QTL analysis for rice grain length and fine mapping of an identified QTL with stable and major effects

Grain length in rice plays an important role in determining rice appearance, milling, cooking and eating quality. In this study, the genetic basis of grain length was dissected into six main-effect quantitative trait loci (QTLs) and twelve pairs of epistatic QTLs. The stability of these QTLs was evaluated in four environments using an F₇ recombinant inbred line (RIL) population derived from the cross between a Japonica variety, Asominori, and an Indica variety, IR24. Moreover, chromosome segment substitution lines (CSSLs) harboring each of the six main-effect QTLs were used to evaluate gene action of QTLs across eight environments. A major QTL denoted as qGL-3a, was found to express stably not only in the isogenic background of Asominori but also in the recombinant background of Asominori and IR24 under multiple environments. The IR24 allele at qGL-3a has a positive effect on grain length. Based on the test of advanced backcross progenies, qGL-3a was dissected as a single Mendelian factor, i.e., long rice grain was controlled by a recessive gene gl-3. High-resolution genetic and physical maps were further constructed for fine mapping gl-3 by using 11 simple sequence repeat (SSR) markers designed using sequence information from seven BAC/PAC clones and a BC₄F₂ population consisting of 2,068 individuals. Consequently, the gl-3 gene was narrowed down to a candidate genomic region of 87.5 kb long defined by SSR markers RMw357 and RMw353 on chromosome 3, which provides a basis for map-based cloning of this gene and for marker-aided QTL pyramiding in rice quality breeding.     

Identification of a stable quantitative trait locus for percentage grains with white chalkiness in rice (Oryza sativa)

High chalkiness is a major problem in many rice-producing areas of the world, especially in hybrid rice (Oryza sativa L.) in China. We previously showed a major quantitative trait locus for the percentage of grains with white chalkiness (QTLqPGWC-8) in the interval G1149-R727 on chromosome 8 using a chromosome segment substitution line (CSSL). Here, we selected the line-CSSL50 harboring the QTLqPGWC-8 allele from the CSSLs derived from a cross between Asominori (as a recurrent parent) and IR24 (as a donor parent), which had higher percentage chalkiness, markedly different from that of Asominori. There were also significant differences in starch granules, appearance of amylose content (AAC) and milling qualities between Asominori and CSSL50, but not in grain size or thousand grain weight (TGW). The BC(4) F(2) and BC(4) F(3) populations from a cross between CSSL50 and Asominori were used for fine mapping of qPGWC-8. We narrowed down the location of this QTL to a 142 kb region between Indel markers 8G-7 and 8G-9. QTLqPGWC-8 accounted for 50.9% of the difference in PGWC between the parents. The markers tightly linked to qPGWC-8 should facilitate cloning of the gene underlying this QTL and will be of value for marker-assisted selection in breeding rice varieties with better grain quality.     

Precise mapping Fhb5, a major QTL conditioning resistance to Fusarium infection in bread wheat (Triticum aestivum L.)

Qfhi.nau-5A is a major quantitative trait locus (QTL) against Fusarium graminearum infection in the resistant wheat germplasm Wangshuibai. Genetic analysis using BC(3)F(2) and BC(4)F(2) populations, derived from selfing two near-isogenic lines (NIL) heterozygous at Qfhi.nau-5A that were developed, respectively, with Mianyang 99-323 and PH691 as the recurrent parent, showed that Qfhi.nau-5A inherited like a single dominant gene. This QTL was thus designated as Fhb5. To fine map it, these two backcross populations and a recombinant inbred line (RIL) population derived from Nanda2419?×?Wangshuibai were screened for recombinants occurring between its two flanking markers Xbarc56 and Xbarc100. Nineteen NIL recombinants were identified from the two backcross populations and nine from the RIL population. In the RIL recombinant selection process, selection against Fhb4 present in the RIL population was incorporated. Genotyping these recombinant lines with ten markers mapping to the Xbarc56-Xbarc100 interval revealed four types of Mianyang 99-323-derived NIL recombinants, three types of PH691-derived NIL recombinants, and four types of RIL recombinants. In different field trials, the percentage of infected spikes of these lines displayed a distinct two-peak distribution. The more resistant class had over 55% less infection than the susceptible class. Common to these resistant genotypes, the 0.3-cM interval flanked by Xgwm304 and Xgwm415 or one of these two loci was derived from Wangshuibai, while none of the susceptible recombinants had Wangshuibai chromatin in this interval. This interval harboring Fhb5 was mapped to the pericentromeric C-5AS3-0.75 bin through deletion bin mapping. The precise localization of Fhb5 will facilitate its utilization in marker-assisted wheat breeding programs.     

