Mapping QTLs for 100-seed weight in an interspecific soybean cross of Williams 82 (Glycine max) and PI 366121 (Glycine soja)

2017 ◽  
Vol 68 (2) ◽  
pp. 148 ◽  
Author(s):  
Krishnanand P. Kulkarni ◽  
Sovetgul Asekova ◽  
Dong-Ho Lee ◽  
Kristin Bilyeu ◽  
Jong Tae Song ◽  
...  
Keyword(s):  
Seed Weight ◽  
Glycine Soja ◽  
Recombinant Inbred Lines ◽  
Molecular Genetic ◽  
Interval Mapping ◽  
Major Influence ◽  
Environment Interaction ◽  
Molecular Genetic Basis ◽  
The Individual ◽  
100 Seed Weight

Seed weight can be an important component for soybean quality and yield. The objective of the present study was to identify quantitative trait loci (QTLs) for 100-seed weight by using 169 recombinant inbred lines (RILs) derived from the cross Williams 82 × PI 366121. The parental lines and RILs were grown for four consecutive years (2012–15) in the field. The seeds were harvested after maturity, dried and used to measure 100-seed weight. Analysis of variance indicated significant differences among the RILs for 100-seed weight. The environment had significant effect on seed-weight expression as indicated by the genotype × environment interaction. QTL analysis employing inclusive composite interval mapping of additive QTLs implemented in QTL IciMapping (Version 4.1) identified nine QTLs (LOD >3) on chromosomes 1, 2, 6, 8, 13, 14, 17 and 20. The individual QTLs explained phenotypic variation in the range 6.1–12.4%. The QTLs were detected in one or two environments, indicating major influence of the growing environment on seed-weight expression. Four QTLs identified in this study, qSW-02_1, qSW-06_1, qSW-13_1 and qSW-14_1, were found to be new QTLs. The findings of the study may be helpful to reveal the molecular genetic basis of the seed-weight trait in soybean.

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.

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.

Deploying inter-specific recombinant inbred lines to map QTLs for yield-related traits in soybean

2020 ◽  
Vol 79 (04) ◽  
Author(s):  
Yashpal . ◽  
D. R. Rathod ◽  
Subhash Chandra ◽  
Anil Kumar ◽  
Raju Ratan Yadav ◽  
...  
Keyword(s):  
Recombinant Inbred ◽  
Glycine Soja ◽  
Recombinant Inbred Lines ◽  
Interval Mapping ◽  
Inbred Lines ◽  
Wild Type ◽  
Single Marker Analysis ◽  
Phenotypic Data ◽  
Single Marker ◽  
Glycine Max L

Quantitative trait loci (QTL) mapping and analyses were conducted for yield and six yield-related traits in soybean using 184 inter-specific recombinant inbred lines (RILs) derived from a cross involving wild type (Glycine soja Sieb. and Zucc.) accession DC2008-1 and cultivated (Glycine max L. Merr.) variety DS9712. A Linkage map of 1639.55 cM length was constructed with 167 SSR markers (65.65% polymorphism) with an average marker interval of 9.82 cM. Using three years phenotypic data 34 QTLs were mapped for 7 traits using Inclusive Composite Interval Mapping approach. The number of QTLs mapped for a trait varied from year to year, however, QTLs for days-to-50% flowering (qDFF5), 100-seed weight (qHSW9-1, qHSW9-2 and qHSW19) and yield (qYLD17) were mapped consistently over the three years of testing. Identified QTLs were validated through single marker analysis in 92 germplasm lines. The study demonstrated the potential of wild type soybean to harness QTLs for yield-related traits. The identified QTLs could be utilized for genetic improvement of soybean through molecular breeding.

Inclusive composite-interval mapping reveals quantitative trait loci for plant architectural traits in sorghum (Sorghum bicolor)

2019 ◽  
Vol 70 (8) ◽  
pp. 659
Author(s):  
Huawen Zhang ◽  
Runfeng Wang ◽  
Bin Liu ◽  
Erying Chen ◽  
Yanbing Yang ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Sorghum Bicolor ◽  
Quantitative Trait ◽  
Composite Interval Mapping ◽  
Recombinant Inbred Lines ◽  
Interval Mapping ◽  
Environment Interaction ◽  
Trait Loci ◽  
Inclusive Composite Interval Mapping ◽  
Architectural Traits

