Identification of quantitative trait loci for leaf traits in rice

A recombinant inbred lines (RILs) population of 90 lines were developed from a subspecies cross between an indica type cultivar, ?Cheongcheong?, and a japonica rice cultivar, ?Nagdong? was evaluated for leaf traits in 2009. A genetic linkage map consisting of 154 simple sequence repeat (SSR) markers was constructed, covering 1973.6 cM of 12 chromosomes with an average map distance of 13.9 cM between markers. By composite interval mapping method a total of 19 QTLs were identified for the leaf traits on 5 chromosomes (Chr.1, Chr.3, Chr.6, Chr.8 and Chr.11). The percentage of phenotypic variance explained by each QTL varied from 8.1% to 29.4%. Five pleiotropic effects loci were identified on chromosomes 1,6.

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QTL mapping for seedling morphology under drought stress in wheat cross synthetic (W7984)/Opata

Plant Genetic Resources ◽

10.1017/s1479262118000023 ◽

2018 ◽

Vol 16 (4) ◽

pp. 359-366

Author(s):

Maria Khalid ◽

Alvina Gul ◽

Rabia Amir ◽

Mohsin Ali ◽

Fakiha Afzal ◽

...

Keyword(s):

Drought Stress ◽

Recombinant Inbred Lines ◽

Genotyping By Sequencing ◽

Interval Mapping ◽

Wheat Breeding ◽

Seedling Stage ◽

Poor Correlation ◽

Root Weight ◽

Phenotypic Variance ◽

Seedling Morphology

AbstractDrought stress ‘particularly at seedling stage’ causes morpho-physiological differences in wheat which are crucial for its survival and adaptability. In the present study, 209 recombinant inbred lines (RILs) from synthetic wheat (W7984)× ‘Opata’ (also known as SynOpRIL) population were investigated under well-watered and water-limited conditions to identify quantitative trait loci (QTL) for morphological traits at seedling stage. Analysis of variance revealed significant differences (P < 0.01) among RILs, and water treatments for all traits with moderate to high broad sense heritability. Pearson's coefficient of correlation revealed positive correlation among all traits except dry root weight that showed poor correlation with fresh shoot weight (FSW) under water-limited conditions. A high-density linkage map was constructed with 2639 genotyping-by-sequencing markers and covering 5047 cM with an average marker density of 2 markers/cM. Composite interval mapping identified 16 QTL distributed over nine chromosomes, of which six were identified under well-watered and 10 in water-limited conditions. These QTL explained from 4 to 59% of the phenotypic variance. Six QTL were identified on chromosome 7B; three for shoot length under water-limited conditions (QSL.nust-7B) at 64, 104 and 221 cM, two for fresh root weight (QFRW.nust-7B) at 124 and 128 cM, and one for root length (QRL.nust-7B) at 122 cM positions. QFSW.nust-7B appeared to be the most significant QTL explaining 59% of the phenotypic variance and also associated with FSW at well-watered conditions. These QTL could serve as target regions for candidate gene discovery and marker-assisted selection in wheat breeding.

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Fine Mapping of a New Race-Specific Blast Resistance Gene, Pi-hk2, in Japonica Heikezijing from Taihu Region of China

Phytopathology ◽

10.1094/phyto-03-16-0151-r ◽

2017 ◽

Vol 107 (1) ◽

pp. 84-91 ◽

Cited By ~ 2

Author(s):

Wanwan He ◽

Nengyan Fang ◽

Ruisen Wang ◽

Yunyu Wu ◽

Guoying Zeng ◽

...

