Supplementary Data

GL3.3, a novel QTL encoding a GSK3/SHAGGY-like kinase, epistatically

interacts with GS3 to form extra-long grains in rice

Duo Xia, Hao Zhou, Rongjia Liu, Wenhan Dan, Pingbo Li, Bian Wu, Xiaojun

Chen, Lingqiang Wang, Guanjun Gao, Qinglu Zhang & Yuqing He§

National Key Laboratory of Crop Genetic Improvement and National Centre of

Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan

430070, China

§To whom correspondence should be addressed:

Y.H.yqhe@mail.hzau.edu.cn

Supplementary Data Contents

Supplemental Methods

Supplemental Figures 1-7

Supplemental Tables 1-2

Supplemental References

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Methods

Plant Materials and trait measurement

F1 hybrid Nanyangzhan×Zhenshan97 was four times backcrossed to Zhenshan97;

100 BC4F1 plants were screened for Heterozygosity of grain shape QTLs detected in

the RIL population and three lines heterozygous for the GL3.3 region were identified.

About 650 progeny from self-crossing of these lines were used to validate the effect

of GL3.3.

These were grown in the field at experimental stations of Huazhong Agricultural

University from Mid-May to late September and at Linshui in Hainan from early

December to April. A total 5,300 BC4F3 plants were screened for recombinants within

the target region defined by QTL GL3.3 and were grown in seedling beds.

Informative recombinants and NIL controls were transplanted and grown to maturity.

Planting density was 16.5 cm between plants in a row, and 26 cm between rows.

Harvested grains were air-dried and stored at room temperature for at least 3 months

before testing. Grain length was measured with a vernier caliper on 10 fully filled

seeds lined up length-wise. The grain widths and weights were measured through

HRPF as described (Yang et al., 2014). Progeny testing was conducted as

necessary.

Fine mapping of GL3.3

Markers flanking GL3.3 were used to identify recombinants among the 650 BC4F2

plants and 5,300 BC4F3 lines. In addition to SSR markers, InDel and SNP markers

were designed based on DNA polymorphisms between Nanyangzhan and Zhenshan

97. Detailed information for all markers used in fine mapping is provided in

Supplemental Table 1. Gene annotation in the target region was performed

according to the Rice Genome Annotation Project (http://rice.plantbiology.msu.edu).

Vector constructs and transformation

The 1.5 kb promoter fragment of GL3.3 from Nanyangzhan was fused with the CDS

from Zhenshan 97 and amplified into the plant binary vector

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pCAMBIA1301S(Cambia) digested by Kpn and Ⅰ Hind to generate complementary Ⅲ

transgenic lines. We used Nanyangzhan as the recipient parent and positive lines

were designated as pGL3.3NYZ: cDNAZS97and negative lines were as pGL3.3NYZ:

cDNANYZ. To prepare a CRISPR/Cas 9 knockout construct, a 20bp target region in

the third exon of GSK5 was inserted into the intermediate vector pER8-Cas9-U6 and

cloned into pCXUN-Cas9 with ZS97 was used as the recipient. For expression

pattern analysis, a 1,752bp promoter sequence upstream of the translation start

codon of GL3.3 from ZS97 was amplified and inserted into the DX2181 vector to

generate a ProGSK5: GUS construct. Constructs were first introduced into E.coli strain

Trans 5α to select the right clones through sequencing and were further introduced

into Agrobacterium tumefaciens strain EHA105 and transferred into relevant

materials by Agrobacterium-mediated transformation (Toki, 1997).

RNA extraction and expression analysis

Total RNAs were isolated with Trizol regent (Invitrogen) according to the

manufacturer`s instructions. Total RNAs were pre-treated with DNaseⅠ(Invitrogen)

and about 2 μg of total RNA was used to synthesize first-strand cDNA using oligo

(dT)18 as primers (Promega). The first-strand cDNA product was then diluted to a

density of 10ng/μL and 5μL of diluted cDNA was used as template in an 11μL PCR.

