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Kumari A, Sharma P, Rani M, Laxmi V, Sahil, Sahi C, Satturu V, Katiyar-Agarwal S, Agarwal M. Meta-QTL and ortho analysis unravels the genetic architecture and key candidate genes for cold tolerance at seedling stage in rice. PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2024; 30:93-108. [PMID: 38435852 PMCID: PMC10902255 DOI: 10.1007/s12298-024-01412-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 12/13/2023] [Accepted: 01/10/2024] [Indexed: 03/05/2024]
Abstract
Rice, a critical cereal crop, grapples with productivity challenges due to its inherent sensitivity to low temperatures, primarily during the seedling and booting stages. Recognizing the polygenic complexity of cold stress signaling in rice, a meta-analysis was undertaken, focusing on 20 physiological traits integral to cold tolerance. This initiative allowed the consolidation of genetic data from 242 QTLs into 58 meta-QTLs, thereby significantly constricting the genetic and physical intervals, with 84% of meta-QTLs (MQTLs) being reduced to less than 2 Mb. The list of 10,505 genes within these MQTLs, was further refined utilizing expression datasets to pinpoint 46 pivotal genes exhibiting noteworthy differential regulation during cold stress. The study underscored the presence of several TFs such as WRKY, NAC, CBF/DREB, MYB, and bHLH, known for their roles in cold stress response. Further, ortho-analysis involving maize, barley, and Arabidopsis identified OsWRKY71, among others, as a prospective candidate for enhancing cold tolerance in diverse crop plants. In conclusion, our study delineates the intricate genetic architecture underpinning cold tolerance in rice and propounds significant candidate genes, offering crucial insights for further research and breeding strategies focused on fortifying crops against cold stress, thereby bolstering global food resilience. Supplementary Information The online version contains supplementary material available at 10.1007/s12298-024-01412-1.
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Affiliation(s)
- Anita Kumari
- Department of Botany, University of Delhi, Delhi, India
| | - Priya Sharma
- Department of Botany, University of Delhi, Delhi, India
| | - Mamta Rani
- Department of Botany, University of Delhi, Delhi, India
| | - Vijay Laxmi
- Department of Botany, University of Delhi, Delhi, India
| | - Sahil
- Department of Botany, University of Delhi, Delhi, India
| | - Chandan Sahi
- Department of Biological Sciences, Indian Institute of Science Education and Research, Bhopal, Madhya Pradesh 462066 India
| | - Vanisree Satturu
- Professor Jayashankar, Telangana State Agricultural University, Hyderabad, India
| | | | - Manu Agarwal
- Department of Botany, University of Delhi, Delhi, India
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Zhou Y, Zhang H, Zhang S, Zhang J, Di H, Zhang L, Dong L, Lu Q, Zeng X, Liu X, Zhang N, Wang Z. The G protein-coupled receptor COLD1 promotes chilling tolerance in maize during germination. Int J Biol Macromol 2023; 253:126877. [PMID: 37716664 DOI: 10.1016/j.ijbiomac.2023.126877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 09/09/2023] [Accepted: 09/10/2023] [Indexed: 09/18/2023]
Abstract
The geographic range and yield of the staple crop maize (Zea mays L.) are both strongly limited by low-temperature conditions. One of the most economical and effective measures for improvement of maize production is chilling tolerance enhancement. In this study, a chilling-tolerance gene in maize, ZmCOLD1, was cloned and characterized. This gene encodes a G protein-coupled receptor that is localized to the plasma membrane and the endoplasmic reticulum. A single nucleotide polymorphism (SNP) in ZmCOLD1, SNP2738, was found to confer chilling tolerance and to have promoted maize adaptations during speciation from teosinte. Overexpression of the excellent haplotype ZmCOLD1Hap11 significantly enhanced chilling tolerance, whereas knocking down ZmCOLD1 increased sensitivity to low temperatures during the germination and seedling stages. ZmCOLD1 was associated with an influx of extracellular Ca2+, increases in abscisic acid content, and decreases in gibberellic acid and indole-3-acetic acid content under low temperatures during the germination stage. ZmCOLD1 interacted with the G protein α subunit ZmCT2 at the plasma membrane, and ZmCT2 interacted with ZmLanCL in the nucleus. These proteins are components of the chilling tolerance signaling pathway in maize that are triggered by abscisic acid and photosynthesis. These results offer novel strategies for improvement of chilling tolerance in key crop species.
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Affiliation(s)
- Yu Zhou
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Engineering Technology Research Center of Maize Germplasm Resources Innovation on Cold land of Heilongjiang Province, Northeast Agricultural University, Harbin, Heilongjiang 150030, China.
| | - Hong Zhang
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Engineering Technology Research Center of Maize Germplasm Resources Innovation on Cold land of Heilongjiang Province, Northeast Agricultural University, Harbin, Heilongjiang 150030, China
| | - Simeng Zhang
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Engineering Technology Research Center of Maize Germplasm Resources Innovation on Cold land of Heilongjiang Province, Northeast Agricultural University, Harbin, Heilongjiang 150030, China
| | - Jiayue Zhang
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Engineering Technology Research Center of Maize Germplasm Resources Innovation on Cold land of Heilongjiang Province, Northeast Agricultural University, Harbin, Heilongjiang 150030, China
| | - Hong Di
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Engineering Technology Research Center of Maize Germplasm Resources Innovation on Cold land of Heilongjiang Province, Northeast Agricultural University, Harbin, Heilongjiang 150030, China
| | - Lin Zhang
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Engineering Technology Research Center of Maize Germplasm Resources Innovation on Cold land of Heilongjiang Province, Northeast Agricultural University, Harbin, Heilongjiang 150030, China
| | - Ling Dong
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Engineering Technology Research Center of Maize Germplasm Resources Innovation on Cold land of Heilongjiang Province, Northeast Agricultural University, Harbin, Heilongjiang 150030, China
| | - Qing Lu
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Engineering Technology Research Center of Maize Germplasm Resources Innovation on Cold land of Heilongjiang Province, Northeast Agricultural University, Harbin, Heilongjiang 150030, China
| | - Xing Zeng
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Engineering Technology Research Center of Maize Germplasm Resources Innovation on Cold land of Heilongjiang Province, Northeast Agricultural University, Harbin, Heilongjiang 150030, China
| | - Xianjun Liu
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Engineering Technology Research Center of Maize Germplasm Resources Innovation on Cold land of Heilongjiang Province, Northeast Agricultural University, Harbin, Heilongjiang 150030, China
| | - Naifu Zhang
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Engineering Technology Research Center of Maize Germplasm Resources Innovation on Cold land of Heilongjiang Province, Northeast Agricultural University, Harbin, Heilongjiang 150030, China
| | - Zhenhua Wang
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Engineering Technology Research Center of Maize Germplasm Resources Innovation on Cold land of Heilongjiang Province, Northeast Agricultural University, Harbin, Heilongjiang 150030, China.
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3
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Padmashree R, Barbadikar KM, Honnappa, Magar ND, Balakrishnan D, Lokesha R, Gireesh C, Siddaiah AM, Madhav MS, Ramesha YM, Bharamappanavara M, Phule AS, Senguttuvel P, Diwan JR, Subrahmanyam D, Sundaram RM. Genome-wide association studies in rice germplasm reveal significant genomic regions for root and yield-related traits under aerobic and irrigated conditions. FRONTIERS IN PLANT SCIENCE 2023; 14:1143853. [PMID: 37538056 PMCID: PMC10395336 DOI: 10.3389/fpls.2023.1143853] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 04/19/2023] [Indexed: 08/05/2023]
Abstract
The development of nutrient-use efficient rice lines is a priority amidst the changing climate and depleting resources viz., water, land, and labor for achieving sustainability in rice cultivation. Along with the traditional transplanted irrigated system of cultivation, the dry direct-seeded aerobic system is gaining ground nationwide. The root-related traits play a crucial role in nutrient acquisition, adaptation and need to be concentrated along with the yield-attributing traits. We phenotyped an association panel of 118 rice lines for seedling vigour index (SVI) traits at 14 and 21 days after sowing (DAS), root-related traits at panicle initiation (PI) stage in polythene bags under controlled aerobic condition, yield and yield-related traits under the irrigated condition at ICAR-IIRR, Hyderabad, Telangana; irrigated and aerobic conditions at ARS, Dhadesugur, Raichur, Karnataka. The panel was genotyped using simple sequence repeats (SSR) markers and genome-wide association studies were conducted for identifying marker-trait associations (MTAs). Significant correlations were recorded for root length, root dry weight with SVI, root volume at the PI stage, number of productive tillers per plant, spikelet fertility, the total number of grains per panicle with grain yield per plant under irrigated conditions, and the total number of grains per panicle with grain yield per plant under aerobic condition. The panel was divided into three sub-groups (K = 3) and correlated with the principal component analysis. The maximum number of MTAs were found on chromosomes 2, 3, and 12 with considerable phenotypic variability. Consistent MTAs were recorded for SVI traits at 14 and 21 DAS (RM25310, RM80, RM22961, RM1385), yield traits under irrigated conditions (RM2584, RM5179, RM410, RM20698, RM14753) across years at ICAR-IIRR, grain yield per plant (RM22961, RM1146) under the aerobic condition, grain yield per plant at irrigated ICAR-IIRR and SVI (RM5501), root traits at PI stage (RM2584, RM80, RM410, RM1146, RM18472). Functionally relevant genes near the MTAs through in-silico expression analysis in root and panicle tissues viz., HBF2 bZIP transcription factor, WD40 repeat-like domain, OsPILS6a auxin efflux carrier, WRKY108, OsSCP42, OsMADS80, nodulin-like domain-containing protein, amino acid transporter using various rice expression databases were identified. The identified MTAs and rice lines having high SVI traits (Langphou, TI-128, Mouli, TI-124, JBB-631-1), high yield under aerobic (Phouren, NPK-43, JBB-684, Ratnamudi, TI-112), irrigated conditions (KR-209, KR-262, Phouren, Keibi-Phou, TI-17), robust root traits like root length (MoirangPhou-Angouba, Wangoo-Phou, JBB-661, Dissi, NPK-45), root volume (Ratnachudi, KJ-221, Mow, Heimang-Phou, PUP-229) can be further employed in breeding programs for the targeted environments aimed at improving seedling vigour, yield-related traits under irrigated condition, aerobic condition as adaptability to water-saving technology.
