Epistasis in the expression of relevant traits in cassava (Manihot esculenta Crantz) for subhumid conditions

There is limited knowledge on the inheritance of agronomic traits in cassava and the importance of epistasis for most crops. A nine-parent diallel study was conducted in subhumid environments. Thirty clones were obtained from each F1 cross. Each clone was represented by six plants, which were distributed in three replications at two locations. Therefore the same 30 genotypes of each F1 cross were planted in the three replications at the two locations. Analysis of variance suggested significant genetic effects for all variables analyzed (reaction to thrips, fresh root and foliage yields, harvest index, dry matter content, and root dry matter yield). Significant epistatic effects were observed for all variables, except harvest index. Dominance variance was always significant, except for dry matter content and dry matter yield. Additive variance was significant only for reaction to thrips. Results suggested that dominance plays an important role in complex traits such as root yield. The significance of epistasis can help us understand the difficulties of quantitative genetics models and QTLs in satisfactorily explaining phenotypic variation in traits with complex inheritance. Significant epistasis would justify the production of inbred parental lines to fix favorable allele combinations in the production of hybrid cassava cultivars.     

Genetic mapping of QTLs affecting productivity and plant architecture in a full-sib cross from non-inbred parents in Cassava (<Emphasis Type="Italic">Manihot esculenta</Emphasis> Crantz)

An attempt was made to identify quantitative trait loci (QTLs) for several productivity and plant architecture traits in a full-sib progeny of 144 individuals from two non-inbred parents in cassava. A molecular linkage map of this cross constructed previously with over 250 markers was the source of molecular markers. The progeny were grown under field conditions at two locations (Palmira and Quilichao) in Colombia and evaluated in 2 years (1998 and 1999) for architecture and productivity traits. Architecture traits evaluated were plant height (PH), branching height (BH), branching levels (BL), branching index (BI), stem portion with leaves (SPL) and leaf area index (LAI). Productivity traits were those related to total dry matter production and distribution, namely fresh root yield (FRY), fresh shoot yield (FSY), harvest index (HI) and the number of storage roots (NR). Phenotypic evaluation of the traits in this population revealed continuous variation for all traits. Broad-sense heritability estimates, ranged from 36% (for NR) to 94% (for BH). Several significant phenotypic correlations were observed between architecture and productivity traits. Primary QTLs, using the single-QTL model, and secondary QTLs, by a primary QTL interaction model, were detected by interval mapping. A total of 30 primary QTLs and 84 secondary QTLs were detected. We identified 35% of detected QTLs in two or more trials, the other QTLs were environment-specific. These results underscore the significant genotype × environment interactions found for most of the traits. Several genomic segments affecting multiple traits were identified and were in agreement with correlation among traits. All QTLs identified for FRY were found associated with either component traits of productivity or architecture traits. This study suggests that QTLs for plant architecture can be used to improve productivity. However an exhaustive search and analysis of QTLs controlling architecture is required before marker-assisted selection (MAS) for increasing productivity can be initiated.Communicated by H. C. Becker     

绿豆5个产量相关性状的QTL分析

利用绿豆(Vigna radiata)品种苏绿16-10和潍绿11杂交构建的F2和F3群体发掘调控绿豆产量相关性状的遗传位点。同时对绿豆产量相关性状进行表型鉴定和相关性分析,并利用构建的遗传连锁图谱进行QTL定位。结果表明,单株产量与单株荚数、单荚粒数、百粒重和分枝数均呈正相关。单株产量与单株荚数的相关性最高,这2个性状在F2和F3群体中的相关系数分别为0.950和0.914。在F2群体中,共检测到8个与产量性状相关的QTL位点,其中与单株荚数、单荚粒数和单株产量相关的QTL位点各1个,分别解释11.09%(qNPP3)、17.93%(qNSP3)和14.18%(qYP3)的表型变异;2个与分枝数相关的QTL位点qBMS3和qBMS11,分别解释18.51%和7.06%的表型变异;3个与百粒重相关的QTL位点qHSW3、qHSW7和qHSW10,分别解释5.33%、46.07%和4.24%的表型变异。在F3群体中,qNSP3和qHSW7再次被检测到,表明这2个QTLs有较好的遗传稳定性。同时,开发了1个与百粒重主效QTLqHSW7紧密连锁的InDel标记R7-13.4,并利用自然群体对...     

