Introduction

Rice is the most important staple food crop for more than half of the global population and accounts for approximately 20% of the daily food calorie intake1. Indian sub-continent and South-East Asia are the most important centers of diversity for rice (Oryza sativa L.), where rice is widely cultivated on the flood plains of the major river basins and deltas. Rice cultivation in these areas is not only crucial for the world food security but is also closely associated with the tradition, culture and customs of the people2,3. It is a semi-aquatic plant that can be grown in a wide range of environments varying from dry rain-fed upland to deep-water lowland rice ecosystems. Submergence at vegetative stage is quite often followed by reproductive stage drought in the rain-fed lowland river plains of India and South-East Asia. The majority of rice growing areas in this region suffers from abiotic stresses such as drought, flooding and salinity4. Worldwide, 15 million hectares of rice suffers from flooding stress of one kind or other causing huge economic losses5. Different kinds of flooding include: (i) flooding during seed germination, (ii) complete submergence for 1–2 weeks due to flash flooding at seedling or tillering stage, (iii) stagnant water flooding of 25–50 cm in the areas with poor drainage, near the banks of overflowing rivers, (iv) saline water flooding in the coastal and tidal areas, and (v) deep water flooding lasting for a prolonged period of more than a month with water levels ranging from a 50 cm to several meters5,6. Traditional varieties and landraces of rice are available for cultivation in each of these situations. These are low yielding but can be useful source of genes for breeding high yielding stress tolerant rice cultivars. Several QTLs and genes for different kinds of flooding stress have been identified from these germplasm7,8,9,10,11,12,13,14,15,16. During 1970s hundreds of landraces of rice collected from the flood-prone areas of the world were screened for flash flood submergence tolerance at IRRI. Consequently, FR13A, FR43B, Kurkarruppan, Goda Heenati, Thuvalu, etc. were recognized as flash flooding tolerant.

Aus cultivar FR13A was found to be one of the best sources for submergence tolerance. Genetic studies using a population derived from FR13A identified a major QTL Submergence 1 (SUB1) on the chromosome 917. This was followed by map-based cloning of three ethylene response factor-like genes, Sub1A, Sub1B, and Sub1C, and demonstration of the role of Sub1A in submergence tolerance by genetic transformation of a sensitive variety Liaogeng18,19. Analysis of 21 rice accessions showed that all of them possessed Sub1B and Sub1C genes, but only a sub-set of 12 cultivars possessed the Sub1A gene, responsible for the submergence tolerance in FR13A19. The Sub1A positive varieties possessed one of the two alleles, Sub1A-1 or Sub1A-2, which were associated with the tolerant or intolerant phenotype, respectively19. At the protein sequence level, the only difference is that Sub1A-1 allele codes for amino acid Ser186, whereas Sub1A-2 codes for a Pro186 at this position, the remaining protein is identical. Phylogenetic analysis of the Sub1 genes from wild rice accessions has revealed that Sub1A arose from the duplication of Sub1B gene20. However, there are limited studies on sequence variation of the Sub1B and Sub1C genes and Sub1A-independent mechanisms of submergence tolerance in flood-tolerant rice germplasm. Earlier, a set of 109 rice genotypes including A and C genome wild rice species were analyzed for stem elongation index and percent survival after 14 days of submergence followed by seven days of recovery and identified Sub1A-dependent and Sub1A-independent mechanisms of survival21. Further, a set of 160 rice varieties representing deep water, flood and tidal prone areas were analyzed for haplotype variation in the Sub1A and Sub1C genes using CAPS markers to identify three and four haplotypes, respectively22. Recently, Zhao et al.23 developed a pan-genome of rice based on deep coverage re-sequencing of 66 diverse rice genotypes, representing different rice cultivar groups and 14 Oryza rufipogon accessions, but they analyzed the presence of Sub1A gene only and not Sub1B and Sub1C genes in the set.

Submergence tolerant rice cultivars have been developed in the background of several popular mega varieties of rice and deployed for commercial cultivation across South and South-East Asia using marker-assisted backcross breeding to transfer 0.8 to 7.8 Mbp of the donor chromosome 9 segment around the Sub1 locus with varying degree of success24,25. However, there is need to find novel genes and alleles for tolerance to submergence and other kinds of flooding stresses including anaerobic germination, deep water and prolonged water stagnation. Collection and characterization of rice landraces and traditional varieties adapted to flood-prone environments is important for the identification of donors with new genes and alleles. Present study aimed to analyze rice accessions from flood-prone areas of South and South East Asia, obtained through Genetic Resource Center (GRC), International Rice Research Institute (IRRI), Philippines and National Bureau of Plant Genetic Resources (NBPGR), New Delhi, India, along with additional genotypes obtained directly from rice breeders and farmers for population structure and sequence variation in the Sub1 genes. A set of 179 diverse rice accessions was assembled and screened for vegetative stage submergence tolerance at multiple locations to identify new donors. Further, the three Sub1 genes were amplified and sequenced to obtain SNP haplotype information and its possible association with the performance of the varieties under submergence stress.

Methods

Plant material

A set of 179 diverse rice genotypes was used (Supplementary Table S1). The seeds were obtained from GRC, International Rice Research Institute (IRRI), Las Banos, Philippines; ICAR-National Bureau of Plant Genetic Resources (NBPGR), New Delhi; Narendra Dev University of Agriculture and Technology (NDUAT), Kumarganj, Ayodhya; ICAR-Indian Agricultural Research Institute (IARI), New Delhi; ICAR-National Rice Research Institute (NRRI), Cuttack; and ICAR- National Institute for Plant Biotechnology (NIPB), New Delhi, including some varieties collected directly from the farmer’s field and maintained by ICAR-NIPB.

Genotyping with 36-plex SNP assay and analysis of population structure and diversity

DNA extraction was performed using QIAGEN DNeasy Plant Mini Kit (Hilden, Germany) from de-husked rice seeds as per manufacturer’s protocol. Sequenom MassARRAY system was used for the SNP genotyping (Sequenom Inc., San Diego, CA, USA; www. sequenom.com). The Sequenom MassARRAY multiplex assay, based on iPLEX gold chemistry, was designed for 36 SNPs, representing conserved single-copy rice genes26, taking three genes (two near the telomeres and one near the centromere) from each of the 12 rice chromosomes27. The 36-plex premixed assays were manufactured and validated by Sequenom Corporation (San Diego). The 30-mer pre-amplification primers and variable length genotyping primers were designed by AssayDesign 3.1 software. Sequenom MassARRAY Typer v3.4 Software was employed for SNP visualization and allele calling. The STRUCTURE v2.3.1 software was used to infer ancestral lineages and clusters of similar genotypes28. The clustering of genotypes were run for a range of K values from 1 to 9 with the admixture model and correlated allele frequency, replicated three times for each K value. A burn-in time span of 25,000 steps followed by 100,000 Monte Carlo Markov Chain replicates was implemented for each run. The ΔK values were plotted with Ln(PD) derived for each K value to generate Evanno plot29. Structure harvester software was used to calculate the optimum population structure (http://taylor0.biology.ucla.edu). The proportion of genome of an individual that belongs to each inferred population (admixture) was also estimated. A dendrogram of the 179 rice cultivars was constructed based on their 36 SNP scores. Concatenated SNP markers were aligned using ClustalW programme inbuilt in the BioEdit tool30. The tree was constructed using neighbor-joining method and phylogeny of the tree was tested using interior-branch test approach with 10,000 bootstrap replications. The genetic distance between sequences were analyzed using proportional (p) distances algorithm inbuilt in the MEGAX software31. The developed tree was visualized in figtree v1.4.3 programme (http://tree.bio.ed.ac.uk/software/figtree/)32.

