QTL mapping analysis of plant height and ear height of maize (Zea mays L.)

Genetic map containing 103 microsatellite loci obtained on 200 F2 plants derived from the cross R15 x 478 was used for quantitative trait loci (QTL) mapping in maize. QTL were characterized in a population of 200 F2:4 lines, derived from selfing the F2 plants, and were evaluated with two replications in two environments. QTL determinations were made from the mean of these two environments. Plant height (PH) and ear height (EH) were measured. Using composite interval mapping (CIM) method, a total of 14 distinct QTLs were identified: nine for PH and five for EH. Additive, partial dominance, dominance, and overdominance actions existed among all detected QTL affecting plant height and ear height. The QTL explained 78.27% of the phenotypic variance of PH and 41.50% of EH. The 14 QTLs displayed mostly dominance or partial dominance gene action and mapped to chromosomes 2, 3, 4, 8 and 9.     

Molecular mapping in tropical maize (Zea mays L.) using microsatellite markers. 2. Quantitative trait loci (QTL) for grain yield, plant height, ear height and grain moisture

A previous genetic map containing 117 microsatellite loci and 400 F(2) plants was used for quantitative trait loci (QTL) mapping in tropical maize. QTL were characterized in a population of 400 F(2:3) lines, derived from selfing the F(2) plants, and were evaluated with two replications in five environments. QTL determinations were made from the mean of these five environments. Grain yield (GY), plant height (PH), ear height (EH) and grain moisture (GM) were measured. Variance components for genotypes (G), environments (E) and GxE interaction were highly significant for all traits. Heritability was 0.69 for GY, 0.66 for PH, 0.67 for EH and 0.23 for GM. Using composite interval mapping (CIM), a total of 13 distinct QTLs were identified: four for GY, four for PH and five for EH. No QTL was detected for GM. The QTL explained 32.73 % of the phenotypic variance of GY, 24.76 % of PH and 20.91 % of EH. The 13 QTLs displayed mostly partial dominance or overdominance gene action and mapped to chromosomes 1, 2, 7, 8 and 9. Most QTL alleles conferring high values for the traits came from line L-14-4B. Mapping analysis identified genomic regions associated with two or more traits in a manner that was consistent with correlation among traits, supporting either pleiotropy or tight linkage among QTL. The low number of QTLs found, can be due to the great variation that exists among tropical environments.     

Influence of dent corn genetic backgrounds on QTL detection for plant-height traits and their relationships in high-oil maize

QTL mapping for plant-height traits has not been hitherto reported in high-oil maize. A high-oil maize inbred ‘GY220’ was crossed with two dent maize inbreds (‘8984’ and ‘8622’) to generate two connected F_2:3 populations. Four plant-height traits were evaluated in 284 and 265 F_2:3 families. Single-trait QTL mapping and multiple-trait joint QTL mapping was used to detect QTLs for the traits and the genetic relationship between plant height (PH) and two other plant-height traits. A total of 28 QTLs and 12 pairs of digenic interactions among detected QTLs for four traits were detected in the two F_2:3 families. Only one marker was shared between the two populations. Joint analysis of PH with ear height (EH) and PH with top height (TH) detected 32 additional QTLs. Our results showed that QTL detection for PH was dependent on the genetic background of dent corn inbreds. Multiple-trait joint QTL analysis could increase the number of detected QTLs.     

玉米株高和穗位高的QTL定位

摘要: 用玉米自交系掖478和丹340构建了397个F_2:3家系群体, 利用双亲间多态的150个共显性SSR标记绘制分子连锁图谱, 图谱总长度1 478.7 cM, 标记间平均距离10.0 cM。在5种环境下对株高和穗位高性状进行鉴定, 复合区间作图法检测到21个株高QTL和25个穗位高QTL。于第1和5染色体的umc2025－umc1035及umc1822－bnlg1118区域检测到平均贡献率分别为12.2%和14.9%的株高QTL。于第3和5染色体的phi029－umc1102及phi109188－bnlg1118区域检测到平均贡献率达到10.2%和22.8%的穗位高QTL。第5染色体的Bin5.05－5.07区域可能存在控制株高和穗位高的主效QTL。株高和穗位高的基因作用方式主要是加性和部分显性效应。文章还分析了群体大小及试验环境对株高和穗位高QTL定位结果的影响     

