RFLP linkage analysis and mapping genes controlling the fatty acid profile of <Emphasis Type="Italic">Brassica juncea</Emphasis> using reciprocal DH populations

An RFLP linkage map, comprising 300 linked and 16 unlinked loci, was constructed using reciprocal DH populations of Brassica juncea. The linked loci were organized into 18 linkage groups and seven unlinked segments, covering a total map distance of 1,564 cM. The A and B genomes were identified. The chi(2) test showed that 96.1% of the common intervals in the two populations differed non-significantly for recombination fractions, thus strongly suggesting the absence of sex-based differences for recombination fractions in B. juncea. Two QTLs, E(1a) and E(1b), significantly affected erucic acid content, and individually explained 53.7% and 32.1%, respectively, and collectively 85.8% of the phenotypic variation in the population. The QTLs E(1a) and E(1b) showed epistasis, and the full model including epistasis explained nearly all of the phenotypic variation in the population. The QTLs E(1a) and E(1b) were also associated with contents of oleic, linoleic and linolenic acids. Three additional QTLs (LN(2), LN(3) and LN(4)) significantly influenced linolenic acid content. The QTL LN(2) accounted for 35.4% of the phenotypic variation in the population. Epistatic interactions were observed between the QTLs E1a and LN(2). The stability of the detected QTLs across years and locations, and breeding strategies for improving the fatty acid profile of B. juncea, are discussed.     

Molecular markers for seed colour in Brassica juncea.

A detailed RFLP map was used to map QTLs associated with seed colour in Brassica juncea using a doubled-haploid population derived from a cross between a black/brown-seeded cultivar and a yellow-seeded breeding line. Segregation analysis suggested that seed colour was under control of 2 unlinked loci with duplicate gene action. However, QTL analysis revealed 3 QTLs, SC-B4, SC-A10 and SC-A6, affecting seed colour. The QTLs were consistent across environments, and individually explained 43%, 31%, and 16%, respectively, and collectively 62% of the phenotypic variation in the population. Digenic interaction analysis showed that closest flanking locus of QTL SC-B4, wg7b6cNM, had strong epistasis with the locus wg5a1a, which is tightly linked to QTL SC-A6. The interaction of these 2 loci explained 27% of the phenotypic variation in the population, while the whole model explained 84%. In a multiple regression model, the effects of QTL SC-A10, as well as its interaction with other loci, were non-significant, whereas the effects of loci wg7b6cNM and wg5a1a and their interaction were significant. Ninety-eight percent of the DH lines carried the expected alleles of loci wg7b6cNM and wg5a1a for seed colour, confirming that only these 2 loci were linked to seed colour in B. juncea. Four additional digenic interactions significantly affected seed colour, and all 5 digenic interactions were consistent across environments.     

Mapping QTLs for root morphological traits inBrassica rapa L. based on AFLP and RAPD markers

Root growth and thickening plays a key role in the final productivity and even the quality of storage roots in root crops. This study was conducted to identify and map quantitative trait loci (QTLs) affecting root morphological traits in Brassica rapa by using molecular markers. An F2 population was developed from a cross between Chinese cabbage (Brassica rapa ssp. chinensis) and turnip (B. rapa ssp. rapifera), which differed greatly in root characters. A genetic map covering 1837.1 cM, with 192 marker loci and 11 linkage groups, was constructed by using this F2 population. The F3 families derived from F2 plants were grown in the field and evaluated for taproot traits (thickness, length, and weight). QTL analysis via simple interval mapping detected 18 QTLs for the 3 root traits, including 7 QTLs for taproot thickness, 5 QTLs for taproot length, and 6 QTLs for taproot weight. Individually, the QTLs accounted for 8.4-27.4% of the phenotypic variation. The 2 major QTLs, qTRT4b for taproot thickness and qTRW4 for taproot weight, explained 27.4% and 24.8% of the total phenotypic variance, respectively. The QTLs for root traits, firstly detected in Brassica crops, may provide a basis for marker-assisted selection to improve productivity in root-crop breeding.     

