Epistasis affecting litter size in mice

Litter size is an important reproductive trait as it makes a major contribution to fitness. Generally, traits closely related to fitness show low heritability perhaps because of the corrosive effects of directional natural selection on the additive genetic variance. Nonetheless, low heritability does not imply, necessarily, a complete absence of genetic variation because genetic interactions (epistasis and dominance) contribute to variation in traits displaying strong heterosis in crosses, such as litter size. In our study, we investigated the genetic architecture of litter size in 166 females from an F2 intercross of the SM/J and LG/J inbred mouse strains. Litter size had a low heritability (h2 = 12%) and a low repeatability (r = 33%). Using interval-mapping methods, we located two quantitative trait loci (QTL) affecting litter size at locations D7Mit21 + 0 cM and D12Mit6 + 8 cM, on chromosomes 7 and 12 respectively. These QTL accounted for 12.6% of the variance in litter size. In a two-way genome-wide epistasis scan we found eight QTL interacting epistatically involving chromosomes 2, 4, 5, 11, 14, 15 and 18. Taken together, the QTL and their interactions explain nearly 49% (39.5% adjusted multiple r2) of the phenotypic variation for litter size in this cross, an increase of 36% over the direct effects of the QTL. This indicates the importance of epistasis as a component of the genetic architecture of litter size and fitness in our intercross population.     

Identification of quantitative trait loci that regulate obesity and serum lipid levels in MRL/MpJ x SJL/J inbred mice

The total body fat mass and serum concentration of total cholesterol, HDL cholesterol, and triglyceride (TG) differ between standard diet-fed female inbred mouse strains MRL/MpJ (MRL) and SJL/J (SJL) by 38-120% (P < 0.01). To investigate genetic regulation of obesity and serum lipid levels, we performed a genome-wide linkage analysis in 621 MRLx SJL F2 female mice. Fat mass was affected by two significant loci, D11Mit36 [43.7 cM, logarithm of the odds ratio (LOD) 11.2] and D16Mit51 (50.3 cM, LOD 3.9), and one suggestive locus at D7Mit44 (50 cM, LOD 2.4). TG levels were affected by two novel loci at D1Mit43 (76 cM, LOD 3.8) and D12Mit201 (26 cM, LOD 4.1), and two suggestive loci on chromosomes 5 and 17. HDL and cholesterol concentrations were influenced by significant loci on chromosomes 1, 3, 5, 7, and 17 that were in the regions identified earlier for other strains of mice, except for a suggestive locus on chromosome 14 that was specific to the MRL x SJL cross. In summary, linkage analysis in MRL x SJL F2 mice disclosed novel loci affecting TG, HDL, and fat mass, a measure of obesity. Knowledge of the genes in these quantitative trait loci will enhance our understanding of obesity and lipid metabolism.     

Mapping quantitative trait Loci interactions from the maternal and offspring genomes

The expression of most developmental or behavioral traits involves complex interactions between quantitative trait loci (QTL) from the maternal and offspring genomes. The maternal-offspring interactions play a pivotal role in shaping the direction and rate of evolution in terms of their substantial contribution to quantitative genetic (co)variation. To study the genetics and evolution of maternal-offspring interactions, a unifying statistical framework that embraces both the direct and indirect genetic effects of maternal and offspring QTL on any complex trait is developed. This model is derived for a simple backcross design within the maximum-likelihood context, implemented with the EM algorithm. Results from extensive simulations suggest that this model can provide reasonable estimation of additive and dominant effects of the QTL at different generations and their interaction effects derived from the maternal and offspring genomes. Although our model is framed to characterize the actions and interactions of maternal and offspring QTL affecting offspring traits, the idea can be readily extended to decipher the genetic machinery of maternal traits, such as maternal care. Our model provides a powerful means for studying the evolutionary significance of indirect genetic effects in any sexually reproductive organisms.     

