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

2015 ◽  
Vol 66 (7) ◽  
pp. 660 ◽  
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.

scholarly journals Genome wide identification of QTL associated with yield and yield components in two popular wheat cultivars TAM 111 and TAM 112

2020 ◽  
Author(s):  
Yan Yang ◽  
Smit Dhakal ◽  
Chenggen Chu ◽  
Shichen Wang ◽  
Qingwu Xue ◽  
...  
Keyword(s):  
Grain Yield ◽  
Great Plains ◽  
Yield Components ◽  
Recombinant Inbred Lines ◽  
Wheat Breeding ◽  
Kernel Weight ◽  
Genetic Maps ◽  
Wheat Cultivars ◽  
Thousand Kernel Weight ◽  
Yield And Yield Components

AbstractTwo drought-tolerant wheat cultivars, ‘TAM 111’ and ‘TAM 112’, have been widely grown in the Southern Great Plains of the U.S. and used as parents in many wheat breeding programs worldwide. This study aimed to reveal genetic control of yield and yield components in the two cultivars under both dryland and irrigated conditions. A mapping population containing 124 F5:7 recombinant inbred lines (RILs) was developed from the cross of TAM 112/TAM 111. A set of 5,948 SNPs from the wheat 90K iSelect array and double digest restriction-site associated DNA sequencing was used to construct high-density genetic maps. Data for yield and yield components were obtained from 11 environments. QTL analyses were performed based on 11 individual environments, across all environments, within and across mega-environments. Thirty-six unique consistent QTL regions were distributed on 13 chromosomes including 1A, 1B, 1D, 2A, 2D, 3D, 4B, 4D, 6A, 6B, 6D, 7B, and 7D. Ten unique QTL with pleiotropic effects were identified on four chromosomes and eight were in common with the consistent QTL. These QTL increased dry biomass grain yield by 16.3 g m−2, plot yield by 28.1 g m−2, kernels spike−1 by 0.7, spikes m−2 by 14.8, thousand kernel weight by 0.9 g with favorable alleles from either parent. TAM 112 alleles mainly increased spikes m−2 and thousand kernel weight while TMA 111 alleles increased kernels spike−1, harvest index and grain yield. The saturated genetic map and markers linked to significant QTL from this study will be very useful in developing high throughput genotyping markers for tracking the desirable haplotypes of these important yield-related traits in popular parental cultivars.

scholarly journals Genome wide identification of QTL associated with yield and yield components in two popular wheat cultivars TAM 111 and TAM 112

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0237293
Author(s):  
Yan Yang ◽  
Smit Dhakal ◽  
Chenggen Chu ◽  
Shichen Wang ◽  
Qingwu Xue ◽  
...  
Keyword(s):  
Grain Yield ◽  
Great Plains ◽  
Yield Components ◽  
Recombinant Inbred Lines ◽  
Wheat Breeding ◽  
Kernel Weight ◽  
Genetic Maps ◽  
Wheat Cultivars ◽  
Thousand Kernel Weight ◽  
Yield And Yield Components

Two drought-tolerant wheat cultivars, ‘TAM 111’ and ‘TAM 112’, have been widely grown in the Southern Great Plains of the U.S. and used as parents in many wheat breeding programs worldwide. This study aimed to reveal genetic control of yield and yield components in the two cultivars under both dryland and irrigated conditions. A mapping population containing 124 F5:7 recombinant inbred lines (RILs) was developed from the cross of TAM 112/TAM 111. A set of 5,948 SNPs from the wheat 90K iSelect array and double digest restriction-site associated DNA sequencing was used to construct high-density genetic maps. Data for yield and yield components were obtained from 11 environments. QTL analyses were performed based on 11 individual environments, across all environments, within and across mega-environments. Thirty-six unique consistent QTL regions were distributed on 13 chromosomes including 1A, 1B, 1D, 2A, 2D, 3D, 4B, 4D, 6A, 6B, 6D, 7B, and 7D. Ten unique QTL with pleiotropic effects were identified on four chromosomes and eight were in common with the consistent QTL. These QTL increased dry biomass grain yield by 16.3 g m-2, plot yield by 28.1 g m-2, kernels spike-1 by 0.7, spikes m-2 by 14.8, thousand kernel weight by 0.9 g with favorable alleles from either parent. TAM 112 alleles mainly increased spikes m-2 and thousand kernel weight while TMA 111 alleles increased kernels spike-1, harvest index and grain yield. The saturated genetic map and markers linked to significant QTL from this study will be very useful in developing high throughput genotyping markers for tracking the desirable haplotypes of these important yield-related traits in popular parental cultivars.

