Global identification of quantitative trait loci and candidate genes for cold stress and chilling acclimation in rice through GWAS and RNA-seq

Main conclusion Associated analysis of GWAS with RNA-seq had detected candidate genes responsible for cold stress and chilling acclimation in rice. Haplotypes of two candidate genes and geographic distribution were analyzed. Abstract To explore new candidate genes and genetic resources for cold tolerance improvement in rice, genome-wide association study (GWAS) mapping experiments with 351 rice core germplasms was performed for three traits (survival rate, shoot length and chlorophyll content) under three temperature conditions (normal temperature, cold stress and chilling acclimation), yielding a total of 134 QTLs, of which 54, 59 and 21 QTLs were responsible for normal temperature, cold stress and chilling acclimation conditions, respectively. Integrated analysis of significant SNPs in 134 QTLs further identified 116 QTLs for three temperature treatments, 53, 43 and 18 QTLs responsible for normal temperature, cold stress and chilling acclimation, respectively, and 2 QTLs were responsible for both cold stress and chilling acclimation. Matching differentially expressed genes from RNA-seq to 43 and 18 QTLs for cold stress and chilling acclimation, we identified 69 and 44 trait-associated candidate genes, respectively, to be classified into six and five groups, particularly involved in metabolisms, reactive oxygen species scavenging and hormone signaling. Interestingly, two candidate genes LOC_Os01g04814, encoding a vacuolar protein sorting-associating protein 4B, and LOC_Os01g48440, encoding glycosyltransferase family 43 protein, showed the highest expression levels under chilling acclimation. Haplotype analysis revealed that both genes had a distinctive differentiation with subpopulation. Haplotypes of both genes with more japonica accessions have higher latitude distribution and higher chilling tolerance than the chilling sensitive indica accessions. These findings reveal the new insight into the molecular mechanism and candidate genes for cold stress and chilling acclimation in rice. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Khatab, Ahmed Adel [verfasserIn] Li, Jianguo Hu, Lihua Yang, Jiangyi Fan, Chuchuan Wang, Lingqiang Xie, Guosheng

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Chilling acclimation Cold stress GWAS RNA-seq Rice

Anmerkung:	© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Übergeordnetes Werk:	Enthalten in: Planta - Berlin : Springer, 1925, 256(2022), 4 vom: 14. Sept.
Übergeordnetes Werk:	volume:256 ; year:2022 ; number:4 ; day:14 ; month:09

Links:	Volltext

DOI / URN:	10.1007/s00425-022-03995-z

Katalog-ID:	SPR04809658X

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520			\|a Main conclusion Associated analysis of GWAS with RNA-seq had detected candidate genes responsible for cold stress and chilling acclimation in rice. Haplotypes of two candidate genes and geographic distribution were analyzed. Abstract To explore new candidate genes and genetic resources for cold tolerance improvement in rice, genome-wide association study (GWAS) mapping experiments with 351 rice core germplasms was performed for three traits (survival rate, shoot length and chlorophyll content) under three temperature conditions (normal temperature, cold stress and chilling acclimation), yielding a total of 134 QTLs, of which 54, 59 and 21 QTLs were responsible for normal temperature, cold stress and chilling acclimation conditions, respectively. Integrated analysis of significant SNPs in 134 QTLs further identified 116 QTLs for three temperature treatments, 53, 43 and 18 QTLs responsible for normal temperature, cold stress and chilling acclimation, respectively, and 2 QTLs were responsible for both cold stress and chilling acclimation. Matching differentially expressed genes from RNA-seq to 43 and 18 QTLs for cold stress and chilling acclimation, we identified 69 and 44 trait-associated candidate genes, respectively, to be classified into six and five groups, particularly involved in metabolisms, reactive oxygen species scavenging and hormone signaling. Interestingly, two candidate genes LOC_Os01g04814, encoding a vacuolar protein sorting-associating protein 4B, and LOC_Os01g48440, encoding glycosyltransferase family 43 protein, showed the highest expression levels under chilling acclimation. Haplotype analysis revealed that both genes had a distinctive differentiation with subpopulation. Haplotypes of both genes with more japonica accessions have higher latitude distribution and higher chilling tolerance than the chilling sensitive indica accessions. These findings reveal the new insight into the molecular mechanism and candidate genes for cold stress and chilling acclimation in rice.
