The decreased expression of GW2 homologous genes contributed to the increased grain width and thousand‑grain weight in wheat-Dasypyrum villosum 6VS·6DL translocation lines

2021 ◽  
Author(s):  
Zhiyu Feng ◽  
Long Song ◽  
Wanjun Song ◽  
Zhongqi Qi ◽  
Jun Yuan ◽  
...  
Keyword(s):  
Grain Weight ◽  
Dasypyrum Villosum ◽  
Thousand Grain Weight ◽  
Homologous Genes ◽  
Translocation Lines ◽  
Grain Width

scholarly journals Validation of a QTL for Grain Size and Weight Using an Introgression Line from a Cross between Oryza sativa and Oryza minuta

Rice ◽  
2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Yue Feng ◽  
Xiaoping Yuan ◽  
Yiping Wang ◽  
Yaolong Yang ◽  
Mengchen Zhang ◽  
...  
Keyword(s):  
Grain Size ◽  
Oryza Sativa ◽  
Candidate Genes ◽  
Introgression Line ◽  
Grain Weight ◽  
Chromosome 7 ◽  
Thousand Grain Weight ◽  
Grain Length ◽  
Oryza Minuta ◽  
Grain Width

Abstract Background Grain size and weight are important target traits determining grain yield and quality in rice. Wild rice species possess substantial elite genes that can be served as an important resource for genetic improvement of rice. In this study, we identify and validate a novel QTL on chromosome 7 affecting the grain size and weight using introgression lines from cross of Oryza sativa and Oryza minuta. Results An introgression line ‘IL188’ has been achieved from a wild species Oryza minuta (2n = 48, BBCC, W303) into O. sativa japonica Nipponbare. The F2 and F2:3 populations derived from a cross between IL188 and Nipponbare were used to map QTLs for five grain size traits, including grain length (GL), grain width (GW), grain length to width ratio (LWR), grain thickness (GT) and thousand grain weight (TGW). A total of 12 QTLs for the five grain traits were identified on chromosomes 1, 2, 3, 6, 7, and 8. The QTL-qGL7 controlling GL on chromosome 7 was detected stably in the F2 and F2:3 populations, and explained 15.09–16.30% of the phenotypic variance. To validate the effect of qGL7, eight residual heterozygous line (RHL) populations were developed through selfing four F2:3 and four F2:4 plants with different heterozygous segments for the target region. By further developing SSR and Indel markers in the target interval, qGL7 was delimited to a ~ 261 kb region between Indel marker Y7–12 and SSR marker Y7–38, which also showed significant effects on grain width and thousand grain weight. Comparing with the reference genome of Nipponbare, stop or frameshift mutations in the exon of the three putative genes LOC_Os07g36830, LOC_Os07g36900 and LOC_Os07g36910 encoding F-box domain-containing proteins may be the candidate genes for qGL7. Scanning electron microscopy analysis of the glume’s epidermal cells showed that the cell length and width of NIL-qGL7IL188 was higher than NIL-qGL7Nip, indicating that qGL7 increases grain size and weight by regulating cell expansion. Conclusions In this study, we detected 12 QTLs regulating grain size and weight using an introgression line from a cross between Oryza sativa and Oryza minuta. Of these loci, we confirmed and delimited the qGL7 to a ~ 261 kb region. Three putative genes, LOC_Os07g36830, LOC_Os07g36900 and LOC_Os07g36910 encoding F-box domain-containing proteins may be the candidate genes for qGL7. These results provide a basis for map-based cloning of the qGL7 gene and useful information for marker assisted selection in rice grain quality improvement.

scholarly journals Analysis of genetic variability, heritability and genetic advance for yield and yield associated traits in some promising advanced lines of rice

2015 ◽  
Vol 26 (1) ◽  
pp. 26-31 ◽  
Author(s):  
MA Islam ◽  
SA Raffi ◽  
MA Hossain ◽  
AK Hasan
Keyword(s):  
Genetic Variability ◽  
Block Design ◽  
Grain Weight ◽  
Genetic Advance ◽  
Thousand Grain Weight ◽  
Randomized Complete Block Design ◽  
Days To Maturity ◽  
Additive Gene ◽  
High Heritability ◽  
Grain Width