Keyword(s):

Resistance Gene ◽

Fine Mapping ◽

Broad Spectrum ◽

Blast Resistance ◽

Recombinant Inbred Lines ◽

Japonica Rice ◽

Phenotypic Variance ◽

Chromosome 11 ◽

Essential Information ◽

Broad Spectrum Resistance

Heikezijing, a japonica rice landrace from the Taihu region of China, exhibited broad-spectrum resistance to more than 300 isolates of the blast pathogen (Magnaporthe oryzae). In our previous research, we fine mapped a broad-spectrum resistance gene, Pi-hk1, in chromosome 11. In this research, 2010-9(G1), one of the predominant races of blast in the Taihu Lake region of China, was inoculated into 162 recombinant inbred lines (RIL) and two parents, Heikezijing and Suyunuo, for mapping the resistance-blast quantitative trait loci (QTL). Three QTL (Lsqtl4-1, Lsqtl9-1, and Lsqtl11-1) associated with lesion scores were detected on chromosomes 4, 9, and 11 and two QTL (Lnqtl1-1 and Lnqtl9-1) associated with average lesion numbers were detected on chromosomes 1 and 9. The QTL Lsqtl9-1 conferring race-specific resistance to 2010-9(G1) at seedling stages showed logarithm of the odds scores of 9.10 and phenotypic variance of 46.19% and might be a major QTL, named Pi-hk2. The line RIL84 with Pi-hk2 derived from a cross between Heikezijing and Suyunuo was selected as Pi-hk2 gene donor for developing fine mapping populations. According to the resistance evaluation of recombinants of three generations (BC1F2, BC1F3, and BC1F4), Pi-hk2 was finally mapped to a 143-kb region between ILP-19 and RM24048, and 18 candidate genes were predicted, including genes that encode pleiotropic drug resistance protein 4 (n = 2), WRKY74 (n = 1), cytochrome b5-like heme/steroid-binding domain containing protein (n = 1), protein kinase (n = 1), and ankyrin repeat family protein (n = 1). These results provide essential information for cloning of Pi-hk2 and its potential utility in breeding resistant rice cultivars by marker-assisted selection.

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QTL Mapping and Validation for Kernel Area and Circumference in Common Wheat via High-Density SNP-Based Genotyping

Frontiers in Plant Science ◽

10.3389/fpls.2021.713890 ◽

2021 ◽

Vol 12 ◽

Author(s):

Tianheng Ren ◽

Tao Fan ◽

Shulin Chen ◽

Xia Ou ◽

Yongyan Chen ◽

...

Keyword(s):

Recombinant Inbred Lines ◽

Snp Array ◽

Interval Mapping ◽

Mapping Method ◽

Kernel Weight ◽

Kernel Size ◽

Specific Pcr ◽

Wheat Kernel ◽

Ril Population ◽

Stable Qtls

As an important component, 1,000 kernel weight (TKW) plays a significant role in the formation of yield traits of wheat. Kernel size is significantly positively correlated to TKW. Although numerous loci for kernel size in wheat have been reported, our knowledge on loci for kernel area (KA) and kernel circumference (KC) remains limited. In the present study, a recombinant inbred lines (RIL) population containing 371 lines genotyped using the Wheat55K SNP array was used to map quantitative trait loci (QTLs) controlling the KA and KC in multiple environments. A total of 54 and 44 QTLs were mapped by using the biparental population or multienvironment trial module of the inclusive composite interval mapping method, respectively. Twenty-two QTLs were considered major QTLs. BLAST analysis showed that major and stable QTLs QKc.sau-6A.1 (23.12–31.64 cM on 6A) for KC and QKa.sau-6A.2 (66.00–66.57 cM on 6A) for KA were likely novel QTLs, which explained 22.25 and 20.34% of the phenotypic variation on average in the 3 year experiments, respectively. Two Kompetitive allele-specific PCR (KASP) markers, KASP-AX-109894590 and KASP-AX-109380327, were developed and tightly linked to QKc.sau-6A.1 and QKa.sau-6A.2, respectively, and the genetic effects of the different genotypes in the RIL population were successfully confirmed. Furthermore, in the interval where QKa.sau-6A.2 was located on Chinese Spring and T. Turgidum ssp. dicoccoides reference genomes, only 11 genes were found. In addition, digenic epistatic QTLs also showed a significant influence on KC and KA. Altogether, the results revealed the genetic basis of KA and KC and will be useful for the marker-assisted selection of lines with different kernel sizes, laying the foundation for the fine mapping and cloning of the gene(s) underlying the stable QTLs detected in this study.