Fine-mapping of QTLs for individual and total isoflavone content in soybean (<Emphasis Type="Italic">Glycine max L.</Emphasis>) using a high-density genetic map

Key message

Fifteen stable QTLs were identified using a high-density soybean genetic map across multiple environments. One major QTL, qIF5-1, contributing to total isoflavone content explained phenotypic variance 49.38, 43.27, 46.59, 45.15 and 52.50%, respectively.

Abstract

Soybeans (Glycine max L.) are a major source of dietary isoflavones. To identify novel quantitative trait loci (QTL) underlying isoflavone content, and to improve the accuracy of marker-assisted breeding in soybean, a valuable mapping population comprised of 196 F_7:8–10 recombinant inbred lines (RILs, Huachun 2 × Wayao) was utilized to evaluate individual and total isoflavone content in plants grown in four different environments in Guangdong. A high-density genetic linkage map containing 3469 recombination bin markers based on 0.2 × restriction site-associated DNA tag sequencing (RAD-seq) technology was used to finely map QTLs for both individual and total isoflavone contents. Correlation analyses showed that total isoflavone content, and that of five individual isoflavone, was significantly correlated across the four environments. Based on the high-density genetic linkage map, a total of 15 stable quantitative trait loci (QTLs) associated with isoflavone content across multiple environments were mapped onto chromosomes 02, 05, 07, 09, 10, 11, 13, 16, 17, and 19. Further, one of them, qIF5-1, localized to chromosomes 05 (38,434,171–39,045,620 bp) contributed to almost all isoflavone components across all environments, and explained 6.37–59.95% of the phenotypic variance, especially explained 49.38, 43.27, 46.59, 45.15 and 52.50% for total isoflavone. The results obtained in the present study will pave the way for a better understanding of the genetics of isoflavone accumulation and reveals the scope available for improvement of isoflavone content through marker-assisted selection.

     

不同生长环境下水稻最上节间长度QTL定位研究

利用由98 个家系组成的 Nipponbare/Kasalath//Nipponbare 回交重组自交系(backcross inbred lines, BIL)作图群体(BC1F12和BC1F13)和复合区间作图方法(CIM), 在3种不同的生长环境下对水稻最上节间长度进行了 QTL 分析。结果表明, 3种不同的生长环境共检测到 13 个 QTL , 分布于第 1, 2, 3, 5, 6, 8, 10, 11 染色体上, 解释性状变异的 3.97%～15.21%。其中qUIL-6在3种不同生长环境中均检测到, qUIL-1a, qUIL-3a, qUIL-3b和 qUIL-10a 等4个位点在两种不同生长环境中均被检测到, 说明这些 QTL 位点受环境影响较小, 表达较为稳定。     

Glucosinolate responses of oilseed rape, mustard and kale to mechanical wounding and infestation by cabbage stem flea beetle (Psylliodes chrysocephala)

Mechanical wounding of the petioles of six laboratory-grown rapeseed ( Brassica napus ) cultivars induced physiological changes in the plant, markedly affecting the levels of individual glucosinolates. Greatest increases were observed for the indole glucosinolates, glucobrassicin and neoglucobrassicin. Such changes were usually associated with large decreases in the levels of aliphatic glucosinolates. The total glucosinolate content of the wounded plant was thus a reflection of these two opposing trends and wounding produced a greater relative indole glucosinolate content in this total figure. Thus increasing wounding was associated with an increase in indole glucosinolates and a decrease in aliphatic compounds.
Infestation of field- and laboratory-grown rapeseed with cabbage stem flea beetle ( Psylliodes chrysocephala ) produced similar effects, which were observed in various parts of the plant. Differences in response between field- and laboratory-grown infested plants are attributed to the different physiological ages of the harvested material.
Laboratory-grown kale and mustards also showed wound-induced glucosinolate changes. The kale, cv. Fribor, produced elevated levels of both indoles and aliphatics after wounding. Total glucosinolate content in the mustards, which, unlike rape and kale, normally contain only traces of indole glucosinolates in the unstressed state, was increased following wounding. This was, however, not associated with elevated levels of indole glucosinolates, but with accumulation of aliphatic ( Brassica nigra, B. juncea ) and aromatic ( Sinapis alba ) glucosinolates. The significance of these findings is discussed.     

