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. 2021 Jan 29;8:38. doi: 10.1038/s41597-021-00828-8

Nelumbo genome database, an integrative resource for gene expression and variants of Nelumbo nucifera

Hui Li 1,2,3,#, Xingyu Yang 4,#, Yue Zhang 1,2,3, Zhiyan Gao 1,2,3, Yuting Liang 4, Jinming Chen 1,2,✉, Tao Shi 1,2,✉
PMCID: PMC7846841  PMID: 33514746

Abstract

Sacred lotus (Nelumbo nucifera, or lotus) is one of the most widely grown aquatic plant species with important uses, such as in water gardening and in vegetable and herbal medicine. A public genomic database of lotus would facilitate studies of lotus and other aquatic plant species. Here, we constructed an integrative database: the Nelumbo Genome Database (NGD, http://nelumbo.biocloud.net). This database is a collection of the most updated lotus genome assembly and contains information on both gene expression in different tissues and coexpression networks. In the NGD, we also integrated genetic variants and key traits from our 62 newly sequenced lotus cultivars and 26 previously reported cultivars, which are valuable for lotus germplasm studies. As applications including BLAST, BLAT, Primer, Annotation Search, Variant and Trait Search are deployed, users can perform sequence analyses and gene searches via the NGD. Overall, the valuable genomic resources provided in the NGD will facilitate future studies on population genetics and molecular breeding of lotus.

Subject terms: Plant molecular biology, Agricultural genetics

Measurement(s) reference genome data • whole genome sequencing • transcriptome
Technology Type(s) Hi-C • PacBio Sequel System • Illumina sequencing • RNA sequencing • DNA sequencing
Sample Characteristic - Organism Nelumbo nucifera
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Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13487271

Background & Summary

Sacred lotus (Nelumbo nucifera, or lotus) is an early-diverging eudicot with important value in terms of understanding the origin and evolution of eudicots1,2. Lotus has a widespread native distribution, ranging from Asia to northern Australia, and it is one of the most economically important aquatic plant species, with widespread uses, such as in water gardening and in vegetable and herbal medicine3–5. In horticulture, lotus is classified into three cultivated types according to their utilization: seed lotus, flower lotus and rhizome lotus. The genome of lotus (2n = 16, assembly size = 821.2 Mb) has been sequenced and assembled, providing an unprecedented opportunity for genetic studies and molecular breeding of lotus6–8.

Since the first draft genome assembly of the lotus variety China Antique was released9, many genomic studies have been carried out on lotus, such as whole-genome resequencing7,10,11, transcriptomic12–14, miRNA-based15–17 and gene family studies18,19. The recent chromosome-level assembly of the China Antique genome facilitates genome-wide studies of functional genes and the evolution of lotus, but a web-based public database of lotus is still unavailable8. Due to public demand for an integrative genomic resource of lotus, we report our Nelumbo Genome Database (NGD, nelumbo.biocloud.net), which comprehensively houses, processes and integrates the newest assembly of lotus variety China Antique, the expression profiles of various tissues, genetic variants and phenotypes of 88 key lotus cultivars (Fig. 1).

Fig. 1.

Fig. 1

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A schematic of the data collection and utilities for the Nelumbo Genome Database (NGD).

Major datasets

The NGD is a collection of the new lotus assembly and annotations8, of which 34,481 genes harbor complete ORFs (> = 30 aa). A total of 28,676 genes were defined as high-confidence genes, with 14,991, 20,878, 15,276, 5,924, 29,095, 20,325, and 28,310 annotated genes in the KOG, PFAM, GO, KEGG, Nr, SwissProt and TrEMBL databases, respectively (Table 1). The NGD also houses the sequences of 150,589 unique transcript isoforms based on RNA-seq and PacBio SMRT methods from our previous studies14,17. It also contains the sequences of 1,517 lotus transcription factors (TFs), which are classified into 56 TF (sub)families. Furthermore, sequence data of lotus gene families, transposable elements (TEs) and other repeats are also present in the NGD, and information concerning gene expression levels and highly coexpressed genes from data from a coexpression (WGCNA) network based on 69 RNA-seq samples from 11 lotus tissues (seed coat, cotyledon, receptacle, carpel, stamen, petal, rhizome, leaf, root, petiole and apical bud tissues) is present in the NGD. Furthermore, information concerning a total of 26,939,834 high-quality SNPs (single nucleotide polymorphisms), 4,177,974 InDels and key horticultural traits from 88 lotus cultivars is present in the NGD.

Table 1.

Summary of functional annotations of lotus genes in different databases.

Database Number of annotated genes
GO 15276
KEGG 5924
KOG 14991
Pfam 20878
Swiss Prot 20325
TrEMBL 28310
Nr 29095
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Uses

Through data collection and downstream processing, our platform provides the most complete lotus genome assembly for browsing via GBrowse or JBrowse20,21. Genes, DNA sequences, amino acids, SNPs and InDels can be viewed via GBrowse. The gene information page includes gene-splicing structures, sequences, and functional annotations such as those from the PFAM, KEGG, GO, KOG, SwissProt, TrEMBL and Nr databases. RNA-seq-based expression profiles across different tissues are also retrievable and can be visualized via a heatmap. Searching genes by keywords is also possible in the NGD. Additionally, coexpressed genes of a query gene in the WGCNA-derived network can be retrieved by setting a weight threshold; these coexpressed genes are likely involved in the same biological process as the query gene. Coding sequences and genomic sequences can be searched based on sequence similarity via BLAST or BLAT. Primers for the PCR experiments can also be designed directly in the NGD.

