Quantitative trait loci for maternal performance for offspring survival in mice

Maternal performance refers to the effect that the environment provided by mothers has on their offspring's phenotypes, such as offspring survival and growth. Variations in maternal behavior and physiology are responsible for variations in maternal performance, which in turn affects offspring survival. In our study we found females that failed to nurture their offspring and showed abnormal maternal behaviors. The genetic architecture of maternal performance for offspring survival was investigated in 241 females of an F(2) intercross of the SM/J and LG/J inbred mouse strains. Using interval-mapping methods we found two quantitative trait loci (QTL) affecting maternal performance at D2Mit17 + 6 cM and D7Mit21 + 2 cM on chromosomes 2 and 7, respectively. In a two-way genome-wide epistasis scan we found 15 epistatic interactions involving 23 QTL distributed across all chromosomes except 12, 16, and 17. These loci form several small sets of interacting QTL, suggesting a complex set of mechanisms operating to determine maternal performance for offspring survival. Taken all together and correcting for the large number of significant factors, QTL and their interactions explain almost 35% of the phenotypic variation for maternal performance for offspring survival in this cross. This study allowed the identification of many possible candidate genes, as well as the relative size of gene effects and patterns of gene action affecting maternal performance in mice. Detailed behavior observation of mothers from later generations suggests that offspring survival in the first week is related to maternal success in building nests, grooming their pups, providing milk, and/or manifesting aggressive behavior against intruders.     

An epistatic genetic basis for physical activity traits in mice

We recently identified several (4-8) quantitative trait loci (QTL) for 3 physical activity traits (daily distance, duration, and speed voluntarily run) in an F(2) population of mice derived from an original intercross of 2 strains that exhibited large differences in activity. These QTL cumulatively explained from 11% to 34% of the variation in these traits, but this was considerably less than their total genetic variability estimated from differences among inbred strains. We therefore decided to test whether epistatic interactions might account for additional genetic variation in these traits in this same population of mice. We conducted a full genome epistasis scan for all possible interactions of QTL between each pair of 20 chromosomes. The results of this scan revealed an abundance of epistasis, with QTL throughout the genome being involved in significant interactions. Overall, epistatic effects contributed an average of 26% of the total variation among the 3 activity traits. These results suggest that epistatic interactions of genes may play as important a role in the genetic architecture of physical activity traits as single-locus effects and need to be considered in future candidate gene identification studies.     

A genome scan for quantitative trait loci in a wild population of red deer (Cervus elaphus)

Recent empirical evidence indicates that although fitness and fitness components tend to have low heritability in natural populations, they may nonetheless have relatively large components of additive genetic variance. The molecular basis of additive genetic variation has been investigated in model organisms but never in the wild. In this article we describe an attempt to map quantitative trait loci (QTL) for birth weight (a trait positively associated with overall fitness) in an unmanipulated, wild population of red deer (Cervus elaphus). Two approaches were used: interval mapping by linear regression within half-sib families and a variance components analysis of a six-generation pedigree of >350 animals. Evidence for segregating QTL was found on three linkage groups, one of which was significant at the genome-wide suggestive linkage threshold. To our knowledge this is the first time that a QTL for any trait has been mapped in a wild mammal population. It is hoped that this study will stimulate further investigations of the genetic architecture of fitness traits in the wild.     

An epistatic genetic basis for fluctuating asymmetry of tooth size and shape in mice

Although there typically is little additive genetic variation for fluctuating asymmetry (FA), or variation in nondirectional differences between left and right sides of bilateral characters, several investigators have hypothesized that FA may have an epistatic genetic basis. We tested this hypothesis by conducting a whole genome scan of FA of size and shape of the mandibular molars in house mice from an F2 intercross population generated from crossing the Large (LG/J) and Small (SM/J) inbred strains. Although no individual genes (QTLs=quantitative trait loci) on any of the 19 autosomes significantly affected FA for centroid size, and only two affected shape FA, a number of pairwise combinations of QTLs exhibited significant epistasis for FA in both molar size and shape. The QTLs involved in these interactions differed for FA in molar size versus FA in molar shape, but their epistatic contributions to the total variance was nearly the same (about 20%) for FA in both molar characters. It was noted that the genetic architecture of FA in the molar characters, consisting of little or no additive genetic variance but an abundance of epistatic genetic variance, is consistent with that of other typical fitness components such as litter size.     