A field experiment was conducted using twenty three rice genotypes including three check varieties during the period from June to December, 2013, at the Agronomy Field Laboratory, Department of Agronomy, Bangladesh Agricultural University, Mymensingh to study genetic variability, heritability and genetic advance (GA) for yield and yield associated traits in rice. The experiment was laid down in a randomized complete block design with three replications. Plant height, number of filled grains per panicle, days to 50% flowering, thousand grain weight, grain width and grain yield showed relatively high genotypic co-efficient of variation (GCV) and phenotypic co-efficient of variation (PCV) estimates. The PCV were higher than GCV for all eight traits indicating that they all interacted with the environment to some extent. High heritability was obtained for grain width (88.54%), followed by days to 50% flowering (87.61%), thousand grain weight (81.96%), grain length (81.94%), days to maturity (81.81%) and number of filled grains per panicle (78.19%) which indicates high heritable portion of variation. High to medium estimates of heritability and genetic advance were obtained for number of filled grains per panicle (18.97), days to 50% flowering (11.89), days to maturity (12.16) indicating the roles of additive gene action and a good scope of selection using their phenotypic performance. Considering, all of these characters, filled gains per panicle and days to 50% flowering and maturity were important yield related traits and could be used for selection in rice breeding programs.Progressive Agriculture 26:26-31, 2015

scholarly journals Validation of a QTL for grain size and weight using an introgression line from a cross between Oryza sativa and Oryza minuta 

2021 ◽  
Author(s):  
Yue Feng ◽  
Xiaoping Yuan ◽  
Yiping Wang ◽  
Yaolong Yang ◽  
Mengchen Zhang ◽  
...  
Keyword(s):  
Grain Size ◽  
Oryza Sativa ◽  
Candidate Genes ◽  
Introgression Line ◽  
Grain Weight ◽  
Chromosome 7 ◽  
Thousand Grain Weight ◽  
Grain Length ◽  
Oryza Minuta ◽  
Grain Width

Abstract Background: Grain size and weight are important target traits determining grain yield and quality in rice. Wild rice species possess substantial elite genes that can be served as an important resource for genetic improvement of rice. In this study, we identify and validate a novel QTL on chromosome 7 affecting the grain size and weight using introgression lines from cross of Oryza sativa and Oryza minuta. Results: An introgression line ‘IL188’ has been achieved from a wild species Oryza minuta (2n = 48, BBCC, W303) into O. sativa japonica Nipponbare. The F2 and F2:3 populations derived from a cross between IL188 and Nipponbare were used to map QTLs for five grain size traits, including grain length (GL), grain width (GW), grain length to width ratio (LWR), grain thickness (GT) and thousand grain weight (TGW). A total of 12 QTLs for the five grain traits were identified on chromosomes 1, 2, 3, 6, 7, and 8. The QTL-qGL7 controlling GL on chromosome 7 was detected stably in the F2 and F2:3 populations, and explained 15.09-16.30% of the phenotypic variance. To validate the effect of qGL7, eight residual heterozygous line (RHL) populations were developed through selfing four F2:3 and four F2:4 plants with different heterozygous segments for the target region. By further developing SSR and Indel markers in the target interval, qGL7 was delimited to a ~261 kb region between Indel marker Y7-12 and SSR marker Y7-38, which also showed significant effects on grain width and thousand grain weight. Comparing with the reference genome of Nipponbare, stop or frameshift mutations in the exon of the three putative genes LOC_Os07g36830, LOC_Os07g36900 and LOC_Os07g36910 encoding F-box domain-containing proteins may be the candidate genes for qGL7. Scanning electron microscopy analysis of the glume's epidermal cells showed that the cell length and width of NIL-qGL7IL188 was higher than NIL-qGL7Nip, indicating that qGL7 increases grain size and weight by regulating cell expansion. Conclusions: In this study, we detected 12 QTLs regulating grain size and weight using an introgression line from a cross between an Oryza sativa and Oryza minuta. Of these loci, we confirmed and delimited the qGL7 to a ~261 kb region. Three putative genes, LOC_Os07g36830, LOC_Os07g36900 and LOC_Os07g36910 encoding F-box domain-containing proteins may be the candidate genes for qGL7. These results provide a basis for map-based cloning of the qGL7 gene and useful information for marker assisted selection in rice grain quality improvement.

scholarly journals Utilization of a Wheat50K SNP Microarray-Derived High-Density Genetic Map for QTL Mapping of Plant Height and Grain Traits in Wheat

