Pyramiding QTLs using multiparental advanced generation introgression lines enhances salinity tolerance in rice
Abstract Rice is a major cereal that nourishes more than half of the global population. But rice lands are under threat from soil salinity leading to reduced productivity. Salinity stress tolerance is challenging due to the multigenic trait and complex tolerance mechanisms. QTL pyramiding is one of...
Ausführliche Beschreibung
Autor*in: |
Chapagain, Sandeep [verfasserIn] |
---|
Format: |
E-Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2023 |
---|
Schlagwörter: |
---|
Anmerkung: |
© The Author(s) under exclusive licence to Franciszek Górski Institute of Plant Physiology, Polish Academy of Sciences, Kraków 2023. Springer Nature or its licensor (e.g. a society or other partner) 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: Acta physiologiae plantarum - Berlin : Springer, 1997, 45(2023), 4 vom: 15. März |
---|---|
Übergeordnetes Werk: |
volume:45 ; year:2023 ; number:4 ; day:15 ; month:03 |
Links: |
---|
DOI / URN: |
10.1007/s11738-023-03539-2 |
---|
Katalog-ID: |
SPR049853147 |
---|
LEADER | 01000naa a22002652 4500 | ||
---|---|---|---|
001 | SPR049853147 | ||
003 | DE-627 | ||
005 | 20230328064816.0 | ||
007 | cr uuu---uuuuu | ||
008 | 230328s2023 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1007/s11738-023-03539-2 |2 doi | |
035 | |a (DE-627)SPR049853147 | ||
035 | |a (SPR)s11738-023-03539-2-e | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 1 | |a Chapagain, Sandeep |e verfasserin |4 aut | |
245 | 1 | 0 | |a Pyramiding QTLs using multiparental advanced generation introgression lines enhances salinity tolerance in rice |
264 | 1 | |c 2023 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
500 | |a © The Author(s) under exclusive licence to Franciszek Górski Institute of Plant Physiology, Polish Academy of Sciences, Kraków 2023. Springer Nature or its licensor (e.g. a society or other partner) 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. | ||
520 | |a Abstract Rice is a major cereal that nourishes more than half of the global population. But rice lands are under threat from soil salinity leading to reduced productivity. Salinity stress tolerance is challenging due to the multigenic trait and complex tolerance mechanisms. QTL pyramiding is one of the efficient approaches to stack desired genes and QTLs from multiple donors. This study developed three populations using multiple salt-tolerant introgression lines (ILs) to accumulate beneficial alleles/QTLs and identify improved salt-tolerant breeding lines. To accumulate the salt-tolerant alleles from salt-tolerant donors, we used salt-tolerant ILs of Pokkali and Nona Bokra in the CL151 background (CLPK683 and CLPK757) and Jupiter background (JN100 and JN520), respectively. The QTLs for shoot $ Na^{+} $ and $ K^{+} $ content, qNa2.2, qK2.1, and qK2.2, from JN100 and qK4.1 and qK8.1 from JN520 were targeted using the molecular markers linked to these QTLs. Both phenotypic and genotypic selection methods were employed to advance the populations. The $ F_{5} $ populations of each cross were finally evaluated for seedling-stage salt tolerance. The visual salt injury score (SIS) and shoot $ Na^{+} $ and $ K^{+} $ concentration in selected lines indicated salt tolerance higher than the IL parents. The targeted QTLs were detected in most salt-tolerant lines. The salt-tolerant breeding lines identified in this study constitute a valuable resource for investigating the physiological and molecular basis of salt tolerance and identifying superior alleles of salt-tolerance genes for use in breeding programs. | ||
650 | 4 | |a Introgression line |7 (dpeaa)DE-He213 | |
650 | 4 | |a Marker-assisted selection |7 (dpeaa)DE-He213 | |
650 | 4 | |a Quantitative trait loci |7 (dpeaa)DE-He213 | |
650 | 4 | |a QTL pyramiding |7 (dpeaa)DE-He213 | |
650 | 4 | |a Salt stress |7 (dpeaa)DE-He213 | |
700 | 1 | |a Pruthi, Rajat |4 aut | |
700 | 1 | |a Subudhi, Prasanta K. |0 (orcid)0000-0003-0512-9076 |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Acta physiologiae plantarum |d Berlin : Springer, 1997 |g 45(2023), 4 vom: 15. März |w (DE-627)516024906 |w (DE-600)2245807-4 |x 1861-1664 |7 nnns |
773 | 1 | 8 | |g volume:45 |g year:2023 |g number:4 |g day:15 |g month:03 |
856 | 4 | 0 | |u https://dx.doi.org/10.1007/s11738-023-03539-2 |z lizenzpflichtig |3 Volltext |
912 | |a GBV_USEFLAG_A | ||
912 | |a SYSFLAG_A | ||
912 | |a GBV_SPRINGER | ||
912 | |a GBV_ILN_11 | ||
912 | |a GBV_ILN_20 | ||
912 | |a GBV_ILN_22 | ||
912 | |a GBV_ILN_23 | ||
912 | |a GBV_ILN_24 | ||
912 | |a GBV_ILN_31 | ||
912 | |a GBV_ILN_32 | ||
912 | |a GBV_ILN_39 | ||
912 | |a GBV_ILN_40 | ||
912 | |a GBV_ILN_60 | ||
912 | |a GBV_ILN_62 | ||
912 | |a GBV_ILN_63 | ||
912 | |a GBV_ILN_65 | ||
912 | |a GBV_ILN_69 | ||
912 | |a GBV_ILN_70 | ||
912 | |a GBV_ILN_73 | ||
912 | |a GBV_ILN_74 | ||
912 | |a GBV_ILN_90 | ||
912 | |a GBV_ILN_95 | ||
912 | |a GBV_ILN_100 | ||
912 | |a GBV_ILN_105 | ||
912 | |a GBV_ILN_110 | ||
912 | |a GBV_ILN_120 | ||
912 | |a GBV_ILN_138 | ||
912 | |a GBV_ILN_150 | ||
912 | |a GBV_ILN_151 | ||
912 | |a GBV_ILN_152 | ||
912 | |a GBV_ILN_161 | ||
912 | |a GBV_ILN_170 | ||
912 | |a GBV_ILN_171 | ||
912 | |a GBV_ILN_187 | ||
912 | |a GBV_ILN_213 | ||
912 | |a GBV_ILN_224 | ||
912 | |a GBV_ILN_230 | ||
912 | |a GBV_ILN_250 | ||
912 | |a GBV_ILN_281 | ||
912 | |a GBV_ILN_285 | ||
912 | |a GBV_ILN_293 | ||
912 | |a GBV_ILN_370 | ||
912 | |a GBV_ILN_602 | ||
912 | |a GBV_ILN_636 | ||
912 | |a GBV_ILN_702 | ||
912 | |a GBV_ILN_2001 | ||
912 | |a GBV_ILN_2003 | ||
912 | |a GBV_ILN_2004 | ||
912 | |a GBV_ILN_2005 | ||
912 | |a GBV_ILN_2006 | ||
912 | |a GBV_ILN_2007 | ||
912 | |a GBV_ILN_2008 | ||
912 | |a GBV_ILN_2009 | ||
912 | |a GBV_ILN_2010 | ||
912 | |a GBV_ILN_2011 | ||
912 | |a GBV_ILN_2014 | ||
912 | |a GBV_ILN_2015 | ||
912 | |a GBV_ILN_2018 | ||
912 | |a GBV_ILN_2020 | ||
912 | |a GBV_ILN_2021 | ||
912 | |a GBV_ILN_2025 | ||
912 | |a GBV_ILN_2026 | ||
912 | |a GBV_ILN_2027 | ||
912 | |a GBV_ILN_2031 | ||
912 | |a GBV_ILN_2034 | ||
912 | |a GBV_ILN_2037 | ||
