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Research Article

Identification of QTLs for Cold Tolerance at Seedling Stage Using a Population Derived from an Inter-specific Cross in Rice

Kyu-Chan Shim1, Yeo-Tae Yun2, Ju-Won Kang3, Sang-Nag Ahn1,*
Plant Breeding and Biotechnology 2022;10(4):282-289.
Published online: December 1, 2022

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*Corresponding author Sang-Nag Ahn, ahnsn@cnu.ac.kr, Tel: +82-42-821-5728, Fax: +82-42-822-2631
• Received: November 10, 2022   • Revised: November 15, 2022   • Accepted: November 16, 2022

Copyright © 2022 by the Korean Society of Breeding Science

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  • Cold stress is one of the serious abiotic stresses for stable rice production especially in high-latitude temperate region and high-altitude tropical area. Improving cold tolerance at seedling stage led stable seedling growth with yield stability. In this study, QTLs for cold tolerance at seedling stage were identified using the 96 introgression lines (ILs) derived from an inter-specific cross between Hwaseong (Oryza sativa) and Oryza rufipogon. Three QTLs were detected and the O. rufipogon alleles at two QTL (qCTS1 and qCTS12) improved cold tolerance in the Hwaseong genetic background whereas the O. rufipogon allele at qCTS10 on chromosome 10 decreased cold tolerance. Among these three QTLs, a major QTL qCTS12 explained 27.5% of phenotypic variation. Fine-mapping indicated that qCTS12 was different from those QTL reported in previous studies based on the map location suggesting that qCTS12 might be a new allele and is not associated with deleterious genes such fertility reduction. Among the 96 introgression lines, two lines, CR60 and CR61 were selected based on enhanced cold tolerance at seedling stage. qCTS12, therefore, provides a valuable allele for breeding rice with improved cold tolerance.
  • Key words: Cold tolerance, Seedling stage, Rice, QTL, Inter-specific cross
Rice is the most important cereal crop for many Asian countries. Rice cultivation and production is largely affected by abiotic stresses such as drought, salinity, heat, flooding, and cold. Among these stresses and environmental factors, cold stress is one of the serious constraints to rice production in high-latitude temperate and high-altitude tropical area (Kim et al. 2014). Cold irrigation water or low air temperature cause cold stress to rice at seedlings stage and induce retardation of stable seedling growth and yield stability (Peterson et al. 1978; Fujino et al. 2008).
It has been demonstrated that cold tolerance at seedling stage (CTS) is controlled by quantitative trait loci (QTL) in rice (Andaya and Mackill 2003; Zhang et al. 2005; Koseki et al. 2010; Suh et al. 2012). Until now, a number of QTLs for CTS have been identified and some QTLs were cloned and fine-mapped (Andaya and Tai 2006; Ma et al. 2015). COLD1 gene encoding regulator of G-protein signaling was cloned from QTL analysis and COLD1 japonica allele confers chilling tolerance in rice by interacting with G-protein alpha-subunit (Ma et al. 2015). Major QTL for cold tolerance at seedling stage on chromosome 12 (qCTS12) was identified from several studies. Andaya and Mackill (2003) reported qCTS12a which explained about 40% of the phenotypic variation in the F6 RIL population derived from a cross between M-202 (cold tolerant) and IR50 (cold sensitive). Fine-mapping narrowed down qCTS12 to 55-kb region including two candidate genes, OsGSTZ1 and OsGSTZ2 (Andaya and Tai 2006). QTL for seedling cold tolerance on chromosome 12 (qSCT12) was detected from an RIL population derived from a cross between Hanareum 2 (cold sensitive) and Unkwang (cold tolerance) (Kim et al. 2017). qSCT12 explained 25% of the phenotypic variation and the physical location of this QTL overlapped with qCTS12.