Targeted re-sequencing of the Sub1 genes using Ion Torrent PGM

Reference sequence of the three Sub1 genes was downloaded from the NCBI GenBank (Sequence Id. for Sub1A, Sub1B, and Sub1C were DQ011598.1:3885-6447, DQ453964.1:2472-4557 and DQ453965.1:14767-16504, respectively) and PCR primers were designed using the Primer3 software (Table 1). Full-length genes were amplified and sequenced using Ion Torrent PGM system after random fragmentation, followed by assembly of the full gene sequence by mapping on the reference sequence using Ion Torrent PGM software. The PCR parameters for Sub1A gene amplification was initial denaturation at 95 °C for 5 min followed by 35 cycles of denaturation at 98 °C for 10 s, annealing at 68.5 °C for 10 s, and extension at 72 °C for 2.30 min, and then a final extension at 72 °C for 10 min. For Sub1B and Sub1C genes, initial denaturation at 95 °C for 5 min was followed by 35 cycles of denaturation at 98 °C for 10 s, annealing at 65.5 °C for 10 s, and extension at 72 °C for 2 min, and a final extension at 72 °C for 10 min. The PCR amplified products were checked by electrophoresis in 0.8% agarose gel. A flow diagram for the pooled amplicon sequencing of bar coded samples is shown in Supplementary Fig. S1. Pooled PCR products (510 ng) were end-repaired, and Ion Torrent adapters P1 and A were ligated using DNA ligase. Following AMPure bead (Beckman Coulter, Brea, CA, USA) purification, adapter-ligated products were nick-translated and PCR-amplified for 10 cycles. The resulting library was purified using AMPure beads (Beckman Coulter) and the concentration and size determined by Fluorometry and E–gel, respectively. The sample was then prepared for sequencing using the Ion Sequencing Kit protocol. The pooled sample was loaded on an Ion 316 chip and sequenced for 65 cycles.

Table 1 Primers used for PCR amplification of full-length Sub1A, Sub1B and Sub1C genes.
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Identification of SNPs, haplotypes and haplotype networks of the Sub1 genes

Data from the Ion Torrent PGM sequencing runs were processed using the Ion Torrent platform-specific software to generate sequence reads, trim adapter sequences and SNP calling by aligning with the reference sequence of the Sub1 genes. The consensus sequence for each variety was obtained using an in-house script; the heterozygous base positions were represented by actual international codes for two nucleotide combinations. DnaSP software was used for combined analysis of intervarietal comparisons. Sliding window analysis was performed to examine nucleotide polymorphism for the Sub1A, Sub1B and Sub1C genes in all the varieties with sequence information (DnaSP software version 5.10). Gene-specific PCR marker AEX1 was used to crosscheck the presence of Sub1A-1 allele25. The haplotype information based on high-quality SNPs in the three Sub1 genes was compiled manually for each rice genotype. Haplotype networks were constructed for analysis of genealogical relationship using Network software33 and haplotype diversity was calculated using DnaSP v5.1034.

Analysis of the Sub1 genes in 66 re-sequenced genomes

Draft genome assemblies of 66 rice genotypes, including 52 cultivars and 14 O. rufipogon wild rice accessions, were downloaded from the RicePanGenome database (http://db.ncgr.ac.cn/RicePanGenome/) and a local database was created. The reference sequence of Sub1A, Sub1B and Sub1C genes was used for BLASTN search35 against a locally created BLAST database of 67 genomes (including Nipponbare reference genome) using the parameters: -word size = 5, -perc identity = 80, -qcovs = 80. The results were tabulated and the hits were filtered at a bit score of ≥1000, nucleotide sequences of all the filtered hits were extracted and fasta files were created. Multiple sequence alignment of the fasta files was performed using Clustalw36, using default parameters and the SNP/InDel information was tabulated manually.

Phylogenetic analysis of the rice Sub1 genes

We searched for the presence of rice Sub1A, Sub1B and Sub1C gene homologs in the non-redundant “Green plant” database downloaded from NCBI (https://www.ncbi.nlm.nih.gov/). For similarity search a standalone NCBI-BLASTX programme was used with default search parameters. Further, we also searched for the copy numbers of rice Sub1C gene homologs in the reference genomes of 20 different monocotyledonous, dicotyledonous, moss and algal species with BLASTN programme using search parameters optimized earlier for such analysis37. Full-length sequence of the Sub1A, Sub1B and Sub1C genes present in each of the 13 rice varieties and Sub1C gene homolog from Sorghum bicolor, used as an outgroup, were aligned using Clustalw inbuilt in the BioEdit software30. The maximum likelihood based phylogenetic tree of the three genes was developed using RAxML v8.2.12 software38 and statistical reliability for each node support was estimated from 1000 replicates of non-parametric bootstrap with HKY85 model. The Sub1C gene homolog in Sorghum bicolor was used as outgroup for rooting the tree. The tree was visualized in figtree v. 1.4.332. The divergence times of Sub1A, Sub1B and Sub1C genes were estimated using the formula, T2 = (KABT1/KAX + KBX), where T2 = divergence time of Sub1A and Sub1B, T1 = divergence time of sorghum and rice, taken as 50–70 Mya39,40,41, KAB, KAX, and KBX are the synonymous substitution values between Sub1A and Sub1B of rice, Sub1A of rice and Sub1C of sorghum, and Sub1B of rice and Sub1C of sorghum, respectively42. The synonymous substitution values for each pair of genes were estimated using DnaSP programme34,43.

