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

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.

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

PeerJ ◽

10.7717/peerj.10733 ◽

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.

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Identification of genes regulating traits targeted for domestication of field cress (Lepidium campestre) as a biennial and perennial oilseed crop

BMC Genetics ◽

10.1186/s12863-018-0624-9 ◽

2018 ◽

Vol 19 (1) ◽

Cited By ~ 4

Author(s):

Cecilia Gustafsson ◽

Jakob Willforss ◽

Fernando Lopes-Pinto ◽

Rodomiro Ortiz ◽

Mulatu Geleta

Keyword(s):

Oilseed Crop ◽

Lepidium Campestre ◽

Field Cress

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On the Differences Between Maximum Likelihood and Regression Interval Mapping in the Analysis of Quantitative Trait Loci

Genetics ◽

10.1093/genetics/156.2.855 ◽

2000 ◽

Vol 156 (2) ◽

pp. 855-865 ◽

Cited By ~ 2

Author(s):

Chen-Hung Kao

Keyword(s):

Quantitative Trait Loci ◽

Maximum Likelihood ◽

Qtl Mapping ◽

Quantitative Trait ◽

Mean Squared Error ◽

Interval Mapping ◽

Size Difference ◽

Ratio Test ◽

Trait Loci ◽

Variance Explained

AbstractThe differences between maximum-likelihood (ML) and regression (REG) interval mapping in the analysis of quantitative trait loci (QTL) are investigated analytically and numerically by simulation. The analytical investigation is based on the comparison of the solution sets of the ML and REG methods in the estimation of QTL parameters. Their differences are found to relate to the similarity between the conditional posterior and conditional probabilities of QTL genotypes and depend on several factors, such as the proportion of variance explained by QTL, relative QTL position in an interval, interval size, difference between the sizes of QTL, epistasis, and linkage between QTL. The differences in mean squared error (MSE) of the estimates, likelihood-ratio test (LRT) statistics in testing parameters, and power of QTL detection between the two methods become larger as (1) the proportion of variance explained by QTL becomes higher, (2) the QTL locations are positioned toward the middle of intervals, (3) the QTL are located in wider marker intervals, (4) epistasis between QTL is stronger, (5) the difference between QTL effects becomes larger, and (6) the positions of QTL get closer in QTL mapping. The REG method is biased in the estimation of the proportion of variance explained by QTL, and it may have a serious problem in detecting closely linked QTL when compared to the ML method. In general, the differences between the two methods may be minor, but can be significant when QTL interact or are closely linked. The ML method tends to be more powerful and to give estimates with smaller MSEs and larger LRT statistics. This implies that ML interval mapping can be more accurate, precise, and powerful than REG interval mapping. The REG method is faster in computation, especially when the number of QTL considered in the model is large. Recognizing the factors affecting the differences between REG and ML interval mapping can help an efficient strategy, using both methods in QTL mapping to be outlined.

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Genome wide association analyses to understand genetic basis of flowering and plant height under three levels of nitrogen application in Brassica juncea (L.) Czern & Coss

Scientific Reports ◽

10.1038/s41598-021-83689-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Javed Akhatar ◽

Anna Goyal ◽

Navneet Kaur ◽

Chhaya Atri ◽

Meenakshi Mittal ◽

...

Keyword(s):

Plant Height ◽

Indian Subcontinent ◽

Association Studies ◽

Snp Markers ◽

Genome Wide Association ◽

Strong Interactions ◽

N Availability ◽

Oilseed Crop ◽

Genome Wide Association Studies ◽

Genome Wide

AbstractTimely transition to flowering, maturity and plant height are important for agronomic adaptation and productivity of Indian mustard (B. juncea), which is a major edible oilseed crop of low input ecologies in Indian subcontinent. Breeding manipulation for these traits is difficult because of the involvement of multiple interacting genetic and environmental factors. Here, we report a genetic analysis of these traits using a population comprising 92 diverse genotypes of mustard. These genotypes were evaluated under deficient (N75), normal (N100) or excess (N125) conditions of nitrogen (N) application. Lower N availability induced early flowering and maturity in most genotypes, while high N conditions delayed both. A genotyping-by-sequencing approach helped to identify 406,888 SNP markers and undertake genome wide association studies (GWAS). 282 significant marker-trait associations (MTA's) were identified. We detected strong interactions between GWAS loci and nitrogen levels. Though some trait associated SNPs were detected repeatedly across fertility gradients, majority were identified under deficient or normal levels of N applications. Annotation of the genomic region (s) within ± 50 kb of the peak SNPs facilitated prediction of 30 candidate genes belonging to light perception, circadian, floral meristem identity, flowering regulation, gibberellic acid pathways and plant development. These included over one copy each of AGL24, AP1, FVE, FRI, GID1A and GNC. FLC and CO were predicted on chromosomes A02 and B08 respectively. CDF1, CO, FLC, AGL24, GNC and FAF2 appeared to influence the variation for plant height. Our findings may help in improving phenotypic plasticity of mustard across fertility gradients through marker-assisted breeding strategies.

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

Genetics Research ◽

10.1017/s0016672306008391 ◽

2006 ◽

Vol 88 (2) ◽

pp. 119-131 ◽

Cited By ~ 6

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.