Cytonuclear epistatic quantitative trait locus mapping for plant height and ear height in maize

Plant height (PH) and ear height (EH) are important traits in maize (Zea mays L.) breeding. Previous research has indicated that these traits are influenced by quantitative trait loci (QTL). However, previous studies attempting to identify the genetic bases of PH and EH have ignored the possibility that cytoplasmic effects and cytonuclear interactions may influence these traits. The objectives of this study were to identify the cytonuclear epistatic QTL and to evaluate the contributions of cytoplasm and QTL × cytoplasm interactions to phenotypic variation of PH and EH. A reciprocal mating design was conducted to generate F2 mapping populations comprising 120 F2 plants from the direct cross (JB × Y53) and 120 F2 plants from the reciprocal cross (Y53 × JB). F2:3 mapping populations were further generated with 91 direct F2:3 families and 120 reciprocal F2:3 families (ten plants per family). The PH and EH of the above F2 and F2:3 mapping populations were evaluated in the same field at the same experimental station in 2007 and 2008. A genetic linkage map with 154 microsatellite markers was constructed, which covered 1,735.0 cM of the maize genome with an average marker spacing of 11.3 cM. A joint-analysis method incorporating the cytonuclear interaction mapping approach was proposed and performed to detect cytonuclear interacting QTL affecting PH and EH. We identified six cytonuclear epistatic QTL affecting PH and five affecting EH. The average phenotypic variance explained by the genetic components of the QTL × cytoplasm interaction for each QTL was 18 % for PH and 9 % for EH. In addition, we observed cytoplasmic effects contributing substantially to phenotypic variance, reaching 9 and 40 % of the phenotypic contributions to PH and EH, respectively.     

Genetic mapping and QTL analysis for yield and agronomic traits with an F2:3 population derived from a waxy corn × sweet corn cross

We constructed a framework map using SSR markers in the F₂ population derived from a cross between a waxy corn inbred line and a sweet corn inbred line. We constructed a genetic linkage map of the F_2:3 population employing 295 SSR markers on 158 F₂ individuals produced from the cross. The map comprised a total genomic length of 2,626.5 cM in 10 linkage groups and an average distance between markers of 8.9 cM. The number of loci per linkage group ranged from 27 (chr. 5) to 34 (chr. 7). The genetic distance per linkage group ranged from 213.6 cM (chr. 10) to 360.6 cM (chr. 2). Χ ² tests revealed that 254 markers (86.1 %) distributed over all 10 chromosomes exhibited a Mendelian segregation ratio of 1:2:1. A total of 14 quantitative trait loci (QTLs) for days to silking (DTS), plant height (PH), ear height (EH), ear height ratio (ER), ear length (L-ear), and setted ear length (L-sear) were found in the 158 F₂ progeny. They were mapped to chromosomes 1, 2, 3, 7, 8, and 10. Among them, one QTL was associated with DTS, three with PH, six with EH, one with ER, two with L-ear, and one QTL was related to L-sear. In our study, we found that four QTLs: qDTS1, qEH1a, qEH1b, and qPH1, were clustered between umc2390 and umc1603 on chromosome 1. These new QTLs identified by the present study could serve as useful molecular markers in selecting for yield and agronomic traits in maize. The results of this study may improve the identification and characterization of genes responsible for yield and agronomic traits in waxy corn and sweet corn.     

Detection of quantitative trait loci on chromosome 5R of rye (Secale cereale L.)

 Progenies of an F₂ mapping population were analyzed for quantitative traits to detect QTLs by using marker information from F₂ plants for chromosome 5R. The mapping population was segregating for the major dwarfing gene Ddw1 and the gene Hp1 for hairy peduncle. The only QTL determining plant height was located between HP1 and Ddw1 on the distal part of chromosome 5RL. At the same position a QTL for peduncle length was found, and this trait was closely related to plant height (r=0.895). Since Hp1 and Ddw1 are dominant marker loci, no dominance effect could be estimated. The QTLs for spike length and the number of florets were located near the centromere on 5RL. These two traits were correlated with r=0.824 and showed partial dominance, but these traits were not correlated to plant height and peduncle length. Homoeologous relationships between the QTLs mapped for the first time in rye and those mapped in other Triticeae members are discussed. Received: 8 June 1998 / Accepted: 8 October 1998     