Plants ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1167
Author(s):  
Dongyun Lv ◽  
Chuanliang Zhang ◽  
Rui Yv ◽  
Jianxin Yao ◽  
Jianhui Wu ◽  
...  
Keyword(s):  
Plant Height ◽  
Genetic Map ◽  
Phenotypic Variation ◽  
Control Plant ◽  
Snp Array ◽  
High Density ◽  
Grain Weight ◽  
Thousand Grain Weight ◽  
Grain Length ◽  
Grain Width

Plant height is significantly correlated with grain traits, which is a component of wheat yield. The purpose of this study is to investigate the main quantitative trait loci (QTLs) that control plant height and grain-related traits in multiple environments. In this study, we constructed a high-density genetic linkage map using the Wheat50K SNP Array to map QTLs for these traits in 198 recombinant inbred lines (RILs). The two ends of the chromosome were identified as recombination-rich areas in all chromosomes except chromosome 1B. Both the genetic map and the physical map showed a significant correlation, with a correlation coefficient between 0.63 and 0.99. However, there was almost no recombination between 1RS and 1BS. In terms of plant height, 1RS contributed to the reduction of plant height by 3.43 cm. In terms of grain length, 1RS contributed to the elongation of grain by 0.11 mm. A total of 43 QTLs were identified, including eight QTLs for plant height (PH), 11 QTLs for thousand grain weight (TGW), 15 QTLs for grain length (GL), and nine QTLs for grain width (GW), which explained 1.36–33.08% of the phenotypic variation. Seven were environment-stable QTLs, including two loci (Qph.nwafu-4B and Qph.nwafu-4D) that determined plant height. The explanation rates of phenotypic variation were 7.39–12.26% and 20.11–27.08%, respectively. One QTL, Qtgw.nwafu-4B, which influenced TGW, showed an explanation rate of 3.43–6.85% for phenotypic variation. Two co-segregating KASP markers were developed, and the physical locations corresponding to KASP_AX-109316968 and KASP_AX-109519968 were 25.888344 MB and 25.847691 MB, respectively. Qph.nwafu-4B, controlling plant height, and Qtgw.nwafu-4B, controlling TGW, had an obvious linkage relationship, with a distance of 7–8 cM. Breeding is based on molecular markers that control plant height and thousand-grain weight by selecting strains with low plant height and large grain weight. Another QTL, Qgw.nwafu-4D, which determined grain width, had an explanation rate of 3.43–6.85%. Three loci that affected grain length were Qgl.nwafu-5A, Qgl.nwafu-5D.2, and Qgl.nwafu-6B, illustrating the explanation rates of phenotypic variation as 6.72–9.59%, 5.62–7.75%, and 6.68–10.73%, respectively. Two QTL clusters were identified on chromosomes 4B and 4D.

scholarly journals Research on a Rice Counting Algorithm Based on an Improved MCNN and a Density Map

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 721
Author(s):  
Ao Feng ◽  
Hongxiang Li ◽  
Zixi Liu ◽  
Yuanjiang Luo ◽  
Haibo Pu ◽  
...  
Keyword(s):  
Grain Weight ◽  
Gaussian Kernel ◽  
Density Level ◽  
Thousand Grain Weight ◽  
Original Algorithm ◽  
Different Types ◽  
Different Shapes ◽  
Density Map ◽  
Important Basis ◽  
Adhesion Condition

The thousand grain weight is an index of size, fullness and quality in crop seed detection and is an important basis for field yield prediction. To detect the thousand grain weight of rice requires the accurate counting of rice. We collected a total of 5670 images of three different types of rice seeds with different qualities to construct a model. Considering the different shapes of different types of rice, this study used an adaptive Gaussian kernel to convolve with the rice coordinate function to obtain a more accurate density map, which was used as an important basis for determining the results of subsequent experiments. A Multi-Column Convolutional Neural Network was used to extract the features of different sizes of rice, and the features were fused by the fusion network to learn the mapping relationship from the original map features to the density map features. An advanced prior step was added to the original algorithm to estimate the density level of the image, which weakened the effect of the rice adhesion condition on the counting results. Extensive comparison experiments show that the proposed method is more accurate than the original MCNN algorithm.

scholarly journals Expected genetic advance for thousand grain weight and grain number per spike of bread wheat and durum wheat

2016 ◽  
Vol 61 (2) ◽  
pp. 113-125
Author(s):  
Gordana Brankovic ◽  
Dejan Dodig ◽  
Desimir Knezevic ◽  
Vesna Kandic ◽  
Jovan Pavlov
Keyword(s):  
Durum Wheat ◽  
Bread Wheat ◽  
Yield Component ◽  
Grain Weight ◽  
Phenotypic Variance ◽  
Environment Interaction ◽  
Genetic Advance ◽  
Thousand Grain Weight ◽  
Grain Number ◽  
Grain Number Per Spike