912 | |a GBV_ILN_2038 | ||
912 | |a GBV_ILN_2039 | ||
912 | |a GBV_ILN_2044 | ||
912 | |a GBV_ILN_2048 | ||
912 | |a GBV_ILN_2049 | ||
912 | |a GBV_ILN_2050 | ||
912 | |a GBV_ILN_2055 | ||
912 | |a GBV_ILN_2056 | ||
912 | |a GBV_ILN_2057 | ||
912 | |a GBV_ILN_2059 | ||
912 | |a GBV_ILN_2061 | ||
912 | |a GBV_ILN_2064 | ||
912 | |a GBV_ILN_2065 | ||
912 | |a GBV_ILN_2068 | ||
912 | |a GBV_ILN_2088 | ||
912 | |a GBV_ILN_2093 | ||
912 | |a GBV_ILN_2106 | ||
912 | |a GBV_ILN_2107 | ||
912 | |a GBV_ILN_2108 | ||
912 | |a GBV_ILN_2110 | ||
912 | |a GBV_ILN_2111 | ||
912 | |a GBV_ILN_2112 | ||
912 | |a GBV_ILN_2113 | ||
912 | |a GBV_ILN_2118 | ||
912 | |a GBV_ILN_2122 | ||
912 | |a GBV_ILN_2129 | ||
912 | |a GBV_ILN_2143 | ||
912 | |a GBV_ILN_2144 | ||
912 | |a GBV_ILN_2147 | ||
912 | |a GBV_ILN_2148 | ||
912 | |a GBV_ILN_2152 | ||
912 | |a GBV_ILN_2153 | ||
912 | |a GBV_ILN_2188 | ||
912 | |a GBV_ILN_2190 | ||
912 | |a GBV_ILN_2232 | ||
912 | |a GBV_ILN_2336 | ||
912 | |a GBV_ILN_2446 | ||
912 | |a GBV_ILN_2470 | ||
912 | |a GBV_ILN_2472 | ||
912 | |a GBV_ILN_2507 | ||
912 | |a GBV_ILN_2522 | ||
912 | |a GBV_ILN_2548 | ||
912 | |a GBV_ILN_4035 | ||
912 | |a GBV_ILN_4037 | ||
912 | |a GBV_ILN_4046 | ||
912 | |a GBV_ILN_4112 | ||
912 | |a GBV_ILN_4125 | ||
912 | |a GBV_ILN_4126 | ||
912 | |a GBV_ILN_4242 | ||
912 | |a GBV_ILN_4246 | ||
912 | |a GBV_ILN_4249 | ||
912 | |a GBV_ILN_4251 | ||
912 | |a GBV_ILN_4305 | ||
912 | |a GBV_ILN_4306 | ||
912 | |a GBV_ILN_4307 | ||
912 | |a GBV_ILN_4313 | ||
912 | |a GBV_ILN_4322 | ||
912 | |a GBV_ILN_4323 | ||
912 | |a GBV_ILN_4324 | ||
912 | |a GBV_ILN_4325 | ||
912 | |a GBV_ILN_4326 | ||
912 | |a GBV_ILN_4328 | ||
912 | |a GBV_ILN_4333 | ||
912 | |a GBV_ILN_4334 | ||
912 | |a GBV_ILN_4335 | ||
912 | |a GBV_ILN_4336 | ||
912 | |a GBV_ILN_4338 | ||
912 | |a GBV_ILN_4393 | ||
912 | |a GBV_ILN_4700 | ||
951 | |a AR | ||
952 | |d 45 |j 2023 |e 4 |b 15 |c 03 |
author_variant |
s c sc r p rp p k s pk pks |
---|---|
matchkey_str |
article:18611664:2023----::yaiigtssnmliaetldacdeeainnrgesolnsna |
hierarchy_sort_str |
2023 |
publishDate |
2023 |
allfields |
10.1007/s11738-023-03539-2 doi (DE-627)SPR049853147 (SPR)s11738-023-03539-2-e DE-627 ger DE-627 rakwb eng Chapagain, Sandeep verfasserin aut Pyramiding QTLs using multiparental advanced generation introgression lines enhances salinity tolerance in rice 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) under exclusive licence to Franciszek Górski Institute of Plant Physiology, Polish Academy of Sciences, Kraków 2023. Springer Nature or its licensor (e.g. a society or other partner) 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 Rice is a major cereal that nourishes more than half of the global population. But rice lands are under threat from soil salinity leading to reduced productivity. Salinity stress tolerance is challenging due to the multigenic trait and complex tolerance mechanisms. QTL pyramiding is one of the efficient approaches to stack desired genes and QTLs from multiple donors. This study developed three populations using multiple salt-tolerant introgression lines (ILs) to accumulate beneficial alleles/QTLs and identify improved salt-tolerant breeding lines. To accumulate the salt-tolerant alleles from salt-tolerant donors, we used salt-tolerant ILs of Pokkali and Nona Bokra in the CL151 background (CLPK683 and CLPK757) and Jupiter background (JN100 and JN520), respectively. The QTLs for shoot $ Na^{+} $ and $ K^{+} $ content, qNa2.2, qK2.1, and qK2.2, from JN100 and qK4.1 and qK8.1 from JN520 were targeted using the molecular markers linked to these QTLs. Both phenotypic and genotypic selection methods were employed to advance the populations. The $ F_{5} $ populations of each cross were finally evaluated for seedling-stage salt tolerance. The visual salt injury score (SIS) and shoot $ Na^{+} $ and $ K^{+} $ concentration in selected lines indicated salt tolerance higher than the IL parents. The targeted QTLs were detected in most salt-tolerant lines. The salt-tolerant breeding lines identified in this study constitute a valuable resource for investigating the physiological and molecular basis of salt tolerance and identifying superior alleles of salt-tolerance genes for use in breeding programs. Introgression line (dpeaa)DE-He213 Marker-assisted selection (dpeaa)DE-He213 Quantitative trait loci (dpeaa)DE-He213 QTL pyramiding (dpeaa)DE-He213 Salt stress (dpeaa)DE-He213 Pruthi, Rajat aut Subudhi, Prasanta K. (orcid)0000-0003-0512-9076 aut Enthalten in Acta physiologiae plantarum Berlin : Springer, 1997 45(2023), 4 vom: 15. März (DE-627)516024906 (DE-600)2245807-4 1861-1664 nnns volume:45 year:2023 number:4 day:15 month:03 https://dx.doi.org/10.1007/s11738-023-03539-2 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_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 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_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_4393 GBV_ILN_4700 AR 45 2023 4 15 03 |
spelling |
10.1007/s11738-023-03539-2 doi (DE-627)SPR049853147 (SPR)s11738-023-03539-2-e DE-627 ger DE-627 rakwb eng Chapagain, Sandeep verfasserin aut Pyramiding QTLs using multiparental advanced generation introgression lines enhances salinity tolerance in rice 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) under exclusive licence to Franciszek Górski Institute of Plant Physiology, Polish Academy of Sciences, Kraków 2023. Springer Nature or its licensor (e.g. a society or other partner) 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 Rice is a major cereal that nourishes more than half of the global population. But rice lands are under threat from soil salinity leading to reduced productivity. Salinity stress tolerance is challenging due to the multigenic trait and complex tolerance mechanisms. QTL pyramiding is one of the efficient approaches to stack desired genes and QTLs from multiple donors. This study developed three populations using multiple salt-tolerant introgression lines (ILs) to accumulate beneficial alleles/QTLs and identify improved salt-tolerant breeding lines. To accumulate the salt-tolerant