scholarly journals QTL Mapping of Agronomic and Economic Traits for Four F2 Populations of Upland Cotton

2020 ◽  
Author(s):  
Hongge Li ◽  
Zhaoe Pan ◽  
Shoupu He ◽  
Yinhua Jia ◽  
Xiaoli Geng ◽  
...  
Keyword(s):  
Complex Traits ◽  
Upland Cotton ◽  
Genetic Basis ◽  
Fiber Quality ◽  
Genetic Maps ◽  
Yield Potential ◽  
High Yield ◽  
World Cotton ◽  
Economic Traits ◽  
High Yield Potential

Abstract Background: Upland cotton (Gossypium hirsutum) accounts for more than 90% of the annual world cotton output because of its high yield potential. However, yield and fiber quality traits often show negative correlations. We constructed four F2 populations of unland cotton, using two normal lines (4133B and SGK9708) with high yield potential but moderate fiber quality and two introgression lines (Suyuan04-3 and J02-247) with superior fiber quality, and used them to investigate the genetic basis underlying complex traits such as yield and fiber quality in upland cotton. We also phenotyped eight agronomic and economic traits and mapped quantitative trait loci (QTLs). Results: Extensive phenotype variations and transgressive segregation were found across the segregation populations. We constructed four genetic maps of 585.97 cM, 752.45 cM, 752.45 cM and 1 163.66 cM, one for each of the four F2 populations.. Fifty QTLs were identified across the four populations (7 for plant height, 27 for fiber quality and 16 for yield). The same QTLs were identified in different populations, including qBW4 and qBW2, which were linked to a common simple sequence repeat (SSR) marker, NAU1255. A QTL cluster containing eight QTLs for six different traits was characterized on linkage group 9 of the 4133B×Suyuan04-3 population. Conclusions: These findings will provide insights into the genetic basis of simultaneous improvement of yield and fiber quality in upland cotton breeding.

scholarly journals QTL mapping of agronomic and economic traits for four F2 populations of upland cotton

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Hongge LI ◽  
Zhaoe PAN ◽  
Shoupu HE ◽  
Yinhua JIA ◽  
Xiaoli GENG ◽  
...  
Keyword(s):  
Complex Traits ◽  
Upland Cotton ◽  
Genetic Basis ◽  
Fiber Quality ◽  
Genetic Maps ◽  
Yield Potential ◽  
High Yield ◽  
World Cotton ◽  
Economic Traits ◽  
High Yield Potential

Abstract Background Upland cotton (Gossypium hirsutum) accounts for more than 90% of the annual world cotton output because of its high yield potential. However, yield and fiber quality traits often show negative correlations. We constructed four F2 populations of upland cotton, using two normal lines (4133B and SGK9708) with high yield potential but moderate fiber quality and two introgression lines (Suyuan04–3 and J02–247) with superior fiber quality, and used them to investigate the genetic basis underlying complex traits such as yield and fiber quality in upland cotton. We also phenotyped eight agronomic and economic traits and mapped quantitative trait loci (QTLs). Results Extensive phenotype variations and transgressive segregation were found across the segregation populations. We constructed four genetic maps of 585.97 centiMorgan (cM), 752.45 cM, 752.45 cM, and 1 163.66 cM, one for each of the four F2 populations. Fifty QTLs were identified across the four populations (7 for plant height, 27 for fiber quality and 16 for yield). The same QTLs were identified in different populations, including qBW4 and qBW2, which were linked to a common simple sequence repeat (SSR) marker, NAU1255. A QTL cluster containing eight QTLs for six different traits was characterized on linkage group 9 of the 4133B × Suyuan04–3 population. Conclusions These findings will provide insights into the genetic basis of simultaneous improvement of yield and fiber quality in upland cotton breeding.

scholarly journals QTL Mapping of Agronomic and Economic Traits for Four F2 Populations in Upland Cotton

2020 ◽  
Author(s):  
Hongge Li ◽  
Zhaoe Pan ◽  
Shoupu He ◽  
Yinhua Jia ◽  
Xiaoli Geng ◽  
...  
Keyword(s):  
Qtl Mapping ◽  
Upland Cotton ◽  
Genetic Basis ◽  
Fiber Quality ◽  
Yield Potential ◽  
World Cotton ◽  
Yield Traits ◽  
Quality Traits ◽  
Economic Traits ◽  
Fiber Quality Traits

Abstract Background: Upland cotton (Gossypium hirsutum) accounts for more than 90% of annual world cotton output due to its high yield potential. However, yield traits and fiber quality traits exhibit negative correlations in most cases. Here, we constructed four F2 populations, using two normal lines and two introgression lines, for simultaneously detection the genetic basis underlying complex traits such as yield and fiber quality in upland cotton. Subsequently, the phenotyping of 8 agronomic and economic traits along with quantitative trait loci (QTL) mapping was implemented. Results: Extensive phenotype variations and transgressive segregation were found across segregation populations. Four genetic maps were constructed with the length of 585.97cM, 752.45cM, 752.45cM and 1163.66cM. The mapping resulted in the identification 50 QTLs (27 were for fiber quality traits and 16 for yield traits) across four populations. Multiple QTLs having the common maker, such as qBW4 and qBW2, or residing in the same QTL cluster, such as qLP9 and qFL9-1, were prioritized for further research. Conclusions: These findings will provide insight into the genetic basis of simultaneous improvement of yield and fiber quality in upland cotton breeding.

scholarly journals QTL Mapping of Agronomic and Economic Traits for Four F2 Populations in Upland Cotton

