Identification and introgression of QTLs implicated in resistance to sorghum downy mildew (Peronosclerospora sorghi (Weston and Uppal) C. G. Shaw) in maize through marker-assisted selection

Sorghum downy mildew caused by Peronosclerospora sorghi is a major disease of maize and resistance is under the control of polygenes which necessitated identification of quantitative-trait loci (QTLs) for initiating marker-assisted introgression of resistant QTLs in elite susceptible inbred lines. In the present study, QTLs for sorghum downy mildew (SDM) resistance in maize were identified based on cosegregation with linked simple sequence repeats in 185 F₂ progeny from a cross between susceptible (CM500-19) and resistant (MAI105) parents. F₃ families were screened in the National Sorghum Downy Mildew Screening Nursery during 2010 and 2011. High heritability was observed for the disease reaction. The final map generated using 87 SSR markers had 10 linkage groups, spanning a length of 1210.3 cM. Although, we used only 87 SSR markers for mapping, the per cent of genome within 20 cM to the nearest marker was 88.5. Three putative QTLs for SDM resistance were located on chromosomes 3 (bin 3.01), 6 (bin 6.01) and 2 (bin 2.02) using composite interval mapping. The locus on chromosome 3 had a major effect and explained up to 12.6% of the phenotypic variation. The other two QTLs on chromosomes 6 and 2 had minor effects with phenotypic variation of 7.1 and 2%. The three QTLs appeared to have additive effects on resistance. The QTLs on chromosomes 3 and 6 were successfully used in the marker-assisted selection programme for introgression of resistance to SDM in eight susceptible maize lines.     

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

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

QTL analysis and mapping of pi21, a recessive gene for field resistance to rice blast in Japanese upland rice

Field resistance is defined as the resistance that allows effective control of a parasite under natural field conditions and is durable when exposed to new races of that parasite. To identify the genes for field resistance to rice blast, quantitative trait loci (QTLs) conferring field resistance to rice blast in Japanese upland rice were detected and mapped using RFLP and SSR markers. QTL analysis was carried out in F₄ progeny lines from the cross between Nipponbare (moderately susceptible, lowland) and Owarihatamochi (resistant, upland). Two QTLs were detected on chromosome 4 and one QTL was detected on each of chromosomes 9 and 12. The phenotypic variation explained by each QTL ranged from 7.9 to 45.7% and the four QTLs explained 66.3% of the total phenotypic variation. Backcrossed progeny lines were developed to transfer the QTL with largest effect using the susceptible cultivar Aichiasahi as a recurrent parent. Among 82 F₃ lines derived from the backcross, resistance segregated in the expected ratio of resistant 1 : heterozygous 2 : susceptible 1. The average score for blast resistance measured in the field was 4.2 ± 0.67, 7.5 ± 0.51and 8.2 ± 0.66, for resistant, heterozygous and susceptible groups, respectively. The resistance gene, designated pi21, was mapped on chromosome 4 as a single recessive gene between RFLP marker loci G271 and G317 at a distance of 5.0 cM and 8.5 cM, respectively. The relationship to previously reported major genes and QTLs conferring resistance to blasts, and the significance of marker-assisted selection to improve field resistance, are discussed. Received: 8 June 2000 / Accepted: 24 November 2000     

Locating QTLs controlling overwintering seedling rate in perennial glutinous rice 89-1 (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

