Evaluation and development of flood‐tolerant soybean cultivars

Soybean (Glycine max [L.] Merr.) cultivars are generally sensitive to flooding stress. The plant growth is severely affected and grain yield is largely reduced in the flooded field. It is important to develop flood‐tolerant soybean cultivars for grain production in regions of heavy rainfalls worldwide. In this study, a total of 722 soybean genotypes were evaluated for flooding tolerance at R1 stages (first flower at any node) in the 5‐year flooding screening tests. Differential soybean genotypes exhibited diverse responses to flooding stress with that plant foliar damage score (FDS) and plant survival rate (PSR) ranged from 1.9 to 8.8 and 3.4% to 81.7%, respectively (p < .0001). Based on our standard of flooding evaluation, most genotypes were sensitive to flooding with 6.0 of average FDS and 38.7% of PSR. Fifty‐two soybean genotypes showed flooding tolerance and 11 genotypes were with consistent flooding tolerance during 4‐ to 5‐year continual evaluations. In the meantime, six genotypes were identified with consistent high sensitivity to flooding. The group analysis showed that genotypes from different sources had distinguishable responses to flooding stress (p < .0001). The interacting analysis of year and flooding tolerance indicated that FDS and PSR means were significantly different among 5 years due to weather temperature and flooding treatment time influences of each year (p < .0001). Furthermore, five breeding lines with high‐yielding and flood‐tolerant traits were developed using selected consistent flood‐tolerant and high‐yielding genotypes through conventional breeding approach.     

Quantitative trait loci controlling rice seed germination under salt stress

Salt tolerance of rice (Oryza sativa L.) at the seed germination stage is one of the major determinants for the stable stand establishment in salinity soil. One population of recombinant inbred lines (RILs, F_2:9), derived from a cross between a japonica rice landrace tolerant to salt stress and a sensitive indica rice variety, was used to determine the germination traits including imbibition rate and germination percentage under control (water) and salt stress (100 mM NaCl) for 10 days at 30 °C. The multiple interval mapping (MIM) were applied to conduct QTL for the traits. The results showed that seed germination was a quantitative trait controlled by several genes, and strongly affected by salt stress. A total of 16 QTLs were detected in this study, and each QTL could explain 4.6–43.7% of the total phenotypic variance. The expression of these QTLs might be developmentally regulated and growth stage-specific. In addition, only one digenic interaction was detected under salt stress, showing small effect on germination percentage with R² 2.7%. Among sixteen QTLs detected in this study, four were major QTLs with R² > 30%, and some novel alleles of salt tolerance genes in rice. The results demonstrated that the japonica rice Jiucaiqing is a good source of gene(s) for salt tolerance and the major or minor QTLs identified could be used to improve the salt tolerance by marker-assisted selection (MAS) in rice.     

Mapping quantitative trait loci (QTLs) underlying seed vitamin E content in soybean with main,epistatic and QTL × environment effects

Soybean (Glycine max (L.) Merr.) seed contains small amounts of tocopherol, a non‐enzymatic antioxidant known as lipid‐soluble vitamin E (VE). Dietary VE contributes to a decreased risk of chronic diseases in humans and has several beneficial effects on resistance to stress in plants, and increasing VE content is an important breeding goal for increasing the nutritional value of soybean. In this study, quantitative trait loci (QTLs) underlying VE content with main, epistatic and QTL × environment effects were identified in a population of F_5 : 6 recombinant inbred lines from a cross between ‘Hefeng 25’ (a low‐VE cultivar) and ‘OAC Bayfield’ (a high‐VE cultivar). A total of 18 QTLs were detected that showed additive main effects (a) and/or additive × environment interaction effects (ae) in different environments. Moreover, 19 epistatic pairs of QTLs were found to be associated with α‐tocopherol (α‐Toc), γ‐tocopherol (γ‐Toc), δ‐tocopherol (δ‐Toc) and total VE (TE) contents. The QTLs identified in multienvironments could provide more information about QTL by environment interactions and could be useful for the marker‐assistant selection of soybean cultivars with high seed VE contents.     