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allfields	10.1007/s00425-022-03995-z doi (DE-627)SPR04809658X (SPR)s00425-022-03995-z-e DE-627 ger DE-627 rakwb eng Khatab, Ahmed Adel verfasserin aut Global identification of quantitative trait loci and candidate genes for cold stress and chilling acclimation in rice through GWAS and RNA-seq 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Main conclusion Associated analysis of GWAS with RNA-seq had detected candidate genes responsible for cold stress and chilling acclimation in rice. Haplotypes of two candidate genes and geographic distribution were analyzed. Abstract To explore new candidate genes and genetic resources for cold tolerance improvement in rice, genome-wide association study (GWAS) mapping experiments with 351 rice core germplasms was performed for three traits (survival rate, shoot length and chlorophyll content) under three temperature conditions (normal temperature, cold stress and chilling acclimation), yielding a total of 134 QTLs, of which 54, 59 and 21 QTLs were responsible for normal temperature, cold stress and chilling acclimation conditions, respectively. Integrated analysis of significant SNPs in 134 QTLs further identified 116 QTLs for three temperature treatments, 53, 43 and 18 QTLs responsible for normal temperature, cold stress and chilling acclimation, respectively, and 2 QTLs were responsible for both cold stress and chilling acclimation. Matching differentially expressed genes from RNA-seq to 43 and 18 QTLs for cold stress and chilling acclimation, we identified 69 and 44 trait-associated candidate genes, respectively, to be classified into six and five groups, particularly involved in metabolisms, reactive oxygen species scavenging and hormone signaling. Interestingly, two candidate genes LOC_Os01g04814, encoding a vacuolar protein sorting-associating protein 4B, and LOC_Os01g48440, encoding glycosyltransferase family 43 protein, showed the highest expression levels under chilling acclimation. Haplotype analysis revealed that both genes had a distinctive differentiation with subpopulation. Haplotypes of both genes with more japonica accessions have higher latitude distribution and higher chilling tolerance than the chilling sensitive indica accessions. These findings reveal the new insight into the molecular mechanism and candidate genes for cold stress and chilling acclimation in rice. Chilling acclimation (dpeaa)DE-He213 Cold stress (dpeaa)DE-He213 GWAS (dpeaa)DE-He213 RNA-seq (dpeaa)DE-He213 Rice (dpeaa)DE-He213 Li, Jianguo aut Hu, Lihua aut Yang, Jiangyi aut Fan, Chuchuan aut Wang, Lingqiang aut Xie, Guosheng (orcid)0000-0001-7925-8386 aut Enthalten in Planta Berlin : Springer, 1925 256(2022), 4 vom: 14. Sept. (DE-627)254639100 (DE-600)1463030-8 1432-2048 nnns volume:256 year:2022 number:4 day:14 month:09 https://dx.doi.org/10.1007/s00425-022-03995-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_211 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2946 GBV_ILN_2949 GBV_ILN_2951 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4393 GBV_ILN_4700 AR 256 2022 4 14 09
spelling	10.1007/s00425-022-03995-z doi (DE-627)SPR04809658X (SPR)s00425-022-03995-z-e DE-627 ger DE-627 rakwb eng Khatab, Ahmed Adel verfasserin aut Global identification of quantitative trait loci and candidate genes for cold stress and chilling acclimation in rice through GWAS and RNA-seq 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Main conclusion Associated analysis of GWAS with RNA-seq had detected candidate genes responsible for cold stress and chilling acclimation in rice. Haplotypes of two candidate genes and geographic distribution were analyzed. Abstract To explore new candidate genes and genetic resources for cold tolerance improvement in rice, genome-wide association study (GWAS) mapping experiments with 351 rice core germplasms was performed for three traits (survival rate, shoot length and chlorophyll content) under three temperature conditions (normal temperature, cold stress and chilling acclimation), yielding a total of 134 QTLs, of which 54, 59 and 21 QTLs were responsible for normal temperature, cold stress and chilling acclimation conditions, respectively. Integrated analysis of significant SNPs in 134 QTLs further identified 116 QTLs for three temperature treatments, 53, 43 and 18 QTLs responsible for normal temperature, cold stress and chilling acclimation, respectively, and 2 QTLs were responsible for