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.     

QTL mapping for resistance to Ceratocystis wilt in <Emphasis Type="Italic">Eucalyptus</Emphasis>

Ceratocystis wilt caused by the fungus Ceratocystis fimbriata, is currently one of the major diseases in commercial plantations of Eucalyptus trees in Brazil. Deployment of resistant genotypes has been the main strategy for effective disease management. The present study aimed at identifying genomic regions underlying the genetic control of resistance to Ceratocystis wilt in Eucalyptus by quantitative trait loci (QTL) mapping in an outbred hybrid progeny derived from a cross between (Eucalyptus dunnii × Eucalyptus grandis) × (Eucalyptus urophylla × Eucalyptus globulus). A segregating population of 127 individuals was phenotyped for resistance to Ceratocystis wilt using controlled inoculation under a completely randomized design with five clonal replicates per individual plant. The phenotypic resistance response followed a continuous variation, enabling us to analyze the trait in a quantitative manner. The population was genotyped with 114 microsatellite markers and 110 were mapped with an average interval of 12.3 cM. Using a sib-pair interval-mapping approach five QTLs were identified for disease resistance, located on linkage groups 1, 3, 5, 8, and 10, and their estimated individual heritability ranged from 0.096 to 0.342. The QTL on linkage group 3 overlaps with other fungal disease-resistance QTLs mapped earlier and is consistent with the annotation of several disease-resistance genes on this chromosome in the E. grandis genome. This is the first study to identify and attempt to quantify the effects of QTLs associated with resistance to Ceratocystis wilt in Eucalyptus.     

QTLs for heading date and plant height under multiple environments in rice

Both heading date and plant height are important traits related to grain yield in rice. In this study, a recombinant inbred lines (RILs) population was used to map quantitative trait loci (QTLs) for both traits under 3 long-day (LD) environments and 1 short-day (SD) environment. A total of eight QTLs for heading date and three QTLs for plant height were detected by composite interval mapping under LD conditions. Additional one QTL for heading date and three QTLs for plant height were identified by Two-QTL model under LD conditions. Among them, major QTLs qHd7.1, qHd7.2 and qHd8 for heading date, and qPh1 and qPh7.1 for plant height were commonly detected. qHd7.1 and qHd7.2 were mapped to small regions of less than 1 cM. Genome position comparison of previously cloned genes with QTLs detected in this study revealed that qHd5 and qPh3.1 were two novel QTLs. The alleles of these QTLs increasing trait values were dispersed in both parents, which well explained the transgressive segregation observed in this population. In addition, the interaction between qHd7.1 and qHd8 was detected under all LD conditions. Multiple-QTL model analysis revealed that all QTLs and their interactions explained over 80% of heading date variation and 50% of plant height variation. Two heading date QTLs were detected under SD condition. Of them, qHd10 were commonly identified under LD condition. The difference in QTL detection between LD and SD conditions indicated most heading date QTLs are sensitive to photoperiod. These findings will benefit breeding design for heading date and plant height in rice.     

Chromosomes A07 and A05 associated with stable and major QTLs for pod weight and size in cultivated peanut (<Emphasis Type="Italic">Arachis hypogaea</Emphasis> L.)

Key message

Co-localized intervals and candidate genes were identified for major and stable QTLs controlling pod weight and size on chromosomes A07 and A05 in an RIL population across four environments.

