Merino sheep: a further look at quantitative trait loci for wool production

A quantitative trait loci (QTL) analysis of wool traits from experimental half-sib data of Merino sheep is presented. A total of 617 animals distributed in 10 families were genotyped for 36 microsatellite markers on four ovine chromosomes OAR1, OAR3, OAR4 and OAR11. The markers covering OAR3 and OAR11 were densely spaced, at an average distance of 2.8 and 1.2 cM, respectively. Body weight and wool traits were measured at first and second shearing. Analyses were conducted under three hypotheses: (i) a single QTL controlling a single trait (for multimarker regression models); (ii) two linked QTLs controlling a single trait (using maximum likelihood techniques) and (iii) a single QTL controlling more than one trait (also using maximum likelihood techniques). One QTL was identified for several wool traits on OAR1 (average curvature of fibre at first and second shearing, and clean wool yield measured at second shearing) and on OAR11 (weight and staple strength at first shearing, and coefficient of variation of fibre diameter at second shearing). In addition, one QTL was detected on OAR4 affecting weight measured at second shearing. The results of the single trait method and the two-QTL hypotheses showed an additional QTL segregating on OAR11 (for greasy fleece weight at first shearing and clean wool yield trait at second shearing). Pleiotropic QTLs (controlling more than one trait) were found on OAR1 (clean wool yield, average curvature of fibre, clean and greasy fleece weightand staple length, all measured at second shearing).     

Genome‐scan analysis for genetic mapping of quantitative trait loci underlying birth weight and onset of puberty in doe kids (Capra hircus)

The objective of this study was to locate quantitative trait loci (QTL) causing variation in birth weight and age of puberty of doe kids in a population of Rayini cashmere goats. Four hundred and thirty kids from five half‐sib families were genotyped for 116 microsatellite markers located on the caprine autosomes. The traits recorded were birth weight of the male and female kids, body weight at puberty, average daily gain from birth to age of puberty and age at puberty of the doe kids. QTL analysis was conducted using the least squares interval mapping approach. Linkage analysis indicated significant QTL for birth weight on Capra hircus chromosomes (CHI) 4, 5, 6, 18 and 21. Five QTL located on CHI 5, 14 and 29 were associated with age at puberty. Across‐family analysis revealed evidence for overlapping QTL affecting birth weight (78 cM), body weight at puberty (72 cM), average daily gain from birth to age of puberty (72 cM) and age at puberty (76 cM) on CHI 5 and overlapping QTL controlling body weight at puberty and age at puberty on CHI 14 at 18–19 cM. The proportion of the phenotypic variance explained by the detected QTL ranged between 7.9% and 14.4%. Confirming some of the previously reported results for birth weight and growth QTL in goats, this study identified more QTL for these traits and is the first report of QTL for onset of puberty in doe kids.     

Microsatellite mapping of quantitative trait loci affecting meat quality, stress hormones and production traits in Duroc × Large White F2 pigs