alleles from salt-tolerant donors, we used salt-tolerant ILs of Pokkali and Nona Bokra in the CL151 background (CLPK683 and CLPK757) and Jupiter background (JN100 and JN520), respectively. The QTLs for shoot $ Na^{+} $ and $ K^{+} $ content, qNa2.2, qK2.1, and qK2.2, from JN100 and qK4.1 and qK8.1 from JN520 were targeted using the molecular markers linked to these QTLs. Both phenotypic and genotypic selection methods were employed to advance the populations. The $ F_{5} $ populations of each cross were finally evaluated for seedling-stage salt tolerance. The visual salt injury score (SIS) and shoot $ Na^{+} $ and $ K^{+} $ concentration in selected lines indicated salt tolerance higher than the IL parents. The targeted QTLs were detected in most salt-tolerant lines. The salt-tolerant breeding lines identified in this study constitute a valuable resource for investigating the physiological and molecular basis of salt tolerance and identifying superior alleles of salt-tolerance genes for use in breeding programs. Introgression line (dpeaa)DE-He213 Marker-assisted selection (dpeaa)DE-He213 Quantitative trait loci (dpeaa)DE-He213 QTL pyramiding (dpeaa)DE-He213 Salt stress (dpeaa)DE-He213 Pruthi, Rajat aut Subudhi, Prasanta K. (orcid)0000-0003-0512-9076 aut Enthalten in Acta physiologiae plantarum Berlin : Springer, 1997 45(2023), 4 vom: 15. März (DE-627)516024906 (DE-600)2245807-4 1861-1664 nnns volume:45 year:2023 number:4 day:15 month:03 https://dx.doi.org/10.1007/s11738-023-03539-2 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_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 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_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_4393 GBV_ILN_4700 AR 45 2023 4 15 03 |
allfields_unstemmed |
10.1007/s11738-023-03539-2 doi (DE-627)SPR049853147 (SPR)s11738-023-03539-2-e DE-627 ger DE-627 rakwb eng Chapagain, Sandeep verfasserin aut Pyramiding QTLs using multiparental advanced generation introgression lines enhances salinity tolerance in rice 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) under exclusive licence to Franciszek Górski Institute of Plant Physiology, Polish Academy of Sciences, Kraków 2023. Springer Nature or its licensor (e.g. a society or other partner) 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 Rice is a major cereal that nourishes more than half of the global population. But rice lands are under threat from soil salinity leading to reduced productivity. Salinity stress tolerance is challenging due to the multigenic trait and complex tolerance mechanisms. QTL pyramiding is one of the efficient approaches to stack desired genes and QTLs from multiple donors. This study developed three populations using multiple salt-tolerant introgression lines (ILs) to accumulate beneficial alleles/QTLs and identify improved salt-tolerant breeding lines. To accumulate the salt-tolerant alleles from salt-tolerant donors, we used salt-tolerant ILs of Pokkali and Nona Bokra in the CL151 background (CLPK683 and CLPK757) and Jupiter background (JN100 and JN520), respectively. The QTLs for shoot $ Na^{+} $ and $ K^{+} $ content, qNa2.2, qK2.1, and qK2.2, from JN100 and qK4.1 and qK8.1 from JN520 were targeted using the molecular markers linked to these QTLs. Both phenotypic and genotypic selection methods were employed to advance the populations. The $ F_{5} $ populations of each cross were finally evaluated for seedling-stage salt tolerance. The visual salt injury score (SIS) and shoot $ Na^{+} $ and $ K^{+} $ concentration in selected lines indicated salt tolerance higher than the IL parents. The targeted QTLs were detected in most salt-tolerant lines. The salt-tolerant breeding lines identified in this study constitute a valuable resource for investigating the physiological and molecular basis of salt tolerance and identifying superior alleles of salt-tolerance genes for use in breeding programs. Introgression line (dpeaa)DE-He213 Marker-assisted selection (dpeaa)DE-He213 Quantitative trait loci (dpeaa)DE-He213 QTL pyramiding (dpeaa)DE-He213 Salt stress (dpeaa)DE-He213 Pruthi, Rajat aut Subudhi, Prasanta K. (orcid)0000-0003-0512-9076 aut Enthalten in Acta physiologiae plantarum Berlin : Springer, 1997 45(2023), 4 vom: 15. März (DE-627)516024906 (DE-600)2245807-4 1861-1664 nnns volume:45 year:2023 number:4 day:15 month:03 https://dx.doi.org/10.1007/s11738-023-03539-2 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_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 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_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_4393 GBV_ILN_4700 AR 45 2023 4 15 03 |
allfieldsGer |
10.1007/s11738-023-03539-2 doi (DE-627)SPR049853147 (SPR)s11738-023-03539-2-e DE-627 ger DE-627 rakwb eng Chapagain, Sandeep verfasserin aut Pyramiding QTLs using multiparental advanced generation introgression lines enhances salinity tolerance in rice 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) under exclusive licence to Franciszek Górski Institute of Plant Physiology, Polish Academy of Sciences, Kraków 2023. Springer Nature or its licensor (e.g. a society or other partner) 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 Rice is a major cereal that nourishes more than half of the global population. But rice lands are under threat from soil salinity leading to reduced productivity. Salinity stress tolerance is challenging due to the multigenic trait and complex tolerance mechanisms. QTL pyramiding is one of the efficient approaches to stack desired genes and QTLs from multiple donors. This study developed three populations using multiple salt-tolerant introgression lines (ILs) to accumulate beneficial alleles/QTLs and identify improved salt-tolerant breeding lines. To accumulate the salt-tolerant alleles from salt-tolerant donors, we used salt-tolerant ILs of Pokkali and Nona Bokra in the CL151 background (CLPK683 and CLPK757) and Jupiter background (JN100 and JN520), respectively. The QTLs for shoot $ Na^{+} $ and $ K^{+} $ content, qNa2.2, qK2.1, and qK2.2, from JN100 and qK4.1 and qK8.1 from JN520 were targeted