甘蓝型油菜遗传图谱的构建及单株产量构成因素的QTL分析

采用常规品系04-1139与高产多角果品系05-1054构建的F2代群体为作图群体, 运用SSR(Simple sequence repeat)和SRAP(Sequence-related amplified polymorphism)构建分子标记遗传图谱并对甘蓝型油菜单株产量构成因素进行QTL分析。遗传图谱包含200个分子标记, 分布于19个连锁群上, 总长度1 700.23 cM, 标记间的平均距离8.50 cM。采用复合区间作图法(Composite interval mapping, CIM)对单株产量构成因素(单株有效角果数、每果粒数和千粒重)进行QTL分析, 共检测到12个QTL: 其中单株有效角果数4个QTL, 分别解释表型变异为35.64%、12.96%、28.71%和34.02%; 每果粒数获得5个QTL, 分别解释表型变异为8.41%、7.87%、24.37%、8.57%和14.31%; 千粒重获得３个QTL, 分别解释表型变异为2.33%、1.81%和1.86%。结果表明: 同一性状的等位基因增效作用可以同时来自高值亲本和低值亲本; 文章中与主效QTL连锁的标记可用于油菜产量性状的分子标记辅助选择和聚合育种。     

Genetic mapping of seed shape in three populations of recombinant inbred lines of soybean (Glycine max L. Merr.)

Round soybean seeds are sought-after for food-type soybean. Also the genetic control of seed geometry is of scientific interest. The objectives of this study were to estimate heritability and map quantitative trait loci (QTLs) responsible for seed shape traits. Three densely mapped recombinant inbred populations each with 192 segregants were used, Minsoy × Archer, Minsoy × Noir1, and Noir1 × Archer. A two rep two location experiment was conducted in Los Andes, Chile, and East Lansing, MI, USA. Seed height (SH), width (SW), length (SL), and seed volume (SV) as width × height × length were measured to determine seed shape. Heritability was estimated by variance component analysis. A total of 19 significant QTLs (LOD ≥ 3.7) in ten linkage groups (LG) were detected for all the traits. Only one QTL was stable across populations and environments and six were stable in at least two populations in both environments. The amount of phenotypic variation explained by a single QTL varied from 7.5% for SH, to 18.5% for SW and at least 30% of the genetic variation for the traits is controlled by four QTL or less. All traits were highly correlated with each other in all populations with values ranging from 0.5 to 0.9, except for SL and SW that were not significantly correlated or had a low correlation in all populations. Narrow sense heritabilities for all traits ranged from 0.42 to 0.88. We note that LG u9, u11, and u14 are hot points of the genome for QTLs for various traits. The number and genomic distribution of the QTLs confirms the complex genetic control of seed shape. Transgressive segregation was observed for all traits suggesting that careful selection of parents with similar phenotypes but different genotypes using molecular markers can result in desirable transgressive segregants.     

QTL in mega-environments: I. Universal and specific seed yield QTL detected in a population derived from a cross of high-yielding adapted × high-yielding exotic soybean lines

Modern soybean [(Glycine max (L.) Merrill] breeding programs rely primarily on the use of elite × elite line crosses to develop high-yielding cultivars. Favorable alleles for traits of interest have been found in exotic germplasm but the successful introduction of such alleles has been hampered by the lack of adaptation of the exotic parent to local mega-environment and difficulties in identifying superior progeny from elite × exotic crosses. The objective of this study was to use a population derived from a cross between an adapted and an exotic elite line to understand the genetic causes underlying adaptation to two mega-environments (China and Canada). A cross between a high-yielding Canadian cultivar ‘OAC Millennium’ and an elite Chinese cultivar ‘Heinong 38’ was performed to develop a recombinant inbred line (RIL) population. The RIL population was evaluated in China and Canada in multiple environments from 2004 to 2006. Significant variation for seed yield was observed among the RILs in both the Chinese and Canadian environment. Individual RILs performed differently between the Chinese and Canadian environments suggesting differential adaptation to intercontinental mega-environments. Seven seed yield quantitative trait loci (QTL) were identified of which five were mega-environment universal QTL (linked to markers Satt100, Satt162, Satt277, Sat_126, and the interval of Satt139-Sat_042) and two were mega-environment-specific QTL (at marker intervals, Satt194-SOYGPA and Satt259-Satt576). Seed yield QTL located near Satt277 has been confirmed and new QTL have been identified explaining between 9 and 37% of the phenotypic variation in seed yield. The QTL located near Satt100 explained the greatest amount of variation ranging from 18 to 37% per environment. Broad sense heritability ranged from 89 to 64% among environments. Epistatic effects have been identified in both mega-environments with pairs of markers explaining between 9 and 14% of the phenotypic variation in seed yield. An improved understanding of the type of QTL action as either universal or mega-environment-specific QTL as well as their interaction may facilitate the development of strategies to introgress specific high-yielding alleles from Chinese to North American germplasm and vice versa to sustain efforts in breeding of high-yielding soybean cultivars.     