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Neighbor QTL: an interval mapping method for quantitative trait loci underlying plant neighborhood effects

10.1101/2020.05.20.089474 ◽

2020 ◽

Author(s):

Yasuhiro Sato ◽

Kazuya Takeda ◽

Atsushi J. Nagano

Keyword(s):

Qtl Mapping ◽

Neighborhood Effects ◽

Quantitative Trait ◽

Recombinant Inbred Lines ◽

Insect Herbivory ◽

R Package ◽

Interval Mapping ◽

Mapping Method ◽

Neighbor Effects ◽

Genotype Probabilities

AbstractPhenotypes of sessile organisms, such as plants, rely not only on their own genotype but also on the genotypes of neighboring individuals. Previously, we incorporated such neighbor effects into a single-marker regression using the Ising model of ferromagnetism. However, little is known about how to incorporate neighbor effects in quantitative trait locus (QTL) mapping. In this study, we propose a new method for interval QTL mapping of neighbor effects, named “Neighbor QTL”. The algorithm of neighbor QTL involves the following: (i) obtaining conditional self-genotype probabilities with recombination fraction between flanking markers, (ii) calculating neighbor genotypic identity using the self-genotype probabilities, and (iii) estimating additive and dominance deviation for neighbor effects. Our simulation using F2 and backcross lines showed that the power to detect neighbor effects increased as the effective range became smaller. The neighbor QTL was applied to insect herbivory on Col × Kas recombinant inbred lines of Arabidopsis thaliana. Consistent with previous evidence, the pilot experiment detected a self QTL effect on the herbivory at GLABRA1 locus. We also observed a weak QTL on chromosome 4 regarding neighbor effects on the herbivory. The neighbor QTL method is available as an R package (https://cran.r-project.org/package=rNeighborQTL), providing a novel tool to investigate neighbor effects in QTL studies.

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Genetic analysis of tolerance to maize streak virus in maize

Genome ◽

10.1139/g98-099 ◽

1999 ◽

Vol 42 (1) ◽

pp. 20-26 ◽

Cited By ~ 31

Author(s):

D T Kyetere ◽

R Ming ◽

M D McMullen ◽

R C Pratt ◽

J Brewbaker ◽

...

Keyword(s):

Zea Mays ◽

Field Experiments ◽

Zea Mays L ◽

Recombinant Inbred Lines ◽

Interval Mapping ◽

Chromosome 1 ◽

Rflp Markers ◽

Streak Virus ◽

Phenotypic Variance ◽

Progress Curve

Maize streak, incited by maize streak geminivirus (MSV), is a major disease limiting maize (Zea mays L.) production over widespread areas of Africa. To understand the genetic basis of tolerance to MSV, recombinant inbred lines (RILs) derived from the cross of the MSV tolerant inbred Tzi4 with the MSV susceptible inbred Hi34, were evaluated for MSV tolerance. Experiments were conducted using controlled leafhopper (Cicadulina spp.) infestation in one glasshouse experiment at Namulonge, Uganda, and two field experiments at Centro Internacional de Mejoramiento de Maiz y Trigo, Harare, Zimbabwe. Eighty-seven RILs were genotyped at 82 loci by restriction fragment length polymorphism (RFLP) analysis. The association between genotype at RFLP marker loci and MSV tolerance was determined using single-factor analysis of variance (SFAOV), multiple regression, and interval mapping procedures. There was a significant association of MSV tolerance with RFLP markers on the short arm of chromosome 1. By SFAOV, the portion of the phenotypic variance explained by genotype class (R2) for the association between npi262 and the area under disease progress curve (AUDPC) measure of MSV tolerance was as high as 76% in field experiments. Interval mapping analyses (Knapp and Bridges 1990; Nelson 1997) identified the chromosome region bracketed by bnl12.06a and npi262 as explaining the largest proportion of the variation in MSV tolerance. After classification of symptom responses from the final field ratings into resistant and susceptible classes, qualitative analysis of data fit a chi-square test to a 1:1 Mendelian ratio, further indicating presence of a single major gene. Multipoint linkage analysis placed this gene, designated msv1, at a genetic distance of 3 cM distal to npi262. Identification of the tightly linked molecular marker locus npi262 should greatly aid ongoing conversion of susceptible African varieties to maize streak resistance.Key words: Zea mays L., Cicadulina spp., host resistance, gene mapping, molecular markers.