Genetic studies on saline and sodic tolerances in soybean

Salt-affected soils are generally classified into two main categories: saline and sodic (alkaline). Developing and using soybean (Glycine max (L.) Merr) cultivars with high salt tolerance is an effective way of maintaining sustainable production in areas where soybean growth is threatened by salt stress. Early classical genetics studies revealed that saline tolerance was conditioned by a single dominant gene. Recently, a series of studies consistently revealed a major quantitative trait locus (QTL) for saline tolerance located on linkage group N (chromosome 3) around the SSR markers Satt255 and Sat_091; other minor QTLs were also reported. In the case of sodic tolerance, most studies focused on iron deficiency caused by a high soil pH, and several QTLs associated with iron deficiency were identified. A wild soybean (Glycine soja Sieb. & Zucc.) accession with high sodic tolerance was recently identified, and a significant QTL for sodic tolerance was detected on linkage group D2 (chromosome 17). These studies demonstrated that saline and sodic tolerances were controlled by different genes in soybean. DNA markers closely associated with these QTLs can be used for marker-assisted selection to pyramid tolerance genes in soybean for both saline and sodic stresses.     

Dissection of genetic architecture for oil content in soybean seed using two backcross populations

Soybean seed oil was valued in foods, animal feed and some industrial applications. Molecular marker‐assisted selection (MAS) for high‐oil‐content cultivars was an important method for soybean breeders. The objective of this study was to identify quantitative trait loci (QTL) and epistatic QTL underlying the seed oil content of soybeans across two backcross (BC) populations (with one common male parent ‘Dongnong47’) and two different environments. Two molecular genetic maps were constructed. They encompassed 1046.8 cM [with an average distance of 6.75 cM in the ‘Dongnong47’  ×  ‘Jiyu89’ (DJ) population] and 846.10 cM [with an average distance of 5.76 cM in the ‘Dongnong47’  ×  ‘Zaoshu18’ (DZ) population]. Nine and seven QTL were identified to be associated with oil content in the DJ and DZ populations, respectively. The phenotypic variation explained by most of the QTL was usually less than 10%. Among the identified QTL, those stable ones across multiple environments and populations often had stronger additive effects. In addition, three stable QTL in the DZ populations were identified in the similar genomic region of the three QTL in the DJ population [qDJE and qDZE‐1 were located near Satt151 of Chromosome 15 (Chr15), qDJA1 and qDZA1 were located near Satt200 of Chr15 (LG A1), and qDJD2‐1 and qDZD2‐1 were located near Sat365 of Chr17]. In conclusion, MAS will be able more effectively to combine beneficial alleles of the different donors to design new genotypes with higher soybean seed oil content using the BC populations.     

A SNP genetic linkage map based on the ‘Hamilton’ by ‘Spencer’ recombinant inbred line population identified QTL for seed isoflavone contents in soybean

Soybean is one of the most important crops worldwide for its protein and oil as well as the health beneficial phytoestrogens or isoflavone. This study reports a relatively dense single nucleotide polymorphism (SNP)‐based genetic map based on ‘Hamilton’ by ‘Spencer’ recombinant inbred line population and quantitative trait loci (QTL) for seed isoflavone contents. The genetic map is composed of 1502 SNP markers and covers about 1423.72 cM of the soybean genome. Two QTL for seed isoflavone contents have been identified in this population. One major QTL that controlled both daidzein (qDZ1) and total isoflavone contents (qTI1) was found on LG C2 (Chr 6). And a second QTL for glycitein content (qGT1) was identified on the LG G (Chr 18). These two QTL in addition to others identified in soybean could be used in soybean breeding to optimize isoflavone content. This newly assembled soybean linkage map is a useful tool to identify and map QTL for important agronomic traits and enhance the identification of the genes involved in these traits.     

