Data Sets

C7AIR – 7K SNP array

Morales KY, Singh N, Perez FA, Ignacio JC, Thapa R, Arbelaez JD, et al. (2020) An improved 7K SNP array, the C7AIR, provides a wealth of validated SNP markers for rice breeding and genetics studies. PLoS ONE 15(5): e0232479. [Paper download] ">

• Germplasm

• S1 Table. List of 544 Oryza accessions with inferred ancestry and subpopulation assignments [Excel File]

• SNP data

• S2 Table. Trait-specific SNP markers [Excel File]
• S3 Table. SNP Manifest File [Excel File]
• S4 Table. SNP Genotype Data Matrix for 7,098 SNPs x 544 Oryza accessions and plant height data for subset of accessions [Excel File]

• Kinship Values

• S5 Table. Kinship values generated using highest performing SNPs [Excel File]

• Polymorphism comparisons

• S6 Table. Polymorphisms between and within Oryza species, subpopulations [Excel File]

Rice Imputation

Diane R. Wang, Francisco Agosto-Perez, Dmytro Chebotarov, Yuxin Shi, Jonathan Marchini, Melissa Fitzgerald, Kenneth L. McNally, Nickolai Alexandrov, Susan R. McCouch. An imputation platform to enable efficient integration of rice genetic resources. Nature Communications doi 10.1038/s41467-018-05538-1

• Genotypes

• RICE-RP dataset [RICE-RP dataset]
• Supplementary Data 1_RIS Germplasm file [Wang_Suppl Data 1_RIS Germplasm file_180703.xlsx]

• Data for indica GWA using imputed data

• Genotype, phenotype and kinship matrix [GWAS_IND_chr6_imputed_var_170309.Rbin]
• Script [GWAS_HDRA_Imputed_amyloseContent_indica_subpop.R]

• GWA Results

• Results using original HDRA data [GWAS_HDRA_nonIMPUTED_chr6_IND_0PC_AMYLOSE.csv]
• Results using imputed data [GWAS_HDRA_IMPUTED_chr6_IND_0PC_AMYLOSE_170309.csv]

CSSLs for Curinga x O. meridionalis and Curinga x O. rufipogon

Arbelaez JD, Moreno LT, Singh N, Tung CW, Maron LG, Ospina Y, Martinez CP, Grenier C, Lorieux M, McCouch SR (2015) Development and GBS-genotyping of introgression lines (ILs) using two wild species of rice, O. meridionalis and O. rufipogon, in a common recurrent parent, O. sativa cv. Curinga. Mol Breeding 35:81. doi 10.1007/s11032-015-0276-7

• Germplasm

• Updated Figure 3 (a) (link to file Figure3_(a)_update.pdf )

• Genotypes

• Curinga x O. meridionalis
• 6K SNP chip
• Excel file with AA (Curinga ) / BB (O. meridionalis) format (link to file - 6K_data_CUMER_CSSL_180725.xlsx )
• Hapmap file with A, C, G, T nucleotide (link to file - 6K_data_CUMER_CSSL_20161107.hmp.txt )
• GBS
• Hapmap file with A, C, G, T nucleotide (link to file - GBS_data_CUMER_CSSL_20161107.hmp.txt )
• Curinga x O. rufipogon
• 6K SNP chip
• Excel file with AA (Curinga ) / BB (O. meridionalis) format (link to file - 6K_data_CURUF_CSSL_180725.xlsx )
• Hapmap file with A, C, G, T nucleotide (link to file - 6K_data_CURUF_CSSL_20161107.hmp.txt )
• GBS
• Hapmap file with A, C, G, T nucleotide (link to file - GBS_data_CURUF_CSSL_20161107.hmp.txt )

Combined GBS and 6K Minimun SNP set

• README (link to file - README_CUMER & CURUF_Minimum SNP set_160929_update.docx )
• Curinga x O. meridionalis (link to file - GBS_6K_CUR_MER_32_566_dbSNPs_MSUv7_20160212.txt )
• Curinga x O. rufipogon (link to file - GBS_6K_CUR_RUF_48_2272_dbSNPs_MSUv7_20160212.txt )

Other tables, figures and supplementary materials

• Please see links to supplementary files in the paper at - https://link.springer.com/article/10.1007/s11032-015-0276-7 )

