QTL mapping of fiber quality in an elite hybrid derived-RIL population of upland cotton

Xiangzamian 2 (XZM2) was the most widely cultivated cotton hybrid planted as F₁ hybrids and as selfed F₂ seeds in China before the release of transgenic Bt hybrids. By crossing two parents of XZM2, Gossypium hirsutum cv. Zhongmiansuo12 (ZMS12) and G. hirsutum acc. 8891, and through subsequent selfings, we obtained F₈ and F₉ populations of 180 recombinant inbred lines (RILs). A RIL population was cultivated in two cotton-growing regions in China for 2 years. The purpose of the present research was to detect quantitative trait loci (QTL) for fiber quality and provide information applicable to cotton breeding. A genetic map was constructed mainly using SSR markers. QTL controlling fiber quality traits were determined at the single-locus and two-locus levels, and genotype-by-environment interactions were analyzed. Among the main-effect QTL, a fiber length QTL qFL-D2-1 and a reflectance QTL qFR-D2-1 were simultaneously detected at two growing regions in 2 years, which suggested a high degree of stability in different environments, and might be of particular value for a marker-assisted selection (MAS) program. The results suggested that epistatic effects, as well as additive effects, of QTL play important roles in fiber quality in these RILs. In our research, the phenomenon of QTL clusters was detected in the cotton genome.     

AFLP marker associations with agronomic and fiber traits in cotton

DNA markers linked with major QTL contributing to traits of importance will be a useful tool for cotton (Gossypium spp.) genetics and breeding. We crossed four photoperiod-sensitive accessions of cotton, G. hirsutum L., with a cultivar, selected day-neutral plants and backcrossed four times to each of the four photoperiod-sensitive accessions, selecting day-neutral plants at each generation. The day-neutral plants from the first cross and the four backcross generations were advanced to the F₆. These 20 day-neutral lines and four cultivars were grown in two environments at Mississippi State, MS and scored for seven agronomic and fiber quality traits. They were also scored for AFLP markers using a bulk sample of leaves from each of 24 lines. More than 50 AFLP markers were associated with the seven traits with fewer markers associated with fiber than agronomic traits. However, one to four markers were associated with 22–93% of the phenotypic variability of each of the seven traits. The results suggest that selected markers could be used in marker assisted selection (MAS) in crosses designed to use alleles from exotic accessions or cultivars to develop elite breeding lines for cotton improvement.     

Identification of quantitative trait loci with main and epistatic effects for plant architecture traits in Upland cotton (Gossypium hirsutum L.)

Plant architecture is important for cotton cultivation and breeding. In this study, two mapping generations/populations F₂ and F_2:3 in Upland cotton (Gossypium hirsutum L.), derived from ‘Baimian1’ and TM‐1, were used to identify quantitative trait loci (QTLs) for 10 plant architecture traits. A total of 55 main‐effect QTLs (M‐QTLs) were detected. Four common M‐QTLs, qTFB‐10(F₂/F_2:3) for total fruit branches, qFBL‐26b(F₂)/qFBL‐26(F_2:3) for fruit branch length, qFBA‐5(F₂/F_2:3) for fruit branch angle and qFBN‐26b(F₂)/qFBN‐26(F_2:3) for fruit branch nodes, were found. The synergistic alleles and the negative alleles can be utilized in cotton plant architecture breeding programmes according to specific breeding objectives. Altogether 54 pairs of epistatic QTLs (E‐QTLs) exhibiting the interactions of additive‐by‐additive (AA), additive‐by‐dominant (AD), dominant‐by‐additive (DA) and dominant‐by‐dominant (DD) were detected. The epistasis appeared to be an important contributor to genetic variation in cotton plant architecture traits. Therefore, the identified markers associated with E‐QTLs as well as M‐QTLs will be of importance in future breeding programmes to develop cotton cultivars exhibiting desirable plant architecture.     