An F2 cross between Duroc and Large White pigs was carried out in order to detect quantitative trait loci (QTL) for 11 meat quality traits (L*, a* and b* Minolta coordinates and water-holding capacity (WHC) of two ham muscles, ultimate pH of two ham and one loin muscles), 13 production traits (birth weight, average daily gain during post-weaning and fattening periods, carcass fat depths at three locations, estimated lean meat content, carcass length and weights of five carcass cuts) and three stress hormone-level traits (cortisol, adrenaline and noradrenaline). Animals from the three generations of the experimental design (including 456 F2 pigs) were genotyped for 91 microsatellite markers covering all the autosomes. A total of 56 QTL were detected: 49 reached the chromosome-wide level (suggestive QTL with a maximal probability of 0.05) and seven were significant at the genome-wide level (with a probability varying from 6 × 10(-4) to 3 × 10(-3)). Twenty suggestive QTL were identified for ultimate pH, colour measurements and WHC on chromosome (SSC) 5, 6, 7, 8, 9, 11, 13, 14, 15 and 17. For production traits, 33 QTL were detected on all autosomes except SSC6, 8 and 9. Seven of these QTL, located on SSC2, 3, 10, 13, 16 and 17, exceeded the genome-wide significance threshold. Finally, three QTL were identified for levels of stress hormones: a QTL for cortisol level on SSC7 in the cortisol-binding globulin gene region, a QTL for adrenaline level on SSC10 and a QTL for noradrenaline level on SSC13. Among all the detected QTL, seven are described for the first time: a QTL for ultimate pH measurement on SSC5, two QTL affecting birth weight on SSC2 and 10, two QTL for growth rate on SSC15 (during fattening) and 17 (during post-weaning) and two QTL affecting the adrenaline and noradrenaline levels. For each QTL, only one to five of the six F1 sires were found to be heterozygous. It means that all QTL are segregating in at least one of the founder populations used in this study. These results suggest that both meat quality and production traits can be improved in purebred Duroc and Large White pigs through marker-assisted selection. It is of particular interest for meat quality traits, which are difficult to include in classical selection programmes.     

Linear and generalized linear models for the detection of QTL effects on within-subject variability

Quantitative trait loci (QTLs) may affect not only the mean of a trait but also its variability. A special aspect is the variability between multiple measured traits of genotyped animals, such as the within-litter variance of piglet birth weights. The sample variance of repeated measurements is assigned as an observation for every genotyped individual. It is shown that the conditional distribution of the non-normally distributed trait can be approximated by a gamma distribution. To detect QTL effects in the daughter design, a generalized linear model with the identity link function is applied. Suitable test statistics are constructed to test the null hypothesis H(0): No QTL with effect on the within-litter variance is segregating versus H(A): There is a QTL with effect on the variability of birth weight within litter. Furthermore, estimates of the QTL effect and the QTL position are introduced and discussed. The efficiency of the presented tests is compared with a test based on weighted regression. The error probability of the first type as well as the power of QTL detection are discussed and compared for the different tests.     

猪部分内脏器官性状和乳头数的QTL检测

对内脏器官重量性状的QTL定位研究,所见报道不多;对于猪的繁殖性状,尚需做进一步的探讨。本研究在总共214头(180头F2个体)组成的资源家系中,在猪的SSC4、SSC6、SSC7、SSC8 和 SSC13上共选取39个微卫星标记,检测了8种内脏器官的重量性状:心重 (HW)、肺重 (LW)、肝 胆重 (LGW)、脾重 (SPW)、胃重 (STW)、小肠重(SIW)、大肠重(LIW) 和肾重(KW);其他一些胴体性状:胴体长性状1(自第一颈椎,CL1)、胴体长性状2(自第一胸椎,CL2)、肋骨数(RNS)和繁殖性状乳头数(TNS)的QTL定位。结果表明,检测到3个染色体极显著水平的QTL(P≤0.01),它们是HW QTL定位在SSC6上30 cM处,RNS QTL定位在SSC7上115 cM处和TNS QTL定位在SSC7上 110 cM处;另外6个染色体显著水平的QTL(P≤0.05)是:LW(SSC13上119 cM处)、LGW(SSC6上94 cM处)、SPW(SSC8上106 cM处)、SIW(SSC 4上0 cM处)、LIW(SSC 4上170 cM 处)和TNS(SSC 6上95 cM处)。上述QTL解释的表型变异从 0.04% 到 14.06%,有些位点的 QTL 可以解释表型变异的 10%以上,如 HW 的 QTL 解释表型变异的9.52%、SIW的QTL解释表型变异的13.47%、定位在SSC6上的TNS QTL解释表型变异的14.06%,而定位在 SSC7上的TNS QTL解释表型变异的11.30%。多数内脏器官重量性状的QTL定位结果未见报道。胴体长未见显著水平的QTL,而在SSC7上定位染色体极显著水平的肋骨数QTL。     

