# Whole genome sequencing dataset for a Vitis vinifera diversity panel

Gautier Sarah, Baptiste Pierre, Eva Coindre, Agnès Doligez, Thierry Lacombe, Anne Mocoeur, Valérie Laucou, Catherine Roux, Sylvain Santoni, Elodie Belmonte, et al.

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Gautier Sarah, Baptiste Pierre, Eva Coindre, Agnès Doligez, Thierry Lacombe, et al. Whole genome sequencing dataset for a Vitis vinifera diversity panel. 2025. hal-05322783

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1 Whole genome sequencing dataset for a Vitis vinifera

2 diversity panel

3

4 Authors

5 Gautier Sarah¹*, Baptiste Pierre¹, Eva Coindre¹,², Agnès Doligez¹, Thierry

6 Lacombe¹, Anne Mocoeur³, Valérie Laucou¹, Catherine Roux¹, Sylvain Santoni¹,

7 Elodie Belmonte⁴, Vincent Pailler⁴, Anthony Theron⁵, Sandrine Dedet³, Vanita

8 Haurheeram⁶, Christine Tollon-Cordet¹, Audrey Weber¹, Vincent Segura¹, Charles

9 Poncet⁴, Arnaud Bellec⁵, Patrice This¹, Dominique This¹ª, Roberto Bacilieri¹ª

10

11 Affiliations

12 1 UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, F-34398

13 Montpellier, France

14 2 LEPSE, Univ Montpellier, INRAE, Institut Agro, Montpellier, France

15 3 Domaine de Vassal, INRAe, route de Sète, 34340 Marseillan, France

16 4 INRAE, UMR 1095 GDEC, UCA INRAE, 5 chemin de Beaulieu, 63000 Clermont-

17 Ferrand, Gentyane platform

18 5 CNRGV, Centre National de Ressources Génomiques Végétales, Toulouse,

19 France

20 6 Université Paris-Saclay, INRAE, BioinfOmics, URGI, 78026, Versailles, France

21 a: These authors contributed equally

22

23 Corresponding author's email address and Twitter handle

24 gautier.sarah@inrae.fr

25

26 Keywords

27 grapevine, genomics, genetics, domestication, selection, breeding

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34

35
36 Abstract

37 Vitis vinifera is a significant agricultural species across continents and a genomic
38 model for perennial crops. A diversity panel of 279 cultivars from the Vassal-
39 Montpellier Grapevine Biological Resources Centre, which represents the
40 diversity of the three main genetics pools of this species, has served as a
41 foundation for genome-wide association studies using genotyping-by-sequencing
42 approaches. Part of this panel (74 cultivars) has recently been sequenced at the
43 whole genome level. Here, we release whole-genome sequencing of the
44 remaining 205 cultivars of the panel, using the short-read NovaSeq6000 S4
45 PE150 technology to achieve complete genomic coverage. To ensure consistency
46 with prior analyses and confirm genetic identities, we performed variant calling
47 and SNP comparison with previously published data. During this stage, we
48 identified two mislabeled samples, which were excluded from the dataset,
49 resulting in a final set of 72 samples from the public data. Additionally, nine
50 representative cultivars spanning major genetic groups underwent long-read
51 sequencing using PacBio Revio technology. All sequences have been deposited
52 at the ENA under project PRJEB95058 for the short-read data and project
53 PRJEB100755 for the long-reads. Variant data have been deposited in the
54 publicly accessible GIGWA SNP database. This expanded genomic dataset
55 establishes a comprehensive foundation for advanced genomic analyses in V.
56 vinifera, including genome-wide association mapping, structural variant
57 characterization, and genetic diversity assessment. The long-read sequences
58 provide high-quality genomic resources for structural variation analysis and
59 pangenome construction. The integration of short- and long-read sequencing
60 technologies enhances the usefulness of this resource for understanding
61 grapevine genomic architecture and supporting genetic improvement initiatives.

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75

## BACKGROUND

76

77 Cultivated grapevine (Vitis vinifera) is an economically important crop for many countries in temperate regions. In France, viticulture has been developing since Roman times, and today it carries historical and cultural values. This interest has favoured an investment in genome sequencing, making grapevine a model for perennial crop genomes[1].