Methods

Data processing

Gene predictions on our chromosome-level genome assembly were performed using transcriptomes, gene homology and ab initio identification. A list of publicly available RNA-seq datasets, which mainly contain samples of the China Antique variety, were downloaded from the NCBI SRA database (Online-only Table 1). First, the corrected consensus PacBio full-length transcripts were mapped to the lotus reference genome using GMAP14. RNA-seq reads (Illumina) were then mapped to the genome using the HISAT2-StringTie pipeline22. All the transcripts were further merged using TACO23. Coding DNA sequences (CDSs) of transcripts were predicted using Transdecoder (https://github.com/TransDecoder). Second, homology-based gene prediction was performed using GeMoMa, which used genome sequences and gene coordinates from Arabidopsis thaliana24, Carica papaya25, Vitis vinifera26, Macadamia ternifolia (Proteales)27 and Brachypodium distachyon28 as inputs. Third, ab initio prediction was performed using Braker2, which used transcript coordinates of RNA-seq as a guide29. Finally, all predictions were merged, and for each gene with more than one gene model (transcripts), the longest one was chosen as the representative gene model. Genes with an ORF less than 30 aa were discarded. Further, high-confidence gene sets were defined as those whose genes that either were homologous to those in other plant species in Plant Plaza 4.0 (https://bioinformatics.psb.ugent.be/plaza/versions/plaza_v4_dicots/) or were supported by RNA-seq (FPKM > 0.1). To quantify the expression of each gene in different lotus tissue samples, FPKM values across different RNA-seq samples were obtained via StringTie22. A coexpression network of different genes based on the expression profile was constructed using the WGCNA (v1.0) package in R30. Specifically, genes with an average FPKM > 0.1 and a coefficient of variation (CV) of gene expression (FPKM) > 2 were retained for the WGCNA. Genes were clustered hierarchically based on Topological Overlap Matrix31 and were assigned to nine modules (minimum module size of 600 and minimum module similarity of 0.5). The weight values between genes were used to represent the connectivity between genes.

Online-only Table 1.

Information and source of genomic data used in Nelumbo Genome Database.