Genome-wide association study (GWAS) also identified a lot of QTLs for cold tolerance at seedling stage in rice (Wang et al. 2016; Schlappi et al. 2017; Ham et al. 2021). Wang et al. (2016) used the rice diversity panel 1 including 295 rice accessions collected from 82 countries and 67 QTLs for CTS were detected on 11 chromosomes. Among these QTLs, informative SNPs were located on the previously reported genes associated with stress tolerance. Five chilling tolerance traits (Five seedling chilling tolerance indices: low temperature germinability, plumule growth rate after cold germination, low temperature seedling survivability, plumule recovery growth after cold exposure, and low temperature survival) were investigated using USDA Mini-Core collection (Schlappi et al. 2017). For low-temperature seedling survivability, 24 QTLs were uncovered and two novel QTLs qLTSS4-1 and qLTSS3-4 were found (Schlappi et al. 2017). GWAS analysis found four significant association QTLs for cold tolerance in rice at the seedling stage using 127 rice accessions and four QTLs explained 16.5% to 18.5% of phenotypic variation (Ham et al. 2021). Os01g0357800, Os05g0171300, and Os05g0400200 were selected as candidate genes of four QTLs and haplotype of these genes were investigated.
In the present study, we analyzed QTL associated with cold tolerance at seedling stage using introgression lines derived from an inter-specific cross between Hwaseong (Oryza sativa) and Oryza rufipogon. Three QTLs for cold tolerance were detected on chromosomes 1, 10, and 12. Among these QTLs, qCTS12 was major QTL and the location of qCTS12 was overlapped with QTLs identified from previous studies. In addition, two introgression lines which displayed strong cold tolerance were selected and these lines might be utilized as pre-breeding lines for breeding program to improve cold tolerance at seedling stage.
Plant materials
Previously developed 96 introgression lines (ILs; CR1~ CR96) derived from an inter-specific cross between the Korea japonica elite line Hwaseong and O. rufipogon (IRGC105491) were used in this study (Yun et al. 2016). At 2020, Hwaseong, O. rufipogon, and 96 ILs were grown in the experimental field at Chungnam National University, Daejeon, Korea. About 50 germinated seeds of each line were sown in the seedling tray at mid of April and one-month-old seedlings were transplanted into paddy field with 30 × 15 cm interval. Plant materials were culti-vated following the standard rice cultivation methods of Rural Development Administration (RDA, 2012). Fully matured seeds were harvested 50 days after flowering and dried in greenhouse for two weeks. Dried seeds were trashed and seed dormancy was broken by treating at 50℃ for four days in the dry oven. After dormancy breaking, seeds were used for seedling cold tolerance test.
Seedling cold tolerance evaluation
Cold tolerance at seedling stage (CTS) was evaluated as described by Wang et al. (2016) with minor modification. Ten seeds of Hwaseong, O. rufipogon, and 96 ILs were sown in seedling tray (3.5 × 3.5 cm) containing commercial potting soil (Soorasangto, Seoulbio, South Korea) with a completely randomized block design with three repli-cations. Seedlings were grown in the growth chamber (HB-301L-3, HANBAEK SCIENTIFIC CO. South Korea) which provided a 12/12 h of light/dark period each with 65% of relative humidity for two weeks. Two-week-old seedlings were transferred to cold treatment chamber (HB-303DH, HANBAEK SCIENTIFIC CO. South Korea). For cold treatment, seedlings were subjected to the 8/10℃ day/night with 65% of relative humidity for four days. To reduce the environment effect caused by tray location, the location of trays was changed every 24 hours so as to allow uniform cold treatment. The experiment was repeated three times following the same protocol. After four days of cold treatment, cold tolerance was assessed by visual rating method based on the leaf wilting and drying phenotype from 1 (tolerant) to 9 (sensitive) (Fig. 1A). For cold tolerance scores of 1, 3, 5, 7, and 9, the percentage of tilted and dried leaves is 0-20%, 21-40%, 41-60%, 61-80%, and 81-100%, respectively.