A new cold tolerant germplasm resource named glutinous rice 89-1 (Gr89-1, Oryza sativa L.) can overwinter using axillary buds, with these buds being ratooned the following year. The overwintering seedling rate (OSR) is an important factor for evaluating cold tolerance. Many quantitative trait loci (QTLs) controlling cold tolerance at different growth stages in rice have been identified, with some of these QTLs being successfully cloned. However, no QTLs conferring to the OSR trait have been located in the perennial O. sativa L. To identify QTLs associated with OSR and to evaluate cold tolerance. 286 F₁₂ recombinant inbred lines (RILs) derived from a cross between the cold tolerant variety Gr89-1 and cold sensitive variety Shuhui527 (SH527) were used. A total of 198 polymorphic simple sequence repeat (SSR) markers that were distributed uniformly on 12 chromosomes were used to construct the linkage map. The gene ontology (GO) annotation of the major QTL was performed through the rice genome annotation project system. Three main-effect QTLs (qOSR2, qOSR3, and qOSR8) were detected and mapped on chromosomes 2, 3, and 8, respectively. These QTLs were located in the interval of RM14208 (35,160,202 base pairs (bp))–RM208 (35,520,147 bp), RM218 (8,375,236 bp)–RM232 (9,755,778 bp), and RM5891 (24,626,930 bp)–RM23608 (25,355,519 bp), and explained 19.6%, 9.3%, and 11.8% of the phenotypic variations, respectively. The qOSR2 QTL displayed the largest effect, with a logarithm of odds score (LOD) of 5.5. A total of 47 candidate genes on the qOSR2 locus were associated with 219 GO terms. Among these candidate genes, 11 were related to cell membrane, 7 were associated with cold stress, and 3 were involved in response to stress and biotic stimulus. OsPIP1;3 was the only one candidate gene related to stress, biotic stimulus, cold stress, and encoding a cell membrane protein. After QTL mapping, a total of three main-effect QTLs—qOSR2, qOSR3, and qOSR8—were detected on chromosomes 2, 3, and 8, respectively. Among these, qOSR2 explained the highest phenotypic variance. All the QTLs elite traits come from the cold resistance parent Gr89-1. OsPIP1;3 might be a candidate gene of qOSR2.     

Identification and validation of QTLs conferring resistance to sorghum downy mildew (Peronosclerospora sorghi) and Rajasthan downy mildew (P. heteropogoni) in maize

We have mapped the quantitative trait loci (QTLs) conferring resistance to sorghum downy mildew (Peronosclerospora sorghi; SDM) and Rajasthan downy mildew (P. heteropogoni; RDM), two species of DM prevalent throughout India. QTL mapping was carried out on a backcross population of 151 individuals derived from a cross between CM139 (susceptible parent) and NAI116 (highly resistant to both SDM and RDM). Heritability estimates were 0.74 for SDM and 0.67 for RDM. Composite interval mapping combined with a linkage map constructed with 80 simple sequence repeat (SSR) markers resulted in the identification of three QTLs (one each on chromosomes 2, 3 and 6) for SDM resistance and two QTLs (one each on chromosomes 3 and 6) for RDM resistance, all of which were contributed by NAI116. The significance of the major QTL on chromosome 6 (bin 6.05) that confers resistance to diverse DMs in tropical Asia, including SDM and RDM in India, was also verified. The results confirmed that some common QTLs contribute to both SDM and RDM resistance, while additional loci might specifically govern resistance to SDM. The QTL information generated in this study provide information that will aid in undertaking an integrated breeding strategy for the transfer of resistance to SDM and RDM in maize lines using marker-assisted selection.     

QTL mapping for downy mildew resistance in cucumber via bulked segregant analysis using next-generation sequencing and conventional methods

Key message

QTL mapping using NGS-assisted BSA was successfully applied to an F ₂ population for downy mildew resistance in cucumber. QTLs detected by NGS-assisted BSA were confirmed by conventional QTL analysis.

Abstract

Downy mildew (DM), caused by Pseudoperonospora cubensis, is one of the most destructive foliar diseases in cucumber. QTL mapping is a fundamental approach for understanding the genetic inheritance of DM resistance in cucumber. Recently, many studies have reported that a combination of bulked segregant analysis (BSA) and next-generation sequencing (NGS) can be a rapid and cost-effective way of mapping QTLs. In this study, we applied NGS-assisted BSA to QTL mapping of DM resistance in cucumber and confirmed the results by conventional QTL analysis. By sequencing two DNA pools each consisting of ten individuals showing high resistance and susceptibility to DM from a F₂ population, we identified single nucleotide polymorphisms (SNPs) between the two pools. We employed a statistical method for QTL mapping based on these SNPs. Five QTLs, dm2.2, dm4.1, dm5.1, dm5.2, and dm6.1, were detected and dm2.2 showed the largest effect on DM resistance. Conventional QTL analysis using the F₂ confirmed dm2.2 (R ² = 10.8–24 %) and dm5.2 (R ² = 14–27.2 %) as major QTLs and dm4.1 (R ² = 8 %) as two minor QTLs, but could not detect dm5.1 and dm6.1. A new QTL on chromosome 2, dm2.1 (R ² = 28.2 %) was detected by the conventional QTL method using an F₃ population. This study demonstrated the effectiveness of NGS-assisted BSA for mapping QTLs conferring DM resistance in cucumber and revealed the unique genetic inheritance of DM resistance in this population through two distinct major QTLs on chromosome 2 that mainly harbor DM resistance.