Mapping quantitative trait loci associated with selenate tolerance in Arabidopsis thaliana

Selenium is essential for many organisms, but is toxic at higher levels. To investigate the genetic basis of selenate tolerance in Arabidopsis thaliana, quantitative trait loci (QTL) associated with selenate tolerance in accessions Landsberg erecta and Columbia were mapped using recombinant inbred lines (RILs). The selenate tolerance index (TI(D10) = root growth + 30 microm selenate/root growth control x 100%) was fourfold higher for parental line Col-4 (59%) than for parent Ler-0 (15%). Among the 96 F8 RILs, TI(D10) ranged from 11 to 75% (mean 37%). Using composite interval mapping, three QTL were found on chromosomes 1, 3 and 5, which together explained 24% of variation in TI(D10) and 32% of the phenotypic variation for the difference in root length +/- Se (RL(D10)). Highly significant epistatic interactions between the QTL and markers on chromosome 2 explained additional variation for both traits. Potential candidate genes for Se tolerance in each of the QTL regions are discussed. These results offer insight into the genetic basis of selenate tolerance, and may be useful for identification of selenate-tolerance genes.     

Identification of QTLs with Additive,Epistatic, and QTL × Seed Maturity Interaction Effects for Seed Vigor in Rice

Seed maturity is a critical process of seed vigor establishment. In this study, one rice population of recombinant inbred lines (RILs) was used to determine the genetic characteristics of seed vigor, including the germination potential (GP), germination rate (GR), germination index (GI), and time for 50 % of germination (T₅₀), at 4, 5, and 6 weeks after heading in 2 years. Significant differences of seed vigor were observed among two parents and RIL population; the heritability of four traits was more than 90 % at three maturity stages. A total of 19 additive and 2 epistatic quantitative trait loci (QTL) for seed vigor were identified using QTL Cartographer and QTLNetwork program, respectively, in 2012, while 16 simple sequence repeat (SSR) markers associated with seed vigor were detected using bulked segregant analysis (BSA) in 2013. The phenotypic variation explained by each additive, epistatic QTL, and QTL × seed maturity interaction ranged from 9.19 to 22.94 %, 7.23 to 7.75 %, and 0.05 to 0.63 %, respectively. Ten additive QTLs were stably expressed in 2 years which might play important roles in establishment of seed vigor in different environments. By comparing chromosomal positions of ten stably expressed additive QTLs with those previously identified, they might be true QTLs for seed vigor; the regions of QTLs for seed vigor are likely to coincide with QTLs for seed dormancy, seed reserve mobilization, low-temperature germinability, and seedling growth. Using four selected RILs, three cross-combinations were predicted to improve seed vigor; 9 to 10 elite alleles could be pyramided by each combination. The selected RILs and the identified QTLs might be applicable for the improvement of seed vigor by marker-assisted selection (MAS) in rice.     