Abstract

Cultivated peanut (Arachis hypogaea L.) is an important legume crops grown in > 100 countries. Hundred-pod weight (HPW) is an important yield trait in peanut, but its underlying genetic mechanism was not well studied. In this study, a mapping population (Xuhua 13 × Zhonghua 6) with 187 recombinant inbred lines (RILs) was developed to map quantitative trait loci (QTLs) for HPW together with pod length (PL) and pod width (PW) by both unconditional and conditional QTL analyses. A genetic map covering 1756.48 cM was constructed with 817 markers. Additive effects, epistatic interactions, and genotype-by-environment interactions were analyzed using the phenotyping data generated across four environments. Twelve additive QTLs were identified on chromosomes A05, A07, and A08 by unconditional analysis, and five of them (qPLA07, qPLA05.1, qPWA07, qHPWA07.1, and qHPWA05.2) showed major and stable expressions in all environments. Conditional QTL mapping found that PL had stronger influences on HPW than PW. Notably, qHPWA07.1, qPLA07, and qPWA07 that explained 17.93–43.63% of the phenotypic variations of the three traits were co-localized in a 5 cM interval (1.48 Mb in physical map) on chromosome A07 with 147 candidate genes related to catalytic activity and metabolic process. In addition, qHPWA05.2 and qPLA05.1 were co-localized with minor QTL qPWA05.2 to a 1.3 cM genetic interval (280 kb in physical map) on chromosome A05 with 12 candidate genes. This study provides a comprehensive characterization of the genetic components controlling pod weight and size as well as candidate QTLs and genes for improving pod yield in future peanut breeding.

     

Genome-wide association studies of net form of net blotch resistance at seedling and adult plant stages in spring barley collection

Net form of net blotch (NFNB) of barley (Hordeum vulgare L.), caused by Pyrenophora teres f. teres (Ptt) Drechsler (anamorph: Drechslera teres [Sacc.] Shoem.), is considered one of the major constraints of successful barley production in major barley growing regions of the world. Resistance to NFNB was evaluated in a barley collection of 336 genotypes (AM-2014), at seedling stage using isolates LGDPtt.19 and TD10 in the USA, and adult stage in seven hotspot environments in Morocco. The AM-2014 panel was genotyped with 9K SNP markers and genome-wide association studies (GWAS) were carried out using mixed linear model (MLM: Q?+?K) accounting for population structure (Q) and kinship (K) as covariates. Significant (P?<?0.001) marker trait associations were corrected for false discovery rate (FDR) at the q?<?0.05. Four genotypes showed an average infection response (IRs ≤ 2) to both isolates, LGDPttt.19 and TD10, at the seedling stage, and 30 genotypes showed resistance in all environments in the field while three genotypes exhibited the highest resistance at both stages. The GWAS of NFNB identified 31 distinct QTLs on all seven barley chromosomes, of which 8 with resistance at seedling stage, 21 were associated with resistance at the adult stage, and two QTLs, QRptt.2H-132.15 and QPtt.6H-54-55, conferred resistance at both stages. Of 31 resistance QTLs reported in this study, 10 QTLs coincided with previously mapped QTL while 21 are novel, thereby validating the GWAS approach used in this study. The resistance sources identified in AM-2014 and QTL mapped in this study are valuable resources for marker-assisted breeding for NFNB resistance in the future.     

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.     

Integrated analysis of leaf morphological and color traits in different populations of Chinese cabbage (<Emphasis Type="Italic">Brassica rapa</Emphasis> ssp. <Emphasis Type="Italic">pekinensis</Emphasis>)

Key message

QTLs and candidate gene markers associated with leaf morphological and color traits were identified in two immortalized populations of Brassica rapa, which will provide genetic information for marker-assisted breeding.

Abstract

Brassica rapa is an important leafy vegetable consumed worldwide and morphology is a key character for its breeding. To enhance genetic control, quantitative trait loci (QTLs) for leaf color and plant architecture were identified using two immortalized populations with replications of 2 and 4 years. Overall, 158 and 80 QTLs associated with 23 and 14 traits were detected in the DH and RIL populations, respectively. Among them, 23 common robust-QTLs belonging to 12 traits were detected in common loci over the replications. Through comparative analysis, five crucifer genetic blocks corresponding to morphology trait (R, J&U, F and E) and color trait (F, E) were identified in three major linkage groups (A2, A3 and A7). These might be key conserved genomic regions involved with the respective traits. Through synteny analysis with Arabidopsis, 64 candidate genes involved in chlorophyll biosynthesis, cell proliferation and elongation were co-localized within QTL intervals. Among them, SCO3, ABI3, FLU, HCF153, HEMB1, CAB3 were mapped within QTLs for leaf color; and CYCD3;1, CYCB2;4, AN3, ULT1 and ANT were co-localized in QTL regions for leaf size. These robust QTLs and their candidate genes provide useful information for further research into leaf architecture with crop breeding.