Quantitative trait loci for panicle size, heading date and plant height co-segregating in trait-performance derived near-isogenic lines of rice (Oryza sativa)

Near-isogenic lines (NILs) are ideal materials for precise estimation of quantitative trait loci (QTL) effects and map-based gene isolation. With the completion of the rice genome sequence, QTL isolation based on NILs is becoming a routine. In this study, a trait-performance derived NIL strategy was adopted to develop NILs. Two plants were identified within one inbred line of recombinant inbred lines (RILs, F₇ generation), exhibiting a significant difference in panicle size. By marker screening of the whole genome the genetic background of the two plants was estimated to be 98.7% identical. These two plants were selected as parents to produce a near-isogenic F₂ (NIL-F₂) population, consisting of 125 individuals, in which spikelets per panicle (SPP), grains per panicle (GPP), heading date (HD) and plant height (PH) were recorded. These four traits expressed discontinuous or bimodal distribution in the NIL-F₂ population and followed the expected segregation ratios for a single Mendelian factor by progeny tests. A partial dominant QTL for the four traits was mapped to the same interval flanked by RM310 and RM126 on chromosome 8. The QTL region explained 83.0, 80.2, 94.9 and 93.8% of trait variation of SPP, GPP, HD and PH in the progenies, respectively. Progeny tests also confirmed co-segregation of QTL for the four traits, tall plants consistently flowering late and carrying large panicles. Different NILs development strategies are discussed.     

The genetic relationship among plant-height traits found using multiple-trait QTL mapping of a dent corn and popcorn cross.

Plant height (PH) is one of the most important traits in maize breeding programs. In popcorn, inferior plant traits can be improved with the dent/flint corn germplasm. In the current study, a total of 259 F2:3 families, developed from a cross between a dent corn inbred and a popcorn inbred, were evaluated for 4 PH traits. Quantitative trait loci (QTLs) for each trait were detected using composite interval mapping methods. In addition, genetic interrelationships were investigated using multiple-trait joint analysis for PH with ear height (EH), and for PH with top height (TH). In total, 6, 5, 2, and 6 QTLs were identified for PH, EH, TH, and TH/PH in single-trait analysis, respectively. Joint-analysis data suggest a strong and complex genetic relationship between PH and EH, and between PH and EH, with no QTLs controlling any single trait independently. In addition, 4 kinds of QTLs detected were classified as closely linked QTLs, pleiotropic QTLs, QTLs with opposite effects, and additional QTLs. It was, consequently, difficult to improve lodge resistance through selection on any individual PH trait. The current study demonstrates that multiple-trait joint analysis not only identified additional QTLs, but also revealed the genetic relationship among different highly correlated traits at the molecular level.     

Genetic mapping in maize with hybrid progeny across testers and generations: plant height and flowering

DNA markers were used to identify quantitative trait loci (QTLs) for plant height, ear height, and three flowering traits in hybrid progeny of two generations (F_2:3, F_6:8) of lines from a Mo17×H99 maize population. For both generations, testcross (TC) progeny were developed by crossing the lines to three inbred testers (B91, A632, B73). The hybrid progeny from the two generations were evaluated at the same locations but in different years as per an early generation testing program. QTLs were identified within each TC population and for mean testcross (MTC) performance. Overall, more QTLs were detected in the F_6:8 than the F_2:3 generation. Totalled over all five traits, 41 (B91) to 69% (B73) of the QTLs for tester effects and 67% of the QTLs for MTC detected in the F_2:3 generation were verified in the F_6:8 generation. Although differences in relative rank of the QTL effects across generations were observed, especially for the flowering traits, parental contributions were nearly always consistent. Several (8–11) QTLs were identified with effects for all three tester populations and for all traits except the anthesis-silk interval, which had only two such regions. Over all five traits, previous evaluations in this population identified 26 QTLs with consistent effects for two (F_2:3, F_6:8) inbred-progeny evaluations, and 20 (77%) were also associated with MTC in at least one of the generations evaluated herein. In all instances of common inbred and TC QTLs, parental contributions were the same. Received: 26 November 1999 / Accepted: 18 April 2000     