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Mean-Variance QTL Mapping Identifies Novel QTL for Circadian Activity and Exploratory Behavior in Mice

10.1101/276972 ◽

2018 ◽

Cited By ~ 1

Author(s):

Robert W. Corty ◽

Vivek Kumar ◽

Lisa M. Tarantino ◽

Joseph S. Takahashi ◽

William Valdar

Keyword(s):

Qtl Mapping ◽

Linear Model ◽

Wheel Running ◽

Interval Mapping ◽

Residual Variance ◽

Running Activity ◽

First Case ◽

Wheel Running Activity ◽

Mean Variance

ABSTRACTWe illustrate, through two case studies, that “mean-variance QTL mapping” can discover QTL that traditional interval mapping cannot. Mean-variance QTL mapping is based on the double generalized linear model, which elaborates on the standard linear model by incorporating not only a linear model for the data itself, but also a linear model for the residual variance. Its potential for use in QTL mapping has been described previously, but it remains underutilized, with certain key advantages undemonstrated until now. In the first case study, we use mean-variance QTL mapping to reanalyze a reduced complexity intercross of C57BL/6J and C57BL/6N mice examining circadian behavior and find a mean-controlling QTL for circadian wheel running activity that was not detected by traditional interval mapping. Mean-variance QTL mapping was more powerful than traditional interval mapping at the QTL because it accounted for the fact that mice homozygous for the C57BL/6N allele had less residual variance than the other mice. In the second case study, we reanalyze an intercross between C57BL/6J and C58/J mice examining anxiety-like behaviors, and identify a variance-controlling QTL for rearing behavior. This QTL was not identified in the original analysis because traditional interval mapping does not target variance QTL.

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

10.1101/355008 ◽

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.

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High-Density Genetic Linkage Map Construction and White Rot Resistance Quantitative Trait Loci Mapping for Genus Vitis Based on Restriction Site-Associated DNA Sequencing

Phytopathology ◽

10.1094/phyto-12-19-0480-r ◽

2021 ◽

pp. PHYTO-12-19-048

Author(s):

Kai Su ◽

Yinshan Guo ◽

Weihao Zhong ◽

Hong Lin ◽

Zhendong Liu ◽

...

Keyword(s):

Qtl Mapping ◽

Dna Sequencing ◽

Quantitative Trait ◽

Restriction Site ◽

Genetic Distances ◽

Snp Markers ◽

High Density ◽

White Rot ◽

Phenotypic Variance ◽

Trait Locus

Grape white rot (Coniothyrium diplodiella) is a major fungal disease affecting grape yield and quality. Quantitative trait locus (QTL) analysis is an important method for studying important horticultural traits of grapevine. This study was conducted to construct a high-density map and conduct QTL mapping for grapevine white rot resistance. A mapping population with 177 genotypes was developed from interspecific hybridization of a white rot-resistant cultivar (Vitis vinifera × V. labrusca ‘Zhuosexiang’) and white rot-susceptible cultivar (V. vinifera ‘Victoria’). Single-nucleotide polymorphism (SNP) markers were developed by restriction site-associated DNA sequencing. The female, male, and integrated maps contained 2,501, 4,110, and 6,249 SNP markers with average genetic distances of adjacent markers of 1.25, 0.77, and 0.50 cM, respectively. QTL mapping was conducted based on white rot resistance identification of 177 individuals in July and August of 2017 and 2018. Notably, one stable QTL related to white rot resistance was detected and located on linkage group LG14. The phenotypic variance ranged from 12.93 to 13.43%. An SNP marker (chr14_3929380), which cosegregated with white rot resistance, was discovered and shows potential for use in marker-assisted selection to generate new grapevine cultivars with resistance to white rot.

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Mapping QTLs for tolerance to salt stress at the early seedling stage in rice (Oryza sativa L.) using a newly identified donor ‘Madina Koyo’

Euphytica ◽

10.1007/s10681-020-02689-5 ◽

2020 ◽

Vol 216 (10) ◽

Author(s):

Nana Kofi Abaka Amoah ◽

Richard Akromah ◽

Alex Wireko Kena ◽

Baboucarr Manneh ◽

Ibnou Dieng ◽

...

Keyword(s):

Salt Stress ◽

Oryza Sativa L ◽

Dry Weight ◽

Interval Mapping ◽

Snp Markers ◽

Seedling Stage ◽

Direct Selection ◽

Chromosome 2 ◽

Shoot Dry Weight ◽

Early Seedling

Abstract Salt stress is a menace to rice production and a threat to food security worldwide. We evaluated 308 F4 families from Sahel 317/Madina Koyo for tolerance to salt stress at the early seedling stage. To better understand genomic regions controlling tolerance in the population, we genotyped the progenies and the two parents using single nucleotide polymorphism (SNP) markers and regressed the genotypic data on their phenotype to detect QTLs. An average reduction of 63.4% was observed for all fitness-related traits among the F4 families. A total of 46 progenies recorded an average salt injury score (SIS) between 1–3 and were rated as tolerant to salt stress at the early seedling stage. A high-density genetic map was constructed for the 12 rice chromosomes using 3698 SNP markers. Multiple interval mapping identified 13 QTLs for SIS, shoot length, shoot dry weight and root length on chromosomes 2, 3, 4, 6, 7, 10 and 12, with trait increasing alleles coming from both parents. Two (qSDW2 and qRL2.2) and three (qSL2, qRL2.1 and qSIS2) QTLs at different regions on chromosome 2 and another two on chromosome 7 (qSDW7 and qSL7) were tightly linked. These QTLs could facilitate breeding for salt tolerance at the early seedling stage as direct selection for one, would mean indirectly selecting for the other. Fine mapping of these novel QTLs in a different genetic background is necessary to confirm their stability and usefulness in breeding for tolerance to salinity in rice.

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