Browsing by Author "Yu, Hongfeng"
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- Allelic variation in rice Fertilization Independent Endosperm 1 contributes to grain width under high night temperature stressDhatt, Balpreet K.; Paul, Puneet; Sandhu, Jaspreet; Hussain, Waseem; Irvin, Larissa; Zhu, Feiyu; Adviento-Borbe, Maria Arlene; Lorence, Argelia; Staswick, Paul; Yu, Hongfeng; Morota, Gota; Walia, Harkamal (2020-10)A higher minimum (night-time) temperature is considered a greater limiting factor for reduced rice yield than a similar increase in maximum (daytime) temperature. While the physiological impact of high night temperature (HNT) has been studied, the genetic and molecular basis of HNT stress response remains unexplored. We examined the phenotypic variation for mature grain size (length and width) in a diverse set of rice accessions under HNT stress. Genome-wide association analysis identified several HNT-specific loci regulating grain size as well as loci that are common for optimal and HNT stress conditions. A novel locus contributing to grain width under HNT conditions colocalized withFie1, a component of the FIS-PRC2 complex. Our results suggest that the allelic difference controlling grain width under HNT is a result of differential transcript-level response ofFie1in grains developing under HNT stress. We present evidence to support the role ofFie1in grain size regulation by testing overexpression (OE) and knockout mutants under heat stress. The OE mutants were either unaltered or had a positive impact on mature grain size under HNT, while the knockouts exhibited significant grain size reduction under these conditions.
- Rice Chalky Grain 5 regulates natural variation for grain quality under heat stressChandran, Anil Kumar Nalini; Sandhu, Jaspreet; Irvin, Larissa; Paul, Puneet; Dhatt, Balpreet K.; Hussain, Waseem; Gao, Tian; Staswick, Paul; Yu, Hongfeng; Morota, Gota; Walia, Harkamal (Frontiers, 2022-10)Heat stress occurring during rice (Oryza sativa) grain development reduces grain quality, which often manifests as increased grain chalkiness. Although the impact of heat stress on grain yield is well-studied, the genetic basis of rice grain quality under heat stress is less explored as quantifying grain quality is less tractable than grain yield. To address this, we used an image-based colorimetric assay (Red, R; and Green, G) for genome-wide association analysis to identify genetic loci underlying the phenotypic variation in rice grains exposed to heat stress. We found the R to G pixel ratio (RG) derived from mature grain images to be effective in distinguishing chalky grains from translucent grains derived from control (28/24 degrees C) and heat stressed (36/32 degrees C) plants. Our analysis yielded a novel gene, rice Chalky Grain 5 (OsCG5) that regulates natural variation for grain chalkiness under heat stress. OsCG5 encodes a grain-specific, expressed protein of unknown function. Accessions with lower transcript abundance of OsCG5 exhibit higher chalkiness, which correlates with higher RG values under stress. These findings are supported by increased chalkiness of OsCG5 knock-out (KO) mutants relative to wildtype (WT) under heat stress. Grains from plants overexpressing OsCG5 are less chalky than KOs but comparable to WT under heat stress. Compared to WT and OE, KO mutants exhibit greater heat sensitivity for grain size and weight relative to controls. Collectively, these results show that the natural variation at OsCG5 may contribute towards rice grain quality under heat stress.
- SeedExtractor: An Open-Source GUI for Seed Image AnalysisZhu, Feiyu; Paul, Puneet; Hussain, Waseem; Wallman, Kyle; Dhatt, Balpreet K.; Sandhu, Jaspreet; Irvin, Larissa; Morota, Gota; Yu, Hongfeng; Walia, Harkamal (2021-02-01)Accurate measurement of seed size parameters is essential for both breeding efforts aimed at enhancing yields and basic research focused on discovering genetic components that regulate seed size. To address this need, we have developed an open-source graphical user interface (GUI) software, SeedExtractor that determines seed size and shape (including area, perimeter, length, width, circularity, and centroid), and seed color with capability to process a large number of images in a time-efficient manner. In this context, our application takes similar to 2 s for analyzing an image, i.e., significantly less compared to the other tools. As this software is open-source, it can be modified by users to serve more specific needs. The adaptability of SeedExtractor was demonstrated by analyzing scanned seeds from multiple crops. We further validated the utility of this application by analyzing mature-rice seeds from 231 accessions in Rice Diversity Panel 1. The derived seed-size traits, such as seed length, width, were used for genome-wide association analysis. We identified known loci for regulating seed length (GS3) and width (qSW5/GW5) in rice, which demonstrates the accuracy of this application to extract seed phenotypes and accelerate trait discovery. In summary, we present a publicly available application that can be used to determine key yield-related traits in crops.