using the molecular markers linked to these QTLs. Both phenotypic and genotypic selection methods were employed to advance the populations. The $ F_{5} $ populations of each cross were finally evaluated for seedling-stage salt tolerance. The visual salt injury score (SIS) and shoot $ Na^{+} $ and $ K^{+} $ concentration in selected lines indicated salt tolerance higher than the IL parents. The targeted QTLs were detected in most salt-tolerant lines. The salt-tolerant breeding lines identified in this study constitute a valuable resource for investigating the physiological and molecular basis of salt tolerance and identifying superior alleles of salt-tolerance genes for use in breeding programs. Introgression line (dpeaa)DE-He213 Marker-assisted selection (dpeaa)DE-He213 Quantitative trait loci (dpeaa)DE-He213 QTL pyramiding (dpeaa)DE-He213 Salt stress (dpeaa)DE-He213 Pruthi, Rajat aut Subudhi, Prasanta K. (orcid)0000-0003-0512-9076 aut Enthalten in Acta physiologiae plantarum Berlin : Springer, 1997 45(2023), 4 vom: 15. März (DE-627)516024906 (DE-600)2245807-4 1861-1664 nnns volume:45 year:2023 number:4 day:15 month:03 https://dx.doi.org/10.1007/s11738-023-03539-2 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_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 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_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_4393 GBV_ILN_4700 AR 45 2023 4 15 03 |
allfieldsSound |
10.1007/s11738-023-03539-2 doi (DE-627)SPR049853147 (SPR)s11738-023-03539-2-e DE-627 ger DE-627 rakwb eng Chapagain, Sandeep verfasserin aut Pyramiding QTLs using multiparental advanced generation introgression lines enhances salinity tolerance in rice 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) under exclusive licence to Franciszek Górski Institute of Plant Physiology, Polish Academy of Sciences, Kraków 2023. Springer Nature or its licensor (e.g. a society or other partner) 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 Rice is a major cereal that nourishes more than half of the global population. But rice lands are under threat from soil salinity leading to reduced productivity. Salinity stress tolerance is challenging due to the multigenic trait and complex tolerance mechanisms. QTL pyramiding is one of the efficient approaches to stack desired genes and QTLs from multiple donors. This study developed three populations using multiple salt-tolerant introgression lines (ILs) to accumulate beneficial alleles/QTLs and identify improved salt-tolerant breeding lines. To accumulate the salt-tolerant alleles from salt-tolerant donors, we used salt-tolerant ILs of Pokkali and Nona Bokra in the CL151 background (CLPK683 and CLPK757) and Jupiter background (JN100 and JN520), respectively. The QTLs for shoot $ Na^{+} $ and $ K^{+} $ content, qNa2.2, qK2.1, and qK2.2, from JN100 and qK4.1 and qK8.1 from JN520 were targeted using the molecular markers linked to these QTLs. Both phenotypic and genotypic selection methods were employed to advance the populations. The $ F_{5} $ populations of each cross were finally evaluated for seedling-stage salt tolerance. The visual salt injury score (SIS) and shoot $ Na^{+} $ and $ K^{+} $ concentration in selected lines indicated salt tolerance higher than the IL parents. The targeted QTLs were detected in most salt-tolerant lines. The salt-tolerant breeding lines identified in this study constitute a valuable resource for investigating the physiological and molecular basis of salt tolerance and identifying superior alleles of salt-tolerance genes for use in breeding programs. Introgression line (dpeaa)DE-He213 Marker-assisted selection (dpeaa)DE-He213 Quantitative trait loci (dpeaa)DE-He213 QTL pyramiding (dpeaa)DE-He213 Salt stress (dpeaa)DE-He213 Pruthi, Rajat aut Subudhi, Prasanta K. (orcid)0000-0003-0512-9076 aut Enthalten in Acta physiologiae plantarum Berlin : Springer, 1997 45(2023), 4 vom: 15. März (DE-627)516024906 (DE-600)2245807-4 1861-1664 nnns volume:45 year:2023 number:4 day:15 month:03 https://dx.doi.org/10.1007/s11738-023-03539-2 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_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 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_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_4393 GBV_ILN_4700 AR 45 2023 4 15 03 |
language |
English |
source |
Enthalten in Acta physiologiae plantarum 45(2023), 4 vom: 15. März volume:45 year:2023 number:4 day:15 month:03 |
sourceStr |
Enthalten in Acta physiologiae plantarum 45(2023), 4 vom: 15. März volume:45 year:2023 number:4 day:15 month:03 |
format_phy_str_mv |
Article |
institution |
findex.gbv.de |
topic_facet |
Introgression line Marker-assisted selection Quantitative trait loci QTL pyramiding Salt stress |
isfreeaccess_bool |
false |
container_title |
Acta physiologiae plantarum |
authorswithroles_txt_mv |
Chapagain, Sandeep @@aut@@ Pruthi, Rajat @@aut@@ Subudhi, Prasanta K. @@aut@@ |
publishDateDaySort_date |
2023-03-15T00:00:00Z |
hierarchy_top_id |
516024906 |
id |
SPR049853147 |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR049853147</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230328064816.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230328s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11738-023-03539-2</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR049853147</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s11738-023-03539-2-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Chapagain, Sandeep</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Pyramiding QTLs using multiparental advanced generation introgression lines enhances salinity tolerance in rice</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s) under exclusive licence to Franciszek Górski Institute of Plant Physiology, Polish Academy of Sciences, Kraków 2023. Springer Nature or its licensor (e.g. a society or other partner) 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">Abstract Rice is a major cereal that nourishes more than half of the global population. But rice lands are under threat from soil salinity