Phenotypic evaluation of vegetative stage submergence tolerance

Screening for survival under submergence was carried out at International Rice Research Institute (IRRI), Las Banos, Philippines; Narendra Deo University of Agriculture and Technology (NDUAT), Ayodhya, India; Banaras Hindu University (BHU), Varanasi, India; and Dr. Rajendra Prasad Central Agricultural University (RPCAU), Samastipur, India. At IRRI in 2012, the vegetative stage submergence screening was performed using an established protocol25. Seeds were sown in plastic trays filled with soil, each tray accommodating 10 entries with 30 plants each in Alpha Plus design to enable randomization of all entries in replication. After 14 days from sowing, the number of seedlings was recorded and the trays containing seedlings were transferred to a concrete submergence tank filled up to 1.5 m height with tap water. Once the susceptible IR42 plants showed severe stress symptoms (about 15 days of submergence) the plants were de-submerged and left for regeneration. Plant survival was recorded 21 days after de-submergence. At NDUAT, in Kharif season of 2012, experiment was laid out in augmented block design with two replications in concrete submergence pond of 20 × 10 × 1.2 m dimensions. Each block had 14 test entries plus two tolerant (Samba Mahsuri-Sub1 and FR13A) and one susceptible (Swarna) check. One-month old seedlings were transplanted in the ponds with row lengths of 2 m, and after establishment for two weeks the plants were submerged for 18 days. In one set as the plants grew under submerged conditions the canopies of highly elongating plants were cut to prevent breathing from the air. Fifteen days after de-submergence the number of surviving plants were recorded for both with and without canopy. The submergence screening was repeated at NDUAT in 2013 but in a lowland field with natural flooding. Experimental design and checks were similar to 2012 but this time with direct seeded rice with spacing of 20 × 10 cm. One month after sowing the fields were naturally flooded under 45–50 cm depths of water for 15 days. Then flood receded and plant survival was recorded 15 days after de-submergence. At BHU, in Kharif season of 2012, rice seeds were planted directly in a muddy pond and after 21 days of growth submergence was imposed for 14 days and then water was pumped out and plant survival was recorded one week after de-submergence. At RPCAU, in Kharif season of 2012, one-month old direct seeded rice plants in augmented design with FR13A and Samba Mahsuri-Sub1 as tolerant checks and IR42 as sensitive check replicated in every block were flooded with 1 m depth of water in a submergence tank. Percent survival of seedlings was recorded after 12 days of submergence followed by 15 days of recovery on de-submergence.

Association between Sub1 SNP haplotypes and submergence tolerance

The phenotypic performance as percent survival after submergence treatment, and SNP data for each of the three Sub1 genes along with its position in the sequence was fed into TASSEL v3 (2011) software44 to find association between Sub1 SNPs and submergence tolerance. A General Linear Model (GLM) analysis was employed, as MLM model did not produce any significant association, and Manhattan plots were prepared. In addition, the relationship of SNP haplotypes of Sub1A, Sub1B and Sub1C genes, Structure sub-populations and percent survival after submergence of the rice cultivars was also visualized in 3D scatter plots drawn using NCSS v19.0.3 software (https://www.ncss.com, date of access 28 Dec 2019) on IRRI 2012 phenotypic data. All the SNP haplotypes of Sub1A and Sub1B genes were used in the 3D scatter plot, but for Sub1C gene only those haplotypes with cultivar frequency of ≥3 were taken for clear visualization.

Results

Genetic diversity and population structure of 179 rice cultivars

Genetic variability of the 179 rice genotypes was assessed using a genome wide 36-plex SNP assay. SNP marker 12-1794 showed the highest major allele frequency of 0.9665, while 07-4304 showed the lowest major allele frequency of 0.4804 (Table 2). Polymorphism information content (PIC) values of the SNP markers ranged from 0.0636 for 12-1794 to 0.4436 for 10-1192-7_C_178 with an average of 0.2788 (Table 2). Analysis of population structure of the rice genotypes revealed two major sub-populations based on the results of Structure Harvester Evanno Plot between delta K and K (Fig. 1a,b). The optimum number of sub-populations (K) was determined after conducting multiple independent runs with K values ranging from 2 to 10. Most of the genotypes clustering in the two groups possessed Fst values of ≥0.80 indicating more than 80 percent inferred ancestry. Four varieties of sub-population 1, namely Aus 287, Ausboro, Jalmagna and Kasalath, and 14 varieties of sub-population 2, namely ARC 12172, Bagaikra, Dihawa, Dubgelong, Dular, FR13A, Kajrahawa, Kalonchi, Kharsu 80A, Khaiyan, Meghi, NCS 348, Suraha and Tundahia with Fst values of <0.80 possessed substantial admixture from the other sub-population. Sub-population 1 comprised 26 genotypes, mostly belonging to Japonica and Aromatic cultivar groups along with some locally adapted cultivars of unknown ancestry such as Badkodi, Baddhana, Bagagoha, Jokhru and Meghraj. Sub-population 2 comprised 151 genotypes belonging to Aus and Indica cultivar groups along with locally adapted Deep-water cultivars specific to flood-prone areas, e.g. Dudhaladu, Kalabunde, Kariyawa, Sugapankh, Suraha and Tundahia (Fig. 1a, Supplementary Tables S1 and S2). The bar diagram and Fst values clearly show that four genotypes in sub-population 1 (red shade), have more than 20% admixture from sub-population 2, whereas 14 genotypes in sub-population 2 (green shade) have more than 20% admixture from sub-population I. Since most of the molecular marker-based studies have reported five groups of rice cultivars, namely Aromatic, Aus, Indica, Temperate Japonica and Tropical Japonica, we further analyzed the population structures at K values of 4 and 5. Interestingly, the combined Aromatic-Japonica cluster in Fig. 1a was not separated even at K value of 5; therefore we restricted our analysis to K value of 4. This separated the Deep-water (sub-population 1), Indica (sub-population 2), Aus (Sub-population 3) and Aromatic-Japonica cultivars together in sub-population 4 (Supplementary Fig. S2, Table S3). Significantly, 17 of the 18 genotypes showing admixture of ancestry between Indica and Japonica cultivar groups at K = 2 (Fig. 1, lighter shades in Table S2), exclusively made the sub-population 3 representing Aus cultivars at K = 4 (orange shade in Table S3), only cultivar Jalmagna with Fst value 0.663 still stayed in the Aromatic-Japonica group. The new sub-population 1 (blue shade in Table S3), representing mostly flood tolerant deep-water rice cultivars of geographically diverse origin in India, Bangladesh, Guinea, Indonesia, Sierra Leone, Sri Lanka and Thailand was separated from the large Indica sub-population at K = 2.

Table 2 Major allele frequency and polymorphism information content (PIC) of 36 SNPs used in population structure and genetic diversity analysis of 179 rice cultivars.
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Figure 1
figure 1

Population structure of 179 rice cultivars based 36 genome wide unlinked SNP markers. (a) Two sub-populations corresponding to ‘Aromatic-Japonica’ (red) and ‘Indica’ (green) cultivar groups. Admixture types in the two sub-populations (with part red and green shades) were ‘Aus’ cultivars that formed a separate group at K = 4, (b) Delta K vs K Evanno plot showing peak delta at K = 2.

