scholarly journals Identification of Grain Size-Related QTLs in Korean japonica Rice Using Genome Resequencing and High-Throughput Image Analysis

Agriculture ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 51
Author(s):  
Yunji Shin ◽  
Yong Jae Won ◽  
Chaewon Lee ◽  
Kyeong-Seong Cheon ◽  
Hyoja Oh ◽  
...  
Keyword(s):  
Grain Size ◽  
Image Analysis ◽  
High Throughput ◽  
Width Ratio ◽  
Japonica Rice ◽  
Multiple Traits ◽  
Genome Resequencing ◽  
Rice Varieties ◽  
Grain Length ◽  
Six Traits

Grain size is a key factor influencing the grain yield in rice. To identify the as-yet-unknown genes regulating grain size in Korean japonica rice, we developed a recombinant inbred line population (n = 162) from a cross between Odae (large-grain) and Joun (small-grain), and measured six traits including the thousand-grain weights of unhulled and hulled seeds, grain area, grain length, grain width and grain length-to-width ratio using high-throughput image analysis at the F8 and F9 generations. A genetic map was constructed using 248 kompetitive allele-specific PCR (KASP) markers that were polymorphic between the parental genotypes, and 29 QTLs affecting the six traits were identified, of which 15 were stable in both F8 and F9 generations. Notably, three QTL clusters affecting multiple traits were detected on chromosomes 6, 7 and 11. We analyzed whole-genome resequencing data of Odae and Joun, and selected candidate genes for the stable QTLs in the identified clusters that have high- or moderate-impact variations between Odae and Joun and encode proteins the families of which have been reported to be related to grain size regulation. These results will facilitate the identification of genes underlying the QTLs and promote molecular breeding of high-yielding Korean japonica rice varieties.

scholarly journals Fine-mapping of qTGW2, a quantitative trait locus for grain weight in rice (Oryza sativa L.)

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8679 ◽  
Author(s):  
Hui Zhang ◽  
Yu-Jun Zhu ◽  
An-Dong Zhu ◽  
Ye-Yang Fan ◽  
Ting-Xu Huang ◽  
...  
Keyword(s):  
Qtl Analysis ◽  
Quantitative Trait ◽  
Oryza Sativa L ◽  
Grain Weight ◽  
Width Ratio ◽  
Isogenic Line ◽  
Rice Varieties ◽  
Grain Length ◽  
Major Qtls ◽  
Length Width

Background Grain weight is a grain yield component, which is an integrated index of grain length, width and thickness. They are controlled by a large number of quantitative trait loci (QTLs). Besides major QTLs, minor QTLs play an essential role. In our previous studies, QTL analysis for grain length and width was performed using a recombinant inbred line population derived from rice cross TQ/IRBB lines. Two major QTLs were detected, which were located in proximity to GS3 and GW5 that have been cloned. In the present study, QTLs for grain weight and shape were identified using rice populations that were homozygous at GS3 and GW5. Method Nine populations derived from the indica rice cross TQ/IRBB52 were used. An F10:11population named W1, consisting of 250 families and covering 16 segregating regions, was developed from one residual heterozygote (RH) in the F7generation of Teqing/IRBB52. Three near isogenic line (NIL)-F2 populations, ZH1, ZH2 and ZH3 that comprised 205, 239 and 234 plants, respectively, were derived from three RHs in F10:11. They segregated the target QTL region in an isogenic background. Two NIL populations, HY2 and HY3, were respectively produced from homozygous progeny of the ZH2 and ZH3 populations. Three other NIL-F2 populations, Z1, Z2 and Z3, were established using three RHs having smaller heterozygous segments. QTL analysis for 1000-grain weight (TGW), grain length (GL), grain width (GW), and length/width ratio (LWR) was conducted using QTL IciMapping and SAS procedure with GLM model. Result A total of 27 QTLs distributed on 12 chromosomes were identified. One QTL cluster, qTGW2/qGL2/qGW2 located in the terminal region of chromosome 2, were selected for further analysis. Two linked QTLs were separated in region Tw31911−RM266. qGL2 was located in Tw31911−Tw32437 and mainly controlled GL and GW. The effects were larger on GL than on GW and the allelic directions were opposite. qTGW2 was located in Tw35293−RM266 and affected TGW, GL and GW with the same allelic direction. Finally, qTGW2 was delimited within a 103-kb region flanked by Tw35293 and Tw35395. Conclusion qTGW2 with significant effects on TGW, GL and GW was validated and fine-mapped using NIL and NIL-F2 populations. These results provide a basis for map-based cloning of qTGW2 and utilization of qTGW2 in the breeding of high-yielding rice varieties.