Quantitative trait locus mapping for seed artificial aging traits using an F2:3 population and a recombinant inbred line population crossed from two highly related maize inbreds

Quantitative trait locus (QTL) mapping for seed longevity is essential for breeding modern cultivars with resistance to deterioration during postharvest storage. The inbred lines X178 and I178 showed large differences in seed vigour after artificial aging treatment, while they had similar performances in terms of most agronomic traits. An F_2:3 population and a recombinant inbred line (RIL) population were generated to map QTL after 5 days under artificial aging conditions. Positive correlations were observed among all investigated traits including the aging germination rate, relative aging germination rate, aging simple vigour index, aging primary root length, aging shoot length and aging total length. Thirteen QTL were identified to locate on five chromosome regions: Chr.1:297 Mb (chromosome 1 region 297 Mb), Chr.3:205 Mb, Chr.4:240 Mb, Chr.5:205 Mb and Chr.7:155 Mb, with 2 to 4 QTL co‐located on a region. In each region, 3–8 previously identified aging‐related QTL were located, confirming the importance of these regions for controlling seed longevity in different maize populations. Taken together, the results of this work provide a foundation for further QTL fine mapping and the molecular‐assisted breeding of aging tolerant maize.     

Selection of soybean elite cultivars based on phenotypic and genomic characters related to lodging tolerance

Soybean lodging can result in serious yield reduction. Detecting the quantitative trait loci (QTL) associated with lodging tolerance for their further application in marker‐assisted selection (MAS) has the potential to enhance soybean breeding efficiency. In this study, a genome‐wide association analysis (GWAS) was performed to identify soybean accessions that could potentially be used to produce lodging‐tolerant varieties, based on the comprehensive evaluation of lodging scores (LS) obtained for the parental cultivar “Tokachi nagaha” and its 137 derived cultivars. Results showed that genotype, environment and genotype × environment interaction significantly influenced LS. Of the 31 significant SNPs identified, 22 were consistently detected in two or more environments and 27 SNPs were located in or close to agronomically important QTL mapped by linkage analysis. Best linear unbiased predictors (BLUPs) of LS tend to decrease with the elite alleles contained by accessions increasing. Some excellent accessions, with lower BLUPs and D_i (stability coefficients) values and more elite alleles, were selected. This study contributed to understand the genetic mechanism of lodging, providing genetic and phenotypic information for MAS.     

Mapping of Quantitative Trait Loci Associated with Reproductive‐Stage Salt Tolerance in Rice

Salinity tolerance in rice varies with the state of growth, with the seedling and reproductive stages being the most sensitive. However, association between tolerances at the two stages is poor, suggesting that they are regulated by different processes and genes. Tolerance at the reproductive stage is the most crucial as it determines grain yield. An F₂ mapping population was developed from two rice genotypes contrasting in tolerance: Cheriviruppu and Pusa Basmati 1 (PB1). Cheriviruppu is highly tolerant at the reproductive stage, while PB1 is highly sensitive at both seedling and reproductive stages. One hundred and thirty‐one microsatellite markers polymorphic between the parents were used to construct a linkage map of 1458.5 cM (Kosambi), with a mean intermarker distance of 11.1 cM. Sixteen QTLs with LOD values ranging from 3.2 to 22.3 were identified on chromosomes 1, 7, 8 and 10, explaining 4–47 % of the phenotypic variation. The maximum number of QTL clusters for different component traits was colocalized on the long arm of chromosome 1 and chromosome 7. We identified several significant epistatic interactions, including three inter‐QTL interactions, using MapManager. The results suggest that pollen fertility, Na⁺ concentration and Na/K ratio in the flag leaf are the most important mechanisms controlling salt tolerance at the reproductive stage in rice. The study reports the construction of a genetic map for reproductive‐stage salt tolerance in rice and demonstrates its utility for molecular mapping of QTLs controlling salinity tolerance‐related traits, which will be useful in marker‐assisted selection in the future.     