Population Structure in the Oryza rufipogon Species Complex

Kim H, Jung J, Singh N, Greenberg A, Doyle J, Tyagi W, Chung J-W, Kimball J, Hamilton R, McCouch S (2016) Population dynamics among six major groups of the Oryza rufipogon species complex, wild relative of cultivated Asian rice. Rice 9:56 doi 10.1186/s12284-016-0119-0

• Germplasm

• Supplementary TabF1-Table S1 (Excel File)

• Genotypes

• Nuclear GBS data: NCBI batch submission ID is 1062455 (Link)
• Chloroplast SNP data: the accession for each region listed below. The records can be retrieved from the nucleotide database by searching Entrez Nucleotide: Using the accession numbers.
• chloroplast_region1: KX556608 - KX556920
• chloroplast_region2: KX556921 - KX557233
• chloroplast_region3: KX556295 - KX556607
• chloroplast_region4: KX555982 - KX556294
• chloroplast_region5: KX555669 - KX555981

High Density Rice Array (HDRA, 700k SNPs)

McCouch S, Wright M, Tung C-W, Maron L, McNally K, Fitzgerald M, Singh N, DeClerck G, Agosto Perez F, Korniliev P, Greenberg A, Nareda ME, Mercado SM, Harrington S, Shi Y, Branchini D, Kuser-Falçao, Leung H, Ebana K, Yano M, Eizenga G, McClung A, Mezey J. (2016) Open Access Resources for Genome Wide Association Mapping in Rice. Nature Comm, 7: 10532 doi 10.1038/ncomms10532

• Germplasm

• Supplementary Table 1 (Text File) , (Excel File)

• Genotypes

• Plink genotype data bundle HDRA-G6-4-RDP1-RDP2-NIAS-2.tar.gz
• VCF genotype data HDRA-G6-4-RDP1-RDP2-NIAS.ACGT.VCF.gz
• Hmp Txt genotype data HDRA-G6-4-RDP1-RDP2-NIAS.AGCT.hmp.txt.gz
• SNP Info HDRA-G6-4-SNP-MAP.tar.gz

• Phenotypes

• Grain length phenoAvLen_G6_4_RDP12_ALL.tar.gz

• GWAS Results

All GWAS results were generated by using our GWAS pipeline which can be obtained from our Tools and Resources section

• Figure 3 from McCouch et al 2016: p-values and best SNP summary file for all subpopulations for RDP1, and all subpopulations for RDP1+2,.
• Download data HDRA_GWAS_figure3-pvalues.tar.gz
• Figure 5 from McCouch et al 2016. p-values and best SNP summary file for RDP1+2 for all subpopulations, INDICA, JAPONICA, with and without covariates.
• Download data HDRA_GWAS_figure5-pvalues.tar.gz
• Supplementary figure 4 from McCouch et al 2016. p-values and best SNP summary file for RDP1+2 for all subpopulations, AUS, IND, TEJ, TRJ, with and without covariates.
• Download data HDRA_GWAS_supplementary_figure4-pvalues.tar.gz
• For more information visit the GWAS viewer on our Tools and Resources section

•NCBI Assets

• GEO Acession ID:GSE71553
• dbSNP Dataset handle: RICE-DIVERSITY-700K. Batch submission ID: 1062024

Panicle Architecture

Crowell S, Korniliev P, Falcão A, Ismail A, Gregorio G, Mezey J, McCouch S. 2016. Genome-wide association and high-resolution phenotyping link Oryza sativa panicle traits to numerous trait-specific QTL clusters. Nature Communications (in press).

• GWAS and Association Network Results Suppl 1-11
• Phenotype Raw and Avg Data Suppl 12-15

