应用中国和欧洲油菜建立的双二倍体群体对3个重要农艺性状的QTL定位以及与环境的互作分析

以中国的高油分自交系“高油”和欧洲高含油量品种“Sollux”的F1产生的282个株系组成的双二倍体(DH)群体为材料,在125个SSR标记座位构建的连锁图谱基础上,根据在中国和欧洲四个不同环境下的表型鉴定结果,采用混合线性模型基础上的QTL分析软件,对油菜3个重要农艺性状:株高,开花期和成熟期进行了数量性状基因座位(QTL)的联合定位分析,估测了这些QTL的加性、上位性以及与环境的互作效应。结果表明各性状均受多个加性、加加上位以及与环境互作的QTL控制。株高受多个QTL影响(12个位点具有加性或兼有环境互作效应,5个位点具有互作效应),以加性效应为主,加性效应总和可解释定位群体表型变异的75%左右,并多兼有上位性效应。12个主效QTL中,9个是“高油”等位基因相对“Sollux”有降低株高的作用,大多数加性×环境互作QTL的有效等位基因具有环境选择特异性。7个ae基因座位中,5个“高油”等位基因在杭州种植环境下,除一例外所有在德国环境下的互作基因座中,“Sollux”等位基因起着增加株高的作用,加加上位性主效总和为加性主效总和的三分之一。7个控制花期和8个控制成熟期的主效QTL中,分别有6个和5个是来自“高油”的等位基因相对“Sollux”具有提前开花和成熟的效应,这些QTL的效应总和占到性状表型变异的60%左右。5个位于第2和第12连锁群中的2个大效应QTL可能和已多次报导的VFN1和VFN3基因相近或相同。开花期和成熟期两性状均检测到显著的ae互作效应,双亲等位基因的效应在各环境下呈离散分布。位于14和19连锁群上的两个主效株高QTL同时也是控制开花期和油分含量的基因位点,因而利用这两个位点进行标记辅助筛选时要考虑到对油分含量的影响。控制成熟期的8个主效QTL中有3个同时也是控制开花期的基因座位,证实了开花期和成熟期高度正相关的遗传基础,两个生育性状均表现有较弱的QTL间加加上位互作,但以主效QTL的作用为主。     

Discovery and utilization of QTLs for insect resistance in soybean

Insect resistance in soybean has been an objective in numerous breeding programs, but efforts to develop high yielding cultivars with insect resistance have been unsuccessful. Three Japanese plant introductions, PIs 171451, 227687 and 229358, have been the primary sources of insect resistance alleles, but a combination of quantitative inheritance of resistance and poor agronomic performance has hindered progress. Linkage drag caused by co-introgression of undesirable agronomic trait alleles linked to the resistance quantitative trait loci (QTLs) is a persistent problem. Molecular marker studies have helped to elucidate the numbers, effects and interactions of insect resistance QTLs in the Japanese PIs, and markers are now being used in breeding programs to facilitate transfer of resistance alleles while minimizing linkage drag. Molecular markers also make it possible to evaluate QTLs independently and together in different genetic backgrounds, and in combination with transgenes from Bacillus thuringiensis.     

Identification of QTL for increased fibrous roots in soybean

Drought stress adversely affects soybean at various developmental stages, which collectively results in yield reduction. Unpredictable rainfall has been reported to contribute about 36% to variation of yield difference between the rain-fed and irrigated fields. Among the drought resistance mechanisms, drought avoidance in genotypes with fibrous roots was recognized to be associated with drought resistance in soybean. Plant introduction PI416937 was shown to possess fibrous roots and has been used as a parent in breeding programs to improve soybean productivity. Little information is available on relative contribution and chromosomal location of quantitative trait loci (QTL) conditioning fibrous roots in soybean. To identify the genomic locations and genetic bases of this trait, a recombinant inbred line population was derived from a cross between PI416937 and ‘Benning’. To detect associated QTLs, phenotypic data were collected and analyzed for 2 years under rain-fed field conditions. The selective genotyping approach was used to reduce the costs and work associated with conducting the QTL analysis. A total of five QTLs were identified on chromosomes Gm01 (Satt383), Gm03 (Satt339), Gm04 (Sct_191), Gm08 (Satt429), and Gm20 (Sat_299), and together explained 51% of the variation in root score. Detected QTLs were co-localized with QTLs related to root morphology, suggesting that fibrous roots QTL may be associated with other morpho-physiological traits and seed yield in soybean. Genetic dissection of the fibrous roots trait at the individual marker loci will allow for marker-assisted selection to develop soybean genotypes with enhanced levels of fibrous roots.     