An effective field screening method for flood tolerance in soybean

Flooding is an abiotic stress that causes considerable reductions in crop growth and yield worldwide. Soybean (Glycine max [L.] Merr.) cultivars are generally sensitive to flooding stress. The objective of this study was to develop an effective flooding tolerance screening method in the field. A total of 40 soybean genotypes were evaluated for flooding tolerance at V5 and R1 growth stages. At each stage, genotypes were exposed to different durations of flooding stress (3, 6, 9, 12 and 15 days). Plant foliar damage score (FDS) and plant survival rate (PSR) were used as the indicators of flooding tolerance. Soybeans were more sensitive to flooding at R1 growth stage than V5 growth stage. Length of flooding duration accounted for the variance of FDS and PSR. Soybean genotypes exposed to a 3‐day flooding in either V5 or R1 growth stage, did not show obvious foliar damage, while genotypes exposed to a 12‐ or 15‐day flooding showed significant foliar damage and plant death. The optimum flooding duration to screen for flooding tolerance in the field was determined to be 9 and 6 days for V5 and R1 growth stages, respectively, as distinguishable responses to flooding allowed genotypes to be classified as either being flooding tolerant or flooding sensitive. High correlation between FDS and PSR (.99, p < .0001) was observed. Similarly, FDS and PSR were highly correlated with grain yield (.95 and .95, p < .0001). The field screening method for flooding tolerance developed in our study will be favourable for selection of soybean flooding‐tolerant germplasm.     

甘蓝型油菜盐胁迫下幼苗鲜重和干重QTL定位及候选基因分析

盐胁迫是非生物胁迫中影响作物产量的一个主要因素,利用分子标记方法选育油菜耐盐品种对提高油菜产量具有重要意义。选用来自GH06与P174杂交后通过单粒传法连续自交获得的高世代重组自交系群体,以含16 g L–1Na Cl的Hoagland溶液培养幼苗进行盐胁迫处理25 d后,分别测定叶和根的鲜重及干重,根据已构建的高密度SNP遗传连锁图谱进行QTL定位,在QTL物理区间筛选耐盐相关基因并以极端表型材料进行q RT-PCR分析。采用复合区间作图法(CIM),在对照和盐胁迫处理中共检测到19个QTL,其中与盐胁迫相关的有6个,可解释的表型变异7.16%~16.15%,分布在A02、A04和C03染色体上,将QTL置信区间序列和拟南芥中与盐胁迫相关的基因比对分析,共找到8个候选基因。对其中4个候选基因在极端表型材料中的表达分析表明,BnaA02g14680D与BnaA02g14490D基因在盐胁迫处理后的48 h或72 h表达量均高于对照组,即基因的表达由盐胁迫引起,而BnaC03g64030D在敏感型材料中的相对表达量高于在耐盐型材料中,BnaC03g62830D在敏感型材料中没有明显变化,但在耐盐型材料中呈现先升高后降低的表达特征,其表达可能会增强植株对盐胁迫的耐受力。本研究为油菜耐盐基因功能挖掘和油菜耐盐品种选育奠定基础。     

Detection of quantitative trait loci for phosphorus deficiency tolerance at soybean seedling stage

Phosphorus deficiency is a primary constraint to soybean productivity in acid and calcareous soils. Our aim was to map quantitative trait loci (QTL) controlling phosphorus deficiency tolerance using 152 recombinant inbred lines derived from a cross between the P stress tolerant variety Nannong94-156 and the P stress sensitive variety Bogao. Five traits were used as parameters to evaluate phosphorus deficiency tolerance at seedling stage under different phosphorus levels in experiments 2005 and 2006. As a result, thirty-four additive QTLs were detected on nine linkage groups, with corresponding contribution ratios of 6.6–19.3%. There were three clusters of QTL found in genomic regions S506-Satt534 (on linkage group B2-1), Sat_183-Satt274 (on linkage group D1b + W), and Sat_185-Satt012 (on linkage group G). The locus flanked by Sat_183-Satt274 on linkage group D1b + W was coincident with four previously discovered QTLs with phosphorus efficiency. Another interesting locus flanked by Sat_185-Satt012 on linkage group G was detected across years. The identified QTL will be useful to improve the stress resistance of soybean against a complex nutritional disorder caused by phosphorus deficiency. In addition, more QTLs were detected under low phosphorus condition and some QTLs were detected that specifically expressed under different phosphorus levels. These particular QTLs could help provide greater understanding of the genetic basis of phosphorus efficiency in soybean.     