Molecular marker genotyping
The 96 ILs were previously genotyped with molecular markers (Yun et al. 2016). Previously developed SSR markers were used for primary mapping (McCouch et al. 2002). Additionally, Kompetitive allele specific PCR (KASP) markers and InDel markers were used to fill the gaps of the previous genotype (Cheon et al. 2018). Genomic DNA was extracted from fresh leaves using CTAB method as described in (Shim et al. 2019). KASP marker genotyping was conducted at the Seed Industry Promotion Center, Foundation of Agri. Tech. Commer-cialization & Transfer, Korea. InDel markers were newly designed in this study. PCR was performed as described in (Kim et al. 2020). PCR amplicon was separated in the 2-3% of agarose gels stained with StaySafe Nucleic Acid Gel Stain (RBC, Taiwan). Newly designed primers were listed in Supplementary Table 1.
QTL analysis and statistical analysis
QTL analysis was carried out using IciMapping 4.1 software (Meng et al. 2015). Single marker analysis and composite interval mapping were conducted with default parameters. QTLs were named as following the nomencla-ture suggested by McCouch and CGSNL (McCouch and Cooperative, 2008). Histograms were drawn using Minitab software.
Distribution of CTS in 96 ILs
Cold tolerance test was conducted using Hwaseong, O. rufipogon, and 96 ILs. Hwaseong and O. rufipogon showed 4.3 and 7.3 of CTS, respectively (Table 1). O. rufipogon seedlings were taller than Hwaseong and O. rufipogon displayed weak cold tolerance phenotype (Fig. 1B). CTS of the IL population ranged from 1.3 to 5.7 with a mean of 3.9 and all of ILs were more tolerant than O. rufipogon (Table 1). The ILs displayed a left tailed distribution in the histogram of CTS (Fig. 2). Skewness and kurtosis were ‒0.6 and ‒0.5, respectively (Table 1). Some introgression lines harboring the O. rufipogon segments showed stronger CTS than the recurrent parent, Hwaseong suggesting that O. rufipogon might harbor some trait-enhancing QTLs associated with CTS in the Hwaseong genetic background.
Genotype of ILs population
Previously, the map of 96 ILs was constructed using a total of 133 markers (Yun et al. 2016). However, the map had some gaps with large intervals between SSR markers. To fill these gaps, we employed 70 KASP and seven InDel markers. We screened a total of 212 markers, and 46 markers failed to detect O. rufipogon alleles. Finally, 167 markers were used for QTL analysis (Fig. 3).
Identification of QTL for CTS
To find loci associated with CTS variation, QTL analy-sis was performed. A total of three QTLs, namely qCTS1, qCTS10, and qCTS12 were mapped on chromosomes 1, 10, and 12 based on a single marker analysis (Table 2). The O. rufipogon alleles at qCTS1 and qCTS12 increased cold tolerance at seedling stage while the Hwaseong allele at qCTS10 enhanced cold tolerance in this IL population. qCTS1, qCTS10, and qCTS12 explained 5.2, 5.3, and 10.3% of the phenotypic variation, respectively. Among these three QTLs, qCTS12 was major QTL with the highest LOD value of 7.1 (Table 2). In the inclusive composite interval mapping, two QTLs (qCTS10 and qCTS12) were identified (Table 3). 11.9 and 27.5% of phonotypic variation was explained by qCTS10 and qCTS12, respectively and the allelic effects of qCTS10 and qCTS12 was similar with those in a single marker analysis.
Selection of cold tolerant lines
Based on the CTS phenotype, two promising lines, namely CR60 and CR61, displaying highest cold tolerance value were selected (Fig. 4). The two lines had the O. rufipogon alleles at two loci (qCTS10 and qCTS12). Two-week-old seedlings of CR60, CR61 and Hwaseong were treated under cold stress at 8/10℃ (day/night) with 65% of the relative humidity condition for four days in the growth chamber. After the treatment, CR60 and CR61 performed better than Hwaseong in wilting and drying of leaves confirming that the two QTL are effective in improving CTS in the Hwaseong background. These lines would be used as pre-breeding line together with molecular markers linked to QTLs.