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A NJ diversity tree of 179 rice cultivars developed based on the 36 genome-wide SNP markers formed a separate cluster of 22 Aromatic-Japonica cultivars corresponding to the Structure sub-population 4 (red fonts in Fig. 2). Only one Aromatic-Japonica cultivar Megharaj was excluded and one deep-water cultivar Asamirupa was included in this cluster. All the 17 Aus cultivars of the Structure sub-population 3 formed a separate cluster in the NJ tree without exception (purple font in Fig. 2). Most of the lowland deep-water rice cultivars of Structure sub-population 1 were also grouped in a single clade (blue font in Fig. 2). The Indica group of cultivars of Structure sub-populations 3 formed six different neighboring sub-clades (green colour in Fig. 2). The Indica and Deep-water cultivars were part of a single clade separated from Aus and Aromatic-Japonica clades at the base of the NJ tree. The red and green clade colors in the NJ tree clearly show how three cultivars from the Japonica (Ausboro, Aus 287 and Kasalath) and 14 cultivars from the Indica (Dular, FR 13 A, Kalonchi, Khaiyan etc.) sub-populations with low Fst values at K = 2 (Fig. 1, Table S2) formed the separate clade of Aus sub-population at K = 4.

Figure 2
figure 2

NJ diversity tree of 179 rice cultivars used for allele mining of the Sub1 genes based on dissimilarity index of 36 genome wide unlinked SNP markers. Clade lines are colored according to groupings at K = 2, and cultivar names are colored according to groupings at K = 4. ‘Indica’ (Green), ‘Aromatic-Japonica’ (Red), ‘Aus’ (Magenta), and ‘Deep-water’ (Blue).

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Nucleotide sequence variation in the Sub1A, Sub1B and Sub1C genes

Three pairs of PCR primer were designed and optimized for amplification of full-length Sub1A, Sub1B and Sub1C genes (Table 1, Supplementary Fig. S3). As some of the rice cultivars are known to be null for Sub1A gene, amplification was not expected in all the genotypes for Sub1A, and indeed it amplified in only 96 of the 179 cultivars (Supplementary Table S4). For unknown reasons even Sub1B was amplified in 110 cultivars only despite repeating the experiment at least three times. This could be either due to absence of Sub1B gene in these genotypes, or more likely due to sequence mismatches at the 3′ end of the primers in these cultivars due to presence of SNPs/InDels. Best results were obtained with Sub1C where amplification was obtained in 174 of the 179 cultivars. The lack of amplification of Sub1C in five cultivars may also be because of sequence mismatches due to presence of mutations at the primer position or in rare case absence of the gene. The Ion Torrent PGM re-sequencing of pooled barcoded amplicons from 179 cultivars generated high-quality sequence data and polymorphism information. The assembled gene sequences have been deposited in NCBI public repository with Accession numbers: BankIt1844231: KT766732-KT766826; BankIt1856637: KT766827-KT766937; BankIt1856643: KT766938- KT767110, for the Sub1A, Sub1B and Sub1C genes, respectively. The SNP calls were made and exported in Excel file format using the Ion Torrent software suite by alignment with the reference BAC sequence of variety FR13A, which has all the three Sub1 genes19. An example of this is shown for Indica rice cultivar Madhukar, which also has the three Sub1 genes sequenced (Fig. 3). The SNP calls were of very high quality due to deep sequence coverage with high quality bases for each call (>10 sequence reads, each with minimum base quality score of Q20), and visual cross verification of the sequence alignment and SNP calls through the Ion PGM sequence analysis suite (Fig. 3). SNPs with low coverage or quality of sequence reads and all InDels, except four large InDels in Sub1C gene, were not considered for haplotype analysis. Only high quality variants, 7 SNPs each in Sub1A, Sub1B genes and 38 SNPs/InDels in Sub1C gene were taken for haplotype analysis. The positions of these high quality variants in the 5′ upstream promoter, intronic and exonic regions of the three genes with respect to the ATG start codon of the FR13A reference genes are shown in Fig. 4. In the protein coding exonic region, there were 2 SNPs in Sub1A and 1 SNP in Sub1B as compared to 29 SNPs and 2 InDels in Sub1C gene. In the 5′ promoter region there was no SNP in Sub1A up to −350 bp position, two SNPs in Sub1B at positions −643 and −282 as compared to 5 SNPs and 2 InDel in Sub1C at positions −38, −35 (InDel), −21 (InDel), −14, −9, −6 and −1. In the intronic region there were 5 SNPs in Sub1A and 4 SNPs in Sub1B, whereas Sub1C has no intron (Fig. 4).

Figure 3
figure 3

Sequence alignment and SNP calling for the Sub1 genes in Indica cultivar ‘Madhukar’ using IonTorrent PGM software. High-quality SNPs are tagged with red and blue squares in the consensus sequence on top of the alignment panel. (a) Sub1A, (b) Sub1B, (c) Sub1C.

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Figure 4
figure 4

Positions of high-quality SNPs/InDels in the Sub1 genes. Numbering of bases starts at the ATG start codon. Sub1C has 34 SNPs and four InDels indicated by *, two each in the 5′ upstream and exonic regions.

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After the initial work by Xu et al.19, there has been no targeted re-sequencing study to identify the allelic sequence variations in the rice Sub1 genes. However, whole genome re-sequence data are available in public domain e.g. 3000 rice varieties with average sequence depth of 14 × (3 K RGP 2014)45. Recently, a high-depth of coverage (average 115×) sequence data on 66 rice genomes, including 52 cultivars and 14 wild rice accessions, has been analyzed for the presence of Sub1A gene23, but not for allelic sequence variation in any of the three Sub1 genes. We analyzed these 66 genomes along with the reference Nipponbare genome and FR13A Sub1 genes for allelic sequence variation and compared it with our targeted re-sequencing results. Detailed results for the three Sub1 genes are presented in Supplementary Figs. S5–S7 and Table S5, but results with Sub1A gene is shown in Table 3. Six of the seven SNPs identified by targeted re-sequencing of Sub1A gene were common to the 66 genomes but one SNP at nucleotide position 878 was unique to the 179 cultivars set. Two SNPs were unique to the 66 genomes set but both of these were contributed by wild rice genotypes e.g. W0141. For the Sub1B gene only three of the seven SNPs identified by targeted re-sequencing were common to the 66 genomes, the remaining four SNPs were unique to the 179 cultivars set. Twenty-nine SNPs, mostly contributed by wild rice genotypes, were unique to the 66 genomes set (Supplementary Table S5). Most of the unique SNPs in the 66 genomes set were present in the 5′ upstream region of the Sub1B gene between −449 to −74 bp positions, where sequence coverage in the 66 genomes was poor, hence some of these could be due to sequencing errors rather than true SNPs. For the Sub1C gene, 28 of the 38 SNPs/InDels identified by targeted re-sequencing were common to the 66 genomes but 8 SNPs and two InDels were unique to the 179 cultivars. We found 22 SNPs unique to the 66 genomes that were spread throughout the gene but these were also contributed mostly by the wild rice genotypes (Supplementary Table S5).

