Current status of whole-genome sequences of Korean angiosperms

Article information

Korean J. Pl. Taxon. 2023;53(3):181-200

Publication date (electronic) : 2023 September 30

doi : https://doi.org/10.11110/kjpt.2023.53.3.181

Jongsun PARK

, Yunho YUN

, Hong XI

, Woochan KWON

, Janghyuk SON

Infoboss Inc. and InfoBoss Research Center, Seoul 06278, Korea

Corresponding author Jongsun PARK E-mail: starflr@infoboss.co.kr

Received 2023 February 21; Revised 2023 September 21; Accepted 2023 September 22.

Abstract

Owing to the rapid development of sequencing technologies, more than 1,000 plant genomes have been sequenced and released. Among them, 69 Korean plant taxa (85 genome sequences) contain at least one whole-genome sequence despite the fact that some samples were not collected in Korea. The sequencing-by-synthesis method (next-generation sequencing) and the PacBio (third-generation sequencing) method were the most commonly used in studies appearing in 65 publications. Several scaffolding methods, such as the Hi-C and 10x types, have also been used for pseudo-chromosomal assembly. The most abundant families among the 69 taxa are Rosaceae (10 taxa), Brassicaceae (7 taxa), Fabaceae (7 taxa), and Poaceae (7 taxa). Due to the rapid release of plant genomes, it is necessary to assemble the current understanding of Korean plant species not only to understand their whole genomes as our own plant resources but also to establish new tools for utilizing plant resources efficiently with various analysis pipelines, including AI-based engines.

Keywords: Korean angiosperm species; plant resource utilization; scaffolding technology; sequencing technology; taxonomical distribution; Whole-genome sequence

INTRODUCTION

A genome sequence consisting of the complete list of nucleotides contains all of the genetic information of an organism (Alberts et al., 2002). Once the genome is deciphered properly, theoretically we may find all information pertaining to an organism, thus providing strong motivation for several early genome projects (Liggett, 2001), including those focusing on Arabidopsis thaliana L. (Martienssen and McCombie 2001; Mitchell-Olds, 2001). In 2000, the first plant whole-genome sequence, five chromosomes of A. thaliana L., was fully assembled and published (The Arabidopsis Genome Initiative, 2000), marking a relatively late start in comparison to those of bacteriophages (Sanger et al., 1977), bacteria (Fleischmann et al., 1995), and fungi (Goffeau et al., 1996). At that time, the A. thaliana genome had 25,498 genes (The Arabidopsis Genome Initiative, 2000), considered to be the most important element to understanding plants (Hutchison et al., 2016). Over time, researchers realized that additional elements, such as non-coding RNAs, also played important roles (Jones-Rhoades et al., 2006; Song et al., 2019) as other aspects by which we could understand plant whole-genome sequences.

Whole-genome sequences have been assembled from small pieces of DNA from organisms due to two major limitations of sequencing: (1) the start position of sequencing cannot be determined in a whole-genome project, and (2) the length of sequences we can obtain is limited, e.g., 500 bp to 1,000 bp when using the Sanger sequencing method. To decipher whole-genome sequences with sufficiently long lengths (e.g., A. thaliana is 119 Mbp (The Arabidopsis Genome Initiative, 2000) and Zea mays L. is 2.3 Gbp (Schnable et al., 2009)), an approach known as the whole-shotgun strategy was adopted after a method based on bacterial artificial chromosome (BAC) sequences (Zhang and Wu, 2001) given the large-scale computing power for genome assembly (Weber and Myers, 1997). After the commercialization of next-generation sequencing (NGS) technologies, which have critically reduced sequencing costs, to promote whole-genome sequencing projects, many plant genome sequences were released.

The National Center for Biotechnology Information (NCBI) has served as a data depository for many plant genome sequences (e.g., Cymbidium goeringii (Rchb.f.) Rchb.f. (Chung et al., 2021)). A centralized database in which to archive plant genome sequences is useful to provide access for comparative genomic analyses. The Plant Genome Database (https://www.plantgenome.info/) is such an example of a centralized database for plant whole-genome sequences (Park et al., 2021a), containing 3,509 genomes originating from 1,431 species (Release 3.0 to be available in March 2023). These genomic resources are important to conduct further various comparative genomic analyses to understand the genomes.