Dynamic Quantitative Trait Locus Analysis of Seed Vigor at Three Maturity Stages in Rice

Seed vigor is an important characteristic of seed quality. In this study, one rice population of recombinant inbred lines (RILs) was used to determine the genetic characteristics of seed vigor, including the germination potential, germination rate, germination index and time for 50% of germination, at 4 (early), 5 (middle) and 6 weeks (late) after heading in two years. A total of 24 additive and 9 epistatic quantitative trait loci (QTL) for seed vigor were identified using QTL Cartographer and QTLNetwork program respectively in 2012; while 32 simple sequence repeat (SSR) markers associated with seed vigor were detected using bulked segregant analysis (BSA) in 2013. The additive, epistatic and QTL × development interaction effects regulated the dry maturity developmental process to improve seed vigor in rice. The phenotypic variation explained by each additive, epistatic QTL and QTL × development interaction ranged from 5.86 to 40.67%, 4.64 to 11.28% and 0.01 to 1.17%, respectively. The QTLs were rarely co-localized among the different maturity stages; more QTLs were expressed at the early maturity stage followed by the late and middle stages. Twenty additive QTLs were stably expressed in two years which might play important roles in establishment of seed vigor in different environments. By comparing chromosomal positions of these stably expressed additive QTLs with those previously identified, the regions of QTL for seed vigor are likely to coincide with QTL for grain size, low temperature germinability and seed dormancy; while 5 additive QTL might represent novel genes. Using four selected RILs, three cross combinations of seed vigor for the development of RIL populations were predicted; 19 elite alleles could be pyramided by each combination.     

Quantitative trait loci controlling resistance to cadmium rhizotoxicity in two recombinant inbred populations of Arabidopsis thaliana are partially shared by those for hydrogen peroxide resistance

To understand mechanisms of cadmium (Cd) tolerance variation associated with root elongation in Arabidopsis thaliana , quantitative trait loci (QTLs) and epistasis were analyzed using relative root length (RRL: % of the root length in +Cd to −Cd) as a tolerant index. Using the composite interval mapping method, three major QTLs ( P < 0.05) were detected on chromosomes 2, 4 and 5 in the recombinant inbred population derived from a cross between Landsberg erecta (L er −0) and Columbia (Col-4). The highest logarithm of odds (LOD) of 5.6 was detected with the QTL on chromosome 5 (QTL5), which is linked to the genetic marker CDPK9 and explained about 26% of the Cd tolerance variation. There was no significant difference in Cd-translocation ratio from roots to shoots between tolerant and sensitive recombinant inbreed lines (RILs), while greater accumulations of reactive oxygen species were observed in the roots of sensitive RILs. This suggested that accumulation of ROS would explain Cd tolerance variation of the L er /Col RILs, which is mainly controlled by the QTL on chromosome 5. The QTL5 in L er /Col population was also detected as one of the major QTLs controlling tolerances to hydrogen peroxide and to copper, which is another ROS generating rhizotoxic metal. The same chromosomal position was detected as a common major QTL for Cd and hydrogen peroxide tolerances in a different recombinant inbreed (RI) population derived from a cross of Col- gl1 and Kashmir (Kas-1). These data, along with a multitraits QTL analysis in both sets of RILs, suggest that peroxide damage depends on the genotype at a major Cd-tolerant locus on the upper part of chromosome 5.     

Quantitative trait loci for resistance to pre-harvest sprouting in US hard white winter wheat Rio Blanco

Pre-harvest sprouting (PHS) of wheat is a major problem that severely limits the end-use quality of flour in many wheat-growing areas worldwide. To identify quantitative trait loci (QTLs) for PHS resistance, a population of 171 recombinant inbred lines (RILs) was developed from the cross between PHS-resistant white wheat cultivar Rio Blanco and PHS-susceptible white wheat breeding line NW97S186. The population was evaluated for PHS in three greenhouse experiments and one field experiment. After 1,430 pairs of simple sequence repeat (SSR) primers were screened between the two parents and two bulks, 112 polymorphic markers between two bulks were used to screen the RILs. One major QTL, QPhs.pseru-3AS, was identified in the distal region of chromosome 3AS and explained up to 41.0% of the total phenotypic variation in three greenhouse experiments. One minor QTL, QPhs.pseru-2B.1, was detected in the 2005 and 2006 experiments and for the means over the greenhouse experiments, and explained 5.0-6.4% of phenotypic variation. Another minor QTL, QPhs.pseru-2B.2, was detected in only one greenhouse experiment and explained 4.5% of phenotypic variation for PHS resistance. In another RIL population developed from the cross of Rio Blanco/NW97S078, QPhs.pseru-3AS was significant for all three greenhouse experiments and the means over all greenhouse experiments and explained up to 58.0% of phenotypic variation. Because Rio Blanco is a popular parent used in many hard winter wheat breeding programs, SSR markers linked to the QTLs have potential for use in high-throughput marker-assisted selection of wheat cultivars with improved PHS resistance as well as fine mapping and map-based cloning of the major QTL QPhs.pseru-3AS.     