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Affiliation(s)
- Revadi Padmashree
- Indian Council of Agricultural Research (ICAR)-Indian Institute of Rice Research (IIRR), Hyderabad, India
- University of Agricultural Sciences (UAS), Raichur, India
| | - Kalyani M. Barbadikar
- Indian Council of Agricultural Research (ICAR)-Indian Institute of Rice Research (IIRR), Hyderabad, India
| | - Honnappa
- Indian Council of Agricultural Research (ICAR)-Indian Institute of Rice Research (IIRR), Hyderabad, India
- University of Agricultural Sciences (UAS), Raichur, India
| | - Nakul D. Magar
- Indian Council of Agricultural Research (ICAR)-Indian Institute of Rice Research (IIRR), Hyderabad, India
- Chaudhary Charan Singh University, Meerut, India
| | - Divya Balakrishnan
- Indian Council of Agricultural Research (ICAR)-Indian Institute of Rice Research (IIRR), Hyderabad, India
| | - R. Lokesha
- University of Agricultural Sciences (UAS), Raichur, India
| | - C. Gireesh
- Indian Council of Agricultural Research (ICAR)-Indian Institute of Rice Research (IIRR), Hyderabad, India
| | - Anantha M. Siddaiah
- Indian Council of Agricultural Research (ICAR)-Indian Institute of Rice Research (IIRR), Hyderabad, India
| | - Maganti Sheshu Madhav
- Indian Council of Agricultural Research (ICAR)-Indian Institute of Rice Research (IIRR), Hyderabad, India
| | - Y. M Ramesha
- Agricultural Research Station (ARS) Dhadesugur, University of Agricultural Sciences (UAS), Raichur, India
| | | | - Amol S. Phule
- Indian Council of Agricultural Research (ICAR)-Indian Institute of Rice Research (IIRR), Hyderabad, India
| | - P. Senguttuvel
- Indian Council of Agricultural Research (ICAR)-Indian Institute of Rice Research (IIRR), Hyderabad, India
| | - J. R. Diwan
- University of Agricultural Sciences (UAS), Raichur, India
| | - D. Subrahmanyam
- Indian Council of Agricultural Research (ICAR)-Indian Institute of Rice Research (IIRR), Hyderabad, India
| | - Raman Menakshi Sundaram
- Indian Council of Agricultural Research (ICAR)-Indian Institute of Rice Research (IIRR), Hyderabad, India
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4
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Yan T, Sun M, Su R, Wang X, Lu X, Xiao Y, Deng H, Liu X, Tang W, Zhang G. Transcriptomic Profiling of Cold Stress-Induced Differentially Expressed Genes in Seedling Stage of Indica Rice. PLANTS (BASEL, SWITZERLAND) 2023; 12:2675. [PMID: 37514289 PMCID: PMC10384097 DOI: 10.3390/plants12142675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 07/15/2023] [Accepted: 07/15/2023] [Indexed: 07/30/2023]
Abstract
Cold stress significantly constrains the growth, development, productivity, and distribution of rice, particularly the indica cultivar, known for its susceptibility to cold, limiting its cultivation to specific regions. This study investigated the genes associated with cold responsiveness in the roots of two indica cultivars, SQSL (cold-tolerant) and XZX45 (cold-susceptible), through transcriptome dynamics analysis during the seedling stage. The analysis identified 8144 and 6427 differentially expressed genes (DEGs) in XZX45 and SQSL, respectively. Among these DEGs, 4672 (G2) were shared by both cultivars, while 3472 DEGs (G1) were specific to XZX45, and 1755 DEGs (G3) were specific to SQSL. Additionally, 572 differentially expressed transcription factors (TFs) from 48 TF families, including WRKY, NAC, bHLH, ERF, bZIP, MYB, C2H2, and GRAS, were identified. Gene Ontology (GO) enrichment analysis revealed significant enrichment of DEGs in the G3 group, particularly in the "response to cold" category, highlighting the crucial role of these specific genes in response to cold stress in SQSL. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated pronounced enrichment of DEGs in the G3 group in metabolic pathways such as "Pyruvate metabolism", "Glycolysis/Gluconeogenesis", and "Starch and sucrose metabolism", contributing to cold tolerance mechanisms in SQSL. Overall, this study provides comprehensive insights into the molecular mechanisms underlying cold responses in the indica cultivar, informing future genetic improvement strategies to enhance cold tolerance in susceptible indica rice cultivars.
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Affiliation(s)
- Tao Yan
- College of Agronomy, Hunan Agricultural University, Changsha 410128, China
- Hunan Provincial Key Laboratory of Rice and Rapeseed Breeding for Disease Resistance, Changsha 410128, China
| | - Meng Sun
- College of Agronomy, Hunan Agricultural University, Changsha 410128, China
- Hunan Provincial Key Laboratory of Rice and Rapeseed Breeding for Disease Resistance, Changsha 410128, China
| | - Rui Su
- College of Agronomy, Hunan Agricultural University, Changsha 410128, China
- Hunan Provincial Key Laboratory of Rice and Rapeseed Breeding for Disease Resistance, Changsha 410128, China
| | - Xiaozhong Wang
- College of Agronomy, Hunan Agricultural University, Changsha 410128, China
- Hunan Provincial Key Laboratory of Rice and Rapeseed Breeding for Disease Resistance, Changsha 410128, China
| | - Xuedan Lu
- College of Agronomy, Hunan Agricultural University, Changsha 410128, China
- Hunan Provincial Key Laboratory of Rice and Rapeseed Breeding for Disease Resistance, Changsha 410128, China
| | - Yunhua Xiao
- College of Agronomy, Hunan Agricultural University, Changsha 410128, China
- Hunan Provincial Key Laboratory of Rice and Rapeseed Breeding for Disease Resistance, Changsha 410128, China
| | - Huabing Deng
- College of Agronomy, Hunan Agricultural University, Changsha 410128, China
- Hunan Provincial Key Laboratory of Rice and Rapeseed Breeding for Disease Resistance, Changsha 410128, China
| | - Xiong Liu
- College of Agronomy, Hunan Agricultural University, Changsha 410128, China
- Hunan Provincial Key Laboratory of Rice and Rapeseed Breeding for Disease Resistance, Changsha 410128, China
| | - Wenbang Tang
- College of Agronomy, Hunan Agricultural University, Changsha 410128, China
- Hunan Provincial Key Laboratory of Rice and Rapeseed Breeding for Disease Resistance, Changsha 410128, China
- Hunan Hybrid Rice Research Center, Hunan Academy of Agricultural Sciences, Changsha 410128, China
- State Key Laboratory of Hybrid Rice, Changsha 410128, China
| | - Guilian Zhang
- College of Agronomy, Hunan Agricultural University, Changsha 410128, China
- Hunan Provincial Key Laboratory of Rice and Rapeseed Breeding for Disease Resistance, Changsha 410128, China
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5
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Barik SR, Moharana A, Pandit E, Behera A, Mishra A, Mohanty SP, Mohapatra S, Sanghamitra P, Meher J, Pani DR, Bhadana VP, Datt S, Sahoo CR, Raj K R R, Pradhan SK. Transfer of Stress Resilient QTLs and Panicle Traits into the Rice Variety, Reeta through Classical and Marker-Assisted Breeding Approaches. Int J Mol Sci 2023; 24:10708. [PMID: 37445885 DOI: 10.3390/ijms241310708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Revised: 04/23/2023] [Accepted: 04/26/2023] [Indexed: 07/15/2023] Open
Abstract
Reeta is a popular late-maturing high-yielding rice variety recommended for cultivation in the eastern Indian states. The cultivar is highly sensitive to submergence stress. Phosphorus deficiency is an additional constraint for realizing high yield. The quantitative trait loci (QTLs), Sub1, for submergence and Pup1 for low phosphorus stress tolerance along with narrow-grained trait, GW5 were introgressed into the variety from the donor parent, Swarna-Sub1 through marker-assisted breeding. In addition, phenotypic selections for higher panicle weight, grain number, and spikelet fertility were performed in each segregating generation. Foreground selection detected the 3 target QTLs in 9, 8 and 7 progenies in the BC1F1, BC2F1, and BC3F1 generation, respectively. Recurrent parent's genome recovery was analyzed using 168 SSR polymorphic markers. The foreground analysis in 452 BC3F2 progenies showed five pyramided lines in homozygous condition for the target QTLs. No donor fragment drag was noticed in the Sub1 and GW5 QTLs carrier while a segmentwas observed in the Pup1 carrier chromosome. The developed lines were higher yielding, had submergence, and had low phosphorus stress-tolerance alongwith similar to the recipient parent in the studied morpho-quality traits. A promising pyramided line is released in the name of Reeta-Panidhan (CR Dhan 413) for the flood-prone areas of Odisha state.
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Affiliation(s)
| | - Arpita Moharana
- ICAR-National Rice Research Institute, Cuttack 753006, India
| | - Elssa Pandit
- Department of Biosciences and Biotechnology, Fakir Mohan University, Balasore 756020, India
| | | | - Ankita Mishra
- ICAR-National Rice Research Institute, Cuttack 753006, India
- College of Agriculture, Odisha University of Agriculture & Technology, Bhubaneswar 751003, India
| | | | - Shibani Mohapatra
- ICAR-National Rice Research Institute, Cuttack 753006, India
- Environmental Science Laboratory, School of Applied Sciences, KIIT Deemed to be University, Bhubaneswar 751024, India
| | | | | | - Dipti Ranjan Pani
- ICAR-National Bureau of Plant Genetic Resources, Base Center, Cuttack 753006, India
| | - Vijai Pal Bhadana
- ICAR-Indian Institute of Agricultural Biotechnology, Ranchi 834003, India
| | - Shiv Datt
- Indian Council of Agricultural Research, Krishi Bhavan, New Delhi 110001, India
| | - Chita Ranjan Sahoo
- College of Agriculture, Odisha University of Agriculture & Technology, Bhubaneswar 751003, India
| | - Reshmi Raj K R
- ICAR-National Rice Research Institute, Cuttack 753006, India
| | - Sharat Kumar Pradhan
- ICAR-National Rice Research Institute, Cuttack 753006, India
- Indian Council of Agricultural Research, Krishi Bhavan, New Delhi 110001, India
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Mohanty SP, Nayak DK, Sanghamitra P, Barik SR, Pandit E, Behera A, Pani DR, Mohapatra S, Raj K R R, Pradhan KC, Sahoo CR, Mohanty MR, Behera C, Panda AK, Jena BK, Behera L, Dash PK, Pradhan SK. Mapping the Genomic Regions Controlling Germination Rate and Early Seedling Growth Parameters in Rice. Genes (Basel) 2023; 14:genes14040902. [PMID: 37107660 PMCID: PMC10138111 DOI: 10.3390/genes14040902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 02/24/2023] [Accepted: 03/31/2023] [Indexed: 04/29/2023] Open
Abstract
Seed vigor is the key performance parameter of good quality seed. A panel was prepared by shortlisting genotypes from all the phenotypic groups representing seedling growth parameters from a total of 278 germplasm lines. A wide variation was observed for the traits in the population. The panel was classified into four genetic structure groups. Fixation indices indicated the existence of linkage disequilibrium in the population. A moderate to high level of diversity parameters was assessed using 143 SSR markers. Principal component, coordinate, neighbor-joining tree and cluster analyses showed subpopulations with a fair degree of correspondence with the growth parameters. Marker-trait association analysis detected eight novel QTLs, namely qAGR4.1, qAGR6.1, qAGR6.2 and qAGR8.1 for absolute growth rate (AGR); qRSG6.1, qRSG7.1 and qRSG8.1 for relative shoot growth (RSG); and qRGR11.1 for relative growth rate (RGR), as analyzed by GLM and MLM. The reported QTL for germination rate (GR), qGR4-1, was validated in this population. Additionally, QTLs present on chromosome 6 controlling RSG and AGR at 221 cM and RSG and AGR on chromosome 8 at 27 cM were detected as genetic hotspots for the parameters. The QTLs identified in the study will be useful for improvement of the seed vigor trait in rice.