scholarly journals Physical Characterisation of Brown and White Fractions of Approved Rice Varieties of Pakistan

2019 ◽  
Vol 62 (3) ◽  
pp. 139-147
Author(s):  
Rebia Ejaz ◽  
Mian Kamran Sharifa ◽  
Imran Pasha ◽  
Muhammad Anjum Zia
Keyword(s):  
Grain Size ◽  
Bulk Density ◽  
Brown Rice ◽  
Kernel Weight ◽  
Width Ratio ◽  
Rice Varieties ◽  
Mean Values ◽  
White Rice ◽  
Foreign Earnings ◽  
Grain Width

 This study was carried out to assess the quality attributes of rice varieties named as Super Kernel, Super Basmati, Basmati-515, PK-386, Kainat and IRRI-9 after milling for the establishment of claimed standards for approved varieties to prohibit rice adulteration. Furthermore, brown and white fractions of selected varieties were evaluated for physical characteristics including grain size (grain length/grain width ratio) thousand kernel weight (TKW) and bulk density. Mean values for grain size (L/W ratio), bulk density and TKW were ranged from 3.86±0.30 to 4.59±0.32, 0.71±0.08 to 0.80±0.10g/mL and 16.74±1.18 to 17.96±0.85g among the rice cultivars. Overall, grain size (4.00±0.21 to 4.48±0.35 and 4.14±0.43 to 4.81±0.37), bulk density (0.66±0.05 to 0.72±0.09g/mL and 0.77±0.05 to 0.82±0.27g/mL) and TKW  (18.00±0.48 to 19.22±0.35g and 15.91±0.84 to 16.78±0.32g) varied significantly in brown and white rice samples. The lowest decrease in length after milling was seen in white rice of Kainat (8.90%) followed by PK-386 (9.86%) and Basmati-515 (10.70%), while the IRRI-9 showed highest decrease (11.84%) as compare to brown rice. Likewise, lowest increase in width was observed in IRRI-9 (10.27%) as compared to Kainat (19.87%) which indicates that IRRI-9 had more width. Conclusively, grain dimensions, kernel weight and bulk density of both brown and white rice fractions were significantly influenced by genetic, environmental and socio-economic factors among locations and cultivars. There is an urgent need to discriminate among premium and local rice varieties of country to boost up the export and foreign earnings.  

scholarly journals Novel High-Throughput Screening Method for Identification of Fungal Dimorphism Blockers

2014 ◽  
Vol 20 (2) ◽  
pp. 285-291 ◽  
Author(s):  
Marios Stylianou ◽  
Hanna Uvell ◽  
José Pedro Lopes ◽  
Per-Anders Enquist ◽  
Mikael Elofsson ◽  
...  
Keyword(s):  
Image Analysis ◽  
High Throughput ◽  
High Throughput Screening ◽  
Screening Method ◽  
Antifungal Drugs ◽  
Width Ratio ◽  
High Morbidity ◽  
Candida Spp ◽  
New Approach ◽  
Length Width

Invasive mycoses have been increasing worldwide, with Candida spp. being the most prevalent fungal pathogen causing high morbidity and mortality in immunocompromised individuals. Only few antimycotics exist, often with severe side effects. Therefore, new antifungal drugs are urgently needed. Because the identification of antifungal compounds depends on fast and reliable assays, we present a new approach based on high-throughput image analysis to define cell morphology. Candida albicans and other fungi of the Candida clade switch between different growth morphologies, from budding yeast to filamentous hyphae. Yeasts are considered proliferative, whereas hyphae are required for invasion and dissemination. Thus, morphotype switching in many Candida spp. is connected to virulence and pathogenesis. It is, consequently, reasonable to presume that morphotype blockers interfere with the virulence, thereby preventing hazardous colonization. Our method efficiently differentiates yeast from hyphal cells using a combination of automated microscopy and image analysis. We selected the parameters length/width ratio and mean object shape to quantitatively discriminate yeasts and hyphae. Notably, Z′ factor calculations for these parameters confirmed the suitability of our method for high-throughput screening. As a second stage, we determined cell viability to discriminate morphotype-switching inhibitors from those that are fungicidal. Thus, our method serves as a basis for the identification of candidates for next-generation antimycotics.