leading to reduced productivity. Salinity stress tolerance is challenging due to the multigenic trait and complex tolerance mechanisms. QTL pyramiding is one of the efficient approaches to stack desired genes and QTLs from multiple donors. This study developed three populations using multiple salt-tolerant introgression lines (ILs) to accumulate beneficial alleles/QTLs and identify improved salt-tolerant breeding lines. To accumulate the salt-tolerant alleles from salt-tolerant donors, we used salt-tolerant ILs of Pokkali and Nona Bokra in the CL151 background (CLPK683 and CLPK757) and Jupiter background (JN100 and JN520), respectively. The QTLs for shoot $ Na^{+} $ and $ K^{+} $ content, qNa2.2, qK2.1, and qK2.2, from JN100 and qK4.1 and qK8.1 from JN520 were targeted using the molecular markers linked to these QTLs. Both phenotypic and genotypic selection methods were employed to advance the populations. The $ F_{5} $ populations of each cross were finally evaluated for seedling-stage salt tolerance. The visual salt injury score (SIS) and shoot $ Na^{+} $ and $ K^{+} $ concentration in selected lines indicated salt tolerance higher than the IL parents. The targeted QTLs were detected in most salt-tolerant lines. The salt-tolerant breeding lines identified in this study constitute a valuable resource for investigating the physiological and molecular basis of salt tolerance and identifying superior alleles of salt-tolerance genes for use in breeding programs.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Introgression line</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Marker-assisted selection</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Quantitative trait loci</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">QTL pyramiding</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Salt stress</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Pruthi, Rajat</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Subudhi, Prasanta K.</subfield><subfield code="0">(orcid)0000-0003-0512-9076</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Acta physiologiae plantarum</subfield><subfield code="d">Berlin : Springer, 1997</subfield><subfield code="g">45(2023), 4 vom: 15. März</subfield><subfield code="w">(DE-627)516024906</subfield><subfield code="w">(DE-600)2245807-4</subfield><subfield code="x">1861-1664</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:45</subfield><subfield code="g">year:2023</subfield><subfield code="g">number:4</subfield><subfield code="g">day:15</subfield><subfield code="g">month:03</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s11738-023-03539-2</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_32</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_90</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_100</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_120</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_138</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_150</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_171</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_187</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_250</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_281</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_636</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_702</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2001</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2004</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2007</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2008</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2009</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2010</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2011</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2015</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2018</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2020</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2025</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2026</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2031</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2034</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2038</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2039</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2044</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2048</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2049</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2050</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2055</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2056</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2057</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2059</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2061</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2064</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2065</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2068</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2088</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2093</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2106</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2107</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2108</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2111</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2113</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2118</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2122</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2129</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2143</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2144</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2147</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2148</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2153</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2188</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2232</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2446</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2470</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2472</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2507</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2522</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2548</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4035</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4046</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4242</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4246</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4251</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4326</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4328</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4333</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4334</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4393</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">45</subfield><subfield