Table 3 Comparison of SNPs in the Sub1A gene identified by targeted re-sequencing of 96 rice cultivars from which the gene could be amplified and sequenced, and analysis of 66 whole genome sequences of cultivated and wild rice (Zhao et al. 2018). SNP positions are indicated with respect to the ATG start codon.
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Sub1 homologs in other plant species and evolution of rice Sub1 genes

A BLASTX search in the NCBI NR database using the reference sequence of three Sub1 genes from cultivar FR13A resulted in only 22 significant matches with species other than Oryza sativa at a cutoff bit score of 100. Four of these matches were with Sub1A, one match with Sub1B, and 17 matches with Sub1C in 12 different species, namely Ipomoea batatas, Ipomoea nil, Lycoris longituba, Mucuna pruriens, Nicotiana tabacum, Nicotiana tomentosiformis, Oryza brachyantha, Oryza eichingeri, Oryza rhizomatis, Oryza rufipogon, Tarenaya hassleriana and Zostera marina (Supplementary Table S6). All the matches with Sub1A and Sub1B genes were limited to Oryza rufipogon and Oryza brachyantha. However, Sub1C homologs were found in eight other non-Oryza species, suggesting that Sub1C is the most ancient of the three Sub1 genes. Therefore, we searched for the presence of Sub1C homologs and its copy number in 20 completed plant genomes. Only nine of the 20 species analyzed possessed the Sub1C homologs and the copy number varied from one to three. Interestingly, only Camellia sinensis and Glycine max of the ten selected dicot species possessed Sub1C homologs. The duplicate matches in non-Oryza species were on different chromosomes ruling out tandem duplication (Supplementary Table S7).

To study the evolution of Sub1 genes in rice a maximum likelihood (ML) phylogenetic tree of the three genes was developed. Full-length sequence of the Sub1A, Sub1B and Sub1C genes present in each of the 13 rice varieties were taken along with the Sub1C homolog in Sorghum bicolor, used as an outgroup (Fig. 5). The phylogenetic tree indicated evolution of Sub1B and Sub1A genes from the ancestral Sub1C gene in that order by tandem duplication and divergence in the genus Oryza as only Sub1C homologs were present in the species other than genus Oryza. The divergence involved insertion of an intron towards the end of single exon in the Sub1C gene to give rise to Sub1B. Subsequently, the size of this intron has almost doubled from 451 bp in Sub1B to 817 bp in Sub1A. The estimated divergence time based on synonymous substitution rates showed that Sub1A diverged from Sub1B 6.44–9.02 Mya, taking monocot-dicot divergence time of 50–70 Mya based on fossil records for calibration of the tree. The estimated divergence time between Sub1B and Sub1C was 12.14–17.00 Mya.

Figure 5
figure 5

ML phylogenetic tree of Sub1A, Sub1B and Sub1C genes based on their sequence in 13 rice cultivars, and using Sorghum bicolor as outgroup. The tree was generated employing RAxML v8.2.12 algorithm and rooted with Sorghum bicolor as outgroup. Bootstrap analysis was performed with 1000 reiterations.

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SNP haplotypes and haplotype networks of the Sub1 genes

Seven high-quality SNPs identified in Sub1A gene by targeted re-sequencing of 96 rice cultivars made eight haplotypes designated H1 to H8, with submergence tolerant cultivar FR13A having reference haplotype H8 (Table 4). Two of the SNPs in the intronic region, namely SNP3 and SNP6 are novel that have not been reported previously. As reported earlier a threonine (T) at position 556 (SNP1) is the functional SNP coding for amino acid serine186 that confers submergence tolerance to FR13A, whereas the alternate base cytosine (C) at this position codes for amino acid proline186 resulting in submergence susceptible phenotype19. Since there was no new SNP in the exonic region in any of the varieties sequenced, no novel protein haplotype of the Sub1A gene was found. The eight SNP haplotypes resulted in two protein haplotypes, corresponding to the tolerant allele Sub1A-1 and intolerant allele Sub1A-2. SNP haplotypes H3-H8 coded for protein haplotype 1, whereas SNP haplotypes H1 and H2 produced protein haplotype 2 (Supplementary Table S9). Similarly, seven high-quality SNPs were identified in the Sub1B gene by re-sequencing of 110 cultivars where the gene could be amplified. Two of these SNPs are in the 5′ upstream region, one in the exon and four in the intron (Fig. 4). The seven SNPs made nine gene haplotypes and two protein haplotypes. All the SNP haplotypes of Sub1B, except H4, code for protein haplotype 1 (base guanine at position 280, SNP3), while H4 (base adenine at position 280, SNP3) codes for protein haplotype 2 (Table 5). This functional mutation leads to a change in amino acid residue from arginine94 in the reference protein haplotype 1 to tryptophan94 in protein haplotype 2 (Supplementary Table S9). The Sub1C gene amplified and sequenced from 174 genotypes revealed 38 high-quality variations (34 SNPs and 4 InDels), seven of which including two InDels were in the 5′ upstream region and 31 were in the exon (Fig. 4). Total size of the Sub1C amplicon sequenced was 1866 bp, including 110 bp of 5′ upstream region, 708 bp of exon and 1048 bp of 3′ downstream region but the 3′ non-coding region was not considered for SNP haplotype analysis. Excluding the downstream region total 67 SNP haplotypes were identified resulting in 36 protein haplotypes (Supplementary Tables S8 and S9).