Mapping of QTL for downy mildew resistance in maize

Quantitative trait loci (QTLs) of maize involved in mediating resistance to Peronosclerospora sorghi, the causative agent of sorghum downy mildew (SDM), were detected in a population of recombinant inbred lines (RILs) derived from the Zea mays L. cross between resistant (G62) and susceptible (G58) inbred lines. Field tests of 94 RILs were conducted over two growing seasons using artificial inoculation. Heritability of the disease reaction was high (around 70%). The mapping population of the RILs was also scored for restriction fragment length polymorphic (RFLP) markers. One hundred and six polymorphic RFLP markers were assigned to ten chromosomes covering 1648 cM. Three QTLs were detected that significantly affected resistance to SDM combined across seasons. Two of these mapped quite close together on chromosome 1, while the third one was on chromosome 9. The percentage of phenotypic variance explained by each QTL ranged from 12.4% to 23.8%. Collectively, the three QTLs identified in this study explained 53.6% of the phenotypic variation in susceptibility to the infection. The three resistant QTLs appeared to have additive effects. Increased susceptibility was contributed by the alleles of the susceptible parent. The detection of more than one QTL supports the hypothesis that several qualitative and quantitative genes control resistance to P. sorghi.     

Identification and mapping of a major dominant quantitative trait locus controlling seeds per silique as a single Mendelian factor in Brassica napus L.

One putative quantitative trait locus (QTL) for seeds per silique (SS), cqSS.A8, was identified using a double haploid (DH) population in Brassica napus, and near-isogenic lines (NILs; BC(3)F(1)) for cqSS.A8 were developed. However, the flanking markers from cqSS.A8 showed no significant difference using single-marker analysis, even though the frequency distribution of SS in the BC(3)F(1) was bimodal, suggesting that one novel locus existed. In this study, we characterized the effects of this locus in the NILs and used a published linkage map to determine its location. A three-step approach was designed for mapping the locus in the NILs (BC(3)F(2)): (1) determining the individual BC(3)F(2) genotype at the locus using a progeny test; (2) identifying amplified fragment length polymorphism (AFLP) markers linked to the locus using a combination of AFLP and bulked segregant analysis; and (3) determining the location and effects of this locus. QTL analysis in the BC(3)F(2) revealed that this locus explained 85.8 and 55.7 % of phenotypic variance for SS and SL, respectively. Its additive and dominant effects on SS were 6.1 and 5.7, respectively. The locus was validated using a DH population by composite interval mapping and located to linkage group C9 (designated as qSS.C9). Mapping qSS.C9 was undertaken using 230 extremely low-SS plants of a BC(4)F(1) population containing 807 plants. We found that qSS.C9 delimited a 1.005-Mb interval including 218 predicted genes in the reference Brassica rapa (Chiifu-401). These results will greatly facilitate map-based cloning of qSS.C9 and seed yield improvement in rapeseed.     

Novel pleiotropic loci controlling panicle architecture across environments in japonica rice （Oryza sativa L.）

To identify quantitative trait loci (QTLs) controlling panicle architecture in japonica rice, a genetic map was constructed based on simple sequence repeat (SSR) markers and 254 recombinant inbred lines (RILs) derived from a cross between cultivars Xiushui 79 and C Bao. Seven panicle traits were investigated under three environments. Single marker analysis indicated that a total of 27 SSR markers were highly associated with panicle traits in all the three environments. Percentage of phenotypic variation explained by single locus varied from 2% to 35%. Based on the mixed linear model, a total of 40 additive QTLs for seven panicle traits were detected by composite interval mapping, explaining 1.2%-35% of phenotypic variation. Among the 9 QTLs with more than 10% of explained phenotypic variation, two QTLs were for the number of primary branches per panicle (NPB), two for panicle length (PL), two for spikelet density (SD), one for the number of secondary branches per panicle (NSB), one for secondary branch distribution density (SBD), and one for the number of spikelets per panicle (NS), respectively. qPLSD-9-1 and qPLSD-9-2 were novel pleiotropic loci, showing effects on PL and SD simultaneously. qPLSD-9-1 explained 34.7% of the phenotypic variation for PL and 25.4% of the phenotypic variation for SD, respec- tively. qPLSD-9-2 explained 34.9% and 24.4% of the phenotypic variation for PL and SD, respectively. The C Bao alleles at the both QTLs showed positive effects on PL, and the Xiushui 79 alleles at the both QTLs showed positive effects on SD. Genetic variation of panicle traits are mainly attributed to additive effects. QTL × environment interactions were not significant for additive QTLs and additive × additive QTL pairs.     