利用RIL和CSSL群体检测水稻种子休眠性QTL

利用由梗稻品种Asominori与籼稻品种IR24的杂交组合衍生的重组自交F10。家系(Recombinant Inbred Lines,RIL)群体及其衍生的染色体片段置换系(Chromosome Segment Substitution Lines,CSSL)群体,进行了种子休眠性QTL的检测和遗传效应分析。其中CSSL群体有2个,即CSSLl(以Asominori为背景,置换片段来自IR24)和CSSL2(以IR24为背景,置换片段来自Asominori)。在RIL群体上共检测到3个种子休眠性QTL,分别位于第3、6和9染色体上;在CSSL1群体中检测到分布在第1、3和7染色体上的3个休眠性QTL;而在CSSl2群体上检测到的3个QTL则分别位于第1、2和7染色体上。同时在两套CSSL群体上,分别检测到位于第1、7染色体上位置相近且效应一致的休眠性QTL,分析表明其所在的Asominori片段含对种子休眠性的增效基因,相应的IB24段含有减效基因。     

A QTL for rice grain yield in aerobic environments with large effects in three genetic backgrounds

A large-effect QTL associated with grain yield in aerobic environments was identified in three genetic backgrounds, Apo/²*Swarna, Apo/²*IR72, and Vandana/²*IR72, using bulk-segregant analysis (BSA). Apo and Vandana are drought-tolerant aerobic-adapted varieties, while Swarna and IR72 are important lowland rice varieties grown on millions of hectares in Asia but perform poorly in aerobic conditions. Two closely linked rice microsatellite (RM) markers, RM510 and RM19367, located on chromosome 6, were found to be associated with yield under aerobic soil conditions in all three backgrounds. The QTL linked to this marker, qDTY6.1 (DTY, grain yield under drought), was mapped to a 2.2 cM region between RM19367 and RM3805 at a peak LOD score of 32 in the Apo/²*Swarna population. The effect of qDTY6.1 was tested in a total of 20 hydrological environments over a period of five seasons and in five populations in the three genetic backgrounds. In the Apo/²*Swarna population, qDTY6.1 had a large effect on grain yield under favorable aerobic (R ² ≤ 66%) and irrigated lowland (R ² < 39%) conditions but not under drought stress; Apo contributed the favorable allele in all the conditions where an effect was observed. In the Apo/IR72 cross, Apo contributed the favorable allele in almost all the aerobic environments in RIL and BC₁-derived populations. In the Vandana/IR72 RIL and BC₁-derived populations, qDTY6.1 had a strong effect on yield in aerobic drought stress, aerobic non-stress, and irrigated lowland conditions; the Vandana allele was favorable in aerobic environments and the IR72 allele was favorable in irrigated lowland environments. We conclude that qDTY6.1 is a large-effect QTL for rice grain yield under aerobic environments and could potentially be used in molecular breeding of rice for aerobic environments.     

QTL consistency and meta-analysis for grain yield components in three generations in maize

Grain yield is the most important and complex trait in maize. In this study, a total of 258 F₉ recombinant inbred lines (RIL), derived from a cross between dent corn inbred Dan232 and popcorn inbred N04, were evaluated for eight grain yield components under four environments. Quantitative trait loci (QTL) and their epistatic interactions were detected for all traits under each environment and in combined analysis. Meta-analysis was used to integrate genetic maps and detected QTL across three generations (RIL, F_2:3 and BC₂F₂) derived from the same cross. In total, 103 QTL, 42 pairs of epistatic interactions and 16 meta-QTL (mQTL) were detected. Twelve out of 13 QTL with contributions (R ²) over 15% were consistently detected in 3–4 environments (or in combined analysis) and integrated in mQTL. Only q100GW-7-1 was detected in all four environments and in combined analysis. 100qGW-1-1 had the largest R ² (19.3–24.6%) in three environments and in combined analysis. In contrast, 35 QTL for 6 grain yield components were detected in the BC₂F₂ and F_2:3 generations, no common QTL across three generations were located in the same marker intervals. Only 100 grain weight (100GW) QTL on chromosome 5 were located in adjacent marker intervals. Four common QTL were detected across the RIL and F_2:3 generations, and two between the RIL and BC₂F₂ generations. Each of five important mQTL (mQTL7-1, mQTL10-2, mQTL4-1, mQTL5-1 and mQTL1-3) included 7–12 QTL associated with 2–6 traits. In conclusion, we found evidence of strong influence of genetic structure and environment on QTL detection, high consistency of major QTL across environments and generations, and remarkable QTL co-location for grain yield components. Fine mapping for five major QTL (q100GW-1-1, q100GW-7-1, qGWP-4-1, qERN-4-1 and qKR-4-1) and construction of single chromosome segment lines for genetic regions of five mQTL merit further studies and could be put into use in marker-assisted breeding.     