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Affiliation(s)
| | | | | | | | - Elssa Pandit
- Department of Biosciences and Biotechnology, Fakir Mohan University, Balasore 756020, India
| | | | - Dipti Ranjan Pani
- ICAR-National Bureau of Plant Genetic Resources, Base Center, Cuttack 753006, India
| | - Shibani Mohapatra
- ICAR-National Rice Research Institute, Cuttack 753006, India
- Environmental Science Laboratory, School of Applied Sciences, KIIT Deemed to be University, Bhubaneswar 751024, India
| | - Reshmi Raj K R
- ICAR-National Rice Research Institute, Cuttack 753006, India
| | - Kartik Chandra Pradhan
- College of Agriculture, Odisha University of Agriculture & Technology, Bhubaneswar 751003, India
| | - Chita Ranjan Sahoo
- Directorate of Research, Odisha University of Agriculture & Technology, Bhubaneswar 751003, India
| | - Mihir Ranjan Mohanty
- Regional Research and Technology Transfer Station (RRTTS), Odisha University of Agriculture & Technology, Jeypore 764001, India
| | - Chinmayee Behera
- Department of Genetics and Plant Breeding, Institute of Agricultural Sciences, SOA University, Bhubaneswar 753001, India
| | - Alok Kumar Panda
- Environmental Science Laboratory, School of Applied Sciences, KIIT Deemed to be University, Bhubaneswar 751024, India
| | - Binod Kumar Jena
- Krishi Vigyan Kendra, Odisha University of Agriculture & Technology, Rayagada 765022, India
| | - Lambodar Behera
- ICAR-National Rice Research Institute, Cuttack 753006, India
| | - Prasanta K Dash
- ICAR-National Institute for Plant Biotechnology, Pusa, New Delhi 110012, India
| | - Sharat Kumar Pradhan
- ICAR-National Rice Research Institute, Cuttack 753006, India
- Indian Council of Agricultural Research, Krishi Bhavan, New Delhi 110001, India
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7
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Yang X, Liu C, Li M, Li Y, Yan Z, Feng G, Liu D. Integrated transcriptomics and metabolomics analysis reveals key regulatory network that response to cold stress in common Bean (Phaseolus vulgaris L.). BMC PLANT BIOLOGY 2023; 23:85. [PMID: 36759761 PMCID: PMC9909927 DOI: 10.1186/s12870-023-04094-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 01/27/2023] [Indexed: 06/18/2023]
Abstract
Cold temperatures can be detrimental to crop survival and productivity. Breeding progress can be improved by understanding the molecular basis of low temperature tolerance. We investigated the key routes and critical metabolites related to low temperature resistance in cold-tolerant and -sensitive common bean cultivars 120 and 093, respectively. Many potential genes and metabolites implicated in major metabolic pathways during the chilling stress response were identified through transcriptomics and metabolomics research. Under chilling stress, the expression of many genes involved in lipid, amino acid, and flavonoid metabolism, as well as metabolite accumulation increased in the two bean types. Malondialdehyde (MDA) content was lower in 120 than in 093. Regarding amino acid metabolism, 120 had a higher concentration of acidic amino acids than 093, whereas 093 had a higher concentration of basic amino acids. Methionine accumulation was clearly higher in 120 than in 093. In addition, 120 had a higher concentration of many types of flavonoids than 093. Flavonoids, methionine and malondialdehyde could be used as biomarkers of plant chilling injury. Transcriptome analysis of hormone metabolism revealed considerably greater, expression of abscisic acid (ABA), gibberellin (GA), and jasmonic acid (JA) in 093 than in 120 during chilling stress, indicating that hormone regulation modes in 093 and 120 were different. Thus, chilling stress tolerance is different between 093 and 120 possibly due to transcriptional and metabolic regulation.
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Affiliation(s)
- Xiaoxu Yang
- Horticulture Department, College of Advanced Agriculture and Ecological Environment, Heilongjiang University, Harbin, 150000, China
| | - Chang Liu
- Horticulture Department, College of Advanced Agriculture and Ecological Environment, Heilongjiang University, Harbin, 150000, China
| | - Mengdi Li
- Horticulture Department, College of Life Sciences, Heilongjiang University, Harbin, 150000, China
| | - Yanmei Li
- Horticulture Department, College of Life Sciences, Heilongjiang University, Harbin, 150000, China
| | - Zhishan Yan
- Horticulture Department, College of Advanced Agriculture and Ecological Environment, Heilongjiang University, Harbin, 150000, China
| | - Guojun Feng
- Horticulture Department, College of Advanced Agriculture and Ecological Environment, Heilongjiang University, Harbin, 150000, China.
| | - Dajun Liu
- Horticulture Department, College of Advanced Agriculture and Ecological Environment, Heilongjiang University, Harbin, 150000, China.
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8
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Feng J, Li Z, Luo W, Liang G, Xu Y, Chong K. COG2 negatively regulates chilling tolerance through cell wall components altered in rice. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:19. [PMID: 36680595 DOI: 10.1007/s00122-023-04261-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 10/10/2022] [Indexed: 06/17/2023]
Abstract
Chilling-tolerant QTL gene COG2 encoded an extensin and repressed chilling tolerance by affecting the compositions of cell wall. Rice as a major crop is susceptible to chilling stress. Chilling tolerance is a complex trait controlled by multiple quantitative trait loci (QTLs). Here, we identify a QTL gene, COG2, that negatively regulates cold tolerance at seedling stage in rice. COG2 overexpression transgenic plants are sensitive to cold, whereas knockout transgenic lines enhance chilling tolerance. Natural variation analysis shows that Hap1 is a specific haplotype in japonica/Geng rice and correlates with chilling tolerance. The SNP1 in COG2 promoter is a specific divergency and leads to the difference in the expression level of COG2 between japonica/Geng and indica/Xian cultivars. COG2 encodes a cell wall-localized extensin and affects the compositions of cell wall, including pectin and cellulose, to defense the chilling stress. The results extend the understanding of the adaptation to the environment and provide an editing target for molecular design breeding of cold tolerance in rice.
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Affiliation(s)
- Jinglei Feng
- The Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- University of the Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhitao Li
- The Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- University of the Chinese Academy of Sciences, Beijing, 100049, China
| | - Wei Luo
- The Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
| | - Guohua Liang
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Centre for Modern Production Technology of Grain Crops, Key Laboratory of Plant Functional Genomics of the Ministry of Education, Yangzhou University, Yangzhou, 225009, China
| | - Yunyuan Xu
- The Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 100093, China
| | - Kang Chong
- The Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.
- University of the Chinese Academy of Sciences, Beijing, 100049, China.
- The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 100093, China.
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9
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Nayak DK, Sahoo S, Barik SR, Sanghamitra P, Sangeeta S, Pandit E, Reshmi Raj KR, Basak N, Pradhan SK. Association mapping for protein, total soluble sugars, starch, amylose and chlorophyll content in rice. BMC PLANT BIOLOGY 2022; 22:620. [PMID: 36581797 PMCID: PMC9801606 DOI: 10.1186/s12870-022-04015-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 12/21/2022] [Indexed: 05/13/2023]
Abstract
BACKGROUND Protein, starch, amylose and total soluble sugars are basic metabolites of seed that influence the eating, cooking and nutritional qualities of rice. Chlorophyll is responsible for the absorption and utilization of the light energy influencing photosynthetic efficiency in rice plant. Mapping of these traits are very important for detection of more number of robust markers for improvement of these traits through molecular breeding approaches. RESULTS A representative panel population was developed by including 120 germplasm lines from the initial shortlisted 274 lines for mapping of the six biochemical traits using 136 microsatellite markers through association mapping. A wide genetic variation was detected for the traits, total protein, starch, amylose, total soluble sugars, chlorophyll a, and chlorophyll b content in the population. Specific allele frequency, gene diversity, informative markers and other diversity parameters obtained from the population indicated the effectiveness of utilization of the population and markers for mapping of these traits. The fixation indices values estimated from the population indicated the existence of linkage disequilibrium for the six traits. The population genetic structure at K = 3 showed correspondence with majority of the members in each group for the six traits. The reported QTL, qProt1, qPC6.2, and qPC8.2 for protein content; qTSS8.1 for total soluble sugar; qAC1.2 for amylose content; qCH2 and qSLCHH for chlorophyll a (Chl. a) while qChl5D for chlorophyll b (Chl. b) were validated in this population. The QTL controlling total protein content qPC1.2; qTSS7.1, qTSS8.2 and qTSS12.1 for total soluble sugars; qSC2.1, qSC2.2, qSC6.1 and qSC11.1 for starch content; qAC11.1, qAC11.2 and qAC11.3 for amylose content; qChla8.1 for Chl. a content and qChlb7.1 and qChlb8.1 for Chl. b identified by both Generalized Linear Model and Mixed Linear Model were detected as novel QTL. The chromosomal regions on chromosome 8 at 234 cM for grain protein content and total soluble sugars and at 363 cM for Chl. a and Chl. b along with the position at 48 cM on chromosome 11 for starch and amylose content are genetic hot spots for these traits. CONCLUSION The validated, co-localized and the novel QTL detected in this study will be useful for improvement of protein, starch, amylose, total soluble sugars and chlorophyll content in rice.
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Affiliation(s)
- D K Nayak
- ICAR-National Rice Research Institute, Cuttack, Odisha, 753006, India
| | - S Sahoo
- ICAR-National Rice Research Institute, Cuttack, Odisha, 753006, India
- College of Agriculture, OUAT, Bhabaneswar, Odisha, 751003, India
| | - S R Barik
- ICAR-National Rice Research Institute, Cuttack, Odisha, 753006, India
| | - P Sanghamitra
- ICAR-National Rice Research Institute, Cuttack, Odisha, 753006, India
| | - S Sangeeta
- ICAR-National Rice Research Institute, Cuttack, Odisha, 753006, India
| | - E Pandit
- Fakir Mohan University, Balasore, Odisha, 756020, India
| | - K R Reshmi Raj
- ICAR-National Rice Research Institute, Cuttack, Odisha, 753006, India
| | - N Basak
- ICAR-National Rice Research Institute, Cuttack, Odisha, 753006, India
| | - S K Pradhan
- ICAR-National Rice Research Institute, Cuttack, Odisha, 753006, India.
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10
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Guo Z, Ma W, Cai L, Guo T, Liu H, Wang L, Liu J, Ma B, Feng Y, Liu C, Pan G. Comparison of anther transcriptomes in response to cold stress at the reproductive stage between susceptible and resistant Japonica rice varieties. BMC PLANT BIOLOGY 2022; 22:500. [PMID: 36284279 PMCID: PMC9597962 DOI: 10.1186/s12870-022-03873-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 09/26/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Rice is one of the most important cereal crops in the world but is susceptible to cold stress (CS). In this study, we carried out parallel transcriptomic analysis at the reproductive stage on the anthers of two Japonica rice varieties with contrasting CS resistance: cold susceptible Longjing11 (LJ11) and cold resistant Longjing25 (LJ25). RESULTS According to the obtained results, a total of 16,762 differentially expressed genes (DEGs) were identified under CS, including 7,050 and 14,531 DEGs in LJ25 and LJ11, respectively. Examining gene ontology (GO) enrichment identified 35 up- and 39 down-regulated biological process BP GO terms were significantly enriched in the two varieties, with 'response to heat' and 'response to cold' being the most enriched. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified 33 significantly enriched pathways. Only the carbon metabolism and amino acid biosynthesis pathways with down-regulated DEGs were enriched considerably in LJ11, while the plant hormone signal transduction pathway (containing 153 DEGs) was dramatically improved. Eight kinds of plant hormones were detected in the pathway, while auxin, abscisic acid (ABA), salicylic acid (SA), and ethylene (ETH) signaling pathways were found to be the top four pathways with the most DEGs. Furthermore, the protein-protein interaction (PPI) network analysis identified ten hub genes (co-expressed gene number ≥ 30), including six ABA-related genes. Various DEGs (such as OsDREB1A, OsICE1, OsMYB2, OsABF1, OsbZIP23, OsCATC, and so on) revealed distinct expression patterns among rice types when the DEGs between LJ11 and LJ25 were compared, indicating that they are likely responsible for CS resistance of rice in cold region. CONCLUSION Collectively, our findings provide comprehensive insights into complex molecular mechanisms of CS response and can aid in CS resistant molecular breeding of rice in cold regions.