both cold stress and chilling acclimation. Matching differentially expressed genes from RNA-seq to 43 and 18 QTLs for cold stress and chilling acclimation, we identified 69 and 44 trait-associated candidate genes, respectively, to be classified into six and five groups, particularly involved in metabolisms, reactive oxygen species scavenging and hormone signaling. Interestingly, two candidate genes LOC_Os01g04814, encoding a vacuolar protein sorting-associating protein 4B, and LOC_Os01g48440, encoding glycosyltransferase family 43 protein, showed the highest expression levels under chilling acclimation. Haplotype analysis revealed that both genes had a distinctive differentiation with subpopulation. Haplotypes of both genes with more japonica accessions have higher latitude distribution and higher chilling tolerance than the chilling sensitive indica accessions. These findings reveal the new insight into the molecular mechanism and candidate genes for cold stress and chilling acclimation in rice. Chilling acclimation (dpeaa)DE-He213 Cold stress (dpeaa)DE-He213 GWAS (dpeaa)DE-He213 RNA-seq (dpeaa)DE-He213 Rice (dpeaa)DE-He213 Li, Jianguo aut Hu, Lihua aut Yang, Jiangyi aut Fan, Chuchuan aut Wang, Lingqiang aut Xie, Guosheng (orcid)0000-0001-7925-8386 aut Enthalten in Planta Berlin : Springer, 1925 256(2022), 4 vom: 14. Sept. (DE-627)254639100 (DE-600)1463030-8 1432-2048 nnns volume:256 year:2022 number:4 day:14 month:09 https://dx.doi.org/10.1007/s00425-022-03995-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_211 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2946 GBV_ILN_2949 GBV_ILN_2951 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4393 GBV_ILN_4700 AR 256 2022 4 14 09
allfields_unstemmed	10.1007/s00425-022-03995-z doi (DE-627)SPR04809658X (SPR)s00425-022-03995-z-e DE-627 ger DE-627 rakwb eng Khatab, Ahmed Adel verfasserin aut Global identification of quantitative trait loci and candidate genes for cold stress and chilling acclimation in rice through GWAS and RNA-seq 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Main conclusion Associated analysis of GWAS with RNA-seq had detected candidate genes responsible for cold stress and chilling acclimation in rice. Haplotypes of two candidate genes and geographic distribution were analyzed. Abstract To explore new candidate genes and genetic resources for cold tolerance improvement in rice, genome-wide association study (GWAS) mapping experiments with 351 rice core germplasms was performed for three traits (survival rate, shoot length and chlorophyll content) under three temperature conditions (normal temperature, cold stress and chilling acclimation), yielding a total of 134 QTLs, of which 54, 59 and 21 QTLs were responsible for normal temperature, cold stress and chilling acclimation conditions, respectively. Integrated analysis of significant SNPs in 134 QTLs further identified 116 QTLs for three temperature treatments, 53, 43 and 18 QTLs responsible for normal temperature, cold stress and chilling acclimation, respectively, and 2 QTLs were responsible for both cold stress and chilling acclimation. Matching differentially expressed genes from RNA-seq to 43 and 18 QTLs for cold stress and chilling acclimation, we identified 69 and 44 trait-associated candidate genes, respectively, to be classified into six and five groups, particularly involved in metabolisms, reactive oxygen species scavenging and hormone signaling. Interestingly, two candidate genes LOC_Os01g04814, encoding a vacuolar protein sorting-associating protein 4B, and LOC_Os01g48440, encoding glycosyltransferase family 43 protein, showed the highest expression levels under chilling acclimation. Haplotype analysis revealed that both genes had a distinctive differentiation with subpopulation. Haplotypes of both genes with more japonica accessions have higher latitude distribution and higher chilling tolerance than the chilling sensitive indica accessions. These findings reveal the new insight into the molecular mechanism and candidate genes for cold stress and chilling acclimation in rice. Chilling acclimation (dpeaa)DE-He213 Cold stress (dpeaa)DE-He213 GWAS (dpeaa)DE-He213 RNA-seq (dpeaa)DE-He213 Rice (dpeaa)DE-He213 Li, Jianguo aut Hu, Lihua aut Yang, Jiangyi aut Fan, Chuchuan aut Wang, Lingqiang aut Xie, Guosheng (orcid)0000-0001-7925-8386 aut Enthalten in Planta Berlin : Springer, 1925 256(2022), 4 vom: 14. Sept. (DE-627)254639100 (DE-600)1463030-8 1432-2048 nnns volume:256 year:2022 number:4 day:14 month:09 https://dx.doi.org/10.1007/s00425-022-03995-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_211 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2946 GBV_ILN_2949 GBV_ILN_2951 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4393 GBV_ILN_4700 AR 256 2022 4 14 09
