Heterosis of Quantitative Trait Loci Affecting Lifespan in Drosophila melanogaster

Knowledge of genes responsible for aging and death is a prerequisite for determining the relative contributions of the different evolutionary factors responsible for the limited duration of life. Polymorphism of these genes probably accounts for the variation in lifespan. Previously, quantitative trait loci (QTLs) controlling this variation were mapped with the use of 98 recombinant inbred (RI) lines originating from two parental isogenicDrosophila melanogaster stocks. In each RI line, lifespan was measured for 25 males and 25 females, and alleles were established for 93 marker genes segregating between the parental lines. Significant correlation between marker segregation and lifespan was revealed for several chromosome regions. The lifespan genes had sex-specific effects and late age onset. In the present work, the effects of the QTLs were compared for homozygous and heterozygous flies. In Six out of the eight detected QTLs alleles that decreased lifespan were recessive. Heterosis was observed for a of QTL at 33E–38A. Thus, heterosis might contribute to maintaining variation in lifespan in natural populations.     

水稻F2不育和抽穗期QTL分析

对台中65（粳稻）/Bhadua（籼稻）杂交F2代群体构建了RFLP连锁图谱,含94个分布较为均匀的标记。对F2小穗不育性状进行单点分析和区间分析的结果基本一致：有两个F2小穗不育QTL座位分别位于染色体1的XNpb113～XNpb346之间和染色体8的G187～XNpb397之间,而且该两个QTL均为新检测出的座位;检测出5个抽穗期TQL,其中3个座位在单点分析和区间分析中的结果一致,分别位于染色体1的XNpb113～XNpb346,染色体4的C891～C335,染色体的8的C166～C1121,另外,染色体6的XNpb27为单点分析结果,染色体10的R716～C405为区间分析结果。由于染色体1上的F2不育QTL和抽穗期QTL重叠,该QTL座位是由于遗传效应所至还是由于环境因素（迟抽穗）所至有待构建近等基因系进一步研究。;位于染色体1和10上的抽穗期QTL座位为新检测的座位。对新检测的F2不育和抽穗期QTL座位正在建立相应的近等基因系以精确定位和克隆上述基因。     

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．     

Identifying Quantitative Trait Loci Affecting Resistance to Congenital Hypothyroidism in 129+Ter/SvJcl Strain Mice

Tyrosylprotein sulfotransferase 2 (TPST2) is one of the enzymes responsible for tyrosine O-sulfation and catalyzes the sulfation of the specific tyrosine residue of thyroid stimulating hormone receptor (TSHR). Since this modification is indispensable for the activation of TSH signaling, a non-functional TPST2 mutation (Tpst2^grt) in DW/J-grt mice leads to congenital hypothyroidism (CH) characterized by severe thyroid hypoplasia and dwarfism related to TSH hyporesponsiveness. Previous studies indicated that the genetic background of the 129^+Ter/SvJcl (129) mouse strain ameliorates Tpst2^grt-induced CH. To identify loci responsible for CH resistance in 129 mice, we performed quantitative trait locus (QTL) analysis using backcross progenies from susceptible DW/J and resistant 129 mice. We used the first principal component calculated from body weights at 5, 8 and 10 weeks as an indicator of CH, and QTL analysis mapped a major QTL showing a highly significant linkage to the distal portion of chromosome (Chr) 2; between D2Mit62 and D2Mit304, particularly close to D2Mit255. In addition, two male-specific QTLs showing statistically suggestive linkage were also detected on Chrs 4 and 18, respectively. All QTL alleles derived from the 129 strain increased resistance to growth retardation. There was also a positive correlation between recovery from thyroid hypoplasia and the presence of the 129 allele at D2Mit255 in male progenies. These results suggested that the major QTL on Chr 2 is involved in thyroid development. Moreover, since DW/J congenic strain mice carrying both a Tpst2^grt mutation and 129 alleles in the major QTL show resistance to dwarfism and thyroid hypoplasia, we confirmed the presence of the resistant gene in this region, and that it is involved in thyroid development. Further genetical analysis should lead to identification of genes for CH tolerance and, from a better understanding of thyroid organogenesis and function, the subsequent development of new treatments for thyroid disorders.     