Datatype Platform Cultivar Name Utility Tissue/developmental stage Accession number (NCBI SRA)
DNA PacBio SMRT China Antique Genome assembly Young leaf SRR7549129
DNA PacBio SMRT China Antique Genome assembly Young leaf SRR7549130
DNA Illumina & Hi-C China Antique Genome assembly Young leaf SRR7615553
DNA Illumina & Hi-C China Antique Genome assembly Young leaf SRR7631523
RNA PacBio SMRT China Antique Gene & isoform prediction mixed tissue samples SRR8182148
RNA Illumina China Antique Gene expression Seed-coat-DAP6 SRR7880135
RNA Illumina China Antique Gene expression Seed-coat-DAP6 SRR7880135
RNA Illumina China Antique Gene expression Seed-coat-DAP6 SRR7880135
RNA Illumina China Antique Gene expression Seed-coat-DAP12 SRR7880134
RNA Illumina China Antique Gene expression Seed-coat-DAP12 SRR7880134
RNA Illumina China Antique Gene expression Seed-coat-DAP12 SRR7880134
RNA Illumina China Antique Gene expression Seed-coat-DAP18 SRR7880133
RNA Illumina China Antique Gene expression Seed-coat-DAP18 SRR7880133
RNA Illumina China Antique Gene expression Seed-coat-DAP18 SRR7880133
RNA Illumina China Antique Gene expression Petal SRR8169126
RNA Illumina China Antique Gene expression Petal SRR8169126
RNA Illumina China Antique Gene expression Immature-stamen SRR8169123
RNA Illumina China Antique Gene expression Immature-stamen SRR8169123
RNA Illumina China Antique Gene expression unpollinated-carpel SRR8169124
RNA Illumina China Antique Gene expression unpollinated-carpel SRR8169124
RNA Illumina China Antique Gene expression Immature-receptacle SRR8169125
RNA Illumina China Antique Gene expression Immature-receptacle SRR8169125
RNA Illumina China Antique Gene expression Mature-stamen SRR8169127
RNA Illumina China Antique Gene expression Mature-stamen SRR8169127
RNA Illumina China Antique Gene expression Pollinated-carpel SRR8169128
RNA Illumina China Antique Gene expression Pollinated-carpel SRR8169128
RNA Illumina China Antique Gene expression Mature-receptacle SRR8169129
RNA Illumina China Antique Gene expression Mature-receptacle SRR8169129
RNA Illumina China Antique Gene expression Cotyledon-DAP9 SRR6432938
RNA Illumina China Antique Gene expression Cotyledon-DAP9 SRR6432938
RNA Illumina China Antique Gene expression Cotyledon-DAP9 SRR6432938
RNA Illumina China Antique Gene expression Cotyledon-DAP12 SRR6432941
RNA Illumina China Antique Gene expression Cotyledon-DAP12 SRR6432941
RNA Illumina China Antique Gene expression Cotyledon-DAP12 SRR6432941
RNA Illumina China Antique Gene expression Cotyledon-DAP15 SRR6432942
RNA Illumina China Antique Gene expression Cotyledon-DAP15 SRR6432942
RNA Illumina China Antique Gene expression Cotyledon-DAP15 SRR6432942
RNA Illumina China Antique Gene expression lotus root SRR826691
RNA Illumina China Antique Gene expression Leaf SRR830399
RNA Illumina China Antique Gene expression Leaf SRR831069
RNA Illumina China Antique Gene expression Leaf SRR831070
RNA Illumina China Antique Gene expression Leaf SRR831071
RNA Illumina China Antique Gene expression Leaf SRR831072
RNA Illumina China Antique Gene expression rhizome Internode SRR831082
RNA Illumina China Antique Gene expression rhizome Internode SRR831083
RNA Illumina China Antique Gene expression rhizome Internode SRR831084
RNA Illumina China Antique Gene expression rhizome Internode SRR831086
RNA Illumina China Antique Gene expression rhizome Internode SRR831087
RNA Illumina China Antique Gene expression Petiole SRR831088
RNA Illumina China Antique Gene expression Petiole SRR831089
RNA Illumina China Antique Gene expression Petiole SRR831090
RNA Illumina China Antique Gene expression Petiole SRR831167
RNA Illumina China Antique Gene expression Petiole SRR831168
RNA Illumina China Antique Gene expression Root SRR831169
RNA Illumina China Antique Gene expression Root SRR831170
RNA Illumina China Antique Gene expression Root SRR831171
RNA Illumina China Antique Gene expression Root SRR831172
RNA Illumina China Antique Gene expression Root SRR831173
RNA Illumina China Antique Gene expression rhizome apical meristem SRR831190
RNA Illumina China Antique Gene expression rhizome elongation Zone SRR831693
RNA Illumina cultivated rhizome lotus (CRL) plants Gene expression Apical buds SRR879365
RNA Illumina wild flower lotus (WFL) plants Gene expression Apical buds SRR879367
RNA Illumina Zhouou Gene expression rhizome (stolon/internode) SRR2052526
RNA Illumina Zhouou Gene expression rhizome (stolon/internode) SRR2052539
RNA Illumina Zhouou Gene expression rhizome (later swelling stage/internode) SRR2052541
RNA Illumina Fenhonglingxiao Gene expression rhizome (stolon/internode) SRR2052538
RNA Illumina Fenhonglingxiao Gene expression rhizome (stolon/internode) SRR2052542
RNA Illumina Zhouou Gene expression rhizome (later swelling stage/internode) SRR2052551
RNA Illumina Zhouou Gene expression rhizome (middle swelling stage/internode) SRR2052560
RNA Illumina Fenhonglingxiao Gene expression rhizome (middle swelling stage/internode) SRR2052568
RNA Illumina Fenhonglingxiao Gene expression rhizome (middle swelling stage/internode) SRR2052569
RNA Illumina Fenhonglingxiao Gene expression rhizome (later swelling stage/internode) SRR2052570
RNA Illumina Zhouou Gene expression rhizome (later swelling stage/internode) SRR2052571
RNA Illumina Fenhonglingxiao Gene expression rhizome (later swelling stage/internode) SRR2052573
DNA Illumina shentong Whole-genome resequencing young leaf SRR8325858
DNA Illumina fozuolian Whole-genome resequencing young leaf SRR8325857
DNA Illumina yuloutai Whole-genome resequencing young leaf SRR8325860
DNA Illumina jiaoyangzuiwu Whole-genome resequencing young leaf SRR8325859
DNA Illumina xiaolianzuo Whole-genome resequencing young leaf SRR8325862
DNA Illumina huoyan Whole-genome resequencing young leaf SRR8325868
DNA Illumina yongshi Whole-genome resequencing young leaf SRR8325864
DNA Illumina chongbanbayilian Whole-genome resequencing young leaf SRR8325863
DNA Illumina ziyulian Whole-genome resequencing young leaf SRR8325866
DNA Illumina hongwanlian Whole-genome resequencing young leaf SRR8325865