allfieldsGer	10.1007/s00425-022-03995-z doi (DE-627)SPR04809658X (SPR)s00425-022-03995-z-e DE-627 ger DE-627 rakwb eng Khatab, Ahmed Adel verfasserin aut Global identification of quantitative trait loci and candidate genes for cold stress and chilling acclimation in rice through GWAS and RNA-seq 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Main conclusion Associated analysis of GWAS with RNA-seq had detected candidate genes responsible for cold stress and chilling acclimation in rice. Haplotypes of two candidate genes and geographic distribution were analyzed. Abstract To explore new candidate genes and genetic resources for cold tolerance improvement in rice, genome-wide association study (GWAS) mapping experiments with 351 rice core germplasms was performed for three traits (survival rate, shoot length and chlorophyll content) under three temperature conditions (normal temperature, cold stress and chilling acclimation), yielding a total of 134 QTLs, of which 54, 59 and 21 QTLs were responsible for normal temperature, cold stress and chilling acclimation conditions, respectively. Integrated analysis of significant SNPs in 134 QTLs further identified 116 QTLs for three temperature treatments, 53, 43 and 18 QTLs responsible for normal temperature, cold stress and chilling acclimation, respectively, and 2 QTLs were responsible for both cold stress and chilling acclimation. Matching differentially expressed genes from RNA-seq to 43 and 18 QTLs for cold stress and chilling acclimation, we identified 69 and 44 trait-associated candidate genes, respectively, to be classified into six and five groups, particularly involved in metabolisms, reactive oxygen species scavenging and hormone signaling. Interestingly, two candidate genes LOC_Os01g04814, encoding a vacuolar protein sorting-associating protein 4B, and LOC_Os01g48440, encoding glycosyltransferase family 43 protein, showed the highest expression levels under chilling acclimation. Haplotype analysis revealed that both genes had a distinctive differentiation with subpopulation. Haplotypes of both genes with more japonica accessions have higher latitude distribution and higher chilling tolerance than the chilling sensitive indica accessions. These findings reveal the new insight into the molecular mechanism and candidate genes for cold stress and chilling acclimation in rice. Chilling acclimation (dpeaa)DE-He213 Cold stress (dpeaa)DE-He213 GWAS (dpeaa)DE-He213 RNA-seq (dpeaa)DE-He213 Rice (dpeaa)DE-He213 Li, Jianguo aut Hu, Lihua aut Yang, Jiangyi aut Fan, Chuchuan aut Wang, Lingqiang aut Xie, Guosheng (orcid)0000-0001-7925-8386 aut Enthalten in Planta Berlin : Springer, 1925 256(2022), 4 vom: 14. Sept. (DE-627)254639100 (DE-600)1463030-8 1432-2048 nnns volume:256 year:2022 number:4 day:14 month:09 https://dx.doi.org/10.1007/s00425-022-03995-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_211 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2946 GBV_ILN_2949 GBV_ILN_2951 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4393 GBV_ILN_4700 AR 256 2022 4 14 09
allfieldsSound	10.1007/s00425-022-03995-z doi (DE-627)SPR04809658X (SPR)s00425-022-03995-z-e DE-627 ger DE-627 rakwb eng Khatab, Ahmed Adel verfasserin aut Global identification of quantitative trait loci and candidate genes for cold stress and chilling acclimation in rice through GWAS and RNA-seq 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Main conclusion Associated analysis of GWAS with RNA-seq had detected candidate genes responsible for cold stress and chilling acclimation in rice. Haplotypes of two candidate genes and geographic distribution were analyzed. Abstract To explore new candidate genes and genetic resources for cold tolerance improvement in rice, genome-wide association study (GWAS) mapping experiments with 351 rice core germplasms was performed for three traits (survival rate, shoot length and chlorophyll content) under three temperature conditions (normal temperature, cold stress and chilling acclimation), yielding a total of 134 QTLs, of which 54, 59 and 21 QTLs were responsible for normal temperature, cold stress and chilling acclimation