QTL mapping of root traits in a doubled haploid population from a cross between upland and lowland japonica rice in three environments

To genetically dissect drought resistance associated with japonica upland rice, we evaluated a doubled haploid (DH) population from a cross between two japonica cultivars for seven root traits under three different growing conditions (upland, lowland and upland in PVC pipe). The traits included basal root thickness (BRT), total root number (RN), maximum root length (MRL), root fresh weight (RFW), root dry weight (RDW), ratio of root fresh weight to shoot fresh weight (RFW/SFW) and ratio of root dry weight to shoot dry weight (RDW/SDW). The BRT was significantly correlated with the index of drought resistance, which was defined as the ratio of yield under the stress of the upland condition to that under the normal lowland condition. A complete genetic linkage map with 165 molecular markers covering 1,535 cM was constructed. Seven additive quantitative trait loci (QTLs) and 15 pairs of epistatic loci for BRT and RN were identified under upland and lowland conditions, and 12 additive QTLs and 17 pairs of epistatic QTLs for BRT, RN, MRL, RFW, RFW/SFW and RDW/SDW were identified under the PVC pipe condition. Four additive QTLs and one pair of epistatic QTLs controlling IDR were also found. These QTLs individually explained up to 25.6% of the phenotypic variance. QTL × environment (Q × E) interactions were detected for all root traits, and the contributions of these interactions ranged from 1.1% to 19.9%. Five co-localized QTLs controlling RFW and RDW, RFW/SFW, RDW/SDW and IDR, BRT and RN, RN, MRL and IDR were found. Four types of QTLs governing BRT and RN were classified by their detection in the upland and lowland conditions. Some common QTLs for root traits across different backgrounds were also revealed. These co-localized QTLs and common QTLs will facilitate marker-assisted selection for root traits in rice breeding programs.     

Molecular mapping of genomic regions harbouring QTLs for root and yield traits in sorghum (Sorghum bicolor L. Moench)

Root system is a vital part of plants for absorbing soil moisture and nutrients and it influences the drought tolerance. Identification of the genomic regions harbouring quantitative trait loci (QTLs) for root and yield traits, and the linked markers can facilitate sorghum improvement through marker-assisted selection (MAS) besides the deeper understanding of the plant response to drought stress. A population of 184 recombinant inbred lines (RILs), derived from E36-1 × SPV570, along with parents were phenotyped for component traits of yield in field and root traits in an above ground rhizotron. High estimates of heritability and genetic advance for all the root traits and for most of the yield traits, presents high scope for improvement of these traits by simple selection. A linkage map constructed with 104 marker loci comprising 50 EST-SSRs, 34 non-genic nuclear SSRs and 20 SNPs, and QTL analysis was performed using composite interval mapping (CIM) approach. A total of eight and 20 QTLs were mapped for root and yield related traits respectively. The QTLs for root volume, root fresh weight and root dry weight were found co-localized on SBI-04, supported by a positive correlation among these traits. Hence, these traits can be improved using the same linked markers. The lack of overlap between the QTLs of component traits of root and yield suggested that these two sets of parameters are independent in their influence and the possibility of combining these two traits might enhance productivity of sorghum under receding moisture condition.     