A two-stage variable-stringency semiparametric method for mapping quantitative-trait loci with the use of genomewide-scan data on sib pairs

Genomewide scans for mapping loci have proved to be extremely powerful and popular. We present a semiparametric method of mapping a quantitative-trait locus (QTL) or QTLs with the use of sib-pair data generated from a two-stage genomic scan. In a two-stage genomic scan, either the entire genome or a large portion of the genome is saturated with low-density markers at the first stage. At the second stage, the intervals that are identified as probable locations of the trait loci, by means of analysis of data from the first stage, are then saturated with higher-density markers. These data are then analyzed for fine mapping of the loci. Our statistical strategy for analysis of data from the first stage is a low-stringency method based on the rank correlation of squared trait-difference values of the sib pairs and the estimated identity-by-descent scores at the marker loci. We suggest the use of a low-stringency method at the first stage, to save on computational time and to avoid missing any marker interval that may contain the trait loci. For analysis of data from the second stage, we have developed a high-stringency nonparametric-regression approach, using the kernel-smoothing technique. Through extensive simulations, we show that this approach is more powerful than is a currently used method for mapping QTLs by use of sib pairs, particularly in the presence of dominance and epistatic effects at the trait loci.     

Molecular mapping of soybean aphid resistance genes in PI 567541B

The soybean aphid (Aphis glycines Matsumura) is an important pest of soybean [Glycine max (L.) Merr.] in North America since it was first reported in 2000. PI 567541B is a newly discovered aphid resistance germplasm with early maturity characteristics. The objectives of this study were to map and validate the aphid resistance genes in PI 567541B using molecular markers. A mapping population of 228 F₃ derived lines was investigated for the aphid resistance in both field and greenhouse trials. Two quantitative trait loci (QTLs) controlling the aphid resistance were found using the composite interval mapping method. These two QTLs were localized on linkage groups (LGs) F and M. PI 567541B conferred resistant alleles at both loci. An additive × additive interaction between these two QTLs was identified using the multiple interval mapping method. These two QTLs combined with their interaction explained most of the phenotypic variation in both field and greenhouse trials. In general, the QTL on LG F had less effect than the one on LG M, especially in the greenhouse trial. These two QTLs were further validated using an independent population. The effects of these two QTLs were also confirmed using 50 advanced breeding lines, which were all derived from PI 567541B and had various genetic backgrounds. Hence, these two QTLs identified and validated in this study could be useful in improving soybean aphid resistance by marker-assisted selection.     

Analysis on additive effects and additive-by-additive epistatic effects of QTLs for yield traits in a recombinant inbred line population of rice

A linkage map consisting of 158 DNA markers were constructed by using a recombinant inbred line (RIL) population derived from the indica-indica rice cross Zhenshan 97B 2 Milyang 46. Quantitative trait loci (QTLs) conditioning grain yield and five yield component traits were determined at the one-locus and two-locus levels, and genotype-by-environment (GE) interactions were analyzed. Thirty-one QTLs were detected to have significant additive effects for yield traits, of which 12 also exhibited significant epistatic effects. Sixteen significant additive-by-additive (AA) interactions were detected, of which nine occurred between QTLs with own additive effects (M_epQTLs), four occurred between QTLs showing epistatic effects only (epQTLs), and three occurred between M_epQTLs and epQTLs. Significant GE interactions were found for six QTLs with additive effects and one AA interaction. Generally, the contributions to the phenotypic variation were higher due to QTL main effects than to epistatic effects. The detection of additive effects and AA effects of a QTL interfered with each other, indicating that the detection of QTLs with main effects, as well as the magnitude and directions of the additive effects, might vary depending on their interactions with other loci.     

