scholarly journals QTL mapping of agronomic traits in wheat using the UK Avalon ×  Cadenza reference mapping population grown in Kazakhstan

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10733
Author(s):  
Akerke Amalova ◽  
Saule Abugalieva ◽  
Vladimir Chudinov ◽  
Grigoriy Sereda ◽  
Laura Tokhetova ◽  
...  
Keyword(s):  
Qtl Mapping ◽  
Agronomic Traits ◽  
Reference Population ◽  
Interval Mapping ◽  
Mapping Method ◽  
Kernel Weight ◽  
Snp Markers ◽  
Potential Yield ◽  
Dh Population ◽  
The Uk

Background The success of wheat production is largely dependent on local breeding projects that focus on the development of high-yielding cultivars with the use of novel molecular tools. One strategy for improving wheat productivity involves the deployment of diverse germplasms with a high potential yield. An important factor for achieving success involves the dissection of quantitative trait loci (QTLs) for complex agronomic traits, such as grain yield components, in targeted environments for wheat growth. Methods In this study, we tested the United Kingdom (UK) spring set of the doubled haploid (DH) reference population derived from the cross between two British cultivars, Avalon (winter wheat) and Cadenza (spring wheat), in the Northern, Central, and Southern regions (Karabalyk, Karaganda, Kyzylorda) of Kazakhstan over three years (2013–2015). The DH population has previously been genotyped by UK scientists using 3647 polymorphic DNA markers. The list of tested traits includes the heading time, seed maturation time, plant height, spike length, productive tillering, number of kernels per spike, number of kernels per meter, thousand kernel weight, and yield per square meter. Windows QTL Cartographer was applied for QTL mapping using the composite interval mapping method. Results In total, 83 out of 232 QTLs were identified as stable QTLs from at least two environments. A literature survey suggests that 40 QTLs had previously been reported elsewhere, indicating that this study identified 43 QTLs that are presumably novel marker-trait associations (MTA) for these environments. Hence, the phenotyping of the DH population in new environments led to the discovery of novel MTAs. The identified SNP markers associated with agronomic traits in the DH population could be successfully used in local Kazakh breeding projects for the improvement of wheat productivity.

scholarly journals Gene–environment interactions in complex diseases: genetic models and methods for QTL mapping in multiple half-sib populations

2006 ◽  
Vol 88 (2) ◽  
pp. 119-131 ◽  
Author(s):  
HAJA N. KADARMIDEEN ◽  
YONGJUN LI ◽  
LUC L. G. JANSS
Keyword(s):  
Qtl Mapping ◽  
Scale Effects ◽  
High Standard ◽  
Interval Mapping ◽  
Mapping Method ◽  
Genetic Models ◽  
Gene Environment ◽  
Trait Locus ◽  
Outbred Populations ◽  
Binary Scale

An interval quantitative trait locus (QTL) mapping method for complex polygenic diseases (as binary traits) showing QTL by environment interactions (QEI) was developed for outbred populations on a within-family basis. The main objectives, within the above context, were to investigate selection of genetic models and to compare liability or generalized interval mapping (GIM) and linear regression interval mapping (RIM) methods. Two different genetic models were used: one with main QTL and QEI effects (QEI model) and the other with only a main QTL effect (QTL model). Over 30 types of binary disease data as well as six types of continuous data were simulated and analysed by RIM and GIM. Using table values for significance testing, results show that RIM had an increased false detection rate (FDR) for testing interactions which was attributable to scale effects on the binary scale. GIM did not suffer from a high FDR for testing interactions. The use of empirical thresholds, which effectively means higher thresholds for RIM for testing interactions, could repair this increased FDR for RIM, but such empirical thresholds would have to be derived for each case because the amount of FDR depends on the incidence on the binary scale. RIM still suffered from higher biases (15–100% over- or under-estimation of true values) and high standard errors in QTL variance and location estimates than GIM for QEI models. Hence GIM is recommended for disease QTL mapping with QEI. In the presence of QEI, the model including QEI has more power (20–80% increase) to detect the QTL when the average QTL effect is small (in a situation where the model with a main QTL only is not too powerful). Top-down model selection is proposed in which a full test for QEI is conducted first and then the model is subsequently simplified. Methods and results will be applicable to human, plant and animal QTL mapping experiments.