code="j">2023</subfield><subfield code="e">4</subfield><subfield code="b">15</subfield><subfield code="c">03</subfield></datafield></record></collection>
|
author |
Chapagain, Sandeep |
spellingShingle |
Chapagain, Sandeep misc Introgression line misc Marker-assisted selection misc Quantitative trait loci misc QTL pyramiding misc Salt stress Pyramiding QTLs using multiparental advanced generation introgression lines enhances salinity tolerance in rice |
authorStr |
Chapagain, Sandeep |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)516024906 |
format |
electronic Article |
delete_txt_mv |
keep |
author_role |
aut aut aut |
collection |
springer |
remote_str |
true |
illustrated |
Not Illustrated |
issn |
1861-1664 |
topic_title |
Pyramiding QTLs using multiparental advanced generation introgression lines enhances salinity tolerance in rice Introgression line (dpeaa)DE-He213 Marker-assisted selection (dpeaa)DE-He213 Quantitative trait loci (dpeaa)DE-He213 QTL pyramiding (dpeaa)DE-He213 Salt stress (dpeaa)DE-He213 |
topic |
misc Introgression line misc Marker-assisted selection misc Quantitative trait loci misc QTL pyramiding misc Salt stress |
topic_unstemmed |
misc Introgression line misc Marker-assisted selection misc Quantitative trait loci misc QTL pyramiding misc Salt stress |
topic_browse |
misc Introgression line misc Marker-assisted selection misc Quantitative trait loci misc QTL pyramiding misc Salt stress |
format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
cr |
hierarchy_parent_title |
Acta physiologiae plantarum |
hierarchy_parent_id |
516024906 |
hierarchy_top_title |
Acta physiologiae plantarum |
isfreeaccess_txt |
false |
familylinks_str_mv |
(DE-627)516024906 (DE-600)2245807-4 |
title |
Pyramiding QTLs using multiparental advanced generation introgression lines enhances salinity tolerance in rice |
ctrlnum |
(DE-627)SPR049853147 (SPR)s11738-023-03539-2-e |
title_full |
Pyramiding QTLs using multiparental advanced generation introgression lines enhances salinity tolerance in rice |
author_sort |
Chapagain, Sandeep |
journal |
Acta physiologiae plantarum |
journalStr |
Acta physiologiae plantarum |
lang_code |
eng |
isOA_bool |
false |
recordtype |
marc |
publishDateSort |
2023 |
contenttype_str_mv |
txt |
author_browse |
Chapagain, Sandeep Pruthi, Rajat Subudhi, Prasanta K. |
container_volume |
45 |
format_se |
Elektronische Aufsätze |
author-letter |
Chapagain, Sandeep |
doi_str_mv |
10.1007/s11738-023-03539-2 |
normlink |
(ORCID)0000-0003-0512-9076 |
normlink_prefix_str_mv |
(orcid)0000-0003-0512-9076 |
title_sort |
pyramiding qtls using multiparental advanced generation introgression lines enhances salinity tolerance in rice |
title_auth |
Pyramiding QTLs using multiparental advanced generation introgression lines enhances salinity tolerance in rice |
abstract |
Abstract Rice is a major cereal that nourishes more than half of the global population. But rice lands are under threat from soil salinity leading to reduced productivity. Salinity stress tolerance is challenging due to the multigenic trait and complex tolerance mechanisms. QTL pyramiding is one of the efficient approaches to stack desired genes and QTLs from multiple donors. This study developed three populations using multiple salt-tolerant introgression lines (ILs) to accumulate beneficial alleles/QTLs and identify improved salt-tolerant breeding lines. To accumulate the salt-tolerant alleles from salt-tolerant donors, we used salt-tolerant ILs of Pokkali and Nona Bokra in the CL151 background (CLPK683 and CLPK757) and Jupiter background (JN100 and JN520), respectively. The QTLs for shoot $ Na^{+} $ and $ K^{+} $ content, qNa2.2, qK2.1, and qK2.2, from JN100 and qK4.1 and qK8.1 from JN520 were targeted using the molecular markers linked to these QTLs. Both phenotypic and genotypic selection methods were employed to advance the populations. The $ F_{5} $ populations of each cross were finally evaluated for seedling-stage salt tolerance. The visual salt injury score (SIS) and shoot $ Na^{+} $ and $ K^{+} $ concentration in selected lines indicated salt tolerance higher than the IL parents. The targeted QTLs were detected in most salt-tolerant lines. The salt-tolerant breeding lines identified in this study constitute a valuable resource for investigating the physiological and molecular basis of salt tolerance and identifying superior alleles of salt-tolerance genes for use in breeding programs. © The Author(s) under exclusive licence to Franciszek Górski Institute of Plant Physiology, Polish Academy of Sciences, Kraków 2023. Springer Nature or its licensor (e.g. a society or other partner) 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 |