conditions, respectively. Integrated analysis of significant SNPs in 134 QTLs further identified 116 QTLs for three temperature treatments, 53, 43 and 18 QTLs responsible for normal temperature, cold stress and chilling acclimation, respectively, and 2 QTLs were responsible for both cold stress and chilling acclimation. Matching differentially expressed genes from RNA-seq to 43 and 18 QTLs for cold stress and chilling acclimation, we identified 69 and 44 trait-associated candidate genes, respectively, to be classified into six and five groups, particularly involved in metabolisms, reactive oxygen species scavenging and hormone signaling. Interestingly, two candidate genes LOC_Os01g04814, encoding a vacuolar protein sorting-associating protein 4B, and LOC_Os01g48440, encoding glycosyltransferase family 43 protein, showed the highest expression levels under chilling acclimation. Haplotype analysis revealed that both genes had a distinctive differentiation with subpopulation. Haplotypes of both genes with more japonica accessions have higher latitude distribution and higher chilling tolerance than the chilling sensitive indica accessions. These findings reveal the new insight into the molecular mechanism and candidate genes for cold stress and chilling acclimation in rice. Chilling acclimation (dpeaa)DE-He213 Cold stress (dpeaa)DE-He213 GWAS (dpeaa)DE-He213 RNA-seq (dpeaa)DE-He213 Rice (dpeaa)DE-He213 Li, Jianguo aut Hu, Lihua aut Yang, Jiangyi aut Fan, Chuchuan aut Wang, Lingqiang aut Xie, Guosheng (orcid)0000-0001-7925-8386 aut Enthalten in Planta Berlin : Springer, 1925 256(2022), 4 vom: 14. Sept. (DE-627)254639100 (DE-600)1463030-8 1432-2048 nnns volume:256 year:2022 number:4 day:14 month:09 https://dx.doi.org/10.1007/s00425-022-03995-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_211 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2946 GBV_ILN_2949 GBV_ILN_2951 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4393 GBV_ILN_4700 AR 256 2022 4 14 09
language	English
source	Enthalten in Planta 256(2022), 4 vom: 14. Sept. volume:256 year:2022 number:4 day:14 month:09
sourceStr	Enthalten in Planta 256(2022), 4 vom: 14. Sept. volume:256 year:2022 number:4 day:14 month:09
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Chilling acclimation Cold stress GWAS RNA-seq Rice
isfreeaccess_bool	false
container_title	Planta
authorswithroles_txt_mv	Khatab, Ahmed Adel @@aut@@ Li, Jianguo @@aut@@ Hu, Lihua @@aut@@ Yang, Jiangyi @@aut@@ Fan, Chuchuan @@aut@@ Wang, Lingqiang @@aut@@ Xie, Guosheng @@aut@@
publishDateDaySort_date	2022-09-14T00:00:00Z
hierarchy_top_id	254639100
id	SPR04809658X
language_de	englisch
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Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Main conclusion Associated analysis of GWAS with RNA-seq had detected candidate genes responsible for cold stress and chilling acclimation in rice. Haplotypes of two candidate genes and geographic distribution were analyzed. Abstract To explore new candidate genes and genetic resources for cold tolerance improvement in rice, genome-wide association study (GWAS) mapping experiments with 351 rice core germplasms was performed for three traits (survival rate, shoot length and chlorophyll content) under three temperature conditions (normal temperature, cold stress and chilling acclimation), yielding a total of 134 QTLs, of which 54, 59 and 21 QTLs were responsible for normal temperature, cold stress and chilling acclimation conditions, respectively. Integrated analysis of significant SNPs in 134 QTLs further identified 116 QTLs for three temperature treatments, 53, 43 and 18 QTLs responsible for normal temperature, cold stress and chilling acclimation, respectively, and 2 QTLs were responsible for both cold stress and chilling acclimation. Matching differentially expressed genes from RNA-seq to 43 and 18 QTLs for cold stress and chilling acclimation, we identified 69 and 44 trait-associated candidate genes, respectively, to be classified into six and five groups, particularly involved in metabolisms, reactive oxygen species scavenging and hormone signaling. Interestingly, two candidate genes LOC_Os01g04814, encoding a vacuolar protein sorting-associating protein 4B, and LOC_Os01g48440, encoding glycosyltransferase family 43 protein, showed the highest expression levels under chilling acclimation. Haplotype analysis revealed that both genes had a distinctive differentiation with subpopulation. Haplotypes of both genes with more japonica accessions have higher latitude distribution and higher chilling tolerance than the chilling sensitive indica accessions. 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author	Khatab, Ahmed Adel