Genomic Selection for IRRI breeding population

• Spindel, J.E., Begum, H., Akdemir, D., Virk, P., Collard, B., Redoña, E., Atlin, G., Jannink, J., McCouch, S. (2015). "Genomic Selection and Association Mapping in rice (Oryza sativa): Effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines." PLoS Genetics 11(2). doi: 10.1371/journal.pgen.1004982
• (co-first authors) Spindel, J.E., Begum, H., Lalusin, A.G., Borromeo, T.H., Gregorio, G.B., Hernandez, J.E., Virk, P.S., Collardy, B.C.Y., McCouch, S. (2015) "Genome-wide association mapping for yield and other agronomic traits in an elite breeding population of tropical rice (Oryza sativa)." PLoS One 10 (3). doi: 10.1371/journal.pone.0119873
• Genotype data
• MET_crfilt_.75_allchrom.hmp.txt.zip -- Post-imputation GBS data for the IRRI breeding population used in Spindel et al., 2015 and Begum and Spindel et al., 2015 (with additional filtering, see papers for details). GBS dataset contains all SNPs with call rates >= .75 and all individuals with missing data < .6.
• MET_crfilt_.90_outliers_removed_for_RRBlup_line_corrected.csv -- Post-imputation GBS dataset used specifically for GS cross-validation in Spindel et al., 2015. Dataset contains all markers with call rates >= .9 and lines that were included in the GS analysis (i.e., sub-population outliers are removed from this dataset). The data are formatted for use with the R rrBLUP package.
• MET_crfilt_.75_MAF_.05_outliers_removed_mono_dropped.hmp.txt.zip -- post-imputation GBS dataset used specifically for GWAS in Spindel and Begum et al., 2015. Dataset contains all markers with call rates >= .75 and minor allele frequency >= 0.05. Monomorphic SNPs and subpopulation outliers are removed.
• binned_subsets_2_14.zip -- contains the evenly distributed genotype subsets used in Spindel et al., 2015
• random_subsets_from_.75_crFilt.zip -- contains the randomly distributed genotype subsets used in Spindel et al., 2015
• Phenotype data
• RYT_plotdata_by_GHID_corrected_PUBLIC_ACCESS.zip -- contains the raw phenotype data for genotyped individuals for 2009-2012, dry and wet seasons, used in Spindel et al., 2015.
• 2012DSRYT_Predicted means_FINAL_PUBLIC.csv -- predicted means for the 2012 dry season phenotype data used in Begum and Spindel et al., 2015
• 2012WSRYT_Predicted means_FINAL_PUBLIC.csv -- predicted means for the 2012 wet season phenotype data used in Begum and Spindel et al., 2015



GBS data for IR64 x Azucena RIL population - GBS data from Spindel et al 2013

• (co-first authors) Spindel, J.E., Wright, M., Chen, C., Cobb, J., Gage, J., Harrington, S., Lorieux, M., Ahmadi, N., McCouch, S. (2013). "Bridging the genotyping gap: using genotyping by sequencing (GBS) to add high-density SNP markers and new value to traditional bi-parental mapping and breeding populations." Theoretical and Applied Genetics 126(11): 2699-2716. doi:10.​1007/​s00122-013-2166-x
• Associated Analysis Tools
• Finalized imputed and corrected GBS dataset for the IR64 x Azucena RIL population: Download Data [TXT - Hapmap]
• Formatted for import into R/qtl: Download Data [CSV]
• SNP convert table of MSUv6 and MSUv7 Download Data [CSV]
• Raw HiSeq library data - formatted for input into PANATI or TASSEL GBS Pipeline. Use with associated key file.
  • C08N9ACXX_1-IR64-Azucena.fq.bz2
  • C08N9ACXX_1-key-file.tsv
  • D0DTNACXX_1-IR64-Azucena.fq.bz
  • D0DTNACXX_1-key-file.tsv
• Oryza sativa MSU6.0 pseudomolecule sequences (gzipped fasta file)
• Oryza sativa RGAP7.0 pseudomolecule sequences (fasta file)



IR64xNipponbare RIL imputed GBS data

IR64xNipponbare RIL imputed GBS data, formatted for rqtl. Parent 1 (A) = IR64
• IR64_Nipp_m15_n60_w5_post_plumage3_rqtl.csv
• IR64_Nipp_m15_n60_w5_post_plumage3.txt
• IR64_Nipp_RILs_m15_n60_w5_genetic_map.pdf



1536 SNP set

We describe the construction and usage of a 1536 SNP chip to study the genetic diversity in O. sativa in this recent publication:

• Zhao K, Wright M, Kimball J, Eizenga G, McClung A, Kovach M, Tyagi W, Ali ML, Tung CW, Reynolds A, Bustamante CD, McCouch SR (2010). Genomic Diversity and Introgression in O. sativa Reveal the Impact of Domestication and Breeding on the Rice Genome. PLoS One. 2010; 5(5): e10780. Published online 2010 May 24. doi: 10.1371/journal.pone.0010780
• Download Data