Seed yield of near-isogenic soybean lines with introgressed quantitative trait loci conditioning resistance to corn earworm (Lepidoptera: Noctuidae) and soybean looper (Lepidoptera: Noctuidae) from PI 229358

The development of superior soybean, Glycine max (L.) Merr., cultivars exhibiting resistance to insects has been hindered due to linkage drag, a common phenomenon when introgressing alleles from exotic germplasm. Simple-sequence repeat (SSR) markers were used previously to map soybean insect resistance (SIR) quantitative trait loci (QTLs) in a'Cobb' X PI 229358 population, and subsequently used to create near-isogenic lines (NILs) with SIR QTL i n a 'Benning' genetic background. SIR QTLs were mapped on linkage groups (LGs) M (SIRQTL-M), G (SIRQTL-G), and H (SIRQTL-H). The objectives of this study were to 1) evaluate linkage drag for seed yield by using Benning-derived NILs selected for SIRQTL-M, SIRQTL-H, and SIRQTL-G; 2) assess the amount of PI 229358 genome surrounding the SIR QTL in each Benning NIL; and 3) evaluate the individual effects these three QTLs on antibiosis and antixenosis to corn earworm, Helicoverpa zea (Boddie), and soybean looper, Pseudoplusia includens (Walker). Yield data collected in five environments indicated that a significant yield reduction is associated with SIRQTL-G compared with NILs without SIR QTL. Overall, there was no yield reduction associated with SIRQTL-M or SIRQTL-H. A significant antixenosis and antibiosis effect was detected for SIRQTL-M in insect feeding assays, with no effect detected in antixenosis or antibiosis assays for SIRQTL-G or SIRQTL-H without the presence of PI 229358 alleles at SIRQTL-M. These results support recent findings concerning these loci.     

A biplot approach for investigating QTL-by-environment patterns

Due to the universal presence of genotype by environment interactions, understanding the pattern of quantitative trait loci (QTL)-by-environment interactions is a prerequisite for effective marker-assisted selection. In this report, we describe a biplot approach for investigating QTL-by-environment patterns. This approach involves two steps. It starts with a two-way table containing effects of individual QTLs in individual environments for the trait under investigation. This table is decomposed into principal components via singular value decomposition, and the first two principal components are plotted for both QTLs and environments to form a biplot. The resulting QQE biplot contains information on QTL main effects (Q) and QTL-by-environment interactions (QE). A QQE biplot displays the QTL-by-environment patterns and allows visualization of: (1) the magnitude of the effect of a QTL, (2) the average effect of a QTL and its stability across environments, (3) the effects of a QTL in individual environments, (4) the similarity/dissimilarity among QTLs in effect and response to the environments, (5) the similarity/dissimilarity among environments in modulating QTL effects, (6) any differentiation of mega-environments, and (7) the combination of QTL alleles for maximum/minimum expression of the trait for each environment or mega-environment. A case study is provided using the QTL-by-environment two-way table for barley yield.     

Abnormal leaf formation in soybean: genetic and environmental effects

Soybean is trifoliolate, but 4-, 5-, or 6-foliolate leaves have been reported and expression of such multi-foliolate (MF) leaf forms has been shown to be heritable. Here we analyze the genetic complexity of the MF phenotype and the dependence of its expression on the environment. Recombinant inbred (RI) segregants of soybean were grown in different environments. The frequency of plants expressing the MF phenotype as well as the frequency of nodes exhibiting MF leaves varied with both the environment and the RI segregant genotype. Growth chamber experiments supported field observations suggesting that environment (day length, temperature, etc.) at emergence influenced expression of MF during subsequent growth. Marker facilitated analyses of three RI segregant populations identified quantitative trait loci (QTLs) in 17 regions of the soybean genome. These either directly regulated MF phenotype expression, or were involved in interactions with such loci. Loci, identified in one RI population also were identifiable in another, different, RI population. Most of the loci affected both the frequency of plants expressing MF, and the number of nodes on MF plants that expressed the phenotype. However, a few loci differentiated between these two effects. Many loci affected plants in both field experiments, however, a few differentiated between the two environments. Similar patterns were observed for interactions between loci. QTLs regulating the MF phenotype were located in genome regions that also contained QTLs regulating major agronomic traits—e.g. yield, lodging, etc. This suggests that the loci involved regulate plant growth at some over-arching level, controlling multiple phenotypes or traits.     