Identification of Indica rice chromosome segments for the improvement of Japonica inbreds and hybrids

Exploitation of heterosis has brought significant advance in plant breeding and agricultural production, although its genetic basis is still poorly understood. In this study, a total of 66 chromosome segment substitution (CSS) lines, derived from a cross between japonica rice inbred line Asominori (as the recurrent parent) and indica rice inbred line IR24 (as the donor parent), were used to investigate the genetic basis of heterosis in indica × japonica inter-subspecific rice hybrids. Each CSS line was crossed with the background parent Asominori, and the heterosis of F(1) hybrids was estimated by comparing the F(1) performance with its two parental lines. Field experiments were carried out across six different environments to evaluate yield and yield-related traits in the 66 CSS lines and their 66 corresponding F(1) hybrids. Quantitative trait loci (QTL) analyses were conducted using a likelihood ratio test based on the stepwise regression. Thirty-six QTL were identified with significant effects in CSSL, 21 with significant effects in hybrids and 13 with significant effects in both. On the basis of average dominance degree, of all the 70 QTL affecting yield-related agronomic traits, 28.6% (20) showed an overdominance, 35.7% (25) a partial dominance and 30% (21) an additive effect, indicating that all effects contribute to trait variation in japonica-indica rice hybrids. Effects of these QTL were examined to identify Indica rice chromosome segments of interest for the improvement of japonica inbred lines and hybrids.     

籼稻稻米碾磨与外观品质性状的QTL定位

文章利用籼籼交组合特青/IRBB衍生的重组自交系群体, 在2个环境下对稻米碾磨品质和外观品质进行QTL定位。共计检测到控制稻米碾磨品质的QTL 12个和控制外观品质的QTL 18个, 包括糙米率8个、精米率2个、整精米率2个、粒长7个、粒宽5个和长宽比6个, 这些QTL分布于除第4和12染色体外的其他10条染色体上。其中, 第3染色体涵盖粒形基因GS3的区域对粒长、长宽比、糙米率和整精米率具有较大效应, 其献率分别为56.71%、42.23%、10.05%和4.91%; 第5染色体涵盖粒宽基因GW5的区域对粒宽、长宽比、糙米率和精米率具有较大效应, 表型变异贡献率分别为59.51%、36.68%、19.51%和4.56%。此外, 第6染色体涵盖直链淀粉含量基因Wx的区域对糙米率和精米率具有较小效应。GS3和GW5对糙米率和粒形具有重要作用。     

QTL Analysis of Aluminum Resistance in Rice (Oryza sativa L.)

Aluminum (Al) toxicity is considered as one of the primary causes of low-rice productivity in acid soils. In the present study, quantitative trait loci (QTLs) controlling Al resistance based on relative root elongation (RRE) were dissected using a complete linkage map and a recombinant inbred lines (RILs) derived from a cross of Al-tolerant japonica cultivar Asominori (Oryza sativa L.) and Al-sensitive indica cultivar IR24 (O. sativa L.). A total of three QTLs (qRRE-1, qRRE-9, and qRRE-11) were detected on chromosomes 1, 9, and 11 with LOD score ranging from 2.64 to 3.60 and the phenotypic variance explained from 13.5 to 17.7%. The Asominori alleles were all associated with Al resistance at all the three QTLs. The existence of these QTLs was confirmed using Asominori chromosome segment substitution lines (CSSLs) in IR24 genetic background (IAS). By QTL comparative analysis, the two QTLs (qRRE-1and qRRE-9) on chromosomes 1 and 9 appeared to be consistent among different rice populations while qRRE-11 was newly detected and syntenic with a major Al resistance gene on chromosome 10 of maize. This region may provide an important case for isolating genes responsible for different mechanisms of Al resistance among different cereals. These results also provide the possibilities of enhancing Al resistance in rice breeding program by marker-assisted selection (MAS) and pyramiding QTLs.     