Mapping quantitative trait loci for a common bean (Phaseolus vulgaris L.) ideotype.

Breeding a model plant that encompasses individual traits thought to enhance yield potential, known as ideotype breeding, has traditionally focused on phenotypic selection of plants with desirable morphological traits. Broadening this breeding method to the molecular level through the use of molecular markers would avoid the environmental interactions associated with phenotypic selection. A population of 110 F5 recombinant inbred lines (RILs), derived from the cross between WO3391 and 'OAC Speedvale', was used to develop a genetic linkage map consisting of 105 random amplified polymorphic DNA (RAPD), simple sequence repeat (SSR), and sequence-tagged site (STS) markers. The map has a total length of 641 cM distributed across 8 linkage groups (LGs). Five of them were aligned on the core linkage map of bean. Twenty-one quantitative trait loci (QTLs) were identified over three environments for eight agronomic and architectural traits previously defined for a bean (Phaseolus vulgaris L.) ideotype. The QTLs were mapped to seven LGs with several regions containing QTLs for multiple traits. At least one QTL was located for each trait and a maximum of four were associated with lodging. Total explained phenotypic variance ranged from 10.6% for hypocotyl diameter to 45.4% for maturity. Some of the QTLs identified will be useful for early generation selection of tall, upright, high-yielding lines in a breeding program.     

Quantitative trait loci analysis of plant height and ear height in maize (Zea mays L.)

Genetic map containing 103 microsatellite loci obtained on 200 F₂ plants derived from the cross R15 × 478 was used for quantitative trait loci (QTL) mapping in maize. QTLs were characterized in a population of 200 F_2:4 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 QTLs affecting plant height and ear height. The QTLs 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. The text was submitted by the authors in English.     

Quantitative trait loci mapping of resistance to Laodelphax striatellus (Homoptera: Delphacidae) in rice using recombinant inbred lines

Laodelphax striatellus Fallén (Homoptera: Delphacidae), is a serious pest in rice, Oryza sativa L., production. A mapping population consisting of 81 recombinant inbred lines (RILs), derived from a cross between japonica' Kinmaze' and indica' DV85' rice, was used to detect quantitative trait loci (QTLs) for the resistance to L. striatellus. Seedbox screening test (SST), antixenosis test, and antibiosis test were used to evaluate the resistance response of the two parents and 81 RILs to L. striatellus at the seedling stage, and composite interval mapping was used for QTL analysis. When the resistance was measured by SST method, two QTLs conferring resistance to L. striatellus were mapped on chromosome 11, namely, Qsbph11a and Qsbph11b, with log of odds scores 2.51 and 4.38, respectively. The two QTLs explained 16.62 and 27.78% of the phenotypic variance in this population, respectively. In total, three QTLs controlling antixenosis against L. striatellus were detected on chromosomes 3, 4, and 11, respectively, accounting for 37.5% of the total phenotypic variance. Two QTLs expressing antibiosis to L. striatellus were mapped on chromosomes 3 and 11, respectively, explaining 25.9% of the total phenotypic variance. The identified QTL located between markers XNpb202 and C1172 on chromosome 11 was detected repeatedly by three different screening methods; therefore, it may be important to confer the resistance to L. striatellus. Once confirmed in other mapping populations, these QTLs should be useful in breeding for resistance to L. striatellus by marker-assisted selection of different resistance genes in rice varieties.     

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.     

Construction of an RAPD linkage map and localization of QTLs for oleic acid level using recombinant inbreds in mustard (Brassica juncea).