Abstract Rice is a major cereal that nourishes more than half of the global population. But rice lands are under threat from soil salinity leading to reduced productivity. Salinity stress tolerance is challenging due to the multigenic trait and complex tolerance mechanisms. QTL pyramiding is one of the efficient approaches to stack desired genes and QTLs from multiple donors. This study developed three populations using multiple salt-tolerant introgression lines (ILs) to accumulate beneficial alleles/QTLs and identify improved salt-tolerant breeding lines. To accumulate the salt-tolerant alleles from salt-tolerant donors, we used salt-tolerant ILs of Pokkali and Nona Bokra in the CL151 background (CLPK683 and CLPK757) and Jupiter background (JN100 and JN520), respectively. The QTLs for shoot $ Na^{+} $ and $ K^{+} $ content, qNa2.2, qK2.1, and qK2.2, from JN100 and qK4.1 and qK8.1 from JN520 were targeted using the molecular markers linked to these QTLs. Both phenotypic and genotypic selection methods were employed to advance the populations. The $ F_{5} $ populations of each cross were finally evaluated for seedling-stage salt tolerance. The visual salt injury score (SIS) and shoot $ Na^{+} $ and $ K^{+} $ concentration in selected lines indicated salt tolerance higher than the IL parents. The targeted QTLs were detected in most salt-tolerant lines. The salt-tolerant breeding lines identified in this study constitute a valuable resource for investigating the physiological and molecular basis of salt tolerance and identifying superior alleles of salt-tolerance genes for use in breeding programs. © The Author(s) under exclusive licence to Franciszek Górski Institute of Plant Physiology, Polish Academy of Sciences, Kraków 2023. Springer Nature or its licensor (e.g. a society or other partner) 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 |
Abstract Rice is a major cereal that nourishes more than half of the global population. But rice lands are under threat from soil salinity leading to reduced productivity. Salinity stress tolerance is challenging due to the multigenic trait and complex tolerance mechanisms. QTL pyramiding is one of the efficient approaches to stack desired genes and QTLs from multiple donors. This study developed three populations using multiple salt-tolerant introgression lines (ILs) to accumulate beneficial alleles/QTLs and identify improved salt-tolerant breeding lines. To accumulate the salt-tolerant alleles from salt-tolerant donors, we used salt-tolerant ILs of Pokkali and Nona Bokra in the CL151 background (CLPK683 and CLPK757) and Jupiter background (JN100 and JN520), respectively. The QTLs for shoot $ Na^{+} $ and $ K^{+} $ content, qNa2.2, qK2.1, and qK2.2, from JN100 and qK4.1 and qK8.1 from JN520 were targeted using the molecular markers linked to these QTLs. Both phenotypic and genotypic selection methods were employed to advance the populations. The $ F_{5} $ populations of each cross were finally evaluated for seedling-stage salt tolerance. The visual salt injury score (SIS) and shoot $ Na^{+} $ and $ K^{+} $ concentration in selected lines indicated salt tolerance higher than the IL parents. The targeted QTLs were detected in most salt-tolerant lines. The salt-tolerant breeding lines identified in this study constitute a valuable resource for investigating the physiological and molecular basis of salt tolerance and identifying superior alleles of salt-tolerance genes for use in breeding programs. © The Author(s) under exclusive licence to Franciszek Górski Institute of Plant Physiology, Polish Academy of Sciences, Kraków 2023. Springer Nature or its licensor (e.g. a society or other partner) 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. |
collection_details |
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_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 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_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_4393 GBV_ILN_4700 |
container_issue |
4 |
title_short |
Pyramiding QTLs using multiparental advanced generation introgression lines enhances salinity tolerance in rice |
url |
https://dx.doi.org/10.1007/s11738-023-03539-2 |
remote_bool |
true |
author2 |
Pruthi, Rajat Subudhi, Prasanta K. |
author2Str |
Pruthi, Rajat Subudhi, Prasanta K. |
ppnlink |
516024906 |
mediatype_str_mv |
c |
isOA_txt |
false |
hochschulschrift_bool |
false |
doi_str |
10.1007/s11738-023-03539-2 |
up_date |
2024-07-04T02:32:39.600Z |
_version_ |
1803614011630026752 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR049853147</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230328064816.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230328s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11738-023-03539-2</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR049853147</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s11738-023-03539-2-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Chapagain, Sandeep</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Pyramiding QTLs using multiparental advanced generation introgression lines enhances salinity tolerance in rice</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s) under exclusive licence to Franciszek Górski Institute of Plant Physiology, Polish Academy of Sciences, Kraków 2023. Springer Nature or its licensor (e.g. a society or other partner) 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">Abstract Rice is a major cereal that nourishes more than half of the global population. But rice lands are under threat from soil salinity leading to reduced productivity. Salinity stress tolerance is challenging due to the multigenic trait and complex tolerance mechanisms. QTL pyramiding is one of the efficient approaches to stack desired genes and QTLs from multiple donors. This study developed three populations using multiple salt-tolerant introgression lines (ILs) to accumulate beneficial alleles/QTLs and identify improved salt-tolerant breeding lines. To accumulate the salt-tolerant alleles from salt-tolerant donors, we used salt-tolerant ILs of Pokkali and Nona Bokra in the CL151 background (CLPK683 and CLPK757) and Jupiter background (JN100 and JN520), respectively. The QTLs for shoot $ Na^{+} $ and $ K^{+} $ content, qNa2.2, qK2.1, and qK2.2, from JN100 and qK4.1 and qK8.1 from JN520 were targeted using the molecular markers linked to these QTLs. Both phenotypic and genotypic selection methods were employed to advance the populations. The $ F_{5} $ populations of each cross were finally evaluated for seedling-stage salt tolerance. The visual salt injury score (SIS) and shoot $ Na^{+} $ and $ K^{+} $ concentration in selected lines indicated salt tolerance higher than the IL parents. The targeted QTLs were detected in most salt-tolerant lines. The salt-tolerant breeding lines identified in this study constitute a valuable resource for investigating the physiological and molecular basis of salt tolerance and identifying superior alleles of salt-tolerance genes for use in breeding programs.