Overdominant epistatic loci are the primary genetic basis of inbreeding depression and heterosis in rice. II. Grain yield components

The genetic basis underlying inbreeding depression and heterosis for three grain yield components of rice was investigated in five interrelated mapping populations using a complete RFLP linkage map, replicated phenotyping, and the mixed model approach. The populations included 254 F(10) recombinant inbred lines (RILs) derived from a cross between Lemont (japonica) and Teqing (indica), two backcross (BC) and two testcross populations derived from crosses between the RILs and the parents plus two testers (Zhong413 and IR64). For the yield components, the RILs showed significant inbreeding depression and hybrid breakdown, and the BC and testcross populations showed high levels of heterosis. The average performance of the BC or testcross hybrids was largely determined by heterosis. The inbreeding depression values of individual RILs were negatively associated with the heterosis measurements of the BC or testcross hybrids. We identified many epistatic QTL pairs and a few main-effect QTL responsible for >65% of the phenotypic variation of the yield components in each of the populations. Most epistasis occurred between complementary loci, suggesting that grain yield components were associated more with multilocus genotypes than with specific alleles at individual loci. Overdominance was also an important property of most loci associated with heterosis, particularly for panicles per plant and grains per panicle. Two independent groups of genes appeared to affect grain weight: one showing primarily nonadditive gene action explained 62.1% of the heterotic variation of the trait, and the other exhibiting only additive gene action accounted for 28.1% of the total trait variation of the F(1) mean values. We found no evidence suggesting that pseudo-overdominance from the repulsive linkage of completely or partially dominant QTL for yield components resulted in the overdominant QTL for grain yield. Pronounced overdominance resulting from epistasis expressed by multilocus genotypes appeared to explain the long-standing dilemma of how inbreeding depression could arise from overdominant genes.     

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

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

Fatness QTL on chicken chromosome 5 and interaction with sex

Quantitative trait loci (QTL) affecting fatness in male chickens were previously identified on chromosome 5 (GGA5) in a three-generation design derived from two experimental chicken lines divergently selected for abdominal fat weight. A new design, established from the same pure lines, produced 407 F2 progenies (males and females) from 4 F1-sire families. Body weight and abdominal fat were measured on the F₂ at 9 wk of age. In each sire family, selective genotyping was carried out for 48 extreme individuals for abdominal fat using seven microsatellite markers from GGA5. QTL analyses confirmed the presence of QTL for fatness on GGA5 and identified a QTL by sex interaction. By crossing one F1 sire heterozygous at the QTL with lean line dams, three recombinant backcross 1 (BC1) males were produced and their QTL genotypes were assessed in backcross 2 (BC2) progenies. These results confirmed the QTL by sex interaction identified in the F2 generation and they allow mapping of the female QTL to less than 8 Mb at the distal part of the GGA5. They also indicate that fat QTL alleles were segregating in both fat and lean lines.     

Overdominant epistatic loci are the primary genetic basis of inbreeding depression and heterosis in rice. I. Biomass and grain yield

To understand the genetic basis of inbreeding depression and heterosis in rice, main-effect and epistatic QTL associated with inbreeding depression and heterosis for grain yield and biomass in five related rice mapping populations were investigated using a complete RFLP linkage map of 182 markers, replicated phenotyping experiments, and the mixed model approach. The mapping populations included 254 F(10) recombinant inbred lines derived from a cross between Lemont (japonica) and Teqing (indica) and two BC and two testcross hybrid populations derived from crosses between the RILs and their parents plus two testers (Zhong 413 and IR64). For both BY and GY, there was significant inbreeding depression detected in the RI population and a high level of heterosis in each of the BC and testcross hybrid populations. The mean performance of the BC or testcross hybrids was largely determined by their heterosis measurements. The hybrid breakdown (part of inbreeding depression) values of individual RILs were negatively associated with the heterosis measurements of their BC or testcross hybrids, indicating the partial genetic overlap of genes causing hybrid breakdown and heterosis in rice. A large number of epistatic QTL pairs and a few main-effect QTL were identified, which were responsible for >65% of the phenotypic variation of BY and GY in each of the populations with the former explaining a much greater portion of the variation. Two conclusions concerning the loci associated with inbreeding depression and heterosis in rice were reached from our results. First, most QTL associated with inbreeding depression and heterosis in rice appeared to be involved in epistasis. Second, most ( approximately 90%) QTL contributing to heterosis appeared to be overdominant. These observations tend to implicate epistasis and overdominance, rather than dominance, as the major genetic basis of heterosis in rice. The implications of our results in rice evolution and improvement are discussed.     