Dynamic Quantitative Trait Loci Analysis of Seed Reserve Utilization during Three Germination Stages in Rice

In this study, one rice population of recombinant inbred lines (RILs) was used to determine the genetic characteristics of seed reserve utilization during the early (day 6), middle (day 10) and late (day 14) germination stages. The seedling dry weight (SDW) and weight of the mobilized seed reserve (WMSR) were increased, while the seed reserve utilization efficiency (SRUE) decreased, during the process of seed germination. The SDW and WMSR were affected by the seed weight, while the SRUE was not affected by the seed weight. A total of twenty unconditional and twenty-one conditional additive QTLs and eight epistatic QTLs were identified at three germination stages, and the more QTLs were expressed at the late germination stage. Among them, twelve additive and three epistatic QTLs for SDW, eight additive and three epistatic QTLs for WMSR and thirteen additive and two epistatic QTLs for SRUE were identified, respectively. The phenotypic variation explained by each additive QTL, epistatic QTL and QTL × development interaction ranged from 6.10 to 23.91%, 1.79 to 6.88% and 0.22 to 2.86%, respectively. Two major additive QTLs qWMSR7.1 and qSRUE4.3 were identified, and each QTL could explain more than 20% of the total phenotypic variance. By comparing the chromosomal positions of these additive QTLs with those previously identified, eleven QTLs might represent novel genes. The best four cross combinations of each trait for the development of RIL populations were selected. The selected RILs and the identified QTLs might be applicable to improve rice seed reserve utilization by the marker-assisted selection approach.     

粳稻穗部结构性状的QTL分析

利用温带粳稻‘沈农265’和‘丽江新团黑谷’构建的重组自交系群体,在沈阳和哈尔滨两地对15个穗部结构性状进行了QTL分析。共检测到61个相关QTL,其中沈阳检测到的38个QTL在第1、4、6、11和12号染色体上形成了sir-QTL簇;而在哈尔滨检测到的31个QTL也在第3、9和10号染色体上形成了QTL簇。仅有8个QTL是在两地同时被检测到的,分别是控制一次枝梗数#＇．jqPBN4、控制穗长的qPL6和qPL9、控制一次枝梗实粒数的qGNPB4、控制一次枝梗颖花数的qTSNPBJ、控制结实率的qPSSIO、以及控制着粒密度qSD3和qSD9。其中,qPBN4（最高表型贡献率43．2％）、qPL9（最高表型贡献率63．2％）、qGNPB4（最高表型贡献率30．9％）和qSD9（最高表型贡献率42．9％）是主效QTL。通过进一步的分析发现控制穗长qPL9和控制着粒密度qSD94于DEPl所在区间。同时控制一次枝梗数和一次枝梗实粒数的位于第4号染色体长臂端的穗部结构主效QTL,qPBN4qGNPB4极富研究与应用价值。     

Seed and agronomic QTL in low linolenic acid, lipoxygenase-free soybean (Glycine max (L.) Merrill) germplasm.

