 mice hardly any neointima is formed. In the present study, we aimed to identify the chromosomal location of the causative gene variants in an F2 intercross between these two mouse strains.

Methods and Results

The neointimal cross-sectional area was significantly different between FVB/N, C57BL/6 and F1 female mice 4 weeks after ligation. Carotid artery ligation and a genome scan using 800 informative SNP markers were then performed in 157 female F2 mice. Using quantitative trait loci (QTL) analysis, we identified suggestive, but no genome-wide significant, QTLs on chromosomes 7 and 12 for neointimal cross-sectional area and on chromosome 14 for media area. Further analysis of the cross revealed 4 QTLs for plasma cholesterol, which combined explained 69% of the variation among F2 mice.

Conclusions

We identified suggestive QTLs for neointima and media area after carotid ligation in an intercross of FVB/N and C57BL/6 mice, but none that reached genome-wide significance indicating a complex genetic architecture of the traits. Genome-wide significant QTLs for total cholesterol levels were identified on chromosomes 1, 3, 9, and 12.     

A dominant X-linked QTL regulating pubertal timing in mice found by whole genome scanning and modified interval-specific congenic strain analysis

Background

Pubertal timing in mammals is triggered by reactivation of the hypothalamic-pituitary-gonadal (HPG) axis and modulated by both genetic and environmental factors. Strain-dependent differences in vaginal opening among inbred mouse strains suggest that genetic background contribute significantly to the puberty timing, although the exact mechanism remains unknown.

Methodology/Principal Findings

We performed a genome-wide scanning for linkage in reciprocal crosses between two strains, C3H/HeJ (C3H) and C57BL6/J (B6), which differed significantly in the pubertal timing. Vaginal opening (VO) was used to characterize pubertal timing in female mice, and the age at VO of all female mice (two parental strains, F1 and F2 progeny) was recorded. A genome-wide search was performed in 260 phenotypically extreme F2 mice out of 464 female progeny of the F1 intercrosses to identify quantitative trait loci (QTLs) controlling this trait. A QTL significantly associated was mapped to the DXMit166 marker (15.5 cM, LOD = 3.86, p<0.01) in the reciprocal cross population (C3HB6F2). This QTL contributed 2.1 days to the timing of VO, which accounted for 32.31% of the difference between the original strains. Further study showed that the QTL was B6-dominant and explained 10.5% of variation to this trait with a power of 99.4% at an alpha level of 0.05.The location of the significant ChrX QTL found by genome scanning was then fine-mapped to a region of ∼2.5 cM between marker DXMit68 and rs29053133 by generating and phenotyping a panel of 10 modified interval-specific congenic strains (mISCSs).

Conclusions/Significance

Such findings in our study lay a foundation for positional cloning of genes regulating the timing of puberty, and also reveal the fact that chromosome X (the sex chromosome) does carry gene(s) which take part in the regulative pathway of the pubertal timing in mice.     

小鼠15号染色体上脊髓重数量性状基因座的精细定位

目的以前的研究结果表明,控制小鼠脊髓重的一个数量性状基因座(QTL)位于15号染色体D15Mit158附近,跨度约30cM。为分离和确认脊髓重相关基因,本文对该QTL区域进行了精细定位。方法以高级互交系小鼠A/J×C57BL/6J(F4)为研究对象,选择脊髓重偏向两极的个体,在D15Mit158位点附近作高密度局部基因组扫描,用Map Manager QTX19软件对脊髓重与基因型进行连锁不平衡分析。结果在15号染色体D15Mit107附近出现了一个很强的连锁峰,LRS值为17.3(P=1.8×10-4),变异解释率为27%,LOD值达到3.75,可以认定为一主效QTL。该QTL跨度范围为3.2cM。另一个提示可能具有连锁关系的QTL位点在D15Mit28附近,LRS值为7.6(P=0.02),变异解释率为13%,跨度范围为5.0cM。结论控制小鼠脊髓重的D15Mit158区域实际上含有两个QTL,其中一个主效QTL位于15号染色体上宽约3.2cM的D15Mit107位点附近;另一个可能的QTL位于宽约5.0cM的D15Mit28附近。     

Quantitative trait locus analysis of atherosclerosis in an intercross between C57BL/6 and C3H mice carrying the mutant apolipoprotein E gene