spellingShingle	Khatab, Ahmed Adel misc Chilling acclimation misc Cold stress misc GWAS misc RNA-seq misc Rice Global identification of quantitative trait loci and candidate genes for cold stress and chilling acclimation in rice through GWAS and RNA-seq
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topic_title	Global identification of quantitative trait loci and candidate genes for cold stress and chilling acclimation in rice through GWAS and RNA-seq Chilling acclimation (dpeaa)DE-He213 Cold stress (dpeaa)DE-He213 GWAS (dpeaa)DE-He213 RNA-seq (dpeaa)DE-He213 Rice (dpeaa)DE-He213
topic	misc Chilling acclimation misc Cold stress misc GWAS misc RNA-seq misc Rice
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title	Global identification of quantitative trait loci and candidate genes for cold stress and chilling acclimation in rice through GWAS and RNA-seq
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title_full	Global identification of quantitative trait loci and candidate genes for cold stress and chilling acclimation in rice through GWAS and RNA-seq
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author_browse	Khatab, Ahmed Adel Li, Jianguo Hu, Lihua Yang, Jiangyi Fan, Chuchuan Wang, Lingqiang Xie, Guosheng
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title_sort	global identification of quantitative trait loci and candidate genes for cold stress and chilling acclimation in rice through gwas and rna-seq
title_auth	Global identification of quantitative trait loci and candidate genes for cold stress and chilling acclimation in rice through GWAS and RNA-seq
abstract	Main conclusion Associated analysis of GWAS with RNA-seq had detected candidate genes responsible for cold stress and chilling acclimation in rice. Haplotypes of two candidate genes and geographic distribution were analyzed. Abstract To explore new candidate genes and genetic resources for cold tolerance improvement in rice, genome-wide association study (GWAS) mapping experiments with 351 rice core germplasms was performed for three traits (survival rate, shoot length and chlorophyll content) under three temperature conditions (normal temperature, cold stress and chilling acclimation), yielding a total of 134 QTLs, of which 54, 59 and 21 QTLs were responsible for normal temperature, cold stress and chilling acclimation conditions, respectively. Integrated analysis of significant SNPs in 134 QTLs further identified 116 QTLs for three temperature treatments, 53, 43 and 18 QTLs responsible for normal temperature, cold stress and chilling acclimation, respectively, and 2 QTLs were responsible for both cold stress and chilling acclimation. Matching differentially expressed genes from RNA-seq to 43 and 18 QTLs for cold stress and chilling acclimation, we identified 69 and 44 trait-associated candidate genes, respectively, to be classified into six and five groups, particularly involved in metabolisms, reactive oxygen species scavenging and hormone signaling. Interestingly, two candidate genes LOC_Os01g04814, encoding a vacuolar protein sorting-associating protein 4B, and LOC_Os01g48440, encoding glycosyltransferase family 43 protein, showed the highest expression levels under chilling acclimation. Haplotype analysis revealed that both genes had a distinctive differentiation with subpopulation. Haplotypes of both genes with more japonica accessions have higher latitude distribution and higher chilling tolerance than the chilling sensitive indica accessions. These findings reveal the new insight into the molecular mechanism and candidate genes for cold stress and chilling acclimation in rice. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