Microsatellite markers associated with lint percentage trait in cotton, Gossypium hirsutum

Molecular markers associated with fiber development traits have the potential to play a key role in understanding of cotton fiber development. Seventeen SSRs out of 304 markers tested from MGHES (EST-SSR), JESPR (genomic SSR), and TMB (BAC-derived SSR) collections showed significant linkage associations (using a Kurskal-Wallis non-parametric test) with lint percentage QTL in a set of recombinant inbred cotton lines (RILs) segregating for lint percentage. The permutation test of these potential markers associated with lint percentage QTL(s) determined that 12 SSR markers have stable estimates, exceeding empirically chosen threshold significance values at or above α = 0.01. Interval mapping demonstrated that 9 SSRs with stable critical LOD threshold values at α = 0.01 have significant QTL effect. Multiple QTL-mapping (MQM) revealed that at least, two highly significant fiber development QTLs exist around regions TMB0471 and MGHES–31 (explained about 23–59% of the phenotypic variation of lint percentage) and around markers MGHES–31 and TMB0366 (accounted for 5.4–12.5% phenotypic variation of lint percentage). These markers, in particular fiber-specific EST-SSRs, might be the possible ‘candidate’ loci contributing for fiber development in cotton. BAC-derived SSRs associated with fiber trait are the possible markers that are useful for the identification of physical genomic contigs that contain fiber development genes. Several lint percentage trait associated SSR markers have been located to chromosomes 12, 18, 23, and 26 using deletion analysis in aneuploid chromosome substitution lines. Outcomes of the work may prove useful in understanding and revealing the molecular basis of the fiber development, and the utilization of these markers for development of superior cotton cultivars through marker-assisted selection (MAS) programs. I. Y. Abdurakhmonov and S. Saha contributed equally to the work     

陆地棉早熟基因来源的遗传分析

棉花早熟性相关的性状多为复杂的数量性状,是由多个基因和环境共同作用的结果,其遗传基础研究比较困难。利用连锁作图和关联分析方法,对目标性状进行基因定位,找出与性状相关联的位点,为解析复杂性状的基因来源提供了新的手段。本文分别以早熟亲本新陆早8号和新陆早10号为母本,以陆地棉标准系TM-1为父本构建F₂作图群体,利用在亲本间筛选出的多态性SSR引物,通过JoinMap 3.0软件构建了2张遗传图谱,以Win QTLCart 2.5复合区间作图法在F₂~F_2:3中定位到控制全生育期、苗期、蕾期、花铃期和霜前铃数等早熟性相关性状的37个QTL。控制早熟性的有利等位基因多来自早熟祖先611波和金字棉。多数性状在两类材料中由不同的基因控制,且以加性遗传为主。在由43个陆地棉品种材料构成的自然群体中通过关联分析检测到54个与这些早熟性相关性状极显著关联的位点。研究表明连锁作图和关联分析的检测结果具有较高的可比性。本研究为早熟陆地棉聚合改良以及分子标记辅助育种打下了基础。     

Marker-assisted selection of Verticillium wilt resistance in progeny populations of upland cotton derived from mass selection-mass crossing

Two progeny populations of upland cotton derived from mass selection-mass crossing, M₃S₂F₅ and its family lines M₃S₂F_5:6, were generated from 17 hybrid cotton lines derived from regional trials conducted in the Yellow River basin and Yangtze River basin in China. These populations were used to verify 39 reported molecular markers that were related to quantitative trait loci (QTLs) for Verticillium wilt resistance of cotton. Only 12 of 39 markers were polymorphic; 19 had no polymorphisms, and amplification failed for eight markers. The differences in disease grades of aa/AA genotype individuals for five markers, BNL3241, NAU1225, NAU1230, JESPR153, and BNL3031, reached either significant or highly significant levels in at least one population. These markers can thus be effectively used for marker-assisted selection (MAS) of the target trait. Especially for JESPR153 and BNL3031, the differences in disease grades of aa/AA genotype individuals both reached either significant or highly significant levels in the two populations. These two markers should be given preferential consideration when undertaking MAS. The two flanking markers were more effective than the single flanking marker for MAS of single-loci QTL. The selection effect will be greatly enhanced through a reasonable allocation of marker combinations for multi-locus QTL polymerization. When using multi-locus markers for multi-locus QTL-assisted polymerization breeding, the selection effect can be improved progressively by increasing the number of polymerization markers. The possible interaction of different QTLs or genetic backgrounds does not influence the selection effect. A combination of resistant genotypes and disease grade performance enabled final selection of three individuals resistant to Verticillium wilt.     

