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. 2016 Aug 8;5:35. doi: 10.1186/s13742-016-0139-0

Improved hybrid de novo genome assembly of domesticated apple (Malus x domestica)

Xuewei Li 1,#, Ling Kui 2,#, Jing Zhang 3, Yinpeng Xie 1, Liping Wang 1, Yan Yan 1, Na Wang 1, Jidi Xu 1, Cuiying Li 1, Wen Wang 2, Steve van Nocker 4, Yang Dong 5,6,, Fengwang Ma 1,, Qingmei Guan 1,
PMCID: PMC4976516  PMID: 27503335

Abstract

Background

Domesticated apple (Malus × domestica Borkh) is a popular temperate fruit with high nutrient levels and diverse flavors. In 2012, global apple production accounted for at least one tenth of all harvested fruits. A high-quality apple genome assembly is crucial for the selection and breeding of new cultivars. Currently, a single reference genome is available for apple, assembled from 16.9 × genome coverage short reads via Sanger and 454 sequencing technologies. Although a useful resource, this assembly covers only ~89 % of the non-repetitive portion of the genome, and has a relatively short (16.7 kb) contig N50 length. These downsides make it difficult to apply this reference in transcriptive or whole-genome re-sequencing analyses.

Findings

Here we present an improved hybrid de novo genomic assembly of apple (Golden Delicious), which was obtained from 76 Gb (~102 × genome coverage) Illumina HiSeq data and 21.7 Gb (~29 × genome coverage) PacBio data. The final draft genome is approximately 632.4 Mb, representing ~ 90 % of the estimated genome. The contig N50 size is 111,619 bp, representing a 7 fold improvement. Further annotation analyses predicted 53,922 protein-coding genes and 2,765 non-coding RNA genes.

Conclusions

The new apple genome assembly will serve as a valuable resource for investigating complex apple traits at the genomic level. It is not only suitable for genome editing and gene cloning, but also for RNA-seq and whole-genome re-sequencing studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s13742-016-0139-0) contains supplementary material, which is available to authorized users.

Keywords: Malus x domestica, Apple, Illumina sequencing, PacBio sequencing

Data description

Whole-genome shotgun sequencing of ‘Golden Delicious’ apple on the Illumina platform

Genomic DNA was extracted from leaf tissues of a single ‘Golden Delicious’ apple tree with the GenElute™ Plant Genomic DNA Miniprep Kit (Sigma-Aldrich; St. Louis, USA). Paired-end libraries with insert sizes ranging from 350–500 bp were constructed with Next UltraTM DNA Library Prep Kit for Illumina (NEB; USA) according to the manufacturer’s instructions. These libraries were sequenced on an Illumina HiSeq 4000 platform (Illumina; CA, USA) using the PE-150 module [1], and yielded about 86 Gb of raw data. These data were then subjected to filtering to remove: (1) reads in which more than 5 % of bases were N or poly-A; (2) reads in which more than 30 bases were of low quality; (3) reads with adapter contamination; (4) reads shorter than 30 bp; and (5) PCR duplicates. These steps yielded a clean sequence of ~76 GB, representing about 102 × genome coverage (Additional file 1: Table S1). De novo assembly was performed with with SOAPec_v2.01 [2] using default parameters.

Single-molecule long read sequencing of ‘Golden Delicious’ apple on the PacBio platform

Single-molecule long reads from the PacBio RS II platform (Pacific Biosciences, USA) were used to assist the subsequent de novo genome assembly [3]. In brief, 15 μg of sheared DNA was used to construct five SMRT Bell libraries with an insert size of 17 kb. The libraries were then sequenced in 20 single-molecule real-time DNA sequencing cells using the P6 polymerase/C4 chemistry combination, and a data collection time of 240 min per cell. The sequencing produced about 21.7 Gb data, consisting of 2,759,937 reads with an average read length of 7,863 bp (Additional file 1: Figure S1). The polymerase read N50 length after single passing was around 16.6 kb, and the polymerase read quality was greater than 82.4 % (Additional file 1: Table S1).