RAPD markers were employed for construction of a linkage map and localization of QTLs for oleic acid level using a set of 94 recombinant inbred lines (RILs) of mustard (Brassica juncea L.) as a mapping population. Only 30% of the 235 random primers used were useful in terms of polymorphism detected and the reproducibility of those patterns. Normal Mendelian segregation was observed for the majority of the 130 markers obtained with 71 informative primers; only 13.1% deviated (P < 0.01) from the expected 1:1 ratio. One-hundred and fourteen markers were assigned to 21 linkage groups (LGs) covering a total length of 790.4 cM with an average distance of 6.93 cM between markers. Two quantitative trait loci (QTL) for oleic acid level were mapped to 14- and 10.6-cM marker intervals on two different LGs. Both loci together explained 32.2% of phenotypic variance. One major QTL explained 28.5% of the trait variance observed in this species.     

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.     

不同发育时期小麦粒重性状QTL的动态分析

利用6044×01-35构建的重组自交系(RIL)群体为试验材料,对小麦粒重性状进行发育动态QTL分析。结果表明,在小麦花后子粒灌浆的7个不同时期,两个试验点共检测到16个与粒重性状相关的QTL。其中开花后20d检测到的单穗粒重QTL位于2A染色体上,解释率达12%,遗传效应超过10;两环境下控制千粒重QTL在7个时期均被检测到。花后的各个时期均能在Xgwm448-Xgpw7399标记区间定位到千粒重QTL。其中花后10d检测到1个千粒重QTL,位于2A染色体的Xgwm448-Xgpw7399标记区间,解释较大的表型变异,达到18%。Qtl8、Qtl13和Qtl14均定位在Xgwm448-Xgpw7399标记区间的同一位置,共同解释11%的表型变异。花后20d和花后25d均检测到1个QTL,位于2A染色体的Xgwm372-Xgwm95标记区间的不同位点,均能解释4%的表型变异。花后40d检测到1个QTL,位于1D染色体的Xwmc93-Xgpw2224标记区间,解释1%的表型变异。从连锁群的位置上看,控制千粒重的QTL主要集中在2A染色体的Xgwm448-Xgpw7399标记区间,这是一个控制千粒重QTL的富集区域,以期进行精细定位和图位克隆。     

Mapping QTLs for chlorophyll content and chlorophyll fluorescence in wheat under heat stress

Heat stress, one of the major abiotic stresses in wheat, affects chlorophyll fluorescence and chlorophyll content and thereby photosynthesis. To identify quantitative trait loci (QTLs) associated with these traits under terminal heat stress, 251 recombinant inbred lines (RILs) derived from a cross HD 2808/HUW510 were phenotyped. Using composite interval mapping, 40 QTLs were identified; 17 were related to conditions after timely sowing and 23 to heat stress after late sowing. The various parameters of chlorophyll fluorescence were associated with 23 QTLs, which were located on chromosomes 1A, 2A, 3A, and 2D and explained 3.67 to 18.04 % of phenotypic variation, whereas chlorophyll content was associated with 17 QTLs on chromosomes 2A, 2B, 2D, 5B, and 7A explaining 3.49 to 31.36 % of phenotypic variation. Most of the identified QTLs were clustered on chromosome 2D followed by 2A and 1A. The QTL Qchc.iiwbr-2A for chlorophyll content linked with marker gwm372 was stable over conditions and explained 3.81 to 18.05 % of phenotypic variation. In addition, 7 epistatic QTL pairs were also detected which explained 1.67 to 11.0 % of phenotypic variance. These identified genomic regions can be used in marker assisted breeding after validation for heat tolerance in wheat.     