scholarly journals Maize-IAS: a maize image analysis software using deep learning for high-throughput plant phenotyping

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Shuo Zhou ◽  
Xiujuan Chai ◽  
Zixuan Yang ◽  
Hongwu Wang ◽  
Chenxue Yang ◽  
...  
Keyword(s):  
Computer Vision ◽  
Image Analysis ◽  
Deep Learning ◽  
High Throughput ◽  
Batch Processing ◽  
Plant Phenotyping ◽  
Plant Science ◽  
Analysis Software ◽  
Image Analysis Software ◽  
Maize Growth

Abstract Background Maize (Zea mays L.) is one of the most important food sources in the world and has been one of the main targets of plant genetics and phenotypic research for centuries. Observation and analysis of various morphological phenotypic traits during maize growth are essential for genetic and breeding study. The generally huge number of samples produce an enormous amount of high-resolution image data. While high throughput plant phenotyping platforms are increasingly used in maize breeding trials, there is a reasonable need for software tools that can automatically identify visual phenotypic features of maize plants and implement batch processing on image datasets. Results On the boundary between computer vision and plant science, we utilize advanced deep learning methods based on convolutional neural networks to empower the workflow of maize phenotyping analysis. This paper presents Maize-IAS (Maize Image Analysis Software), an integrated application supporting one-click analysis of maize phenotype, embedding multiple functions: (I) Projection, (II) Color Analysis, (III) Internode length, (IV) Height, (V) Stem Diameter and (VI) Leaves Counting. Taking the RGB image of maize as input, the software provides a user-friendly graphical interaction interface and rapid calculation of multiple important phenotypic characteristics, including leaf sheath points detection and leaves segmentation. In function Leaves Counting, the mean and standard deviation of difference between prediction and ground truth are 1.60 and 1.625. Conclusion The Maize-IAS is easy-to-use and demands neither professional knowledge of computer vision nor deep learning. All functions for batch processing are incorporated, enabling automated and labor-reduced tasks of recording, measurement and quantitative analysis of maize growth traits on a large dataset. We prove the efficiency and potential capability of our techniques and software to image-based plant research, which also demonstrates the feasibility and capability of AI technology implemented in agriculture and plant science.

scholarly journals Genotypic Variation in Nutrient Uptake Requirements of Rice Using the QUEFTS Model

Agronomy ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 26
Author(s):  
Tao Sun ◽  
Xin Yang ◽  
Sheng Tang ◽  
Kefeng Han ◽  
Ping He ◽  
...  
Keyword(s):  
Nutrient Uptake ◽  
Field Experiments ◽  
Hybrid Rice ◽  
Genotypic Variation ◽  
Tropical Soils ◽  
Study Data ◽  
Japonica Rice ◽  
Rice Varieties ◽  
Indica Hybrid Rice ◽  
Validation Experiments

Nutrient requirements for single-season rice using the quantitative evaluation of the fertility of tropical soils (QUEFTS) model in China have been estimated in a previous study, which involved all the rice varieties; however, it is unclear whether a similar result can be obtained for different rice varieties. In this study, data were collected from field experiments conducted from 2016 to 2019 in Zhejiang Province, China. The dataset was separated into two parts: japonica/indica hybrid rice and japonica rice. To produce 1000 kg of grain, 13.5 kg N, 3.6 kg P, and 20.4 kg K were required in the above-ground plant dry matter for japonica/indica hybrid rice, and the corresponding internal efficiencies (IEs) were 74.0 kg grain per kg N, 279.1 kg grain per kg P, and 49.1 kg grain per kg K. For japonica rice, 17.6 kg N, 4.1 kg P, and 23.0 kg K were required to produce 1000 kg of grain, and the corresponding IEs were 56.8 kg grain per kg N, 244.6 kg grain per kg P, and 43.5 kg grain per kg K. Field validation experiments indicated that the QUEFTS model could be used to estimate nutrient uptake of different rice varieties. We suggest that variety should be taken into consideration when estimating nutrient uptake for rice using the QUEFTS model, which would improve this model.