scholarly journals Identification of quantitative trait loci for leaf traits in rice

Genetika ◽  
2016 ◽  
Vol 48 (2) ◽  
pp. 643-652 ◽  
Author(s):  
Baoyan Jia ◽  
Xinhua Zhao ◽  
Yang Qin ◽  
Muhammad Irfan ◽  
Tae-Heon Kim ◽  
...  
Keyword(s):  
Recombinant Inbred Lines ◽  
Leaf Traits ◽  
Rice Cultivar ◽  
Interval Mapping ◽  
Mapping Method ◽  
Japonica Rice ◽  
Phenotypic Variance ◽  
Simple Sequence ◽  
Variance Explained ◽  
Map Distance

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.

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

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.

Detection of molecular markers associated with yield and yield components in durum wheat (Triticum turgidum L. var. durum) under saline conditions

2013 ◽  
Vol 64 (10) ◽  
pp. 957 ◽  
Author(s):  
S. Dura ◽  
M. Duwayri ◽  
M. Nachit ◽  
F. Al Sheyab
Keyword(s):  
Grain Yield ◽  
Durum Wheat ◽  
Yield Components ◽  
Agronomic Traits ◽  
Triticum Turgidum ◽  
Recombinant Inbred Lines ◽  
Wheat Breeding ◽  
Phenotypic Data ◽  
Yield And Yield Components ◽  
Ssr Loci

Durum wheat is one of the most important staple food crops, grown mainly in the Mediterranean region where its productivity is drastically affected by salinity. The objective of this study was to identify markers associated with grain yield and its related traits under saline conditions. A population of 114 F8 recombinant inbred lines (RILs) was derived by single-seed descent from a cross between Belikh2 (salinity-tolerant variety) and Omrabi5 (less salinity tolerant) was grown under non-saline and saline conditions in a glasshouse. Phenotypic data of the RILs and parental lines were measured for 15 agronomic traits. Association of 96 simple sequence repeat (SSR) loci covering all 14 chromosomes with 15 agronomic traits was analysed with a mixed linear model. In total, 49 SSR loci were significantly associated with these traits. Under saline conditions, 12 markers were associated with phenological traits and 19 markers were associated with yield and yield components. Marker alleles from Belikh2 were associated with a positive effect for the majority of markers associated with yield and yield components. Under saline condition, five markers (Xwmc182, Xwmc388, Xwmc398, Xbarc61, and Xwmc177) were closely linked with grain yield, located on chromosomes 2A, 3A, 3B, 4B, 5A, 6B, and 7A. These markers could be used for marker-assisted selection in durum wheat breeding under saline conditions.

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

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.

GENOTYPIC AND PHENOTYPIC VARIABILITY, HERITABILITY AND PHENOTYPIC CORRELATION FOR YIELD AND YIELD COMPONENTS IN BREAD WHEAT VARIETIES

2001 ◽  
Vol 49 (3) ◽  
pp. 237-242 ◽  
Author(s):  
K. Z. Korkut ◽  
I. BAŞER ◽  
O. Bilgin
Keyword(s):  
Grain Yield ◽  
Plant Height ◽  
Bread Wheat ◽  
Yield Components ◽  
Phenotypic Variability ◽  
Kernel Weight ◽  
Phenotypic Correlation ◽  
Genotypic Variability ◽  
Wheat Varieties ◽  
Yield And Yield Components

This research was conducted to determine the effect of genetic and phenotypic variability on the yield and yield components of some bread wheat varieties over a period of four years (1995–1998). Experiments were established according to a completely randomised block design with three replicates in the Experimental Field of Tekirda đ Agricultural Faculty, Thrace University. In the present research, genotypic and phenotypic variability, heritability and phenotypic correlation coefficients were estimated for plant height, spike length, number of spikelets per spike, number of spikes per square metre, thousand kernel weight, test weight and grain yield per hectare. The results of data analyses showed that the highest genotypic variability was obtained for per hectare yield, whereas the highest phenotypic variability values were found for plant height, thousand kernel weight and grain yield. For plant height, thousand grain yield and test weight, the broad sense heritability coefficient was found to be the highest, while it was low for spike length, number of spikelets per spike and number of Key words: bread wheat, genotypic variability, phenotypic variability, heritability coefficient, phenotypic correlation, grain yield

scholarly journals Mapping of QTLs Detected in a Broccoli Double Diploid Population for Plant Height and Leaf Characteristics