Cold tolerance is one of the essential components for rice yield stability. Wild relatives of rice have great potential for improving agronomic traits including cold tolerance. Tolerance for cold stress at seedling stage is controlled by multiple genes and a lot of QTLs have been identified from bi-parental population and genome-wide association studies. A total of 295 rice cultivars was screened under low-temperature condition at seedling stage and cold tolerance score was significantly different depending on the ecotype of rice (Wang et al. 2016). Temperate and tropical japonica rice showed significantly stronger cold tolerance than admixture, aromatic, aus, and indica rice. Other studies have reported that japonica rice has better tolerance to cold stress than other ecotypes including indica rice (Ma et al. 2015; Ham et al. 2021). Therefore, identifying cold tolerance QTLs which can contribute to enhancing cold tolerance in the japonica genetic back-ground would be more valuable for modern breeding program.
In this study, we identified three QTLs using the popula-tion derived an inter-specific cross between Hwaseong and O. rufipogon. Among these QTLs, qCTS1 and qCTS12 of O. rufipogon allele improved the cold tolerance at seedling stage in the Hwaseong genetic background. Frequency distribution of IL lines showed that about half of the ILs have better cold tolerance than its recurrent parent Hwaseong (Fig. 2). The transgressive distribution observed in this population could be a genetic interaction between genetic background of Hwaseong and introgressions of O. rufipogon alleles. This result supports the idea that this O. rufipogon accession is a valuable genetic resource for improving cold tolerance in the breeding program. However, it is necessary to check whether the O. rufipogon alleles at qCTS1 and qCTS12 could improve cold tolerance in other japonica rice genetic background. In addition, existence of genetic interaction in regulating cold tolerance phenotype needs to be checked in the segregating population.
qCTS1 was located on the end of short arm of chromosome 1. In the GRAMENE QTL database (https:// archive.gramene.org/qtl/), no QTL associated with cold tolerance was detected near qCTS1 detected in this report. Luo et al. (2007) reported qCTS1-a, b, and c and qCTS1-a was located on the middle of short arm on chromosome 1. However, the physical distance of qCTS1-a reported from Luo et al. (2007) and qCTS1 detected in this study is about 3-Mb, indicating two QTLs might not be allelic to each other. To know whether qCTS1 is novel or not, QTL validation is required using the segregating population. The possibility that qCTS1 could be false positive QTL cannot be ruled out because this QTL was not detected in inclusive composite interval mapping (Tables 2 and 3). In addition, 96 ILs genotype data showed that O. rufipogon chromosomal segments are not equally distributed in the genome and some chromosomal segments are repeatedly found in the ILs (Fig. 3). These population structure possibly contributes to false positive QTL detection.
qCTS10 was found in the marker interval between RM147 and RM333 and the O. rufipogon allele decreased cold tolerance in the Hwaseong genetic background (Tables 2 and 3). The location of qCTS10 was overlapped with QTL for low-temperature germinability, qLTG10.2 detected from an F2 population derived from a cross between two introgression lines CR1517 and CR1518 (Akhtamov et al. 2020). CR1517 and CR1518 were selected from 96 ILs used in this study and the O. rufipogon qLTG10.2 allele decreased low-temperature germinability and coleoptile growth under low-temperature condition. It is interesting that the O. rufipogon chromosome segment on chromosome 10 including qCTS10 and qLTG10.2 decreased cold tolerance at seedling stage and gemination stage in the Hwaseong genetic background. It is possible that this locus is associated with cold stress response and regulation. Other studies also reported QTL for low- temperature germinability on chromosome 10 (qGR-10, qLTG10-1, and qLTG10-2) near qCTS10 and qLTG10.2 (Ji et al. 2009; Li et al. 2019). Further study will be conducted to find the causal gene for qCTS10 and qLTG10.2 and to know whether these two QTLs are allelic to each other.