     

Development of SSR markers and identification of major quantitative trait loci controlling shelling percentage in cultivated peanut (<Emphasis Type="Italic">Arachis hypogaea</Emphasis> L.)

Key message

A total of 204,439 SSR markers were developed in diploid genomes, and 25 QTLs for shelling percentage were identified in a RIL population across 4 years including five consistent QTLs.

Abstract

Cultivated peanut (Arachis hypogaea L.) is an important grain legume providing edible oil and protein for human nutrition. Genome sequences of its diploid ancestors, Arachis duranensis and A. ipaensis, were reported, but their SSRs have not been well exploited and utilized hitherto. Shelling percentage is an important economic trait and its improvement has been one of the major objectives in peanut breeding programs. In this study, the genome sequences of A. duranensis and A. ipaensis were used to develop SSR markers, and a mapping population (Yuanza 9102 × Xuzhou 68-4) with 195 recombinant inbred lines was used to map QTLs controlling shelling percentage. The numbers of newly developed SSR markers were 84,383 and 120,056 in the A. duranensis and A. ipaensis genomes, respectively. Genotyping of the mapping population was conducted with both newly developed and previously reported markers. QTL analysis using the phenotyping data generated in Wuhan across four consecutive years and genotyping data of 830 mapped loci identified 25 QTLs with 4.46–17.01% of phenotypic variance explained in the four environments. Meta-analysis revealed five consistent QTLs that could be detected in at least two environments. Notably, the consistent QTL cqSPA09 was detected in all four environments and explained 10.47–17.01% of the phenotypic variance. The segregation in the progeny of a residual heterozygous line confirmed that the cpSPA09 locus had additive effect in increasing shelling percentage. These consistent and major QTL regions provide opportunity not only for further gene discovery, but also for the development of functional markers for breeding.

     

Single nucleotide polymorphism tightly linked to a major QTL on chromosome 7A for both kernel length and kernel weight in wheat

Thousand-kernel weight (TKW) is one of the major components of grain yield in wheat (Triticum aestivum). Identifying major quantitative trait loci (QTLs) for TKW and developing effective markers are prerequisite for success in marker-assisted selection (MAS) to improve wheat yield through breeding. This study mapped a major QTL, designated as TaTKW-7AL, for increasing TKW on the long arm of chromosome 7A of ‘Clark’ to a 1.3-cM interval between single nucleotide polymorphism (SNP) markers IWB13913 and IWA5913. This QTL explained 19.7 % of the phenotypic variation for TKW. A QTL for increasing kernel length (KL), one of the major components of TKW, was mapped in the same interval as TaTKW-7AL, suggesting that increased TKW by the QTL in ‘Clark’ is most likely due to the increased KL. Association analysis on a diversity panel of 200 US winter wheat accessions also identified a haplotype of three SNP markers (IWB13913, IWB6693 and IWA5913) that were tightly associated with the both KL and TKW. The analysis of allele frequencies of the haplotype in the diversity panel suggested that the favorable allele of TaTKW-7AL has not been strongly selected for in practice and has potential to be used to improve grain yield in US hard winter wheat breeding. Two user-friendly flanking KASPar markers, IWB13913 and IWA5913, were developed for MAS of TaTKW-7AL.     