The accumulation of genome data for eukaryotes on a global scale has already begun (Lewin et al., 2018). Synthesizing the current status of whole-genome data on a local scale is necessary to set the stage for future research to ascertain the biodiversity and evolution of Korean plants and to discern applications of genomic resources ultimately to conserve endangered species. In this review, we examine the historical background of genome sequencing for plants, emphasizing the development of various sequencing technologies and the current status of whole genomes for angiosperms in Korea.

HISTORY OF SEQUENCING TECHNOLOGIES UTILIZED FOR DECIPHERING PLANT GENOMES

Sequencing technologies have been improved based on the requirements of whole-genome projects. First, it is now possible to increase the number of reads when conducting a whole-genome assembly given the greater computing power. As an example, the human genome project initiated by Craig Venter ended with the generation of 14.8 billion base-pairs (~5× coverage) for de novo assembly (Venter et al., 2001). Second, improved de novo assembly results are now possible by increasing the length of NGS raw reads. The first advance triggered the development of NGS technologies, including pyrosequencing (Fakhrai-Rad et al., 2002), sequencing by synthesis (Fuller et al., 2009), and sequencing by ligation (Smith et al., 2010). These technologies produced a great many reads in comparison to the Sanger sequencing method, though the reads are shorter than those generated by the Sanger sequencing method, apart from those that use pyrosequencing technology. After several plant genome sequences, including A. thaliana (The Arabidopsis Genome Initiative, 2000), Populus trichocarpa Torr. & A. Gray ex. Hook. (Tuskan et al., 2006), Vitis vinifera L. (Jaillon et al., 2007), and Z. mays (Schnable et al., 2009), were deciphered by the Sanger sequencing method, the cucumber (Cucumis sativus L.) genome was successfully assembled mainly based on sequencing by a synthesis method (commonly known as the Illumina method) (Huang et al., 2009). Although the NGS read length is relatively short, it has been shown that plant genome sequences can be assembled based on early short-read sequences (36-bp reads) generated by NGS technology. On the other hand, the 22-Gbp plant genome of Pinus taeda L. was successfully assembled (Zimin et al., 2014) based on pyrosequencing, implying that the de novo assembly of very large plant genomes is also possible with read lengths similar to those by the Sanger sequencing method.

As more plant genome sequences continue to be sequenced based on NGS technologies at a much lower cost in comparison to the Sanger sequencing method, the short length has become a critical hurdle hindering the realization of high-quality genome assemblies. New sequencing technologies after NGS technologies, referred to as third-generation sequencing (TGS) technologies, have been developed, with high-throughput sequencing reads longer than 10 kb, much longer than those by pyrosequencing and even the Sanger sequencing method (Terminology 1). Currently, the average length of the most recent single-molecular real-time (SMRT) sequencing method by Pacific Biosciences (PacBio) is around 10-25 kb with high accuracy (Hon et al., 2020) and the nanopore sequencing method by Oxford Nanopore Technologies (ONT) (referred to as Nanopore hereafter) produces ultra-long reads (>100 kb) (Amarasinghe et al., 2020).

Based on 65 genome publications covering 72 plant genomes (Table 1), the corresponding sequencing methods were investigated (Fig. 1). Most of the investigated genome projects utilized multiple methods, especially for those that adopted TGS methods requiring a base pair polishing process supported by NGS technologies. Only two genomes (2.77%), A. thaliana (The Arabidopsis Genome Initiative, 2000) and Arabidopsis lyrata (L.) O'Kane & Al-Shehbaz (Hu et al., 2011), were sequenced with only the Sanger sequencing method (Fig. 1, Table 1). Thirteen genomes were sequenced together with pyrosequencing and MiSeq technologies, which provide longer sequences than the typical NGS technologies; however, these methods were selected not due to the large genome (i.e., P. taeda (Zimin et al., 2014)) but because of available optimized sequencing technologies when these projects were conducted. Since the commercialization of TGS technologies, most genomes have been sequenced with PacBio or Nanopore (Fig. 1). Because Nanopore was commercialized later than PacBio, there have been fewer genomes deciphered using this method compared to those by PacBio (Fig. 1).

Table 1.

List of plant whole genome sequences of Korean angiosperms.

Fig. 1.

Sequencing methods used in whole-genome projects focusing on native and naturalized Korean plant species: the X-axis presents the sequencing methods used in genome projects with four-color tagged legends denoting their classification. The Y-axis displays the number of genomes for each method.