Genetic analysis of alcohol intake in recombinant inbred and congenic strains derived from A/J and C57BL/6J progenitors

The objective of the present study was to map quantitative trait loci (QTL) for alcohol intake using A × B/B × A recombinant inbred (RI) and AcB/BcA recombinant congenic (RC) strains of mice that were independently derived from the A/J and C57BL/6J progenitors. Mice were screened for levels of alcohol consumption with four days of forced exposure to alcohol, followed by three weeks of free choice between water and a 10% alcohol solution. Alcohol consumption data previously collected for 27 A × B/B × A RI strains were reanalyzed using a larger marker set and composite interval mapping. The reanalysis found markers on Chromosome 2 (D2Mit74, 107 cM) (males and females) and on Chromosome 11 (Pmv22, 8 cM) (females only) that exceeded the threshold for significant loci, and found suggestive loci (in males) on Chromosomes 10 (D10 Mit126, 21 cM), 12 (D12Mit37, 1 cM), 15 (Pdgfb, 46.8 cM), and 16 (D16Mit125, 29 cM). An additional suggestive locus was identified in female RI mice on Chromosome 11 (D11Mit120, 47.5 cM). Composite interval mapping (CIM) analysis indicated that there was a significant association between loci at Pdgfb and D2Mit74 in both males and females. Analysis of the AcB/BcA RC strains identified 11 QTL on Chromosomes 2, 3, 5,6, 7, 8, 9, 10, 12, 13, and 15. QTL on Chromosomes 7, 10, 12, and 15 were identified in both the A × B/B × A RI and AcB/BcA RC strains of mice. Additional QTLs identified on Chromosomes 2, 3, 7, 11, and 15 overlap with those previously identified in the literature using strains of mice with a C57BL/6J progenitor.     

Maternal genotype affects adult offspring lipid, obesity, and diabetes phenotypes in LGXSM recombinant inbred strains

Maternal effects on offspring phenotypes occur because mothers in many species provide an environment for their developing young. Although these factors are correctly "environmental" with respect to the offspring genome, their variance may have both a genetic and an environmental basis in the maternal generation. Here, reciprocal crosses between C57BL/6J and 10 LGXSM recombinant inbred (RI) strains were performed, and litters were divided at weaning into high-fat and low-fat dietary treatments. Differences between reciprocal litters were used to measure genetic maternal effects on offspring phenotypes. Nearly all traits, including weekly body weights and adult blood serum traits, show effects indicative of genetic variation in maternal effects across RI strains, allowing the quantitative trait loci involved to be mapped. Although much of the literature on maternal effects relates to early life traits, we detect strong and significant maternal effects on traits measured at adulthood (as much as 10% of the trait variance at 17 or more weeks after weaning). We also found an interaction affecting adult phenotype between the effects of maternal care between RI strain mothers and C57BL/6J mothers and a later environmental factor (dietary fat intake) for some age-specific weights.     

Fine-mapping of a marbling trait to a 2.9-cM region on bovine chromosome 7 in Japanese Black cattle

To locate quantitative trait loci (QTL) for intramuscular fat deposition (marbling) in a local population of Japanese Black cattle, we performed a genome scan using a paternal half-sib family of Bull A. A marbling QTL was mapped in the region flanked by DIK0079 (20.7 cM) and TGLA303 (39.3 cM) on bovine chromosome (BTA) 7, affecting 5.0% of the total family variance. Haplotype analysis of the QTL region revealed that the marbling-increasing Q allele was transmitted from the dam. On the other hand, Bull B, a maternal half-sib of Bull A, did not receive the Q allele from its dam, based on the following findings: (i) a marbling QTL on BTA7 was not detected in the Bull B paternal half-sib family; (ii) recombination between DIK0079 (20.7 cM) and RM006 (25.4 cM) in the QTL region was observed in the maternal chromosome of Bull B; and (iii) the Q -harbouring steers from Bull A exhibited significantly higher marbling than the steers from Bull B and the remaining steers from Bull A. To precisely compare the maternal chromosomes of both bulls, we constructed a bacterial artificial chromosome contig covering the region between DIK0079 and RM006 and developed DNA markers. The recombination occurred between DIK8042 and DIK8044 , indicating that the marbling QTL was in a 2.9-cM region flanked by DIK0079 and DIK8044 .     