     

Genetic analysis of genetic basis of a physiological disorder “straighthead” in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

Straighthead is a physiological disorder in rice that causes yield losses and is a serious threat to rice production worldwide. Identification of QTL conferring resistance will help develop resistant cultivars for straighthead control. We conducted linkage mapping to identify QTL involved with straighthead. The study was based on a F₂ population developed from a cross between ‘Zhe733(resistant)/R312(susceptible)’. Using phenotypic data of F₂ plants and their F_2:3 families, two major QTL, qSTH-2 and qSTH-8, were identified using bulked segregant analysis, explaining 11.1 and 28.1 % of the phenotypic variation on chromosome 2 and 8, respectively. The qSTH-2 for straighthead resistance was identified by linkage mapping. qSTH-2 was situated near a QTL “AsS” responsible for arsenic accumulation. Straighthead is frequently observed on land where As has accumulated. The result suggests a kind of internal connection between qSTH-2 and AsS. Additionally, the QTL qSTH-8 was located close to HD5 related with heading date. The close location may be associated with the observation of early heading among straighthead resistant varieties. These findings should be useful for further genetic study of straighthead.     

Identification and fine mapping of <Emphasis Type="Italic">qWBPH11</Emphasis> conferring resistance to whitebacked planthopper (<Emphasis Type="Italic">Sogatella furcifera</Emphasis> Horvath) in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

The whitebacked planthopper (WBPH), Sogatella furcifera Horvath, is one of the most destructive pests in rice (Oryza sativa L.) production. Host-plant resistance has been considered as an efficient and eco-friendly strategy to reduce yield losses caused by WBPH. In this study, we found that an indica rice cultivar IR54751-2-44-15-24-2 (IR54751) displayed high resistance to WBPH at both seedling and tillering stages. The resistance of IR54751 was mainly contributed by antixenosis and tolerance rather than antibiosis. An F₂ population derived from a cross between IR54751 and a susceptible japonica cultivar 02428 was constructed to detect the quantitative trait loci (QTLs) conferring the resistance to WBPH. In total, four QTLs including qWBPH3.1, qWBPH3.2, qWBPH11, and qWBPH12 were identified and distributed on three different chromosomes. The four QTLs had LOD scores of 3.8, 8.2, 5.8, and 3.9, accounting for 8.2, 21.5, 13.9, and 10.4% of the phenotypic variation, respectively. Except for qWBPH3.1, the resistance alleles of the other three QTLs were all from IR54751. Further, a secondary population harboring only single qWBPH11 locus was developed from the F₂ population by marker-assisted selection. Finally, qWBPH11 was delimited in a 450-kb region between markers DJ53973 and SNP56. The identification of WBPH resistance QTLs and the fine mapping of qWBPH11 will be helpful for cloning resistance genes and breeding resistant rice cultivars.     

Evaluation of QTLs for Shoot Fly (<Emphasis Type="Italic">Atherigona soccata</Emphasis>) Resistance Component Traits of Seedling Leaf Blade Glossiness and Trichome Density on Sorghum (<Emphasis Type="Italic">Sorghum bicolor</Emphasis>) Chromosome SBI-10L