水稻幼苗活力性状的低温反应数量性状基因座检测

以籼粳交“密阳23/吉冷1号”的F2：3代200个家系作为作图群体,在12℃冷水胁迫下,进行苗高、苗鲜重和苗干重等水稻幼苗活力性状的低温反应鉴定,并利用由SSR标记构建的分子连锁图谱为基础,对冷水胁迫下苗高、苗鲜重和苗干重以及它们的低温反应指数进行了数量性状基因座（QTLs）检测。研究结果表明,低温胁迫下上述幼苗活力性状在F3家系群中均表现为接近正态的连续分布,表现为由多基因控制的数量性状;在第1、2、7、8和12染色体上,检测到与幼苗活力性状的低温反应相关的QTL共12个,对表型变异的贡献率范围为5．2％-17．9％,其中位于第2染色体RM262-RM263区间和第12染色体RM270-RM17区间的与低温下苗高相关的qCSH2和qCSH12,以及位于第12染色体RM19-RM270区间和第1染色体RM129-RM9区间的分别控制低温下苗干重及其低温反应指数的qSDW12和qCSDW1对表型变异的贡献率较大,分别为16．6％、17．9％、15．9％和16．2％。其增效等位基因均来自吉冷1号,前两者均表现为加性效应,后两者分别表现为显性和超显性。     

Identification of Quantitative Trait Loci Controlling High Calcium Response in Arabidopsis thaliana

Natural variation for primary root growth response to high Ca stress in Arabidopsis thaliana was studied by screening a series of accessions (ecotypes) under high Calcium (40 mM CaCl₂ ) conditions. The genetic basis of this variation was further investigated by QTL analysis using recombinant inbred lines from Landsberg erecta (Ler)×Cape Verde Islands (Cvi) cross. Four QTLs were identified in chromosome 1, 2 and 5,and named response to high Calcium (RHCA) 1–4. The three QTLs (RHCA1, RHCA2 and RHCA4) were further confirmed by analysis of near isogenic lines harboring Cvi introgression fragments in Ler background. Real-time PCR analysis showed that several genes associated with high Ca response including SMT1 and XHT25 have changed expression pattern between Ler and near isogenic lines. These results were useful for detecting molecular mechanisms of plants for high Ca adaption.     

雄性不交换条件下F2群体区间标记——QTL定位的相关方法（英文）

提出了雄性不交换条件下F2群体区间标记定位QTL的相关方法,并且对其适用的条件进行了讨论,通过对分子区间标记进行赋值,计算在无交叉干涉条件下分子标记与表型值的简单相关系数,并在此基础上进行连锁检验,在特定条件下可以估计数量性状座位（QTL）与分子标记座位间的连锁值。     

雄性不交换条件下F2群体高密度分子区间标记QTL的精确作图

提出雄性不交换条件下F2群体间标记定位QTL的相关方法，研究高密度分子标记存在强烈交叉干涉时，QTL的精确定位方法。     

Determination of Quantitative Trait Loci (QTL) for Early Maturation in Rainbow Trout (<Emphasis Type="Italic">Oncorhynchus mykiss</Emphasis>)

To identify quantitative trait loci (QTL) influencing early maturation (EM) in rainbow trout (Oncorhynchus mykiss), a genome scan was performed using 100 microsatellite loci across 29 linkage groups. Six inter-strain paternal half-sib families using three inter-strain F(1) brothers (approximately 50 progeny in each family) derived from two strains that differ in the propensity for EM were used in the study. Alleles derived from both parental sources were observed to contribute to the expression of EM in the progeny of the brothers. Four genome-wide significant QTL regions (i.e., RT-8, -17, -24, and -30) were observed. EM QTL detected on RT-8 and -24 demonstrated significant and suggestive QTL effects in both male and female progeny. Furthermore, within both male and female full-sib groupings, QTL on RT-8 and -24 were detected in two or more of the five parents used. Significant genome-wide and several strong chromosome-wide QTL for EM localized to different regions in males and females, suggesting some sex-specific control. Namely, QTL detected on RT-13, -15, -21, and -30 were associated with EM only in females, and those on RT-3, -17, and -19 were associated with EM only in males. Within the QTL regions identified, a comparison of syntenic EST markers from the rainbow trout linkage map with the zebrafish (Danio rerio) genome identified several putative candidate genes that may influence EM.     

玉米雌雄开花间隔天数、结穗率与产量的数量性状位点（QTL）分析

采用SSR标记连锁图谱和复合区间作图法在山西灌溉和干旱胁迫条件下,对玉米(Zea mays L.)自交系黄早四×掖107组合的F_3群体雌雄开花间隔天数(ASI)、结穗率和籽粒产量进行了数量性状位点(QTL)定位及基因效应分析。结果表明,在两种水分处理下,ASI、结穗率与籽粒产量的相关性均达到显著水平(P<0.05)。在灌溉和干旱胁迫卜,分别检测到3个和2个控制ASI的QTL,位于第1、2、3和第2、5染色体上。在灌溉条件下,在第3和第6染色体上各检测到1个控制结穗率的QTL,基因作用方式呈加性或部分显性,可解释19.9％的表型变异;在干旱条件下,在第3、7、10染色体上共检测到4个控制结穗率的QTL,基因作用方式为显性或部分显性,可解释60.4％的表型变异。在灌溉和干旱胁迫下,控制产量的QTL分别定位在第3、6、7和第1、2、4、8染色体上,基因作用方式均以加性或部分显性为主,可解释的表型变异为7.3％～22.0％。在干旱条件下,借助连锁分子标记和基因效应分析,可构建包含ASI、结穗率和产量QTL的选择指数,用于分子标记辅助育种。     