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Introgression line</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Marker-assisted selection</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Quantitative trait loci</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">QTL pyramiding</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Salt stress</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Pruthi, Rajat</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Subudhi, Prasanta K.</subfield><subfield code="0">(orcid)0000-0003-0512-9076</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Acta physiologiae plantarum</subfield><subfield code="d">Berlin : Springer, 1997</subfield><subfield code="g">45(2023), 4 vom: 15. März</subfield><subfield code="w">(DE-627)516024906</subfield><subfield code="w">(DE-600)2245807-4</subfield><subfield code="x">1861-1664</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:45</subfield><subfield code="g">year:2023</subfield><subfield code="g">number:4</subfield><subfield code="g">day:15</subfield><subfield code="g">month:03</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s11738-023-03539-2</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_32</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_90</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_100</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_120</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_138</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_150</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_171</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_187</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_250</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_281</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_636</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_702</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2001</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2004</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2007</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2008</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2009</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2010</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2011</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2015</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2018</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2020</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2025</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2026</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2031</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2034</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2038</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2039</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2044</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2048</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2049</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2050</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2055</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2056</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2057</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2059</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2061</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2064</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2065</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2068</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2088</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2093</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2106</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2107</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2108</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2111</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2113</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2118</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2122</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2129</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2143</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2144</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2147</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2148</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2153</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2188</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2232</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2446</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2470</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2472</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2507</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2522</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2548</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4035</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4046</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4242</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4246</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4251</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4326</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4328</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4333</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4334</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4393</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">45</subfield><subfield code="j">2023</subfield><subfield code="e">4</subfield><subfield code="b">15</subfield><subfield code="c">03</subfield></datafield></record></collection>
|
score |
7.399108 |