Shoot fly is a major insect pest of sorghum damaging early crop growth, establishment and productivity. Host plant resistance is an efficient approach to minimize yield losses due to shoot fly infestation. Seedling leaf blade glossiness and trichome density are morphological traits associated with shoot fly resistance. Our objective was to identify and evaluate QTLs for glossiness and trichome density using- i) 1894 F₂s, ii) a sub-set of 369 F₂-recombinants, and iii) their derived 369 F_2:3 progenies, from a cross involving introgression lines RSG04008-6 (susceptible)?×?J2614-11 (resistant). The QTLs were mapped to a 37–72 centimorgan (cM) or 5–15 Mb interval on the long arm of sorghum chromosome 10 (SBI-10L) with flanking markers Xgap001 and Xtxp141. One QTL each for glossiness (QGls10) and trichome density (QTd10) were mapped in marker interval Xgap001-Xnhsbm1044 and Xisep0630-Xtxp141, confirming their loose linkage, for which phenotypic variation accounted for ranged from 2.29 to 11.37 % and LOD values ranged from 2.03 to 24.13, respectively. Average physical map positions for glossiness and trichome density QTLs on SBI-10 from earlier studies were 4 and 2 Mb, which in the present study were reduced to 2 Mb and 800 kb, respectively. Candidate genes Glossy15 (Sb10g025053) and ethylene zinc finger protein (Sb10g027550) falling in support intervals for glossiness and trichome density QTLs, respectively, are discussed. Also we identified a sub-set of recombinant population that will facilitate further fine mapping of the leaf blade glossiness and trichome density QTLs on SBI-10.     

Genetic mapping of maize streak virus resistance from the Mascarene source. II. Resistance in line CIRAD390 and stability across germplasm

The streak disease has a major effect on maize in sub-Saharan Africa. Various genetic factors for resistance to the virus have been identified and mapped in several populations; these factors derive from different sources of resistance. We have focused on the Réunion island source and have recently identified several factors in the D211 line. A second very resistant line, CIRAD390, was crossed to the same susceptible parent, B73. The linkage map comprised 124 RFLP markers, of which 79 were common with the D211×B73 map. A row-column design was used to evaluate the resistance to maize streak virus (MSV) of 191 F_2:3 families under artificial infestation at two locations: Harare (Zimbabwe) and in Réunion island. Weekly ratings of resistance were taken and disease incidence and severity calculated. QTL analyses were conducted for each scoring date and for the integration over time of the disease scores, of incidence, and of severity. Heritability estimates (71–98%) were as high as for the D211×B73 population. Eight QTLs were detected on chromosomes 1, 2, 3, 5 (two QTLs), 6, 8, and 10. The chr1-QTL explained the highest proportion of phenotypic variation, about 45%. The QTLs on chromosomes 1, 2, and 10 were located in the same chromosomal bin as QTLs for MSV resistance in the D211×B73 population. In a simultaneous fit, QTLs explained together 43–67% of the phenotypic variation. The QTLs on chromosomes 3, 5, and 6 appeared to be specific for one or the other component of the resistance. For the chr3-QTL, resistance was contributed by the susceptible parent. There were significant QTL × environment interactions for some of the variables studied, but QTLs were stable in the two environments. They also appeared to be stable over time. Global gene action ranged from partial dominance to overdominance, except for disease severity. Some additional putative QTLs were also detected. The major QTL on chromosome 1 seemed to be common to the other sources of resistance, namely Tzi4, a tolerant line from IITA, and CML202 from CIMMYT. However, the distribution of the other QTLs within the genome revealed differences in Réunion germplasm and across these other resistance sources. This diversity is of great importance when considering the durability of the resistance. Received: 15 June 1998 / Accepted: 30 January 1999     

Identification of quantitative trait loci controlling resistance to gray leaf spot disease in maize