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QTL mapping for plant height and yield components in common wheat under water-limited and full irrigation environments

Crop and Pasture Science ◽

10.1071/cp14236 ◽

2015 ◽

Vol 66 (7) ◽

pp. 660 ◽

Cited By ~ 16

Author(s):

Xingmao Li ◽

Xianchun Xia ◽

Yonggui Xiao ◽

Zhonghu He ◽

Desen Wang ◽

...

Keyword(s):

Plant Height ◽

Yield Components ◽

Recombinant Inbred Lines ◽

Interval Mapping ◽

Wheat Breeding ◽

Kernel Weight ◽

Full Irrigation ◽

Inclusive Composite Interval Mapping ◽

Cropping Seasons ◽

Simple Sequence

Plant height (PH) and yield components are important traits for yield improvement in wheat breeding. In this study, 207 F2:4 recombinant inbred lines (RILs) derived from the cross Jingdong 8/Aikang 58 were investigated under limited and full irrigation environments at Beijing and Gaoyi, Hebei province, during the 2011–12 and 2012–13 cropping seasons. The RILs were genotyped with 149 polymorphic simple sequence repeat (SSR) markers, and quantitative trait loci (QTLs) for PH and yield components were analysed by inclusive composite interval mapping. All traits in the experiment showed significant genetic variation and interaction with environments. The range of broad-sense heritabilities of PH, 1000-kernel weight (TKW), number of kernels per spike (KNS), number of spikes per m2 (NS), and grain yield (GY) were 0.97–0.97, 0.87–0.89, 0.59–0.61, 0.58–0.68, and 0.23–0.48. The numbers of QTLs detected for PH, TKW, KNS, NS, and GY were 3, 10, 8, 7 and 9, respectively, across all eight environments. PH QTLs on chromosomes 4D and 6A, explaining 61.3–80.2% of the phenotypic variation, were stably expressed in all environments. QPH.caas-4D is assumed to be the Rht-D1b locus, whereas QPH.caas-6A is likely to be a newly discovered gene. The allele from Aikang 58 at QPH.caas-4D reduced PH by 11.5–18.2% and TKW by 2.6–3.8%; however, KNS increased (1.2–3.7%) as did NS (2.8–4.1%). The QPH.caas-6A allele from Aikang 58 reduced PH by 8.0–11.5% and TKW by 6.9–8.5%, whereas KNS increased by 1.2–3.6% and NS by 0.9–4.5%. Genotypes carrying both QPH.caas-4D and QPH.caas-6A alleles from Aikang 58 showed reduced PH by 28.6–30.6%, simultaneously reducing TKW (13.8–15.2%) and increasing KNS (3.4–4.9%) and NS (6.5–10%). QTKW.caas-4B and QTKW.caas-5B.1 were stably detected and significantly associated with either KNS or NS. Major KNS QTLs QKNS.caas-4B and QKNS.caas-5B.1 and the GY QTL QGY.caas-3B.2 were detected only in water-limited environments. The major TKW QTKW.caas-6D had no significant effect on either KNS or NS and it could have potential for improving yield.