For quantitative real-time PCR, 5.5μL of SYBR Green was added to the reaction mixⅠ

and run on an ABI QuantStudio6 Flex machine according to the manufacturer`s

instructions. The melting curve was acquired at the end and transcript data were

calculated by QuantStudio Real-Time PCR software. OsActin1 was used as an

internal control and relative expression level was calculated by 2 -ΔΔCt. Each

experiment was performed with at least three replicates. Primers used in real-time

PCR are listed in Supplemental Table 1.

GUS staining

GUS staining was performed according to a described method (Jefferson et al.,

1987). Different tissues of ProGL3.3: GUS transgenic plants were incubated in a

solution containing 50mM NaH2PO4 and Na2HPO4 buffer (pH7.0), 10mM Na2EDTA,

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0.5 mMK3Fe(CN)6, 0.5mM K4Fe(CN)6, 0.1% Triton X-100 and 1mM X-Gluc at 37°C

overnight. Green tissues, including leaves and stems were cleared using chloroform.

Images were taken under a camera.

Subcellular localization

Subcellular localization of GL3.3 was detected using the full-length cDNA sequence

of GL3.3 with TAG excluded fused in-frame to YFP driven by the 35S promoter. The

vector used for subcellular localization was PM999-YFP. Ghd7-CFP plasmid was

used as a nuclear marker (Xue et al., 2008) and the empty vector of PM999-YFP was

used as a negative control. The GL3.3-YFP and Ghd7-CFP plasmids were co-

transferred into rice protoplasts as described previously (Li et al., 2014). Imaging of

fluorescent proteins in protoplast was conducted under a laser scanning confocal

microscope (Leica TCS SP2) after 12 to 18 h of expression, with excitation

wavelengths for CFP and YFP of 440nm and 514nm, respectively.

Scanning electron microscopy

For scanning electron microscopy, lemmas of pre-headed spikelets (4 days before

heading) were collected and coated with gold under vacuum conditions. Glume

morphology was examined with a scanning electron microscope (JSM-6390LV,

JEOL) at an accelerating voltage of 10kV and a spot size of 30nm. The morphology

of glumes cells was scanned at a magnification of 100X to measure length and width

and at 37X to calculate the cell number of outer glumes. Scanning electron

microscopy analysis was based on at least three biological replications of mounted

specimens. All procedures were carried out according to the manufacturer’s protocol.

Population genetic analysis

The 4,726 O.sative accessions used in this study comprised three sets; the first set

of 533 accessions was sequenced in our previous study (Zhao et al., 2015); the

second set comprised 950 accessions sequenced by Huang et al. (Huang et al.,

2012); The third set consisted of 3,243 accessions from the 3,000 Rice Genomes

Project (3KRGP) (Li et al., 2014). The grain length data for set 1, and SNP variation

data for GL3.3 all 4,726 accessions are available at RiceVarMap

(http://ricevarmap.ncpgr.cn/). The grain length data of 3KRGP were kindly provided

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by Dr Wensheng Wang (Institute of Crop Science and the National Key Facility for

Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural

Sciences, Beijing). Subpopulation identities were inferred using ADMIXTURE

(Alexander et al., 2009), and can also be queried from RiceVarMap. There were 72

SNPs and 18 InDels in the 6.3 kb sequence of LOC_Os03g62500. Nucleotide

diversity (π and ) was calculated using the DnaSP program (Watterson, 1975;

Tajima, 1983; Rozas et al., 2003). Haplotypes were extracted using the same

program after removing low-frequency variations and non-informative InDels.

Haplotypes for extended haplotype homozygosity (EHH) analysis were constructed

from 200 SNPs that spanned a 4Mb region around GL3.3 (3 Mb downstream and

2Mb upstream) in all accessions.