qCTS12 was identified in the marker interval between RM19 to KJ12_009 and its physical location is approxi-mately 12: 2,433,226-4,218,137. Previously reported qCTS12 which was found from a cross between M-202 and IR50 was fine-mapped, and OsGSTZ1 and OsGSTZ2 were selected as candidate genes (Andaya and Tai 2006). These two genes were tandemly located on chromosome 12: 5,756,479-5,760,022 for OsGSTZ1 and 5,760,537-5,763,699 for OsGSTZ2. qSCT12 was also mapped on chromosome 12 with marker interval between id12002113-id12002563 and the physical location of id12002113-id12002563 was approximately 4,663,607-5,764,918 (Thomson et al. 2012; Kim et al. 2017). Although our molecular map covers OsGSTZ1 and OsGSTZ2 region with InDel markers from 12_HR_1 to 12_HR_7 (12: 5,473,100 – 7,421,232), OsGSTZ1 and OsGSTZ2 genes were not included in the QTL region. This result indicated that the qCTS12 in this study is possibly different from qCTS12 reported in Andaya and Tai (2006) and qSCT12 reported from Kim et al. (2017).
In this study, three putative QTLs for cold tolerance at seedling stage were identified using an inter-specific cross population. Two QTLs, qCTS1 and qCTS12, of O. rufipogon alleles improved cold tolerance in the Hwaseong genetic background. CR60 and CR61 were selected as pre-breeding lines with strong cold tolerance phenotype and these lines could be used for enhancing cold tolerance of japonica rice. In addition, molecular markers linked to the QTLs could be applied in selection of progenies in the breeding program utilizing O. rufipogon accession. Breeders also can utilize two introgression lines, CR60 or CR61 to speed up the process of transferring qCTS12 into the japonica back-ground in the program considering that two lines do not possess any deleterious traits including tall plant stature and fertility reduction (Yun et al. 2016).
pbb-10-4-282-supple.xlsx
This work was carried out with the support of “Coope-rative Research Program for Agriculture Science and Technology Development (Project No. PJ015757)” Rural Development Administration, Republic of Korea.
Fig. 1
Frequency distribution of cold tolerance score of 96 introgression lines and their parental lines.
pbb-10-4-282-f1.jpg
Fig. 2
Frequency distribution of cold tolerance score of 96 introgression lines and their parental lines.
pbb-10-4-282-f2.jpg
Fig. 3
Graphical genotype map of the introgression lines. Light gray and dark gray block indicate Hwaseong and O. rufipogon chromosome segments. White block indicates missing genotype data.
pbb-10-4-282-f3.jpg
Fig. 4
Cold stress treatment of Hwaseong and two promising lines (CR60 and CR61) seedlings. (A) Two-week old seedlings grown in the growth chamber. (B) Four days after cold stress treatment under 8/10℃ (day/night).
pbb-10-4-282-f4.jpg
Table 1
Cold tolerance values at seedling stage in two parents and introgression population.
Table 1
Trait Parents IL population
Hwaseong O. rufipogon Mean ± SD Range Skewness Kurtosis
CTS 4.3 ± 1.2 7.3 ± 1.1 3.9 ± 1.1 1.3-5.7 ‒0.6 ‒0.5
Table 2
QTL results of 96 ILs based on the single marker analysis.
Table 2
Marker Chr. LOD R2 Addz) HHy) RRx)
qCTS1 RM495 1 3.3 5.2 ‒0.7 4.0 2.6
RM147 10 3.3 5.3 0.5 3.7 4.6
qCTS10 KJ10_041 10 3.3 5.3 0.5 3.6 4.5
RM333 10 2.5 4.1 0.4 3.7 4.6
qCTS12 RM19 12 2.5 4.1 ‒0.9 4.0 2.2
RM247 12 7.0 10.2 ‒1.1 4.0 1.9
KJ12_009 12 7.1 10.3 ‒1.0 4.1 2.0