Mapping quantitative trait Loci underlying fitness-related traits in a free-living sheep population

We searched for quantitative trait loci (QTL) underlying fitness-related traits in a free-living pedigree of 588 Soay sheep in which a genetic map using 251 markers with an average spacing of 15 cM had been established previously. Traits examined included birth date and weight, considered both as maternal and offspring traits, foreleg length, hindleg length, and body weight measured on animals in August and jaw length and metacarpal length measured on cleaned skeletal material. In some cases the data were split to consider different age classes separately, yielding a total of 15 traits studied. Genetic and environmental components of phenotypic variance were estimated for each trait and, for those traits showing nonzero heritability (N= 12), a QTL search was conducted by comparing a polygenic model with a model including a putative QTL. Support for a QTL at genome-wide significance was found on chromosome 11 for jaw length; suggestive QTL were found on chromosomes 2 and 5 (for birth date as a trait of the lamb), 8 (birth weight as a trait of the lamb), and 15 (adult hindleg length). We discuss the prospects for refining estimates of QTL position and effect size in the study population, and for QTL searches in free-living pedigrees in general.     

胡萝卜(Daucus carota L.)中主要胡萝卜素和番茄红素含量的QTL分析

以高胡萝卜素自交系P50006和HCM A.C.为亲本构建的F2群体为作图群体,对胡萝卜中α-胡萝卜素、α-胡萝卜素、总胡萝卜素和番茄红素含量进行QTL定位及遗传分析。结果表明,α、β-胡萝卜素、总胡萝卜素和番茄红素含量的广义遗传力分别为0.75、0.50、0.31和0.93。遗传图谱包含91个SRAP(Sequence-related amplified polymorphism)标记,分布于9个连锁群,总长度502.9cM,标记间平均距离5.5cM。除α-胡萝卜素含量外,α-胡萝卜素、总胡萝卜素和番茄红素含量分别检测到1个主效QTL,均为加性遗传效应,分别解释表型变异为12.79%、12.87%和14.61%。此外,α-胡萝卜素和番茄红素含量还分别检测到1对上位性QTL,最大遗传效应分别为显性×加性互作和显性×显性互作,分别解释表型变异为15.1%和6.5%。文章中与QTL连锁的分子标记可用于高胡萝卜素、番茄红素的种质筛选和聚合育种。     

Deciphering the genomic architecture of the stickleback brain with a novel multilocus gene‐mapping approach

Quantitative traits important to organismal function and fitness, such as brain size, are presumably controlled by many small‐effect loci. Deciphering the genetic architecture of such traits with traditional quantitative trait locus (QTL) mapping methods is challenging. Here, we investigated the genetic architecture of brain size (and the size of five different brain parts) in nine‐spined sticklebacks (Pungitius pungitius) with the aid of novel multilocus QTL‐mapping approaches based on a de‐biased LASSO method. Apart from having more statistical power to detect QTL and reduced rate of false positives than conventional QTL‐mapping approaches, the developed methods can handle large marker panels and provide estimates of genomic heritability. Single‐locus analyses of an F₂ interpopulation cross with 239 individuals and 15 198, fully informative single nucleotide polymorphisms (SNPs) uncovered 79 QTL associated with variation in stickleback brain size traits. Many of these loci were in strong linkage disequilibrium (LD) with each other, and consequently, a multilocus mapping of individual SNPs, accounting for LD structure in the data, recovered only four significant QTL. However, a multilocus mapping of SNPs grouped by linkage group (LG) identified 14 LGs (1–6 depending on the trait) that influence variation in brain traits. For instance, 17.6% of the variation in relative brain size was explainable by cumulative effects of SNPs distributed over six LGs, whereas 42% of the variation was accounted for by all 21 LGs. Hence, the results suggest that variation in stickleback brain traits is influenced by many small‐effect loci. Apart from suggesting moderately heritable (h² ≈ 0.15–0.42) multifactorial genetic architecture of brain traits, the results highlight the challenges in identifying the loci contributing to variation in quantitative traits. Nevertheless, the results demonstrate that the novel QTL‐mapping approach developed here has distinctive advantages over the traditional QTL‐mapping methods in analyses of dense marker panels.     