Breeding maize for gray leaf spot (GLS) resistance has been hindered by the quantitative nature of the inheritance of GLS resistance and by the limitations of selection under less than optimumal disease pressure. In order to identify the quantitative trait loci (QTLs) controlling GLS resistance, a cross was made between B73 (susceptible) and Va14 (resistant) to generate a large F₂ population. Six GLS disease assessments were made throughout the disease season for over 1000 F₂ plants in 1989, and for 600 F₂-derived F₃ lines replicated in two blocks in 1990. RFLP analysis for78 marker loci representing all ten maize chromosomes was conducted in 239 F₂ individuals including those with the extreme GLS disease phenotypes. The GLS disease scores of the three field evaluations, each averaged over six ratings, were separately used for the interval mapping in order to determine the consistency of the QTL effects. The heavy GLS disease pressure, meticulous disease ratings, and large population size of this study afforded us the sensitivity for detecting QTL effects. QTLs located on three chromosomes (1, 4, and 8) had large effects on GLS resistance, each explaining 35.0–56.0%, 8.8–14.3%, and 7.7–11.0% of the variance, respectively. These three QTL effects were remarkably consistent across three disease evaluations over 2 years and two generations. Smaller QTL effects were also found on chromosomes 2 and 5, but the chromosome-5 effect might be a false positive because it was not repeatable even in the same location. The chromosome-1 QTLs had the largest effect or highest R² reported for any quantitative trait to-date. Except for the chromosome-4 gene, which was from the susceptible parent B73, the resistance alleles at all QTL were derived from Va14. The resistance QTLs on chromosomes 1 and 2 appear to have additive effects, but those on chromosomes 4 and 8 are dominant and recessive, respectively. Significant interaction between the QTLs on chromosomes 1 and 4 was detected in all three evaluations. Cumulatively, the four QTLs identified in this study explained 44, 60, and 68% of the variance in F₂, and in F₃ replications 1 and 2, respectively.     

QTL mapping for bacterial wilt resistance in peanut (<Emphasis Type="Italic">Arachis hypogaea</Emphasis> L.)

Bacterial wilt (BW) caused by Ralstonia solanacearum is a serious, global, disease of peanut (Arachis hypogaea L.), but it is especially destructive in China. Identification of DNA markers linked to the resistance to this disease will help peanut breeders efficiently develop resistant cultivars through molecular breeding. A F₂ population, from a cross between disease-resistant and disease-susceptible cultivars, was used to detect quantitative trait loci (QTL) associated with the resistance to this disease in the cultivated peanut. Genome-wide SNPs were identified from restriction-site-associated DNA sequencing tags using next-generation DNA sequencing technology. SNPs linked to disease resistance were determined in two bulks of 30 resistant and 30 susceptible plants along with two parental plants using bulk segregant analysis. Polymorphic SSR and SNP markers were utilized for construction of a linkage map and for performing the QTL analysis, and a moderately dense linkage map was constructed in the F₂ population. Two QTL (qBW-1 and qBW-2) detected for resistance to BW disease were located in the linkage groups LG1 and LG10 and account for 21 and 12 % of the bacterial wilt phenotypic variance. To confirm these QTL, the F₈ RIL population with 223 plants was utilized for genotyping and phenotyping plants by year and location as compared to the F₂ population. The QTL qBW-1 was consistent in the location of LG1 in the F₈ population though the QTL qBW-2 could not be clarified due to fewer markers used and mapped in LG10. The QTL qBW-1, including four linked SNP markers and one SSR marker within 14.4-cM interval in the F₈, was closely related to a disease resistance gene homolog and was considered as a candidate gene for resistance to BW. QTL identified in this study would be useful to conduct marker-assisted selection and may permit cloning of resistance genes. Our study shows that bulk segregant analysis of genome-wide SNPs is a useful approach to expedite the identification of genetic markers linked to disease resistance traits in the allotetraploidy species peanut.     

Identification of novel recessive gene <Emphasis Type="Italic">xa44</Emphasis>(<Emphasis Type="Italic">t</Emphasis>) conferring resistance to bacterial blight races in rice by QTL linkage analysis using an SNP chip

Key message

Using QTL analysis and fine mapping, the novel recessive gene xa44(t) conferring resistance to BB was identified and the expression level of the gene was confirmed through qRT-PCR analysis.