Table 4 Nucleotide positions of seven high-quality SNPs with respect to the ATG start codon in the Sub1A gene and SNP haplotype frequencies in 96 rice cultivars from which the gene could be amplified and sequenced.
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Table 5 Nucleotide positions of seven high-quality SNPs with respect to the ATG start codon in Sub1B gene and SNP haplotype frequencies in 110 cultivars from which the gene could be amplified and sequenced.
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Initially, haplotype analysis was performed directly based on the nucleotide sequence of Sub1A, Sub1B and Sub1C genes using DnaSP programme. Haplotypes were identified (http://cmpg.unibe.ch/software/arlequin35) and networks were constructed using Hapstar software version 0.646,47. But, due to presence of additional InDels and heterozygous calls, much larger number of haplotypes was obtained (39 each for Sub1A, Sub11B and 140 for the Sub1C, (data not shown). Hence, for simplicity only manually curated high-quality variants, i.e. eight haplotypes for Sub1A gene in 96 cultivars, nine haplotypes for Sub1B gene in 110 cultivars and 67 haplotypes for Sub1C gene in 174 cultivars were considered for the network analysis. Although 38 high-quality SNPs/InDels in Sub1C gene of 174 cultivars formed total 67 haplotypes (Supplementary Table S8), network analysis was performed only on 15 haplotypes with genotype frequencies of three or more for a clear visualization of the network (Fig. 6). Network analysis of Sub1A gene clearly showed the evolutionary relationship and frequencies of its eight haplotypes (Fig. 6, Sub1A), where H5 was the ancestral haplotype from which other haplotypes have evolved through three independent routes. The most frequent haplotype H8 representing tolerant cultivar FR13A seems to have evolved most recently from the ancestral haplotype H5 through H6 and H7. Submergence sensitive haplotype H2 has followed a different evolutionary route from H5 through H3 and has further diversified into H1, whereas H4 has evolved directly from H5. Network analysis of Sub1B showed that the most frequent haplotype H6 representing 61 cultivars is the ancestral type from which other haplotypes have evolved through five independent routes (Fig. 6, Sub1B). The second most frequent haplotype H9, representing 37 cultivar including reference variety FR13A has evolved from H6 through H7 and H8 and has further diverged into H3. Haplotypes H1, H2, H4, and H5 have evolved directly from H6. Five of the nine haplotypes were present in just one cultivar each while H4 and H7 were present in 4 cultivars each (Table 5). Network analysis of Sub1C gene based on 15 most frequent haplotypes showed that the H47 was the most ancestral haplotype from which other haplotypes have evolved through multiple complex routes (Fig. 6, Sub1C). The reference variety FR13A possessed haplotype H1, which seems to have evolved recently through H61, H13 and H6. The most frequent haplotypes of Sub1C with genotype frequency of ten or higher were H1, H37, H61 and H50.

Figure 6
figure 6

Haplotype networks for Sub1A, Sub1B and Sub1C genes. Size of the circles reflects allele frequency in the cultivar set. Haplotype names (H1, H2…) correspond to that in Tables 4, 5 and Supplementary Table S8.

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Association of submergence tolerance with Sub1 haplotypes of the cultivars

Phenotyping for vegetative stage submergence tolerance was done at four different locations in 2012, including IRRI Manila, NDUAT Ayodhya, BHU Varanasi and RPCAU Samastipur. At NDUAT there were two trials in 2012 one with canopy and another one with cut canopy of elongating plants, also the experiment was repeated here in 2013, thus making total six sets of phenotyping data (Fig. 7, Supplementary Tables S10–S14). Trial conditions for the six experiments varied with respect to the structure of submergence pond, quality of water, age of plants submerged and duration of submergence and recovery, all of which affected the results. Full replications were possible only in IRRI 2012 because of plastic tray based mini plots and NDUAT 2013 due to natural field submergence in a large area. The remaining four experiments followed augmented design with only the check varieties repeated in each block in the submergence ponds. Accordingly, the replication means or adjusted means of survival were used for the analysis of cultivar performance. The stress was most severe at BHU 2012 where average survival rate of 126 genotypes after two weeks of submergence in natural floodwater was the lowest at 11.6% with a range of 0–100%. The stress level was mildest at RPCAU resulting in the highest average survival rate of 84.6% with a range of 42 - 100% for 175 cultivars, likely due to the shortest duration of only 12 days submergence. The stress here was too low to allow proper discrimination between tolerant and sensitive cultivars hence it was not used for further analysis. Stress level in the experiment at IRRI 2012 was optimum providing the best discrimination among 165 cultivars with mean survival rate of 65.9% in a range of 9.8–100%. In NDUAT 2012, average survival rate was 69.4% with a rage of 0–100% for the experiment with normal leaf canopy, which was more than twice the average of 31.3% survival where leaf canopies of elongating cultivars were cut to prevent air breathing. In NDUAT 2013, the stress level was high due to natural flooding with muddy water for two weeks.

Figure 7
figure 7

Regeneration of rice cultivars after two weeks of complete submergence in a concrete pond at NDUAT, Ayodhya in 2012. Differential response of the cultivars (planted in single rows) is clearly visible two weeks after de-submergence.

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However, despite the variation in trial conditions tolerant checks FR13A, FR43B, Sambha-Sub1 and Swarna-Sub1 showed high rate of survival and susceptible check IR42 showed low rate of survival across the five trials. The stress level at RPCAU with 81 cultivars showing more than 90% survival was non-discriminatory (Supplementary Table S15). Tolerant check FR13A showed 92.1–100% survival and sensitive check IR42 showed 0–35% survival in the five trials. Association between phenotypic performance of the rice cultivars and SNP genotypes was evaluated separately for each site and year because of large variation in the results. Large variation in phenotypic performance was observed for different locations and seasons. Significant association was detected using TASSEL software only with the SNPs in Sub1C gene and submergence tolerance data of BHU 2012 and NDUAT 2013 (Supplementary Fig. S4). Failure to validation of the known association of SNPs in the Sub1A gene with submergence tolerance in the TASSEL analysis, prompted us to make 3-D plots for graphical visualization of three-way relationship among population structure (Aus, Indica, Deep-water and Japonica-Aromatic cultivar groups), SNP haplotypes and percent survival of the cultivars under submergence stress based on survival data of IRRI 2012 (Fig. 8, Supplementary Table S16). The 3-D plots clearly show that submergence tolerant genotypes were present in all the four sub-populations, but there were proportionately larger number of tolerant genotypes in the Aus group, represented by FR13A. Among the various haplotypes of the Sub1A, Sub1B and Sub1C genes, there was no clear association between haplotype and the level of tolerance. There were exceptions to the known association of tolerant Sub1A-1 allele (haplotype H8) of FR13A, where nine cultivars with haplotype H8 showed survival rates below 50% (Fig. 8, Sub1A, Supplementary Table S16). Conversely, there were 15 cultivars without haplotype H8 but with more than 80% survival, e.g. six out eight cultivars with haplotype H3 and all four cultivars with haplotype H5 showed above 60% survival. However, both haplotype H3 and H5 have the same protein haplotype as the tolerant haplotype H8. Two cultivars with haplotype H1 and nine cultivars with haplotype H2 (both representing the sensitive allele Sub1A-2) showed more than 70% survival. Since Sub1A-1 (Haplotype H8) is the established tolerant allele, we analyzed all the genotypes using functional allele-specific PCR marker AEX125 to reconfirm the presence of Sub1A1 allele (Supplementary Table S17). It is expected that all the cultivars with SNP haplotypes H1 and H2 or null allele for the Sub1A gene should not give any amplification, whereas haplotypes H3-H8 should produce a PCR amplicon of 231 bp. As expected none of the 31 cultivars with haplotypes H1 and H2 gave AEX product. However, nine out of 83 cultivars without Sub1A gene amplification showed AEX amplification, the discrepancy is most likely due to failure of PCR amplification of the Sub1A gene in these due to primer mismatches. Forty-one of the 65 cultivars possessing Sub1A haplotypes H3-H8, also showed the expected AEX amplification, 24 did not amplify which again could be because of primer mismatches due to mutational changes in the flanking sequences.