After assembling whole-genome sequences from raw reads successfully, additional processes for chromosomal-level assembly, including Hi-C (Lieberman-Aiden et al., 2009), 10X Genomics Chromium (termed 10× hereafter) (Weisenfeld et al., 2017), and Bionano (Bocklandt et al., 2019), referred to as the scaffolding method hereafter, were conducted for 20 genomes (23.53%; the Rosa rugosa Thunb. genome project used both Hi-C and 10× technologies) (Fig. 1) (Chen et al., 2021). The most frequently used technology is Hi-C (65.00%) (Fig. 1), which has been utilized in a wide range of genomic studies (Kong and Zhang, 2019). The remaining scaffolding methods, including old-fashioned techniques, i.e., the BAC-end (Osoegawa et al., 2001) and Fosmid-end (Williams et al., 2012) sequencing methods, showed to be rarely used (Fig. 1). Based on the ratio between N50 and the total length, recent scaffolding methods including Hi-C, 10×, and Bionano presented better efficiency of assembly with some exceptional cases, i.e., Erysimum cheiranthoides L. and Prunus davidiana Carrière (Fig. 2). In addition, the ratio does not present a correlation with the total genome length (R² = 0.0397), strongly suggesting that the N50 lengths of plant genomes depend on the species (Terminology 2).

Fig. 2.

Genome assembly properties, the ratio of N50 and total lengths and total lengths of genomes using scaffolding technologies the Xaxis displays species names in a genome project with two-color tags denoting the classification of the scaffolding technologies. Bars indicate the genome length of each species and the line graph shows the ratio of N50 and the total lengths.

CURRENT STATUS OF WHOLE GENOMES OF KOREAN ANGIOSPERM SPECIES

There are official lists of native and naturalized Korean plant species, including (1) the Database of National Species List of Korea (Park et al., 2020a), (2) the Standard List of Korean plant species (http://www.nature.go.kr/kpni), and (3) The Northeastern Asia Biodiversity Institute’s List of Korean Vascular Plants. All three lists suggest approximately 4,500 native and naturalized plant species in Korea, also presenting utility as a filter to select published plant genome sequences to investigate the current status of plant genomes of native and naturalized Korean plant species. We used the Northeastern Asia Biodiversity Institute’s List of Korean Vascular Plants, selecting 85 plant genomes originating from 69 taxa as Korean angiosperm species genomes from the Plant Genome Database (https://www.plantgenome.info/), which contains available plant whole genome-sequences (Park et al., 2021a) (Table 1). The difference between the numbers of plant genome sequences and the taxa indicates that multiple genomes of some plant taxa were sequenced, making this a good resource to understand intraspecific variations at the level of the genome. We excluded more than 1,700 A. thaliana genomes (Ossowski et al., 2008; Ashelford et al., 2011; Cao et al., 2011; Gan et al., 2011; Long et al., 2013; Schmitz et al., 2013; The 1001 Genomes Consortium, 2016; Zou et al., 2017) due to the extremely large number of genomes in this case.

Despite the time gap between the releases of genome sequences and the corresponding publication dates, only 15.29% (13 out of 85 genomes) of genomes do not have any publication. Moreover, five species, Spirodela polyrhiza (L.) Schleid., Diospyros lotus L., Glycine soja Sieb. and Zucc., Castanea mollissima Blume, and Boehmeria nivea (L.) Gaudich., contained three genomes while six species, Panax ginseng C. A. Mey., Corylus heterophylla Fisch. ex Trautv., Setaria viridis (L.) P. Beauv., Typha latifolia L., Pyrus pyrifolia (Burm. f.) Nakai., and Ziziphus jujuba Mill., covered two genomes (Table 1), making them good candidates for understanding intraspecific variations at the genome-wide level. Remarkably, only two genome publications with accessible genome sequences, Gastrodia elata Blume and Codonopsis lanceolata (Siebold. & Zucc.) Trautv., described the whole genome of Korean angiosperm species (Table 1), indicating that most genomes filtered by the Korean angiosperm species list described in this paper were sequenced based on samples outside of Korea. As the importance of biological resources increases, as exemplified in the Nagoya Protocol (Buck and Hamilton, 2011), additional efforts to obtain whole-genome sequences of these species using the samples isolated in Korea and to prepare assembled sequences (i.e., unfortunately, while the G. soja genome was sequenced in Korea (Kim et al., 2010), no assembled sequence is available.) are required to maximize the benefits of the low sequencing costs and feasible bioinformatic analyses.