Abstract

Bacterial blight (BB) disease caused by Xanthomonas oryzae pv. oryzae (Xoo) is a major factor causing rice yield loss in most rice-cultivating countries, especially in Asia. The deployment of cultivars with resistance to BB is the most effective method to control the disease. However, the evolution of new Xoo or pathotypes altered by single-gene-dependent mutations often results in breakdown of resistance. Thus, efforts to identify novel R-genes with sustainable BB resistance are urgently needed. In this study, we identified three quantitative trait loci (QTLs) on chromosomes 1, 4, and 11, from an F₂ population of 493 individuals derived from a cross between IR73571-3B-11-3-K3 and Ilpum using a 7K SNP chip. Of these QTLs, one major QTL, qBB_11, on chromosome 11 explained 61.58% of the total phenotypic variance in the population, with an LOD value of 113.59, based on SNPs 11964077 and 11985463. The single major R-gene, with recessive gene action, was designated xa44(t) and was narrowed down to a 120-kb segment flanked within 28.00 Mbp to 28.12 Mbp. Of nine ORFs present in the target region, two ORFs revealed significantly different expression levels of the candidate genes. These candidate genes (Os11g0690066 and Os11g0690466) are described as “serine/threonine protein kinase domain containing protein” and “hypothetical protein,” respectively. The results will be useful to further understand BB resistance mechanisms and provide new sources of resistance, together with DNA markers for MAS breeding to improve BB resistance in rice.

     

Identification and genetic mapping for <Emphasis Type="Italic">rht-DM</Emphasis>, a dominant dwarfing gene in mutant semi-dwarf maize using QTL-seq approach

Semi-dwarfism is an agronomically important trait in breeding for stable high yields and for resistance to damage by wind and rain (lodging resistance). Many QTLs and genes causing dwarf phenotype have been found in maize. However, because of the yield loss associated with these QTLs and genes, they have been difficult to use in breeding for dwarf stature in maize. Therefore, it is important to find the new dwarfing genes or materials without undesirable characters. The objectives of this study were: (1) to figure out the inheritance of semi-dwarfism in mutants; (2) mapping dwarfing gene or QTL. Maize inbred lines ‘18599’ and ‘DM173’, which is the dwarf mutant derived from the maize inbred line ‘173’ through ⁶⁰Co-γ ray irradiation. F₂ and BC₁F₁ population were used for genetic analysis. Whole genome resequencing-based technology (QTL-seq) were performed to map dwarfing gene and figured out the SNP markers in predicted region using dwarf bulk and tall bulk from F₂ population. Based on the polymorphic SNP markers from QTL-seq, we were fine-mapping the dwarfing gene using F₂ population. In F₂ population, 398 were dwarf plants and 135 were tall plants. Results of χ² tests indicated that the ratio of dwarf plants to tall plants was fitted to 3:1 ratio. Furthermore, the χ² tests of BC₁F₁ population showed that the ratio was fitted to 1:1 ratio. Based on QTL-seq, the dwarfing gene was located at the region from 111.07 to 124.56 Mb of chromosome 9, and we named it rht-DM. Using traditional QTL mapping with SNP markers, the rht-DM was narrowed down to 400 kb region between SNP-21 and SNP-24. The two SNPs were located at 0.43 and 0.11 cM. Segregation analysis of F₂ and BC₁F₁ indicated that the dwarfing gene was likely a dominant gene. This dwarfing gene was located in the region between 115.02 and 115.42 Mb on chromosome 9.     

Fine mapping a major QTL <Emphasis Type="Italic">qFCC7</Emphasis><Subscript><Emphasis Type="Italic">L</Emphasis></Subscript> for chlorophyll content in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) cv. PA64s

Chlorophyll (Chl) content is an important agronomic trait directly affecting the photosynthetic rate. Using a high-density genetic map of 132 recombinant inbred lines (RILs) derived from the cross between 93-11 and PA64s, we detected the quantitative trait loci (QTLs) for Chl content of the top three leaves under two nitrogen (N) conditions at two developmental stages. A total of 32 main-effect QTLs located on chromosomes 1, 4, 5, 6, 7, 8, and 12 were identified, and these QTLs individually accounted for 6.0–20.8?% of the total phenotypic variation. A major QTL qFCC7 _L affecting the Chl content under low N condition was identified, and its positive allele came from PA64s. This QTL might be associated with the ability to tolerate low-N stress in rice. The chromosomal segment substitution line (CSSL) with the corresponding segment from PA64s had a higher SPAD value and photosynthetic rate than 93-11 and showed a lower specific leaf area (SLA). We performed a fine-mapping using a BC₄F₂ population via marker-assisted backcross and finally mapped this QTL to a 124.5 kb interval on the long arm of chromosome 7. Candidate gene analysis showed that there were sequence variations and expression differences in the predicted candidate gene between the two parents. These results suggest that the QTL qFCC7 _L may be useful for breeding the rice varieties with higher photosynthetic rate and grain yield.     