玉米雌雄开花间隔天数、结穗率与产量的数量性状位点(QTL)分析

采用SSR标记连锁图谱和复合区间作图法在山西灌溉和干旱胁迫条件下,对玉米(Zea mays L.)自交系黄早四×掖107组合的F3群体雌雄开花间隔天数(ASI)、结穗率和籽粒产量进行了数量性状位点(QTL)定位及基因效应分析.结果表明,在两种水分处理下,ASI、结穗率与籽粒产量的相关性均达到显著水平(P＜0.05).在灌溉和干旱胁迫下,分别检测到3个和2个控制ASI的QTL,位于第1、2、3和第2、5染色体上.在灌溉条件下,在第3和第6染色体上各检测到1个控制结穗率的QTL,基因作用方式呈加性或部分显性,可解释19.9%的表型变异;在干旱条件下,在第3、 7、10染色体上共检测到4个控制结穗率的QTL,基因作用方式为显性或部分显性,可解释60.4%的表型变异.在灌溉和干旱胁迫下,控制产量的QTL分别定位在第3、6、7和第1、2、4、8染色体上,基因作用方式均以加性或部分显性为主,可解释的表型变异为7.3%～22.0%.在干旱条件下,借助连锁分子标记和基因效应分析,可构建包含ASI、结穗率和产量QTL的选择指数,用于分子标记辅助育种.     

Phenotypic Integration Without Modularity: Testing Hypotheses About the Distribution of Pleiotropic Quantitative Trait Loci in a Continuous Space

Theories of phenotypic integration have relied heavily on the concept of modularity in order to model the ways in which traits in an organism correlate and covary. Recent investigations suggest that, while some functional and developmental processes may be morphologically and ontogenetically localized, and thus modular in a developmental sense, there is a great deal of overlap among these influences on patterns of integration in the adult form. This can result in blurry boundaries between hypothesized modules constructed to test hypotheses about phenotypic integration. This investigation tests hypotheses about the contribution of pleiotropic quantitative trait loci (QTL) to phenotypic integration in the mouse mandible without using a priori categorical hypotheses about which traits constitute a module. We ask two main questions: (1) Are the effects of pleiotropic QTL localized to highly correlated traits or more spread out among traits than one might expect by chance? (2) Does the pattern of trait influence when all pleiotropic QTL are considered together deviate from what we might expect if QTL affect traits without regard for the correlations among traits? We find that a large proportion of pleiotropic QTL affect traits that are more highly correlated than we expect by chance with the remainder having effects that are distributed as if by chance. Furthermore, the overall distribution of the effects of pleiotropic QTL differs significantly from the null distribution of no association between pleiotropic effects on traits and correlations among traits. The main modular hypothesis used by earlier studies often does not predict the distribution of sets of traits sharing a common QTL. These results suggest that there is a clear tendency for pleiotropic effects of QTL to be localized but that the localization may be best thought of as occurring in a continuous space rather being clustered in discrete modules.     

Fine‐mapping of Obesity‐related Quantitative Trait Loci in an F9/10 Advanced Intercross Line

Obesity develops in response to a combination of environmental effects and multiple genes of small effect. Although there has been significant progress in characterizing genes in many pathways contributing to metabolic disease, knowledge about the relationships of these genes to each other and their joint effects upon obesity lags behind. The LG,SM advanced intercross line (AIL) model of obesity has been used to characterize over 70 loci involved in fatpad weight, body weight, and organ weights. Each of these quantitative trait loci (QTLs) encompasses large regions of the genome and require fine‐mapping to isolate causative sequence changes and possible mechanisms of action as indicated by the genetic architecture. In this study we fine‐map QTLs first identified in the F₂ and F_2/3 populations in the combined F_9/10 advanced intercross generations. We observed significantly narrowed QTL confidence regions, identified many single QTL that resolve into multiple QTL peaks, and identified new QTLs that may have been previously masked due to opposite gene effects at closely linked loci. We also present further characterization of the pleiotropic and epistatic interactions underlying these obesity‐related traits.     