DNA Illumina baixuegongzhu Whole-genome resequencing young leaf SRR8325880
DNA Illumina baiwanwan Whole-genome resequencing young leaf SRR8325879
DNA Illumina yudie Whole-genome resequencing young leaf SRR8325878
DNA Illumina fenwanlian Whole-genome resequencing young leaf SRR8325877
DNA Illumina taizhenchuyu Whole-genome resequencing young leaf SRR8325884
DNA Illumina manaohong Whole-genome resequencing young leaf SRR8325883
DNA Illumina luoxiayingxue Whole-genome resequencing young leaf SRR8325882
DNA Illumina mudanxianzi Whole-genome resequencing young leaf SRR8325881
DNA Illumina pinghuqiuyue Whole-genome resequencing young leaf SRR8325872
DNA Illumina tianshanbitai Whole-genome resequencing young leaf SRR8325871
DNA Illumina lihuabai Whole-genome resequencing young leaf SRR8325836
DNA Illumina hongjuan Whole-genome resequencing young leaf SRR8325837
DNA Illumina xinlingmei Whole-genome resequencing young leaf SRR8325834
DNA Illumina shuangjie Whole-genome resequencing young leaf SRR8325835
DNA Illumina fenghuazhengmao Whole-genome resequencing young leaf SRR8325840
DNA Illumina juhong Whole-genome resequencing young leaf SRR8325841
DNA Illumina cenglinjinran Whole-genome resequencing young leaf SRR8325838
DNA Illumina fenmudan Whole-genome resequencing young leaf SRR8325839
DNA Illumina chanjuan Whole-genome resequencing young leaf SRR8325843
DNA Illumina cuitai Whole-genome resequencing young leaf SRR8325844
DNA Illumina zixiabei Whole-genome resequencing young leaf SRR8325870
DNA Illumina bixuedanxin Whole-genome resequencing young leaf SRR8325869
DNA Illumina xiaofengliangyue Whole-genome resequencing young leaf SRR8325853
DNA Illumina xiaotaihong Whole-genome resequencing young leaf SRR8325847
DNA Illumina nanjinghong Whole-genome resequencing young leaf SRR8325874
DNA Illumina shuimeiren Whole-genome resequencing young leaf SRR8325873
DNA Illumina yubanbai Whole-genome resequencing young leaf SRR8325876
DNA Illumina yuhua Whole-genome resequencing young leaf SRR8325875
DNA Illumina liuhuo Whole-genome resequencing young leaf SRR8325867
DNA Illumina xiaoxia Whole-genome resequencing young leaf SRR8325861
DNA Illumina baiyun Whole-genome resequencing young leaf SRR8325895
DNA Illumina baiqianye Whole-genome resequencing young leaf SRR8325848
DNA Illumina jinzhuluoyupan Whole-genome resequencing young leaf SRR8325849
DNA Illumina hanhong Whole-genome resequencing young leaf SRR8325850
DNA Illumina fengximudan Whole-genome resequencing young leaf SRR8325851
DNA Illumina suzhibingzi Whole-genome resequencing young leaf SRR8325852
DNA Illumina chongbanyizhangqing Whole-genome resequencing young leaf SRR8325842
DNA Illumina zhongshanhongtai Whole-genome resequencing young leaf SRR8325854
DNA Illumina shennvzi Whole-genome resequencing young leaf SRR8325855
DNA Illumina yanzhilu Whole-genome resequencing young leaf SRR8325856
DNA Illumina xinjie Whole-genome resequencing young leaf SRR8325892
DNA Illumina chaitoufeng Whole-genome resequencing young leaf SRR8325891
DNA Illumina caiyunfeidu Whole-genome resequencing young leaf SRR8325890
DNA Illumina lianxia Whole-genome resequencing young leaf SRR8325889
DNA Illumina pizhenhong Whole-genome resequencing young leaf SRR8325888
DNA Illumina haoyue Whole-genome resequencing young leaf SRR8325887
DNA Illumina jiaoniang Whole-genome resequencing young leaf SRR8325886
DNA Illumina danxiuqiu Whole-genome resequencing young leaf SRR8325885
DNA Illumina hongdenggaozhao Whole-genome resequencing young leaf SRR8325894
DNA Illumina fenxia Whole-genome resequencing young leaf SRR8325893
DNA Illumina zhaoyun Whole-genome resequencing young leaf SRR8325845
DNA Illumina baimeilian Whole-genome resequencing young leaf SRR8325846
DNA Illumina hongtailian Whole-genome resequencing young leaf SRR7159815
DNA Illumina shuguangxiu Whole-genome resequencing young leaf SRR7159817
DNA Illumina donghuxinhong Whole-genome resequencing young leaf SRR7159818
DNA Illumina xiangbihe Whole-genome resequencing young leaf SRR7159820
DNA Illumina fengjuanhongqi Whole-genome resequencing young leaf SRR7159821
DNA Illumina xingkongmudan Whole-genome resequencing young leaf SRR7159822
DNA Illumina honghehuan Whole-genome resequencing young leaf SRR7159825
DNA Illumina jinlinghuodu Whole-genome resequencing young leaf SRR7159826
DNA Illumina xiaoqu Whole-genome resequencing young leaf SRR7159827
DNA Illumina xiaojingling Whole-genome resequencing young leaf SRR7159828
DNA Illumina zuidongfeng Whole-genome resequencing young leaf SRR7159829
DNA Illumina hongyun Whole-genome resequencing young leaf SRR7159830
DNA Illumina jinlingzhixing Whole-genome resequencing young leaf SRR7159831
DNA Illumina danyue Whole-genome resequencing young leaf SRR7159832
DNA Illumina qinhuaibaiyu Whole-genome resequencing young leaf SRR7159833
DNA Illumina baige Whole-genome resequencing young leaf SRR4308656
DNA Illumina baiyangdianhonglian Whole-genome resequencing young leaf SRR4308659
DNA Illumina donghonghua Whole-genome resequencing young leaf SRR4308651
DNA Illumina fenhonglingxiao Whole-genome resequencing young leaf SRR4308650
DNA Illumina heilongjianghonglian Whole-genome resequencing young leaf SRR4308657
DNA Illumina jianxuan17 Whole-genome resequencing young leaf SRR4308643
DNA Illumina puzheheibailian Whole-genome resequencing young leaf SRR4308658
DNA Illumina qianbanlian Whole-genome resequencing young leaf SRR4308655
DNA Illumina weishanhonglian Whole-genome resequencing young leaf SRR4308645
DNA Illumina xihuhonglian Whole-genome resequencing young leaf SRR4308660
DNA Illumina zhigaowushang Whole-genome resequencing young leaf SRR4308649
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Gene functions were annotated using the Gene Ontology (GO), KEGG, KOG, Pfam, SwissProt, TrEMBL, and Nr databases via KOBAS 3.0, BlastKOALA, PfamScan and BLAST32,33. As protein domains are conserved units shared by related genes, we clustered genes into domain families (gene families) according to the HMM Pfam domain annotations34. In addition, all transcription factors (TFs) were predicted and clustered into TF families via PlantTFDB 4.035.