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.

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

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.

scholarly journals High-resolution genetic map and QTL analysis of growth-related traits of Hevea brasiliensis cultivated under suboptimal temperature and humidity conditions

2018 ◽  
Author(s):  
André Ricardo Oliveira Conson ◽  
Cristiane Hayumi Taniguti ◽  
Rodrigo Rampazo Amadeu ◽  
Isabela Aparecida Araújo Andreotti ◽  
Livia Moura de Souza ◽  
...  
Keyword(s):  
Hevea Brasiliensis ◽  
Rubber Tree ◽  
Tree Height ◽  
Interval Mapping ◽  
Mapping Method ◽  
Snp Markers ◽  
Genetic Maps ◽  
Stem Diameter ◽  
Breeding Cycle ◽  
Phenotypic Traits

AbstractRubber tree (Hevea brasiliensis) cultivation is the main source of natural rubber worldwide and has been extended to areas with suboptimal climates and lengthy drought periods; this transition affects growth and latex production. High-density genetic maps with reliable markers support precise mapping of quantitative trait loci (QTL), which can help reveal the complex genome of the species, provide tools to enhance molecular breeding, and shorten the breeding cycle. In this study, QTL mapping of the stem diameter, tree height, and number of whorls was performed for a full-sibling population derived from a GT1 and RRIM701 cross. A total of 225 simple sequence repeats (SSRs) and 186 single-nucleotide polymorphism (SNP) markers were used to construct a base map with 18 linkage groups and to anchor 671 SNPs from genotyping by sequencing (GBS) to produce a very dense linkage map with small intervals between loci. The final map was composed of 1,079 markers, spanned 3,779.7 cM with an average marker density of 3.5 cM, and showed collinearity between markers from previous studies. Significant variation in phenotypic characteristics was found over a 59-month evaluation period with a total of 38 QTLs being identified through a composite interval mapping method. Linkage group 4 showed the greatest number of QTLs (7), with phenotypic explained values varying from 7.67% to 14.07%. Additionally, we estimated segregation patterns, dominance, and additive effects for each QTL. A total of 53 significant effects for stem diameter were observed, and these effects were mostly related to additivity in the GT1 clone. Associating accurate genome assemblies and genetic maps represents a promising strategy for identifying the genetic basis of phenotypic traits in rubber trees. Then, further research can benefit from the QTLs identified herein, providing a better understanding of the key determinant genes associated with growth of Hevea brasiliensis under limiting water conditions.

scholarly journals Precision mapping of quantitative trait loci.

Genetics ◽  
1994 ◽  
Vol 136 (4) ◽  
pp. 1457-1468 ◽  
Author(s):  
Z B Zeng
Keyword(s):  
Quantitative Trait Loci ◽  
Qtl Mapping ◽  
Quantitative Trait ◽  
Interval Mapping ◽  
Mapping Method ◽  
Search Problem ◽  
Test Statistic ◽  
Advantages And Disadvantages ◽  
A Genome ◽  
Trait Loci

Abstract Adequate separation of effects of possible multiple linked quantitative trait loci (QTLs) on mapping QTLs is the key to increasing the precision of QTL mapping. A new method of QTL mapping is proposed and analyzed in this paper by combining interval mapping with multiple regression. The basis of the proposed method is an interval test in which the test statistic on a marker interval is made to be unaffected by QTLs located outside a defined interval. This is achieved by fitting other genetic markers in the statistical model as a control when performing interval mapping. Compared with the current QTL mapping method (i.e., the interval mapping method which uses a pair or two pairs of markers for mapping QTLs), this method has several advantages. (1) By confining the test to one region at a time, it reduces a multiple dimensional search problem (for multiple QTLs) to a one dimensional search problem. (2) By conditioning linked markers in the test, the sensitivity of the test statistic to the position of individual QTLs is increased, and the precision of QTL mapping can be improved. (3) By selectively and simultaneously using other markers in the analysis, the efficiency of QTL mapping can be also improved. The behavior of the test statistic under the null hypothesis and appropriate critical value of the test statistic for an overall test in a genome are discussed and analyzed. A simulation study of QTL mapping is also presented which illustrates the utility, properties, advantages and disadvantages of the method.