Genetic mapping of quantitative trait loci for fiber quality and yield trait by RIL approach in Upland cotton

The improvement of cotton fiber quality has become more important because of changes in spinning technology. Stable quantitative trait loci (QTLs) for fiber quality will enable molecular marker-assisted selection to improve fiber quality of future cotton cultivars. A simple sequence repeat (SSR) genetic linkage map consisting of 156 loci covering 1,024.4 cM was constructed using a series of recombinant inbred lines (RIL) developed from an F₂ population of an Upland cotton (Gossypium hirsutum L.) cross 7235 × TM-1. Phenotypic data were collected at Nanjing and Guanyun County in 2002 and 2003 for 5 fiber quality and 6 yield traits. We found 25 major QTLs (LOD ≥ 3.0) and 28 putative QTLs (2.0 < LOD < 3.0) for fiber quality and yield components in two or four environments independently. Among the 25 QTLs with LOD ≥ 3, we found 4 QTLs with large effects on fiber quality and 7 QTLs with large effects on yield components. The most important chromosome D8 in the present study was densely populated with markers and QTLs, in which 36 SSR loci within a chromosomal region of 72.7 cM and 9 QTLs for 8 traits were detected.     

Identification of quantitative trait loci across interspecific F2, F2:3 and testcross populations for agronomic and fiber traits in tetraploid cotton

The most widely grown tetraploid Gossypium hirsutum and G. barbadense differ greatly in yield potential and fiber quality and numerous quantitative trait loci (QTLs) have been reported. However, correspondence of QTLs between experiments and populations is poor due to limited number of markers, small population size and inaccurate phenotyping. The purpose of the present study was to map QTLs for yield, yield components and fiber quality traits using testcross progenies between a large interspecific F₂ population and a commercial cotton cultivar as the tester. The results were compared to these from its F₂ and F_2:3 progenies. Of the 177 QTLs identified from the three populations, 65 fiber QTLs and 51 yield QTLs were unique with an average of 8–12 QTLs per traits. All the 26 chromosomes carried QTLs, but differed in the number of QTLs and the number of QTLs between fiber and yield QTLs. The congruence of QTLs identified across populations was higher (20–60 %) for traits with higher heritabilities including fiber quality, seed index and lint percentage, but lower (10–25 %) for lower heritability traits-seedcotton and lint yields. Major QTLs, QTL clusters for the same traits and QTL ‘hotspots’ for different traits were also identified. This research represents the first report using a testcross population in QTL mapping in interspecific cotton crosses and provides useful information for further comparative analysis and marker-assisted selection.     

Identifying QTL for fiber quality traits with three upland cotton (Gossypium hirsutum L.) populations

Cotton fiber quality was quantitative trait, controlled by multiple genes. Identification of stable quantitative trait loci (QTL) effectively contributing to favorable fiber quality traits would provide the key basis for marker-assisted selection used in molecular breeding projects. Three upland cotton F₂ populations were established with a common parent Chinese cultivar Yumian 1 and three American commercial cultivars/lines (Acala Maxxa, CA3084 and TAM94L-25), each of which had unique fiber quality characteristic that was favorable economically. Three whole genome genetic maps were constructed with 323, 302 and 262 SSR loci for population (Yumian 1 × Acala Maxxa), (Yumian 1 × CA3084), and (Yumian 1 × TAM 94L-25) respectively, spanning 1,617.2, 1,639.9 and 1,441.4 cM. Based on these genetic maps and three generation phenotypic data of fiber quality traits (F₂, F_2:3 and F_2:4), 77 QTL were detected, including 19 for fiber length, 14 for fiber uniformity, 17 for micronaire, 10 for fiber elongation, and 17 for fiber strength. Among these QTL, 46 QTL were significant QTL and 31 were putative QTL, including that one QTL (qFL05.1) and four QTL (qFL23.1, qFM06.1, qFM06.2 and qFE25.1) were detected across three and two populations respectively; two QTL qFL10.1 (Yumian 1 × TAM 94L-25) and qFL15.1 (Yumian 1 × Acala Maxxa) were detected in three generations; qFM23.1, qFE18.1 and qFS21.2 detected in population (Yumian 1 × CA3084), qFE10.1, and qFS10.2 detected in population (Yumian 1 × TAM 94L-25), and qFS15.1 detected in population (Yumian 1 × Acala Maxxa), were all detected in two generations. Alleles underlying these stable QTL were valuable candidate gene for fine mapping, cloning, and favorable gene pyramiding projects. Our study also verified that QTL mapping of fiber quality traits using multiple populations with a common parent had higher efficiency compared to single population crossed with two parents and favorable alleles contributed to QTL effect could be conferred by parents with inferior fiber quality traits.     