Inbred mouse strains C57BL/6J (B6) and C3H/HeJ (C3H) differ significantly in atherosclerosis susceptibility and plasma lipid levels on the apolipoprotein E-deficient (apoE-/-) background when fed a Western diet. To determine genetic factors contributing to the variations in these phenotypes, we performed quantitative trait locus (QTL) analysis using an intercross between the two strains carrying the apoE-/- gene. Atherosclerotic lesions at the aortic root and plasma lipid levels of 234 female F2 mice were analyzed after being fed a Western diet for 12 weeks. QTL analysis revealed one significant QTL, named Ath22 (42 cM, LOD 4.1), on chromosome 9 and a suggestive QTL near D11mit236 (20 cM, LOD 2.4) on chromosome 11 that influenced atherosclerotic lesion size. One significant QTL on distal chromosome 1, which accounted for major variations in plasma LDL/VLDL cholesterol and triglyceride levels, coincided with a QTL having strong effects on body weight. Plasma LDL/VLDL cholesterol or triglyceride levels of F2 mice were significantly correlated with body weight, but they were not correlated with atherosclerotic lesion sizes. These data indicate that atherosclerosis susceptibility and plasma cholesterol levels are controlled by separate genetic factors in the B6 and C3H mouse model and that genetic linkages exist between body weight and lipoprotein metabolism.     

Quantitative Trait Locus Analysis of Plasma Cholesterol and Triglyceride Levels in KK × RR F2 Mice

A previous quantitative trait locus (QTL) study on hyperlipidemia in C57BL/6J x KK-Ay/a F2 mice identified three significant cholesterol QTLs (Cq1 and Cq2 on chromosome 1, and Cq3 on chromosome 3), and a suggestive triglyceride QTL on chromosome 9. An alternative analysis of this study identified a novel cholesterol QTL on chromosome 9 (Cq4), and a significant triglyceride QTL on chromosome 9 (Tgq1). In the present study, QTL analysis was performed on KK x RR F2 mice. A significant cholesterol QTL (Cq5, lod score 5.6) was identified on chromosome 9, and a significant triglyceride QTL (Tgq2, lod score 4.7) was identified on chromosome 8. The Cq5 locus was mapped to a region similar to the Cq4 locus. On the other hand, the Tgq2 locus overlapped with the QTL region responsible for glucose intolerance (Giq1) that was identified in a previous study. The results suggest that a different combination of QTLs is involved in the trait when a different counterpart strain is used. Identification of distinct, but related traits in an identical chromosomal region will facilitate revealing the responsible gene.     

玉米SSR连锁图谱构建及叶面积的QTL定位

叶片是玉米进行光合作用的主要器官,叶面积的大小(尤其是穗三叶面积)对于玉米干物质的积累及产量形成起着至关重要的作用。研究玉米叶面积的遗传基础对于指导玉米高产育种具有理论意义。文章以两个叶面积差异显著的亲本478×武312为基础材料所构建的218个F8代的重组自交系为作图群体,构建了一张包含184个SSR标记的遗传连锁图谱,图谱总长度为2084.1cM,平均图距为11.3cM。通过两年的田间试验对玉米叶面积(穗三叶)进行了QTL定位分析。两年共定位到7个和叶面积相关的QTL位点,2006年定位到4个QTL位点;2007年定位到3个QTL位点。在第2染色体umc1542-umc1518标记区间发现一个主效QTL位点,该位点可以在两年同时检测到,两年分别解释12.5%和17.3%的表型变异。该位点能稳定地检测到且具有较大的贡献率,可能会在玉米叶面积分子标记辅助选择上有所应用。     

Quantitative genetic study of maximal electroshock seizure threshold in mice: evidence for a major seizure susceptibility locus on distal chromosome 1

We conducted a quantitative trait locus (QTL) mapping study to dissect the multifactorial nature of maximal electroshock seizure threshold (MEST) in C57BL/6 (B6) and DBA/2 (D2) mice. MEST determination involved a standard paradigm in which 8- to 12-week-old mice received one shock per day with a daily incremental increase in electrical current until a maximal seizure (tonic hindlimb extension) was induced. Mean MEST values in parental strains were separated by over five standard deviation units, with D2 mice showing lower values than B6 mice. The distribution of MEST values in B6xD2 F2 intercrossed mice spanned the entire phenotypic range defined by parental strains. Statistical mapping yielded significant evidence for QTLs on chromosomes 1, 2, 5, and 15, which together explained over 60% of the phenotypic variance in the model. The chromosome 1 QTL represents a locus of major effect, accounting for about one-third of the genetic variance. Experiments involving a congenic strain (B6.D2-Mtv7(a)/Ty) enabled more precise mapping of the chromosome 1 QTL and indicate that it lies in the genetic interval between markers D1Mit145 and D1Mit17. These results support the hypothesis that the distal portion of chromosome 1 harbors a gene(s) that has a fundamental role in regulating seizure susceptibility.