Mapping of quantitative trait loci for carcass traits in a Japanese Black (Wagyu) cattle population

To detect quantitative trait loci (QTL) that influence economically important traits in a purebred Japanese Black cattle population, we performed a preliminary genome-wide scan using 187 microsatellite markers across a paternal half-sib family composed of 258 offspring. We located six QTL at the 1% chromosome-wise level on bovine chromosomes (BTA) 4, 6, 13, 14 and 21. A second screen of these six QTL regions using 138 additional paternal offspring half-sib from the same sire, provided further support for five QTL: carcass weight on BTA14 (22-39 cM), one for rib thickness on BTA6 (27-58 cM) and three for beef marbling score (BMS) on BTA4 (59-67 cM), BTA6 (68-89 cM) and BTA21 (75-84 cM). The location of QTL for subcutaneous fat thickness on BTA13 was not supported by the second screen (P > 0.05). We determined that the combined contribution of the three QTLs for BMS was 10.1% of the total variance. The combined phenotypic average of these three Q was significantly different (P < 0.001) from those of other allele combinations. Analysis of additional half-sib families will be necessary to confirm these QTL.     

Quantitative trait loci for urinary albumin in crosses between C57BL/6J and A/J inbred mice in the presence and absence of Apoe

We investigated the effect of apolipoprotein E (Apoe) on albuminuria in the males of two independent F2 intercrosses between C57BL/6J and A/J mice, using wild-type inbred strains in the first cross and B6-Apoe(-/-) animals in the second cross. In the first cross, we identified three quantitative trait loci (QTL): chromosome (Chr) 2 [LOD 3.5, peak at 70 cM, confidence interval (C.I.) 28-88 cM]; Chr 9 (LOD 2.0, peak 5 cM, C.I. 5-25 cM); and Chr 19 (LOD 1.9, peak 49 cM, C.I. 23-54 cM). The Chr 2 and Chr 19 QTL were concordant with previously found QTL for renal damage in rat and human. The Chr 9 QTL was concordant with a locus found in rat. The second cross, testing only Apoe(-/-) progeny, did not identify any of these loci, but detected two other loci on Chr 4 (LOD 3.2, peak 54 cM, C.I. 29-73 cM) and Chr 6 (LOD 2.6, peak 33 cM, C.I. 11-61 cM), one of which was concordant with a QTL found in rat. The dependence of QTL detection on the presence of Apoe and the concordance of these QTL with rat and human kidney disease QTL suggest that Apoe plays a role in renal damage.     

QTL on mouse chromosomes 1 and 4 causing sperm-head morphological abnormality and male subfertility

The B10.M mouse strain represents a model for male subfertility as it produces a significantly low number of offspring. The only known male reproductive phenotype of this strain is its high frequency of sperm-head morphological abnormalities (44.7 ± 2.4 %). We previously reported that this phenotype was the product of two recessive loci. In this study we mapped the loci causing the high frequency of sperm-head morphological abnormalities in this strain using F2 animals produced by crossing B10.M and C3H mice. Quantitative trait loci (QTL) analysis (n = 178) identified two recessive genes, one on Chromosome (Chr) 1 (LOD score = 30.585) and one on Chr 4 (LOD score = 4.532). Further analysis (n = 854) mapped the locus on Chr 1 between Ercc5 (23.55 cM) and D1Mit528 (25.95 cM) and the locus on Chr 4 between D4Mit148 (69.48 cM) and D4Mit170 (70.47 cM). It was also found that the effects of these two loci were not independent. The major locus on Chr 1 determines the expression of sperm-head abnormalities, while the locus on Chr 4 enhances the frequency of abnormalities only when the genotype of the Chr 1 locus is homozygous for the B10.M allele. The major locus on Chr 1 was named sperm-head morphology 1 (Shm1), while the modifier locus on Chr 4 was named sperm-head morphology 2 (Shm2).     