Sixty-nine taxa were classified into 17 orders and 30 families. Rosales covering four families (Moraceae, Rosaceae, Rhamnaceae, and Utricaceae) contained the largest number of genomes, and Poales covered the second largest from Poaceae to Typhaceae, while Boraginales, Caryophyllales, Cucurbitales, Solanales, and Vitales had only one genome (Fig. 3). At the family level, Rosaceae (10 taxa), Brassicaceae (7 taxa), Fabaceae (7 taxa), and Poaceae (7 taxa) contained a large number of genomes among the 30 families (Fig. 3). This taxonomical bias was expected due to various technical factors associated with genome sequencing projects, including the genome size and ploidy. Most taxa are economically important species. Based on current sequencing technologies, especially TGS technologies, many of these problems have already been overcome; e.g., the hexaploid large genome of wheat (Triticum aestivum L.) was sequenced and successfully assembled at the pseudo-chromosomal level (International Wheat Genome Sequencing Consortium, 2018). Rosaceae contained ten genomes originating from five genera, specifically Prunus, Rosa, Fragaria, Malus, and Pyrus and Poaceae, had nine genomes from the six genera, displaying large taxonomic coverage (Fig. 3, Table 1). These genomes are good candidates for understanding the genomic features of the aforementioned families.

Fig. 3.

Taxonomical distribution of 69 native and naturalized Korean plant taxa containing whole-genome sequences: (A) graph displaying the order-level distribution, and (B) graph showing the family-level distribution. Dotted lines represent the relationship between families and orders.

GENOMIC STATISTICS OF 85 NATIVE AND NATURALIZED KOREAN PLANT GENOMES

The genome length and GC ratio of 85 native and naturalized Korean plant genomes were investigated, indicating average genome lengths of Araliaceae, Caryophyllaceae, and Orchidaceae of 3.20, 2.60, and 2.03 Gbp, respectively; the standard deviation of the Orchidaceae genome length was largest at 1.70 Gbp, while that of the Salicaceae genome is smallest at 16.79 Mbp (Fig. 4). Three genomes from Orchidaceae showed that two of the three genomes were around 1 Gbp; while one was 3 Gbp in length, with Salicaceae covering two genomes from the same genus, Populus. The trend of genome size variations along with the families is congruent with the findings of earlier work (Šmarda et al., 2014). In addition, the standard deviation of the GC ratio in Zosteraceae is extremely large, 4.05%, despite the fact that the two genomes are from the same genus, Zostera (Table 1). Araceae, Fabaceae, and Poaceae displayed that the standard deviation of the GC ratio ranges from 1.18 to 1.25% (Fig. 4), which is a large value in comparison to the other families. These variations in GC ratio are similar to those in a previous study that investigated variations of the GC ratio of the whole genome in a monocot species (Šmarda et al., 2014). The number of genomes in each family is small to present a corresponding trend, therefore they provide a glimpse of family-specific genomic features through these numbers as an indicator. This indicates that further genomic studies of Korean plants are necessary.

Fig. 4.

Family-level genomic properties, total length and GC ratio: the X-axis shows families containing at least one whole genome used in this paper. Bars show the average genome length with the error bars of the standard deviation. The line represents the average GC ratio of genomes with the error bars of the standard deviation.

UTILIZATION OF KOREAN ANGIOSPERM GENOME SEQUENCES

More than 1,000 plant whole genomes have been sequenced, meaning that we can investigate their characteristics in detail. However, grants and proper human resources are still required for us to present the potential or direct economic value of this resource. Genomics-assisted breeding, a good example of the utilization of whole genomes, can be conducted based on genome-wide association studies to target useful phenotypes for breeding (Ahmar et al., 2020, 2021). To shorten the breeding time and increase the efficiency of the process, genomic editing is a viable upcoming strategy, with modifications to genetic elements to achieve helpful characteristics for humans using CRISPR-associated protein 9 (Lee et al., 2019). Legal regulations pertaining to genetically modified organisms, considered a main suppression factor, have become positive, accepting genome-edited plants in comparison to genetically modified organisms (Sprink et al., 2022). This development will promote the potential usage of plant whole-genome sequences because the techniques mentioned above commonly require whole genomes.

