scholarly journals Impact of epistasis and QTL×environmental interaction on the mass filling rate during seed development of soybean

2012 ◽  
Vol 94 (2) ◽  
pp. 63-71 ◽  
Author(s):  
ZHENFENG JIANG ◽  
YINGPENG HAN ◽  
WEILI TENG ◽  
YONGGUANG LI ◽  
XUE ZHAO ◽  
...  
Keyword(s):  
Seed Development ◽  
Developmental Stages ◽  
Environmental Control ◽  
Recombinant Inbred Lines ◽  
Soybean Seed ◽  
Environment Interaction ◽  
Filling Rate ◽  
Seed Filling ◽  
Environment Effects ◽  
Initial Stage

SummarySeed filling rate of soybean has been shown to be a dynamic process in different developmental stages affected by both genotype and environment. The objective of the present study was to determine additive, epistatic and quantitative trait loci (QTLs)×environment interaction (QE) effects of the QTL underlying a seed filling rate of soybean. One hundred and forty-three recombinant inbred lines (RILs) derived from the cross of Charleston and Dongnong 594 were used with 2 years of field data (2004 and 2005). Eleven QTLs with significantly unconditional and conditional additive (a) effect and/or additive×environment interaction (ae) effect at different filling stages were identified. Of them six QTLs showed positive a effects and four QTLs had negative a effects on the seed filling rate during seed development. aa and aae effects of 12 pairs of QTLs were identified by unconditional mapping from the initial stage to the final stage. Thirteen pairs of QTLs underlying the seed filling rate with aa and aae effects were identified by conditional mapping. QTLs with aa and aae (additive×additive×environment) effects appeared to vary at different filling stages. Our results demonstrated that the mass filling rate in soybean seed were under genetic and environmental control.

scholarly journals Impact of epistasis and QTL×environment interaction on the accumulation of seed mass of soybean (Glycine max L. Merr.)

2008 ◽  
Vol 90 (6) ◽  
pp. 481-491 ◽  
Author(s):  
YINGPENG HAN ◽  
WEILI TENG ◽  
DESHENG SUN ◽  
YUPING DU ◽  
LIJUAN QIU ◽  
...  
Keyword(s):  
Seed Development ◽  
Seed Weight ◽  
Developmental Stages ◽  
Environmental Control ◽  
Recombinant Inbred Lines ◽  
Seed Mass ◽  
Environment Interaction ◽  
Glycine Max L ◽  
Trait Locus ◽  
100 Seed Weight

SummaryThe accumulation of seed mass in soybean is affected by both genotype and environment. The aim of the present study was to measure additive, epistatic and quantitative trait locus (QTL)×environment (QE) interaction effects of QTLs on the development of 100-seed weight in a population of 143 F5 derived recombinant inbred lines (RILs) developed from the cross between the soybean cultivars ‘Charleston’ and ‘Dong Nong 594’. Broad-sense heritability of 100-seed weight from 30 days (30D) to 80D stages was 0·58, 0·52, 0·62, 0·60, 0·66 and 0·57, respectively. A total of 17 QTLs with conditional additive (a) effect and/or conditional additive×environment interaction (ae) effect at specific stages were identified in ten linkage groups by conditional mapping. Of them, only 4 QTLs had significant a effect or ae effect at different stages of seed development. Among QTLs with significant a effect, five acted positively and six acted negatively on seed development. A total of 35 epistatic pairwise QTLs of 100-seed weight were identified by conditional mapping at different developmental stages. Five pairs of QTL showed the additive×additive epistatic (aa) effect and 16 QTLs showed the aa×environment interaction (aae) effect at the different developmental stages. QTLs with aa effect as well with their environmental interaction effect appeared to vary at different developmental stages. Overall, the results indicated that 100-seed weight in soybean is under developmental, genetic and environmental control.

Identification of quantitative trait loci underlying seed protein content of soybean including main, epistatic, and QTL × environment effects in different regions of Northeast China

Genome ◽  
2017 ◽  
Vol 60 (8) ◽  
pp. 649-655 ◽  
Author(s):  
Weili Teng ◽  
Wen Li ◽  
Qi Zhang ◽  
Depeng Wu ◽  
Xue Zhao ◽  
...  
Keyword(s):  
Protein Content ◽  
Phenotypic Variation ◽  
Genetic Linkage Map ◽  
Seed Protein ◽  
Soybean Protein ◽  
Recombinant Inbred Lines ◽  
Environment Interaction ◽  
Phenotypic Data ◽  
Environment Effects ◽  
Stable Qtls