Deciphering genetic basis of developmental and agronomic traits by integrating high-throughput optical phenotyping and genome-wide association studies in wheat

Dissecting the genetic basis of complex traits such as dynamic growth and yield potential is a major challenge in crops. Monitoring the growth throughout growing season in a large wheat population to uncover the temporal genetic controls for plant growth and yield-related traits has so far not been explored. In this study, a diverse wheat panel composed of 288 lines was monitored by a non-invasive and high-throughput phenotyping platform to collect growth traits from seedling to grain filling stage and their relationship with yield-related traits was further explored. Whole genome re-sequencing of the panel provided 12.64 million markers for a high-resolution genome-wide association analysis using 190 image-based traits and 17 agronomic traits. A total of 8327 marker-trait associations were detected and clustered into 1605 quantitative trait loci (QTLs) including a number of known genes or QTLs. We identified 277 pleiotropic QTLs controlling multiple traits at different growth stages which revealed temporal dynamics of QTLs action on plant development and yield production in wheat. A candidate gene related to plant growth that was detected by image traits was further validated. Particularly, our study demonstrated that the yield-related traits are largely predictable using models developed based on i-traits and provide possibility for high-throughput early selection, thus to accelerate breeding process. Our study explored the genetic architecture of growth and yield-related traits by combining high-throughput phenotyping and genotyping, which further unravelled the complex and stage-specific contributions of genetic loci to optimize growth and yield in wheat.     

In silico integration of quantitative trait loci for seed yield and yield-related traits in Brassica napus

Mapping quantitative trait loci (QTLs) is a foundation for molecular marker-assisted selection and map-based gene cloning. During the past decade, numerous QTLs for seed yield (SY) and yield-related traits in Brassica napus L. have been identified. However, integration of these results in order to compare QTLs from different mapping populations has not been undertaken, due to the lack of common molecular markers between studies. Using previously reported Brassica rapa and Brassica oleracea genome sequences, we carried out in silico integration of 1,960 QTLs associated with 13 SY and yield-related traits from 15 B. napus mapping experiments over the last decade. A total of 736 SY and yield-related QTLs were mapped onto 283 loci in the A and C genomes of B. napus. These QTLs were unevenly distributed across the 19 B. napus chromosomes, with the most on chromosome A3 and the least on chromosome C6. Our integrated QTL map identified 142 loci where the conserved QTLs were detected and 25 multifunctional loci, mostly for the traits of flowering time (FT), plant height, 1,000-seed weight, maturity time and SY. These conserved QTLs and multifunctional loci may result from pleiotropism or clustered genes. At the same time, a total of 146 genes underlying the QTLs for FT and other yield-related traits were identified by comparative mapping with the Arabidopsis genome. These results facilitate the retrieval of B. napus SY and yield-related QTLs for research communities, increase the density of targeted QTL-linked markers, validate the existence of QTLs across different populations, and advance the fine mapping of genes.     

QTL mapping for fiber yield-related traits by constructing the first genetic linkage map in ramie (Boehmeria nivea L. Gaud)

Ramie fiber extracted from stem bast is one of the most important natural fibers. The fiber yield of ramie is a valuable trait and is decided by several components, including stem number per plant (SN), the fiber yield per stem (FYPS), stem length (SL), stem diameter (SD), and bark thickness (BT). All of these fiber yield-related traits are inherited in a quantitative manner. The genetic basis for these traits is still uncharacterized, which has hindered the improvement of yield traits through selective ramie breeding. In this study, an F₂ population derived from two ramie varieties, Zhongzhu 1 and Qingyezhuma, with striking differences in fiber yield-related traits, was used for cutting propagation and to develop an F₂ agamous line (FAL) population. A genetic linkage map with 132 DNA loci spanning 2,265.1 cM was first constructed. The analysis of quantitative trait locus (QTL) for fiber yield-related traits was performed in ramie for the first time. Finally, a total of 6, 9, 5, 7, and 6 QTLs for FYPS, SL, SN, SD, and BT, respectively, were identified in the FAL population in two environments. Among these 33 QTLs, 9 QTLs were detected in both environments and 24 QTLs exhibited overdominance. The overdominance of these QTLs possibly contributed to the heterosis of these yield-related traits in ramie. Moreover, there were 7 QTL clusters identified. The identification of the QTLs for fiber yield-related traits will be helpful for improving the fiber yield in ramie breeding programs.     