Native plant resources have been utilized to develop a range of useful products, including medicines over many years due to effective compounds such as aspirin, an acetyl salicylic acid from willow bark (Norn et al., 2009), and paclitaxel extracted from the bark of Taxus brevifolia Nutt. (Bose et al., 2020). In addition, various natural product medicines have also been developed based on plant extracts (Ngo et al., 2013) as well as traditional medicines, which have been utilized for several thousand years (Ansari and Inamdar, 2010), reflecting the commercial usage of plant resources. Whole-genome sequences can be analyzed to predict useful phytocompounds because they contain all enzymes involved in biochemical synthesis theoretically (Kang et al., 2020; Park et al., 2020b), suggesting another useful feature of Korean native plant genomes.

FURTHER DIRECTIONS FOR KOREAN ANGIOSPERM GENOME SEQUENCES

Currently, more than a hundred plant whole genomes have been sequenced per year, a rate much faster than that of ten years ago, when NGS technologies were merely utilized for the de novo assembly of plant genomes. Hence, more Korean angiosperm genomes will also be available from our own genome projects and genome projects conducted outside of Korea. We can consider two main strategies for a database for archive and utilization of Korean angiosperm genomes. First, to expand the coverage of Korean angiosperm genomes, additional Korean angiosperm genomes, especially endemic species which can be utilized commercially or which may be valuable in research, can be sequenced. Second, additional individuals or populations of Korean angiosperm species can be sequenced to understand genome-wide intraspecific variations (Slavov et al., 2012; The 3,000 Rice Genomes Project, 2014; Gulyaev et al., 2022) as well as functional gene families (Kim et al., 2021a, 2021b), as useful phenotypes of plant resources show differences in an intraspecific manner (Moore et al., 2014; Aspinwall et al., 2015; Ren et al., 2020). In addition, all of these genomes can be managed under the environment of a standardized integrated platform to analyze them further, such as the web-based genomic analysis platform Galaxy (Giardine et al., 2005; Blankenberg et al., 2010) or the Genome Information System (GeIS; https://geis.infoboss.co.kr/), which have been utilized in various genomics studies (Lee et al., 2020; Park et al., 2020c, 2021b).

Acknowledgements

This study was carried out with the support of the InfoBoss Research Grant (IBG-0042).

Notes

CONFLICTS OF INTEREST

The authors declare that there are no conflicts of interest.

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Table 1.

List of plant whole genome sequences of Korean angiosperms.