Mapping the epistatic network underlying murine reproductive fatpad variation

Genome-wide mapping analyses are now commonplace in many species and several networks of interacting loci have been reported. However, relatively few details regarding epistatic interactions and their contribution to complex trait variation in multicellular organisms are available and the identification of positional candidate loci for epistatic QTL (epiQTL) is hampered, especially in mammals, by the limited genetic resolution inherent in most study designs. Here we further investigate the genetic architecture of reproductive fatpad weight in mice using the F(10) generation of the LG,SM advanced intercross (AI) line. We apply multiple mapping techniques including a single-locus model, locus-specific composite interval mapping (CIM), and tests for multiple QTL per chromosome to the 12 chromosomes known to harbor single-locus QTL (slQTL) affecting obesity in this cross. We also perform a genome-wide scan for pairwise epistasis. Using this combination of approaches we detect 199 peaks spread over all 19 autosomes, which potentially contribute to trait variation including all eight original F(2) loci (Adip1-8), novel slQTL peaks on chromosomes 7 and 9, and several novel epistatic loci. Extensive epistasis is confirmed involving both slQTL confidence intervals (C.I.) as well as regions that show no significant additive or dominance effects. These results provide important new insights into mapping complex genetic architectures and the role of epistasis in complex trait variation.     

Lifetime Reproductive Success and Heritability in Nature

The observation that traits closely related to fitness ("fitness traits") have lower heritabilities than traits more distantly associated with fitness has traditionally been framed in terms of Fisher's fundamental theorem of natural selection-fitness traits are expected to have low levels of additive genetic variance due to rapid fixation of alleles conferring highest fitness. Subsequent treatments have challenged this view by pointing out that high environmental and nonadditive genetic contributions to phenotypic variation may also explain the low heritability of fitness traits. Analysis of a large data set from the collared flycatcher Ficedula albicollis confirmed a previous finding that traits closely associated with fitness tend to have lower heritability. However, analysis of coefficients of additive genetic variation (CVA) revealed that traits closely associated with fitness had higher levels of additive genetic variation (VA) than traits more distantly associated with fitness. Hence, the negative relationship between a trait's association with fitness and its heritability was not due to lower levels of VA in fitness traits but was due to their higher residual variance. However, whether the high residual variance was mainly due to higher levels of environmental variance or due to higher levels of nonadditive genetic variance remains a challenge to be addressed by further studies. Our results are consistent with earlier suggestions that fitness-related traits may have more complex genetic architecture than traits more distantly associated with fitness.     

Genetic Mapping of Quantitative Trait Loci Controlling Growth and Wood Quality Traits in Eucalyptus Grandis Using a Maternal Half-Sib Family and Rapd Markers

Quantitative trait loci (QTL) mapping of forest productivity traits was performed using an open pollinated half-sib family of Eucalyptus grandis. For volume growth, a sequential QTL mapping approach was applied using bulk segregant analysis (BSA), selective genotyping (SG) and cosegregation analysis (CSA). Despite the low heritability of this trait and the heterogeneous genetic background employed for mapping. BSA detected one putative QTL and SG two out of the three later found by CSA. The three putative QTL for volume growth were found to control 13.7% of the phenotypic variation, corresponding to an estimated 43.7% of the genetic variation. For wood specific gravity five QTL were identified controlling 24.7% of the phenotypic variation corresponding to 49% of the genetic variation. Overlapping QTL for CBH, WSG and percentage dry weight of bark were observed. A significant case of digenic epistasis was found, involving unlinked QTL for volume. Our results demonstrate the applicability of the within half-sib design for QTL mapping in forest trees and indicate the existence of major genes involved in the expression of economically important traits related to forest productivity in Eucalyptus grandis. These findings have important implications for marker-assisted tree breeding.     

Quantitative trait loci for litter size and prenatal loss in a White Duroc × Chinese Erhualian resource population

To detect quantitative trait loci (QTL) for litter size related traits, the total number of born piglets (TNB), the number of born alive piglets (NBA), the number of stillborn piglets (NSB) and the number of mummies (NM) at the first parity were recorded in 299 F₂ sows in a White Duroc × Chinese Erhualian intercross resource population. A whole genome scan was performed with 183 microsatellites distributed across 19 porcine chromosomes in the resource population, and the QTL analysis was performed with a least-squares method. A 5% genome-wide significant QTL was detected at 88 cM on pig chromosome (SSC) 15 for NBA, which also showed suggestive effect on TNB. In addition, four suggestive QTL were detected on SSC 6, 7, 8 and 15 for TNB, NBA or NSB. Two of the five QTL detected showed accordance with previous reports. No QTL was found for NM.     

Quantitative trait loci for growth and body size in the nine‐spined stickleback Pungitius pungitius L.