Estimation of the ‘Golden Delicious’ apple genome size

Quality-filtered reads from the Illumina platform were subjected to 23-mer frequency distribution analysis with Jellyfish [4]. Analysis parameters were set at -k 23, and the final result was plotted as a frequency graph (Additional file 1: Figure S2). Two distinctive modes were observed from the distribution curve: the higher peak at a depth of 88 reflected the high heterozygosity of the apple genome; the lower peak provided a peak depth of 179 for the estimation of its genome size. Based on the total number of k-mers (125,428,662,216), the apple genome size was calculated to be approximately 701 Mb, using the following formula: genome size = k-mer_Number/Peak_Depth.

Hybrid de novo genome assembly

A hybrid genome assembly pipeline was used to overcome challenges posed by heterozygous apple genome (Additional file 1: Figure S3). An Illumina-based de novo genome assembly was first generated using Platanus [2], yielding a total length of 1.05 Gb, with a contig N50 length of 534 bp. Then, all PacBio RS reads were used in the hybrid assembly process via the DBG2OLC [5] pipeline with the following parameters: LD10, MinLen 200, KmerCovTh 2, MinOverlap 10, AdaptiveTh 0.001, and RemoveChimera 1. This led to a preliminary apple genome assembly of 632.4 Mb with a contig N50 size of 111,619 bp, representing ~90 % of the estimated apple genome (701 Mb). The contig N50 size represents a ~6.9 fold improvement in length from the previously reported 16.1 kb [6]. These improvements were made possible by introducing the long-read sequencing strategy (Additional file 1: Figure S4), which increased the sequencing precision of repeats.

Evaluation of the completeness of the ‘Golden Delicious’ apple genome assembly

CEGMA was used to evaluate the quality of the final assembly with a set of 248 ultra-conserved core eukaryotic genes [7]. Comparison analysis showed that 231 of 248 genes could be fully annotated (93.15 % completeness, see Table 1), and 243 of 248 genes met the criteria for partial annotation (97.98 % completeness). Using the same evaluation parameters, the completeness of the ‘Golden Delicious’ apple genome assembly v1.0 by Velasco et al. [6] was also evaluated, and a completeness of 88.71 % was obtained (220 of 248 genes could be fully annotated, see Additional file 1: Table S3). This benchmark further demonstrates the improved quality of the genome assembly reported herein.

Table 1.

Statistics of the completeness of the hybrid de novo assembly genome of ‘Golden Delicious’ based on 248 core eukaryotic genes, produced by the software CEGMA [7] with default parameters

Group #Prots %Completeness #Total Average %Ortho
Complete 231 93.15 545 2.36 74.46
Group1 63 95.45 127 2.02 66.67
Group2 50 89.29 120 2.40 78.00
Group3 58 95.08 136 2.34 72.41
Group4 60 92.31 162 2.70 81.67
Partial 243 97.98 710 2.92 86.01
Group1 64 96.97 173 2.70 82.81
Group2 54 96.43 159 2.94 87.04
Group3 61 100.00 181 2.97 88.52
Group4 64 98.46 197 3.08 85.94

#Prots: number of 248 ultra-conserved CEGs present in genome

%Completeness: percentage of 248 ultra-conserved CEGs present

Total: total number of CEGs present including putative orthologs

Average: average number of orthologs per CEG

%Ortho: percentage of detected CEGS that have more than 1 ortholog

‘Complete’: predicted proteins in the set of 248 CEGs that, when aligned to the HMM (a hidden markov model) for the KOG (eukaryotic orthologous groups) for that protein family, give an alignment length that is at least 70 % of the protein length

‘Partial’: If a protein is not complete, but exceeds a pre-computed minimum alignment score, then we call the protein ‘partial’. The pre-computed scores are all in the file CEGMA/data/completeness_cutoff.tbl [7]

CEGs: core eukaryotic genes

Repeat annotation of the ‘Golden Delicious’ apple genome assembly

Tandem Repeat Finder [8] was used to identify tandem repeats in the ‘Golden Delicious’ apple genome. RepeatMasker and RepeatProteinMasker [9] were used against Repbase [10] to identify known transposable element repeats. In addition, RepeatModeler [11] and LTR FINDER [12] were used to identify de novo evolved repeats. The combined results show that the total length of repeated sequences is about 382 Mb, accounting for ~60 % of the ‘Golden Delicious’ apple genome assembly (Additional file 1: Table S4).