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Exploring genetic architecture of grain yield and quality traits in a 16-way indica by japonica rice MAGIC global population

Scientific Reports ◽

10.1038/s41598-019-55357-7 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 4

Author(s):

Hein Zaw ◽

Chitra Raghavan ◽

Arnel Pocsedio ◽

B. P. Mallikarjuna Swamy ◽

Mona Liza Jubay ◽

...

Keyword(s):

Complex Traits ◽

Genome Wide Association Study ◽

Recombinant Inbred Lines ◽

Interval Mapping ◽

Japonica Rice ◽

Quality Traits ◽

Significant Qtls ◽

Grain Yield And Quality ◽

Global Population ◽

Trait Associations

AbstractIdentification of Quantitative Trait Loci (QTL) has been a challenge for complex traits due to the use of populations with narrow genetic base. Most of QTL mapping studies were carried out from crosses made within the subspecies, either indica × indica or japonica × japonica. In this study we report advantages of using Multi-parent Advanced Generation Inter-Crosses global population, derived from a combination of eight indica and eight japonica elite parents, in QTL discovery for yield and grain quality traits. Genome-wide association study and interval mapping identified 38 and 34 QTLs whereas Bayesian networking detected 60 QTLs with 22 marker-marker associations, 32 trait-trait associations and 65 marker-trait associations. Notably, nine known QTLs/genes qPH1/OsGA20ox2, qDF3/OsMADS50, PL, QDg1, qGW-5b, grb7-2, qGL3/GS3, Amy6/Wx gene and OsNAS3 were consistently identified by all approaches for nine traits whereas qDF3/OsMADS50 was co-located for both yield and days-to-flowering traits on chromosome 3. Moreover, we identified a number of candidate QTLs in either one or two analyses but further validations will be needed. The results indicate that this new population has enabled identifications of significant QTLs and interactions for 16 traits through multiple approaches. Pyramided recombinant inbred lines provide a valuable source for integration into future breeding programs.

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Mapping Net Form Net Blotch and Septoria Speckled Leaf Blotch Resistance Loci in Barley

Phytopathology ◽

10.1094/phyto-100-1-0080 ◽

2010 ◽

Vol 100 (1) ◽

pp. 80-84 ◽

Cited By ~ 23

Author(s):

S. St. Pierre ◽

C. Gustus ◽

B. Steffenson ◽

R. Dill-Macky ◽

K. P. Smith

Keyword(s):

Phenotypic Variation ◽

Recombinant Inbred Lines ◽

Interval Mapping ◽

Net Blotch ◽

Upper Midwest ◽

Breeding Lines ◽

Leaf Blotch ◽

Net Form Net Blotch ◽

Development And Utilization ◽

Simple Sequence

Septoria speckled leaf blotch (SSLB), caused by Septoria passerinii Sacc., and net form net blotch (NB), caused by Pyrenophora teres f. teres Drechsler, are fungal diseases that decrease the yields of barley in the Upper Midwest. An effective way to manage these diseases is to plant resistant cultivars. To characterize the genetics of resistance to both pathogens, two advanced barley breeding lines, one resistant to NB (M120) and another resistant to SSLB (Sep2-72), were crossed, creating a population of 115 recombinant inbred lines. The two parents and the population were evaluated in three greenhouse seedling assays for each pathogen and for simple-sequence repeat and diversity arrays technology markers. Composite interval mapping revealed two major quantitative trait loci (QTL) associated with NB on chromosome 6H, located in bins 2 and 6. The QTL located in bin 6 explained 19 to 48% of the phenotypic variation and the QTL located in bin 2 explained 25 to 44% of the phenotypic variation. A new locus for resistance to SSLB, Rsp4, was identified on chromosome 6H, located in bins 3 to 4. Mapping these genes in elite breeding germplasm will accelerate the development and utilization of marker-assisted selection to enhance resistance to these diseases.