44K SNP set

We show the results of a genome-wise association study based on genotyping 44,100 SNP variants across 413 diverse accessions of O. sativa from 82 countries that were systematically phenotyped from 34 traits:

• Keyan Zhao, Chih-Wei Tung, Georgia C. Eizenga, Mark H. Wright, M. Liakat Ali, Adam H. Price, Gareth J. Norton, M. Rafiqul Islam, Andy Reynolds, Jason Mezey, Anna M. McClung, Carlos D. Bustamante & Susan R. McCouch (2011). Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa. Nat Comm 2:467 | DOI: 10.1038/ncomms1467, Published Online 13 Sep 2011.
• Download Data



384 SNP OPAs

We describe the development of seven different 384-SNP assays designed for application in different subpopulations and species of rice, as described in this publication:

• Michael J. Thomson, Keyan Zhao, Mark Wright, Kenneth L. McNally, Jessica Rey, Chih-Wei Tung, Andy Reynolds, Brian Scheffler, Georgia Eizenga Anna McClung, Hyunjung Kim, Abdelbagi M. Ismail, Marjorie de Ocampo, Chromewell Mojica, Ma. Ymber Reveche, Christine J. Dilla-Ermita, Ramil Mauleon, Hei Leung, Carlos Bustamante, Susan R. McCouch (2011) High-throughput single nucleotide polymorphism genotyping for breeding applications in rice using the BeadXpress platform. Mol Breeding (on-line ahead of print) DOI 10.1007/s11032-011-9663-x.
• Download Data

Seven custom GoldenGate VeraCode oligo pool assay (OPA) sets designed for multiplexed SNP genotyping in rice

Rice SNP set	Illumina OPA ID	No. of SNPs (MSU6)	No. of SNPs (MSU7)	Description	Applications
RiceOPA1.0	VC0011438-OPA	96	95	Quality control	Assign accessions into one of five O. sativa subgroups, and use for quality control of seeds/samples.
RiceOPA2.1	GS0011861-OPAa	384	383	Indica/Indica	Assay variation within indica and aus germplasm, informative for Indica/Indica populations.
RiceOPA3.1	GS0011862-OPAb	384	384	Indica/Japonica	Assay variation across O. sativa groups, informative for Indica/Japonica populations.
RiceOPA4.0	GS0011897-OPA	384	384	Japonica/Japonica	Assay variation within tropical japonica germplasm, informative for Japonica/Japonica populations.
RiceOPA5.0	GS0011972-OPA	384	383	Indica/O. rufipogon	Informative for Indica/O. rufipogon populations.
RiceOPA6.0	VC0011530-OPA	384	383	Japonica/O. rufipogon	Informative for Japonica/O. rufipogon populations.
RiceOPA7.0	VC0011440-OPA	384	384	Indica/Japonica	Informative for specific Indica/Japonica populations.

^a This OPA is a re-design of the earlier VC0011439-OPA (15 of the 384 SNPs were replaced).
^b This OPA is a re-design of the earlier VC0011460-OPA (11 of the 384 SNPs were replaced).

2, 240 SSR markers for rice

In this study, a set of di-, tri-, and tetra-nucleotide non-redundant SSR primer pairs representing unique marker loci were developed and experimentally validated for rice (Oryza sativa L.). The majority (92%) of primer pairs were developed in regions flanking perfect repeats ≥24 bp in length. In combination with the pool of 500 previously mapped SSR markers, this release makes available a total of 2740 experimentally confirmed SSR markers for rice, or approximately one SSR every 157 kb

• McCouch S, Teytelman L, Xu Y, Lobos K, Clare K, Walton M, Fu B, Maghirang R, Li Z, Xing Y, Zhang Q, Kono I, Yano M, Fjellstrom R, DeClerck G, Schneider D, Cartinhour S, Ware D, Stein L. (2002) Development of 2,240 new SSR markers for rice (Oryza sativa L.). DNA Research 9(6):199–207. McCouch_2,240 SSRs for rice_DNARes_02.pdf
• Supplemental Figure 1 Here
• Supplemental Table 1 Here