Mapping for Axillary Shooting, Flowering Date, Primary Axis Length, and Number of Leaves in Pepper (Capsicum annuum)

Mimura, Yutaka; Minamiyama, Yasuhiro; Sano, Hikazu; Hirai, Masashi

doi:10.2503/jjshs1.79.56

Cited by 18 publications

(26 citation statements)

References 24 publications

(31 reference statements)

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“…A limited number of studies have identified QTL associated with vegetative parts of the plant (leaves, stem internodes, and petioles) (Barchi et al, M.M. Moulin et al 2009;Mimura et al, 2010). Lee et al (2011) located a QTL related to the pepper fruit length, located in linkage group 3, which explained 27% of trait phenotypic variation.…”

Section: Introductionmentioning

confidence: 99%

Genetic dissection of agronomic traits in Capsicum baccatum var. pendulum

et al. 2015

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ABSTRACT. Genetic mapping is very useful for dissecting complex agronomic traits. Genetic mapping allows for identification of quantitative trait loci (QTL), provide knowledge on a gene position and its adjacent region, and enable prediction of evolutionary mechanisms, in addition to contributing to synteny studies. The aim of this study was to predict genetic values associated with different agronomic traits evaluated in an F 2 population of Capsicum baccatum var. pendulum. Previously, a reference genetic map for C. baccatum was constructed, which included 183 markers (42 microsatellite, 85 inter-simple sequence repeat, and 56 random amplification of polymorphic DNA) arranged in 16 linkage groups. The map was used to identify QTL associated with 11 agronomic traits, including plant height, crown diameter, number of days to flowering, days to fruiting, number of fruits per plant, average fruit weight, fruit length, fruit diameter, fruit QTLs for agronomic traits in C. baccatum var. pendulum pulp thickness, soluble solids, and fruit dry weight. QTL mapping was performed by standard interval mapping. The number of small QTL effects ranged from 3-11, with a total of 61 QTL detected in 9 linkage groups. This is the first report involving QTL analysis for C. baccatum species.

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Section: Introductionmentioning

confidence: 99%

Genetic dissection of agronomic traits in Capsicum baccatum var. pendulum

et al. 2015

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“…In all four environments, traits were highly heritable (mean 0.86 with range from 0.43 -0.96); hence good possibilities for mapping QTLs governing these traits. Our estimates of heritability are generally comparable with earlier results from Barchi et al (2009) and Mimura et al (2010) for related traits such as Axl, NLE and INL. We estimated higher heritabilities for NF and DWF as compared to result of Rao et al (2003).…”

Section: Linkage Groupsupporting

confidence: 89%

“…QTLs for fruit yield (DWF) found on LG 2 and 4 were picked up in most of the studies that evaluated fruit yield. The detected QTL for Axl on LG 3 in this study was also found in the study of Mimura et al (2010), Alimi et al (2010), Barchi et al (2009) andBen Chaim et al (2001b). Some QTLs were only picked up in some of the studies possibly due to any of the factors listed above including lack of segregation in that particular population and/or population size.…”

Section: Linkage Groupsupporting

confidence: 83%

“…Results from these studies revealed clusters of QTLs on chromosomes 2, 3 and 4 for fruit traits such as fruit weight/yield, diameter, length and shape. Only few studies have reported on QTLs influencing vegetative-related traits such as stem length and number of internodes (Ben Chaim et al, 2001b;Barchi et al, 2009;Mimura et al, 2010). In these studies, major QTLs influencing primary vegetative components like length and number of internodes on the primary stem were found on chromosomes 2, 3 and 12.…”

Section: Qtl Mapping In Peppermentioning

confidence: 99%

“…A number of studies have already assessed performances of many fruit and some vegetative phenotypes of pepper (Ben Chaim et al, 2001b;Rao et al, 2003;Zygier et al, 2005;Ben Chaim et al, 2006a;Barchi et al, 2009;Mimura et al, 2010). In all of these studies, traits were assessed in a single environment; hence comparing the performances of their populations between environments was not possible.…”

Section: Linkage Groupmentioning

confidence: 99%

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Statistical methods for QTL mapping and genomic prediction of multiple traits and environments: case studies in pepper

Alimi

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In this thesis we describe the results of a number of quantitative techniques that were used to understand the genetics of yield in pepper as an example of complex trait measured in a number of environments. Main objectives were; i) to propose a number of mixed models to detect QTLs for multiple traits and multiple environments, ii) to extend the multi-trait QTL models to a multi-trait genomic prediction model, iii) to study how well the complex trait yield can be indirectly predicted from its component traits, and iv) to understand the 'causal' relationships between the target trait yield and its component traits.The thesis is part of an EU-FP7 project "Smart tools for Prediction and Improvements of Crop Yield" (SPICY-http://www.spicyweb.eu/). This project generated phenotypic data from four environments using 149 individuals from the sixth generation of recombinant inbred lines obtained from intraspecific cross between large -fruited inbred pepper cultivar 'Yolo Wonder' (YW) and the hot pepper cultivar 'Criollo de Morelos 334' (CM 334). A total of 16 physiological traits were evaluated across the four trials and various types of genetic parameters were estimated. In a first analysis, the traits were univariately analyzed using linear mixed model. Trait heritabilities were generally large (ranging between 0.43 -0.96 with an average of 0.86) and mostly comparable across trials while many of the traits displayed heterosis and transgression. The same QTLs were detected across the four trials, though QTL magnitude differed for many of the traits. We also found that some QTLs affected more than one trait, suggesting QTL pleiotropy (a QTL region affecting more than one trait). We discussed our results in the light of previously reported QTLs for these and similar traits in pepper.We addressed the presence of genotype-by-environment interaction (GEI) in yield and the other traits through a multi-environment (ME) mixed model methodology with terms for QTL-by-environment interaction (QEI). We opined that yield would benefit from joint analysis with other traits and so deployed two other mixed model based multi-response QTL approaches: a multi-trait approach (MT) and a multi-trait multi-environment approach (MTME). For yield as well as the other traits, MTME was superior to ME and MT in the number of QTLs, the explained variance and accuracy of predictions. Many of the detected QTLs were pleiotropic and showed quantitative QEI. The results confirmed the feasibility and strengths of novel mixed model QTL methodology to study the architecture of complex traits.The QTL methods considered thus far are not well suited for prediction purposes as only a limited set of QTL-related markers are used. Since the main interest of this research includes improvement of yield prediction, we explored both single-trait and multi-trait versions of genomic prediction (GP) models as alternatives to the QTL-based prediction (QP) models. This was termed direct prediction. The methods differed in their predictive accuracies with GP meth...

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Conventional and Contemporary Approaches to Enhance Efficiency in Breeding Chilli/Hot Pepper

Rao

Kumar

2020

Accelerated Plant Breeding, Volume 2

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Mapping for Axillary Shooting, Flowering Date, Primary Axis Length, and Number of Leaves in Pepper (Capsicum annuum)

Cited by 18 publications

References 24 publications

Genetic dissection of agronomic traits in Capsicum baccatum var. pendulum

Genetic dissection of agronomic traits in Capsicum baccatum var. pendulum

Statistical methods for QTL mapping and genomic prediction of multiple traits and environments: case studies in pepper

Conventional and Contemporary Approaches to Enhance Efficiency in Breeding Chilli/Hot Pepper

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