A molecular genome scan analysis to identify chromosomal regions influencing economic traits in the pig. I. Growth and body composition

Genome scans can be employed to identify chromosomal regions and eventually genes (quantitative trait loci or QTL) that control quantitative traits of economic importance. A three-generation resource family was developed by using two Berkshire grand sires and nine Yorkshire grand dams to detect QTL for growth and body composition traits in pigs. A total of 525 F₂ progeny were produced from 65 matings. All F₂ animals were phenotyped for birth weight, 16-day weight, growth rate, carcass weight, carcass length, back fat thickness, and loin eye area. Animals were genotyped for 125 microsatellite markers covering the genome. Least squares regression interval mapping was used for QTL detection. All carcass traits were adjusted for live weight at slaughter. A total of 16 significant QTL, as determined by a permutation test, were detected at the 5% chromosome-wise level for growth traits on Chromosomes (Chrs) 1, 2, 3, 4, 6, 7, 8, 9, 11, 13, 14, and X, of which two were significant at the 5% genome-wise level and two at the 1% genome-wise level (on Chrs 1, 2, and 4). For composition traits, 20 QTL were significant at the 5% chromosome-wise level (on Chrs 1, 4, 5, 6, 7, 12, 13, 14, 18), of which one was significant at the 5% genome-wise level and three were significant at the 1% genome-wise level (on Chrs 1, 5, and 7). For several QTL the favorable allele originated from the breed with the lower trait mean. Received: 29 November 2000 / Accepted: 27 March 2001     

Quantitative trait locus analysis of a recombinant inbred line population derived from a Lycopersicon esculentum x Lycopersicon cheesmanii cross

Quantitative trait loci influencing fruit traits were identified by restriction fragment length polymorphism (RFLP) analysis in a population of recombinant inbred lines (RIL) derived from a cross of the cultivated tomato, Lycopersicon esculentum with a related wild species Lycopersicon cheesmanii. One hundred thirty-two polymorphic RFLP loci spaced throughout the tomato genome were scored for 97 F₈ RIL families. Fruit weight and soluble solids were measured in replicated trials during 1991 and 1992. Seed weight was measured in 1992. Significant (P<0.01 level) quantitative trait locus (QTL) associations of marker loci were identified for each trait. A total of 73 significant marker locus-trait associations were detected for the three traits measured. Fifty-three of these associations were for fruit weight and soluble solids, many of which involved marker loci signficantly associated with both traits. QTL with large effects on all three traits were detected on chromosome 6. Greater homozygosity at many loci in the RIL population as compared to F₂ populations and greater genomic coverage resulted in increased precision in the estimation of QTL effects, and large proportions of the total phenotypic variance were explained by marker class variation at significant marker loci for many traits. The RIL population was effective in detecting and discriminating among QTL for these traits previously identified in other investigations despite skewed segregation ratios at many marker loci. Large additive effects were measured at significant marker loci. Lower fruit weight, higher soluble solids, and lower seed weight were generally associated with RFLP alleles from theL. cheesmanii parent.     

QTL for pubertal and seasonality traits in male Père David's x red deer interspecies hybrids

The unique Pere David's (Elaphurus davidianus) x red deer (Cervus elaphus) backcross hybrid has been used to search for evidence of quantitative trait loci (QTL) for antler pubertal (date and live weight at pedicle initiation) and antler seasonality (date of antler cleaning and casting) traits in temperate species of deer. Analyses using marker information revealed evidence for a QTL for date at pedicle initiation (LOD = 3.7) and live weight at pedicle initiation (LOD = 3.1). These QTL explained 13% and 11% of the phenotypic variance in these traits, respectively.     