Gene annotation

Genes for the ‘Golden Delicious’ genome were annotated using multiple methods, including transcriptome-based predictions, de novo predictions, and homology-based predictions. For de novo predictions, Augustus [13], GenScan [14], glimmerHMM [15] and SNAP [16] analysis were performed on the repeat-masked genome, with parameters trained from Arabidopsis thaliana. Partial sequences and genes with fewer than 150 bp of coding sequence length were removed. Predicted protein sequences from B. oleracea, G. max, O. sativa, P. mume, P. trichocarpa, P. persica, P. communis, V. vinifera, and Z. mays were used (Phytozome v10.3 [17]) for homology-based predictions. First, query sequences were subjected to TBLASTN analysis with an Expect (E)-value cutoff of 1 e-5. BLAST hits corresponding to reference proteins were concatenated by Solar software (The Beijing Genomics Institute (BGI) development), and low-quality records were removed. The genomic sequence of each reference protein was extended upstream and downstream by 2,000 bp to represent a protein-coding region. GeneWise software [18] was used to predict gene structure contained in each protein region. For transcriptome-based predictions, RNA from three structures (leaves, flowers, and stems) was isolated and RNA-seq data (NCBI SRP067376) were used for gene annotation, processed by Tophat and Cufflinks [19]. The homology, de novo and transcriptomic gene sets were merged to form a comprehensive and non-redundant reference gene set using EVidenceModeler [20] software. Our analysis indicates that the ‘Golden Delicious’ apple genome contains 53,922 protein-coding genes (Table 2). This is slightly fewer than the previous prediction of 57,386 genes [6]. Approximately 60 % of predicted genes were represented in our transcriptome data.

Table 2.

Statistics for ‘Golden Delicious’ genome protein-coding sequences annotation

Gene_number Avg_mRNA_length (bp) Total_exon_number Avg_exon_length (bp) Avg_cds_length (bp) Avg_exon_number Total_intron_length (bp)
De novo augustus 37693 2233.785106 203848 166.933235 902.793781 5.408113 50169056
genscan 33206 8849.329489 210077 158.970511 1005.723303 6.326477 260454787
glimmerHMM 48129 1404.407447 151751 182.492643 575.400299 3.153005 39899285
snap 73555 936.269975 219634 162.207063 484.347577 2.985983 33241152
Homolog B. oleracea 7000 2320.829429 46309 139.074802 920.059286 6.615571 9805391
G. max 8578 2427.167172 60008 137.457522 961.593728 6.995570 12571689
O. sativa 11000 1887.083182 61308 137.971668 768.978818 5.573455 12299148
P. mume 9000 2623.029667 67760 135.473332 1019.963667 7.528889 14427594
P. trichocarpa 30585 2321.131764 207830 138.869210 943.638646 6.795161 42130627
P. persica 12733 2431.885573 93666 134.420665 988.820074 7.356161 18374553
P. communis 34642 2833.118267 256347 129.467222 958.043242 7.399890 64956349
V. vinifera 17175 2460.852402 118296 138.772773 955.823231 6.887686 25848876
Z. mays 22341 2004.558569 130795 138.548645 811.130657 5.854483 26662373
RNA-seq GDflorwer1 48423 2234.847387 212811 300.027231 1318.569585 4.394833 49998557
GDflorwer2 49952 2231.126001 220057 304.286867 1340.495976 4.405369 50837822
GDflorwer3 49848 2242.481785 223056 305.307031 1366.164440 4.474723 49515976
GDleaf1 45034 2258.958920 203894 296.653634 1343.116223 4.527557 46765622
GDleaf2 44669 2300.217086 204106 298.250576 1362.795943 4.569299 47700782
GDleaf3 45220 2292.436975 206566 301.208723 1375.928372 4.568023 47304519
GDstem1 46908 2299.298840 212019 308.944807 1396.396542 4.519890 48015182
GDstem2 46271 2308.347604 209286 307.787090 1392.136090 4.523049 48368862
GDstem3 46657 2296.511542 209284 310.624348 1393.332319 4.485586 48454706
EVM 53922 1793.161066 221394 167.775983 688.857906 4.105820 59546235