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Affiliation(s)
- Zhenhua Guo
- Rice Research Institute of Heilongjiang Academy of Agricultural Sciences, 154026, Jiamusi, Heilongjiang, China
- National Engineering Research Center of Plant Space Breeding, South China Agricultural University, 510642, Guangzhou, Guangdong, China
| | - Wendong Ma
- Rice Research Institute of Heilongjiang Academy of Agricultural Sciences, 154026, Jiamusi, Heilongjiang, China
| | - Lijun Cai
- Jiamusi Branch of Heilongjiang Academy of Agricultural Sciences, 154007, Jiamusi, Heilongjiang, China.
| | - Tao Guo
- National Engineering Research Center of Plant Space Breeding, South China Agricultural University, 510642, Guangzhou, Guangdong, China
| | - Hao Liu
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, 510640, Guangzhou, Guangdong, China
| | - Linan Wang
- Rice Research Institute of Heilongjiang Academy of Agricultural Sciences, 154026, Jiamusi, Heilongjiang, China
| | - Junliang Liu
- Jiamusi Longjing Seed Industry Co., LTD, 154026, Jiamusi, Heilongjiang, China
| | - Bo Ma
- Qiqihar Branch of Heilongjiang Academy of Agricultural Sciences, 161006, Qiqihar, Heilongjiang, China
| | - Yanjiang Feng
- Rice Research Institute of Heilongjiang Academy of Agricultural Sciences, 154026, Jiamusi, Heilongjiang, China.
| | - Chuanxue Liu
- Rice Research Institute of Heilongjiang Academy of Agricultural Sciences, 154026, Jiamusi, Heilongjiang, China.
| | - Guojun Pan
- Rice Research Institute of Heilongjiang Academy of Agricultural Sciences, 154026, Jiamusi, Heilongjiang, China.
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11
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Ashfaq M, Rasheed A, Sajjad M, Ali M, Rasool B, Javed MA, Allah SU, Shaheen S, Anwar A, Ahmad MS, Mubashar U. Genome wide association mapping of yield and various desirable agronomic traits in Rice. Mol Biol Rep 2022; 49:11371-11383. [PMID: 35939183 DOI: 10.1007/s11033-022-07687-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Revised: 04/28/2022] [Accepted: 06/08/2022] [Indexed: 10/15/2022]
Abstract
BACKGROUND Rice (Oryza sativa L.) is one of the staple foods worldwide. To feed the growing population, the improvement of rice cultivars is important. To make the improvement in the rice breeding program, it is imperative to understand the similarities and differences of the existing rice accessions to find out the genetic diversity. Previous studies demonstrated the existence of abundant elite genes in rice landraces. A genome-wide association study (GWAS) was performed for yield and yield related traits to find the genetic diversity. DESIGN Experimental study. METHODS AND RESULTS A total of 204 SSRs markers were used among 17 SSRs found to be located on each chromosome in the rice genome. The diversity was analyzed using different genetic characters i.e., the total number of alleles (TNA), polymorphic information content (PIC), and gene diversity by Power markers, and the values for each genetic character per marker ranged from 2 to 9, 0.332 to 0.887 and 0.423 to 0.900 respectively across the whole genome. The results of population structure identified four main groups. MTA identified several markers associated with many agronomically important traits. These results will be very useful for the selection of potential parents, recombinants, and MTAs that govern the improvements and developments of new high yielding rice varieties. CONCLUSIONS Analysis of diversity in germplasm is important for the improvement of cultivars in the breeding program. In the present study, the diversity was analyzed with different methods and found that enormous diversity was present in the studied rice germplasm. The structure analysis found the presence of 4 genetic groups in the existing germplasm. A total of 129 marker-trait associations (MTAs) have been found in this study.
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Affiliation(s)
- Muhammad Ashfaq
- Department of Plant Breeding and Genetics, Faculty of Agricultural Sciences, University of the Punjab, Lahore, Pakistan.
| | - Abdul Rasheed
- Department of Plant Breeding and Genetics, Faculty of Agricultural Sciences, University of the Punjab, Lahore, Pakistan
| | - Muhammad Sajjad
- Department of Biosciences, COMSATS University Islamabad (CUI), Park Road, 45550, Islamabad, Pakistan
| | - Muhammad Ali
- Department of Entomology Faculty of Agricultural Sciences, University of the Punjab, Lahore, Pakistan.,Department of Biosciences, COMSAT University, Islamabad, Pakistan
| | - Bilal Rasool
- Department of Zoology, Government College University Faisalabad, Faisalabad, Pakistan
| | - Muhammad Arshad Javed
- Department of Plant Breeding and Genetics, Faculty of Agricultural Sciences, University of the Punjab, Lahore, Pakistan
| | - Sami Ul Allah
- Department of Plant Breeding and Genetics, Bahuddin Zakaria University Bahudar Campus Layyah, Bahudar, Pakistan
| | - Shabnum Shaheen
- Department of Botany, Lahore College for Women University, Lahore, Pakistan
| | - Alia Anwar
- Department of Plant Breeding and Genetics, Faculty of Agricultural Sciences, University of the Punjab, Lahore, Pakistan
| | - Muhammad Shafiq Ahmad
- Department of Plant Breeding and Genetics, Faculty of Agricultural Sciences, University of the Punjab, Lahore, Pakistan
| | - Urooj Mubashar
- Government Training Education Academy, Gujranwala, Pakistan
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12
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Unraveling the genomic regions controlling the seed vigour index, root growth parameters and germination per cent in rice. PLoS One 2022; 17:e0267303. [PMID: 35881571 PMCID: PMC9321372 DOI: 10.1371/journal.pone.0267303] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 04/06/2022] [Indexed: 12/21/2022] Open
Abstract
High seed vigour ensures good quality seed and higher productivity. Early seedling growth parameters indicate seed vigour in rice. Seed vigour via physiological growth parameters is a complex trait controlled by many quantitative trait loci. A panel was prepared representing a population of 274 rice landraces by including genotypes from all the phenotypic groups of sixseedling stage physiological parameters including germination % for association mapping. Wide variations for the six studiedtraits were observed in the population. The population was classified into 3 genetic groups. Fixation indices indicated the presence of linkage disequilibrium in the population. The population was classified into subpopulations and each subpopulation showed correspondence with the 6 physiological traits. A total of 5 reported QTLs viz., qGP8.1 for germination % (GP); qSVII2.1, qSVII6.1 and qSVII6.2 for seed vigour index II (SVII), and qRSR11.1 for root-shoot ratio (RSR) were validated in this mapping population. In addition, 13 QTLs regulating the physiological parameters such as qSVI 11.1 for seed vigour index I; qSVI11.1 and qSVI12.1 for seed vigour index II; qRRG10.1, qRRG8.1, qRRG8.2, qRRG6.1 and qRRG4.1 for rate of root growth (RRG); qRSR2.1, qRSR3.1 and qRSR5.1 for root-shoot ratio (RSR) while qGP6.2 and qGP6.3 for germination %were identified. Additionally, co-localization or co-inheritance of QTLs, qGP8.1 and qSVI8.1 for GP and SVI-1; qGP6.2 and qRRG6.1 for GP and RRG, and qSVI11.1 and qRSR11.1 for SVI and RSR were detected. The QTLs identified in this study will be useful for improvement of seed vigour trait in rice.
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13
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Xu Q, Wang X, Wang Y, Zhang H, Zhang H, Di H, Zhang L, Dong L, Zeng X, Liu X, Lee M, Wang Z, Zhou Y. Combined QTL mapping and RNA-Seq pro-filing reveal candidate genes related to low-temperature tolerance in maize. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:33. [PMID: 37312966 PMCID: PMC10248625 DOI: 10.1007/s11032-022-01297-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 05/16/2022] [Indexed: 06/15/2023]
Abstract
Maize (Zea mays L.) is the most important food crop in the world, with significant acreage and production across the globe. However, it is affected by low temperatures throughout its growth process, especially during germination. Therefore, it is important to identify more QTLs or genes associated with germination under low-temperature conditions. For the QTL analysis of traits related to low-temperature germination, we used a high-res genetic map of 213 lines of the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, which had 6618 bin markers. We detected 28 QTLs of eight phenotypic characteristics associated with low-temperature germination, while they explained the phenotypic contribution rate of 5.4 ~ 13.34%. Additionally, 14 overlapping QTLs produced six QTL clusters on every chromosome, except for 8 and 10. RNA-Seq found six genes related to low-temperature tolerance in these QTLs, while qRT-PCR analysis demonstrated that the expression trends of the Zm00001d045568 gene in the LT_BvsLT_M group and the CK_BvsCK_M group were highly significantly different at all four-time points (P < 0.01), and encoded the RING zinc finger protein. It was located on qRTL9-2 and qRSVI9-1 and is related to the total length and simple vitality index. These results provided potential candidate genes for further gene cloning and improving the low-temperature tolerance of maize. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-022-01297-6.
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Affiliation(s)
- Qingyu Xu
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Xuerui Wang
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Yuhe Wang
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Hong Zhang
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Hongzhou Zhang
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Hong Di
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Lin Zhang
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Ling Dong
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Xing Zeng
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Xianjun Liu
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Michael Lee
- Department of Agronomy, Iowa State University, Ames, IA 50011 USA
| | - Zhenhua Wang
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Yu Zhou
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
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14
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Sanghamitra P, Barik SR, Bastia R, Mohanty SP, Pandit E, Behera A, Mishra J, Kumar G, Pradhan SK. Detection of Genomic Regions Controlling the Antioxidant Enzymes, Phenolic Content, and Antioxidant Activities in Rice Grain through Association Mapping. PLANTS (BASEL, SWITZERLAND) 2022; 11:1463. [PMID: 35684236 PMCID: PMC9183076 DOI: 10.3390/plants11111463] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 05/23/2022] [Accepted: 05/25/2022] [Indexed: 05/08/2023]
Abstract
Because it is rich in antioxidant compounds, the staple food of rice provides many health benefits. Four antioxidant traits in rice grain, viz., catalase, CUPRAC, DPPH, FRAP and peroxidase, were mapped in a representative panel population containing 117 germplasm lines using 131 SSR markers through association mapping. Donor lines rich in multiple antioxidant properties were identified from the mapping population. The population was classified into three genetic groups and each group showed reasonable correspondence with the antioxidant traits. The presence of linkage disequilibrium in the population was confirmed from the estimated Fst values. A strong positive correlation of DPPH was established with TPC, FRAP and CUPRAC. A moderate to high mean gene diversity was observed in the panel population. Eleven significant marker-trait associations for antioxidant traits were mapped, namely, qACD2.1, qACD11.1 and qACD12.2 for DPPH; qCAT8.1 and qCAT11.1 for catalase; qFRAP11.1, qFRAP12.1 and qFRAP12.2 for FRAP; and qCUPRAC3.1, qCUPRAC11.1 and qCUPRA12.1 regulating CUPRAC. Co-localization of the QTLs for qACD11.1, qFRAP11.1 and qCUPRAC11.1 were detected, which may act as antioxidant hotspots regulating DPPH, FRAP and CUPRAC activities, respectively, while qACD12.2 and qFRAP12.1 remained close on the chromosome 12. These detected QTLs will be useful in antioxidant improvement programs in rice.