No.	Order	Family	Species	Cultivar/Strain	Method	Genome size (bp)	No. of scaffolds	N50 (bp)	GC ratio (%)	No. of genes	Reference
1	Alismatales	Araceae	Lemna minor	-	HiSeq MiSeq	763,364,415	6,868	335,126	44.81	N/A	Van Hoeck et al. (2015)
2	Alismatales	Araceae	Spirodela polyrhiza	7498	454 BAC-end	132,009,443	207	5,765,642	42.45	N/A	Wang et al. (2014)
3	Alismatales	Araceae	Spirodela polyrhiza	9509	HiSeq Irys	136,591,703	20	7,641,483	42.30	N/A	Michael et al. (2017)
4	Alismatales	Araceae	Spirodela polyrhiza	Sp9504	N/A	137,175,874	16,051	14,533	42.21	N/A	Unpublished
5	Alismatales	Zosteraceae	Zostera marina	-	HiSeq	203,914,448	2,228	485,578	38.34	20,450	Olsen et al. (2016)
6	Alismatales	Zosteraceae	Zoysia japonica	Nagirizaki	HiSeq	334,384,427	11,786	2,370,062	44.08	N/A	Tanaka et al. (2016)
7	Apiales	Apiaceae	Centella asiatica	BB-174	10x Hi-C	430,216,894	8,739	50,798,654	34.17	N/A	Pootakham et al. (2021)
8	Apiales	Apiaceae	Oenanthe javanica	-	HiSeq	1,650,714,995	150,335	32,514	35.44	N/A	Liu et al. (2021a)
9	Apiales	Araliaceae	Panax ginseng	-	HiSeq	3,414,349,854	83,074	108,708	34.94	N/A	Xu et al. (2017)
10	Apiales	Araliaceae	Panax ginseng	-	HiSeq	2,984,993,682	9,845	3,641,815	34.84	59,352	Kim et al. (2018)
11	Asparagales	Orchidaceae	Gastrodia elata	EJP_2020-GE1012	HiSeq PacBio Hi-C	1,046,143,939	514	50,595,616	34.27	N/A	Bae et al. (2022)
12	Asparagales	Orchidaceae	Gastrodia elata f. glauca	-	HiSeq	1,060,984,162	3,768	4,911,943	34.52	N/A	Yuan et al. (2018)
13	Asparagales	Orchidaceae	Cymbidium goeringii	-	HiSeq PacBio Hi-C	3,990,519,457	19,377	178,198,413	33.77	29,556	Chung et al. (2021)
14	Asterales	Asteraceae	Artemisia annua	-	HiSeq 454 PacBio	1,792,856,094	39,400	104,891	35.34	N/A	Shen et al. (2018)
15	Asterales	Campanulaceae	Codonopsis lanceolata	NIHHS 239928	Nanopore HiSeq	1,347,489,827	22,630	82,893	37.21	N/A	Jang et al. (2023)
16	Asterales	Campanulaceae	Codonopsis pilosula	-	N/A	937,709,907	1,154	2,556,440	37.13	N/A	Unpublished
17	Boraginales	Boraginaceae	Lithospermum erythrorhizon	-	Nanopore HiSeq	366,684,367	2,451	315,765	35.15	32,360	Auber et al. (2020)
18	Brassicales	Brassicaceae	Arabidopsis lyrata	MN47	Sanger	206,667,935	695	24,464,547	36.08	32,550	Hu et al. (2011)
19	Brassicales	Brassicaceae	Arabidopsis thaliana	Col-0	Sanger	119,145,879	5	23,459,830	36.03	48,113	Kaul et al. (2000)
20	Brassicales	Brassicaceae	Arabis glabra	-	N/A	171,129,789	250	5,712,653	36.01	N/A	Unpublished
21	Brassicales	Brassicaceae	Capsella bursa-pastoris	-	HiSeq MiSeq	268,430,517	8,186	627,605	35.74	52,528	Kasianov et al. (2017)
22	Brassicales	Brassicaceae	Erysimum cheiranthoides	-	HiSeq PacBio Hi-C	177,180,559	223	22,409,365	36.29	N/A	Züst et al. (2020)
23	Brassicales	Brassicaceae	Isatis tinctoria	-	N/A	756,237,117	37,877	85,498	36.89	116,152	Unpublished
24	Brassicales	Brassicaceae	Rorippa islandica	-	N/A	390,742,222	430	3,103,162	35.67	65,406	Unpublished
25	Caryophyllales	Caryophyllaceae	Silene noctiflora	OPL-1.1	N/A	2,598,026,552	79,767	59,004	37.95	N/A	Unpublished
26	Cucurbitales	Cucurbitaceae	Gynostemma pentaphyllum	JGL-2020	HiSeq BGISeq PacBio Hi-C	582,948,444	578	50,780,587	32.86	N/A	Huang et al. (2021)
27	Ericales	Actinidiaceae	Actinidia rufa	Fuchu	HiSeq PacBio	677,239,177	501	15,941,708	35.44	52,342	Tahir et al. (2022)