Genetic mapping of maize stripe disease resistance from the Mascarene source

Maize stripe virus (MStV) is a potentially threatening virus disease of maize in the tropics. We mapped quantitative trait loci (QTLs) controlling resistance to MStV in a maize population of 157 F(2:3) families derived from the cross between two maize lines, Rev81 (tropical resistant) and B73 (temperate susceptible). Resistance was evaluated under artificial inoculations in replicated screenhouse trials across different seasons in Réunion Island, France. Composite interval mapping was employed for QTL detection with a linkage map of 143 microsatellite markers. Heritability estimates across seasons were 0.96 and 0.90 for incidence and severity, respectively, demonstrating a high genotypic variability and a good control of the environment. Three regions on chromosomes 2L, 3 and 5, with major effects, and another region on chromosome 2S, with minor effects, provided resistance to MStV in Rev81. In individual seasons, the chr2L QTL explained 60-65% of the phenotypic variation for disease incidence and 21-42% for severity. The chr3 QTL, mainly associated with incidence and located near centromere, explained 42-57% of the phenotypic variation, whereas the chr5 QTL, mainly associated with severity, explained 26-53%. Overall, these QTLs explained 68-73% of the phenotypic variance for incidence and 50-59% for severity. The major QTLs on chr2 and 3 showed additive gene action and were found to be stable over time and across seasons. They also were found to be included in genomic regions with important clusters of resistance genes to diseases and pests. The major QTL on chr5 appeared to be partially dominant in favour of resistance. It was stable over time but showed highly significant QTL x season interactions. Possible implications of these QTLs in different mechanisms of resistance against the virus or the insect vector are discussed. The prospects for transferring these QTLs in susceptible maize cultivars and combining them with other resistances to virus diseases by conventional or marker-assisted breeding are promising.     

Identification of quantitative trait loci for agronomically important traits and their association with genic-microsatellite markers in sorghum

The identification of quantitative trait loci (QTLs) affecting agronomically important traits enable to understand their underlying genetic mechanisms and genetic basis of their complex interactions. The aim of the present study was to detect QTLs for 12 agronomic traits related to staygreen, plant early development, grain yield and its components, and some growth characters by analyzing replicated phenotypic datasets from three crop seasons, using the population of 168 F₇ RILs of the cross 296B × IS18551. In addition, we report mapping of a subset of genic-microsatellite markers. A linkage map was constructed with 152 marker loci comprising 149 microsatellites (100 genomic- and 49 genic-microsatellites) and three morphological markers. QTL analysis was performed by using MQM approach. Forty-nine QTLs were detected, across environments or in individual environments, with 1–9 QTLs for each trait. Individual QTL accounted for 5.2–50.4% of phenotypic variance. Several genomic regions affected multiple traits, suggesting the phenomenon of pleiotropy or tight linkage. Stable QTLs were identified for studied traits across different environments, and genetic backgrounds by comparing the QTLs in the study with previously reported QTLs in sorghum. Of the 49 mapped genic-markers, 18 were detected associating either closely or exactly as the QTL positions of agronomic traits. EST marker Dsenhsbm19, coding for a key regulator (EIL-1) of ethylene biosynthesis, was identified co-located with the QTLs for plant early development and staygreen trait, a probable candidate gene for these traits. Similarly, such exact co-locations between EST markers and QTLs were observed in four other instances. Collectively, the QTLs/markers identified in the study are likely candidates for improving the sorghum performance through MAS and map-based gene isolations.     

Genetic architecture of quantitative trait loci associated with morphological and agronomic trait differences in a wild by cultivated barley cross.

Hordeum vulgare subsp. spontaneum is the progenitor of cultivated barley (Hordeum vulgare L.). Domestication combined with plant breeding has led to the morphological and agronomic characteristics of modern barley cultivars. The objective of this study was to map the genetic factors that morphologically and agronomically differentiate wild barley from modern barley cultivars. To address this objective, we identified quantitative trait loci (QTLs) associated with plant height, flag leaf width, spike length, spike width, glume length in relation to seed length, awn length, fragility of ear rachis, endosperm width and groove depth, heading date, flag leaf length, number of tillers per plant, and kernel color in a Harrington/OUH602 advanced backcross (BC2F8) population. This population was genotyped with 113 simple sequence repeat markers. Thirty QTLs were identified, of which 16 were newly identified in this study. One to 4 QTLs were identified for each of the traits except glume length, for which no QTL was detected. The portion of phenotypic variation accounted for by individual QTLs ranged from about 9% to 54%. For traits with more than one QTL, the phenotypic variation explained ranged from 25% to 71%. Taken together, our results reveal the genetic architecture of morphological and agronomic traits that differentiate wild from cultivated barley.     