QTL analysis of soybean seed weight across multi-genetic backgrounds and environments

Seed weight, measured as mass per seed, is an important yield component of soybean and is generally positively correlated with seed yield (Burton et al, Crop Sci 27:1093, 1987). In previous reports, quantitative trait loci (QTL) associated with seed weight, were identified in single genetic background. The objective of the present study was to identify QTL and epistatic QTL underlying soybean seed weight in three RIL populations (with one common male parent 'Hefeng25') and across three different environments. Overall, 18, 11, and 17 seed weight QTL were identified in HC ('Hefeng25' × 'Conrad'), HM ('Hefeng25' × 'Maple Arrow'), and HB ('Hefeng25' × 'Bayfield') populations, respectively. The amount of phenotypic variation explained by a single QTL underlying seed weight was usually less than 10 %. The environment and background-independent QTL often had higher additive (a) effects. In contrast, the environment or background-dependent QTL were probably due to weak expression of QTL. QTL by environment interaction effects were in the opposite direction of a effects and/or epistasis effects. Four QTL and one QTL could be identified (2.0 < LOD < 9.06) in the HC and HB populations, respectively, across three environments (swHCA2-1, swHCC2-1, swHCD1b-1, swHCA2-2 (linked to Satt233, Satt424, Satt460, Satt428, respectively) and swHBA1-1(Satt449). Seven QTL could be identified in all three RIL populations in at least one location. Two QTL could be identified in the three RIL populations across three environments. These two QTL may have greater potential for use in marker-assisted selection of seed weight in soybean.     

QTL analysis for grain quality traits in 2 BC2F2 populations derived from crosses between Oryza sativa cv Swarna and 2 accessions of O. nivara

The appearance and cooking quality of rice determine its acceptability and price to a large extent. Quantitative trait loci (QTLs) for 12 grain quality traits were mapped in 2 mapping populations derived from Oryza sativa cv Swarna × O. nivara. The BC(2)F(2) population of the cross Swarna × O. nivara IRGC81848 (population 1) was evaluated during 2005 and that from Swarna × O. nivara IRGC81832 (population 2) was evaluated during 2006. Linkage maps were constructed using 100 simple sequence repeat (SSR) markers in population 1 and 75 SSR markers in population 2. In all, 21 QTLs were identified in population 1 (43% from O. nivara) and 37 in population 2 (38% QTLs from O. nivara). The location of O. nivara-derived QTLs mp1.2 for milling percent, kw6.1 for kernel width, and klac12.1 for kernel length after cooking coincided in the 2 populations and appear to be useful for Marker Assisted Selection (MAS). Four QTLs for milling percent, 1 QTL each for amylose content, water uptake, elongation ratio, 2 QTLs for kernel width, and 3 QTLs for gel consistency, each explained more than 20% phenotypic variance. Three QTL clusters for grain quality traits were close to the genes/QTLs for shattering and seed dormancy. QTLs for 4 quality traits were associated with 5 of the 7 major yield QTLs reported in the same 2 mapping populations. Useful introgression lines have been developed for several agronomic traits. It emerges that 40% O. nivara alleles were trait enhancing in both populations, and QTLs for grain quality overlapped with yield meta-QTLs and QTLs for dormancy and seed shattering.     

基于分离亚群体QTL定位的模拟研究

在数量性状QTL的精细定位中, 通过数量性状目标QTL的近等基因系可构建分离群体。在目标QTL效应较大的情况下, 数量性状表型值可反映目标QTL的基因型。若目标QTL附近的标记密度大时, 大样本才能定位该QTL。但是, 这增加了试验费用。为节约试验经费, 若只利用QTL纯合隐性基因型植株的分子标记信息, 也可比较准确地定位该QTL。利用极大似然法, 分别推导出F2、BC、DH以及RIL群体中重组率及其标准误的估计公式。Monte Carlo模拟研究表明, 基于定位群体中全部数据或隐性纯合基因型数据所获得的重组率估计值是一致的, 且在相同样本容量条件下, 二者精度相当。     

Map-based cloning proves qGC-6, a major QTL for gel consistency of japonica/indica cross, responds by Waxy in rice (Oryza sativa L.)