Linolenic acid and seed lipoxygenases are associated with off flavours in soybean products. F5 recombinant inbred lines (RILs) from a cross between a low linolenic acid line (RG10) and a seed lipoxygenase-free line (OX948) were genotyped for simple sequence repeats (SSR), random amplified polymorphic DNA (RAPD), sequence-tagged sites (STS), and cleaved amplified polymorphic sequence (CAPS) markers and evaluated for seed and agronomic traits at 3 Ontario locations in 2 years. One hundred twenty markers covering 1247.5 cM were mapped to 18 linkage groups (LGs) in the soybean composite genetic map. Seed lipoxygenases L-1 and L-2 mapped as single major genes to the same location on LG G13-F. L-3 mapped to LG G11-E. This is the first report of a map position for L-3. A major quantitative trait locus (QTL) associated with reduced linolenic acid content was identified on LG G3-B2. QTLs for 12 additional seed and agronomic traits were detected. Linolenic acid content, linoleic acid content, yield, seed mass, protein content, and plant height QTL were present in at least 4 of 6 environments. Three to 8 QTLs per trait were detected that accounted for up to 78% of total variation. Linolenic acid and lipoxygenase loci did not overlap yield QTL, suggesting that it should be possible to develop high-yielding lines resistant to oxidative degradation by marker-assisted selection (MAS).     

Mapping QTL for growth and shank traits in chickens divergently selected for high or low body weight

An F₂ population (695 individuals) was established from broiler chickens divergently selected for either high (HG) or low (LG) growth, and used to localize QTL for developmental changes in body weight (BW), shank length (SL9) and shank diameter (SD9) at 9 weeks. QTL mapping revealed three genome‐wide QTL on chromosomes (GGA) 2, 4 and 26 and three suggestive QTL on GGA 1, 3 and 5. Most of the BW QTL individually explained 2–5% of the phenotypic variance. The BW QTL on GGA2 explained about 7% of BW from 3 to 7 weeks of age, while that on GGA4 explained 15% of BW from 5 to 9 weeks. The BW QTL on GGA2 and GGA4 could be associated with early and late growth respectively. The GGA4 QTL also had the largest effect on SL9 and SD9 and explained 7% and 10% of their phenotypic variances respectively. However, when SL9 and SD9 were corrected with BW9, a shank length percent QTL was identified on GGA2. We identified novel QTL and also confirmed previously identified loci in other chicken populations. As the foundation population was established from commercial broiler strains, it is possible that QTL identified in this study could still be segregating in commercial strains.     

Construction of microsatellite-based linkage maps and identification of size-related quantitative trait loci for Zhikong scallop (Chlamys farreri)

We constructed the microsatellite-based linkage maps using 318 markers typed in two F₁ outbred families of Zhikong scallop ( Chlamys farreri ). The results showed an extremely high proportion (56.2%) of non-amplifying null alleles and a high ratio (30%) of segregation distortion. By aligning different individual-based linkage maps, 19 linkage groups were identified, which are consistent with the haploid chromosome number of Zhikong scallop. The integrated linkage map contains 154 markers covering 1561.8 cM with an average intermarker spacing of 12.3 cM and 77.0% of genome coverage. We found that the heterogeneity in recombination rate was not determined by sexes but by different individuals on 18 linkage regions. The phenotypic marker of general shell colour was placed on LG4, which was flanked by microsatellite markers CFLD064 and CFBD055 . Four size-related traits including shell length (SL), shell width (SW), shell height (SH) and gross weight (GW) were analysed to identify the putative quantitative trait loci (QTL). Under the half-sib model, using dam as common parent, three, two, two and one QTL affecting SL, SW, SH and GW exceeded the genome-wide thresholds respectively. While using sir as common parent, a larger number of QTL were detected for these four traits: four, five, three and two for SL, SW, SH and GW respectively. The single QTL explained 3.7–19.2% of the phenotypic variation. The linkage map and the QTL associated with economic traits will provide useful information for marker-assisted selection of Zhikong scallop.     

QTL mapping for fiber quality traits across multiple generations and environments in upland cotton