Genetic Contributions to Body Weight in Mice: Relationship of Exploratory Behavior to Weight

Objective: The A/J and C57BL/6J mouse strains differ markedly in their exploratory behavior and their weight gain on a high‐fat diet. We examined the genetic contributions of exploratory behavior to body weight and tested for shared, pleiotropic loci influencing energy homeostasis. Research Methods and Procedures: Segregating (A×B6)F2 intercross (n = 514) and (B6AF1×A/J)N2 backcross (N = 223) populations were studied, phenotyping for weight and exploratory behaviors. Relationships among traits were analyzed by correlations. Weight traits were dissected with a genome‐wide scan. Results: Modest correlations were found between exploratory behaviors and weight, explaining 2% to 14% of the variance. Quantitative trait loci (QTL) for body weight at 8 weeks (wgt8), 10 weeks (wgt10), and 2‐week weight gain (difference between weeks 8 and 10) on a 6% fat diet were mapped. Two QTL on chromosome 1 (peaks at 66 cM and 100 cM; Bw8q1) affected wgt8 [likelihood of the odds ratio (Lod), 3.0 and 4.4] and wgt10 (Lod, 2.2 and 3.4), respectively. In the backcross, a significant QTL on chromosome 4 (peak at 66 cM; Bw8q2) affected wgt 8 (Lod, 3.3) and wgt10 (Lod, 3.1). For 2‐week weight gain, suggestive QTL were mapped on chromosomes 4 and 6. The chromosome 6 QTL region overlaps a human 7q locus for obesity. A search for between‐strain sequence polymorphisms in the leptin and NPY genes was unrevealing. Discussion: In mice, loci influencing exploratory activity play a modest role in body‐weight regulation. Some forms of obesity may emerge from loci regulating normal body weight.     

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。     

Fine mapping of a murine growth locus to a 1.4-cM region and resolution of linked QTL

Previous work identified a QTL affecting murine size (particularly tail length) in a cross between C57BL/6J and DBA/2J mice and refined its location to an 8-cM region between D1Mit30 and D1Mit57. The present study used recombinant progeny testing to fine map this QTL. Individuals from a partially congenic strain carrying chromosomes recombinant between D1Mit30 and D1Mit57 were mated to DBA/2J, generating 942 progeny. Two QTL affecting 10-week tail length were identified in this population: one at 9.7 cM distal to D1Mit30 (the position estimated in previous work), and another of smaller effect near D1Mit30. A second population (n=787) was generated by mating siblings from the progeny test population that were heterozygous for the same segment of chromosome, including only recombinants between D1Mit265 and D1Mit57. In the latter population, two QTL were also identified: one at 10.2 cM distal to D1Mit30, and another of smaller effect at the distal end of the mapped region (at D1Mit150). When the two populations were analyzed together, the estimated location of the central QTL was 10.2 cM distal to D1Mit30 and there was marginally significant evidence of the distal QTL. The central QTL explained approximately 7% of the phenotypic variance, and the 95% confidence interval for its position (determined by bootstrapping) was a 1.4-cM region, approximately the region from D1Mit451 to D1Mit219. The central QTL also affected tail length and body mass at 3 and 6 weeks of age, but to a lesser degree than 10-week tail length.     

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.     

Mapping of QTL for Body Conformation and Behavior in Cattle

Genome scans for quantitative trait loci (QTL) in farm animals have concentrated on primary production and health traits, and information on QTL for other important traits is rare. We performed a whole genome scan in a granddaughter design to detect QTL affecting body conformation and behavior in dairy cattle. The analysis included 16 paternal half-sib families of the Holstein breed with 872 sons and 264 genetic markers. The markers were distributed across all 29 autosomes and the pseudoautosomal region of the sex chromosomes with average intervals of 13.9 cM and covering an estimated 3155.5 cM. All families were analyzed jointly for 22 traits using multimarker regression and significance thresholds determined empirically by permutation. QTL that exceeded the experiment-wise significance threshold (5% level) were detected on chromosome 6 for foot angle, teat placement, and udder depth, and on chromosome 29 for temperament. QTL approaching experiment-wise significance (10% level) were located on chromosome 6 for general quality of feet and legs and general quality of udder, on chromosome 13 for teat length, on chromosome 23 for general quality of feet and legs, and on chromosome 29 for milking speed. An additional 51 QTL significant at the 5% chromosome-wise level were distributed over 21 chromosomes. This study provides the first evidence for QTL involved in behavior of dairy cattle and identifies QTL for udder conformation on chromosome 6 that could form the basis of recently reported QTL for clinical mastitis.     