The objective here was to identify QTL underlying soybean protein content (PC), and to evaluate the additive and epistatic effects of the QTLs. A mapping population, consisting of 129 recombinant inbred lines (RILs), was created by crossing ‘Dongnong 46’ and ‘L-100’. Phenotypic data of the parents and RILs were collected for 4 years in three locations of Heilongjiang Province of China. A total of 213 SSR markers were used to construct a genetic linkage map. Eight QTLs, located on seven chromosomes (Chr), were identified to be associated with PC among the 10 tested environments. Of the seven QTLs, five QTLs, qPR-2 (Satt710, on Chr9), qPR-3 (Sat_122, on Chr12), qPR-5 (Satt543, on Chr17), qPR-7 (Satt163, on Chr18), and qPR-8 (Satt614, on Chr20), were detected in six, seven, seven, six, and seven environments, respectively, implying relatively stable QTLs. qPR-3 could explain 3.33%–11.26% of the phenotypic variation across eight tested environments. qPR-5 and qPR-8 explained 3.64%–10.1% and 11.86%–18.40% of the phenotypic variation, respectively, across seven tested environments. Eight QTLs associated with PC exhibited additive and (or) additive × environment interaction effects. The results showed that environment-independent QTLs often had higher additive effects. Moreover, five epistatic pairwise QTLs were identified in the 10 environments.

Identification of quantitative trait loci underlying seed oil content of soybean including main, epistatic and QTL×environment effects in different regions of Northeast China

2017 ◽  
Vol 68 (7) ◽  
pp. 625 ◽  
Author(s):  
Weili Teng ◽  
Binbin Zhang ◽  
Qi Zhang ◽  
Wen Li ◽  
Depeng Wu ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Oil Content ◽  
Recombinant Inbred Lines ◽  
Soybean Seed ◽  
Environment Interaction ◽  
Additive Effects ◽  
Linkage Groups ◽  
Soybean Breeding ◽  
Trait Loci

Oil content is a primary trait in soybean and determines the quality of soy food, feed and oil product. Increasing oil content is a major objective of soybean breeding. The aims of the present study were to identify quantitative trait loci (QTLs) and epistatic QTLs associated with oil content in soybean seed by using 129 recombinant inbred lines derived from a cross between cultivar Dongnong 46 (oil content 22.53%) and the semi-wild line L-100 (oil content 17.33%). Phenotypic data were collected from 10 tested environments including Harbin in the years 2012–15, Hulan in 2013–15 and Acheng in 2013–15. A genetic linkage map including 213 simple sequence repeat markers in 18 chromosomes (or linkage groups) was constructed, covering ~3623.39 cM. Seven QTLs, located on five chromosomes (or linkage groups), were identified to be associated with oil content, explaining 2.24–17.54% of the phenotypic variation in multi-environments. Among these identified QTLs, five (qOIL-2, qOIL-4, qOIL-5, qOIL-6 and qOIL-7) were detected in more than five environments. Seven QTLs had additive and/or additive × environment interaction effects. QTLs with higher additive effects were more stable in multi-environments than those with lower additive effects. Moreover, five epistatic, pairwise QTLs were identified in different environments. The findings with respect to genetic architecture for oil content could be valuable for marker-assisted selection in soybean breeding programs for high oil content.

Identification of QTL underlying mass filling rate at different developmental stages of soybean seed

Euphytica ◽  
2012 ◽  
Vol 189 (2) ◽  
pp. 249-260 ◽  
Author(s):  
Zhenfeng Jiang ◽  
Junjie Ding ◽  
Yingpeng Han ◽  
Weili Teng ◽  
Zhongchen Zhang ◽  
...  
Keyword(s):  
Developmental Stages ◽  
Soybean Seed ◽  
Filling Rate

Identification of QTL underlying the oil filling rate at different developmental stages of soybean seed

Euphytica ◽  
2010 ◽  
Vol 176 (3) ◽  
pp. 391-402 ◽  
Author(s):  
Zhenfeng Jiang ◽  
Yingpeng Han ◽  
Weili Teng ◽  
Zhongchen Zhang ◽  
Desheng Sun ◽  
...  
Keyword(s):  
Developmental Stages ◽  
Soybean Seed ◽  
Filling Rate ◽  
Oil Filling Rate

Dissection of the genetic architecture for soybean seed weight across multiple environments

2017 ◽  
Vol 68 (4) ◽  
pp. 358 ◽  
Author(s):  
Weili Teng ◽  
Lei Feng ◽  
Wen Li ◽  
Depeng Wu ◽  
Xue Zhao ◽  
...  
Keyword(s):  
Phenotypic Variation ◽  
Seed Weight ◽  
Average Distance ◽  
Recombinant Inbred Lines ◽  
Molecular Genetic ◽  
Soybean Seed ◽  
Environment Interaction ◽  
Phenotypic Data ◽  
Molecular Genetic Map ◽  
Variation Explained