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Affiliation(s)
- Priyadarsini Sanghamitra
- ICAR-National Rice Research Institute, Cuttack 753006, Odisha, India; (P.S.); (S.R.B.); (R.B.); (S.P.M.); (E.P.); (A.B.); (J.M.); (G.K.)
| | - Saumya Ranjan Barik
- ICAR-National Rice Research Institute, Cuttack 753006, Odisha, India; (P.S.); (S.R.B.); (R.B.); (S.P.M.); (E.P.); (A.B.); (J.M.); (G.K.)
| | - Ramakrushna Bastia
- ICAR-National Rice Research Institute, Cuttack 753006, Odisha, India; (P.S.); (S.R.B.); (R.B.); (S.P.M.); (E.P.); (A.B.); (J.M.); (G.K.)
| | - Shakti Prakash Mohanty
- ICAR-National Rice Research Institute, Cuttack 753006, Odisha, India; (P.S.); (S.R.B.); (R.B.); (S.P.M.); (E.P.); (A.B.); (J.M.); (G.K.)
| | - Elssa Pandit
- ICAR-National Rice Research Institute, Cuttack 753006, Odisha, India; (P.S.); (S.R.B.); (R.B.); (S.P.M.); (E.P.); (A.B.); (J.M.); (G.K.)
- Department of Biosciences and Biotechnology, Fakir Mohan University, Balasore 756020, Odisha, India
| | - Abhisarika Behera
- ICAR-National Rice Research Institute, Cuttack 753006, Odisha, India; (P.S.); (S.R.B.); (R.B.); (S.P.M.); (E.P.); (A.B.); (J.M.); (G.K.)
| | - Jyotirmayee Mishra
- ICAR-National Rice Research Institute, Cuttack 753006, Odisha, India; (P.S.); (S.R.B.); (R.B.); (S.P.M.); (E.P.); (A.B.); (J.M.); (G.K.)
| | - Gaurav Kumar
- ICAR-National Rice Research Institute, Cuttack 753006, Odisha, India; (P.S.); (S.R.B.); (R.B.); (S.P.M.); (E.P.); (A.B.); (J.M.); (G.K.)
| | - Sharat Kumar Pradhan
- ICAR-National Rice Research Institute, Cuttack 753006, Odisha, India; (P.S.); (S.R.B.); (R.B.); (S.P.M.); (E.P.); (A.B.); (J.M.); (G.K.)
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15
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Uhlarik A, Ćeran M, Živanov D, Grumeza R, Skøt L, Sizer-Coverdale E, Lloyd D. Phenotypic and Genotypic Characterization and Correlation Analysis of Pea (Pisum sativum L.) Diversity Panel. PLANTS 2022; 11:plants11101321. [PMID: 35631746 PMCID: PMC9146737 DOI: 10.3390/plants11101321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 04/10/2022] [Accepted: 05/01/2022] [Indexed: 11/16/2022]
Abstract
Phenotypic and genotypic characterization were performed to assess heritability, variability, and seed yield stability of pea genotypes used in breeding to increase the pea production area. A European pea diversity panel, including genotypes from North America, Asia, and Australia consisting of varieties, breeding lines, pea, and landraces was examined in 2019 and 2020 in Serbia and Belgium using augmented block design. The highest heritability was for thousand seed weight; the highest coefficient of variation was for seed yield. The highest positive correlation was between number of seeds per plant and number of pods per plant; the highest negative correlation was between seed yield and protein content. Hierarchical clustering separated pea germplasm based on use and type. Different Principal component analysis grouping of landraces, breeding lines, and varieties, as well as forage types and garden and dry peas, confirms that there was an apparent decrease in similarity between the genotypes, which can be explained by their different purposes. Pea breeding should be focused on traits with consistent heritability and a positive effect on seed yield when selecting high-yielding genotypes, and on allowing for more widespread use of pea in various agricultural production systems.
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Affiliation(s)
- Ana Uhlarik
- Institute of Field and Vegetable Crops, Maksima Gorkog 30, 21000 Novi Sad, Serbia; (M.Ć.); (D.Ž.)
- Correspondence:
| | - Marina Ćeran
- Institute of Field and Vegetable Crops, Maksima Gorkog 30, 21000 Novi Sad, Serbia; (M.Ć.); (D.Ž.)
| | - Dalibor Živanov
- Institute of Field and Vegetable Crops, Maksima Gorkog 30, 21000 Novi Sad, Serbia; (M.Ć.); (D.Ž.)
| | - Radu Grumeza
- Agro Seed Research, Nijverheidslaan 1506, 3660 Oudsbergen, Belgium;
| | - Leif Skøt
- Institute of Biological, Environmental & Rural Sciences (IBERS), Aberystwyth University, Penglais, Ceredigion, Aberystwyth SY23 3DA, UK; (L.S.); (E.S.-C.); (D.L.)
| | - Ellen Sizer-Coverdale
- Institute of Biological, Environmental & Rural Sciences (IBERS), Aberystwyth University, Penglais, Ceredigion, Aberystwyth SY23 3DA, UK; (L.S.); (E.S.-C.); (D.L.)
| | - David Lloyd
- Institute of Biological, Environmental & Rural Sciences (IBERS), Aberystwyth University, Penglais, Ceredigion, Aberystwyth SY23 3DA, UK; (L.S.); (E.S.-C.); (D.L.)
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16
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Zhao W, Xiao W, Sun J, Chen M, Ma M, Cao Y, Cen W, Li R, Luo J. An Integration of MicroRNA and Transcriptome Sequencing Analysis Reveal Regulatory Roles of miRNAs in Response to Chilling Stress in Wild Rice. PLANTS 2022; 11:plants11070977. [PMID: 35406957 PMCID: PMC9002458 DOI: 10.3390/plants11070977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 04/01/2022] [Accepted: 04/01/2022] [Indexed: 12/03/2022]
Abstract
A chromosome single segment substitution line (CSSL) DC90, which was generated by introgressing CTS-12, a locus derived from common wild rice (Oryza rufipogon Griff.), into the 9311 (Oryza sativa L. ssp. indica) background, exhibits a chilling tolerance phenotype under chilling stress. Here, an integration of microRNA (miRNA) deep sequencing and transcriptomic sequencing analysis was performed to explore the expression profiles of miRNAs and their target genes mediated by CTS-12 under chilling stress, and to reveal the possible regulatory mechanisms of miRNAs that are involved in chilling tolerance. Integration analysis revealed that a number of differentially expressed miRNAs (DEMs) and putative target genes with different expression patterns and levels were identified in 9311 and DC90 under chilling stress. KEGG enrichment analysis revealed that the target genes that are regulated by chilling-induced miRNAs are involved in the regulation of various biological processes/pathways, including protein biosynthesis, redox process, photosynthetic process, and chloroplast development in two genotypes. CRISPR/Cas9 editing of the target genes of the key DEMs in a chilling tolerant rice variety Zhonghua 11 (ZH11) found that LOC_Os11g48020 (OsGL1-11), one of the putative target genes of osa-miR1846a/b-5p and encoding a wax synthesis protein, is correlated with a chilling stress tolerance phenotype, implying osa-miR1846a/b-5p/OsGL1-11 plays an important role in CTS-12-mediated chilling stress tolerance regulatory pathway(s). Therefore, we speculate that the CTS-12 may regulate the key miRNA target genes in response to chilling stress by differential regulation of miRNAs in wild rice, thereby resulting in the variation of chilling tolerance phenotype between 9311 and DC90.
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Affiliation(s)
- Wenlong Zhao
- College of Life Science and Technology, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530004, China; (W.Z.); (W.X.); (J.S.); (M.C.); (M.M.); (Y.C.); (W.C.)
| | - Weiyu Xiao
- College of Life Science and Technology, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530004, China; (W.Z.); (W.X.); (J.S.); (M.C.); (M.M.); (Y.C.); (W.C.)
| | - Jinliang Sun
- College of Life Science and Technology, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530004, China; (W.Z.); (W.X.); (J.S.); (M.C.); (M.M.); (Y.C.); (W.C.)
| | - Mingxin Chen
- College of Life Science and Technology, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530004, China; (W.Z.); (W.X.); (J.S.); (M.C.); (M.M.); (Y.C.); (W.C.)
| | - Mingqing Ma
- College of Life Science and Technology, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530004, China; (W.Z.); (W.X.); (J.S.); (M.C.); (M.M.); (Y.C.); (W.C.)
| | - Yaqi Cao
- College of Life Science and Technology, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530004, China; (W.Z.); (W.X.); (J.S.); (M.C.); (M.M.); (Y.C.); (W.C.)
| | - Weijian Cen
- College of Life Science and Technology, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530004, China; (W.Z.); (W.X.); (J.S.); (M.C.); (M.M.); (Y.C.); (W.C.)
| | - Rongbai Li
- Agriculture College, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530004, China;
| | - Jijing Luo
- College of Life Science and Technology, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530004, China; (W.Z.); (W.X.); (J.S.); (M.C.); (M.M.); (Y.C.); (W.C.)
- Correspondence:
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Liu Z, Su J, Luo X, Meng J, Zhang H, Li P, Sun Y, Song J, Peng X, Yu C. Nitrogen limits zinc‐mediated stimulation of tillering in rice by modifying phytohormone balance under low‐temperature stress. Food Energy Secur 2021. [DOI: 10.1002/fes3.359] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Affiliation(s)
- Zhilei Liu
- College of Resources and Environment Northeast Agricultural University Harbin China
- Key Laboratory of Germplasm Innovation Ministry of Education Physiology and Ecology of Grain Crop in Cold Region (Northeast Agricultural University) Harbin China
| | - Jinkai Su
- College of Resources and Environment Northeast Agricultural University Harbin China
| | - Xiangyu Luo
- College of Resources and Environment Northeast Agricultural University Harbin China
| | - Jingrou Meng
- College of Resources and Environment Northeast Agricultural University Harbin China
| | - Haonan Zhang
- College of Resources and Environment Northeast Agricultural University Harbin China
| | - Pengfei Li
- College of Resources and Environment Northeast Agricultural University Harbin China
- Key Laboratory of Germplasm Innovation Ministry of Education Physiology and Ecology of Grain Crop in Cold Region (Northeast Agricultural University) Harbin China
| | - Yankun Sun
- College of Resources and Environment Northeast Agricultural University Harbin China
| | - Jiamei Song
- College of Resources and Environment Northeast Agricultural University Harbin China
| | - Xianlong Peng
- College of Resources and Environment Northeast Agricultural University Harbin China
- Key Laboratory of Germplasm Innovation Ministry of Education Physiology and Ecology of Grain Crop in Cold Region (Northeast Agricultural University) Harbin China
| | - Cailian Yu
- The School of Material Science and Chemical Engineering Harbin University of Science and Technology Harbin China
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Pawar S, Pandit E, Mohanty IC, Saha D, Pradhan SK. Population genetic structure and association mapping for iron toxicity tolerance in rice. PLoS One 2021; 16:e0246232. [PMID: 33647046 PMCID: PMC7920388 DOI: 10.1371/journal.pone.0246232] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Accepted: 11/11/2020] [Indexed: 02/01/2023] Open
Abstract
Iron (Fe) toxicity is a major abiotic stress which severely reduces rice yield in many countries of the world. Genetic variation for this stress tolerance exists in rice germplasms. Mapping of gene(s)/QTL controlling the stress tolerance and transfer of the traits into high yielding rice varieties are essential for improvement against the stress. A panel population of 119 genotypes from 352 germplasm lines was constituted for detecting the candidate gene(s)/QTL through association mapping. STRUCTURE, GenAlEx and Darwin softwares were used to classify the population. The marker-trait association was detected by considering both the Generalized Linear Model (GLM) and Mixed Linear Model (MLM) analyses. Wide genetic variation was observed among the genotypes present in the panel population for the stress tolerance. Linkage disequilibrium was detected in the population for iron toxicity tolerance. The population was categorized into three genetic structure groups. Marker-trait association study considering both the Generalized Linear Model (GLM) and Mixed Linear Model (MLM) showed significant association of leaf browning index (LBI) with markers RM471, RM3, RM590 and RM243. Three novel QTL controlling Fe-toxicity tolerance were detected and designated as qFeTox4.3, qFeTox6.1 and qFeTox10.1. A QTL reported earlier in the marker interval of C955-C885 on chromosome 1 is validated using this panel population. The present study showed that QTL controlling Fe-toxicity tolerance to be co-localized with the QTL for Fe-biofortification of rice grain indicating involvement of common pathway for Fe toxicity tolerance and Fe content in rice grain. Fe-toxicity tolerance QTL qFeTox6.1 was co-localized with grain Fe-biofortification QTLs qFe6.1 and qFe6.2 on chromosome 6, whereas qFeTox10.1 was co-localized with qFe10.1 on chromosome 10. The Fe-toxicity tolerance QTL detected from this mapping study will be useful in marker-assisted breeding programs.