影响水稻花药培养力的数量性状基因座位间的互作

控制数量性状的多个基因间不仅存在加性效应,还存在非等位基因间的互作。对一个籼粳交后代的加倍单倍体群体花药培养,通过Ｅｐｉｓｔａｔ软件分析影响水稻花药 数量性状基因座位间的互作。结果表明,愈伤组织诱导率主要受两个单基因的影响,不存在双基因条件型互作,但有２对互适型互作与其有关。     

Selection on domestication traits and quantitative trait loci in crop-wild sunflower hybrids

The strength and extent of gene flow from crops into wild populations depends, in part, on the fitness of the crop alleles, as well as that of alleles at linked loci. Interest in crop-wild gene flow has increased with the advent of transgenic plants, but nontransgenic crop-wild hybrids can provide case studies to understand the factors influencing introgression, provided that the genetic architecture and the fitness effects of loci are known. This study used recombinant inbred lines (RILs) generated from a cross between crop and wild sunflowers to assess selection on domestication traits and quantitative trait loci (QTL) in two contrasting environments, in Indiana and Nebraska, USA. Only a small fraction of plants (9%) produced seed in Nebraska, due to adverse weather conditions, while the majority of plants (79%) in Indiana reproduced. Phenotypic selection analysis found that a mixture of crop and wild traits were favoured in Indiana (i.e. had significant selection gradients), including larger leaves, increased floral longevity, larger disk diameter, reduced ray flower size and smaller achene (seed) mass. Selection favouring early flowering was detected in Nebraska. QTLs for fitness were found at the end of linkage groups six (LG6) and nine (LG9) in both field sites, each explaining 11-12% of the total variation. Crop alleles were favoured on LG9, but wild alleles were favoured on LG6. QTLs for numerous domestication traits overlapped with the fitness QTLs, including flowering date, achene mass, head number, and disk diameter. It remains to be seen if these QTL clusters are the product of multiple linked genes, or individual genes with pleiotropic effects. These results indicate that crop trait values and alleles may sometimes be favoured in a noncrop environment and across broad geographical regions.     

Selection on domestication traits and quantitative trait loci in crop–wild sunflower hybrids

The strength and extent of gene flow from crops into wild populations depends, in part, on the fitness of the crop alleles, as well as that of alleles at linked loci. Interest in crop–wild gene flow has increased with the advent of transgenic plants, but nontransgenic crop–wild hybrids can provide case studies to understand the factors influencing introgression, provided that the genetic architecture and the fitness effects of loci are known. This study used recombinant inbred lines (RILs) generated from a cross between crop and wild sunflowers to assess selection on domestication traits and quantitative trait loci (QTL) in two contrasting environments, in Indiana and Nebraska, USA. Only a small fraction of plants (9%) produced seed in Nebraska, due to adverse weather conditions, while the majority of plants (79%) in Indiana reproduced. Phenotypic selection analysis found that a mixture of crop and wild traits were favoured in Indiana (i.e. had significant selection gradients), including larger leaves, increased floral longevity, larger disk diameter, reduced ray flower size and smaller achene (seed) mass. Selection favouring early flowering was detected in Nebraska. QTLs for fitness were found at the end of linkage groups six (LG6) and nine (LG9) in both field sites, each explaining 11–12% of the total variation. Crop alleles were favoured on LG9, but wild alleles were favoured on LG6. QTLs for numerous domestication traits overlapped with the fitness QTLs, including flowering date, achene mass, head number, and disk diameter. It remains to be seen if these QTL clusters are the product of multiple linked genes, or individual genes with pleiotropic effects. These results indicate that crop trait values and alleles may sometimes be favoured in a noncrop environment and across broad geographical regions.     