Identification of QTLs for fruit quality traits in Japanese apples: QTLs for early ripening are tightly related to preharvest fruit drop

Many important apple (Malus × domestica Borkh.) fruit quality traits are regulated by multiple genes, and more information about quantitative trait loci (QTLs) for these traits is required for marker-assisted selection. In this study, we constructed genetic linkage maps of the Japanese apple cultivars ‘Orin’ and ‘Akane’ using F₁ seedlings derived from a cross between these cultivars. The ‘Orin’ map consisted of 251 loci covering 17 linkage groups (LGs; total length 1095.3 cM), and the ‘Akane’ map consisted of 291 loci covering 18 LGs (total length 1098.2 cM). We performed QTL analysis for 16 important traits, and found that four QTLs related to harvest time explained about 70% of genetic variation, and these will be useful for marker-assisted selection. The QTL for early harvest time in LG15 was located very close to the QTL for preharvest fruit drop. The QTL for skin color depth was located around the position of MYB1 in LG9, which suggested that alleles harbored by ‘Akane’ are regulating red color depth with different degrees of effect. We also analyzed soluble solids and sugar component contents, and found that a QTL for soluble solids content in LG16 could be explained by the amount of sorbitol and fructose.     

QTL mapping for agronomic and fibre traits using two interspecific chromosome substitution lines of Upland cotton

CS‐B14Sh and CS‐B22Sh are cotton interspecific chromosome substitution (CS)‐B lines, in which a pair of short arms of chromosome 14 and chromosome 22 were introgressed from Gossypium barbadense doubled‐haploid line 3‐79 with the background of Gossypium hirsutum line TM‐1, respectively. These two CS‐B lines were crossed with TM‐1, and segregating progenies (F₂ and F_2:3, respectively) were obtained. Phenotypic data of lint yield, yield‐related traits and fibre‐quality traits were collected from two trials. In the cross CS‐B14SH X TM‐1, QTL for boll weight (BW), lint percentage (LP), fibre upper half mean length (UHML), micronaire reading (MIC), and fibre breaking tensile strength (STR) were repeatedly detected. Alleles from 3‐79 decreased BW and MIC, but increased UHML and STR. In the cross CS‐B22Sh X TM‐1, QTL for BW, LP, UHML, MIC, STR, fibre elongation (EL),seed weight(SW), node of first fruiting branch (NFB) and fibre uniformity index (UI) were repeatedly detected, and alleles from 3‐79 decreased UHML, UI and STR, but increased NFB, SW, MIC and EL. QTL clusters were found in both populations.     

Evaluation of the effects of five QTL regions on Fusarium head blight resistance and agronomic traits in spring wheat (Triticum aestivum L.)

Fusarium head blight (FHB) is an important disease of wheat (Triticum aestivum L.). The aim of this study was to determine the effects of quantitative trait locus (QTL) regions for resistance to FHB and estimate their effects on reducing FHB damage to wheat in Hokkaido, northern Japan. We examined 233 F₁-derived doubled-haploid (DH) lines from a cross between ‘Kukeiharu 14’ and ‘Sumai 3’ to determine their reaction to FHB during two seasons under field conditions. The DH lines were genotyped at five known FHB-resistance QTL regions (on chromosomes 3BS, 5AS, 6BS, 2DL and 4BS) by using SSR markers. ‘Sumai 3’ alleles at the QTLs at 3BS and 5AS effectively reduced FHB damage in the environment of Hokkaido, indicating that these QTLs will be useful for breeding spring wheat cultivars suitable for Hokkaido. Some of the QTL regions influenced agronomic traits: ‘Sumai 3’ alleles at the 4BS and 5AS QTLs significantly increased stem length and spike length, that at the 2DL QTL significantly decreased grain weight, and that at the 6BS QTL significantly delayed heading, indicating pleiotropic or linkage effects between these agronomic traits and FHB resistance.     