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Affiliation(s)
- S. Pawar
- Crop Improvement Division, ICAR-National Rice Research Institute, Cuttack, Odisha, India
| | - E. Pandit
- Crop Improvement Division, ICAR-National Rice Research Institute, Cuttack, Odisha, India
- Department of Bio-Science and Bio-Technology, Fakir Mohan University, Balasore, Odisha, India
| | - I. C. Mohanty
- Department of Biotechnology, College of Agriculture, OUAT, Bhubaneswar, Odisha, India
| | - D. Saha
- Department of Biotechnology, College of Agriculture, OUAT, Bhubaneswar, Odisha, India
| | - S. K. Pradhan
- Crop Improvement Division, ICAR-National Rice Research Institute, Cuttack, Odisha, India
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Sahoo S, Sanghamitra P, Nanda N, Pawar S, Pandit E, Bastia R, Muduli KC, Pradhan SK. Association of molecular markers with physio-biochemical traits related to seed vigour in rice. PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2020; 26:1989-2003. [PMID: 33088044 PMCID: PMC7548267 DOI: 10.1007/s12298-020-00879-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 08/18/2020] [Accepted: 09/01/2020] [Indexed: 05/08/2023]
Abstract
Eighteen physio-biochemical traits influencing seed vigour were studied for their association with molecular markers using a mini core set constituted from 120 germplasm lines. High genetic variation was detected in the parameters namely chlrophyll a, Chlrophyll b, total chlorophyll, carotenoids, total anthocyanin content, gamma-oryzanols, total phenolics content, superoxide dismutase, catalase, guaicol peroxidase, total soluble sugar, total protein, seed vigour index -I and seed vigour index -II. Strong positive correlation of seed vigour index II was observed with amylose content, total anthocyanin content, catalase, total phenolic content and total flavonoid content while a negative association was observed for gamma-oryzanol content. High gene diversity (0.7169) and informative markers value (0.6789) were estimated from the investigation. Three genetic structure groups were observed in the panel population and genotypes were grouped in the subpopulations based on the seed vigour trait. Differences in the fixation indices of the three sub populations indicated existence of linkage disequilibrium in the studied panel population. Association of the traits namely total flavonoids, superoxide dismutase, catalase, chlorophyll a, Chlorophyll b, total chlorophyll, carotenoids, starch, amylose, total anthocyanin, gamma-oryzanol, total phenolics with the molecular markers were detected by Generalized Linear Model and Mixed Linear Model showing > 0.10 R2 value. Association of the trait, total flavonoids with marker RM7364 located on chromosome 8 reported in earlier study was validated in this investigation. The validated markers and the novel markers detected showing higher R2 value will be useful for improvement of seed vigour in rice.
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Affiliation(s)
- Swastideepa Sahoo
- Department of Seed Technology, College of Agriculture, OUAT, Bhubaneswar, 751003 Odisha India
| | | | - Nibedita Nanda
- Department of Seed Technology, College of Agriculture, OUAT, Bhubaneswar, 751003 Odisha India
| | - Swapnil Pawar
- Crop Improvement Division, ICAR-National Rice Research Institute, Cuttack, Odisha 753006 India
| | | | - Ramakrushna Bastia
- Crop Improvement Division, ICAR-National Rice Research Institute, Cuttack, Odisha 753006 India
| | - Kumuda Chandra Muduli
- Department of Seed Technology, College of Agriculture, OUAT, Bhubaneswar, 751003 Odisha India
| | - Sharat Kumar Pradhan
- Crop Improvement Division, ICAR-National Rice Research Institute, Cuttack, Odisha 753006 India
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Donde R, Mohapatra S, Baksh SKY, Padhy B, Mukherjee M, Roy S, Chattopadhyay K, Anandan A, Swain P, Sahoo KK, Singh ON, Behera L, Dash SK. Identification of QTLs for high grain yield and component traits in new plant types of rice. PLoS One 2020; 15:e0227785. [PMID: 32673318 PMCID: PMC7365460 DOI: 10.1371/journal.pone.0227785] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2019] [Accepted: 06/11/2020] [Indexed: 11/18/2022] Open
Abstract
A panel of 60 genotypes comprising New Plant Types (NPTs) along with indica, tropical and temperate japonica genotypes was phenotypically evaluated for four seasons in irrigated situation for grain yield per se and component traits. Twenty NPT genotypes were found promising with an average grain yield varying from 5.45 to 8.8 t/ha. A total of 85 SSR markers were used in the study to identify QTLs associated with grain yield per se and related traits. Sixty-six (77.65%) markers were found to be polymorphic. The PIC values varied from 0.516 to 0.92 with an average of 0.704. A moderate level of genetic diversity (0.39) was detected among genotypes. Variation to the tune of 8% within genotypes, 68% among the genotypes within the population and 24% among the populations were observed (AMOVA). This information may help in identification of potential parents for development of transgressive segregants with very high yield. The association analysis using GLM and MLM models led to the identification of 30 and 10 SSR markers associated with 70 and 16 QTLs, respectively. Thirty novel QTLs linked with 16 SSRs were identified to be associated with eleven traits, namely tiller number (qTL-6.1, qTL-11.1, qTL-4.1), panicle length (qPL-1.1, qPL-5.1, qPL-7.1, qPL-8.1), flag leaf length (qFLL-8.1, qFLL-9.1), flag leaf width (qFLW-6.2, qFLW-5.1, qFLW-8.1, qFLW-7.1), total no. of grains (qTG-2.2, qTG-a7.1), thousand-grain weight (qTGW-a1.1, qTGW-a9.2, qTGW-5.1, qTGW-8.1), fertile grains (qFG-7.1), seed length-breadth ratio (qSlb-3.1), plant height (qPHT-6.1, qPHT-9.1), days to 50% flowering (qFD-1.1) and grain yield per se (qYLD-5.1, qYLD-6.1a, qYLD-11.1).Some of the SSRs were co-localized with more than two traits. The highest co-localization was identified with RM5709 linked to nine traits, followed by RM297 with five traits. Similarly, RM5575, RM204, RM168, RM112, RM26499 and RM22899 were also recorded to be co-localized with more than one trait and could be rated as important for marker-assisted backcross breeding programs, for pyramiding of these QTLs for important yield traits, to produce new-generation rice for prospective increment in yield potentiality and breaking yield ceiling.
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Affiliation(s)
- Ravindra Donde
- ICAR-National Rice Research Institute (NRRI), Cuttack, Odisha, India
| | - Shibani Mohapatra
- ICAR-National Rice Research Institute (NRRI), Cuttack, Odisha, India
| | - S. K. Yasin Baksh
- ICAR-National Rice Research Institute (NRRI), Cuttack, Odisha, India
| | - Barada Padhy
- ICAR-National Rice Research Institute (NRRI), Cuttack, Odisha, India
| | - Mitadru Mukherjee
- ICAR-National Rice Research Institute (NRRI), Cuttack, Odisha, India
| | - Somnath Roy
- ICAR-NRRI, Regional Research Station (CRURRS), Hazaribagh, Jharkhand
| | | | - A. Anandan
- ICAR-National Rice Research Institute (NRRI), Cuttack, Odisha, India
| | - Padmini Swain
- ICAR-National Rice Research Institute (NRRI), Cuttack, Odisha, India
| | | | - Onkar Nath Singh
- ICAR-National Rice Research Institute (NRRI), Cuttack, Odisha, India
| | - Lambodar Behera
- ICAR-National Rice Research Institute (NRRI), Cuttack, Odisha, India
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Kong W, Zhang C, Qiang Y, Zhong H, Zhao G, Li Y. Integrated RNA-Seq Analysis and Meta-QTLs Mapping Provide Insights into Cold Stress Response in Rice Seedling Roots. Int J Mol Sci 2020; 21:ijms21134615. [PMID: 32610550 PMCID: PMC7369714 DOI: 10.3390/ijms21134615] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 06/24/2020] [Accepted: 06/26/2020] [Indexed: 12/20/2022] Open
Abstract
Rice (Oryza sativa L.) is a widely cultivated food crop around the world, especially in Asia. However, rice seedlings often suffer from cold stress, which affects their growth and yield. Here, RNA-seq analysis and Meta-QTLs mapping were performed to understand the molecular mechanisms underlying cold tolerance in the roots of 14-day-old seedlings of rice (RPY geng, cold-tolerant genotype). A total of 4779 of the differentially expressed genes (DEGs) were identified, including 2457 up-regulated and 2322 down-regulated DEGs. The GO, COG, KEEG, and Mapman enrichment results of DEGs revealed that DEGs are mainly involved in carbohydrate transport and metabolism, signal transduction mechanisms (plant hormone signal transduction), biosynthesis, transport and catabolism of secondary metabolites (phenylpropanoid biosynthesis), defense mechanisms, and large enzyme families mechanisms. Notably, the AP2/ERF-ERF, NAC, WRKY, MYB, C2H2, and bHLH transcription factors participated in rice’s cold–stress response and tolerance. On the other hand, we mapped the identified DEGs to 44 published cold–stress-related genes and 41 cold-tolerant Meta-QTLs regions. Of them, 12 DEGs were the published cold–stress-related genes and 418 DEGs fell into the cold-tolerant Meta-QTLs regions. In this study, the identified DEGs and the putative molecular regulatory network can provide insights for understanding the mechanism of cold stress tolerance in rice. In addition, DEGs in KEGG term-enriched terms or cold-tolerant Meta-QTLs will help to secure key candidate genes for further functional studies on the molecular mechanism of cold stress response in rice.