High-resolution mapping of genes involved in plant stage-specific partial resistance of barley to leaf rust

Partial resistance quantitative trait loci (QTLs) Rphq11 and rphq16 against Puccinia hordei isolate 1.2.1 were previously mapped in seedlings of the mapping populations Steptoe/Morex and Oregon Wolfe Barleys, respectively. In this study, QTL mapping was performed at adult plant stage for the two mapping populations challenged with the same rust isolate. The results suggest that Rphq11 and rphq16 are effective only at seedling stage, and not at adult plant stage. The cloning of several genes responsible for partial resistance of barley to P. hordei will allow elucidation of the molecular basis of this type of plant defence. A map-based cloning approach requires to fine-map the QTL in a narrow genetic window. In this study, Rphq11 and rphq16 were fine-mapped using an approach aiming at speeding up the development of plant material and simplifying its evaluation. The plant materials for fine-mapping were identified from early plant materials developed to produce QTL-NILs. The material was first selected to carry the targeted QTL in heterozygous condition and susceptibility alleles at other resistance QTLs in homozygous condition. This strategy took four to five generations to obtain fixed QTL recombinants (i.e., homozygous resistant at the Rphq11 or rphq16 QTL alleles, homozygous susceptible at the non-targeted QTL alleles). In less than 2 years, Rphq11 was fine-mapped into a 0.2-cM genetic interval and a 1.4-cM genetic interval for rphq16. The strongest candidate gene for Rphq11 is a phospholipid hydroperoxide glutathione peroxidase. Thus far, no candidate gene was identified for rphq16.     

Analysis of genomic region spanning <Emphasis Type="Italic">Saltol</Emphasis> using SSR markers in rice genotypes showing differential seedlings stage salt tolerance

Micro satellite markers located in the Saltol QTL of 5 Mb region (10.4–15.6 Mb) in chromosome 1 confering seedling stage salt tolerance were used to evaluate 94 rice genotypes. Out of 21, eight SSR markers at Saltol region of Chromosome were found polymorphic. Based on the phenotypic screening, 94 genotypes were grouped as highly tolerant (20), tolerant (18) moderately tolerant (32), sensitive (19) and highly sensitive (5). The marker RM3412 appears to be diagnostic of salinity tolerance and associate to salinity tolerance at seedling stage as it is closely linked to SKC gene. Based on Saltol markers study, CSR 31, CSR 38, CSR 41, CSR 32, Wild 11, CSR 18, Azgo, Pant Dhan 4, Trichi 1, CSR 10 and IR64426-4B-11-1 could not be identified as tolerant genotypes though had expressed tolerant to highly tolerant phenotype to salinity stress at seedling stage, suggesting that QTLs other than Saltol might be controlling their salinity tolerance. It is suggested that these genotypes could serve as potentially novel germplasm and could be exploited for the development of new breeding lines with high level of salinity tolerance by pyramiding of the Saltol and other QTLs.     

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.

     

QTL mapping and epistatic interaction analysis of field resistance to sudden death syndrome (<Emphasis Type="Italic">Fusarium virguliforme</Emphasis>) in soybean

Key message

Two interactive quantitative trait loci (QTLs) controlled the field resistance to sudden death syndrome (SDS) in soybean. The interaction between them was confirmed.