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Supplemental Figures

Supplemental Figure 1. Effects of GL3.3 in NILs. Phenotypes of NIL-NYZ and NIL-ZS97 for heading date (A), plant height (B), panicle length (C), grain length (D), grain width (E), 1,000-grain weight (F), grain number (G), panicle number (H), Seed setting (I) and grain yield (J). Data in A-J are shown as means±SD (n = 60). Student’s t tests were used to generate P values.

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Supplemental Figure 2. Positional cloning of GL3.3. (A) GL3.3 was mapped to a

~15kb genomic DNA region between markers 3D3-8 and 3D3-9 using 5,200 BC4F3

plants. Numbers below the bar indicate the number of recombinants between GL3.3 and

markers. (B) Genotyping of recombinants used to narrow the region of GL3.3. Grain

lengths are shown for these recombinants and NIL-NYZ (C) Allelic variations in the

candidate gene LOC_Os03g62500 between NYZ and ZS97. (D) RT–PCR of GL3.3 from

NIL-ZS97 and NIL-NYZ using young panicles (3 cm) for RNA extraction. (E) Difference in

the CDS of GL3.3 from ZS97 (black) and NYZ (red). Dash line indicates the deletion.

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Supplemental Figure 3. Functional confirmation of GL3.3 in transgenic plants. (A) Grains of ZS97 and GL3.3 knock-out line (gl3.3-1) generated by CRISPR-Cas9. (B) Editing targets of gl3.3-1. (C-E) Grain size and grain weight of ZS97 and gl3.3-1. Data are shown as means±SD. (F) Grains of the complemented transgenic plants in NYZ background. (G-I) Grain size and grain weight of the complemented transgenic plants in NYZ background. Data are shown as means±SD.

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Supplemental Figure 4. Amino acid alignments of GL3.3 in different accessions or alleles. Nipponbare and ZS97 represent wild type GL3.3; NYZ represents mutant type gl3.3jap; Dular represents mutant type gl3.3aus.

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Supplemental Figure 5. Population genetic analysis of GL3.3. (A) Gene structure and SNP variations in GL3.3. Full line arrows indicate SNPs that lead to amino acid changes and dash line arrows indicate functional SNPs. (B) Major haplotypes of GL3.3 in 4,726 rice accessions. White indicates the reference allele (Nipponbare), grey indicates a variant SNP alleles, and black highlights functional SNPs. (C) Grain length difference among accessions with C allele and A allele at the C672A position in GL3.3 from aus. (D) Genetic diversity shown by π and in two mutant alleles (gl3.3Aus and gl3.3Jap) and wild allele (GL3.3). (E) EHH across the GL3.3 genomic region for the aus subpopulation. EHH values for individuals containing the mutant (long grain) or wild type (short grain) alleles at GL3.3 are indicated by thin and thick lines, respectively.

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Supplemental Figure 6. Expression pattern of GL3.3. (A) Subcellular localization of GL3.3 in the nucleus. (B) Histochemical staining of GUS activity in various tissues. (C) Comparative expression pattern of GL3.3 in NIL-NYZ and NIL-ZS97 in various organs determined by real-time RT-PCR analysis: YP, young panicles; DAP, days after pollination. Data are shown as means±SD. (D) Expression levels of genes involved in the cell cycle in young panicles of NIL-NYZ and NIL-ZS97. Expression levels were

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determined by real-time PCR with four biological replications each with three technical replications. Data are shown as means±SD. *, P<0.01; **, P<0.001.

Supplemental Figure 7. Supplementary of SEM analysis. (A) Pre-heading spikelets of NILs. Dashed boxes indicate the part used for measurement of cell length and width. (B-C) Difference in transverse cell number (B) and cell width (C) of lemmas of spikelet hulls between NIL-NYZ and NIL-ZS97. Data are shown as means±SD.