There were 88 recorded lotus cultivars chosen in this study as representing various floral traits (color, shape, flowering time, etc.). Among these cultivars, 62 were sequenced in our current study, while the sequences of 26 with detailed phenotypic records were downloaded from the NCBI database (Online-only Table 2). Genomic DNA was first extracted from young leaves by the CTAB method36, and then DNA libraries were constructed by cutting the DNA into 250~280 bp fragments using a NEBNext® Ultra DNA Library Prep Kit for Illumina (NEB, USA) following the manufacturer’s recommendations. Paired-end reads (PE150) were sequenced on an Illumina NovaSeq. 6000 (San Diego, CA, USA), which generated approximately 16 × -depth data for each cultivar sample. Clean reads were obtained by removing the adapters and low-quality reads, including those comprising > 10% N, with < 20% low-quality bases, with low-quality/ambiguous fragments at the read ends within a 5 bp window and with a quality < 20 via FASTX-Toolkit (http://hannonlab.cshl.edu/fastx_toolkit/). The clean reads were mapped to the reference genome by BWA-men37. Variants were subsequently called by pipeline via GATK 4.0 (Genome Analysis Toolkit) with further SNP hard-filtering parameters (“QD < 2.0 || FS > 60.0 || MQ < 40.0 || MQRankSum < -12.5 || ReadPosRankSum < -8.0” and InDel hard-filtering parameters of “QD < 2.0 || FS > 200.0 || ReadPosRankSum < -20.0”)38. The phenotypes and some images of these cultivars were collected from reference books39,40; the phenotypes were further validated across two years of field investigations. Images of floral traits for these cultivars displayed in the NGD were taken mostly during flowering at the Wuhan Institute of Landscape Architecture (Wuhan, China).

Online-only Table 2.

Mapping rate and depth on reference genome for 88 lotus cultivars.