Identification and validation of quantitative trait loci controlling seed isoflavone content across multiple environments and backgrounds in soybean

Soybean is important throughout the world not only due to the high seed protein and oil but also owing to the seed isoflavone. To improve the isoflavone concentration in seeds, detecting and mining the stable and reliable quantitative trait loci (QTLs) and related genes in multiple environments and genetic backgrounds become more and more important. In view of this, a F_6:7 recombinant inbred line (RIL) population of 345 lines derived from a cross between Zheng 92116 and Liaodou14 (ZL) was genotyped using 1739 polymorphic SNP and 127 SSR markers in this study and was phenotyped for individual and total seed isoflavone in four environments over 2 years. In total, 48 additive QTLs, which explained 3.00–29.83% of seed isoflavone variation, were identified. Of them, eight QTLs (qDA1_1, qGA1_1, qTIA1_1, qDA1_2, qGA1_2, qTIA1_2, qDA1_3, qTIA1_3) with phenotypic variation explained (PVE) ranging from 14.09 to 28.59% for daidzin, genistin, and total isoflavone were located on the same region of linkage group (LG) A1. These QTLs were further verified in another RIL population derived from Zheng 92116 × Qihuang 30 (ZQ). Meanwhile, the other four overlapping QTLs on linkage group B1, which were associated with glycitin content (qGLB1_1, qGLB1_2, qGLB1_3, qGLB1_4) and explained 16.52 to 29.83% of phenotypic variation, were also verified using the ZQ population. Moreover, the individuals with different genotypes at the common flanking SNP markers for these QTLs on LGs A1 and B1 in the two mapping populations showed significant different isoflavone content, which further validate the QTL mapping results. And also, some candidate genes might participate in the isoflavone biosynthesis processes were found in these stable QTL regions. Thus, the novel and stable QTLs identified and verified in this study could be applied in marker-assisted selection breeding or map-based candidate genes cloning in soybean seed isoflavone genetic improvement in future.     

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.     

Correlation and Quantitative Trait Loci Analyses of Total Chlorophyll Content and Photosynthetic Rate of Rice (Oryza sativa) under Water Stress and Well-watered Conditions

In order to explore the relevant molecular genetic mechanisms of photosynthetic rate (PR) and chlorophyll content (CC) in rice ( Oryza sativa L.), we conducted a series of related experiments using a population of recombinant inbred lines (Zhenshan97B × IRAT109). We found a significant correlation between CC and PR ( R = 0.19**) in well-watered conditions, but no significant correlation during water stress ( r = 0.08). We detected 13 main quantitative trait loci (QTLs) located on chromosomes 1, 2, 3, 4, 5, 6, and 10, which were associated with CC, including six QTLs located on chromosomes 1, 2, 3, 4, and 5 during water stress, and seven QTLs located on chromosomes 2, 3, 4, 6, and 10 in well-watered conditions. These QTLs explained 47.39% of phenotypic variation during water stress and 56.19% in well-watered conditions. We detected four main QTLs associated with PR; three of them ( qPR2 , qPR10 , qPR11 ) were located on chromosomes 2, 10, and 11 during water stress, and one ( qPR10 ) was located on chromosome 10 in well-watered conditions. These QTLs explained 34.37% and 18.41% of the phenotypic variation in water stress and well-watered conditions, respectively. In total, CC was largely controlled by main QTLs, and PR was mainly controlled by epistatic QTL pairs.