z)Add (additive effect) = (O. rufipogon homozygous ‒ Hwaseong homozygous)/2.

y)HH: Mean CTS of Hwaseong homozygotes.

x)RR: Mean CTS of O. rufipogon homozygotes.

Table 3
QTL results of 96 ILs based on the inclusive composite interval mapping.
Table 3
Marker Chr LOD R2 Addz) HHy) RRx)
qCTS10 KJ10_041 10 3.4 11.9 0.4 2.6 3.6
qCTS12 KJ12_009 12 7.2 27.5 ‒1.0 4.2 2.3

z)Add (additive effect) = (O. rufipogon homozygous ‒ Hwaseong homozygous)/2.

y)HH: Mean CTS of Hwaseong homozygotes.

x)RR: Mean CTS of O. rufipogon homozygotes.

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Identification of QTLs for Cold Tolerance at Seedling Stage Using a Population Derived from an Inter-specific Cross in Rice
Plant Breed. Biotech.. 2022;10(4):282-289.   Published online December 1, 2022
DOI: https://doi.org/10.9787/PBB.2022.10.4.282
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Identification of QTLs for Cold Tolerance at Seedling Stage Using a Population Derived from an Inter-specific Cross in Rice
Plant Breed. Biotech.. 2022;10(4):282-289.   Published online December 1, 2022
DOI: https://doi.org/10.9787/PBB.2022.10.4.282
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Identification of QTLs for Cold Tolerance at Seedling Stage Using a Population Derived from an Inter-specific Cross in Rice
Image Image Image Image
Fig. 1 Frequency distribution of cold tolerance score of 96 introgression lines and their parental lines.
Fig. 2 Frequency distribution of cold tolerance score of 96 introgression lines and their parental lines.
Fig. 3 Graphical genotype map of the introgression lines. Light gray and dark gray block indicate Hwaseong and O. rufipogon chromosome segments. White block indicates missing genotype data.
Fig. 4 Cold stress treatment of Hwaseong and two promising lines (CR60 and CR61) seedlings. (A) Two-week old seedlings grown in the growth chamber. (B) Four days after cold stress treatment under 8/10℃ (day/night).

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Identification of QTLs for Cold Tolerance at Seedling Stage Using a Population Derived from an Inter-specific Cross in Rice

Cold tolerance values at seedling stage in two parents and introgression population.

Trait Parents IL population
Hwaseong O. rufipogon Mean ± SD Range Skewness Kurtosis
CTS 4.3 ± 1.2 7.3 ± 1.1 3.9 ± 1.1 1.3-5.7 ‒0.6 ‒0.5

QTL results of 96 ILs based on the single marker analysis.

Marker Chr. LOD R2 Addz) HHy) RRx)
qCTS1 RM495 1 3.3 5.2 ‒0.7 4.0 2.6
RM147 10 3.3 5.3 0.5 3.7 4.6
qCTS10 KJ10_041 10 3.3 5.3 0.5 3.6 4.5
RM333 10 2.5 4.1 0.4 3.7 4.6
qCTS12 RM19 12 2.5 4.1 ‒0.9 4.0 2.2
RM247 12 7.0 10.2 ‒1.1 4.0 1.9
KJ12_009 12 7.1 10.3 ‒1.0 4.1 2.0

QTL results of 96 ILs based on the inclusive composite interval mapping.

Marker Chr LOD R2 Addz) HHy) RRx)
qCTS10 KJ10_041 10 3.4 11.9 0.4 2.6 3.6
qCTS12 KJ12_009 12 7.2 27.5 ‒1.0 4.2 2.3
Table 1 Cold tolerance values at seedling stage in two parents and introgression population.
Table 2 QTL results of 96 ILs based on the single marker analysis.

z)Add (additive effect) = (O. rufipogon homozygous ‒ Hwaseong homozygous)/2.

y)HH: Mean CTS of Hwaseong homozygotes.

x)RR: Mean CTS of O. rufipogon homozygotes.

Table 3 QTL results of 96 ILs based on the inclusive composite interval mapping.

z)Add (additive effect) = (O. rufipogon homozygous ‒ Hwaseong homozygous)/2.

y)HH: Mean CTS of Hwaseong homozygotes.

x)RR: Mean CTS of O. rufipogon homozygotes.

Table 1

Table 2

Table 3

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