A genome‐wide association study of 23 agronomic traits in Chinese wheat landraces

Uncovering the genetic basis of agronomic traits in wheat landraces is important for ensuring global food security via the development of improved varieties. Here, 723 wheat landraces from 10 Chinese agro‐ecological zones were evaluated for 23 agronomic traits in six environments. All accessions could be clustered into five subgroups based on phenotypic data via discriminant function analysis, which was highly consistent with genotypic classification. A genome‐wide association study was conducted for these traits using 52 303 DArT‐seq markers to identify marker‐trait associations and candidate genes. Using both the general linear model and the mixed linear model, 149 significant markers were identified for 21 agronomic traits based on best linear unbiased prediction values. Considering the linkage disequilibrium decay distance in this study, significant markers within 10 cM were combined as a quantitative trait locus (QTL), with a total of 29 QTL identified for 15 traits. Of these, five QTL for heading date, flag leaf width, peduncle length, and thousand kernel weight had been reported previously. Twenty‐five candidate genes associated with significant markers were identified. These included the known vernalization genes VRN‐B1 and vrn‐B3 and the photoperiod response genes Ppd and PRR. Overall, this study should be helpful in elucidating the underlying genetic mechanisms of complex agronomic traits and performing marker‐assisted selection in wheat.     

Maternal genetic effects set the potential for evolution in a free-living vertebrate population

Heritable maternal effects have important consequences for the evolutionary dynamics of phenotypic traits under selection, but have only rarely been tested for or quantified in evolutionary studies. Here we estimate maternal effects on early-life traits in a feral population of Soay sheep (Ovis aries) from St Kilda, Scotland. We then partition the maternal effects into genetic and environmental components to obtain the first direct estimates of maternal genetic effects in a free-living population, and furthermore test for covariance between direct and maternal genetic effects. Using an animal model approach, direct heritabilities (h2) were low but maternal genetic effects (m2) represented a relatively large proportion of the total phenotypic variance for each trait (birth weight m2=0.119, birth date m2=0.197, natal litter size m2=0.211). A negative correlation between direct and maternal genetic effects was estimated for each trait, but was only statistically significant for natal litter size (ram= -0.714). Total heritabilities (incorporating variance from heritable maternal effects and the direct-maternal genetic covariance) were significant for birth weight and birth date but not for natal litter size. Inadequately specified models greatly overestimated additive genetic variance and hence direct h2 (by a factor of up to 6.45 in the case of birth date). We conclude that failure to model heritable maternal variance can result in over- or under-estimation of the potential for traits to respond to selection, and advocate an increased effort to explicitly measure maternal genetic effects in evolutionary studies.     

POSITIVE GENETIC CORRELATION BETWEEN PARASITE RESISTANCE AND BODY SIZE IN A FREE-LIVING UNGULATE POPULATION

Abstract Parasite resistance and body size are subject to directional natural selection in a population of feral Soay sheep (Ovis aries) on the island of St. Kilda, Scotland. Classical evolutionary theory predicts that directional selection should erode additive genetic variation and favor the maintenance of alleles that have negative pleiotropic effects on other traits associated with fitness. Contrary to these predictions, in this study we show that there is considerable additive genetic variation for both parasite resistance, measured as fecal egg count (FEC), and body size, measured as weight and hindleg length, and that there are positive genetic correlations between parasite resistance and body size in both sexes. Body size traits had higher heritabilities than parasite resistance. This was not due to low levels of additive genetic variation for parasite resistance, but was a consequence of high levels of residual variance in FEC. Measured as coefficients of variation, levels of additive genetic variation for FEC were actually higher than for weight or hindleg length. High levels of additive genetic variation for parasite resistance may be maintained by a number of mechanisms including high mutational input, balancing selection, antagonistic pleiotropy, and host‐parasite coevolution. The positive genetic correlation between parasite resistance and body size, a trait also subject to sexual selection in males, suggests that parasite resistance and growth are not traded off in Soay sheep, but rather that genetically resistant individuals also experience superior growth.     