82 In 2016, Nicolas et al.[2], designed from the large grape collection of the Vassal-Montpellier Grapevine Biological Resources Centre (France, https://www6.montpellier.inrae.fr/vassal) a diversity panel comprising 279 distinct cultivars evenly distributed among the three main genetic groups. This panel has since been used in Genome-Wide Association Studies using microarray and Genotyping-By-Sequencing data [3], [4], and its living clones have been disseminated internationally for various research applications. However, whole genome sequencing data for these cultivars are still incomplete, only 74 having being sequenced so far. In this paper, we completed the genome sequence dataset for the panel from [5], [6], [7], [8], with newly obtained sequencing data for 205 cultivars, to achieve coverage of almost each cultivar within the panel.

93

94

## DATA DESCRIPTION

95

96 We present whole-genome sequencing data for a diversity panel comprising 279 cultivar accessions, as previously described by Nicolas et al. [2]. 205 cultivars were newly sequenced using an Illumina 6000 S4 PE150 sequencer. Raw sequencing data can be accessed under ENA project PRJEB95058. Theoretical short-read coverage ranges from 13.7X for cultivar Solana (code var 3308) to 60X for cultivar Crimposie (code var 2243). Additionally, 74 cultivars were already publicly available: 66 from [5], 6 from [6], 1 from [7], and 1 from [8]. We completed the sample metadata in `tableSequence_download_information` that can be accessed from the INRAE dataverse at https://doi.org/10.57745/VS1I4].

105 To validate sample identity, we performed variant calling and SNP comparison with publicly available relevant samples. It occurred that 2 samples were mislabelled, Khalili Belyi (CRR495374) and Loureiro (CRR496536). We therefore dismissed them from the dataset. After quality filtering, genotyping results were compiled and deposited in GIGWA database [9], publicly available at https://gigwa.southgreen.fr/gigwa/.

111 We also present long read data for nine cultivars, selected as three representatives from each of the three genetic pools defined by Nicolas et al. [2]. These data were produced using a Pacbio HiFi Revio. They are accessible in ENA project PRJEB100755.

115

116
117 EXPERIMENTAL DESIGN, MATERIALS AND METHODS
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120 Plant Material

121 Plants are maintained in the Grape Collection of the Vassal-Montpellier
122 Grapevine Biological Resource Centre (France,
123 https://www6.montpellier.inrae.fr/vassal), with single line unit plots of five clones
124 for each accession. Fresh expanding leaves were collected in May and June in
125 years 2022, 2023 and 2024. They were brought in a cooler to the UMR AGAP
126 genotyping platform, grinded in liquid nitrogen and stored at -80°C. The full list
127 of collected accessions is given in the file Short_read_stats available here:
128 https://doi.org/10.57745/VS1I4J. Further information on accessions can be found
129 either on the INRAE Vassal database
130 (https://bioweb.supagro.inra.fr/collections_vigne/Home.php) or on the Vitis
131 International Variety Catalogue database (https://www.vivc.de/) using as entry
132 point either variety name or ID number.

133 DNA extraction for short-read sequencing

134 DNA was isolated from frozen young leaves of 205 cultivars using a custom
135 protocol (INRAE ref. PEX-EXT-004g). Briefly, 500 mg of young leaf material were
136 grinded in liquid nitrogen with mortar and pestle. After 30 min of lysis in an
137 EDTA-CTAB buffer, one centrifugation step and several washing steps, DNA was
138 eluted, then desalted and concentrated by isopropyl alcohol precipitation.
139 Washing in 70% ethanol was performed before resuspending the DNA in EB
140 buffer (Qiagen). A final purification step was carried out using a Kingfisher™ Flex
141 robot.

142 Analyses of DNA quantity and quality were performed using NanoDrop and Qubit
143 (Thermo Fisher Scientific, MA, USA). A preliminary run on an Illumina MiSeq
144 machine was carried out to better estimate effective DNA concentration and
145 refine dosage before sample multiplexing.

146 Library preparation for short-read paired-end Illumina sequencing

147 We then built three libraries, each with 70 multiplexed samples, using a custom
148 PCR-free blunt/TA ligase protocol (INRAE ref. PEX-NGS-030). This protocol uses
149 the Illumina TruSeq DNA UD Indexes (Ref. 20023784), an NEBNext Ultra END
150 Repair /dA-Tailling Module (Ref. E7546L) and NEB Blunt /TA Ligase Master Mix
151 (Ref. M0367S). These steps were followed by an AMPure purification to eliminate
152 primers and short fragments (< 250bp).