QTL x environment interactions in rice. I. heading date and plant height

One hundred twenty six doubled-haploid (DH) rice lines were evaluated in nine diverse Asian environments to reveal the genetic basis of genotype × environment interactions (GEI) for plant height (PH) and heading date (HD). A subset of lines was also evaluated in four water-limited environments, where the environmental basis of G × E could be more precisely defined. Responses to the environments were resolved into individual QTL × environment interactions using replicated phenotyping and the mixed linear-model approach. A total of 37 main-effect QTLs and 29 epistatic QTLs were identified. On average, these QTLs were detectable in 56% of the environments. When detected in multiple environments, the main effects of most QTLs were consistent in direction but varied considerably in magnitude across environments. Some QTLs had opposite effects in different environments, particularly in water-limited environments, indicating that they responded to the environments differently. Inconsistent QTL detection across environments was due primarily to non- or weak-expression of the QTL, and in part to significant QTL × environment interaction effects in the opposite direction to QTL main effects, and to pronounced epistasis. QTL × environment interactions were trait- and gene-specific. The greater GEI for HD than for PH in rice were reflected by more environment-specific QTLs, greater frequency and magnitude of QTL × environment interaction effects, and more pronounced epistasis for HD than for PH. Our results demonstrated that QTL × environment interaction is an important property of many QTLs, even for highly heritable traits such as height and maturity. Information about QTL × environment interaction is essential if marker-assisted selection is to be applied to the manipulation of quantitative traits.Communicated by G. Wenzel     

Identification of quantitative trait loci and epistatic interactions for plant height and heading date in rice

Appropriate heading date and plant height are prerequisites for attaining the desired yield level in rice breeding programs. In this study, we analyzed the genetic bases of heading date and plant height at both single- locus and two-locus levels, using a population of 240 F_2:3 families derived from a cross between two elite rice lines. Measurements for the traits were obtained over 2 years in replicated field trials. A linkage map was constructed with 151 polymorphic marker loci, based on which interval mapping was performed using Mapmaker/QTL. The analyses detected six QTLs for plant height and six QTLs for heading date; collectively the QTLs for heading date accounted for a much greater amount of phenotypic variation than did the QTLs for plant height. Two-way analyses of variance, with all possible two-locus combinations, detected large numbers (from 101 to 257) of significant digenic interactions in the 2 years for both traits involving markers distributed in the entire genome; 22 and 39 were simultaneously detected in both years for plant height and heading date, respectively. Each of the interactions individually accounted for only a very small portion of the phenotypic variation. The majority of the significant interactions involved marker loci that did not detect significant effects by single-locus analyses, and many of the QTLs detected by single-locus analyses were involved in epistatic interactions. The results clearly demonstrated the importance of epistatic interactions in the genetic bases of heading date and plant height. Received: 5 May 2001 / Accepted: 3 August 2001     

Detection of additive and dominance effects of QTLs in interval mapping of F2 RFLP data

A model for interval mapping of quantitative trait loci (QTLs) in an F₂ population using genetic markers such as restriction fragment length polymorphisms (RFLPs) is proposed. Based on this model the log-likelihood ratio statistic is divided into two useful statistics which can be used to detect additive and dominance effects of QTLs, separately. The properties of the two statistics were investigated for the theoretical construction of critical regions to test the gene action of QTLs. The model was applied to 1000 simulated-sets of 200 F₂ individuals.     