Heterogeneity of genetic architecture of body size traits in a free‐living population

Knowledge of the underlying genetic architecture of quantitative traits could aid in understanding how they evolve. In wild populations, it is still largely unknown whether complex traits are polygenic or influenced by few loci with major effect, due to often small sample sizes and low resolution of marker panels. Here, we examine the genetic architecture of five adult body size traits in a free‐living population of Soay sheep on St Kilda using 37 037 polymorphic SNPs. Two traits (jaw and weight) show classical signs of a polygenic trait: the proportion of variance explained by a chromosome was proportional to its length, multiple chromosomes and genomic regions explained significant amounts of phenotypic variance, but no SNPs were associated with trait variance when using GWAS. In comparison, genetic variance for leg length traits (foreleg, hindleg and metacarpal) was disproportionately explained by two SNPs on chromosomes 16 (s23172.1) and 19 (s74894.1), which each explained >10% of the additive genetic variance. After controlling for environmental differences, females heterozygous for s74894.1 produced more lambs and recruits during their lifetime than females homozygous for the common allele conferring long legs. We also demonstrate that alleles conferring shorter legs have likely entered the population through a historic admixture event with the Dunface sheep. In summary, we show that different proxies for body size can have very different genetic architecture and that dense SNP helps in understanding both the mode of selection and the evolutionary history at loci underlying quantitative traits in natural populations.     

Analyses of lamb survival of Scottish Blackface sheep

Scottish Blackface lamb viability records at birth, and postnatal survival from 1 day to 14 days, from 15 days to 120 days and from 121 days to 180 days were used to determine influential factors and to estimate variance components of lamb survival traits. The binary trait viability at birth was analysed using a linear model whereas the postnatal survival traits were analysed as continuous traits using a Weibull model. The data consisted of about 15 000 survival records of lambs born from 1996 to 2005 on two farms in Scotland. The models included fixed factors that had significant effects and random direct and maternal additive genetic effects and maternal litter effects for viability at birth, and sire and maternal litter effects for the postnatal survival traits. The possible effect of maternal behaviour measured around lambing on lamb survival was investigated in separate analyses. Male lambs were found to be at a higher risk of mortality than females during all periods considered. The effect of type of birth and age of dam was more important during the preweaning period than at later ages. The postnatal hazard rate was not significantly affected by the behaviour score of the dams. The genetic merit of dams had more influence on viability at birth than the genetic merit of lambs themselves. Estimates of heritability for postnatal survival traits were in the range of 0.18 to 0.33 and were significantly greater than zero. These results indicate that lamb survival can be improved through farm management practices and genetic selection. Both animal and maternal genetic effects should be considered in breeding programmes for improving viability at birth.     

Use of trial clustering to study QTL × environment effects for grain yield and related traits in maize

A population of 300 F_3:4 lines derived from the cross between maize inbred lines F2 and F252 was evaluated for testcross value in a large range of environmental conditions (11 different locations in 2 years: 1995 and 1996) in order to study (1) the magnitude of genotype × environment and (2) the stability of quantitative trait loci (QTL) effects. Several agronomic traits were measured: dry grain yield (DGY), kernel weight, average number of kernels per plant, silking date (SD) and grain moisture at harvest. A large genotype × environment interaction was found, particularly for DGY. A hierarchical classification of trials and an additive main effects and multiplicative interaction (AMMI) model were carried out. Both methods led to the conclusion that trials could be partitioned into three groups consistent with (1) the year of experiment and (2) the water availability (irrigated vs non-irrigated) for the trials sown in 1995. QTL detection was carried out for all the traits in the different groups of trials. Between 9 and 15 QTL were detected for each trait. QTL × group and QTL × trial effects were tested and proved significant for a large proportion of QTL. QTL detection was also performed on coordinates on the first two principal components (PC) of the AMMI model. PC QTL were generally detected in areas where QTL × group and QTL × trial interactions were significant. A region located on chromosome 8 near an SD QTL seemed to play a key role in DGY stability. Our results confirm the key role of water availability and flowering earliness on grain yield stability in maize.     