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Supplemental Table 1. Primers used for mapping, sequencing, vector construction and qRT-PCR

Primers Forward ReversePositional cloning

3D297 CGATGCCAGTAGAGCTAGAC TTCGTCACGTCGTTCCAA3D324 AAGGTAGCACGTCAATGC TAGGAGGACCAACACAAC3D3-6 AATAGACACGGCTGGAAGGG GGTCGATATGTCCGAGTGGT3D3-8 GGTAACGGTCTTGTAAGGAC TGCTCATCGGTACCTGTGTG3D386 TCGGGAACCAGACGTTCGAT TCCACTTCCCGAAATGGCAG3D398 GTGAGACATGGAGAAGATGG TTGCCTTTCTTGGAAGCTCG3D3-9 TCGAGGATTACTGGCATCGT ATTGGCAGCCGAACGAACAG3D401 CGCTAGCTTCTCTTTCAATTC TGATGGGTACTGACTAGAGC3D4015 GGACACGAAAACCAGGGTTT AATCAAGTGTGCCGGTCCAG3D402 GCTCATCTGAAGTCTTCATG AACTAACCTGCGTAGCATGG3D639 GCAGGAGGCATTTGCTTGCT TTTGATGATCAGGCTCAGGC3D6546 ACAGTGCAATGGCAATGC CACGTTAGACAATGCACG3D656 GCACTGCACTATCACACTA AAGAGGAGGAGATCGACATCG3D659 GCCTACGCTAGAAAGACAG GGACTGATTGATCTCATG3D667 AGACGGACAGTCAAACGTTG TCACAACTTCCGTAACGGCA3D668 GGATGCTCTAGACGGTTGAA AAAGGAGAGCAACGTGATG

Candidate gene sequencing3SDG3846-3858 CTCGGACATCGTAGATGATC GTGTGCACAAAGGATCTCAG3SDG3855-3866 GCTCCCTTCAATCTTCTGAAG CGTCTAACACCTCATGTAGAC3SDG3861-3874 TCTAGCCAAAGACCTTATCC TGGGTACTCCAACAAGGGAA3SDG3870-3883 GGACATTGCTCACACACGCA GGCTGATGGAAGAGCACTTT

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3SDG3880-3891 GTACATGCATGATCACGGTT TGAGTTGTTCTATACACCTG3SDG3888-3900 GAGGATCTGTACAGCAAAAC GCCTTTGCATTGGACCAGTA3SDG3897-3909 TGCTCCCTTGCAGATGGTTG GTCACCTGTCACCAGAATCA3SDG3906-3918 TAGAGCCGTCGACTACATCT TCATCCTCTTCCGATTCCCT3SDG3915-3926 ATCCCGAACAGATCAATCTC AAGAGAAGAATGGATGCCTT3SDG3922-3935 GCAATTACAACAGGCATCGACT TCTCACAGCACACATGAGC3SDG3932-3944 CCACAGATCTGCCTGCCTAC GTGCTCTTGTTCTTCTAGCG3SDG3941-3953 GTGTGTCTAGCTTCGATAAC CCAATGATAGCAATGCAGATCC3SDG3951-3963 GATTGCATAAGACAACAGGGC GTTCACTGTTGAAACCGACC3SDG3960-3972 GACTGGTTTAGGGTCACATG CTTAGAGATGTTCTCTCCCA3SDG3969-3982 GGATAGCACAGGAAAGGAAAG GAAGTGCCACGTGTCCACGA