Sample ID Sample Name Mapping rate Depth NCBI SRR
63 shentong 99.01% 11.9566 SRR8325858
74 fozuolian 98.97% 12.4726 SRR8325857
75 yuloutai 98.89% 14.0595 SRR8325860
86 jiaoyangzuiwu 98.12% 13.0646 SRR8325859
102 xiaolianzuo 99.00% 13.4425 SRR8325862
107 huoyan 98.81% 12.3096 SRR8325868
116 yongshi 98.96% 11.8835 SRR8325864
146 chongbanbayilian 99.13% 11.7565 SRR8325863
160 ziyulian 99.07% 13.6243 SRR8325866
163 hongwanlian 98.68% 13.5703 SRR8325865
169 baixuegongzhu 99.07% 12.748 SRR8325880
218 baiwanwan 99.24% 16.2777 SRR8325879
221 yudie 98.71% 16.6949 SRR8325878
235 fenwanlian 99.32% 16.2768 SRR8325877
239 taizhenchuyu 99.28% 16.1965 SRR8325884
274 manaohong 99.38% 16.5347 SRR8325883
296 luoxiayingxue 99.40% 16.9159 SRR8325882
305 mudanxianzi 99.23% 16.5897 SRR8325881
317 pinghuqiuyue 99.40% 18.1952 SRR8325872
319 tianshanbitai 99.35% 17.3546 SRR8325871
322 lihuabai 99.30% 18.5732 SRR8325836
334 hongjuan 99.09% 17.2609 SRR8325837
338 xinlingmei 99.32% 16.7434 SRR8325834
365 shuangjie 99.06% 11.9673 SRR8325835
368 fenghuazhengmao 99.40% 18.83 SRR8325840
380 juhong 99.37% 17.0724 SRR8325841
381 cenglinjinran 99.29% 16.1654 SRR8325838
388 fenmudan 99.27% 15.0731 SRR8325839
419 chanjuan 99.34% 17.5767 SRR8325843
421 cuitai 99.36% 18.721 SRR8325844
440 zixiabei 99.29% 15.9078 SRR8325870
450 bixuedanxin 99.35% 17.1246 SRR8325869
451 xiaofengliangyue 99.41% 17.1499 SRR8325853
452 xiaotaihong 99.38% 17.3033 SRR8325847
453 nanjinghong 99.34% 16.9085 SRR8325874
461 shuimeiren 99.37% 16.9447 SRR8325873
467 yubanbai 99.30% 15.5537 SRR8325876
468 yuhua 99.35% 17.4529 SRR8325875
495 liuhuo 99.20% 15.6028 SRR8325867
566 xiaoxia 99.40% 17.5277 SRR8325861
591 baiyun 99.45% 16.3501 SRR8325895
600 baiqianye 99.32% 17.2098 SRR8325848
619 jinzhuluoyupan 99.43% 15.6951 SRR8325849
640 hanhong 97.50% 17.2591 SRR8325850
642 fengximudan 99.34% 17.7888 SRR8325851
643 suzhibingzi 99.48% 17.5635 SRR8325852
652 chongbanyizhangqing 99.50% 16.64 SRR8325842
653 zhongshanhongtai 99.40% 16.5431 SRR8325854
656 shennvzi 99.31% 16.3544 SRR8325855
674 yanzhilu 99.46% 17.481 SRR8325856
678 xinjie 97.81% 16.2709 SRR8325892
709 chaitoufeng 99.33% 15.3606 SRR8325891
770 caiyunfeidu 99.43% 16.9894 SRR8325890
782 lianxia 99.33% 18.4933 SRR8325889
807 pizhenhong 99.23% 16.1976 SRR8325888
832 haoyue 98.68% 16.1062 SRR8325887
846 jiaoniang 99.34% 16.6935 SRR8325886
847 danxiuqiu 99.37% 17.3691 SRR8325885
855 hongdenggaozhao 99.18% 15.4943 SRR8325894
896 fenxia 99.46% 15.3978 SRR8325893
908 zhaoyun 99.43% 16.3684 SRR8325845
911 baimeilian 99.45% 20.3636 SRR8325846
7159815 hongtailian 99.31% 11.5062 SRR7159815
7159817 shuguangxiu 99.18% 12.0447 SRR7159817
7159818 donghuxinhong 99.34% 11.7097 SRR7159818
7159820 xiangbihe 99.03% 11.582 SRR7159820
7159821 fengjuanhongqi 99.14% 11.1591 SRR7159821
7159822 xingkongmudan 98.93% 12.5915 SRR7159822
7159825 honghehuan 98.30% 11.5102 SRR7159825
7159826 jinlinghuodu 98.91% 14.5597 SRR7159826
7159827 xiaoqu 99.16% 12.7112 SRR7159827
7159828 xiaojingling 97.92% 11.7524 SRR7159828
7159829 zuidongfeng 99.33% 13.1111 SRR7159829
7159830 hongyun 99.24% 13.9575 SRR7159830
7159831 jinlingzhixing 99.27% 13.6104 SRR7159831
7159832 danyue 99.16% 12.4043 SRR7159832
7159833 qinhuaibaiyu 98.41% 11.6404 SRR7159833
BG baige 99.36% 20.3992 SRR4308656
BYDHL baiyangdianhonglian 99.11% 3.68911 SRR4308659
DH2 donghonghua 99.27% 22.267 SRR4308651
FH fenhonglingxiao 99.04% 18.6101 SRR4308650
HLJHL heilongjianghonglian 98.92% 3.93594 SRR4308657
JX jianxuan17 99.27% 20.6081 SRR4308643
PZHBL puzheheibailian 99.17% 5.14056 SRR4308658
QBL qianbanlian 99.11% 3.83764 SRR4308655
WSHL weishanhonglian 99.14% 7.54628 SRR4308645
XHHL xihuhonglian 99.01% 4.30606 SRR4308660
ZGWS zhigaowushang 99.07% 20.4065 SRR4308649
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Database construction

All genomic sequence, annotation, expression, and genetic variation data were stored via MySQL on a Ubuntu server. A user-friendly website was developed using HTML5 and JavaScript; this website which can be accessed through different browsers, such as Google Chrome and Firefox. Gene models and transcript isoforms are provided via GBrowse and JBrowse. Heatmaps of gene expression are plotted via R, and query searches are achieved via JavaScript and Java. Common utilities for genomic studies such as BLAST, BLAT and Primer Design are also deployed and accessible.