Body size is an ecologically important trait shown to be genetically variable both within and among different animal populations as revealed by quantitative genetic studies. However, few studies have looked into underlying genetic architecture of body size variability in the wild using genetic mapping methods. With the aid of quantitative trait loci (QTL) analyses based on 226 microsatellite markers, we mapped body size and growth rate traits in the nine‐spined stickleback (Pungitius pungitius) using an F₂‐intercross (n = 283 offspring) between size‐divergent populations. In total, 17 QTL locations were detected. The proportion of phenotypic variation explained by individual body size‐related QTL ranged from 3% to 12% and those related to growth parameters and increments from 3% to 10%. Several of the detected QTL affected either early or late growth. These results provide a solid starting point for more in depth investigations of structure and function of genomic regions involved in determination of body size in this popular model of ecological and evolutionary research.     

Identification of quantitative trait loci for cold-tolerance of photosynthesis in maize (Zea mays L.)

The effects of low growth temperature (15 degrees C) on the photosynthetic apparatus of maize were investigated in a set of 233 recombinant inbred lines by means of chlorophyll fluorescence, gas exchange measurements and analysis of photosynthetic pigments. A quantitative trait loci (QTL) analysis of five traits related to the functioning of the photosynthetic apparatus revealed a total of eight genomic regions that were significantly involved in the expression of the target traits. Four of these QTLs, located on chromosomes 1 (around 146 cM), 2 (around 138 cM), 3 (around 70 cM), and 9 (around 62 cM), were identified across several traits and the phenotypic correlation observed among those traits confirmed at the genetic level. The two QTLs on chromosomes 1 and 9 were also expressed in leaves developed at near-optimal temperature (25 degrees C) whilst the two QTLs on chromosomes 2 and 3 were specific to leaves developed at sub-optimal temperature. A QTL analysis conducted on traits related to the pigment composition of the leaves developed at 15 degrees C detected the QTL on chromosome 3 around 70 cM in 7 of the 11 traits analysed. This QTL accounted for up to 28% of the phenotypic variance of the quantum yield of electron transport at PSII in the fourth leaf after about 3 weeks at a sub-optimal temperature. The results presented here suggest that key gene(s) involved in the development of functional chloroplasts of maize at low temperature should be located on chromosome 3, close to the centromere.     

Mapping quantitative trait loci affecting chicken body size traits via genome scanning

Body size traits reflect the condition of body development, are always mentioned when a breed is described, and are also targets in breeding programmes. In chicken, there are several reports focused on body size traits, such as shank length, tibia length or bone traits. However, no study was carried out on chest width (CW), chest depth (CD), body slope length (BL) and head width (HW) traits. In this study, genome scans were conducted on an F₂ resource population (238 F₂ individuals from 15 full‐sib families derived from an intercross of the White Plymouth Rock with the Silkies Fowl) to identify quantitative trait loci (QTL) associated with CW, CD, BL and HW from 7 to 12 weeks of age. In total, 21 significant or suggestive QTL were found that affected four body size traits. Four QTL reached 1% genome‐wide significance level: at 297 cM on GGA3 (associated with CW at 9 weeks of age), between 155 and 184 cM on GGA1 (affecting BL traits at 9 and 10 weeks of age), at 22 cM on GGA2 (related with BL traits at 12 weeks of age) and at 36 cM on GGA1 (for HW trait at 8 weeks of age).     

Genetic variation in pleiotropy: differential epistasis as a source of variation in the allometric relationship between long bone lengths and body weight

Pleiotropy is an aspect of genetic architecture underlying the phenotypic covariance structure. The presence of genetic variation in pleiotropy is necessary for natural selection to shape patterns of covariation between traits. We examined the contribution of differential epistasis to variation in the intertrait relationship and the nature of this variation. Genetic variation in pleiotropy was revealed by mapping quantitative trait loci (QTLs) affecting the allometry of mouse limb and tail length relative to body weight in the mouse-inbred strain LG/J by SM/J intercross. These relationship QTLs (rQTLs) modify relationships between the traits affected by a common pleiotropic locus. We detected 11 rQTLs, mostly affecting allometry of multiple bones. We further identified epistatic interactions responsible for the observed allometric variation. Forty loci that interact epistatically with the detected rQTLs were identified. We demonstrate how these epistatic interactions differentially affect the body size variance and the covariance of traits with body size. We conclude that epistasis, by differentially affecting both the canalization and mean values of the traits of a pleiotropic domain, causes variation in the covariance structure. Variation in pleiotropy maintains evolvability of the genetic architecture, in particular the evolvability of its modular organization.     