Genomic regions controlling components of resistance for pea rust caused by Uromyces fabae (Pers.) de-Bary

Pea rust caused by Uromyces fabae (Pers.) de-Bary is an important disease in subtropical regions of the world. The use of partial resistance or slow rusting is an important strategy for developing varieties having durable rust resistance. A mapping population of 136 F_6:7 Recombinant Inbred Lines (RILs) derived from the cross HUVP 1?×?FC 1 was evaluated for disease severity percent (DS%) and three components of slow rusting, number of aecial pustules per leaf (AP), leaf area covered by sporulating pustules (LASP) and number of aecial cups per leaf (TNAC) during crop seasons 2006–07 and 2007–08 in polyhouse and field experiments. The components were governed by four quantitative trait loci, two major (Qruf on LGVII, Qruf2 on LGI), and two minor QTLs (Qruf1 on LG VII and Qruf3 on LGVI). This confirmed the positions of one each of the major (Qruf) and minor (Qruf1) QTLs and also detected two new QTLs Qruf2 and Qruf3. The new major QTL Qruf2 (phenotypic variance 21.3 to 29.6 %) appeared to be the most important component-specific QTL and played key role in deciding disease resistance. The minor QTL Qruf3 appeared environment-specific and contributed by the susceptible parent.     

Mapping of QTL for downy mildew resistance in maize

Quantitative trait loci (QTLs) of maize involved in mediating resistance to Peronosclerospora sorghi, the causative agent of sorghum downy mildew (SDM), were detected in a population of recombinant inbred lines (RILs) derived from the Zea mays L. cross between resistant (G62) and susceptible (G58) inbred lines. Field tests of 94 RILs were conducted over two growing seasons using artificial inoculation. Heritability of the disease reaction was high (around 70%). The mapping population of the RILs was also scored for restriction fragment length polymorphic (RFLP) markers. One hundred and six polymorphic RFLP markers were assigned to ten chromosomes covering 1648 cM. Three QTLs were detected that significantly affected resistance to SDM combined across seasons. Two of these mapped quite close together on chromosome 1, while the third one was on chromosome 9. The percentage of phenotypic variance explained by each QTL ranged from 12.4% to 23.8%. Collectively, the three QTLs identified in this study explained 53.6% of the phenotypic variation in susceptibility to the infection. The three resistant QTLs appeared to have additive effects. Increased susceptibility was contributed by the alleles of the susceptible parent. The detection of more than one QTL supports the hypothesis that several qualitative and quantitative genes control resistance to P. sorghi.     

Rapid identification of QTLs underlying resistance to <Emphasis Type="Italic">Cucumber mosaic virus</Emphasis> in pepper (<Emphasis Type="Italic">Capsicum frutescens</Emphasis>)

Key message

Next-generation sequencing enabled a fast discovery of QTLs controlling CMV resistant in pepper. The gene CA02g19570 as a possible candidate gene of qCmr2.1 was identified for resistance to CMV in pepper.

Abstract

Cucumber mosaic virus (CMV) is one of the most important viruses infecting pepper, but the genetic basis of CMV resistance in pepper is elusive. In this study, we identified a candidate gene for CMV resistance QTL, qCmr2.1 through SLAF-seq. Segregation analysis in F₂, BC₁ and F_2:3 populations derived from a cross between two inbred lines ‘PBC688’ (CMV-resistant) and ‘G29’ (CMV-susceptible) suggested quantitative inheritance of resistance to CMV in pepper. Genome-wide comparison of SNP profiles between the CMV-resistant and CMV-susceptible bulks constructed from an F₂ population identified two QTLs, designated as qCmr2.1 on chromosome 2 and qCmr11.1 on chromosome 11 for resistance to CMV in PBC688, which were confirmed by InDel marker-based classical QTL mapping in the F₂ population. As a major QTL, joint SLAF-seq and traditional QTL analysis delimited qCmr2.1 to a 330 kb genomic region. Two pepper genes, CA02g19570 and CA02g19600, were identified in this region, which are homologous with the genes LOC104113703, LOC104248995, LOC102603934 and LOC101248357, which were predicted to encode N-like protein associated with TMV-resistant in Solanum crops. Quantitative RT-PCR revealed higher expression levels of CA02g19570 in CMV resistance genotypes. The CA02g19600 did not exhibit obvious regularity in expression patterns. Higher relative expression levels of CA02g19570 in PBC688 and F₁ were compared with those in G29 during days after inoculation. These results provide support for CA02g19570 as a possible candidate gene of qCmr2.1 for resistance to CMV in pepper.