scholarly journals Grain Size Selection Using Novel Functional Markers Targeting 14 Genes in Rice

Rice ◽  
2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Lin Zhang ◽  
Bin Ma ◽  
Zhong Bian ◽  
Xiaoyuan Li ◽  
Changquan Zhang ◽  
...  
Keyword(s):  
Grain Size ◽  
Grain Yield ◽  
Rational Design ◽  
Width Ratio ◽  
Functional Markers ◽  
Rice Breeding ◽  
Nucleotide Polymorphisms ◽  
Yield And Quality ◽  
Grain Width ◽  
Grain Yield And Quality

Abstract Background Grain size is an extremely important aspect of rice breeding, affecting both grain yield and quality traits. It is controlled by multiple genes and tracking these genes in breeding schemes should expedite selection of lines with superior grain yield and quality, thus it is essential to develop robust, efficient markers. Result In this study, 14 genes related to grain size (GW2, GS2, qLGY3, GS3, GL3.1, TGW3, GS5, GW5, GS6, TGW6, GW6a, GLW7, GL7 and GW8) were selected for functional marker development. Twenty-one PCR-gel-based markers were developed to genotype the candidate functional nucleotide polymorphisms (FNPs) of these genes, and all markers can effectively recognize the corresponding allele types. To test the allele effects of different FNPs, a global collection of rice cultivars including 257 accessions from the Rice Diversity Panel 1 was used for allele mining, and four grain-size-related traits were investigated at two planting locations. Three FNPs for GW2, GS2 and GL3.1 were genotyped as rare alleles only found in cultivars with notably large grains, and the allele contributions of the remaining FNPs were clarified in both the indica and japonica subspecies. Significant trait contributions were found for most of the FNPs, especially GS3, GW5 and GL7. Of note, GW5 could function as a key regulator to coordinate the performance of other grain size genes. The allele effects of several FNPs were also tested by QTL analysis using an F2 population, and GW5 was further identified as the major locus with the largest contribution to grain width and length to width ratio. Conclusions The functional markers are robust for genotyping different cultivars and may facilitate the rational design of grain size to achieve a balance between grain yield and quality in future rice breeding efforts.

REACTION OF RICE VARIETIES PERMITED FOR USE IN CONNECTION WITH YIELD FORMATION WITH A HIGH GRAIN QUALITY ON LEVEL OF NITROGEN NUTRITION IN AGROLANDSCAPE ZONES OF KRASNODAR REGION

2020 ◽  
Author(s):  
N.G. Tumanian ◽  
Keyword(s):  
Grain Size ◽  
Grain Quality ◽  
Nitrogen Nutrition ◽  
Nitrogen Fertilizers ◽  
Quality Traits ◽  
Rice Varieties ◽  
Head Rice ◽  
Krasnodar Region ◽  
Yield Formation ◽  
Applied Nitrogen

An increase in the doses of nitrogen fertilizers applied during the cultivation of new rice varieties Nautilus and Yakhont in the old-deltoid and valley agrolandscape zones led to significant changes in grain quality traits. The grain size of the varieties grown in the Krasnoarsmeysky district did not change due to the level of nitrogen fertilizers, for those grown in the Abinsky district, decreased by 0.3 g in variety Nautilus and increased in variety Yakhont with increased dose of applied nitrogen. The vitreousity of grain increased in Nautilus in the Krasnoarmeysky district by 2%, in Abinsky - by 7%; in the variety Yakhont - increased by 2% and practically did not change, respectively. A tendency toward a decrease in grain fracture in the Krasnoarmeysky district and an increase in head rice content in the variety Nautilus in the Krasnoarmeysky and Abinsky districts was noted.

scholarly journals GRAIN LENGTH AND AWN 1 negatively regulates grain size in rice

2019 ◽  
Vol 61 (10) ◽  
pp. 1036-1042 ◽  
Author(s):  
Tao Wang ◽  
Ting Zou ◽  
Zhiyuan He ◽  
Guoqiang Yuan ◽  
Tao Luo ◽  
...  
Keyword(s):  
Grain Size ◽  
Grain Length
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