Figure 8
figure 8

3-D graphs showing relationship between Structure sub-population, SNP haplotype and percent survival of rice cultivars based on submergence tolerance data from IRRI in 2012. Reference alleles of Sub1A, Sub1B and Sub1C genes from tolerant variety FR13A are represented by haplotypes H8, H9 and H1, respectively.

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For Sub1B gene, H9 was the reference haplotype of cultivar FR13A, which together with all other SNP haplotypes coded for protein haplotype 1, except for H4 that coded for protein haplotype 2. Five of the nine haplotypes are represented by one genotype each hence not suitable for association analysis. Of the remaining four, H4 coding for an altered protein and genotype frequency of four showed a range of survival from 15.8% to 89.2%. Haplotype H6 with the highest genotype frequency of 61 also showed a wide range of survival response from 18.4% to 95%, haplotype H8 with genotype frequency of four also showed survival range of 17.5% to 92.5%. Interestingly, all but one of the 37 genotypes possessing reference haplotype H9 showed survival of more than 50%. A clear difference was visible between the survival patterns of cultivars possessing two most frequent Sub1B haplotypes H6 and H9 with the reference haplotype H9 showing much higher survival frequency (Fig. 8, Sub1B).

For Sub1C gene, the 3D plot was drawn for 15 SNP haplotypes with genotype frequencies of three and above (Fig. 8, Sub1C). The reference haplotype H1 representing tolerant cultivar FR13A was present in the highest number of 22 cultivars, 20 of which showed survival above 50%, 17 genotypes above 60% and 9 genotypes above 80%. Thus, H1 was clearly associated with submergence tolerance with very few exceptions. Another common haplotype H37 was present in 14 cultivars but showed variable level of survival from 26–92.1% with seven of them showing survival above 75%. Haplotype H50 was present in 11 cultivars but only two of these showed survival higher than 75%. Another frequent haplotype H61 was present in 13 cultivars only three of which showed survival above 75%. Among minor alleles, haplotypes H41, H43 and H52 with genotype frequencies of 4, 4 and 5, respectively have more than three-fourth of the genotypes with survival above 80%, whereas most of the cultivars with haplotypes H6, H13, H39 and H47 showed poor survival.

Novel non-Sub1A-1 sources of submergence tolerance

A comparison of the best performing entries across five trials at three different locations at IRRI, NDUAT and BHU identified cultivars showing consistently high level of submergence tolerance across locations and trial conditions (Table 6, Supplementary Table S15). The best four cultivars, showing consistent high level of submergence tolerance in each of the five trials, were Madal, Mahadikwee, S-138 and Singhara. Another group of 10 cultivars showing high level of tolerance in four out of five trials included, ARC 614, Dholmon 64-3, Goda Heenati, Heen Sulai, Houra Kani, Kariyawa, Kaluwee, Naldak, Nirboi, and Tetep. Further 18 cultivars, namely Ausboro, Birpala, CR1009, IR 64, Jaldungi, Kajarahawa, Karkati 87, Karnal Local, Kasalath, Menyar Hunei, Naaluumoli Karuppan, Paiaim, Pakri Buna, Panidubi, Pankee, Pataim, Rajbhog and Sangkhla showed high level of submergence tolerance in three out of the five trials. These 32 cultivars can be considered as having consistently high level of submergence tolerance. A look at the Sub1 gene haplotypes of these cultivars revealed that five of these cultivars have the Sub1A, Sub1B and Sub1C haplotype combination H8, H9, H1 that is identical to the tolerant cultivar FR13A (Table 6). Another nine cultivars even though having different haplotypes for the Sub1B and Sub1C genes, possessed either identical (H8) or synonymous haplotypes (H3-H7) for the Sub1A gene (Table 6), and therefore possess the same Sub1A-1 dependent submergence tolerance. The remaining 18 cultivars were either null or possessed the sensitive allele Sub1A-2 (haplotypes H1 and H2) of the Sub1A gene (Table 6). Hence, these must possess Sub1A-1 independent mechanism of submergence tolerance. In fact 10 of the 14 cultivars showing consistent submergence tolerance in four to five trials appear to possess non-Sub1A1 type submergence tolerance (Table 6).

Table 6 Submergence tolerant rice cultivars showing consistent performance in five different trials across three locations, along with population Structure (1. Deep-water, 2. Indica, 3. Aus, 4. Aromatic-Japonica), AEX marker amplification and Sub1 SNP haplotypes. Bold and normal fonts indicate Sub1A-1 dependent and Sub1A-1 independent tolerance, respectively.
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Discussion

Utilization of the Sub1 QTL in development and commercialization of submergence tolerant versions of high-yielding rice cultivars is a remarkable success story of genomics-assisted breeding for accelerated transfer of climate resilience from traditional varieties into green revolution varieties25,48,49. However, there are different kinds of flooding stresses affecting establishment and yield of rice including submergence during germination, water stagnation for extended period and deep-water flooding that need attention16. Also, there are Sub1-independent mechanisms of complete submergence tolerance that need to be explored and harnessed. There is limited number of studies on allelic sequence variation in the three Sub1 genes. This includes sequence survey of the three Sub1 genes in 17 Indica and four Japonica cultivars19, 14 accessions of cultivated and three accessions of wild rice O. rufipogon20, marker survey of Sub1A and Sub1C alleles in 109 rice genotypes and sequencing of Sub1 gene orthologs in two accessions of O. eichingeri and O. rhizomatis21, marker survey of Sub1A and Sub1C alleles in 76 rice cultivars50, and CAPS marker survey of Sub1A and Sub1C genes in 160 rice varieties22. Whole genome sequence data is available for 3000 rice varieties from 3 K RGP project45 and 66 rice genomes including 14 wild rice accessions23, but these have not been analysed for sequence variation in the Sub1 genes. Thus, present study on the analysis of sequence variation in Sub1A, Sub1B and Sub1C genes of 179 diverse rice cultivars grown in the flood prone areas and its association with submergence tolerance provides novel information.