Maternal exposure to predation risk decreases offspring antipredator behaviour and survival in threespined stickleback

1. Adaptive maternal programming occurs when mothers alter their offspring's phenotype in response to environmental information such that it improves offspring fitness. When a mother's environment is predictive of the conditions her offspring are likely to encounter, such transgenerational plasticity enables offspring to be better-prepared for this particular environment. However, maternal effects can also have deleterious effects on fitness.2. Here, we test whether female threespined stickleback fish exposed to predation risk adaptively prepare their offspring to cope with predators. We either exposed gravid females to a model predator or not, and compared their offspring's antipredator behaviour and survival when alone with a live predator. Importantly, we measured offspring behaviour and survival in the face of the same type of predator that threatened their mothers (Northern pike).3. We did not find evidence for adaptive maternal programming; offspring of predator-exposed mothers were less likely to orient to the predator than offspring from unexposed mothers. In our predation assay, orienting to the predator was an effective antipredator behaviour and those that oriented, survived for longer.4. In addition, offspring from predator-exposed mothers were caught more quickly by the predator on average than offspring from unexposed mothers. The difference in antipredator behaviour between the maternal predator-exposure treatments offers a potential behavioural mechanism contributing to the difference in survival between maternal treatments.5. However, the strength and direction of the maternal effect on offspring survival depended on offspring size. Specifically, the larger the offspring from predator-exposed mothers, the more vulnerable they were to predation compared to offspring from unexposed mothers.6. Our results suggest that the predation risk perceived by mothers can have long-term behavioural and fitness consequences for offspring in response to the same predator. These stress-mediated maternal effects can have nonadaptive consequences for offspring when they find themselves alone with a predator. In addition, complex interactions between such maternal effects and offspring traits such as size can influence our conclusions about the adaptive nature of maternal effects.     

Fine mapping reveals sex bias in quantitative trait loci affecting growth, skeletal size and obesity-related traits on mouse chromosomes 2 and 11

Previous speed congenic analysis has suggested that the expression of growth and obesity quantitative trait loci (QTL) on distal mouse chromosomes (MMU) 2 and 11, segregating between the CAST/EiJ (CAST) and C57BL/6J-hg/hg (HG) strains, is dependent on sex. To confirm, fine map, and further evaluate QTL x sex interactions, we constructed congenic by recipient F2 crosses for the HG.CAST-(D2Mit329-D2Mit457)N(6) (HG2D) and HG.CAST-(D11Mit260-D11Mit255)N(6) (HG11) congenic strains. Over 700 F2 mice were densely genotyped and phenotyped for a panel of 40 body and organ weight, skeletal length, and obesity-related traits at 9 weeks of age. Linkage analysis revealed 20 QTL affecting a representative subset of phenotypes in HG2DF2 and HG11F2 mice. The effect of sex was quantified by comparing two linear models: the first model included sex as an additive covariate and the second incorporated sex as an additive and an interactive covariate. Of the 20 QTL, 8 were sex biased, sex specific, or sex antagonistic. Most traits were regulated by single QTL; however, two closely linked loci were identified for five traits in HG2DF2 mice. Additionally, the confidence intervals for most QTL were significantly reduced relative to the original mapping results, setting the stage for quantitative trait gene (QTG) discovery. These results highlight the importance of assessing the contribution of sex in complex trait analyses.     

Genome-wide identification of QTL for age at puberty in gilts using a large intercross F2 population between White Duroc × Erhualian

Puberty is a fundamental development process experienced by all reproductively competent adults, yet the specific factors regulating age at puberty remain elusive in pigs. In this study, we performed a genome scan to identify quantitative trait loci (QTL) affecting age at puberty in gilts using a White Duroc × Erhualian intercross. A total of 183 microsatellites covering 19 porcine chromosomes were genotyped in 454 F₂ gilts and their parents and grandparents in the White Duroc × Erhualian intercross. A linear regression method was used to map QTL for age at puberty via QTLexpress. One 1% genome-wise significant QTL and one 0.1% genome-wise significant QTL were detected at 114 cM (centimorgan) on SSC1 and at 54 cM on SSC7, respectively. Moreover, two suggestive QTL were found on SSC8 and SSC17, respectively. This study confirmed the QTL for age at puberty previously identified on SSC1, 7 and 8, and reports for the first time a QTL for age at puberty in gilts on SSC17. Interestingly, the Chinese Erhualian alleles were not systematically favourable for younger age at puberty.     