Quantitative trait loci for seed yield and yield-related traits, and their responses to reduced phosphorus supply in Brassica napus

Background and Aims

One of the key targets of breeding programmes in rapeseed (Brassica napus) is to develop high-yield varieties. However, the lack of available phosphorus (P) in soils seriously limits rapeseed production. The aim of this study was to dissect the genetic control of seed yield and yield-related traits in B. napus grown with contrasting P supplies.

Methods

Two-year field trials were conducted at one site with normal and low P treatments using a population of 124 recombinant inbred lines derived from a cross between ‘B104-2’ and ‘Eyou Changjia’. Seed yield, seed weight, seed number, pod number, plant height, branch number and P efficiency coefficient (PEC) were investigated. Quantitative trait locus (QTL) analysis was performed by composite interval mapping.

Key Results

The phenotypic values of most of the tested traits were reduced under the low P conditions. In total, 74 putative QTLs were identified, contributing 7·3–25·4 % of the phenotypic variation. Of these QTLs, 16 (21·6 %) were detected in two seasons and in the mean value of two seasons, and eight QTLs for two traits were conserved across P levels. Low-P-specific QTLs were clustered on chromosomes A1, A6 and A8. By comparative mapping between Arabidopsis and B. napus, 161 orthologues of 146 genes involved in Arabidopsis P homeostasis and/or yield-related trait control were associated with 45 QTLs corresponding to 23 chromosomal regions. Four gene-based markers developed from genes involved in Arabidopsis P homeostasis were mapped to QTL intervals.

Conclusions

Different genetic determinants were involved in controlling seed yield and yield-related traits in B. napus under normal and low P conditions. The QTLs detected under reduced P supply may provide useful information for improving the seed yield of B. napus in soils with low P availability in marker-assisted selection.     

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.     

Analysis of QTLs for yield-related traits in Yuanjiang common wild rice （Oryza rufipogon Griff.）

Using an accession of common wild rice(Oryza rufipogon Griff.)collected from Yunnjiang County,Yunnan Province,China,as the donor and an elite cnltivar 93-11,widely used in two-line indica hybrid rice production in China,as the recurrent parent,an advanced backcross populations were developed.Through genotyping of 187 SSR markers and investigation of six yield-related traits of two generations(BC4F2 and BC4F4),a total of 26 QTLs were detected by employing single point analysis and interval mapping in both generations.Of the 26 QTLs,the alleles of 10(38.5%)QTLs originating from O.rufipogon had shown a beneficial effect for yield-related traits in the 93-11 genetic background.In addition,five QTLs controlling yield and its components were newly identified,indicating that there arc potentially novel alleles in Yuanjiang common wild rice.Three regions underling significant QTLs for several yield-related traits were detected on chromosome 1,7 and 12.The QTL clusters were founded and corresponding agronomic traits of those QTLs showed highly significant correlation,suggesting the pleiotropism or tight linkage.Fine-mapping and cloning of these yield-related QTLs from wild rice would be helpful to elucidating molecular mechanism of rice domestication and rice breeding in the future.     

Conditional and unconditional QTL mapping of drought-tolerance-related traits of wheat seedling using two related RIL populations

For discovering the quantitative trait loci (QTLs) contributing to early seedling growth and drought tolerance during germination, conditional and unconditional analyses of 12 traits of wheat seedlings: coleoptile length, seedling height, longest root length, root number, seedling fresh weight, stem and leaves fresh weight, root fresh weight, seedling dry weight, stem and leaves dry weight, root dry weight, root to shoot fresh weight ratio, root-to-shoot dry weight ratio, were conducted under two water conditions using two F_8:9 recombinant inbred line (RIL) populations. The results of unconditional analysis are as follows: 88 QTLs accounting for 3.33–77.01% of the phenotypic variations were detected on chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 4A, 4B, 4D, 5A, 5B, 5D, 6A, 6B, 6D, 7A, 7B and 7D. Among these QTLs, 19 were main-effect QTLs with a contribution rate greater than 10%. The results of the conditional QTL analysis of 12 traits under osmotic stress on normal water conditions were as follows: altogether 22 QTLs concerned with drought tolerance were detected on chromosomes 1B, 2A, 2B, 3B, 4A, 5D, 6A, 6D, 7B, and 7D. Of these QTLs, six were main-effect QTLs. These 22 QTLs were all special loci directly concerned with drought tolerance and most of them could not be detected by unconditional analysis. The finding of these QTLs has an important significance for fine-mapping technique, map-based cloning, and molecular marker-assisted selection of early seedling traits, such as growth and drought tolerance.     