     

A major QTL (<Emphasis Type="Italic">qFT12.1</Emphasis>) allele from wild soybean delays flowering time

Soybean is highly sensitive to photoperiod. To improve the adaptability and productivity of soybean, it is essential to understand the molecular mechanisms regulating flowering time. To identify new flowering time QTLs, we evaluated a BC₃F₅ population consisting of 120 chromosome segment substitution lines (CSSLs) over 2 years under field conditions. CSSLs were derived from a cross between the cultivated soybean cultivar Jackson and the wild soybean accession JWS156-1, followed by continuous backcrossing using Jackson as the recurrent parent. Four QTLs (qFT07.1, qFT12.1, qFT12.2, and qFT19.1) were detected on three chromosomes. Of these, qFT12.1 showed the highest effect, accounting for 36.37–38.27% of the total phenotypic variation over 2 years. This QTL was further confirmed in the F₇ recombinant inbred line population (n?=?94) derived from the same cross (Jackson × JWS156-1). Analysis of the qFT12.1 BC₃F₅ residual heterozygous line RHL509 validated the allele effect of qFT12.1 and revealed that the recessive allele of qFT12.1 resulted in delayed flowering. Evaluating the qFT12.1 near-isogenic lines (NILs) under different growth conditions showed that NILs with the wild soybean genotype always showed later flowering than those with the cultivated soybean genotype. qFT12.1 was delimited to a 2703-kb interval between the markers BARCSOYSSR_12_0220 and BARCSOYSSR_12_0368 on chromosome 12. qFT12.1 may be a new flowering time gene locus in soybean.     

Mapping novel aphid resistance QTL from wild soybean, <Emphasis Type="Italic">Glycine soja</Emphasis> 85-32

Key message

Two novel QTLs conferring aphid resistance were mapped and validated on soybean chromosomes 8 and 16, respectively. Closely linked markers were developed to assist breeding for aphid resistance.

Abstract

Soybean aphid, Aphis glycines Matsumura, is a highly destructive pest for soybean production. E08934, a soybean advanced breeding line derived from the wild soybean Glycine soja 85-32, has shown strong resistance to aphids. To dissect the genetic basis of aphid resistance in E08934, a mapping population (070020) consisting of 140 F₃-derived lines was developed by crossing E08934 with an aphid-susceptible line E00003. This mapping population was evaluated for aphid resistance in a greenhouse trial in 2010 and three field trials in 2009, 2010, and 2011, respectively. The broad-sense heritability across the field trials was 0.84. In the mapping population 070020, two major quantitative trait loci (QTL) were detected as significantly associated with aphid resistance, and designated as Rag6 and Rag3c, respectively. Rag6 was mapped to a 10.5 centiMorgan (cM) interval between markers MSUSNP08-2 and Satt209 on chromosome 8, explaining 19.5–46.4% of the phenotypic variance in different trials. Rag3c was located at a 7.5 cM interval between markers MSUSNP16-10 and Sat_370 on chromosome 16, explaining 12.5–22.9% of the phenotypic variance in different trials. Rag3c had less resistance effect than Rag6 across all the trials. Furthermore, Rag6 and Rag3c were confirmed in two validation populations with different genetic backgrounds. No significant interaction was detected between Rag6 and Rag3c in either the mapping population or the validation populations. Both Rag6 and Rag3c were indicated as conferring antibiosis resistance to aphids by a no-choice test. The new aphid-resistance gene(s) derived from the wild germplasm G. soja 85-32 are valuable in improving soybeans for aphid resistance.