Abstract

Sudden death syndrome (SDS), caused by Fusarium virguliforme, is a major disease of soybean [Glycine max (L.) Merr.] in the United States. Breeding for soybean resistance to SDS is the most cost-effective method to manage the disease. The objective of this study was to identify and characterize quantitative trait loci (QTLs) underlying field resistance to SDS in a recombinant inbred line population from the cross GD2422?×?LD01-5907. This population was genotyped with 1786 polymorphic single nucleotide polymorphisms (SNPs) using SoySNP6 K iSelect BeadChip and evaluated for SDS resistance in a naturally infested field. Four SDS resistance QTLs were mapped on Chromosomes 4, 8, 12 and 18. The resistant parent, LD01-5907, contributed the resistance alleles for the QTLs on Chromosomes 8 and 18 (qSDS-8 and qSDS-18), while the other parent, GD2422, provided the resistance alleles for the QTLs on Chromosomes 4 and 12 (qSDS-4 and qSDS-12). The minor QTL on Chromosome 12 (qSDS-12) is novel. The QTL on Chromosomes 8 and 18 (qSDS-8 and qSDS-18) overlapped with two soybean cyst nematode resistance-related loci, Rhg4 and Rhg1, respectively. A significant interaction between qSDS-8 and qSDS-18 was detected by disease incidence. Individual effects together with the interaction effect explained around 70% of the phenotypic variance. The epistatic interaction of qSDS-8 and qSDS-18 was confirmed by the field performance across multiple years. Furthermore, the resistance alleles at qSDS-8 and qSDS-18 were demonstrated to be recessive. The SNP markers linked to these QTLs will be useful for marker-assisted breeding to enhance the SDS resistance.

     

Genetic analysis of shoot fresh weight in a cross of wild (<Emphasis Type="Italic">G. soja</Emphasis>) and cultivated (<Emphasis Type="Italic">G. max</Emphasis>) soybean

Shoot fresh weight (SFW) is one of the parameters, used to estimate the total plant biomass yield in soybean. In the present study, a total of 188 F_5:8 recombinant inbred lines (RIL) derived from an interspecific cross of PI 483463 (Glycine soja) and Hutcheson (Glycine max) were investigated for SFW variation in the field for three consecutive years. The parental lines and RILs were phenotyped in the field at the R6 stage by measuring total biomass in kg/plot to identify the QTLs for SFW. Three QTLs qSFW6_1, qSFW15_1, and qSFW19_1 influencing SFW were identified on chromosome 6, 15, and 19, respectively. The QTL qSFW19_1 flanked between the markers BARC-044913-08839 and BARC-029975-06765 was the stable QTL expressed in all the three environments. The phenotypic variation explained by the QTLs across all environments ranged from 6.56 to 21.32 %. The additive effects indicated contribution of alleles from both the parents and additive × environment interaction effects affected the expression of SFW QTL. Screening of the RIL population with additional SSRs from the qSFW19_1 region delimited the QTL between the markers SSR19-1329 and BARC-29975-06765. QTL mapping using bin map detected two QTLs, qSFW19_1A and qSFW19_1B. The QTL qSFW19_1A mapped close to the Dt1 gene locus, which affects stem termination, plant height, and floral initiation in soybean. Potential candidate genes for SFW were pinpointed, and sequence variations within their sequences were detected using high-quality whole-genome resequencing data. The findings in this study could be useful for understanding genetic basis of SFW in soybean.     

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

Key message

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

Abstract

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

     

QTL mapping of panicle blast resistance in japonica landrace heikezijing and its application in rice breeding

The rice blast caused by Magnaporthe oryzae is one of the most devastating diseases worldwide, and the panicle blast could result in more loss of yield in rice production. However, the quantitative trait loci (QTLs) and genes related to panicle-blast resistance have not been well studied due to the time-consuming screening methodology involved and variation in symptoms. The QTLs for panicle blast resistance have been mapped in a population of 162 RILs (recombination inbreeding lines), derived from a cross between a highly blast-resistant rice landrace, Heikezijing, and a susceptible variety, Suyunuo. Two QTLs for panicle-blast resistance, qPbh-11–1 and qPbh-7-1, were identified, which were distributed on chromosomes 11 and 7. The QTL qPbh-11–1 was stably detected in three independent experiments, at Nanjing in 2013 and 2014 and at Hainan in 2014, located between the region of RM27187 and RM27381 on the distal end of chromosome 11 far from the reported resistant loci Pb1 and qPbm11 for panicle blast. The QTL qPbh-7-1 was detected only at Nanjing in 2013 and located between the region of M18 and RM3555 on chromosome 7. With marker-assisted selection (MAS) three introgression lines with the major panicle blast-resistance QTL qPbh-11–1 were developed from a recurrent parent Nanjing 44 (NJ44) and the panicle resistance of introgression lines was improved 46.36–55.47 % more than NJ44. Based on the results provided, Heikezijing appears to be a valuable source for panicle blast resistance.     