Detection of QTL controlling digestive efficiency and anatomy of the digestive tract in chicken fed a wheat-based diet

Background

Improving digestive efficiency is a major goal in poultry production, to reduce production costs, make possible the use of alternative feedstuffs and decrease the volume of manure produced. Since measuring digestive efficiency is difficult, identifying molecular markers associated with genes controlling this trait would be a valuable tool for selection. Detection of QTL (quantitative trait loci) was undertaken on 820 meat-type chickens in a F2 cross between D- and D+ lines divergently selected on low or high AMEn (apparent metabolizable energy value of diet corrected to 0 nitrogen balance) measured at three weeks in animals fed a low-quality diet. Birds were measured for 13 traits characterizing digestive efficiency (AMEn, coefficients of digestive utilization of starch, lipids, proteins and dry matter (CDUS, CDUL, CDUP, CDUDM)), anatomy of the digestive tract (relative weights of the proventriculus, gizzard and intestine and proventriculus plus gizzard (RPW, RGW, RIW, RPGW), relative length and density of the intestine (RIL, ID), ratio of proventriculus and gizzard to intestine weight (PG/I); and body weight at 23 days of age. Animals were genotyped for 6000 SNPs (single nucleotide polymorphisms) distributed on 28 autosomes, the Z chromosome and one unassigned linkage group.

Results

Nine QTL for digestive efficiency traits, 11 QTL for anatomy-related traits and two QTL for body weight at 23 days of age were detected. On chromosome 20, two significant QTL at the genome level co-localized for CDUS and CDUDM, i.e. two traits that are highly correlated genetically. Moreover, on chromosome 16, chromosome-wide QTL for AMEn, CDUS, CDUDM and CDUP, on chromosomes 23 and 26, chromosome-wide QTL for CDUS, on chromosomes 16 and 26, co-localized QTL for digestive efficiency and the ratio of intestine length to body weight and on chromosome 27 a chromosome-wide QTL for CDUDM were identified.

Conclusions

This study identified several regions of the chicken genome involved in the control of digestive efficiency. Further studies are necessary to identify the underlying genes and to validate these in commercial populations and breeding environments.     

Multi-trait QTL mapping in barley using multivariate regression

Many studies of QTL locations record several different traits on the same population, but most analyses look at this information on a trait-by-trait basis. In this paper we show how the regression approach to QTL mapping of Haley & Knott (1992) may be extended to a multi-trait analysis via multivariate regression, easily programmed in statistical packages. A procedure for identifying QTL locations using forward selection and bootstrapping is proposed. The method is applied to examine the locations for QTLs for six yield characters (the number of fertile stems, the grain number of the main stem, the main stem grain weight, the single plant yield, the plot yield and the thousand grain weight) in a doubled haploid population of spring barley. Several chromosomal locations with effects on more than one trait are found. The method is also suitable for examining a single trait measured in different years or environments, and is used here to examine data on heading date, a highly heritable trait, and plot yield, a trait with moderate heritability and showing QTL-environment interactions.     

Quantitative genetics of growth and cryptic evolution of body size in an island population