Pleiotropic effects on mandibular morphology II: differential epistasis and genetic variation in morphological integration

The evolution of morphological modularity through the sequestration of pleiotropy to sets of functionally and developmentally related traits requires genetic variation in the relationships between traits. Genetic variation in relationships between traits can result from differential epistasis, where epistatic relationships for pairs of loci are different for different traits. This study maps relationship quantitative trait loci (QTLs), specifically QTLs that affect the relationship between individual mandibular traits and mandible length, across the genome in an F2 intercross of the LG/J and SM/J inbred mouse strains (N = 1045). We discovered 23 relationship QTLs scattered throughout the genome. All mandibular traits were involved in one or more relationship QTL. When multiple traits were affected at a relationship QTL, the traits tended to come from a developmentally restricted region of the mandible, either the muscular processes or the alveolus. About one-third of the relationship QTLs correspond to previously located trait QTLs affecting the same traits. These results comprise examples of genetic variation necessary for an evolutionary response to selection on the range of pleiotropic effects.     

Contribution of maternal effect QTL to genetic architecture of early growth in mice

Existing approaches to characterizing quantitative trait loci (QTL) utilize a paradigm explicitly focused on the direct effects of genes, where phenotypic variation among individuals is mapped onto genetic variation of those individuals. For many characters, however, the genotype of the mother via its maternal effect accounts for a considerable portion of the genetically based variation in progeny phenotypes. Thus the focus on direct effect QTL may result in an insufficient or misleading characterization of genetic architecture due to the omission of the potentially important source of genetic variance contributed by maternal effects. We analyze the relative contribution of direct and maternal effect (ME) QTL to early growth in mice using a three-generation intercross of the Small (SM/J) and Large (LG/J) inbred mouse lineages. Using interval mapping and composite interval mapping, direct effect (DE) QTL for early growth (change in body mass during the interval from week 1 to 2) were detected in the F(2) generation of the intercross (n = 510), where no maternal genetic effect variance is present (all individuals are progeny of genetically identical F(1) mothers). ME QTL were detected by treating the phenotypes of cross-fostered F(3) pups as a characteristic of their nurse-dam (n = 168 dams with cross-fostered progeny). Five DE QTL, significant at a chromosome wide level (alpha = 0.05), were detected, with two significant at a genome wide level. FourME QTL significant at the chromosome wide level were detected, with three significant at the genome wide level. A model containing only DE QTL accounted for 11.8% of phenotypic variance, while a model containing only ME QTL accounted for 31.5% of the among litter variance in growth. There was no evidence for pleiotropy of DE and ME loci since there was no overlap between loci detected in these two analyses. Epistasis between all pairs of loci was analyzed for both DEs and MEs. Ten pairs of loci showed significant epistasis for MEs (alpha = 0.05 corrected for multiple comparisons) while four pairs showed significant epistasis for DEs on early growth.     

A genome‐wide linkage analysis for reproductive traits in F2 Large White × Meishan cross gilts

Female reproductive performance traits in pigs have low heritabilities thus limiting improvement through traditional selective breeding programmes. However, there is substantial genetic variation found between pig breeds with the Chinese Meishan being one of the most prolific pig breeds known. In this study, three cohorts of Large White × Meishan F₂ cross‐bred pigs were analysed to identify quantitative trait loci (QTL) with effects on reproductive traits, including ovulation rate, teat number, litter size, total born alive and prenatal survival. A total of 307 individuals were genotyped for 174 genetic markers across the genome. The genome‐wide analysis of the trait‐recorded F₂ gilts in their first parity/litter revealed one QTL for teat number significant at the genome level and a total of 12 QTL, which are significant at the chromosome‐wide level, for: litter size (three QTL), total born alive (two QTL), ovulation rate (four QTL), prenatal survival (one QTL) and teat number (two QTL). Further support for eight of these QTL is provided by results from other studies. Four of these 12 QTL were mapped for the first time in this study: on SSC15 for ovulation rate and on SSC18 for teat number, ovulation rate and litter size.     

ON THE LOW HERITABILITY OF LIFE-HISTORY TRAITS

Life-history traits such as longevity and fecundity often show low heritability. This is usually interpreted in terms of Fisher's fundamental theorem to mean that populations are near evolutionary equilibrium and genetic variance in total fitness is low. We develop the causal relationship between metric traits and life-history traits to show that a life-history trait is expected to have a low heritability whether or not the population is at equilibrium. This is because it is subject to all the environmental variation in the metric traits that affect it plus additional environmental variation. There is no simple prediction regarding levels of additive genetic variance in life-history traits, which may be high at equilibrium. Several other patterns in the inheritance of life-history traits are readily predicted from the causal model. These include the strength of genetic correlations between life-history traits, levels of nonadditive genetic variance, and the inevitability of genotype-environment interaction.     

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。