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Pradhan SK, Pandit E, Pawar S, Naveenkumar R, Barik SR, Mohanty SP, Nayak DK, Ghritlahre SK, Sanjiba Rao D, Reddy JN, Patnaik SSC. Linkage disequilibrium mapping for grain Fe and Zn enhancing QTLs useful for nutrient dense rice breeding. BMC PLANT BIOLOGY 2020; 20:57. [PMID: 32019504 PMCID: PMC7001215 DOI: 10.1186/s12870-020-2262-4] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Accepted: 01/20/2020] [Indexed: 05/23/2023]
Abstract
BACKGROUND High yielding rice varieties are usually low in grain iron (Fe) and zinc (Zn) content. These two micronutrients are involved in many enzymatic activities, lack of which cause many disorders in human body. Bio-fortification is a cheaper and easier way to improve the content of these nutrients in rice grain. RESULTS A population panel was prepared representing all the phenotypic classes for grain Fe-Zn content from 485 germplasm lines. The panel was studied for genetic diversity, population structure and association mapping of grain Fe-Zn content in the milled rice. The population showed linkage disequilibrium showing deviation of Hardy-Weinberg's expectation for Fe-Zn content in rice. Population structure at K = 3 categorized the panel population into distinct sub-populations corroborating with their grain Fe-Zn content. STRUCTURE analysis revealed a common primary ancestor for each sub-population. Novel quantitative trait loci (QTLs) namely qFe3.3 and qFe7.3 for grain Fe and qZn2.2, qZn8.3 and qZn12.3 for Zn content were detected using association mapping. Four QTLs, namely qFe3.3, qFe7.3, qFe8.1 and qFe12.2 for grain Fe content were detected to be co-localized with qZn3.1, qZn7, qZn8.3 and qZn12.3 QTLs controlling grain Zn content, respectively. Additionally, some Fe-Zn controlling QTLs were co-localized with the yield component QTLs, qTBGW, OsSPL14 and qPN. The QTLs qFe1.1, qFe3.1, qFe5.1, qFe7.1, qFe8.1, qZn6, qZn7 and gRMm9-1 for grain Fe-Zn content reported in earlier studies were validated in this study. CONCLUSION Novel QTLs, qFe3.3 and qFe7.3 for grain Fe and qZn2.2, qZn8.3 and qZn12.3 for Zn content were detected for these two traits. Four Fe-Zn controlling QTLs and few yield component QTLs were detected to be co-localized. The QTLs, qFe1.1, qFe3.1, qFe5.1, qFe7.1, qFe8.1, qFe3.3, qFe7.3, qZn6, qZn7, qZn2.2, qZn8.3 and qZn12.3 will be useful for biofortification of the micronutrients. Simultaneous enhancement of Fe-Zn content may be possible with yield component traits in rice.
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Affiliation(s)
- S. K. Pradhan
- ICAR-National Rice Research Institute, Cuttack, Odisha India
| | - E. Pandit
- ICAR-National Rice Research Institute, Cuttack, Odisha India
| | - S. Pawar
- ICAR-National Rice Research Institute, Cuttack, Odisha India
| | - R. Naveenkumar
- ICAR-National Rice Research Institute, Cuttack, Odisha India
| | - S. R. Barik
- ICAR-National Rice Research Institute, Cuttack, Odisha India
| | - S. P. Mohanty
- ICAR-National Rice Research Institute, Cuttack, Odisha India
| | - D. K. Nayak
- ICAR-National Rice Research Institute, Cuttack, Odisha India
| | | | - D. Sanjiba Rao
- ICAR-Indian Institute of Rice Research, Hyderabad, India
| | - J. N. Reddy
- ICAR-National Rice Research Institute, Cuttack, Odisha India
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Liu C, Yang X, Yan Z, Fan Y, Feng G, Liu D. Analysis of differential gene expression in cold-tolerant vs. cold-sensitive varieties of snap bean (Phaseolus vulgaris L.) in response to low temperature stress. Genes Genomics 2019; 41:1445-1455. [PMID: 31535316 DOI: 10.1007/s13258-019-00870-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2019] [Accepted: 09/04/2019] [Indexed: 11/24/2022]
Abstract
BACKGROUND Snap bean, Phaseolus vulgaris L., as a warm-season vegetable, low temperature stress seriously affect the yield and quality. At present, little is known about the genes and molecular regulation mechanism in cold response in snap bean exposed to low temperature. OBJECTIVES Our objectives were to identify the low temperature response genes in snap bean and to examine differences in the gene response between cold-tolerant and cold-sensitive genotypes. METHODS We used two highly inbred snap bean lines in this study, the cold-tolerant line '120', and the cold-sensitive line '093'. The plants were grown to the three leaf and one heart stage and exposed to 4 °C low temperature. We used RNA sequencing (RNA-seq) to analyze the differences of gene expression. RESULTS 988 and 874 cold-responsive genes were identified in 'T120 vs CK120' and 'T093 vs CK093' ('T' stands for low temperature treatment, and 'CK' stands for control at room temperature), respectively. Of these, 555 and 442 genes were unique to cold-stressed lines '120' and '093', respectively compared to the control. Our analysis of these differentially expressed genes indicates that Ca2+, ROS, and hormones act as signaling molecules that play important roles in low temperature response in P. vulgaris. Altering the expression of genes in these signaling pathways activates expression of downstream response genes which can interact with other signaling regulatory networks. This may maintained the balance of ROS and hormones, making line '120' more cold-tolerant than line '093'. CONCLUSION Our results provide a preliminarily understanding of the molecular basis of low temperature response in snap bean, and also establish a foundation for the future genetic improvement of cold sensitivity in snap bean by incorporating genes for cold tolerance.
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Affiliation(s)
- Chang Liu
- Horticulture Department, Academy of Crop Science, Heilongjiang University, 74 Xuefu Road, Harbin, 150000, Heilongjiang, China.,Work Station of Science and Technique for Post-doctoral in Sugar Beet Institute Affiliated to Heilongjiang University, 74 Xuefu Road, Harbin, 150000, Heilongjiang, China.,Post-doctoral Research Station Affiliated To Northeast Agricultural University, 59 Mucai Road, Harbin, 150000, Heilongjiang, China
| | - Xiaoxu Yang
- Horticulture Department, Academy of Crop Science, Heilongjiang University, 74 Xuefu Road, Harbin, 150000, Heilongjiang, China.,Work Station of Science and Technique for Post-doctoral in Sugar Beet Institute Affiliated to Heilongjiang University, 74 Xuefu Road, Harbin, 150000, Heilongjiang, China.,Post-doctoral Research Station Affiliated To Northeast Agricultural University, 59 Mucai Road, Harbin, 150000, Heilongjiang, China
| | - Zhishan Yan
- Horticulture Department, Academy of Crop Science, Heilongjiang University, 74 Xuefu Road, Harbin, 150000, Heilongjiang, China
| | - Youjun Fan
- Horticulture Department, Academy of Crop Science, Heilongjiang University, 74 Xuefu Road, Harbin, 150000, Heilongjiang, China
| | - Guojun Feng
- Horticulture Department, Academy of Crop Science, Heilongjiang University, 74 Xuefu Road, Harbin, 150000, Heilongjiang, China.
| | - Dajun Liu
- Horticulture Department, Academy of Crop Science, Heilongjiang University, 74 Xuefu Road, Harbin, 150000, Heilongjiang, China.
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Development of flash-flood tolerant and durable bacterial blight resistant versions of mega rice variety 'Swarna' through marker-assisted backcross breeding. Sci Rep 2019; 9:12810. [PMID: 31488854 PMCID: PMC6728354 DOI: 10.1038/s41598-019-49176-z] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Accepted: 08/19/2019] [Indexed: 01/28/2023] Open
Abstract
Bacterial blight (BB) disease and submergence due to flash flood are the two major constraints for achieving higher yield from rainfed lowland rice. Marker-assisted backcross breeding was followed to develop submergence tolerant and durable BB resistant variety in the background of popular cultivar ‘Swarna’. Four BB resistance genes viz., Xa4, xa5, xa13, Xa21 and Sub1 QTL for submergence tolerance were incorporated into the mega variety. Foreground selection for the five target genes was performed using closely linked markers and tracked in each backcross generations. Background selection in plants carrying the target genes was performed by using 100 simple sequence repeat markers. Amongst backcross derivatives, the plant carrying five target genes and maximum recurrent parent genome content was selected in each generation and hybridized with recipient parent. Eighteen BC3F2 plants were obtained by selfing the selected BC3F1 line. Amongst the pyramided lines, 3 lines were homozygous for all the target genes. Bioassay of the 18 pyramided lines containing BB resistance genes was conducted against different Xoo strains conferred very high levels of resistance to the predominant isolates. The pyramided lines also exhibited submergence tolerance for 14 days. The pyramided lines were similar to the recurrent parent in 14 morpho-quality traits.
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25
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Pradhan SK, Pandit E, Nayak DK, Behera L, Mohapatra T. Genes, pathways and transcription factors involved in seedling stage chilling stress tolerance in indica rice through RNA-Seq analysis. BMC PLANT BIOLOGY 2019; 19:352. [PMID: 31412781 PMCID: PMC6694648 DOI: 10.1186/s12870-019-1922-8] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Accepted: 07/03/2019] [Indexed: 05/18/2023]
Abstract
BACKGROUND Rice plants show yellowing, stunting, withering, reduced tillering and utimately low productivity in susceptible varieties under low temperature stress. Comparative transcriptome analysis was performed to identify novel transcripts, gain new insights into different gene expression and pathways involved in cold tolerance in rice. RESULTS Comparative transcriptome analyses of 5 treatments based on chilling stress exposure revealed more down regulated genes in susceptible and higher up regulated genes in tolerant genotypes. A total of 13930 and 10599 differentially expressed genes (DEGs) were detected in cold susceptible variety (CSV) and cold tolerant variety (CTV), respectively. A continuous increase in DEGs at 6, 12, 24 and 48 h exposure of cold stress was detected in both the genotypes. Gene ontology (GO) analysis revealed 18 CSV and 28 CTV term significantly involved in molecular function, cellular component and biological process. GO classification showed a significant role of transcription regulation, oxygen, lipid binding, catalytic and hydrolase activity for tolerance response. Absence of photosynthesis related genes, storage products like starch and synthesis of other classes of molecules like fatty acids and terpenes during the stress were noticed in susceptible genotype. However, biological regulations, generation of precursor metabolites, signal transduction, photosynthesis, regulation of cellular process, energy and carbohydrate metabolism were seen in tolerant genotype during the stress. KEGG pathway annotation revealed more number of genes regulating different pathways resulting in more tolerant. During early response phase, 24 and 11 DEGs were enriched in CTV and CSV, respectively in energy metabolism pathways. Among the 1583 DEG transcription factors (TF) genes, 69 WRKY, 46 bZIP, 41 NAC, 40 ERF, 31/14 MYB/MYB-related, 22 bHLH, 17 Nin-like 7 HSF and 4C3H were involved during early response phase. Late response phase showed 30 bHLH, 65 NAC, 30 ERF, 26/20 MYB/MYB-related, 11 C3H, 12 HSF, 86 Nin-like, 41 AP2/ERF, 55 bZIP and 98 WRKY members TF genes. The recovery phase included 18 bHLH, 50 NAC, 31 ERF, 24/13 MYB/MYB-related, 4 C3H, 4 HSF, 14 Nin-like, 31 bZIP and 114 WRKY TF genes. CONCLUSIONS Transcriptome analysis of contrasting genotypes for cold tolerance detected the genes, pathways and transcription factors involved in the stress tolerance.