Architecture-efficient sorghum (Sorghum bicolor (L.) Moench) has erect leaves forming a compact canopy that enables highly effective utilisation of solar radiation; it is suitable for high-density planting, resulting in an elevated overall production. Development of sorghum ideotypes with optimal plant architecture requires knowledge of the genetic basis of plant architectural traits. The present study investigated seven production-related architectural traits by using 181 sorghum recombinant inbred lines (RILs) with contrasting architectural phenotypes developed from the cross Shihong 137 × L-Tian. Parents along with RILs were phenotyped for plant architectural traits for two consecutive years (2012, 2013) at two locations in the field. Analysis of variance revealed significant (P ≤ 0.05) differences among RILs for architectural traits. All traits showed medium to high broad-sense heritability estimates (0.43–0.94) and significant (P ≤ 0.05) genotype × environment effects. We employed 181 simple sequence repeat markers to identify quantitative trait loci (QTLs) and the effects of QTL × environment interaction based on the inclusive composite interval mapping algorithm. In total, 53 robust QTLs (log of odds ≥4.68) were detected for these seven traits and explained 2.11–12.11% of phenotypic variation. These QTLs had small effects of QTL × environment interaction and yet significant epistatic effects, indicating that they could stably express across environments but influence phenotypes through strong interaction with non-allelic loci. The QTLs and linked markers need to be verified through function and candidate-gene analyses. The new knowledge of the genetic regulation of architectural traits in the present study will provide a theoretical basis for the genetic improvement of architectural traits in sorghum.

scholarly journals GENOTYPE-ENVIRONMENT INTERACTION FOR SEED YIELD AND YIELD CONTRIBUTING CHARACTERS IN CHICKPEA (Cicer arietinum L.)

2007 ◽  
Vol 20 (1) ◽  
pp. 09-12
Author(s):  
F. Mahmud ◽  
M. Z. Ullah ◽  
K. M. K. Huda
Keyword(s):  
Seed Yield ◽  
Significant Variation ◽  
Seed Weight ◽  
Environment Interaction ◽  
Stability Parameters ◽  
Cicer Arietinum L ◽  
Plant Seeds ◽  
Genotype Environment Interaction ◽  
Days To Maturity ◽  
100 Seed Weight

Genotype-environment interaction was studied in seven genotypes of chickpea under four different cultural environments. Significant variation for genotype (G), environment (E) and G × E interactions were found for the characters days to maturity, plant height, pods/plant, seeds/plant, 100-seed weight and seed yield/plant. On the basis of stability parameters the genotypes Barichola-2, Barichola-3, Barichola-4, Barichola-7 and Barichola-8 could be considered stable for seed yield but suitable only under poor environments where no fertilizers were used. The genotype Barichola-1 was highly responsive but suitable for favorable environments only. DOI: http://dx.doi.org/10.3329/bjpbg.v20i1.17012

scholarly journals The Genetic Architecture of Drosophila Sensory Bristle Number

Genetics ◽  
2002 ◽  
Vol 162 (4) ◽  
pp. 1655-1674 ◽  
Author(s):  
Christy L Dilda ◽  
Trudy F C Mackay
Keyword(s):  
Complex Traits ◽  
Molecular Genetic ◽  
Interval Mapping ◽  
Isogenic Line ◽  
Wild Type ◽  
Epistatic Interactions ◽  
Bristle Number ◽  
Molecular Genetic Basis ◽  
Marker Loci ◽  
Mapping Populations

AbstractWe have mapped quantitative trait loci (QTL) for Drosophila mechanosensory bristle number in six recombinant isogenic line (RIL) mapping populations, each of which was derived from an isogenic chromosome extracted from a line selected for high or low, sternopleural or abdominal bristle number and an isogenic wild-type chromosome. All RILs were evaluated as male and female F1 progeny of crosses to both the selected and the wild-type parental chromosomes at three developmental temperatures (18°, 25°, and 28°). QTL for bristle number were mapped separately for each chromosome, trait, and environment by linkage to roo transposable element marker loci, using composite interval mapping. A total of 53 QTL were detected, of which 33 affected sternopleural bristle number, 31 affected abdominal bristle number, and 11 affected both traits. The effects of most QTL were conditional on sex (27%), temperature (14%), or both sex and temperature (30%). Epistatic interactions between QTL were also common. While many QTL mapped to the same location as candidate bristle development loci, several QTL regions did not encompass obvious candidate genes. These features are germane to evolutionary models for the maintenance of genetic variation for quantitative traits, but complicate efforts to understand the molecular genetic basis of variation for complex traits.