28	Ericales	Ebenaceae	Diospyros lotus	Kunsenshi	N/A	945,758,782	8,975	653,513	36.35	N/A	Unpublished
29	Ericales	Ebenaceae	Diospyros lotus	W01	N/A	617,726,390	142	40,720,603	36.52	N/A	Unpublished
30	Ericales	Ebenaceae	Diospyros lotus	Yz01	N/A	630,098,508	42	42,671,757	36.57	N/A	Unpublished
31	Fabales	Fabaceae	Amphicarpaea edgeworthii	AE-2020	BGISeq Nanopore	299,059,313	24	27,224,559	32.06	N/A	Liu et al. (2021b)
32	Fabales	Fabaceae	Glycine soja	F	N/A	975,918,537	320	48,777,390	34.78	57,501	Unpublished
33	Fabales	Fabaceae	Glycine soja	USDA:GRIN:PI 483463	HiSeq PacBio Bionano	985,259,865	306	48,820,272	34.94	N/A	Valliyodan et al. (2019)
34	Fabales	Fabaceae	Glycine soja	W05	HiSeq PacBio Hi-C	863,568,428	33,170	404,776	33.56	50,337	Xie et al. (2019)
35	Fabales	Fabaceae	Medicago ruthenica	Xinghe	HiSeq PacBio Hi-C	904,130,090	650	99,386,155	35.89	N/A	Yin et al. (2021)
36	Fabales	Fabaceae	Vicia sativa	KSR5	HiSeq PacBio	1,541,180,487	54,083	90,105	34.96	N/A	Shirasawa et al. (2021b)
37	Fabales	Fabaceae	Vigna minima	-	HiSeq PacBio	486,496,346	2,940	25,346,430	34.19	N/A	Naito et al. (2022)
38	Fagales	Betulaceae	Betula pendula	-	HiSeq SOLiD	435,914,794	5,644	239,696	35.74	86,599	Salojärvi et al. (2017)
39	Fagales	Betulaceae	Corylus heterophylla	CHET03		346,499,040	381	2,025,119	35.99	N/A	Unpublished
40	Fagales	Betulaceae	Corylus heterophylla	R026	Nanopore Hi-C	370,750,808	951	31,328,411	35.84	N/A	Zhao et al. (2021)
41	Fagales	Fagaceae	Castanea crenata	Ginyose	HiSeq PacBio	721,168,657	781	1,595,543	35.14	N/A	Shirasawa et al. (2021c)
42	Fagales	Fagaceae	Castanea mollissima	N11-1	HiSeq PacBio Hi-C	833,240,550	112	57,343,431	35.11	N/A	Wang et al. (2020)
43	Fagales	Fagaceae	Castanea mollissima	Vanuxem	454 MiSeq	725,180,808	14,110	101,575	35.06	34,314	Staton et al. (2020)
44	Fagales	Fagaceae	Castanea mollissima	Hubei	HiSeq PacBio	785,529,252	2,707	944,461	35.21	36,479	Xing et al. (2019)
45	Fagales	Fagaceae	Quercus mongolica	Qm_2020SYAU	HiSeq PacBio Hi-C	809,993,317	321	66,735,633	35.84	N/A	Ai et al. (2022)
46	Fagales	Juglandaceae	Juglans mandshurica	-	HiSeq	558,070,702	13,809	496,923	36.26	N/A	Bai et al. (2018)
47	Lamiales	Lamiaceae	Perilla citriodora	-	N/A	618,797,171	29,924	2,413,193	35.38	155,867	Unpublished
48	Lamiales	Oleaceae	Fraxinus mandshurica	-	HiSeq MiSeq 454	830,473,688	297,505	30,144	34.96	N/A	Sollars et al. (2017)
49	Lamiales	Oleaceae	Fraxinus sieboldiana	-	HiSeq MiSeq 454	744,777,403	709,960	1,987	36.21	N/A	Sollars et al. (2017)
50	Lamiales	Orobanchaceae	Phtheirospermum japonicum	Okayama	N/A	1,226,606,249	10,559	1,109,341	36.03	30,299	Unpublished
51	Malpighiales	Euphorbiaceae	Euphorbia esula	-	N/A	1,124,886,465	1,633,094	1,035	34.80	N/A	Unpublished
52	Malpighiales	Salicaceae	Populus davidiana	NFU_1	N/A	417,659,603	1,565	562,472	33.56	N/A	Unpublished
53	Malpighiales	Salicaceae	Populus simonii	-	HiSeq PacBio	441,407,051	369	19,598,675	33.65	N/A	Wu et al. (2020)
54	Poales	Poaceae	Brachypodium sylvaticum	-	N/A	358,283,154	629	38,764,466	46.38	50,263	Unpublished
55	Poales	Poaceae	Echinochloa crus-galli	STB08	HiSeq PacBio	1,486,609,408	4,534	1,802,240	45.70	N/A	Guo et al. (2017)
56	Poales	Poaceae	Eleusine indica	HZ-2018	HiSeq	492,270,386	24,072	233,459	44.42	N/A	Zhang et al. (2019)
57	Poales	Poaceae	Miscanthus sacchariflorus	-	HiSeq	2,074,815,175	105,321	37,711	45.94	N/A	De Vega et al. (2021)