Seed weight (SW), measured as mass per seed, significantly affects soybean (Glycine max (L.) Merr.) yield and the quality of soybean-derived food. The objective of the present study was to identify quantitative trait loci (QTLs) and epistatic QTLs associated with SW in soybean across 129 recombinant inbred lines (RILs) derived from a cross between Dongnong 46 (100-seed weight, 20.26 g) and ‘L-100 (4.84 g). Phenotypic data were collected from this population after it was grown in nine environments. A molecular genetic map including 213 simple sequence repeat (SSR) markers was constructed, which distributed in 18 of 20 chromosomes (linkage groups). This map encompassed ~3623.39 cM, with an average distance of 17.01 cM between markers. Nine QTLs associated with SW were identified. These QTLs explained 1.07–18.43% of the observed phenotypic variation in the nine different environments, and the phenotypic variation explained by most QTLs was 5–10%. Among these nine QTLs, qSW-3 (Satt192) and qSW-5 (Satt568) explained 2.33–9.96% and 7.26–15.11% of the observed phenotypic variation across eight tested environments, respectively. QTLs qSW-8 (Satt514) and qSW-9 (Satt163) were both identified in six environments and explained 8.99–16.40% and 3.68–18.43% of the observed phenotypic variation, respectively. Nine QTLs had additive and/or additive × environment interaction effects, and the environment-independent QTLs often had higher additive effects. Moreover, nine epistatic pairwise QTLs were identified in different environments. Understanding the existence of additive and epistatic effects of SW QTLs could guide the choice of which reasonable SW QTL to manipulate and could predict the outcomes of assembling a large number of SW QTLs with marker-assisted selection of soybean varieties with desirable SW.

Impact of epistasis and QTL × environmental interaction on the oil filling rate of soybean seed at different developmental stages

Euphytica ◽  
2010 ◽  
Vol 177 (3) ◽  
pp. 431-442 ◽  
Author(s):  
Zhenfeng Jiang ◽  
Binbin Zhang ◽  
Weili Teng ◽  
Yingpeng Han ◽  
Xue Zhao ◽  
...  
Keyword(s):  
Developmental Stages ◽  
Soybean Seed ◽  
Filling Rate ◽  
Environmental Interaction ◽  
Oil Filling Rate

Identification of QTL underlying the filling rate of protein at different developmental stages of soybean seed

Euphytica ◽  
2010 ◽  
Vol 175 (2) ◽  
pp. 227-236 ◽  
Author(s):  
Zhenfeng Jiang ◽  
Yingpeng Han ◽  
Weili Teng ◽  
Zhongchen Zhang ◽  
Desheng Sun ◽  
...  
Keyword(s):  
Developmental Stages ◽  
Soybean Seed ◽  
Filling Rate

scholarly journals Analysis of miRNAs Targeted Storage Regulatory Genes during Soybean Seed Development Based on Transcriptome Sequencing

Genes ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 408 ◽  
Author(s):  
Jing-Yao Yu ◽  
Zhan-Guo Zhang ◽  
Shi-Yu Huang ◽  
Xue Han ◽  
Xin-Yu Wang ◽  
...  
Keyword(s):  
Expression Pattern ◽  
Seed Development ◽  
Small Rna ◽  
Target Genes ◽  
Soybean Seed ◽  
Regulatory Genes ◽  
Small Rna Sequencing ◽  
Grain Development ◽  
Regulatory Relationship ◽  
Novel Mirna

Soybeans are an important cash crop and are widely used as a source of vegetable protein and edible oil. MicroRNAs (miRNA) are endogenous small RNA that play an important regulatory role in the evolutionarily conserved system of gene expression. In this study, we selected four lines with extreme phenotypes, as well as high or low protein and oil content, from the chromosome segment substitution line (CSSL) constructed from suinong (SN14) and ZYD00006, and planted and sampled at three stages of grain development for small RNA sequencing and expression analysis. The sequencing results revealed the expression pattern of miRNA in the materials, and predicted miRNA-targeted regulatory genes, including 1967 pairs of corresponding relationships between known-miRNA and their target genes, as well as 597 pairs of corresponding relationships between novel-miRNA and their target genes. After screening and annotating genes that were targeted for regulation, five specific genes were identified to be differentially expressed during seed development and subsequently analyzed for their regulatory relationship with miRNAs. The expression pattern of the targeted gene was verified by Real-time Quantitative PCR (RT-qPCR). Our research provides more information about the miRNA regulatory network in soybeans and further identifies useful genes that regulate storage during soy grain development, providing a theoretical basis for the regulation of soybean quality traits.

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