Quantitative analysis and QTL mapping for agronomic and fiber traits in an RI population of upland cotton

Genetic mapping is an essential tool for cotton (Gossypium hirsutum L.) molecular breeding and application of DNA markers for cotton improvement. In this present study, we evaluated an RI population including 188 RI lines developed from 94 F₂-derived families and their two parental lines, ‘HS 46’ and ‘MARCABUCAG8US-1-88’, at Mississippi State, MS, for two years. Fourteen agronomic and fiber traits were measured. One hundred forty one (141) polymorphic SSR markers were screened for this population and 125 markers were used to construct a linkage map. Twenty six linkage groups were constructed, covering 125 SSR loci and 965 cM of overall map distance. Twenty four linkage groups (115 SSR loci) were assigned to specific chromosomes. Quantitative genetic analysis showed that the genotypic effects accounted for more than 20% of the phenotypic variation for all traits except fiber perimeter (18%). Fifty six QTLs (LOD > 3.0) associated with 14 agronomic and fiber traits were located on 17 chromosomes. One QTL associated with fiber elongation was located on linkage group LGU01. Nine chromosomes in sub-A genome harbored 27 QTLs with 10 associated with agronomic traits and 17 with fiber traits. Eight chromosomes in D sub-genome harbored 29 QTLs with 13 associated with agronomic traits and 16 with fiber traits. Chromosomes 3, 5, 12, 13, 14, 16, 20, and 26 harbor important QTLs for both yield and fiber quality compared to other chromosomes. Since this RI population was developed from an intraspecific cross within upland cotton, these QTLs should be useful for marker assisted selection for improving breeding efficiency in cotton line development. Paper number J1116 of the Mississippi Agricultural and Forestry Experiment Station, Mississippi State University, Mississippi State, MS 39762. Mention of trademark, proprietary product, or vendor does not constitute a guarantee or warranty of the product by USDA, ARS and does not imply its approval to the exclusion of other products or vendors that may also be suitable.     

New QTLs for lint percentage and boll weight mined in introgression lines from two feral landraces into Gossypium hirsutum acc TM‐1

Overuse of a small number of Upland cotton cultivars has narrowed cotton's genetic base, leading to major difficulties in developing cotton cultivars with diverse genetic backgrounds that are able to adapt to adverse conditions. To effectively broaden the genetic base, chromosome introgression lines (ILs) were developed, where TM‐1, the genetic standard of Upland cotton, was used as the common recipient and its two feral landraces, TX‐256 and TX‐1046, were used as the donors. A total of 115 ILs, with an average segment length of 11.15 cM, were first developed via intraspecific hybridization by marker‐assisted selection (MAS) in BC₃F₂ generations, spanning 3887.75 cM of the cotton genome. Association analysis showed that 63 markers were found to be associated with boll weight (BW), lint percentage (LP) and seed index. The percent of phenotypic variance explained by 148 QTLs detected was 4.12% on average. Eleven and five new QTLs for BW and LP (one stable QTL identified for LP in all environments) were detected, respectively, which can be used for efficiently pyramiding favourable alleles into one cultivar by MAS.     