While evolution occurs when selection acts on a heritable trait, empirical studies of natural systems have frequently reported phenotypic stasis under these conditions. We performed quantitative genetic analyses of weight and hindleg length in a free-living population of Soay sheep (Ovis aries) to test whether genetic constraints can explain previously reported stasis in body size despite evidence for strong positive directional selection. Genetic, maternal and environmental covariance structures were estimated across ontogeny using random regression animal models. Heritability increased with age for weight and hindleg length, though both measures of size were highly heritable across ontogeny. Genetic correlations among ages were generally strong and uniformly positive, and the covariance structures were also highly integrated across ontogeny. Consequently, we found no constraint to the evolution of larger size itself. Rather we expect size at all ages to increase in response to positive selection acting at any age. Consistent with expectation, predicted breeding values for age-specific size traits have increased over a twenty-year period, while maternal performance for offspring size has declined. Re-examination of the phenotypic data confirmed that sheep are not getting larger, but also showed that there are significant negative trends in size at all ages. The genetic evolution is therefore cryptic, with the response to selection presumably being masked at the phenotypic level by a plastic response to changing environmental conditions. Density-dependence, coupled with systematically increasing population size, may contribute to declining body size but is insufficient to completely explain it. Our results demonstrate that an increased understanding of the genetic basis of quantitative traits, and of how plasticity and microevolution can occur simultaneously, is necessary for developing predictive models of phenotypic change in nature.     

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).     

Comparison of quantitative trait loci controlling seedling characteristics at two seedling stages using rice recombinant inbred lines

A better understanding of the genetics of seedling characteristics in rice could be helpful in improving rice varieties. Zhenshan 97 and Minghui 63, the parents of Shanyou 63, an elite hybrid developed during the last decade in China, vary greatly with respect to their physiological and morphological traits at the seedling growth stage. In this study, we used a population of 240 recombinant inbred lines derived from a cross between Zhenshan 97 and Minghui 63 to identify quantitative trait loci (QTL) for seedling characteristics. All plant material was grown in hydroponic culture. Data for the following characters were collected at 30 days and 40 days post-sowing: plant height, shoot dry matter weight (SDW), maximum root length, root dry weight (RDW), total dry weight , and root-shoot ratio (the ratio of SDW to RDW). Analysis using composite interval mapping detected 16 QTL for the six traits in 30-day-old seedlings. Of these 16 QTL, Minghui 63 alleles increased trait values at only two of them. The QTL in the vicinity of R3166 on chromosome 5 simultaneously influenced PH, SDW, MRL, RDW, and TDW in the same direction. Twenty QTL were detected for the same traits in the 40-day-old seedlings. However, at this stage Minghui 63 alleles increased trait values at eight QTL. The QTL linked to R3166 also affected PH, SDW, MRL, RDW, and TDW. Only four QTL were common to the two stages. These results clearly indicate that different genes (QTL) control the same traits during different time intervals. Zhenshan 97 alleles had positive effects during the first 30 days of seedling growth, but thereafter the positive effects of Minghui 63 alleles on seedling growth gradually became more pronounced.     

Localization of quantitative trait loci for diapause and other photoperiodically regulated life history traits important in adaptation to seasonally varying environments

Seasonally changing environments at high latitudes present great challenges for the reproduction and survival of insects, and photoperiodic cues play an important role in helping them to synchronize their life cycle with prevalent and forthcoming conditions. We have mapped quantitative trait loci (QTL) responsible for the photoperiodic regulation of four life history traits, female reproductive diapause, cold tolerance, egg‐to‐eclosion development time and juvenile body weight in Drosophila montana strains from different latitudes in Canada and Finland. The F2 progeny of the cross was reared under a single photoperiod (LD cycle 16:8), which the flies from the Canadian population interpret as early summer and the flies from the Finnish population as late summer. The analysis revealed a unique QTL for diapause induction on the X chromosome and several QTL for this and the other measured traits on the 4th chromosome. Flies’ cold tolerance, egg‐to‐eclosion development time and juvenile body weight had several QTL also on the 2nd, 3rd and 5th chromosome, some of the peaks overlapping with each other. These results suggest that while the downstream output of females’ photoperiodic diapause response is partly under a different genetic control from that of the other traits in the given day length, all traits also share some QTL, possibly involving genes with pleiotropic effects and/or multiple tightly linked genes. Nonoverlapping QTL detected for some of the traits also suggest that the traits are potentially capable of independent evolution, even though this may be restricted by epistatic interactions and/or correlations and trade‐offs between the traits.