Identification of quantitative trait loci (QTL) for fiber quality traits that are stable across multiple generations and environments could facilitate marker-assisted selection for improving cotton strains. In the present study, F₂, F_2:3, and recombinant inbred lines (RILs, F _6:8 ) populations derived from an upland cotton (Gossypium hirsutum L.) cross between strain 0-153, which has excellent fiber quality, and strain sGK9708, a commercial transgenic cultivar, were constructed for QTL tagging of fiber quality. We used 5,742 simple sequence repeat primer pairs to screen for polymorphisms between the two parent strains. Linkage maps of F₂ and RILs were constructed, containing 155 and 190 loci and with a total map distance of 959.4 centimorgans (cM) and 700.9?cM, respectively. We screened fiber quality QTL across multiple generations and environments through composite interval mapping of fiber quality data. Specifically, we studied F₂ and F_2:3 family lines from Anyang (Henan Province) in 2003 and 2004 and RILs in Anyang in 2007 and Anyang, Quzhou (Hebei Province), and Linqing (Shandong Province) in 2008. We identified 50 QTL for fiber quality: 10 for fiber strength, 10 for fiber length, 10 for micronaire, eight for fiber uniformity, and 12 for fiber elongation. Nine of these fiber quality QTL were identified in F₂, F_2:3 and RILs simultaneously. Two QTL for fiber strength on chromosomes C7 and C25 were detected in all three generations and all four environments and explained 16.67?C27.86% and 9.43?C21.36% of the phenotypic variation, respectively. These stable QTL for fiber quality traits could be used for marker assisted selection.     

Quantitative trait loci mapping in five new large recombinant inbred line populations of Arabidopsis thaliana genotyped with consensus single-nucleotide polymorphism markers

Quantitative approaches conducted in a single mapping population are limited by the extent of genetic variation distinguishing the parental genotypes. To overcome this limitation and allow a more complete dissection of the genetic architecture of complex traits, we built an integrated set of 15 new large Arabidopsis thaliana recombinant inbred line (RIL) populations optimized for quantitative trait loci (QTL) mapping, having Columbia as a common parent crossed to distant accessions. Here we present 5 of these populations that were validated by investigating three traits: flowering time, rosette size, and seed production as an estimate of fitness. The large number of RILs in each population (between 319 and 377 lines) and the high density of evenly spaced genetic markers scored ensure high power and precision in QTL mapping even under a minimal phenotyping framework. Moreover, the use of common markers across the different maps allows a direct comparison of the QTL detected within the different RIL sets. In addition, we show that following a selective phenotyping strategy by performing QTL analyses on genotypically chosen subsets of 164 RILs (core populations) does not impair the power of detection of QTL with phenotypic contributions >7%.     

Classical genetic and quantitative trait loci analyses of heterosis in a maize hybrid between two elite inbred lines

The exploitation of heterosis is one of the most outstanding advancements in plant breeding, although its genetic basis is not well understood yet. This research was conducted on the materials arising from the maize single cross B73 x H99 to study heterosis by procedures of classical genetic and quantitative trait loci (QTL) analyses. Materials were the basic generations, the derived 142 recombinant inbred lines (RILs), and the three testcross populations obtained by crossing the 142 RILs to each parent and their F(1). For seedling weight (SW), number of kernels per plant (NK), and grain yield (GY), heterosis was >100% and the average degree of dominance was >1. Epistasis was significant for SW and NK but not for GY. Several QTL were identified and in most cases they were in the additive-dominance range for traits with low heterosis and mostly in the dominance-overdominance range for plant height (PH), SW, NK, and GY. Only a few QTL with digenic epistasis were identified. The importance of dominance effects was confirmed by highly significant correlations between heterozygosity level and phenotypic performance, especially for GY. Some chromosome regions presented overlaps of overdominant QTL for SW, PH, NK, and GY, suggesting pleiotropic effects on overall plant vigor.     

Interval mapping of QTLs controlling yield-related traits and seed protein content in Pisum sativum

A linkage map of garden pea was constructed on the basis of 114 plants (F2 generation) derived from a cross combination Wt10245 x Wt11238. The map, consisting of 204 morphological, isozyme, AFLP, ISSR, STS, CAPS and RAPD markers, was used for interval mapping of quantitative trait loci (QTLs) controlling seed number, pod number, 1000-seed weight, 1000-yield, and seed protein content. Characterization of each QTL included identification of QTL position with reference to the flanking markers, estimation of the part of variance explained by this QTL, and determination of its gene action. The yield-related traits were measured in F2 plants and in F4 recombinant inbred lines (RILs). The interval mapping revealed two to six QTLs per trait, demonstrating linkage to seven pea chromosomes. A total of 37 detected QTLs accounted for 9.1-55.9% of the trait's phenotypic variation and showed different types of gene action. As many as eight and ten QTLs influencing the analysed traits were mapped in linkage groups III and V, respectively, indicating an important role of these regions of the pea genome in the control of yield and seed protein content.