QTL studies reveal little relevance of chilling-related seedling traits for yield in maize

Prolonged low temperature phases and short-term cold spells often occur in spring during the crucial stages of early maize (Zea mays L.) development. The effect of low temperature-induced growth retardation at the seedling stage on final yield is poorly studied. Therefore, the aim was to identify genomic regions associated with morpho-physiological traits at flowering and harvest stage and their relationship to previously identified quantitative trait loci (QTLs) for photosynthesis and morpho-physiological traits from the same plants at seedling stage. Flowering time, plant height and shoot biomass components at harvest were measured in a dent mapping population for cold tolerance studies, which was sown in the Swiss Midlands in early and late spring in two consecutive years. Early-sown plants exhibited chilling stress during seedling stage, whereas late-sown plants grew under favorable conditions. Significant QTLs, which were stable across environments, were found for plant height and for the time of flowering. The QTLs for flowering were frequently co-localized with QTLs for plant height or ear dry weight. The comparison with QTLs detected at seedling stage revealed only few common QTLs. A pleiotropic effect was found on chromosome 3 which revealed that a good photosynthetic performance of the seedling under warm conditions had a beneficial effect on plant height and partially on biomass at harvest. However, a high chilling tolerance of the seedling seemingly had an insignificant or small negative effect on the yield.     

Identification of QTLs for root characteristics in maize grown in hydroponics and analysis of their overlap with QTLs for grain yield in the field at two water regimes

We investigated the overlap among quantitative trait loci (QTLs) in maize for seminal root traits measured in hydroponics with QTLs for grain yield under well-watered (GY-WW) and water-stressed (GY-WS) field conditions as well as for a drought tolerance index (DTI) computed as GY-WS/GY-WW. In hydroponics, 11, 7, 9, and 10 QTLs were identified for primary root length (R1L), primary root diameter (R1D), primary root weight (R1W), and for the weight of the adventitious seminal roots (R2W), respectively. In the field, 7, 8, and 9 QTLs were identified for GY-WW, GY-WS, and DTI, respectively. Despite the weak correlation of root traits in hydroponics with GY-WW, GY-WS, and DTI, a noticeable overlap between the corresponding QTLs was observed. QTLs for R2W most frequently and consistently overlapped with QTLs for GY-WW, GY-WS, and/or DTI. At four QTL regions, an increase in R2W was positively associated with GY-WW, GY-WS, and/or DTI. A 10 cM interval on chromosome 1 between PGAMCTA205 and php20644 showed the strongest effect on R1L, R1D, R2W, GY-WW, GY-WS, and DTI. These results indicate the feasibility of using hydroponics in maize to identify QTL regions controlling root traits at an early growth stage and also influencing GY in the field. A comparative analysis of the QTL regions herein identified with those described in previous studies investigating root traits in different maize populations revealed a number of QTLs in common.     

QTL analyses of heterosis for grain yield and yield-related traits in indica-japonica crosses of rice (Oryza sativa L.)