153 High Molecular Weight DNA extraction with Qiagen Genomic-Tip 500/G

154 High-molecular-weight (HMW) DNA was isolated from frozen young leaves of 9
155 cultivars using QIAGEN Genomic-tips 500/G kit (Qiagen, MD, USA), following the
156 tissue protocol extraction. Briefly, 0.5g of young leaf material was ground in
157 liquid nitrogen with mortar and pestle. After 3h lysis and one centrifugation step,
158 DNA was fixed onto the column. After several washing steps, DNA was eluted
159 from the column, then desalted and concentrated by Isopropyl alcohol
160 precipitation. A final wash in 70% ethanol was performed before resuspending
161 DNA in EB buffer (Qiagen).
162 Analyses of DNA quantity and quality were performed using NanoDrop and Qubit
163 (Thermo Fisher Scientific, MA, USA).

164 **Pacbio Hifi library preparation**

165 HiFi libraries were prepared using the SMRTbell® Template Prep Kit 3.0 (Pacific
166 Biosciences, Menlo Park, CA, USA), following the manufacturer's
167 recommendations (SMRTbell prep kit 3.0 PacBio® 102-182-700). HMWDNA
168 samples were first purified using 1X Agencourt AMPure XP beads (Beckman
169 Coulter, CA, USA), then sheared to an average size of 20 kb with the Megaruptor
170 3 system (Diagenode, Liège, Belgium). Following end-repair, A-tailing, and
171 ligation of barcoded SMRTbell adapters, libraries were size-selected using the
172 BluePippin system (Sage Science, MA, USA) to retain fragments in the 10-50 kb
173 range.

174 The size and concentration of the nine individual libraries were assessed using
175 the Agilent FP-1002 Genomic DNA 165 kb kit on the Femto Pulse system (Agilent,
176 CA, USA), along with the Qubit dsDNA HS Assay Kit (Thermo Fisher Scientific).
177 Equimolar pooling of the libraries was performed to generate three final libraries.

178 Sequencing

179 The 3 short read multiplexed libraries including 210 samples (the 205 samples
180 of interest and 5 controls) were sequenced at the MGX Montpellier Genomix
181 platform on a NovaSeq 6000 sequencer. The 3 libraries for long-read sequencing
182 were sequenced on a PacBio Revio system at INRAE Gentyane platform.

183 Variant Calling

184 From the newly generated and publicly available sequence data grouped
185 together, we used a workflow based on GATK to obtain a variant matrix [10]. This
186 workflow uses the PN40024 v5 genome as reference [11]. The full workflow can
187 be accessed here: https://gitlab.cirad.fr/agap/cluster/snakemake/GATK.

188 Shortly, the workflow cleans reads using fastp [12], aligns sequences using BWA-
189 MEM2 [13], and removes duplicates using sambamba [14]. Genomic variants are
190 then called following GATK Best Practices (HaplotypeCaller, GenomicsDBImport,
191 GenotypeGVCFs) [10].

192 The variant matrix obtained was then filtered using the VCFtools software [15].
193 First, we kept only data with GQ > 30 and DP > 10. We then removed variants
194 with > 20% missing data. After all filters, we obtained a matrix containing
195 15,949,350 variants

196 Sample Identity Check

197 To check genotype identity, we compared our data generated by whole genome
198 sequencing (WGS) with public data from the GBS and chip SNP sets described by
199 Flutre et al. [3] and Laucou et al. [16] respectively. The VCF files were read using
200 the gaston package (https://cran.r-project.org/web/packages/gaston/index.html)
201 and converted into genotypic matrices. Identifier correspondence tables were
202 used to match sample names between different datasets, ensuring consistency
203 between studies and allowing each accession to be unambiguously associated
204 with its unique code. In order to work with a single SNP nomenclature, SNP
205 positions of the two previously published works were projected from their 12X
206 assembly positions [17] to the corresponding positions on the T2T version [11].
207 The GBS/Chip and WGS data were then merged into a single matrix, from which
208 we calculated genotypic similarities based on the proportion of identical alleles
209 (IBS). These similarities were used to perform hierarchical clustering and
210 principal component analyses, allowing us to check consistency between
211 datasets and to assign each sequenced accession to its corresponding genotype
212 in the reference collection.