Confirmation of quantitative trait loci for resistance to multiple-HG types of soybean cyst nematode (<Emphasis Type="Italic">Heterodera glycines</Emphasis> Ichinohe)

Genetic analysis of resistance of plant introduction (PI) 438489B to soybean cyst nematode (SCN) have shown that this PI is highly resistant to many SCN HG types. However, validation of the previously detected quantitative trait loci (QTL) has not been done. In this study, 250 F_2:3 progeny of a Magellan (susceptible) × PI 438489B (resistant) cross were used for primary genetic mapping to detect putative QTL for resistance to five SCN HG types. QTL confirmation study was subsequently conducted using F_6:7 recombinant inbred lines (RILs) derived from the same cross. Simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers were employed for molecular genotyping. Interval mapping (IM), permutation tests, cofactor selection, and composite interval mapping (CIM) were performed to identify and map QTL. Results showed that five QTL intervals were associated with resistance to either multiple- or single-HG types of SCN. Among these, two major QTL for resistance to multiple-SCN HG types were mapped to chromosomes (Chr.) 8 and 18, consistent with the known rhg1 and Rhg4 locations. The other QTL were mapped to Chr. 4. The results of our study confirmed earlier reported SCN resistance QTL in this PI. Moreover, SSR and SNP molecular markers tightly linked to these QTL can be useful for the near-isogenic lines (NILs) development aiming to fine-mapping of these QTL regions and map-based cloning of SCN resistance candidate genes.     

Identification of quantitative trait loci and candidate genes controlling the tocopherol synthesis pathway in soybean (Glycine max)

A recombinant inbred line (RIL) population was used to identify quantitative trait loci (QTLs) and their candidate genes controlling the tocopherol (Toc) synthesis pathway. The RIL population was cultivated in field conditions in 3 years. A genetic map constructed using 1624 DNA markers was used for QTL analysis. We identified 22 QTLs for seed tocopherol contents and their ratios, of which two QTL clusters on chromosomes (Chr) 9 and 14 exerted consistent large effects on tocopherol composition across the 3 years. The QTL cluster localized on Chr 9 might correspond to γ-TMT3, which controls the conversion of γ-Toc into α-Toc. The QTL cluster localized on Chr 14 was novel, which might regulate the conversion of MPBQ (a precursor of δ-Toc) into DMPBQ (the precursor of γ-Toc). The effect of the QTL cluster on Chr 14 was validated in a pair of near isogenic lines, and its candidate gene was mined. The identified QTLs and their candidate genes might be used in breeding programmes to improve α-Toc content in soybean seeds.     

Meta‐analysis and overview analysis of quantitative trait locis associated with fatty acid content in soybean for candidate gene mining

As soybean seed fatty acid content is valued in food, animal feed and some industrial applications, plant breeders continually aim to improve seed fatty acid constituent value. This study analysed 163 original quantitative trait loci (QTLs) related to soybean fatty acid content from databases and references and revealed 43 consensus QTLs. Meta‐analysis using BioMercator ver.2.1 indicated that these were located across 16 linkage groups (LGs) excluding LG D1a, LG C1, LG M and LG H. Moreover, the overview method was used to optimize these QTLs based on statistical analysis. Some valid QTL regions were narrowed down to 0.5 Mb and mapped on the same LGs as the meta‐analysis result. Furthermore, the functions of all genes located in these consensus QTL intervals were predicted and eight candidate genes were identified. KEGG pathway analysis indicated that Glyma.13G127900 and Glyma.18G232000 were involved in the fatty acid synthesis metabolic (pathway ID ko00071, ko00062, ko01040). These results lay a foundation for fine mapping of QTLs related to fatty acid content and marker‐assisted breeding in soybean.     

QTLs for phosphorus deficiency tolerance detected in upland NERICA varieties

Phosphorous (P) deficiency is a major yield limiting factor in rice (Oryza sativa L.) production. The interspecific New Rice for Africa (NERICA) varieties combine general stress tolerance from African cultivated rice (Oryza glaberrima Steud) with characteristics associated with high yield from O. sativa. However, little is known about their ability to tolerate P deficiency. Here, we examined the variation for tolerance to P deficiency among the 18 upland NERICAs and their parents in multi‐year field experiments. The good performance under P deficiency of the O. glaberrima parent CG 14 and some NERICAs suggested that these tolerant NERICAs contain loci associated with P deficiency tolerance inherited from CG 14. Additionally, four QTL clusters for P deficiency tolerance were detected on chromosomes 4, 6 and 11 using F₃ lines derived from the cross between the P deficiency tolerant variety NERICA10 and a Japonica‐type sensitive variety ‘Hitomebore’. These QTLs represent the first step in identifying stress tolerance genes from O. glaberrima that could subsequently be used to enhance P deficiency tolerance in O. sativa.     