Two sets of rice materials, 166 RILs derived from a cross between Milyang 23 (Korean indica-type rice) and Tong 88-7 (japonica Rice), and BC₁F₁ hybrids derived from crosses between the RILs and the female parent, Milyang 23, were produced to identify QTLs for heterosis of yield and yield-related traits. The QTLs were detected from three different phenotype data sets including the RILs, BC1F1 hybrids, and mid-parental heterosis data set acquired from the definition of mid-parental heterosis. A total of 57 QTLs were identified for nine traits. Of eight QTLs detected for yield heterosis, five overlapped with other heterosis QTLs for yield-related traits such as spikelet number per panicle, days to heading, and spikelet fertility. Four QTLs for yield heterosis, gy1.1, py6, gy10, and py11, were newly identified in this study. We identified a total of 17 EpQTLs for yield heterosis that explain 21.4 ?? 59.0 % of total phenotypic variation, indicating that epistatic interactions may play an important role in heterosis.     

Conditional QTL mapping of protein content in wheat with respect to grain yield and its components

Grain protein content in wheat (Triticum aestivum L.) is generally considered a highly heritable character that is negatively correlated with grain yield and yield-related traits. Quantitative trait loci (QTL) for protein content was mapped using data on protein content and protein content conditioned on the putatively interrelated traits to evaluate possible genetic interrelationships between protein content and yield, as well as yield-related traits. Phenotypic data were evaluated in a recombinant inbred line population with 302 lines derived from a cross between the Chinese cultivar Weimai 8 and Luohan 2. Inclusive composite interval mapping using IciMapping 3.0 was employed for mapping unconditional and conditional QTL with additives. A strong genetic relationship was found between protein content and grain yield, and yield-related traits. Unconditional QTL mapping analysis detected seven additive QTL for protein content, with additive effects ranging in absolute size from 0.1898% to 0.3407% protein content, jointly accounting for 43.45% of the trait variance. Conditional QTL mapping analysis indicated two QTL independent from yield, which can be used in marker-assisted selection for increasing yield without affecting grain protein content. Three additional QTL with minor effects were identified in the conditional mapping. Of the three QTLs, two were identified when protein content was conditioned on yield, which had pleiotropic effects on those two traits. Conditional QTL mapping can be used to dissect the genetic interrelationship between two traits at the individual QTL level for closely correlated traits. Further, conditional QTL mapping can reveal additional QTL with minor effects that are undetectable in unconditional mapping.     

Quantitative trait loci underlying domestication- and yield-related traits in an Oryza sativa x Oryza rufipogon advanced backcross population

To understand the genetic characteristics of the traits related to differentiation between cultivated rice and its wild progenitor, genetic factors controlling domestication- and yield-related traits were identified using a BC3F2 population derived from an accession of common wild rice (donor, Oryza rufipogon Griff.) collected from Yuanjiang, Yunnan province, China, and an indica cultivar, Teqing (recipient, Oryza sativa L.). A genetic linkage map consisting of 125 simple sequence repeat (SSR) markers was constructed. Based on the phenotypes of the 383 BC3F2 families evaluated in two environments, two domestication-related morphological traits, panicle shape and growth habit, were found to be controlled by single Mendelian factors. This implies that the recessive mutations of single genes controlling some morphological traits could have been easily selected during early domestication. By single-point analysis and interval mapping, 59 putative quantitative trait loci (QTLs) that influence 11 quantitative traits were detected at two sites, and 37.5% of the QTL alleles originating from O. rufipogon had a beneficial effect for yield-related traits in the Teqing background. Regions with significant QTLs for domestication- and yield-related traits were detected on chromosomes 1, 4, 5, 7, 8, and 12. Fine mapping and cloning of these domestication-related genes and QTLs will be useful in elucidating the origin and differentiation of Asian cultivated rice in the future.     