213 Based on previous information and the use of identical controls, IBS values >
214 0.95 are generally consistent with identity between two sequences (allowing for
215 sequencing errors, genotype calling errors, and clonal mutations between
216 several accessions of the same variety). In practice, we observed a clear
217 distinction between values of IBS between 0.95 and 1 - compatible with clonal
218 identity - and IBS < 0.85 which matches the threshold corresponding to first
219 degree parentship. We used these thresholds to classify individuals as true-to-
220 type or not. The identity of the few remaining individuals, showing intermediate
221 IBS values between 0.85 and 0.95, was verified using microsatellite
222 fingerprinting, which allowed us to refute the matches for Khalili Belyi
223 (CRR495374) and Loureiro (CRR496536), and to confirm those of the other
224 individuals.. Khalili Belyi (CRR495374) and Loureiro (CRR496536) were therefore
225 dismissed from the dataset, reducing its size from 279 to 277 individuals.

226

227 Variants accessibility through GIGWA

228 The filtered variant matrix was deposited on the GIGWA database [9] and can be
229 accessed on the following address: https://gigwa.southgreen.fr/gigwa/

230

231 LIMITATIONS

232

233 Due to field identification error, we had to remove two individuals ( Khalili Belyi
234 (CRR495374) and Loureiro (CRR496536)) from the dataset and have data for 277
235 out of the original 279.

236 ETHICS STATEMENT

237

238 The authors have read and follow the ethical requirements for publication in Data
239 in Brief and confirm that the current work does not involve human subjects,
240 animal experiments, or any data collected from social media platforms.

241

242

243

244

245
246 CREDIT AUTHOR STATEMENT

247

248 **Gautier Sarah:** Software, Formal analysis, Data Curation, Writing - Original

249 Draft. **Baptiste Pierre:** Formal analysis, Validation, Writing - Review & Editing.

250 **Eva Coindre:** Validation, Writing - Review & Editing. **Agnès Doligez:**

251 Resources, Writing - Review & Editing. **Thierry Lacombe:** Resources, Data

252 Curation, Writing - Review & Editing. **Anne Mocoeur:** Resources, Data Curation.

253 **Valérie Laucou:** Investigation, Writing - Review & Editing. **Catherine Roux:**

254 Investigation. **Sylvain Santoni:** Investigation, Supervision. **Elodie Belmonte:**

255 Investigation. **Vincent Pailler:** Investigation. **Anthony Theron:** Investigation.

256 **Sandrine Dedet:** Resources. **Vanita Haurheeram:** Data Curation. **Christine**

257 **Tollon-Cordet:** Investigation. **Audrey Weber:** Investigation. **Vincent Segura:**

258 Software, Validation, Writing - Review & Editing. **Charles Poncet:** Investigation,

259 Resources. **Arnaud Bellec:** Investigation, Resources. **Patrice This:** Supervision,

260 Funding acquisition. **Dominique This:** Investigation, Supervision, Data Curation,

261 Writing - Review & Editing, Project administration, Funding acquisition. **Roberto**

262 **Bacilieri:** Investigation, Supervision, Data Curation, Writing - Review & Editing,

263 Project administration, Funding acquisition.

264

265

266 ACKNOWLEDGEMENTS

267

268 This work was funded by Vinid'Occ, a research program on cultivated grapevine,

269 supported by the Occitanie region (France) and managed by the University of

270 Montpellier (PlastiVigne flagship program), by the Agence Nationale de

271 recherche, programme France2030's project AgroDiv (ANR-22-PEAE-0005) and

272 project BReiF (ANR-22-PEAE-0014)

273 The authors wish to thank Jérôme Salse and Anne-Françoise Adam-Blondon for

274 their contribution to long-read data generation.

275

276 DECLARATION OF COMPETING INTERESTS

277

278 The authors declare that they have no known competing financial interests or

279 personal relationships that could have appeared to influence the work reported

280 in this paper.

281

282

283

284
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