Data Records

The genomic raw PacBio sequencing data are available in the NCBI Sequence Read Archive (SRA) database under accession numbers SRR754912941 and SRR754913042, and the Illumina and Hi-C sequencing data are deposited under SRR761555343 and SRR763152344, which helped us in our genome assembly (Online-only Table 1). Raw whole-genome resequencing reads for 62 strains can be downloaded from the NCBI database under Bioproject accession SRP17354745, and the resequencing data of the other 22 cultivars are also accessible via the NCBI SRA46,47 (Online-only Table 2). The latest assembly and annotations of the ‘China Antique’ lotus variety is deposited in the Nelumbo Genome Database (Download links: http://nelumbo.biocloud.net/downloadData/download?path = NNU.genomic.fa and http://nelumbo.biocloud.net/downloadData/download?path = NNU.gff3). Additionally, this Whole Genome Shotgun project has been deposited at DDBJ/ENA/GenBank under the accession DUZY00000000, and the version described in this paper is version DUZY0100000048. Improved gene and repeat (including transposable element) predictions (GFF3), coding and peptide sequences (FASTA), gene and transcript functional annotations, gene expression and coexpression profiles, SNP and InDel variations, phenotypic traits and images for 88 lotus strains have been uploaded into the Figshare database49 and deployed in the newly developed Nelumbo Genome Database (http://nelumbo.biocloud.net).

Technical Validation

Quality control of genome annotation, expression, and genome resequencing was performed during data processing for the NGD.

Genome annotation

We used a set of conserved single-copy plant genes from the BUSCO database to assess the completeness of gene annotations50. Compared with previous annotations of the lotus variety China Antique (BUSCOs = 74.6%), our new annotation version provides much improved, complete BUSCOs (97.5%), and 41,140 out of 46,713 annotated genes with either complete or partial ORFs (88%) were validated by 69 transcriptome datasets (Figure S1a), which suggests relatively high quality and completeness of the genome assembly and gene annotations (Table 2).

Table 2.

BUSCO assessment of the completeness of gene annotation.

Gene numbera BUSCO ratioa Gene numberb BUSCO ratiob
Complete BUSCOs 1404 97.5% 1074 74.6%
Complete and single-copy BUSCOs 750 52.1% 947 65.8%
Complete and duplicated BUSCOs 654 45.4% 127 8.8%
Fragmented BUSCOs 16 1.1% 152 10.6%
Missing BUSCOs 20 1.4% 214 14.9%
Total BUSCO groups searched 1440 1440
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aThe current genome assembly and annotation of var. China Antique8.

bEarly genome assembly and annotation of var. China Antique9.

Gene expression

To ensure that the FPKMs of genes accurately reflect the gene expression in different tissues and at different developmental stages, hierarchical clustering of gene FPKMs across different RNA-seq samples of the variety China Antique was performed via Expander 6.051. All sample repeats clustered together, while all developmental stages from the same tissue clustered together, except for one petiole sample, and the relative expression of randomly selected genes in different tissues was validated through qRT-PCR (Fig. 2 and Figure S1b). Therefore, we confirmed the accuracy of FPKM as an indicator of lotus gene expression.

Fig. 2.

Fig. 2

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Hierarchical clustering of different RNA-seq samples based on a gene expression matrix (FPKM) from the lotus variety China Antique. Note that only a small portion of the genes are shown in the heatmap.

Whole-genome resequencing

Before genome mapping, adapters and low-quality Illumina reads were filtered and removed (see the Methods). Base content, error rate, insert size distribution and log-transformed read coverage across the lotus chromosomes were checked, all of which met the criteria for downstream analyses (Fig. 3). The quality of genome mapping was also checked. The average mapping rate for cultivars from this study was 99.18%, while the numbers in the other cultivars collected from two previous studies were 98.98% and 99.13% (Online-only Table 2). The average depth for the cultivars from the current study was 16.1×, while the depth was 12.4× and 11.8× for cultivars from the other two reports (Online-only Table 2). To ensure the final quality of SNPs and InDels called by the GATK pipeline, stringent hard-filtering parameters were set (see the Methods). Because the majority of alleles in the SNP data set are expected to be shared by at least two individuals, we plotted the frequency of SNPs according to the minor allele count (MAC) across the 88 cultivars. Indeed, most of the SNPs had MACs ≥ 2, while the SNP density peaked around MACs of four or five (Fig. 4). SNP variants were further validated and visualized using IGVtools (http://software.broadinstitute.org/software/igv/igvtools) (Figure S1c).

Fig. 3.

Fig. 3

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Quality evaluation of the genome resequencing data of cultivars, including the base content (a), error rate (b), insert size distribution (c) and log-transformed read coverage across eight lotus chromosomes (d), as demonstrated by the example of lotus cultivar Xiaoxia. The resequencing quality met the criterion for downstream variant calling analyses.

Fig. 4.

Fig. 4

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Distribution of SNPs according to the minor allele count (MAC) across 88 lotus cultivars.

Supplementary information

Supplementary file (328.5KB, docx)

Acknowledgements

This work was supported by grants from the Strategic Priority Research Program CAS (No. XDB31000000), the National Natural Science Foundation of China (No. 31570220, No. 31870208 and No. 31700197), the Youth Innovation Promotion Association of the Chinese Academy of Sciences (No. 2019335), the Bureau of Landscaping and Forestry of Wuhan Municipality (No. WHGF2019A10), the Hubei Provincial Natural Science Foundation of China (No. 2019CFB275), and the Hubei Chenguang Talented Youth Development Foundation. We thank Razgar Seyed Rahmani from Ghent University for the discussion.

Online-only Tables

Author contributions

Genome sequencing, assembly and annotation: T.S.; RNA-seq and gene expression: Y.Z., X.Y.; genome resequencing of cultivars: H.L., X.Y.; phenotype collection: X.Y., Z.G.; sample collection and experiments: C.W., Y.L.; communications, web design and conceptualization: J.C.; manuscript writing and revising: H.L., J.C. and T.S.