Three QTLs from Lycopersicon peruvianum confer a high level of resistance to Clavibactermichiganensis ssp. michiganensis

Lycopersicon peruvianum LA2157 originates from 1650 m above sea level and harbours several beneficial traits for cultivated tomatoes such as cold tolerance, nematode resistance and resistance to bacterial canker (Clavibacter michiganensis ssp. michiganensis). In order to identify quantitative trait loci (QTLs) for bacterial canker resistance, a QTL mapping approach was carried out in an F₂ population derived from the interspecific F₁ between Lycopersicon esculentum cv Solentos and L. peruvianum LA2157. Three QTLs for resistance mapped to chromosomes 5, 7 and 9 respectively. The resistance loci were additive and co-dominant with the QTL on chromosome 7 explaining the largest part of the variation for resistance in the F₂ population. The combination of this QTL with either of the other two QTLs conferred a resistance similar to the level in the resistant parent L. peruvianum. Some RFLP markers flanking this QTL on chromosome 7 were converted into SCAR markers allowing efficient marker-assisted selection of plants with high resistance to bacterial canker. Received: 26 February 1999 / Accepted: 12 March 1999     

Mapping of the quantitative trait locus (QTL) conferring partial resistance to rice leaf blast disease

Malaysian rice, Pongsu Seribu 2, has wide-spectrum resistance against blast disease. Chromosomal locations conferring quantitative resistance were detected by linkage mapping with SSRs and quantitative trait locus (QTL) analysis. For the mapping population, 188 F₃ families were derived from a cross between the susceptible cultivar, Mahsuri, and a resistant variety, Pongsu Seribu 2. Partial resistance to leaf blast in the mapping population was assessed. A linkage map covering ten chromosomes and consisting of 63 SSR markers was constructed. 13 QTLs, including 6 putative and 7 putative QTLs, were detected on chromosomes 1, 2, 3, 5, 6, 10, 11 and 12. The resulting phenotypic variation due to a single QTL ranged from 2 to 13 %. These QTLs accounted for approx. 80 % of the total phenotypic variation within the F₃ population. Therefore, partial resistance to blast in Pongsu Seribu 2 is due to combined effects of multiple loci with major and minor effects.     

Analysis of QTL×environment interaction for yield components and plant height in rice

 An F₂ and two equivalent F₃ populations of an indica-indica cross of rice, Tesanai 2/CB, were constructed and grown in different environments. The identification of quantitative trait loci (QTL) for yield components and plant height and an analysis of QTL×environment interaction were conducted for three trials. Interval mapping of QTL for eight traits was employed with a threshold of LOD=2 using the computer package MAPMAKER/QTL. A total of 44 QTL were detected in 18 intervals of nine chromosomes, including 3 for the number of panicles (NP), 5 for the number of filled grains (NFG), 6 for total number of spikelets (TNS), 3 for spikelet fertility (SF), 7 for 1000-grain weight (TGWT), 5 for grain weight per plant (GWT), 8 for plant height (PH) and 7 for panicle length (PL). The numbers of QTL detected in two or three trials were 1 for NP, 1 for NFG, 1 for TNS, none for SF, 4 for TGWT, 3 for GWT, 2 for PH and 5 for PL, making a total of 17. When a QTL was detected in more than one trial the direction and magnitude of its additive effect, the dominance effect and the degree of dominance were generally in good agreement. In all three trials, QTL were frequently detected for related traits in the same intervals. The directions of additive effect of QTL for related traits in a given interval were in agreement with few exceptions, no matter whether they were detected in the same trial or not. This result suggested that pleiotropism rather than close linkage of different QTL was the major reason why QTL for different traits were frequently detected in the same intervals. When gene pleiotropism was considered, 23 of the 29 QTL for yield and its components and 9 of the 15 QTL for plant stature were detected in more than one trial. This indicated that the detection of chromosomal segments harboring QTL was hardly affected by environmental factors. Received: 30 January 1997 / Accepted: 21 March 1997     

Two consensus quantitative trait loci clusters controlling anthesis–silking interval, ear setting and grain yield might be related with drought tolerance in maize

Unravelling the molecular basis of drought tolerance will provide novel opportunities for improving crop yield under water-limited conditions. The present study was conducted to identify quantitative trait loci (QTLs) controlling anthesis–silking interval (ASI), ear setting percentage (ESP) and grain yield (GY). The mapping population included 234 F₂ plants derived from the cross X178 (drought tolerant) × B73 (drought susceptible). The corresponding F_2:3 progenies, along with their parents, were evaluated for the above-mentioned traits under both well-watered and water-stressed field conditions in three different trials carried out in central and southern China. Interval mapping and composite interval mapping identified 45 and 65 QTLs for the investigated traits, respectively. Two QTL clusters influencing ASI and ESP on chromosomes 1 (bin 1.03) and 9 (bins 9.03–9.05) were identified in more than two environments, showing sizeable additive effects and contribution to phenotypic variance; these two QTL clusters influenced GY only in one environment. No significant interaction was detected between the two genomic regions. A comparative analysis of these two QTL clusters with the QTLs controlling maize drought tolerance previously described in three mapping populations confirmed and extended their relevance for marker-assisted breeding to improve maize production under water-limited conditions.     