A genome scan for eye color in 502 twin families: most variation is due to a QTL on chromosome 15q.

We have rated eye color on a 3-point scale (1 = blue/grey, 2 = hazel/green, 3 = brown) in 502 twin families and carried out a 5-10 cM genome scan (400-757 markers). We analyzed eye color as a threshold trait and performed multipoint sib pair linkage analysis using variance components analysis in Mx. A lod of 19.2 was found at the marker D15S1002, less than 1 cM from OCA2, which has been previously implicated in eye color variation. We estimate that 74% of variance in eye color liability is due to this QTL and a further 18% due to polygenic effects. However, a large shoulder on this peak suggests that other loci affecting eye color may be telomeric of OCA2 and inflating the QTL estimate. No other peaks reached genome-wide significance, although lods > 2 were seen on 5p and 14q and lods >1 were additionally seen on chromosomes 2, 3, 6, 7, 8, 9, 17 and 18. Most of these secondary peaks were reduced or eliminated when we repeated the scan as a two locus analysis with the 15q linkage included, although this does not necessarily exclude them as false positives. We also estimated the interaction between the 15q QTL and the other marker locus but there was only minor evidence for additive x additive epistasis. Elaborating the analysis to the full two-locus model including non-additive main effects and interactions did not strengthen the evidence for epistasis. We conclude that most variation in eye color in Europeans is due to polymorphism in OCA2 but that there may be modifiers at several other loci.     

The quantitative genetic basis of male mating behavior in Drosophila melanogaster

Male mating behavior is an important component of fitness in Drosophila and displays segregating variation in natural populations. However, we know very little about the genes affecting naturally occurring variation in mating behavior, their effects, or their interactions. Here, we have mapped quantitative trait loci (QTL) affecting courtship occurrence, courtship latency, copulation occurrence, and copulation latency that segregate between a D. melanogaster strain selected for reduced male mating propensity (2b) and a standard wild-type strain (Oregon-R). Mating behavior was assessed in a population of 98 recombinant inbred lines derived from these two strains and QTL affecting mating behavior were mapped using composite interval mapping. We found four QTL affecting male mating behavior at cytological locations 1A;3E, 57C;57F, 72A;85F, and 96F;99A. We used deficiency complementation mapping to map the autosomal QTL with much higher resolution to five QTL at 56F5;56F8, 56F9;57A3, 70E1;71F4, 78C5;79A1, and 96F1;97B1. Quantitative complementation tests performed for 45 positional candidate genes within these intervals revealed 7 genes that failed to complement the QTL: eagle, 18 wheeler, Enhancer of split, Polycomb, spermatocyte arrest, l(2)05510, and l(2)k02206. None of these genes have been previously implicated in mating behavior, demonstrating that quantitative analysis of subtle variants can reveal novel pleiotropic effects of key developmental loci on behavior.     

Enrichment of a common wheat genetic map and QTL mapping for fatty acid content in grain

DArT and SSR markers were used to saturate and improve a previous genetic map of RILs derived from the cross Chuan35050 × Shannong483. The new map comprised 719 loci, 561 of which were located on specific chromosomes, giving a total map length of 4008.4 cM; the rest 158 loci were mapped to the most likely intervals. The average chromosome length was 190.9 cM and the marker density was 7.15 cM per marker interval. Among the 719 loci, the majority of marker loci were DArTs (361); the rest included 170 SSRs, 100 EST-SSRs, and 88 other molecular and biochemical loci. QTL mapping for fatty acid content in wheat grain was conducted in this study. Forty QTLs were detected in different environments, with single QTL explaining 3.6-58.1% of the phenotypic variations. These QTLs were distributed on 16 chromosomes. Twenty-two QTLs showed positive additive effects, with Chuan35050 increasing the QTL effects, whereas 18 QTLs were negative with increasing effects from Shannong483. Six sets of co-located QTLs for different traits occurred on chromosomes 1B, 1D, 2D, 5D, and 6B.