Phenotypic traits and diversity of different leaf shape accessions of the wild soybean (Glycine soja Sieb. et Zucc.) in China

2014 ◽  
Vol 94 (2) ◽  
pp. 397-404 ◽  
Author(s):  
Xuefei Yan ◽  
Hongkun Zhao ◽  
Xiaodong Liu ◽  
Qiyun Li ◽  
Yumin Wang ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Seed Weight ◽  
Glycine Soja ◽  
Leaf Shape ◽  
Wild Soybean ◽  
Phenotypic Traits ◽  
Evolutionary Status ◽  
Important Indicator ◽  
Linear Leaf ◽  
100 Seed Weight

Yan, X., Zhao, H., Liu, X., Li, Q., Wang, Y., Yuan, C. and Dong, Y. 2014. Phenotypic traits and diversity of different leaf shape accessions of the wild soybean (Glycine soja Sieb. et Zucc.) in China. Can. J. Plant Sci. 94: 397–404. The phenotypic traits and diversity of different leaf shape groups of 6169 wild soybean accessions were investigated. The results included the following conclusions. First, the lanceolate leaf group had the highest genetic diversity. Second, the mean 100-seed weight was highest in the round leaf group (10.1 g); mean maturity time was longest in the eliptical leaf group (142 d); the ovate–round and linear leaf groups had higher mean protein content (45.7–46.1%); and the round leaf group had the highest oil content (16.3%). Finally, frequencies of white flower, high 100-seed weight and other traits in the round leaf group were disproportionately high; in contrast, linear leaf accessions were primarily characterized by purple flower and low 100-seed weight. Based on these results, we inferred that the lanceolate and linear leaves accessions tended to be wild types, while the round leaf group represented more recently evolved accessions. In addition, the accessions with eliptical, ovate–round and other leaves belonged to the intermediate evolutionary types. Our results also suggest that the abundant variation in leaf shape is an important indicator of level of genetic diversity and evolutionary status, which could facilitate the utilization of germplasm evaluation and classification for the wild soybean.

scholarly journals Heritability for Morphological Traits Determine Adaptability of Elite Cowpea Genotypes in different Environments

2021 ◽  
Vol 26 (01) ◽  
pp. 105-114
Author(s):  
Joseph Nwafor Akanwe Asiwe
Keyword(s):  
Grain Yield ◽  
Yield Components ◽  
Seed Weight ◽  
Block Design ◽  
Field Trials ◽  
Research Station ◽  
Environment Interaction ◽  
Randomized Complete Block Design ◽  
The University ◽  
100 Seed Weight

Lack of improved and high-yielding adapted varieties constitutes limitation to cowpea (Vigna unguiculata (L.) Walp) production in South Africa. Therefore, field trials were conducted in two locations (the University of Limpopo Experimental Farm, (Mankweng) and Towoomba Research Station, Bela-Bela) during 2015–16 and 2016–17, to assess yield components, genotype x environment interaction as well as the adaptability of elite cowpea genotypes. The experiment was laid out using a randomized complete block design in three replications. Data were collected on flowering, maturity and yield components. Results revealed that “genotype, and genotype × year and genotype × location interactions were significant for most of the traits evaluated”. „The days to 50% flowering‟ and „90% maturity‟ ranged between 53 and 60 days, and between 89 and 96 days, respectively. The „100-seed weight‟ varied from 15.8 g to 22.5 g. „Broad-sense heritability‟ varied from 0 to 93% for days to maturity and grain yield, respectively. „Grain yield‟ varied from 1465.7 to 2594.9 kg ha-1, and the best yielders were lines „L2‟, „L10‟, and „L7‟. The „PC1‟ and „PC2‟ explained 82.57% variation for maturity, 79.12% for the „pods per plant‟, 83.78% for „seeds per pod‟, 93.09% for „100-seed weight‟ and 95.84% for „grain yield‟. Towoomba was a more productive location compared to Sykerfuil. Lines „L2‟, „L10‟, and „L7‟ yielded very well in both locations and years. This implies that they are adapted and are recommended for registration and commercial release in the region. © 2021 Friends Science Publishers

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