Sorghum MSD3 Encodes an ω-3 Fatty Acid Desaturase that Increases Grain Number by Reducing Jasmonic Acid Levels

Dampanaboina, Lavanya; Jiao, Yinping; Chen, Junping; Gladman, Nicholas; Chopra, Ratan; Burow, Gloria; Hayes, Chad; Christensen, Shawn A.; Burke, John J.; Ware, Doreen; Xin, Zhanguo

doi:10.3390/ijms20215359

Cited by 29 publications

(22 citation statements)

References 48 publications

(92 reference statements)

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“…This led to the identification of the correct causal mutations in each case, as shown in Fig. S3 (ms9 (J. Chen et al, 2019)), S4 (msd1 (Jiao, Lee, et al, 2018)), S5 (bm40 (Jiao, Burow, et al, 2018)), and S6 (msd3 (Dampanaboina et al, 2019)). The results are summarized in Table 1.…”

Section: Resultsmentioning

confidence: 99%

BSAseq: an interactive and integrated web-based workflow for identification of causal mutations in bulked F2 populations

Wang¹

2020

Preprint

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With the advance of next-generation sequencing (NGS) technologies and reductions in the costs of these techniques, bulked segregant analysis (BSA) has become not only a powerful tool for mapping quantitative trait loci (QTL) but also a useful way to identify causal gene mutations underlying phenotypes of interest. However, due to the presence of background mutations and errors in sequencing, genotyping, and reference assembly, it is often difficult to distinguish true causal mutations from background mutations. In this study, we developed the BSAseq workflow, which includes an automated bioinformatics analysis pipeline with a probabilistic model for estimating the segregation region and an interactive Shiny web application for visualizing the results. We deeply sequenced a male sterile parental line (ms8) to capture the majority of background mutations in our bulked F2 data. We applied the workflow to 11 bulked F2 populations and identified the true causal mutation in each population. The workflow is intuitive and straightforward, facilitating its adoption by users without bioinformatics analysis skills. We anticipate that BSAseq will be broadly applicable to the identification of causal mutations for many phenotypes of interest.

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Section: Resultsmentioning

confidence: 99%

BSAseq: an interactive and integrated web-based workflow for identification of causal mutations in bulked F2 populations

Wang¹

2020

Preprint

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“…S3 (ms9 (J. ), S4 (msd1 (Jiao, Lee, et al, 2018)), S5 (bm40 (Jiao, Burow, et al, 2018)), and S6 (msd3 (Dampanaboina et al, 2019)). The results are summarized in Table 1.…”

Section: Resultsmentioning

confidence: 99%

“…By coupling BSA with NGS, we identified the functions of several recessive sorghum genes using bulked F2 pools derived by backcrossing EMS mutants with a wild-type BTx623 founder line (BTx623¢). These genes include msd1 (Jiao, Lee, et al, 2018), bm40 (Jiao, Burow, et al, 2018), msd3 (Dampanaboina et al, 2019), and ms9 (J. . To filter out false-positive candidates, the causal genes were usually identified using more than one EMS mutant.…”

Section: Introductionmentioning

confidence: 99%

BSAseq: an interactive and integrated web-based workflow for identification of causal mutations in bulked F2 populations

Wang

Regulski

et al. 2020

Bioinformatics

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Summary With the advance of next-generation sequencing (NGS) technologies and reductions in the costs of these techniques, bulked segregant analysis (BSA) has become not only a powerful tool for mapping quantitative trait loci (QTL) but also a useful way to identify causal gene mutations underlying phenotypes of interest. However, due to the presence of background mutations and errors in sequencing, genotyping, and reference assembly, it is often difficult to distinguish true causal mutations from background mutations. In this study, we developed the BSAseq workflow, which includes an automated bioinformatics analysis pipeline with a probabilistic model for estimating the linked region (the region linked to the causal mutation) and an interactive Shiny web application for visualizing the results. We deeply sequenced a sorghum male-sterile parental line (ms8) to capture the majority of background mutations in our bulked F2 data. We applied the workflow to 11 bulked sorghum F2 populations and 1 rice F2 population and identified the true causal mutation in each population. The workflow is intuitive and straightforward, facilitating its adoption by users without bioinformatics analysis skills. We anticipate that the BSAseq workflow will be broadly applicable to the identification of causal mutations for many phenotypes of interest. Availability BSAseq is freely available on https://www.sciapps.org/page/bsa Supplementary information Supplementary data are available at Bioinformatics online.

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“…Three genes, MSD1 , MSD2 and MSD3 have been found to be involved in inflorescence development. They encode a plant-specific transcription factor with a TCP domain, a lipoxygenase, and an ω-3 fatty acid desaturase that catalyses the conversion of linoleic acid (18:2) to linolenic acid (18:3), respectively (Jiao et al 2018 ; Dampanaboina et al 2019 ; Gladman et al 2019 ). MSD1 can bind to the upstream sequences of the transcriptional start site of itself and MSD2 to control the expression.…”

Section: Genomic Research In Sorghummentioning

confidence: 99%

Sorghum breeding in the genomic era: opportunities and challenges

Hao

Leng

et al. 2021

Theor Appl Genet

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Key message The importance and potential of the multi-purpose crop sorghum in global food security have not yet been fully exploited, and the integration of the state-of-art genomics and high-throughput technologies into breeding practice is required. Abstract Sorghum, a historically vital staple food source and currently the fifth most important major cereal, is emerging as a crop with diverse end-uses as food, feed, fuel and forage and a model for functional genetics and genomics of tropical grasses. Rapid development in high-throughput experimental and data processing technologies has significantly speeded up sorghum genomic researches in the past few years. The genomes of three sorghum lines are available, thousands of genetic stocks accessible and various genetic populations, including NAM, MAGIC, and mutagenised populations released. Functional and comparative genomics have elucidated key genetic loci and genes controlling agronomical and adaptive traits. However, the knowledge gained has far away from being translated into real breeding practices. We argue that the way forward is to take a genome-based approach for tailored designing of sorghum as a multi-functional crop combining excellent agricultural traits for various end uses. In this review, we update the new concepts and innovation systems in crop breeding and summarise recent advances in sorghum genomic researches, especially the genome-wide dissection of variations in genes and alleles for agronomically important traits. Future directions and opportunities for sorghum breeding are highlighted to stimulate discussion amongst sorghum academic and industrial communities.

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Sorghum MSD3 Encodes an ω-3 Fatty Acid Desaturase that Increases Grain Number by Reducing Jasmonic Acid Levels

Cited by 29 publications

References 48 publications

BSAseq: an interactive and integrated web-based workflow for identification of causal mutations in bulked F2 populations

BSAseq: an interactive and integrated web-based workflow for identification of causal mutations in bulked F2 populations

BSAseq: an interactive and integrated web-based workflow for identification of causal mutations in bulked F2 populations

Sorghum breeding in the genomic era: opportunities and challenges

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