Quantitative trait loci for agronomic and seed quality traits in an F2 and F4:6 soybean population

Molecular breeding is becoming more practical as better technology emerges. The use of molecular markers in plant breeding for indirect selection of important traits can favorably impact breeding efficiency. The purpose of this research is to identify quantitative trait loci (QTL) on molecular linkage groups (MLG) which are associated with seed protein concentration, seed oil concentration, seed size, plant height, lodging, and maturity, in a population from a cross between the soybean cultivars ‘Essex’ and ‘Williams.’ DNA was extracted from F₂ generation soybean leaves and amplified via polymerase chain reaction (PCR) using simple sequence repeat (SSR) markers. Markers that were polymorphic between the parents were analyzed against phenotypic trait data from the F₂ and F_4:6 generation. For the F₂ population, significant additive QTL were Satt540 (MLG M, maturity, r² = 0.11; height, r² = 0.04, seed size, r²= 0.06], Satt373 (MLG L, seed size, r² = 0.04; height, r² = 0.14), Satt50 (MLG A1, maturity r² = 0.07), Satt14 (MLG D2, oil, r² = 0.05), and Satt251 (protein r² = 0.03, oil, r² =0.04). Significant dominant QTL for the F₂ population were Satt540 (MLG M,height, r² = 0.04; seed size, r² = 0.06) and Satt14 (MLG D2, oil, r² = 0.05). In the F_4:6 generation significant additive QTL were Satt239 (MLGI, height, r² = 0.02 at Knoxville, TN and r² = 0.03 at Springfield, TN), Satt14 (MLG D2, seed size, r² = 0.14 at Knoxville, TN), Satt373 (MLG L, protein, r² = 0.04 at Knoxville, TN) and Satt251 (MLG B1, lodging r² = 0.04 at Springfield, TN). Averaged over both environments in the F_4:6 generation, significant additive QTL were identified as Satt251 (MLG B1, protein, r² = 0.03), and Satt239 (MLG I, height, r² = 0.03). The results found in this study indicate that selections based solely on these QTL would produce limited gains (based on low r² values). Few QTL were detected to be stable across environments. Further research to identify stable QTL over environments is needed to make marker-assisted approaches more widely adopted by soybean breeders. This revised version was published online in July 2006 with corrections to the Cover Date.     

QTL analyses of complex traits with cross validation, bootstrapping and other biometric methods

With the development of molecular markers, dissection of complex quantitative traits by mapping the underlying genetic factors has become a major research area in plant breeding. Here, we report results from a vast QTL mapping experiment in maize with testcrosses of N= 976 F_4:5 lines evaluated in E= 16 environments. Although the number of detected QTL confirmed the infinitesimal model of quantitative genetics (e.g., 30 QTL detected with LOD ≥ 2.5 for plant height, explaining p= 61% of the genetic variance), cross validation (CV) still revealed an upward bias of about 10% in p. With smaller values of N (122, 244, 488) and E (2, 4), the number of detected QTL decreased, but the estimates of p remained almost the same due to a tremendous increase in the bias. This illustrates that QTL effects obtained from smaller sample sizes are usually highly inflated, leading to an overly optimistic assessment of the prospects of MAS. Moreover, inferences about the genetic architecture (number of QTL and their effects) of complex traits cannot be achieved reliably with smaller sample sizes. Based on simulations, we conclude that CV and one method of bootstrapping (BS) performed well with regard to yielding realistic estimates of p. In addition, we briefly review progress in new biometric methods and approaches to QTL mapping in plants including Bayesian methods that show great promise to overcome the present limitations of QTL mapping. This revised version was published online in July 2006 with corrections to the Cover Date.     

New quantitative trait loci for enhancing adaptation to salinity in rice from Hasawi,a Saudi landrace into three African cultivars at the reproductive stage

Salinity is a major constraint affecting rice productivity in rainfed and irrigated agro-ecosystems. Understanding salinity effects on rice production at the reproductive stage could improve adaptation for this trait. Identifying quantitative trait loci (QTLs) controlling adaptation to salinity may also accelerate breeding rice germplasm for environments prone to this stress. We used the salt tolerant landrace ‘Hasawi’ as a donor parent to generate three F₂ offspring (consisting each of 500 individuals) with three African cultivars (‘NERICA-L-19’, ‘Sahel 108’ and ‘BG90-2’) used as recipient parents (RP). The F₂s and F_2:3s were evaluated for grain yield and other traits in saline fields. Salinity caused reduction in all measured traits across the F₂-derived offspring, e.g. grain yield reduced between 65 and 73 %, but some offspring had twice the RP’s grain yield. QTL analysis revealed 75 QTLs for different traits in all 3 genetic backgrounds (GBs): 24 of them were common among all the 3 GBs while 31 were noted in 2 GBs, and 17 in one GB. ‘Hasawi’ contributed on average 49 % alleles to these QTLs. Two yield and yield related QTLs (qGY11 and qTN11) common in all 3 GBs were mapped on the same chromosomal segment suggesting these QTLs might be stable across different GBs. Four other QTLs were strongly associated with salinity tolerance with peak marker RM419, representing a potential candidate for MAS due to high LOD score and relatively large effect QTLs.     