scholarly journals Inheritance Analysis and Quantitative Trait Loci Detection of Head Splitting Resistance in Cabbage (Brassica oleracea L. var. capitata)

HortScience ◽  
2015 ◽  
Vol 50 (7) ◽  
pp. 944-951 ◽  
Author(s):  
Yanbin Su ◽  
Yumei Liu ◽  
Huolin Shen ◽  
Xingguo Xiao ◽  
Zhansheng Li ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Qtl Mapping ◽  
Quantitative Trait ◽  
Major Gene ◽  
Genetic Regulation ◽  
Interval Mapping ◽  
Phenotypic Data ◽  
Dh Population ◽  
Trait Loci ◽  
Inclusive Composite Interval Mapping

Head splitting resistance (HSR) in cabbage is an important trait closely related to appearance, yield, storability, and mechanical harvestability. In this study, a doubled haploid (DH) population derived from a cross between head splitting-susceptible inbred cabbage line 79-156 and resistant line 96-100 was used to analyze inheritance and detect quantitative trait loci (QTLs) for HSR during 2011–12 in Beijing, China. The analysis was performed using a mixed major gene/polygene inheritance method and QTL mapping. This approach, which uncovered no cytoplasmic effect, indicated that HSR can be attributed to additive-epistatic effects of three major gene pairs combined with those of polygenes. Major gene and polygene heritabilities were estimated to be 88.03% to 88.22% and 5.65% to 7.60%, respectively. Using the DH population, a genetic map was constructed with simple sequence repeat (SSR) markers anchored on nine linkage groups spanning 906.62 cM. Eight QTLs for HSR were located on chromosomes C4, C5, C7, and C9 based on 2 years of phenotypic data using both multiple-QTL mapping and inclusive composite interval mapping. The identified QTLs collectively explained 37.6% to 46.7% of phenotypic variation. Three or four major QTLs (Hsr 4.2, 7.2, 9.3, and/or 9.1) showing a relatively larger effect were robustly detected in different years or with different mapping methods. The HSR trait was shown to have a complex genetic basis. Results from QTL mapping and classical genetic analysis were consistent. Our results provide a foundation for further research on HSR genetic regulation and molecular marker-assisted selection (MAS) for HSR in cabbage.

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

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.

scholarly journals QTL Mapping for Domestication-Related Characteristics in Field Cress (Lepidium campestre)—A Novel Oil Crop for the Subarctic Region

Genes ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 1223
Author(s):  
Cecilia Hammenhag ◽  
Ganapathi Varma Saripella ◽  
Rodomiro Ortiz ◽  
Mulatu Geleta
Keyword(s):  
Qtl Mapping ◽  
Interval Mapping ◽  
Snp Markers ◽  
Oilseed Crop ◽  
Subarctic Region ◽  
Speed Up ◽  
Lepidium Campestre ◽  
Marker Alleles ◽  
Number Of Stems ◽  
Field Cress

Domestication of a new crop requires identification and improvement of desirable characteristics Field cress (Lepidium campestre) is being domesticated as a new oilseed crop, particularly for northern temperate regions.. In the present study, an F2 mapping population and its F3 progenies were used to identify quantitative trait loci (QTLs) for plant height (PH), number of stems per plant (NS), stem growth orientation (SO), flowering habit (FH), earliness (ER), seed yield per plant (SY), pod shattering resistance (SHR), and perenniality (PE). A highly significant correlation (p < 0.001) was observed between several pairs of characteristics, including SY and ER (negative) or ER and PE (positive). The inclusive composite interval mapping approach was used for QTL mapping using 2330 single nucleotide polymorphism (SNP) markers mapped across the eight field cress linkage groups. Nine QTLs were identified with NS, PH, SO, and PE having 3, 3, 2, and 1 QTLs, explaining 21.3%, 29.5%, 3.8%, and 7.2% of the phenotypic variation, respectively. Candidate genes behind three of the QTLs and favorable marker alleles for different classes of each characteristic were identified. Following their validation through further study, the identified QTLs and associated favorable marker alleles can be used in marker-aided breeding to speed up the domestication of field cress.

scholarly journals Position Validation of the Dwarfing Gene Dw6 in Oat (Avena sativa L.) and Its Correlated Effects on Agronomic Traits