2020 ◽  
Author(s):  
Hongge Li ◽  
Zhaoe Pan ◽  
Shoupu He ◽  
Yinhua Jia ◽  
Xiaoli Geng ◽  
...  
Keyword(s):  
Qtl Mapping ◽  
Upland Cotton ◽  
Fiber Quality ◽  
Genetic Maps ◽  
Yield Potential ◽  
World Cotton ◽  
Yield Traits ◽  
Quality Traits ◽  
Economic Traits ◽  
Fiber Quality Traits

Abstract Background: Upland cotton (Gossypium hirsutum) accounts for more than 90% of annual world cotton output due to its high yield potential. However, yield traits and fiber quality traits exhibit negative correlations in most cases. Here, to dissect simultaneously the genetic basis underlying complex traits such as yield and fiber quality as well as their genetic correlations in upland cotton, four F2 populations were constructed using two normal lines and two introgression lines. Subsequently, phenotyping of 8 agronomic and economic traits along with QTL mapping were implemented.Results: Extensive phenotype variations and transgressive segregation were found across segregation populations. Four genetic maps with length of 585.97cM, 752.45cM, 752.45cM and 1163.66cM were construct. The result of mapping displayed a total of 50 QTLs across four populations were identified, of which 27 were for fiber quality traits and 16 for yield traits. Multiple QTLs having the common maker, such as qBW4 and qBW2, or residing in the same QTL cluster, such as qLP9 and qFL9-1, were prioritized for further research.Conclusions: These findings will provide insight into simultaneous improvement of yield and fiber quality in upland cotton breeding.

scholarly journals QTL Mapping of Agronomic and Economic Traits for Four F2 Populations in Upland Cotton

2020 ◽  
Author(s):  
Hongge Li ◽  
Zhaoe Pan ◽  
Shoupu He ◽  
Yinhua Jia ◽  
Xiaoli Geng ◽  
...  
Keyword(s):  
Qtl Mapping ◽  
Upland Cotton ◽  
Genetic Basis ◽  
Fiber Quality ◽  
Yield Potential ◽  
World Cotton ◽  
Yield Traits ◽  
Quality Traits ◽  
Economic Traits ◽  
Fiber Quality Traits

Abstract Background: Upland cotton (Gossypium hirsutum) accounts for more than 90% of annual world cotton output due to its high yield potential. However, yield traits and fiber quality traits exhibit negative correlations in most cases. Here, we constructed four F2 populations, using two normal lines and two introgression lines, for simultaneously detection the genetic basis underlying complex traits such as yield and fiber quality in upland cotton. Subsequently, the phenotyping of 8 agronomic and economic traits along with quantitative trait loci (QTL) mapping was implemented. Results: Extensive phenotype variations and transgressive segregation were found across segregation populations. Four genetic maps were constructed with the length of 585.97cM, 752.45cM, 752.45cM and 1 163.66cM. A total of 50 QTLs were identified across four populations (7 for plant height, 27 for fiber quality traits and 16 for yield traits). The same QTLs were identified from different populations such as qBW4 and qBW2 which were linked to common markers. A QTL cluster was characterized in D09 of population 4Su which contained 8 QTLs for 6 different traits. Conclusions: These findings will provide insight into the genetic basis of simultaneous improvement of yield and fiber quality in upland cotton breeding.

FloRunTM ‘331’ Peanut Variety

EDIS ◽  
2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Barry L. Tillman
Keyword(s):  
Seed Size ◽  
Growth Habit ◽  
Yield Potential ◽  
High Yield ◽  
University Of Florida ◽  
High Oleic ◽  
Central Stem ◽  
Research And Education ◽  
The University ◽  
High Yield Potential

FloRunTM ‘331’ peanut variety was developed by the University of Florida, Institute of Food and Agricultural Sciences, North Florida Research and Education Center near Marianna, Florida.  It was released in 2016 because it combines high yield potential with excellent disease tolerance. FloRunTM ‘331’ has a typical runner growth habit with a semi-prominent central stem and medium green foliage.  It has medium runner seed size with high oleic oil chemistry.

scholarly journals Genomic Prediction and Indirect Selection for Grain Yield in US Pacific Northwest Winter Wheat Using Spectral Reflectance Indices from High-Throughput Phenotyping

2019 ◽  
Vol 21 (1) ◽  
pp. 165 ◽  
Author(s):  
Dennis N. Lozada ◽  
Jayfred V. Godoy ◽  
Brian P. Ward ◽  
Arron H. Carter
Keyword(s):  
Winter Wheat ◽  
Pacific Northwest ◽  
Prediction Accuracy ◽  
Indirect Selection ◽  
Yield Potential ◽  
High Yield ◽  
High Throughput Phenotyping ◽  
Reflectance Indices ◽  
Selection Of ◽  
High Yield Potential

Secondary traits from high-throughput phenotyping could be used to select for complex target traits to accelerate plant breeding and increase genetic gains. This study aimed to evaluate the potential of using spectral reflectance indices (SRI) for indirect selection of winter-wheat lines with high yield potential and to assess the effects of including secondary traits on the prediction accuracy for yield. A total of five SRIs were measured in a diversity panel, and F5 and doubled haploid wheat breeding populations planted between 2015 and 2018 in Lind and Pullman, WA. The winter-wheat panels were genotyped with 11,089 genotyping-by-sequencing derived markers. Spectral traits showed moderate to high phenotypic and genetic correlations, indicating their potential for indirect selection of lines with high yield potential. Inclusion of correlated spectral traits in genomic prediction models resulted in significant (p < 0.001) improvement in prediction accuracy for yield. Relatedness between training and test populations and heritability were among the principal factors affecting accuracy. Our results demonstrate the potential of using spectral indices as proxy measurements for selecting lines with increased yield potential and for improving prediction accuracy to increase genetic gains for complex traits in US Pacific Northwest winter wheat.

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