Identification of new QTL for salt tolerance from rice variety Pokkali

Salt stress is an ever-present threat to rice production worldwide. Rice salinity tolerance is complex, both genetically and physiologically. The success and effectiveness in selecting salt-tolerant rice variety require the identification of QTL for the tolerance and closely linked molecular markers. In the present study, a RIL population consisting of 148 lines, derived from a cross between IR29 (salt-sensitive) and Pokkali (salt-tolerant), was used to identify new QTL for salt tolerance and investigate the relationships between salt stress caused injury and the changes in different physiological and morphological traits at the seedling stage. 14,470 high-quality SNP markers generated by the Rice 56K SNP array were converted to 1,467 bin markers for linkage mapping. A high-density genetic linkage map covering 1,680.9 cM was constructed, with the physical to genetic distance ratio being 222 Kb/cM. In total, 23 QTL for different salt tolerance indices were identified, including the previously reported Saltol which is currently used in breeding programmes. Three QTL for salt injury score (SIS) were located on chromosomes 1, 4 and 12, all being closely related to the long-distant Na⁺ transport from roots to shoots. These QTL showed additive effects, thus can be effectively used in breeding programme to pyramid various tolerance genes.     

Fine‐mapping a fibre strength QTL QFS‐D11‐1 on cotton chromosome 21 using introgressed lines

An initial F₂ mapping population of 223 plants of the cross between TM‐1 (Gossypium hirsutum L.) × H102 (Gossypium barbadense L.) was used to map QTLs controlling fibre strength in cotton. A genetic linkage map with 408 SSR markers was constructed with a total length of 3872.6 cM. Multiple‐QTL model of the software MapQTL version 5.0 was used to map QTLs related to fibre strength of the F_2 : 3 population. QTL QFS‐D11‐1 conferring fibre strength was mapped between NAU2950 and NAU4855 on chromosome 21 (Chr. 21) which explained 23.4% of phenotypic variation. Introgressed lines (ILs), that is, IL‐D11‐1, IL‐D11‐2 and IL‐D11‐3 were obtained through marker‐assisted backcrossing in TM‐1 background. An F₂ population of 758 plants derived from cross IL‐D11‐2 × TM‐1 was used for fine‐mapping QTL QFS‐D11‐1. QFS‐D11‐1 was mapped between markers NAU2110 and NAU2950, adjacent to its initial interval NAU2950–NAU4855 with phenotypic variation explaining 35.8%. QFS‐D11‐1 was further mapped to 0.6 cM from the flanking marker NAU2950. The results will give a basis for marker‐assisted selection of QFS‐D11‐1 in cotton breeding and to lay the foundation for cloning QFS‐D11‐1.     

小麦燕大1817×北农6号重组自交系群体在正常和盐胁迫水培条件下苗期性状的QTL定位

小麦苗期性状能够指示品种的耐盐性。本研究以小麦骨干亲本燕大1817与品系北农6号衍生的230个重组自交系为材料,利用2013年3个不同时间的水培试验数据和已经构建的SSR和SNP高密度遗传连锁图谱分别对正常和盐胁迫条件下根数和最长根长等7个苗期性状进行QTL定位。利用完备复合区间作图法(ICIM)共检测到69个加性效应QTL(LOD≥2.5),分布于除1A染色体外的所有20条染色体上,单个QTL解释的表型变异率为2.70%~19.00%。有46个QTL的增效效应来自于燕大1817,有23个QTL的增效效应来自于北农6号。有12个QTL能够在3个或3个以上的环境中被检测到,在燕大1817中定位到稳定的多分蘖主效QTL QTn.cau-7BS.1和盐胁迫条件下特异表达的根数QTL QRn.cau-2A,解析了小麦骨干亲本燕大1817的繁茂性和抗逆性遗传基础,为解析小麦品种耐盐遗传机制和耐盐性的分子标记辅助选择提供了重要信息。