Non-coding RNA annotation

tRNAscan-SE (version 1.31) [21] software with default parameters for eukaryotes was used for tRNA annotation. rRNA annotation was based on homology with rRNAs from several diverse higher plant species (not shown), using BLASTN with ‘E-value = 1e-5’. miRNA and snRNA genes were predicted by INFERNAL software [22] using the Rfam database (release 11.0) [23]. The final results included 321 miRNAs, 274 tRNAs, 605 rRNAs, and 480 snRNAs (Additional file 1: Table S5).

Availability of supporting data

Sequencing reads of each sequencing library and RNA-seq data have been deposited at NCBI with the project ID SRP067376. Supporting data are also available in the GigaScience database, GigaDB [24]. All supplementary figures and tables are provided in Additional file 1.

Abbreviations

CDS, coding DNA sequence; NCBI, National Center for Biotechnology Information

Funding

This work was support by the National Science Foundation of China (31572106) and QG is supported by funding from the Thousand Talents Plan.

Authors’ contributions

FM, QG, YD and WW designed the study. JZ assembled the genome. XL, YX and NW extracted DNA, LK constructed libraries, LW and YY analyzed the data. QG, JZ XL, and SN wrote the manuscript. All authors read and approved the final manuscript.

Competing interests

JZ is a shareholder of Agri-biotech Lab Company (Kunming, Yunnan).

Additional file

Additional file 1: (327KB, zip)

Supplementary figures and tables. (ZIP 326 kb)

Contributor Information

Xuewei Li, Email: vivian@nwsuaf.edu.cn.

Ling Kui, Email: kuiling2008@163.com.

Jing Zhang, Email: 1600578887@qq.com.

Yinpeng Xie, Email: xyp413826@163.com.

Liping Wang, Email: lipingwang@nwsuaf.edu.cn.

Yan Yan, Email: yannwsuaf@126.com.

Na Wang, Email: wang1993na@163.com.

Jidi Xu, Email: xujidi@nwsuaf.edu.cn.

Cuiying Li, Email: lcy1262@nwsuaf.edu.cn.

Wen Wang, Email: wwang@mail.kiz.ac.cn.

Steve van Nocker, Email: vannocke@msu.edu.

Yang Dong, Email: loyalyang@163.com.

Fengwang Ma, Email: fwm64@sina.com.

Qingmei Guan, Email: qguan@nwsuaf.edu.cn.