Epistatic association mapping in homozygous crop cultivars

The genetic dissection of complex traits plays a crucial role in crop breeding. However, genetic analysis and crop breeding have heretofore been performed separately. In this study, we designed a new approach that integrates epistatic association analysis in crop cultivars with breeding by design. First, we proposed an epistatic association mapping (EAM) approach in homozygous crop cultivars. The phenotypic values of complex traits, along with molecular marker information, were used to perform EAM. In our EAM, all the main-effect quantitative trait loci (QTLs), environmental effects, QTL-by-environment interactions and QTL-by-QTL interactions were included in a full model and estimated by empirical Bayes approach. A series of Monte Carlo simulations was performed to confirm the reliability of the new method. Next, the information from all detected QTLs was used to mine novel alleles for each locus and to design elite cross combination. Finally, the new approach was adopted to dissect the genetic basis of seed length in 215 soybean cultivars obtained, by stratified random sampling, from 6 geographic ecotypes in China. As a result, 19 main-effect QTLs and 3 epistatic QTLs were identified, more than 10 novel alleles were mined and 3 elite parental combinations, such as Daqingdou and Zhengzhou790034, were predicted.     

QTL mapping and epistatic interaction analysis of field resistance to sudden death syndrome (<Emphasis Type="Italic">Fusarium virguliforme</Emphasis>) in soybean

Key message

Two interactive quantitative trait loci (QTLs) controlled the field resistance to sudden death syndrome (SDS) in soybean. The interaction between them was confirmed.

Abstract

Sudden death syndrome (SDS), caused by Fusarium virguliforme, is a major disease of soybean [Glycine max (L.) Merr.] in the United States. Breeding for soybean resistance to SDS is the most cost-effective method to manage the disease. The objective of this study was to identify and characterize quantitative trait loci (QTLs) underlying field resistance to SDS in a recombinant inbred line population from the cross GD2422?×?LD01-5907. This population was genotyped with 1786 polymorphic single nucleotide polymorphisms (SNPs) using SoySNP6 K iSelect BeadChip and evaluated for SDS resistance in a naturally infested field. Four SDS resistance QTLs were mapped on Chromosomes 4, 8, 12 and 18. The resistant parent, LD01-5907, contributed the resistance alleles for the QTLs on Chromosomes 8 and 18 (qSDS-8 and qSDS-18), while the other parent, GD2422, provided the resistance alleles for the QTLs on Chromosomes 4 and 12 (qSDS-4 and qSDS-12). The minor QTL on Chromosome 12 (qSDS-12) is novel. The QTL on Chromosomes 8 and 18 (qSDS-8 and qSDS-18) overlapped with two soybean cyst nematode resistance-related loci, Rhg4 and Rhg1, respectively. A significant interaction between qSDS-8 and qSDS-18 was detected by disease incidence. Individual effects together with the interaction effect explained around 70% of the phenotypic variance. The epistatic interaction of qSDS-8 and qSDS-18 was confirmed by the field performance across multiple years. Furthermore, the resistance alleles at qSDS-8 and qSDS-18 were demonstrated to be recessive. The SNP markers linked to these QTLs will be useful for marker-assisted breeding to enhance the SDS resistance.

     