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Neighbor QTL: an interval mapping method for quantitative trait loci underlying plant neighborhood effects

G3 Genes|Genome|Genetics ◽

10.1093/g3journal/jkab017 ◽

2021 ◽

Author(s):

Yasuhiro Sato ◽

Kazuya Takeda ◽

Atsushi J Nagano

Keyword(s):

Qtl Mapping ◽

Neighborhood Effects ◽

Quantitative Trait ◽

Recombinant Inbred Lines ◽

Insect Herbivory ◽

R Package ◽

Interval Mapping ◽

Mapping Method ◽

Neighbor Effects ◽

Genotype Probabilities

Abstract Phenotypes of sessile organisms, such as plants, rely not only on their own genotypes but also on those of neighboring individuals. Previously, we incorporated such neighbor effects into a single-marker regression using the Ising model of ferromagnetism. However, little is known regarding how neighbor effects should be incorporated in quantitative trait locus (QTL) mapping. In this study, we propose a new method for interval QTL mapping of neighbor effects, designated” neighbor QTL,” the algorithm of which includes: (i) obtaining conditional self-genotype probabilities with recombination fraction between flanking markers; (ii) calculating conditional neighbor genotypic identity using the self-genotype probabilities; and (iii) estimating additive and dominance deviations for neighbor effects. Our simulation using F2 and backcross lines showed that the power to detect neighbor effects increased as the effective range decreased. The neighbor QTL was applied to insect herbivory on Col × Kas recombinant inbred lines of Arabidopsis thaliana. Consistent with previous results, the pilot experiment detected a self-QTL effect on the herbivory at the GLABRA1 locus. Regarding neighbor QTL effects on herbivory, we observed a weak QTL on the top of chromosome 4, at which a weak self-bolting QTL was also identified. The neighbor QTL method is available as an R package ( https://cran.r-project.org/package=rNeighborQTL ), providing a novel tool to investigate neighbor effects in QTL studies.

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Genetic analysis of partial resistance to basal stem rot (Sclerotinia sclerotiorum) in sunflower

Genetika ◽

10.2298/gensr1303737a ◽

2013 ◽

Vol 45 (3) ◽

pp. 737-748 ◽

Cited By ~ 9

Author(s):

Masoumeh Amouzadeh ◽

Reza Darvishzadeh ◽

Parham Haddadi ◽

Mandoulakani Abdollahi ◽

Danesh Rezaee

Keyword(s):

Sclerotinia Sclerotiorum ◽

Partial Resistance ◽

Recombinant Inbred Lines ◽

Interval Mapping ◽

Stem Rot ◽

Phenotypic Variance ◽

Basal Stem Rot ◽

Paternal Line ◽

Randomized Design ◽

Parental Lines

Basal stem rot, caused by Sclerotinia sclerotiorum (Lib.) de Bary, is one of the major diseases of sunflower (Helianthus annuus L.) in the world. Quantitative trait loci (QTLs) implicated in partial resistance to basal stem rot disease were identified using 99 recombinant inbred lines (RILs) from the cross between sunflower parental lines PAC2 and RHA266. The study was undertaken in a completely randomized design with three replications under controlled conditions. The RILs and their parental lines were inoculated with a moderately aggressive isolate of S. sclerotiorum (SSKH41). Resistance to disease was evaluated by measuring the percentage of necrosis area three days after inoculation. QTLs were mapped using an updated high-density SSR and SNP linkage map. ANOVA showed significant differences among sunflower lines for resistance to basal stem rot (P?0.05). The frequency distribution of lines for susceptibility to disease showed a continuous pattern. Composite interval mapping analysis revealed 5 QTLs for percentage of necrotic area, localized on linkage groups 1, 3, 8, 10 and 17. The sign of additive effect was positive in 5 QTLs, suggesting that the additive allele for partial resistance to basal stem rot came from the paternal line (RHA266). The phenotypic variance explained by QTLs (R2) ranged from 0.5 to 3.16%. Identified genes (HUCL02246_1, GST and POD), and SSR markers (ORS338, and SSL3) encompassing the QTLs for partial resistance to basal stem rot could be good candidates for marker assisted selection.

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