References

  • 1.Quail MA, Smith M, Coupland P, Otto TD, Harris SR, Connor TR, et al. A tale of three next generation sequencing platforms: comparison of Ion Torrent, Pacific Biosciences and Illumina MiSeq sequencers. BMC Genomics. 2012;13:341. doi: 10.1186/1471-2164-13-341. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Luo R, Liu B, Xie Y, Li Z, Huang W, Yuan J, et al. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience. 2012;1:18–24. doi: 10.1186/2047-217X-1-18. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Eid J, Fehr A, Gray J, Luong K, Lyle J, Otto G, et al. Real-time DNA sequencing from single polymerase molecules. Science. 2009;323:133–138. doi: 10.1126/science.1162986. [DOI] [PubMed] [Google Scholar]
  • 4.Marçais G, Kingsford C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics. 2011;27:764–770. doi: 10.1093/bioinformatics/btr011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Ye C, Hill C, Koren S, Ruan J, Ma Z. DBG2OLC: Efficient assembly of large genomes using the compressed overlap graph. http://arxiv.org/abs/1410.2801. Accessed 24 May 2016.
  • 6.Velasco R, Zharkikh A, Affourtit J, Dhingra A, Cestaro A, Kalynaraman A, et al. The genome of the domesticated apple (Malus x domestica Borkh.) Nat Genet. 2010;42:833–839. doi: 10.1038/ng.654. [DOI] [PubMed] [Google Scholar]
  • 7.Parra G, Bradnam K, Korf I. CEGMA: a pipeline to accurately annotate core genes in eukaryotic genomes. Bioinformatics. 2007;23:1061–1067. doi: 10.1093/bioinformatics/btm071. [DOI] [PubMed] [Google Scholar]
  • 8.Benson G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 1999;27:573–580. doi: 10.1093/nar/27.2.573. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Tarailo-Graovac M, Chen N. Using RepeatMasker to identify repetitive elements in genomic sequences. Curr. Protoc. Bioinformatics. 2009;3:4–14. doi: 10.1002/0471250953.bi0410s25. [DOI] [PubMed] [Google Scholar]
  • 10.Visser M, Van der Walt AP, Maree HJ, Rees DJ G, Burger JT. Extending the sRNAome of apple by next-generation sequencing. PLoS one. 2014;9:e95782. doi: 10.1371/journal.pone.0095782. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Smit A, Hubley R. RepeatModeler Open-1.0.8, 2008; http://www.repeatmasker.org/RepeatModeler.html.
  • 12.Xu Z, Wang H. LTR_FINDER: an efficient tool for the prediction of full-length LTR retrotransposons. Nucleic Acids Res. 2007;35(Suppl 2):W265–W268. doi: 10.1093/nar/gkm286. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Stanke M, Steinkamp R, Waack S, Morgenstern B. AUGUSTUS: a web server for gene finding in eukaryotes. Nucleic Acids Res. 2004;32(Suppl 2):W309–W312. doi: 10.1093/nar/gkh379. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Cai Y, Gonzalez JV, Liu Z, Huang T. Computational systems biology methods in molecular biology, chemistry biology, molecular biomedicine, and biopharmacy. Biomed Res Int. 2014;2014:746814. doi: 10.1155/2014/746814. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Majoros WH, Pertea M, Salzberg SL. TigrScan and GlimmerHMM: two open source ab initio eukaryotic gene-finders. Bioinformatics. 2004;20:2878–2879. doi: 10.1093/bioinformatics/bth315. [DOI] [PubMed] [Google Scholar]
  • 16.Korf I. Gene finding in novel genomes. BMC Bioinformatics. 2004;5:59. doi: 10.1186/1471-2105-5-59. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Goodstein DM, Shu S, Howson R, Neupane R, Hayes RD, Fazo J. Phytozome: a comparative platform for green plant genomics. Nucleic Acids Res. 2012;40:D1178–D1186. doi: 10.1093/nar/gkr944. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Birney E, Durbin R. Using GeneWise in the Drosophila annotation experiment. Genome Res. 2000;10:547–548. doi: 10.1101/gr.10.4.547. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Trapnell C, Roberts A, Goff L, Pertea G, Kim D, Kelley DR, et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nature Protoc. 2012;7:562–578. doi: 10.1038/nprot.2012.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Haas BJ, Salzberg SL, Zhu W, Pertea M, Eallen J, Orvis J, et al. Automated eukaryotic gene structure annotation using EVidenceModeler and the Program to Assemble Spliced Alignments. Genome Biol. 2008;9:R7. doi: 10.1186/gb-2008-9-1-r7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Lowe TM, Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 1997;25:955–964. doi: 10.1093/nar/25.5.0955. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Nawrocki EP, Kolbe DL, Eddy SR. Infernal 1.0: inference of RNA alignments. Bioinformatics. 2009;25:1335–1337. doi: 10.1093/bioinformatics/btp157. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Nawrocki EP, Eddy SR. Infernal 1.1: 100-fold faster RNA homology searches. Bioinformatics. 2013;29:2933–2935. doi: 10.1093/bioinformatics/btt509. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Guan Q, Li X, Kui L, Zhang J, Xie Y, Wang L, Yan Y, Wang N, Xu J, Li C, Wang W, Nocker SV, Dong Y, Ma F. Supporting information for “Improved hybrid de novo genome assembly of domesticated apple (Malus x domestica)”. GigaScience Database; 2016. http://gigadb.org/dataset/view/id/100189/token/BO7top5IQS1mkuyL. [DOI] [PMC free article] [PubMed]

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