Dynamic QTL mapping for plant height in Upland cotton (Gossypium hirsutum)

Plant height served as one of model traits to analyse dynamic development. The objective of this research was to investigate quantitative trait loci (QTL) and dynamic QTL for plant height trait using an intraspecific recombinant inbred line (RIL) population and a constructed genetic map in Upland cotton (Gossypium hirsutum L.). Totally, 41 QTL and 23 conditional QTL controlling plant height were detected at two experimental environments, respectively. Four stable QTL were identified simultaneously in both environments. Some QTL identified at the early stage could not be detected at the final stage at plant maturity. Conditional QTL with different genetic effects were identified at certain stages, demonstrating that the expression of QTL had temporal characteristic during plant growth. Therefore, the study of dynamic QTL could unravel temporal genetic patterns controlling complex developmental quantitative traits.     

Dent corn genetic background influences QTL detection for grain yield and yield components in high-oil maize

Despite the well-recognized importance of grain yield in high-oil maize (Zea mays L.) breeding and production, few studies have reported the application of QTL mapping of such traits. An inbred line of high-oil maize designated ‘GY220’ was crossed with two dent maize inbred lines to generate two connected F_2:3 populations with 284 and 265 F_2:3 families. Our main objective was to evaluate the influence of genetic background on QTL detection of grain yield traits through comparisons between the F_2:3 populations. The field experiments were conducted during the spring in Luoyang and summer in Xuchang, Henan, China. Two genetic linkage maps were constructed with a genetic distance of 2111.7 and 2298.5 cM using 185 and 173 polymorphic SSR markers, respectively. In total, 18 and 15 QTL were detected for six grain yield traits in the two populations. Only one common QTL marker was shared between the two populations. A QTL cluster associated with five traits was identified at bin 1.05–1.06, including the shared QTL for 100GW, which demonstrated the largest effect (16.7%). Among the detected QTL, 12 digenic interactions were identified. Our results reflect the substantial influence of dent maize genetic background on QTL detection of grain yield traits.     

Participatory selection assisted by DNA markers for enhanced drought resistance and productivity in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

In this study, a F₂ population derived from the cross between deep-rooted variety “Moroberekan” with shallow-rooted variety “IR20” were used to identify and validate of SSR markers associated with root morphological traits. The F₂ lines were divided into two groups. In the first group, 152 seedling having minimum of four tillers were chosen and separated into four plantlets to plant them in polyvinyl chloride pipes for root study under well-watered (WW) condition at maturity stage. The lines were genotyped using SSR markers. QTLs for maximum root length (MRL) and root dry weight showed co-segregation with RM472, RM7 and RM201. The same material was forwarded to next generation (F₃) to validate the linked markers under both WW and low-moisture stress (LMS) conditions. These three markers were associated consistently with MRL across generations. In the second group, 1240 F₂ plants were forwarded to F₅ using SSD breeding method to test the effectiveness of the marker-assisted selection (MAS) method for drought resistant. The high performing genotypic group was significantly superior to low performing genotypic group for MRL, grain yield, root volume, root dry weight and root number, indicating the efficiency of MAS for root-related traits under LMS. Comparing MAS with farmer selection in F₆, the results showed that MAS group means were significantly different from farmer group means for MRL, root volume, root dry weight and root number. Thus, MAS was combined with participatory selection to select five high-yielding and deep rooted promising lines. Identification of stable QTL for root morphological traits under WW and LMS conditions can aid in MAS and to introduce them into varieties with good yield potential and accepted by farmer.