abstractGer	Main conclusion Associated analysis of GWAS with RNA-seq had detected candidate genes responsible for cold stress and chilling acclimation in rice. Haplotypes of two candidate genes and geographic distribution were analyzed. Abstract To explore new candidate genes and genetic resources for cold tolerance improvement in rice, genome-wide association study (GWAS) mapping experiments with 351 rice core germplasms was performed for three traits (survival rate, shoot length and chlorophyll content) under three temperature conditions (normal temperature, cold stress and chilling acclimation), yielding a total of 134 QTLs, of which 54, 59 and 21 QTLs were responsible for normal temperature, cold stress and chilling acclimation conditions, respectively. Integrated analysis of significant SNPs in 134 QTLs further identified 116 QTLs for three temperature treatments, 53, 43 and 18 QTLs responsible for normal temperature, cold stress and chilling acclimation, respectively, and 2 QTLs were responsible for both cold stress and chilling acclimation. Matching differentially expressed genes from RNA-seq to 43 and 18 QTLs for cold stress and chilling acclimation, we identified 69 and 44 trait-associated candidate genes, respectively, to be classified into six and five groups, particularly involved in metabolisms, reactive oxygen species scavenging and hormone signaling. Interestingly, two candidate genes LOC_Os01g04814, encoding a vacuolar protein sorting-associating protein 4B, and LOC_Os01g48440, encoding glycosyltransferase family 43 protein, showed the highest expression levels under chilling acclimation. Haplotype analysis revealed that both genes had a distinctive differentiation with subpopulation. Haplotypes of both genes with more japonica accessions have higher latitude distribution and higher chilling tolerance than the chilling sensitive indica accessions. These findings reveal the new insight into the molecular mechanism and candidate genes for cold stress and chilling acclimation in rice. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
abstract_unstemmed	Main conclusion Associated analysis of GWAS with RNA-seq had detected candidate genes responsible for cold stress and chilling acclimation in rice. Haplotypes of two candidate genes and geographic distribution were analyzed. Abstract To explore new candidate genes and genetic resources for cold tolerance improvement in rice, genome-wide association study (GWAS) mapping experiments with 351 rice core germplasms was performed for three traits (survival rate, shoot length and chlorophyll content) under three temperature conditions (normal temperature, cold stress and chilling acclimation), yielding a total of 134 QTLs, of which 54, 59 and 21 QTLs were responsible for normal temperature, cold stress and chilling acclimation conditions, respectively. Integrated analysis of significant SNPs in 134 QTLs further identified 116 QTLs for three temperature treatments, 53, 43 and 18 QTLs responsible for normal temperature, cold stress and chilling acclimation, respectively, and 2 QTLs were responsible for both cold stress and chilling acclimation. Matching differentially expressed genes from RNA-seq to 43 and 18 QTLs for cold stress and chilling acclimation, we identified 69 and 44 trait-associated candidate genes, respectively, to be classified into six and five groups, particularly involved in metabolisms, reactive oxygen species scavenging and hormone signaling. Interestingly, two candidate genes LOC_Os01g04814, encoding a vacuolar protein sorting-associating protein 4B, and LOC_Os01g48440, encoding glycosyltransferase family 43 protein, showed the highest expression levels under chilling acclimation. Haplotype analysis revealed that both genes had a distinctive differentiation with subpopulation. Haplotypes of both genes with more japonica accessions have higher latitude distribution and higher chilling tolerance than the chilling sensitive indica accessions. These findings reveal the new insight into the molecular mechanism and candidate genes for cold stress and chilling acclimation in rice. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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title_short	Global identification of quantitative trait loci and candidate genes for cold stress and chilling acclimation in rice through GWAS and RNA-seq
url	https://dx.doi.org/10.1007/s00425-022-03995-z
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author2	Li, Jianguo Hu, Lihua Yang, Jiangyi Fan, Chuchuan Wang, Lingqiang Xie, Guosheng
author2Str	Li, Jianguo Hu, Lihua Yang, Jiangyi Fan, Chuchuan Wang, Lingqiang Xie, Guosheng
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doi_str	10.1007/s00425-022-03995-z
up_date	2024-07-03T16:59:03.577Z
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Global identification of quantitative trait loci and candidate genes for cold stress and chilling acclimation in rice through GWAS and RNA-seq

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