RFLP tagging of QTLs conditioning specific leaf weight and leaf size in soybean

 Selection for high specific leaf weight (SLW) in soybean [Glycine max (L) Merr.] may increase apparent photosynthetic rate per unit leaf area (AP), which in turn may improve seed yield. In general, the SLW and leaf size are negatively correlated in soybean. To maximize total photosynthetic performance, and perhaps the seed yield, of a soybean cultivar, it would be necessary to establish a large leaf area rapidly while maintaining a high SLW. The objective of the present study was to identify quantitative trait loci (QTLs) conditioning SLW and leaf size in soybean. One hundred and twenty F₄-derived lines from a ‘Young’×PI416937 population were evaluated using restriction fragment length polymorphism (RFLP) markers. The genetic map consisted of 155 loci on 33 linkage groups (LGs) covering 973 cM of map distance. The phenotypic data were collected from two different environments – a greenhouse at Athens, Ga. and a field site at Windblow, N.C. The SLW and leaf-size measurements were made on leaves from the 8th and 9th node of soybean plants at the V12 stage of development. Combined over environments, six putative independent RFLP markers were associated with SLW, and four of these loci were consistent across environments. Individually, the six markers each explained between 8 and 18% of the phenotypic variation among lines for SLW. The Young alleles contributed to a greater SLW at four of the six independent marker loci, and transgressive segregation occurred among the progeny for SLW. Three putative independent RFLP markers were associated with leaf size, each explaining between 6 to 11% of the phenotypic variation in the trait, and one of these markers was identified in both environments. There was no correlation between SLW and leaf size in this population. Similarly, none of the six QTLs conditioning SLW were linked to any of the three QTLs for leaf size. In this soybean population, it is possible to select for progeny lines with greater SLW than either parent perhaps without affecting the leaf size. It is feasible to pyramid all of the desirable alleles for greater SLW and large leaf size in a single genetic background. Received: 16 August 1997 / Accepted: 20 October 1997     

The genetic basis of adaptive population differentiation: a quantitative trait locus analysis of fitness traits in two wild barley populations from contrasting habitats

We used a quantitative trait locus (QTL) approach to study the genetic basis of population differentiation in wild barley, Hordeum spontaneum. Several ecotypes are recognized in this model species, and population genetic studies and reciprocal transplant experiments have indicated the role of local adaptation in shaping population differences. We derived a mapping population from a cross between a coastal Mediterranean population and a steppe inland population from Israel and assessed F3 progeny fitness in the natural growing environments of the two parental populations. Dilution of the local gene pool, estimated as the proportion of native alleles at 96 marker loci in the recombinant lines, negatively affected fitness traits at both sites. QTLs for fitness traits tended to differ in the magnitude but not in the direction of their effects across sites, with beneficial alleles generally conferring a greater fitness advantage at their native site. Several QTLs showed fitness effects at one site only, but no opposite selection on individual QTLs was observed across the sites. In a common-garden experiment, we explored the hypothesis that the two populations have adapted to divergent nutrient availabilities. In the different nutrient environments of this experiment, but not under field conditions, fitness of the F3 progeny lines increased with the number of heterozygous marker loci. Comparison of QTL-effects that underlie genotype x nutrient interaction in the common-garden experiment and genotype x site interaction in the field suggested that population differentiation at the field sites may have been driven by divergent nutrient availabilities to a limited extent. Also in this experiment no QTLs were observed with opposite fitness effects in contrasting environments. Our data are consistent with the view that adaptive differentiation can be based on selection on multiple traits changing gradually along ecological gradients. This can occur without QTLs showing opposite fitness effects in the different environments, that is, in the absence of genetic trade-offs in performance between environments.     

Molecular-Marker-Facilitated Investigations of Quantitative-Trait Loci in Maize. I. Numbers, Genomic Distribution and Types of Gene Action

Individual genetic factors which underlie variation in quantitative traits of maize were investigated in each of two F2 populations by examining the mean trait expressions of genotypic classes at each of 17-20 segregating marker loci. It was demonstrated that the trait expression of marker locus classes could be interpreted in terms of genetic behavior at linked quantitative trait loci (QTLs). For each of 82 traits evaluated, QTLs were detected and located to genomic sites. The numbers of detected factors varied according to trait, with the average trait significantly influenced by almost two-thirds of the marked genomic sites. Most of the detected associations between marker loci and quantitative traits were highly significant, and could have been detected with fewer than the 1800-1900 plants evaluated in each population. The cumulative, simple effects of marker-linked regions of the genome explained between 8 and 40% of the phenotypic variation for a subset of 25 traits evaluated. Single marker loci accounted for between 0.3% and 16% of the phenotypic variation of traits. Individual plant heterozygosity, as measured by marker loci, was significantly associated with variation in many traits. The apparent types of gene action at the QTLs varied both among traits and between loci for given traits, although overdominance appeared frequently, especially for yield-related traits. The prevalence of apparent overdominance may reflect the effects of multiple QTLs within individual marker-linked regions, a situation which would tend to result in overestimation of dominance. Digenic epistasis did not appear to be important in determining the expression of the quantitative traits evaluated. Examination of the effects of marked regions on the expression of pairs of traits suggests that genomic regions vary in the direction and magnitudes of their effects on trait correlations, perhaps providing a means of selecting to dissociate some correlated traits. Marker-facilitated investigations appear to provide a powerful means of examining aspects of the genetic control of quantitative traits. Modifications of the methods employed herein will allow examination of the stability of individual gene effects in varying genetic backgrounds and environments.     