2020 ◽  
Author(s):  
Jingjing Huang ◽  
Jifeng Sun ◽  
Eryan Liu ◽  
Yumei Liu ◽  
Zhiyuan Fang ◽  
...  
Keyword(s):  
Molecular Markers ◽  
Plant Height ◽  
Interval Mapping ◽  
Chromosome 1 ◽  
Planting Density ◽  
Leaf Width ◽  
Contribution Rate ◽  
Diploid Population ◽  
Dh Population ◽  
Inclusive Composite Interval Mapping

Abstract Background The planting density of broccoli can directly affect the yield and overall health of plants. So there is necessary to reveal the regulatory genes of planting density in broccoli by QTL mapping. In this study, the important planting density-dependent factors of broccoli, plant height (PH), maximum outer petiole length (PL) and leaf width (LW), were investigated during 2017 and 2018. The mapping of QTLs for PH, PL and LW were performed, and the interaction between QTLs and the environment was also analyzed by a DH population constructed with 176 genotypes derived from F1 obtained by crossing the broccoli inbred lines 86101 (P1) and 90196 (P2).Results A linkage group including a total of 438 SSR markers were constructed covering a length of 1168.26 cM using QTL IciMapping 4.0 software. Finally, there were mainly four QTLs (phc1, phc2, phc4-1, phc4-2), one QTL (plc6), and two QTLs (lwc1, lwc3) corresponding for PH, PL and LW recurred during the two years. In three environments, inclusive composite interval mapping (ICIM) analysis showed that there was a major QTL for PH at 7.20 cM on chromosome 1 between molecular markers 8C024 and sf4482 with a high explanatory contribution rate of 20.05%. The QTL at the 11.10 cM position of chromosome 6 was located for the PL with a high explanatory contribution rate of 20.02% between the molecular markers sc2170 and sf43960. The QTL at the 147.00 cM position of chromosome 3 was located on LW with a high explanatory contribution rate of 19.97% between molecular markers of Sc52751 and RA2-E12.Conclusions According to the QTL results of planting density in broccoli by a DH population, the possible positions of candidate genes were screened to provide a basis for further locating and cloning genes for plant height, maximum outer petiole and leaf width.

Inclusive composite-interval mapping reveals quantitative trait loci for plant architectural traits in sorghum (Sorghum bicolor)

2019 ◽  
Vol 70 (8) ◽  
pp. 659
Author(s):  
Huawen Zhang ◽  
Runfeng Wang ◽  
Bin Liu ◽  
Erying Chen ◽  
Yanbing Yang ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Sorghum Bicolor ◽  
Quantitative Trait ◽  
Composite Interval Mapping ◽  
Recombinant Inbred Lines ◽  
Interval Mapping ◽  
Environment Interaction ◽  
Trait Loci ◽  
Inclusive Composite Interval Mapping ◽  
Architectural Traits

Architecture-efficient sorghum (Sorghum bicolor (L.) Moench) has erect leaves forming a compact canopy that enables highly effective utilisation of solar radiation; it is suitable for high-density planting, resulting in an elevated overall production. Development of sorghum ideotypes with optimal plant architecture requires knowledge of the genetic basis of plant architectural traits. The present study investigated seven production-related architectural traits by using 181 sorghum recombinant inbred lines (RILs) with contrasting architectural phenotypes developed from the cross Shihong 137 × L-Tian. Parents along with RILs were phenotyped for plant architectural traits for two consecutive years (2012, 2013) at two locations in the field. Analysis of variance revealed significant (P ≤ 0.05) differences among RILs for architectural traits. All traits showed medium to high broad-sense heritability estimates (0.43–0.94) and significant (P ≤ 0.05) genotype × environment effects. We employed 181 simple sequence repeat markers to identify quantitative trait loci (QTLs) and the effects of QTL × environment interaction based on the inclusive composite interval mapping algorithm. In total, 53 robust QTLs (log of odds ≥4.68) were detected for these seven traits and explained 2.11–12.11% of phenotypic variation. These QTLs had small effects of QTL × environment interaction and yet significant epistatic effects, indicating that they could stably express across environments but influence phenotypes through strong interaction with non-allelic loci. The QTLs and linked markers need to be verified through function and candidate-gene analyses. The new knowledge of the genetic regulation of architectural traits in the present study will provide a theoretical basis for the genetic improvement of architectural traits in sorghum.

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

2010 ◽  
Vol 100 (1) ◽  
pp. 80-84 ◽  
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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