Genetic diversity and population structure of uncharacterized flood tolerant rice germplasm is an essential pre-requisite for association studies for identification of new QTLs and genes. Germplasm characterization using high-throughput genotyping methods and development of breeding strategy based on this has already started in rice51,52. Structure analysis of 179 such cultivars in this study classified them into two major sub-populations, representing (i) Japonica and Aromatic cultivar groups, and (ii) Indica and Aus cultivar groups. Four cultivars in sub-population 1 and 14 cultivars in sub-population 2 showed inferred ancestry of less than 80% of the group they belonged, indicating admixture types. It was interesting that Structure analysis at K value of four separated all the 14 admixture types from Indica sub-population and three out of four admixture types from Aromatic-Japonica sub-population to make a separate group of 17 Aus cultivars each with a high Fst value of greater than 0.80. This indicates that Aus cultivars share common ancestry with both Indica and Japonica groups and may provide a link between the two. Aus cultivars are important source of genes for tolerance to abiotic stress including flood and drought. They have short duration, adaptation to multiple stresses and are grown all over Indian sub-continent and adjoining regions of South-East Asia. Aromatic cultivars are known to be closer to Japonica group and Aus cultivars are closer to Indica group51,53,54. Isozyme-based diversity analysis by Glasszmann54, classified rice into six cultivar groups, with only one Japonica group (combining tropical and temperate Japonica) but two additional groups of Rayada and Ashina, representing deep water and floating rice of Bangladesh and India, respectively. Studies with large number of genomic SSR/SNP markers have reported five groups of rice cultivars, namely Indica, Tropical Japonica, Temperate Japonica, Aromatic and Aus51,52. Our results are in closer agreement with the classical work of Glaszmann54 employing 15 isozyme marker loci, likely because we used 36 SNP markers from conserved single-copy genes distributed on the 12 rice chromosomes.

Analysis of sequence polymorphism in the functional genes for agronomic traits is necessary for identification of superior alleles in the germplasm. Map-based cloning of Sub1A gene and its functional validation by genetic transformation has proven its role in submergence tolerance of rice19. But after the original work, which also included sequencing of Sub1A, Sub1B and Sub1C genes from 21 rice cultivars, no further studies have been undertaken on allelic sequence variation in the Sub1 genes, although marker based allele surveys have been done for Sub1A and Sub1C genes in larger sets of cultivars21,22,50. Here, we generated high-quality sequence information by targeted re-sequencing of pooled PCR products from 96 cultivars for Sub1A, 110 cultivars for Sub1B and 174 cultivars for Sbu1C gene, resulting in comprehensive allelic sequence information. We also analysed the publicly available whole genome sequence data on 66 rice genomes for this purpose. These together identified 9 SNPs in Sub1A, 37 SNPs in Sub1B and 56 SNPs plus four InDels in Sub1C gene. Of these, one, four and 10 SNPs were unique to the 179 cultivars set, whereas two, 29 and 22 SNPs were unique to the 66 genomes set, respectively. Most of the unique SNPs in the 66 genomes set were due to 14 wild rice accessions (Supplementary Table S5), suggesting that our res-sequencing work has provided a comprehensive coverage of the Sub1 gene sequence variation in rice cultivars.

Based on the seven SNPs each in the Sub1A and Sub1B genes and 38 SNPs/InDels in the Sub1C gene in 179 cultivars, eight, nine and 67 SNP haplotypes were identified, respectively. Many of these haplotypes were rare represented by only one or two cultivars. The number of SNPs in the exonic regions was limited to 2 in Sub1A, 1 in Sub1B but it was very high 29 in Sub1C gene. The high level of variation in Sub1C gene is indicative of its ancient origin resulting in accumulation of more mutations over time as compared to Sub1A and Sub1B. This was also supported by our BLASTX search results showing that Sub1A and Sub1B gene homologs were limited to genus Oryza only, while Sub1C homologs were present in other distant genera including Zostera, Mucuna, Torenya and Nicotiana, indicating their ancient origin. The ML based phylogenetic tree of the three Sub1 genes from 13 rice cultivars, rooted with a Sub1C homolog from S. bicolor, also indicated the evolution of Sub1B and Sub1A genes by duplication and divergence of the ancestral Sub1C gene at the most 12.40 Mya and 17.0 Mya, respectively (Fig. 5). Fukao et al.20 has also suggested evolution of Sub1A gene by duplication and divergence from Sub1B which in turn has evolved from duplication of Sub1C. Major haplotypes of the three genes were present in both Indica and Japonica sub-populations suggesting no substantial barrier for gene flow across the two groups. The reported absence of Sub1A gene in Japonica cultivars has been because of limited number of Japonica varieties analysed in the earlier allele survey studies19.

No consistent association was found between SNPs in the Sub1 genes and percent survival after submergence of 179 cultivars by TASSEL analysis. Only significant association was obtained with SNPs in the Sub1C gene and submergence tolerance data from BHU 2012 and NDUAT 2013, where stress intensity was the highest with average survival rates of 11.6% and 31.3%, respectively (Supplementary Fig. S4). Whether or not this association is real need further validation using precise phenotyping repeated in different locations/seasons. Surprisingly, the known association of the Sub1A-1 allele with submergence tolerance was not validated in the present study due to presence of several exceptions in the present cultivar set. This was also reflected in a direct visualization of data in 3D plots (Fig. 8), where nine cultivars with the tolerant Sub1A-1 allele (haplotype H8) showed poor survival after submergence. On the other hand several cultivars with the sensitive Sub1A-2 allele (haplotype H2) showed high level of tolerance across locations (Fig. 8, Table 6). There are at least six published reports of Sub1A-1-independent mechanisms of submergence tolerance in rice5,9,14,21,50,55. Supporting our TASSEL results of significant associations with Sub1C SNPs at two locations, the 3D plot also showed only one exception to the association between submergence tolerance and tolerant Sub1C allele (haplotype H1). However, these exceptions need further analysis in bi-parental segregating populations. Importance of Sub1-independent mechanism of submergence tolerance has been highlighted decades ago56 and major non-Sub1 QTLs have been identified using Madabaru/IR72 and Chehrang-Sub1/IR10F365 populations, suggesting Sub1-independent mechanism of vegetative stage submergence tolerance14,21.

To conclude, we identified several new alleles of the three Sub1 genes by targeted re-sequencing of 179 rice cultivars. Further, we identified 32 cultivars showing consistently high level of submergence tolerance in five trials at three different locations. Fourteen of these cultivars possessed the known Sub1A-1 dependent submergence tolerance, but 18 cultivars have Sub1A-1 independent submergence tolerance as they are either null for the Sub1A or possess submergence sensitive allele Sub1A-2 (haplotypes H1 and H2), although cultivar Goda Heenati is shown in other studies to possess the tolerant allele19. There is a need to identify the submergence tolerance QTLs and underlying genes in these cultivars using bi-parental mapping populations for effective utilization in rice breeding programme. We also report for the first time presence of Sub1A gene in Japonica and Aromatic groups of rice cultivars including Kola Joha and Karnal Local, which will be useful in breeding flood-tolerant aromatic rice cultivars.