Vector construction

U6CCCCTTTCGCCAGGGGTACCTATGTACAGCATTACGTAGG

TACGAATTCGAGCTCGGTACCGATGGTGCTTACTGTTTAG

DU6-g1e3FGGTCGGAACTGGTTCTTTTGGTTTTAGAGCTAGAAATAGCAAGTTA CAAAAGAACCAGTTCCGACCAACCTGAGCCTCAGCGCAGC

DPU-GSk-FTTACGAACGATAGCCGGTACCATGGCCTATTCTGGACTAAGGCAT

TTTGCGGACTCTAGAGGATCCCCAACTGCACAAGCACACCAAAGCAC

DX-GSK-FTGATCTACAGCGCTGAAGCTTCCATGCATGTTGTATCGTTCTACCGAA

GGACTGACCACCCGGGGATCCCCCCCACTACCCGAGATTCCCCA

DPC-GSK-ProTACGAATTCGAGCTCGGTACCCCATGCATGTTGTATCGTTCTACCGAA ATGCCTTAGTCCAGAATAGGCCAT

DPC-GSK-CDS ATGGCCTATTCTGGACTAAGGCATACGACGGCCAGTGCCAAGCTTCCAACTGCACAAGCACACCAAAGCAC

YFP-GSK-F GCAGATCTATCGATTCTAGAATGGCCTATTCTGGAC TTGCTCACCATGGCTCTAGAGGTGCGCAGCGCCATGAACA

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TAAGG1E3S CCAAGACTGCACTTTGGTTTAC GACAACAAATCAGGGCTGACGUS CCAGGCAGTTTTAACGATCAGTTCGC GAGTGAAGATCCCTTTCTTGTTACCG

qPCRCYCD3 CCTTCCACACTGACGGTACAGTT TGCCGCTGCCAAATAGACACYCD4 GCCATGGAGTTGATACATCCAA CCAGTAGGGCTCCGTGGAATCAK1 GACGGTCAGTTAGACGCAAGA TCCAAAGGATGACCACACAK1A GACCGACAAGGGTTTCAGCAT CCAGCATGTTCAGGAAGATACAATCDKA1 GGTTTGGACCTTCTCTCTAAAATGC AGAGCCTGTCTAGCTGTGATCCTTCDKA2 CGAGATTTGAAGCCCCAGAA TCCGCGAGCTCAATGAGTTCYCT1 GCATTTGTTGAGCTCAAG TCACCACTTCGCTGACTTATTGE2F2 TGTTGGTGGCTGCCGATAT CGCCAGGTGCACCCTTTH1 GCAAGGCACCTGCAGCTT AGGCAGCCTTTGTACAGATCCTMCM2 AAGTTGGCAAAAGATCCACGG CCCCCAAACATAGCTAGTGCAAMCM3 TTCATGCGTCACTAAATGCGAG TGAATCTGGAAGCCCAATGTTCMCM4 CCCGAATGCGATTCTCTGAA ACCAGTGGCATGATCAGTTGCMCM5 AAGGAGAACTGCCTGTCCATGA AGTGGCCTTAGCTTTCACCCTCCDT2 AACCGCACCAAACACTGGAA GCAATTCACCATCTGCACTGGCYCA2.1 AGGTTGTCAAGATGGAGAGCGA CGCTTTTTGTCTTCCTGGCACYCA2.3 GTTTCGGTTGACGAGACGATGT CGCTGCAAGGAACCTAGAACTGCYCB2.1 AAGTTTGGCCAGGAGTGAGCA TCAAGAGCATCAGCGTCGAGACYCB2.2 CTCAAGGCTGCACAATCTGACA GCAATGACGGCTGGAATTTGCYCIaZm CACTCTCAAGCACCACACTGGA ACAACCCTCAGCTTGCTCTCAGCDKB AAGTTTGGCCAGGAGTGAGCA TCAAGAGCATCAGCGTCGAGA

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Actin1 TGCTATGTACTGCGCCATCCAG AATGAGTAACCACGCTCCGTCA

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Supplemental Table 2 Two-factor analysis of variance decomposing the genetic effects of GS3 and GL3.3 in RILs

Sourceof variation

dfSum Squares

Mean Square

F-value P-value

GS3 1 39.819 39.819 114.862 3.72E-21

GL3.3 1 20.167 20.167 58.173 1.22E-12

GS3:GL3.3 1 2.565 2.565 7.398 0.007153

Residuals 185 64.134 0.347

Total 188 126.685 　 　 　

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