Mapping quantitative trait loci for downy mildew resistance in pearl millet

Quantitative trait loci (QTLs) for resistance to pathogen populations of Scelerospora graminicola from India, Nigeria, Niger and Senegal were mapped using a resistant x susceptible pearl millet cross. An RFLP map constructed using F₂ plants was used to map QTLs for traits scored on F₄ families. QTL analysis was carried out using the interval mapping programme Mapmaker/QTL. Independent inheritance of resistance to pathogen populations from India, Senegal, and populations from Niger and Nigeria was shown. These results demonstrate the existence of differing virulences in the pathogen populations from within Africa and between Africa and India. QTLs of large effect, contributing towards a large porportion of the variation in resistance, were consistently detected in repeated screens. QTLs of smaller and more variable effect were also detected. There was no QTLs that were effective against all four pathogen populations, demonstrating that pathotype-specific resistance is a major mechanism of downy mildew resistance in this cross. For all but one of the QTLs, resistance was inherited from the resistant parent and the inheritance of resistance tended to be the result of dominance or over-dominance. The implications of this research for pearl millet breeding are discussed.     

Interactions between markers can be caused by the dominance effect of quantitative trait loci

F₂ populations are commonly used in genetic studies of animals and plants. For simplicity, most quantitative trait locus or loci (QTL) mapping methods have been developed on the basis of populations having two distinct genotypes at each polymorphic marker or gene locus. In this study, we demonstrate that dominance can cause the interactions between markers and propose an inclusive linear model that includes marker variables and marker interactions so as to completely control both additive and dominance effects of QTL. The proposed linear model is the theoretical basis for inclusive composite-interval QTL mapping (ICIM) for F₂ populations, which consists of two steps: first, the best regression model is selected by stepwise regression, which approximately identifies markers and marker interactions explaining both additive and dominance variations; second, the interval mapping approach is applied to the phenotypic values adjusted by the regression model selected in the first step. Due to the limited mapping population size, the large number of variables, and multicollinearity between variables, coefficients in the inclusive linear model cannot be accurately determined in the first step. Interval mapping is necessary in the second step to fine tune the QTL to their true positions. The efficiency of including marker interactions in mapping additive and dominance QTL was demonstrated by extensive simulations using three QTL distribution models with two population sizes and an actual rice F₂ population.     

Identification of QTLs for Yield and Associated Traits in F₂ Population of Rice

Identification of quantitative trait loci (QTLs) controlling yield and yield-related traits in rice was performed in the F₂ mapping population derived from parental rice genotypes DHMAS and K343. A total of 30 QTLs governing nine different traits were identified using the composite interval mapping (CIM) method. Four QTLs were mapped for number of tillers per plant on chromosomes 1 (2 QTLs), 2 and 3; three QTLs for panicle number per plant on chromosomes 1 (2 QTLs) and 3; four QTLs for plant height on chromosomes 2, 4, 5 and 6; one QTL for spikelet density on chromosome 5; four QTLs for spikelet fertility percentage (SFP) on chromosomes 2, 3 and 5 (2 QTLs); two QTLs for grain length on chromosomes 1 and 8; three QTLs for grain width on chromosomes1, 3 and 8; three QTLs for 1000-grain weight (TGW) on chromosomes 1, 4 and 8 and six QTLs for yield per plant (YPP) on chromosomes 2 (3 QTLs), 4, 6 and 8. Most of the QTLs were detected on chromosome 2, so further studies on chromosome 2 could help unlock some new chapters of QTL for this cross of rice variety. Identified QTLs elucidating high phenotypic variance can be used for marker-assisted selection (MAS) breeding. Further, the exploitation of information regarding molecular markers tightly linked to QTLs governing these traits will facilitate future crop improvement strategies in rice.