2021 ◽  
Vol 12 ◽  
Author(s):  
Honghai Yan ◽  
Kaiquan Yu ◽  
Yinghong Xu ◽  
Pingping Zhou ◽  
Jun Zhao ◽  
...  
Keyword(s):  
Plant Height ◽  
Avena Sativa ◽  
Positional Cloning ◽  
Agronomic Traits ◽  
Single Gene ◽  
Kernel Weight ◽  
Potential Yield ◽  
Coleoptile Length ◽  
Dwarfing Gene ◽  
Kernel Length

An F6:8 recombinant inbred line (RIL) population derived from the cross between WAOAT2132 (Dw6) and Caracas along with the two parents were used to evaluate the genetic effects of Dw6 dwarfing gene on plant height and other agronomic traits in oat (Avena sativa L.) across three environments, and develop closely linked markers for marker-assisted selection (MAS) for Dw6. The two parents differed in all investigated agronomic traits except for the number of whorls. The RIL lines showed a bimodal distribution for plant height in all three tested environments, supporting the height of this population was controlled by a single gene. Dw6 significantly reduced plant height (37.66∼44.29%) and panicle length (13.99∼22.10%) but without compromising the coleoptile length which was often positively associated with the reduced stature caused by dwarfing genes. Dw6 has also strong negative effects on hundred kernel weight (14.00∼29.55%), and kernel length (4.21∼9.47%), whereas the effects of Dw6 on the kernel width were not uniform across three environments. By contrast, lines with Dw6 produced more productive tillers (10.11∼10.53%) than lines without Dw6. All these together suggested the potential yield penalty associated with Dw6 might be partially due to the decrease of kernel weight which is attributed largely to the reduction of kernel length. Eighty-one simple sequence repeat (SSR) primer pairs from chromosome 6D were tested, five of them were polymorphic in two parents and in two contrasting bulks, confirming the 6D location of Dw6. By using the five polymorphic markers, Dw6 was mapped to an interval of 1.0 cM flanked by markers SSR83 and SSR120. Caution should be applied in using this information since maker order conflicts were observed. The close linkages of these two markers to Dw6 were further validated in a range of oat lines. The newly developed markers will provide a solid basis for future efforts both in the identification of Dw6 in oat germplasm and in the determination of the nature of the gene through positional cloning.

Yield performance with heritability measurements of half sib families obtained from maize variety Azam

1970 ◽  
pp. 33-36
Author(s):  
Faizan Mahmood, Hidayat- Ur-Rahman, Nazir Ahmad ◽  
Fahim-ul- Haq ◽  
Samrin Gul, Quaid Hussain ◽  
Ammara Khalid ◽  
Touheed Iqbal ◽  
...  
Keyword(s):  
Grain Yield ◽  
Agronomic Traits ◽  
Heritability Estimate ◽  
Kernel Weight ◽  
Yield Performance ◽  
Grain Moisture ◽  
Maize Variety ◽  
Ear Height ◽  
Sib Families

This study evaluated the performance of 64 half sib families (HSF) derived from “Azam” variety of maize using partially balanced lattice square design with two replications. Data were recorded on grain yield and other agronomic traits. Observations showed difference in half-sib families for studied traits. Among the 64 half-sib families, minimum days to 50% tasseling (51 days) were observed for HS-49 while maximum (57 days) for HS-63. Minimum days to 50% silking (56 days) were counted for HS-6 while maximum (63 days) for HS-23. Minimum days to 50% anthesis (55 days) were counted for HS-1 and HS-6 while maximum (62 days) for HS-23. Similarly, minimum ASI (-2 days) were observed in HS-1, HS-15, HS-16, HS-28 and HS-63 while maximum (2 days) in HS-48. Minimum (60 cm) ear height was recorded for HS-11 and maximum (93.5 cm) for HS-28. Minimum fresh ear weight (1.3 kg) was weighted for HS-17 while maximum (3.2 kg) for HS-21. Grain moisture was recorded minimum (19.35 %) for HS-19 and maximum (31.25%) for HS-2. HS-42 showed minimum (28 g) 100 kernel weight while HS-5 showed maximum (47 g). Grain yield was minimum (2323 kg ha-1) for HS-17 and maximum (5742 kg ha-1) for HS-21. Maximum heritability estimate (0.92) was recorded for fresh ear weight, while minimum (0.41) was observed for ear height.

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