A Model Selection Approach for the Identification of Quantitative Trait Loci in Experimental Crosses, Allowing Epistasis

The identification of quantitative trait loci (QTL) and their interactions is a crucial step toward the discovery of genes responsible for variation in experimental crosses. The problem is best viewed as one of model selection, and the most important aspect of the problem is the comparison of models of different sizes. We present a penalized likelihood approach, with penalties on QTL and pairwise interactions chosen to control false positive rates. This extends the work of Broman and Speed to allow for pairwise interactions among QTL. A conservative version of our penalized LOD score provides strict control over the rate of extraneous QTL and interactions; a more liberal criterion is more lenient on interactions but seeks to maintain control over the rate of inclusion of false loci. The key advance is that one needs only to specify a target false positive rate rather than a prior on the number of QTL and interactions. We illustrate the use of our model selection criteria as exploratory tools; simulation studies demonstrate reasonable power to detect QTL. Our liberal criterion is comparable in power to two Bayesian approaches.     

水稻条纹叶枯病抗性位点的检测和效应分析

利用111个家系组成的热研2号(Oryza sativa subsp. japonica ‘Reyan2’)/ Mi lyang23(Oryza sativa subsp. indica ‘Mi lyang23’)重组自交系(recombinant inbred l ines, RIL)群体(F7), 采用重病区田间自然接种方法, 以病情指数作为条纹叶枯病的表型值, 鉴定了2个亲本及111个RIL家系对条纹叶枯病的抗性。使用QTL Cartographer 软件复合区间作图法, 对水稻(Oryza a sativa)条纹叶枯病抗性基因进行了QTL分析。结果检测到2个抗水稻条纹叶枯病的QTL, 分别位于第2和第11染色体上, 其中第11染色体上的QTL贡献率为19.58%, 表明这是一个主效的QTL, 该QTL及其附近的分子标记, 可以用于水稻条纹叶枯病抗性分子标记辅助育种。     

水稻条纹叶枯病抗性位点的检测和效应分析

利用111个家系组成的热研2号（Oryza sativa subsp．japonica‘Reyan2’）／Milyang23（Oryza sativa subsp．indica‘Milyang23’）重组自交系（recombinant inbred lines,RIL）群体（F7）,采用重病区田间自然接种方法,以病情指数作为条纹叶枯病的表型值,鉴定了2个亲本及111个RIL家系对条纹叶枯病的抗性。使用QTL Cartographer软件复合区间作图法,对水稻（Oryza sativa）条纹叶枯病抗性基因进行了QTL分析。结果检测到2个抗水稻条纹叶枯病的QTL,分别位于第2和第11染色体上,其中第11染色体上的QTL贡献率为19．58％,表明这是一个主效的QTL,该QTL及其附近的分子标记,可以用于水稻条纹叶枯病抗性分子标记辅助育种。     

Genome-wide mapping of Quantitative Trait Loci for fatness,fat cell characteristics and fat metabolism in three porcine F2 crosses

Background

QTL affecting fat deposition related performance traits have been considered in several studies and mapped on numerous porcine chromosomes. However, activity of specific enzymes, protein content and cell structure in fat tissue probably depend on a smaller number of genes than traits related to fat content in carcass. Thus, in this work traits related to metabolic and cytological features of back fat tissue and fat related performance traits were investigated in a genome-wide QTL analysis. QTL similarities and differences were examined between three F₂ crosses, and between male and female animals.

Methods

A total of 966 F₂ animals originating from crosses between Meishan (M), Pietrain (P) and European wild boar (W) were analysed for traits related to fat performance (11), enzymatic activity (9) and number and volume of fat cells (20). Per cross, 216 (M × P), 169 (W × P) and 195 (W × M) genome-wide distributed marker loci were genotyped. QTL mapping was performed separately for each cross in steps of 1 cM and steps were reduced when the distance between loci was shorter. The additive and dominant components of QTL positions were detected stepwise by using a multiple position model.

Results

A total of 147 genome-wide significant QTL (76 at P < 0.05 and 71 at P < 0.01) were detected for the three crosses. Most of the QTL were identified on SSC1 (between 76-78 and 87-90 cM), SSC7 (predominantly in the MHC region) and SSCX (in the vicinity of the gene CAPN6). Additional genome-wide significant QTL were found on SSC8, 12, 13, 14, 16, and 18. In many cases, the QTL are mainly additive and differ between F₂ crosses. Many of the QTL profiles possess multiple peaks especially in regions with a high marker density. Sex specific analyses, performed for example on SSC6, SSC7 and SSCX, show that for some traits the positions differ between male and female animals. For the selected traits, the additive and dominant components that were analysed for QTL positions on different chromosomes, explain in combination up to 23% of the total trait variance.

Conclusions

Our results reveal specific and partly new QTL positions across genetically diverse pig crosses. For some of the traits associated with specific enzymes, protein content and cell structure in fat tissue, it is the first time that they are included in a QTL analysis. They provide large-scale information to analyse causative genes and useful data for the pig industry.