The nature of quantittative genetic variation revisited: Lessons from Drosophila bristles

Most characters that distinguish one individual from another, like height or weight, vary continuously in populations. Continuous variation of these ‘quantitative’ traits is due to the simultaneous segregation of multiple quantitative trait loci (QTLs) as well as environmental influences. A major challenge in human medicine, animal and plant breeding and evolutionary genetics is to identify QTLs and determine their genetic properties. Studies of the classic quantitative traits, abdominal and sternopleural bristle numbers of Drosophila, have shown that: (1) many loci have small effects on bristle number, but a few have large effects and cause most of the genetic variation; (2) ‘candidate’ loci involved in bristle development often have large quantitative effects on bristle number; and (3) alleles at QTLs affecting bristle number have variable degrees of dominance, interact with each other, and affect other quantitative traits, including fitness. Lessons learned from this model system will be applicable to studies of the genetic basis of quantitative variation in other species.     

QTL analysis of potato tuberization

Quantitative trait loci (QTLs) affecting tuberization were detected in reciprocal backcrosses between Solanum tuberosum and S. berthaultii. Linkage analyses were performed between traits and RFLP alleles segregating from both the hybrid and the recurrent parent using a set of framework markers from the potato map. Eleven distinct loci on seven chromosomes were associated with variation in tuberization. Most of the loci had small effects, but a QTL explaining 27% of the variance was found on chromosome 5. More QTLs were detected while following alleles segregating from the recurrent S. tuberosum parent used to make the backcross than were detected by following alleles segregating from the hybrid parent. More than half of the alleles favoring tuberization were at least partly dominant. Tuberization was favored by an allele from S. berthaultii at 3 of the 5 QTLs detected by segregation from the hybrid parent. The additive effects of the QTLs for tuberization explained up to 53% of the phenotypic variance, and inclusion of epistatic effects increased this figure to 60%. The most common form of epistasis was that in which presence of an allele at each of 2 loci favoring tuberization was no more effective than the presence of a favorable allele at 1 of the 2 loci. The QTLs detected for tuberization traits are discussed in relationship to those previously detected for trichome-mediated insect resistance derived from the unadapted wild species.Paper number 54 of the Department of Fruit and Vegetable Science, Cornell University     

Identification of major QTLs and epistatic interactions for seed protein concentration in soybean under multiple environments based on a high-density map

The concentration of protein in soybean is an important trait that drives successful soybean quality. A recombinant inbred line derived from a cross between the Charleston and Dongnong594 cultivars was planted in one location across 10 years and two locations across 5 years in China (20 environments in total), and the genetic effects were partitioned into additive main effects, epistatic main effects and their environmental interaction effects using composite interval mapping and inclusive composite interval mapping models based on a high-density genetic map. Ten main-effect quantitative trait loci (QTLs) were identified on chromosomes 3, 6, 7, 13, 15 and 20 and detected in more than three environments, with each of the main-effect QTLs contributing a phenotypic variation of around 10 %. Between the intervals of the main-effect QTLs, 93 candidate genes were screened for their involvement in seed protein storage and/or amino acid biosynthesis and metabolism processes based on gene ontology and annotation information. Furthermore, an analysis of epistatic interactions showed that three epistatic QTL pairs were detected, and could explain approximately 50 % of the phenotypic variation. The additive main-effect QTLs and epistatic QTL pairs contributed to high phenotypic variation under multiple environments, and the results were also validated and corroborated with previous research, indicating that marker-assisted selection can be used to improve soybean protein concentrations and that the candidate genes can also be used as a foundation data set for research on gene function.