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Affiliation(s)
- Sharat Kumar Pradhan
- Crop Improvement Division, National Rice Research Institute, Cuttack, Odisha India
| | - Elssa Pandit
- Crop Improvement Division, National Rice Research Institute, Cuttack, Odisha India
| | - Deepak Kumar Nayak
- Crop Improvement Division, National Rice Research Institute, Cuttack, Odisha India
| | - Lambodar Behera
- Crop Improvement Division, National Rice Research Institute, Cuttack, Odisha India
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Pradhan SK, Pandit E, Nayak DK, Behera L, Mohapatra T. Genes, pathways and transcription factors involved in seedling stage chilling stress tolerance in indica rice through RNA-Seq analysis. BMC PLANT BIOLOGY 2019; 19:352. [PMID: 31412781 DOI: 10.1186/s12870-12019-11922-12878] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Accepted: 07/03/2019] [Indexed: 05/23/2023]
Abstract
BACKGROUND Rice plants show yellowing, stunting, withering, reduced tillering and utimately low productivity in susceptible varieties under low temperature stress. Comparative transcriptome analysis was performed to identify novel transcripts, gain new insights into different gene expression and pathways involved in cold tolerance in rice. RESULTS Comparative transcriptome analyses of 5 treatments based on chilling stress exposure revealed more down regulated genes in susceptible and higher up regulated genes in tolerant genotypes. A total of 13930 and 10599 differentially expressed genes (DEGs) were detected in cold susceptible variety (CSV) and cold tolerant variety (CTV), respectively. A continuous increase in DEGs at 6, 12, 24 and 48 h exposure of cold stress was detected in both the genotypes. Gene ontology (GO) analysis revealed 18 CSV and 28 CTV term significantly involved in molecular function, cellular component and biological process. GO classification showed a significant role of transcription regulation, oxygen, lipid binding, catalytic and hydrolase activity for tolerance response. Absence of photosynthesis related genes, storage products like starch and synthesis of other classes of molecules like fatty acids and terpenes during the stress were noticed in susceptible genotype. However, biological regulations, generation of precursor metabolites, signal transduction, photosynthesis, regulation of cellular process, energy and carbohydrate metabolism were seen in tolerant genotype during the stress. KEGG pathway annotation revealed more number of genes regulating different pathways resulting in more tolerant. During early response phase, 24 and 11 DEGs were enriched in CTV and CSV, respectively in energy metabolism pathways. Among the 1583 DEG transcription factors (TF) genes, 69 WRKY, 46 bZIP, 41 NAC, 40 ERF, 31/14 MYB/MYB-related, 22 bHLH, 17 Nin-like 7 HSF and 4C3H were involved during early response phase. Late response phase showed 30 bHLH, 65 NAC, 30 ERF, 26/20 MYB/MYB-related, 11 C3H, 12 HSF, 86 Nin-like, 41 AP2/ERF, 55 bZIP and 98 WRKY members TF genes. The recovery phase included 18 bHLH, 50 NAC, 31 ERF, 24/13 MYB/MYB-related, 4 C3H, 4 HSF, 14 Nin-like, 31 bZIP and 114 WRKY TF genes. CONCLUSIONS Transcriptome analysis of contrasting genotypes for cold tolerance detected the genes, pathways and transcription factors involved in the stress tolerance.
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Affiliation(s)
- Sharat Kumar Pradhan
- Crop Improvement Division, National Rice Research Institute, Cuttack, Odisha, India.
| | - Elssa Pandit
- Crop Improvement Division, National Rice Research Institute, Cuttack, Odisha, India.
| | - Deepak Kumar Nayak
- Crop Improvement Division, National Rice Research Institute, Cuttack, Odisha, India
| | - Lambodar Behera
- Crop Improvement Division, National Rice Research Institute, Cuttack, Odisha, India
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Graffelman J, Galván Femenía I, de Cid R, Barceló Vidal C. A Log-Ratio Biplot Approach for Exploring Genetic Relatedness Based on Identity by State. Front Genet 2019; 10:341. [PMID: 31068965 PMCID: PMC6491861 DOI: 10.3389/fgene.2019.00341] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2018] [Accepted: 03/29/2019] [Indexed: 12/31/2022] Open
Abstract
The detection of cryptic relatedness in large population-based cohorts is of great importance in genome research. The usual approach for detecting closely related individuals is to plot allele sharing statistics, based on identity-by-state or identity-by-descent, in a two-dimensional scatterplot. This approach ignores that allele sharing data across individuals has in reality a higher dimensionality, and neither regards the compositional nature of the underlying counts of shared genotypes. In this paper we develop biplot methodology based on log-ratio principal component analysis that overcomes these restrictions. This leads to entirely new graphics that are essentially useful for exploring relatedness in genetic databases from homogeneous populations. The proposed method can be applied in an iterative manner, acting as a looking glass for more remote relationships that are harder to classify. Datasets from the 1,000 Genomes Project and the Genomes For Life-GCAT Project are used to illustrate the proposed method. The discriminatory power of the log-ratio biplot approach is compared with the classical plots in a simulation study. In a non-inbred homogeneous population the classification rate of the log-ratio principal component approach outperforms the classical graphics across the whole allele frequency spectrum, using only identity by state. In these circumstances, simulations show that with 35,000 independent bi-allelic variants, log-ratio principal component analysis, combined with discriminant analysis, can correctly classify relationships up to and including the fourth degree.
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Affiliation(s)
- Jan Graffelman
- Department of Statistics and Operations Research, Technical University of Catalonia, Barcelona, Spain.,Department of Biostatistics, University of Washington, Seattle, WA, United States
| | - Iván Galván Femenía
- Department of Computer Science, Applied Mathematics and Statistics, University of Girona, Girona, Spain.,Genomes For Life - GCAT Lab, Institute for Health Science Research Germans Trias i Pujol (IGTP), Badalona, Spain
| | - Rafael de Cid
- Genomes For Life - GCAT Lab, Institute for Health Science Research Germans Trias i Pujol (IGTP), Badalona, Spain
| | - Carles Barceló Vidal
- Department of Computer Science, Applied Mathematics and Statistics, University of Girona, Girona, Spain
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Pradhan SK, Pandit E, Pawar S, Bharati B, Chatopadhyay K, Singh S, Dash P, Reddy JN. Association mapping reveals multiple QTLs for grain protein content in rice useful for biofortification. Mol Genet Genomics 2019; 294:963-983. [PMID: 30963249 DOI: 10.1007/s00438-019-01556-w] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2018] [Accepted: 03/26/2019] [Indexed: 11/30/2022]
Abstract
Rice is the staple food for majority of the global population. But, rice grain has low protein content (PC). Mapping of QTLs controlling grain PC is essential for enhancement of the trait through breeding programs. A shortlisted panel population for grain protein content was studied for genetic diversity, population structure and association mapping for grain PC. Phenotyping results showed a wide variation for grain PC. The panel population showed a moderate level of genetic diversity estimated through 98 molecular markers. AMOVA and structure analysis indicated linkage disequilibrium for grain PC and deviation of Hardy-Weinberg's expectation. The analysis showed 15% of the variation among populations and 73% among individuals in the panel population. STRUCTURE analysis categorized the panel population into three subpopulations. The analysis also revealed a common primary ancestor for each subpopulation with few admix individuals. Marker-trait association using 98 molecular markers detected 7 strongly associated QTLs for grain PC by both MLM and GLM analysis. Three novel QTLs qPC3.1, qPC5.1 and qPC9.1 were detected for controlling the grain PC. Four reported QTLs viz., qPC3, QPC8, qPC6.1 and qPC12.1 were validated for use in breeding programs. Reported QTLs, qPC6, qPC6.1 and qPC6.2 may be same QTL controlling PC in rice. A very close marker RM407 near to protein controlling QTL, qProt8 and qPC8, was detected. The study provided clue for simultaneous improvement of PC with high grain yield in rice. The strongly associated markers with grain PC, namely qPC3, qPC3.1, qPC5.1, qPC6.1, qPC8, qPC9.1 and qPC12.1, will be useful for their pyramiding for developing protein rich high yielding rice.
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Affiliation(s)
- S K Pradhan
- Crop Improvement Division, ICAR-National Rice Research Institute, Cuttack, India.
| | - E Pandit
- Crop Improvement Division, ICAR-National Rice Research Institute, Cuttack, India
| | - S Pawar
- Crop Improvement Division, ICAR-National Rice Research Institute, Cuttack, India
| | - Barsha Bharati
- Crop Improvement Division, ICAR-National Rice Research Institute, Cuttack, India
| | - K Chatopadhyay
- Crop Improvement Division, ICAR-National Rice Research Institute, Cuttack, India
| | - S Singh
- ICAR-National Research Center for Plant Biotechnology, Pusa, New Delhi, India
| | - P Dash
- ICAR-National Research Center for Plant Biotechnology, Pusa, New Delhi, India
| | - J N Reddy
- Crop Improvement Division, ICAR-National Rice Research Institute, Cuttack, India
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Li X, Wang G, Fu J, Li L, Jia G, Ren L, Lubberstedt T, Wang G, Wang J, Gu R. QTL Mapping in Three Connected Populations Reveals a Set of Consensus Genomic Regions for Low Temperature Germination Ability in Zea mays L. FRONTIERS IN PLANT SCIENCE 2018; 9:65. [PMID: 29445387 PMCID: PMC5797882 DOI: 10.3389/fpls.2018.00065] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Accepted: 01/12/2018] [Indexed: 05/19/2023]
Abstract
Improving seed vigor in response to cold stress is an important breeding objective in maize that allows early sowing. Using two cold tolerant inbred lines 220 and P9-10 and two susceptible lines Y1518 and PH4CV, three connected F2:3 populations were generated for detecting quantitative trait locus (QTL) related to seed low-temperature germination ability. At 10°C, two germination traits (emergence rate and germination index) were collected from a sand bed and three seedling traits (seedling root length, shoot length, and total length) were extracted from paper rolls. Significant correlations were found among all traits in all populations. Via single-population analysis, 43 QTL were detected with explained phenotypic variance of 0.62%∼39.44%. Seventeen QTL explained more than 10% phenotypic variance; of them sixteen (94.12%) inherited favorable alleles from the tolerant lines. After constructing a consensus map, three meta-QTL (mQTL) were identified to include at least two initial QTL from different populations. mQTL1-1 included seven initial QTL for both germination and seedling traits; with three explaining more than 30% phenotypic variance. mQTL2-1 and mQTL9-1 covered two to three initial QTL. The favorable alleles of the QTL within these three mQTL regions were all inherited from the tolerant line 220 and P9-10. These results provided a basis for cloning of genes underlying the mQTL regions to uncover the molecular mechanisms of maize cold tolerance during germination.
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Affiliation(s)
- Xuhui Li
- Center of Seed Science and Technology, Beijing Key Laboratory of Crop Genetics and Breeding, Innovation Center for Seed Technology (Ministry of Agriculture), China Agricultural University, Beijing, China
| | - Guihua Wang
- Center of Seed Science and Technology, Beijing Key Laboratory of Crop Genetics and Breeding, Innovation Center for Seed Technology (Ministry of Agriculture), China Agricultural University, Beijing, China
| | - Junjie Fu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Li Li
- Center of Seed Science and Technology, Beijing Key Laboratory of Crop Genetics and Breeding, Innovation Center for Seed Technology (Ministry of Agriculture), China Agricultural University, Beijing, China
| | - Guangyao Jia
- Center of Seed Science and Technology, Beijing Key Laboratory of Crop Genetics and Breeding, Innovation Center for Seed Technology (Ministry of Agriculture), China Agricultural University, Beijing, China
| | - Lisha Ren
- Center of Seed Science and Technology, Beijing Key Laboratory of Crop Genetics and Breeding, Innovation Center for Seed Technology (Ministry of Agriculture), China Agricultural University, Beijing, China
| | | | - Guoying Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jianhua Wang
- Center of Seed Science and Technology, Beijing Key Laboratory of Crop Genetics and Breeding, Innovation Center for Seed Technology (Ministry of Agriculture), China Agricultural University, Beijing, China
- *Correspondence: Jianhua Wang, Riliang Gu,
| | - Riliang Gu
- Center of Seed Science and Technology, Beijing Key Laboratory of Crop Genetics and Breeding, Innovation Center for Seed Technology (Ministry of Agriculture), China Agricultural University, Beijing, China
- *Correspondence: Jianhua Wang, Riliang Gu,
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