Genomic regions underlying agronomic traits in linseed （Linum usitatissimum L.） as revealed by association mapping

The extreme climate of the Canadian Prairies poses a major chal enge to improve yield. Although it is possible to breed for yield per se, focusing on yield-related traits could be advantageous because of their simpler genetic architecture. The Canadian flax core col ection of 390 accessions was genotyped with 464 simple sequence repeat markers, and phenotypic data for nine agronomic traits including yield, bol s per area, 1,000 seed weight, seeds per bol , start of flowering, end of flowering, plant height, plant branching, and lodging col ected from up to eight environments was used for association mapping. Based on a mixed model （principal component analysis （PCA） t kinship matrix （K））, 12 significant marker-trait associations for six agronomic traits were identi-fied. Most of the associations were stable across environments as revealed by multivariate analyses. Statistical simulation for five markers associated with 1000 seed weight indicated that the favorable al eles have additive effects. None of the modern cultivars carried the five favorable al eles and the maximum number of four observed in any accessions was mostly in＆amp;nbsp;breeding lines. Our results confirmed the complex genetic architecture of yield-related traits and the inherent difficulties associated with their identification while il ustrating the potential for improvement through marker-assisted selection.     

Mapping QTLs of root morphological traits at different growth stages in rice

Roots are a vital organ for absorbing soil moisture and nutrients and influence drought resistance. The identification of quantitative trait loci (QTLs) with molecular markers may allow the estimation of parameters of genetic architecture and improve root traits by molecular marker-assisted selection (MAS). A mapping population of 120 recombinant inbred lines (RILs) derived from a cross between japonica upland rice 'IRAT109' and paddy rice 'Yuefu' was used for mapping QTLs of developmental root traits. All plant material was grown in PVC-pipe. Basal root thickness (BRT), root number (RN), maximum root length (MRL), root fresh weight (RFW), root dry weight (RDW) and root volume (RV) were phenotyped at the seedling (I), tillering (II), heading (III), grain filling (IV) and mature (V) stages, respectively. Phenotypic correlations showed that BRT was positively correlated to MRL at the majority of stages, but not correlated with RN. MRL was not correlated to RN except at the seedling stage. BRT, MRL and RN were positively correlated to RFW, RDW and RV at all growth stages. QTL analysis was performed using QTLMapper 1.6 to partition the genetic components into additive-effect QTLs, epistatic QTLs and QTL-by-year interactions (Q x E) effect. The results indicated that the additive effects played a major role for BRT, RN and MRL, while for RFW, RDW and RV the epistatic effects showed an important action and Q x E effect also played important roles in controlling root traits. A total of 84 additive-effect QTLs and 86 pairs of epistatic QTLs were detected for the six root traits at five stages. Only 12 additive QTLs were expressed in at least two stages. This indicated that the majority of QTLs were developmental stage specific. Two main effect QTLs, brt9a and brt9b, were detected at the heading stage and explained 19% and 10% of the total phenotypic variation in BRT without any influence from the environment. These QTLs can be used in breeding programs for improving root traits.     

Mapping Quantitative Trait Loci Associated with Toot Traits Using Sequencing-Based Genotyping Chromosome Segment Substitution Lines Derived from 9311 and Nipponbare in Rice (Oryza sativa L.)

Identification of quantitative trait loci (QTLs) associated with rice root morphology provides useful information for avoiding drought stress and maintaining yield production under the irrigation condition. In this study, a set of chromosome segment substitution lines derived from 9311 as the recipient and Nipponbare as donor, were used to analysis root morphology. By combining the resequencing-based bin-map with a multiple linear regression analysis, QTL identification was conducted on root number (RN), total root length (TRL), root dry weight (RDW), maximum root length (MRL), root thickness (RTH), total absorption area (TAA) and root vitality (RV), using the CSSL population grown under hydroponic conditions. A total of thirty-eight QTLs were identified: six for TRL, six for RDW, eight for the MRL, four for RTH, seven for RN, two for TAA, and five for RV. Phenotypic effect variance explained by these QTLs ranged from 2.23% to 37.08%, and four single QTLs had more than 10% phenotypic explanations on three root traits. We also detected the correlations between grain yield (GY) and root traits, and found that TRL, RTH and MRL had significantly positive correlations with GY. However, TRL, RDW and MRL had significantly positive correlations with biomass yield (BY). Several QTLs identified in our population were co-localized with some loci for grain yield or biomass. This information may be immediately exploited for improving rice water and fertilizer use efficiency for molecular breeding of root system architectures.