The research was aimed at examining variability, variance components, broadsense heritability (h2), expected genetic advance of thousand grain weight (TGW) and grain number per spike (GNS) of 15 genotypes of bread wheat and 15 genotypes of durum wheat. Field trials were carried out during 2010-2011 and 2011-2012 growing seasons at the three sites: Rimski Sancevi, Zemun Polje and Padinska Skela. Results of this investigation showed that the genetic component of variance (?2 g) was predominant for TGW of bread and durum wheat and for GNS of bread wheat. The genotype ? environment interaction (?2 ge) component of phenotypic variance was 8.72 times higher than ?2 g for GNS of durum wheat and pointed to the greater instability of durum wheat genotypes. h2 was very high (>90%) for TGW and GNS of bread wheat, high for TGW of durum wheat - 87.3% and low for GNS of durum wheat - 39.5%. Considering the high values obtained for h2 - 96.4% and the highest value for expected genetic advance as percent of mean (GAM) - 19.3% for TGW of bread wheat, the success of selection for desired values of this yield component can be anticipated. The success of selection cannot be predicted for GNS of durum wheat due to low values obtained for h2 and GAM of 39.5% and 2.8%, respectively.

scholarly journals Genetic correlations and path-coefficient analysis of yield and quality components in wheat, Triticum aestivum L.

Genetika ◽  
2004 ◽  
Vol 36 (1) ◽  
pp. 13-21 ◽  
Author(s):  
Veselinka Zecevic ◽  
Desimir Knezevic ◽  
Danica Micanovic
Keyword(s):  
Genetic Correlation ◽  
Harvest Index ◽  
Genetic Correlations ◽  
Grain Weight ◽  
Spike Length ◽  
Phenotypic Correlation ◽  
Path Coefficient ◽  
Thousand Grain Weight ◽  
Path Coefficient Analysis ◽  
Bread Making

The genetic and phenotypic correlations between yield components (productive tillering, plant height, spike length, number of spikelets per spike, number of grains per spike, grain weight per spike, grain weight per plant, harvest index, thousand grain weight) and quality components (grain protein content and sedimentation value) were investigated. The plant material was comprised of 50 genotypes of winter wheat grown during two years. Path- coefficient analysis of genetic correlation coefficients for grain mass/plant and other traits determined interrelationships among grain mass per plant and other yield and bread making quality components. The strongest positive genetic correlation was found between grain weight per spike and thousand grain weight and between spike length and number of spikelets per spike. Phenotypic correlation analysis indicated that grain weight per spike correlated positively and significantly with harvest index and thousand kernel weight. The strongest direct effect on grain weight per plant had harvest index and number of spikelets per spike. The spike length through number of spikelets per spike had the strongest indirect effect on grain weight per plant.

Dissection of Closely Linked QTLs Controlling Grain Size in Rice

2021 ◽  
Author(s):  
Pao Xue ◽  
Yu-yu Chen ◽  
Xiao-xia Wen ◽  
Bei-fang Wang ◽  
Qin-qin Yang ◽  
...  
Keyword(s):  
Grain Size ◽  
Genetic Resources ◽  
Candidate Genes ◽  
Cell Expansion ◽  
Grain Weight ◽  
Cytological Observation ◽  
Yield Improvement ◽  
Transcript Levels ◽  
Grain Width ◽  
Successive Generations

Abstract Grain size is a key constituent of grain weight and appearance in rice. However, insufficient attention has been paid to the small-effect QTLs on grain size. In the present study, residual heterozygous populations were developed for mapping two genetically linked small-effect QTLs for grain size. After genotyping and phenotyping of five successive generations, qGS7.1 was dissected into three QTLs and two were selected for further analysis. qTGW7.2a was finally mapped into a 21.10-kb interval containing four annotated candidate genes. Transcript levels assay showed that the expression of candidates LOC_Os07g39490 and LOC_Os07g39500 were significantly reduced in the NIL- qTGW7.2a BG1 . Cytological observation indicated that qTGW7.2a regulated grain width through controlling cell expansion. Use the same strategy, qTGW7.2b was fine mapped into a 52.71-kb interval, showing a significant effect on grain length and width with opposite allelic directions but little on grain weight. Our study provides new genetic resources for yield improvement and fine-tunes of grain size in rice.

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