Code availability

The genomic and transcriptomic sequence data were produced by corresponding software provided by the sequencing platform manufacturer, and the software (including versions, parameters and settings) used for genome assembly was cited in the Methods section, with default parameters used when no detailed parameters were mentioned. The code for the NGD construction in Java is available in the Figshare database49.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

These authors contributed equally: Hui Li, Xingyu Yang.

Contributor Information

Jinming Chen, Email: jmchen@wbgcas.cn.

Tao Shi, Email: shitao323@wbgcas.cn.

Supplementary information

The online version contains supplementary material available at 10.1038/s41597-021-00828-8.

References

  • 1.Gandolfo MA, Nixon KC, Crepet WL. Cretaceous flowers of Nymphaeaceae and implications for complex insect entrapment pollination mechanisms in early angiosperms. Proc. Natl. Acad. Sci. USA. 2004;101:8056–8060. doi: 10.1073/pnas.0402473101. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Zheng C, Sankoff D. Practical halving; the Nelumbo nucifera evidence on early eudicot evolution. Comput Biol Chem. 2014;50:75–81. doi: 10.1016/j.compbiolchem.2014.01.010. [DOI] [PubMed] [Google Scholar]
  • 3.Hayes V, Schneider EL, Carlquist S. Floral development of Nelumbo nucifera (Nelumbonaceae) Int. J. Plant Sci. 2000;161:S183–S191. doi: 10.1086/317577. [DOI] [Google Scholar]
  • 4.Slocum, P. D. Waterlilies and Lotuses: Species, Cultivars, and New Hybrids. (Timber Press, 2005).
  • 5.Zhou M, et al. Identification and comparison of anti-inflammatory ingredients from different organs of lotus nelumbo by UPLC/Q-TOF and PCA coupled with a NF-kappaB reporter gene assay. PloS One. 2013;8:e81971. doi: 10.1371/journal.pone.0081971. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Cheng T, et al. Development and identification of three functional markers associated with starch content in lotus (Nelumbo nucifera) Sci. Rep. 2020;10:4242. doi: 10.1038/s41598-020-60736-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Li Y, et al. Comparative population genomics reveals genetic divergence and selection in lotus. Nelumbo nucifera. BMC Genom. 2020;21:146. doi: 10.1186/s12864-019-6376-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Shi T, et al. Distinct expression and methylation patterns for genes with different fates following a single whole-genome duplication in flowering plants. Mol. Biol. Evol. 2020;37:2394–2413. doi: 10.1093/molbev/msaa105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Ming R, et al. Genome of the long-living sacred lotus (Nelumbo nucifera Gaertn.) Genome Biol. 2013;14:R41. doi: 10.1186/gb-2013-14-5-r41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Huang L, et al. Whole genome re-sequencing reveals evolutionary patterns of sacred lotus (Nelumbo nucifera) J Integr Plant Biol. 2018;60:2–15. doi: 10.1111/jipb.12606. [DOI] [PubMed] [Google Scholar]
  • 11.Zhao M, et al. Detection of highly differentiated genomic regions between lotus (Nelumbo nucifera Gaertn.) with contrasting plant architecture and their functional relevance to plant architecture. Front. Plant Sci. 2018;9:1219. doi: 10.3389/fpls.2018.01219. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Yang M, et al. Transcriptomic analysis of the regulation of rhizome formation in temperate and tropical Lotus (Nelumbo nucifera) Sci. Rep. 2015;5:13059. doi: 10.1038/srep13059. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Li J, et al. Systematic transcriptomic analysis provides insights into lotus (Nelumbo nucifera) seed development. Plant Growth Regul. 2018;86:339–350. doi: 10.1007/s10725-018-0433-1. [DOI] [Google Scholar]
  • 14.Zhang Y, Nyong AT, Shi T, Yang P. The complexity of alternative splicing and landscape of tissue-specific expression in lotus (Nelumbo nucifera) unveiled by Illumina- and single-molecule real-time-based RNA-sequencing. DNA Res. 2019;26:301–311. doi: 10.1093/dnares/dsz010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Zheng Y, et al. Genome-wide analysis of microRNAs in sacred lotus, Nelumbo nucifera (Gaertn) Tropical Plant Biol. 2013;6:117–130. doi: 10.1007/s12042-013-9127-z. [DOI] [Google Scholar]
  • 16.Shi T, Wang K, Yang P. The evolution of plant microRNAs: insights from a basal eudicot sacred lotus. Plant J. 2017;89:442–457. doi: 10.1111/tpj.13394. [DOI] [PubMed] [Google Scholar]
  • 17.Zhang Y, Rahmani RS, Yang X, Chen J, Shi T. Integrative expression network analysis of microRNA and gene isoforms in sacred lotus. BMC Genom. 2020;21:429. doi: 10.1186/s12864-020-06853-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Wang Y, et al. Genome-wide identification and characterization of GRAS transcription factors in sacred lotus (Nelumbo nucifera) PeerJ. 2016;4:e2388. doi: 10.7717/peerj.2388. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Li H, Yang X, Lu M, Chen J, Shi T. Gene expression and evolution of Family-1 UDP-glycosyltransferases—insights from an aquatic flowering plant (sacred lotus) Aquat. Bot. 2020;166:103270. doi: 10.1016/j.aquabot.2020.103270. [DOI] [Google Scholar]
  • 20.Chui R, Jaromczyk JW, Moore N, Schardl CL. FPD2GB2: automating a transition from a customized genome browser to GBrowse2. BMC Bioinform. 2013;14:A17. doi: 10.1186/1471-2105-14-S17-A17. [DOI] [Google Scholar]
  • 21.Buels R, et al. JBrowse: a dynamic web platform for genome visualization and analysis. Genome Biol. 2016;17:66. doi: 10.1186/s13059-016-0924-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Pertea M, Kim D, Pertea GM, Leek JT, Salzberg SL. Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown. Nat. Protoc. 2016;11:1650–1667. doi: 10.1038/nprot.2016.095. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Niknafs YS, Pandian B, Iyer HK, Chinnaiyan AM, Iyer MK. TACO produces robust multisample transcriptome assemblies from RNA-seq. Nat. Methods. 2017;14:68–70. doi: 10.1038/nmeth.4078. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Michael TP, et al. High contiguity Arabidopsis thaliana genome assembly with a single nanopore flow cell. Nat. Commun. 2018;9:541. doi: 10.1038/s41467-018-03016-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Ming R, et al. The draft genome of the transgenic tropical fruit tree papaya (Carica papaya Linnaeus) Nature. 2008;452:991–996. doi: 10.1038/nature06856. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Jaillon O, et al. The grapevine genome sequence suggests ancestral hexaploidization in major angiosperm phyla. Nature. 2007;449:463–467. doi: 10.1038/nature06148. [DOI] [PubMed] [Google Scholar]
  • 27.Nock CJ, Baten A, King GJ. Complete chloroplast genome of Macadamia integrifolia confirms the position of the Gondwanan early-diverging eudicot family Proteaceae. BMC Genom. 2014;15:S13. doi: 10.1186/1471-2164-15-S9-S13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Fox SE, et al. Sequencing and de novo transcriptome assembly of Brachypodium sylvaticum (Poaceae) Appl. Surf. Sci. 2013;1:apps.1200011. doi: 10.3732/apps.1200011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Hoff KJ, Lomsadze A, Borodovsky M, Stanke M. Whole-genome annotation with BRAKER. Methods Mol. Biol. 2019;1962:65–95. doi: 10.1007/978-1-4939-9173-0_5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinform. 2008;9:559. doi: 10.1186/1471-2105-9-559. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Zhang B, Horvath S. A general framework for weighted gene co-expression network analysis. Stat. Appl. Genet. Mol. Biol. 2005;4:Article17. doi: 10.2202/1544-6115.1128. [DOI] [PubMed] [Google Scholar]
  • 32.Kanehisa M, Goto S, Kawashima S, Okuno Y, Hattori M. The KEGG resource for deciphering the genome. Nucleic Acids Res. 2004;32:D277–280. doi: 10.1093/nar/gkh063. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Ai C, Kong L. CGPS: A machine learning-based approach integrating multiple gene set analysis tools for better prioritization of biologically relevant pathways. J Genet Genomics. 2018;45:489–504. doi: 10.1016/j.jgg.2018.08.002. [DOI] [PubMed] [Google Scholar]
  • 34.El-Gebali S, et al. The Pfam protein families database in 2019. Nucleic Acids Res. 2019;47:D427–D432. doi: 10.1093/nar/gky995. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Jin J, et al. PlantTFDB 4.0: toward a central hub for transcription factors and regulatory interactions in plants. Nucleic Acids Res. 2017;45:D1040–D1045. doi: 10.1093/nar/gkw982. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Cota-Sánchez JH, Remarchuk K, Ubayasena K, Ready-to-use DNA. extracted with a CTAB method adapted for herbarium specimens and mucilaginous plant tissue. Plant Mol. Biol. Rep. 2006;24:161–167. doi: 10.1007/BF02914055. [DOI] [Google Scholar]
  • 37.Li H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics. 2010;26:589–595. doi: 10.1093/bioinformatics/btp698. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.McKenna A, et al. The genome analysis toolkit: a mapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010;20:1297–1303. doi: 10.1101/gr.107524.110. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Zhang, X. & Wang, Q. New Lotus Flower Cultivars in China. (China Forestry Publishing House, 2011).
  • 40.Zhang, X. & Wang, Q. Lotus Flower Cultivars in China. (China Forestry Publishing House, 2005).
  • 41.2018. NCBI Sequence Read Archive. SRR7549129
  • 42.2018. NCBI Sequence Read Archive. SRR7549130
  • 43.2018. NCBI Sequence Read Archive. SRR7615553
  • 44.2018. NCBI Sequence Read Archive. SRR7631523
  • 45.2018. NCBI Sequence Read Archive. SRP173547
  • 46.2018. NCBI Sequence Read Archive. SRP145546
  • 47.2016. NCBI Sequence Read Archive. SRP090666
  • 48.2020. GenBank whole genome shotgun sequencing project. DUZY00000000
  • 49.Li H, 2020. Nelumbo genome database, an integrative resource for gene expression and variants of Nelumbo nucifera. figshare. [DOI] [PMC free article] [PubMed]
  • 50.Simao FA, Waterhouse RM, Ioannidis P, Kriventseva EV, Zdobnov EM. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics. 2015;31:3210–3212. doi: 10.1093/bioinformatics/btv351. [DOI] [PubMed] [Google Scholar]
  • 51.Sharan R, Maron-Katz A, Shamir R. CLICK and EXPANDER: a system for clustering and visualizing gene expression data. Bioinformatics. 2003;19:1787–1799. doi: 10.1093/bioinformatics/btg232. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Citations

  1. 2018. NCBI Sequence Read Archive. SRR7549129
  2. 2018. NCBI Sequence Read Archive. SRR7549130
  3. 2018. NCBI Sequence Read Archive. SRR7615553
  4. 2018. NCBI Sequence Read Archive. SRR7631523
  5. 2018. NCBI Sequence Read Archive. SRP173547
  6. 2018. NCBI Sequence Read Archive. SRP145546
  7. 2016. NCBI Sequence Read Archive. SRP090666
  8. 2020. GenBank whole genome shotgun sequencing project. DUZY00000000
  9. Li H, 2020. Nelumbo genome database, an integrative resource for gene expression and variants of Nelumbo nucifera. figshare. [DOI] [PMC free article] [PubMed]

Supplementary Materials

Supplementary file (328.5KB, docx)

Data Availability Statement

The genomic and transcriptomic sequence data were produced by corresponding software provided by the sequencing platform manufacturer, and the software (including versions, parameters and settings) used for genome assembly was cited in the Methods section, with default parameters used when no detailed parameters were mentioned. The code for the NGD construction in Java is available in the Figshare database49.

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