In this study, one major QTL affecting gel consistency (GC) of japonica/indica cross was identified on chromosome 6 using a DH population. To understand the molecular mechanism that regulates GC in rice grains, the major QTL (qGC-6) was isolated through a map-based cloning approach utilizing chromosome segment substitution lines (CSSLs). Using 64 plants with extremely soft GC that were selected on recombinant break points between two SSR markers, RM540 and RM8200 in a BC4F2 population, qGC-6 was mapped to a 60-kb DNA region between two STS markers, S26 and S27. These two markers were then used to further identify recombination break points. Finally, qGC-6 was delimited in an interval of a 11-kb region. Gene prediction analysis of the 11-kb DNA sequence containing qGC-6 identified only one putative ORF, which encodes granule-bound starch synthesis protein (Wx protein). Results of sequencing analysis and complementation experiment confirmed that this candidate ORF is responsible for rice GC. Genetic evidences revealed that Wx might contribute equally to the grain amylose content-controlling gene as well as gel consistency. This new information is important to breed rice varieties with improved grain quality.     

Mapping of a major QTL for pre-harvest sprouting tolerance on chromosome 3A in bread wheat

Quantitative trait loci (QTL) analysis was conducted for pre-harvest sprouting tolerance (PHST) in bread wheat for a solitary chromosome 3A, which was shown to be important for this trait in earlier studies. An intervarietal mapping population in the form of recombinant inbred lines (RILs) developed from a cross between SPR8198 (a PHS tolerant genotype) and HD2329 (a PHS susceptible cultivar) was used for this purpose. The parents and the RIL population were grown in six different environments and the data on PHS were collected in each case. A framework linkage map of chromosome 3A with 13 markers was prepared and used for QTL analysis. A major QTL (QPhs.ccsu-3A.1) was detected on 3AL at a genetic distance of ∼183 cM from centromere, the length of the map being 279.1 cM. The QTL explained 24.68% to 35.21% variation in individual environments and 78.03% of the variation across the environments (pooled data). The results of the present study are significant on two counts. Firstly, the detected QTL is a major QTL, explaining up to 78.03% of the variation and, secondly, the QTL showed up in all the six environments and also with the pooled data, which is rather rare in QTL analysis. The positive additive effects in the present study suggest that a superior allele of the QTL is available in the superior parent (SPR8198), which can be used for marker-aided selection for the transfer of this QTL allele to obtain PHS-tolerant progeny. It has also been shown that the red-coloured grain of PHS tolerant parent is not associated with the QTL for PHST identified during the present study, suggesting that PHS tolerant white-grained cultivars can be developed.Electronic Supplementary Material Supplementary material is available for this article at     

Simultaneous improvement and genetic dissection of grain yield and its related traits in a backbone parent of hybrid rice (Oryza sativa L.) using selective introgression

Three populations with a total of 125 BC2F3:4 introgression lines (ILs) selected for high yields from three BC2F2 populations were used for genetic dissection of rice yield and its related traits. The progeny testing in replicated phenotyping across two environments and genotyping with 140 polymorphic simple sequence repeat markers allowed the identification of 21 promising ILs that had significantly higher yields than the recurrent parent Shuhui527 (SH527). A total of 94 quantitative trait loci (QTL) were identified using the selective introgression method based on Chi-squared (χ ²) and multi-locus probability tests and the RSTEP-LRT method based on stepwise regression. These QTL were mostly mapped to 12 clusters on seven rice chromosomes. Several important properties of the QTL affecting grain yield (GY) and its related traits were revealed. The first one was the presence of strong and frequent non-random associations between or among QTL that affect low-heritability traits (GY and spikelet number per panicle, SN) in the ILs with high trait values. Second, beneficial alleles at 88.9 % GY and 75 % SN QTL for increased productivity were from the donors, suggesting that direct phenotypic selection for high yield in our introgression breeding program was a powerful way to transfer beneficial alleles at many loci from the donors into SH527. Third, most QTL were in clusters with large effects on multiple traits, which should be the focal points in further investigations and marker-assisted selection in rice. The majority of the QTL identified were expressed only in one of the environments, suggesting that differential expression of QTL in different environments is the primary genetic basis of genotype × environment interaction. Finally, a large variation in both the direction and magnitude of QTL effects was detected for different donor alleles at seven QTL in the same genetic background and environments. This finding suggests the possible presence of functional diversity among the donor alleles at these loci. The promising ILs and QTL identified provide valuable materials and genetic information for further improving the yield potential of SH527, which is a backbone restorer of hybrid rice in China.