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.     

Quantitative trait locus (QTL) analysis of fruit-quality traits for mandarin breeding in Japan

The improvement of fruit quality is an important objective in citrus breeding. Using an F₁ segregating population from a cross between citrus cultivars ‘Harehime’ (‘E647’—‘Kiyomi’ [Citrus unshiu Marcow. ‘Miyagawa Wase’ × Citrus sinensis (L.) Osbeck ‘Trovita’] × ‘Osceola’—a cultivar of clementine [Citrus clementina hort. ex Tanaka] × ‘Orland’ [Citrus paradisi Macfad. ‘Duncan’ × Citrus tangerina hort. ex Tanaka] × ‘Miyagawa Wase’) and ‘Yoshida’ ponkan (Citrus reticulata Blanco ‘Yoshida’), a SNP-based genetic linkage map was constructed and quantitative trait locus (QTL) mapping of four fruit-quality traits (fruit weight, sugar content, peel puffing, and water rot) was performed. The constructed genetic linkage map of ‘Harehime’ consisted of 442 single nucleotide polymorphisms (SNPs) on 9 linkage groups (LGs) and covered 635.8 cM of the genome, while that of ‘Yoshida’ ponkan consisted of 332 SNPs on 9 LGs and covered 892.9 cM of its genome. We identified four QTLs associated with fruit weight, one QTL associated with sugar content, three QTLs associated with peel puffing, and one QTL associated with water rot. For these QTL regions, we estimated the haplotypes of the crossed parents and verified the founding cultivars that these QTLs were originated from and their inheritance in descendant cultivars using pedigree information. QTLs identified in this study provide useful information for marker-assisted breeding of citrus in Japan.     

Identification of candidate genes of QTLs for seed weight in <Emphasis Type="Italic">Brassica napus</Emphasis> through comparative mapping among <Emphasis Type="Italic">Arabidopsis</Emphasis> and <Emphasis Type="Italic">Brassica</Emphasis>species

Background

Map-based cloning of quantitative trait loci (QTLs) in polyploidy crop species remains a challenge due to the complexity of their genome structures. QTLs for seed weight in B. napus have been identified, but information on candidate genes for identified QTLs of this important trait is still rare.

Results

In this study, a whole genome genetic linkage map for B. napus was constructed using simple sequence repeat (SSR) markers that covered a genetic distance of 2,126.4 cM with an average distance of 5.36 cM between markers. A procedure was developed to establish colinearity of SSR loci on B. napus with its two progenitor diploid species B. rapa and B. oleracea through extensive bioinformatics analysis. With the aid of B. rapa and B. oleracea genome sequences, the 421 homologous colinear loci deduced from the SSR loci of B. napus were shown to correspond to 398 homologous loci in Arabidopsis thaliana. Through comparative mapping of Arabidopsis and the three Brassica species, 227 homologous genes for seed size/weight were mapped on the B. napus genetic map, establishing the genetic bases for the important agronomic trait in this amphidiploid species. Furthermore, 12 candidate genes underlying 8 QTLs for seed weight were identified, and a gene-specific marker for BnAP2 was developed through molecular cloning using the seed weight/size gene distribution map in B. napus.

Conclusions

Our study showed that it is feasible to identify candidate genes of QTLs using a SSR-based B. napus genetic map through comparative mapping among Arabidopsis and B. napus and its two progenitor species B. rapa and B. oleracea. Identification of candidate genes for seed weight in amphidiploid B. napus will accelerate the process of isolating the mapped QTLs for this important trait, and this approach may be useful for QTL identification of other traits of agronomic significance.