58	Poales	Poaceae	Miscanthus sinensis	-	HiSeq Hi-C	2,079,430,866	14,431	88,510,541	45.77	89,486	Mitros et al. (2020)
59	Poales	Poaceae	Setaria viridis	A10	HiSeq pacBio	395,731,502	14	46,702,114	46.17	52,459	Mamidi et al. (2020)
60	Poales	Poaceae	Setaria viridis	ME034V	HiSeq Nanopore	397,031,521	9	46,382,547	45.99	N/A	Thielen et al. (2020)
61	Poales	Poaceae	Themeda triandra	sf006	N/A	889,201,528	3,179	600,859	46.24	N/A	Unpublished
62	Poales	Poaceae	Zizania latifolia	HSD2	HiSeq	603,989,347	4,522	604,864	42.72	N/A	Guo et al. (2015)
63	Poales	Typhaceae	Typha latifolia	L0001	N/A	214,326,387	81	14,472,745	37.76	N/A	Unpublished
64	Poales	Typhaceae	Typha latifolia	SDW-2020	HiSeq PacBio	287,194,721	1,158	8,705,712	38.07	N/A	Widanagama et al. (2022)
65	Rosales	Moraceae	Ficus erecta	-	HiSeq PacBio Genetic map	595,834,738	2,455	697,200	34.32	111,921	Shirasawa et al. (2020)
66	Rosales	Rosaceae	Fragaria nipponica	-	454 HiSeq	206,414,979	215,024	1,275	38.44	87,803	Hirakawa et al. (2014)
67	Rosales	Rosaceae	Fragaria orientalis	-	454 HiSeq	214,184,046	323,163	722	38.11	99,674	Hirakawa et al. (2014)
68	Rosales	Rosaceae	Malus baccata	-	HiSeq	703,023,564	47,474	743,357	38.13	45,900	Chen et al. (2019)
69	Rosales	Rosaceae	Prunus yedoensis var. nudiflora*	-	HiSeq PacBio Fosmid-end	319,209,792	4,016	145,140	37.65	41,294	Baek et al. (2018)
70	Rosales	Rosaceae	Prunus yeonesis	-	HiSeq PacBio	690,105,700	4,571	918,183	37.93	N/A	Shirasawa et al. (2019)
71	Rosales	Rosaceae	Prunus davidiana	ST	HiSeq PacBio Hi-C	243,913,910	127	28,110,464	37.55	N/A	Tan et al. (2021)
72	Rosales	Rosaceae	Pyrus pyrifolia	Nijisseiki	BGISeq PacBio	503,888,133	114	7,676,629	37.34	N/A	Shirasawa et al. (2021a)
73	Rosales	Rosaceae	Pyrus pyrifolia	Cuiguan	HiSeq PacBio	541,340,367	428	27,968,327	37.36	42,559	Gao et al. (2021)
74	Rosales	Rosaceae	Rosa lucieae	-	N/A	786,105,075	500,476	10,695	38.73	N/A	Unpublished
75	Rosales	Rosaceae	Rosa multiflora	-	HiSeq MiSeq	739,637,845	83,189	90,830	38.91	67,380	Nakamura et al. (2018)
76	Rosales	Rosaceae	Rosa rugosa	-	PacBio 10x Hi-C	401,223,225	43	61,014,187	39.31	39,704	Chen et al. (2021)
77	Rosales	Rhamnaceae	Ziziphus jujuba	Dongzao	HiSeq BAC	437,753,511	4,789	25,259,912	33.40	37,526	Liu et al. (2014)
78	Rosales	Rhamnaceae	Ziziphus jujuba	Junzao	HiSeq	362,583,438	47	27,412,306	32.95	N/A	Huang et al. (2016)
79	Rosales	Rhamnaceae	Ziziphus jujuba var. spinosa	AT0	HiSeq PacBio Hi-C	405,636,987	538	30,278,369	33.07	24,146	Shen et al. (2021)
80	Rosales	Urticaceae	Boehmeria nivea	-		344,616,830	12,775	1,094,501	35.25	N/A	Unpublished
81	Rosales	Urticaceae	Boehmeria nivea	ZZ1	HiSeq	316,026,324	330	17,838,734	35.20	N/A	Liu et al. (2018)
82	Rosales	Urticaceae	Boehmeria nivea	Zhongsizhu	HiSeq Nanopore PacBio	266,599,076	154,955	48,874	36.94	N/A	Wang et al. (2021a)
83	Rosales	Urticaceae	Boehmeria nivea var. tenacissima	-	HiSeq Nanopore PacBio	270,213,153	135	19,552,154	35.19	N/A	Wang et al. (2021a)
84	Solanales	Convolvulaceae	Cuscuta australis		HiSeq PacBio	262,630,465	218	3,625,894	36.40	18,157	Sun et al. (2018)
85	Vitales	Vitaceae	Vitis amurensis	IBCAS1988	HiSeq PacBio Hi-C Bionano	603,559,200	3,040	26,085,413	34.36	N/A	Wang et al. (2021b)

Asterisks indicate Korean endemic species (Chung et al., 2023).

N/A, not available.