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. 2018 Jun 5;14:43. doi: 10.1186/s13007-018-0300-0

Genome skimming herbarium specimens for DNA barcoding and phylogenomics

Chun-Xia Zeng 1,#, Peter M Hollingsworth 2,#, Jing Yang 1, Zheng-Shan He 1, Zhi-Rong Zhang 1, De-Zhu Li 1,✉, Jun-Bo Yang 1,✉
PMCID: PMC5987614  PMID: 29928291

Abstract

Background

The world’s herbaria contain millions of specimens, collected and named by thousands of researchers, over hundreds of years. However, this treasure has remained largely inaccessible to genetic studies, because of both generally limited success of DNA extraction and the challenges associated with PCR-amplifying highly degraded DNA. In today’s next-generation sequencing world, opportunities and prospects for historical DNA have changed dramatically, as most NGS methods are actually designed for taking short fragmented DNA molecules as templates.

Results

As a practical test of routine recovery of rDNA and plastid genome sequences from herbarium specimens, we sequenced 25 herbarium specimens up to 80 years old from 16 different Angiosperm families. Paired-end reads were generated, yielding successful plastid genome assemblies for 23 species and nuclear rDNAs for 24 species, respectively. These data showed that genome skimming can be used to generate genomic information from herbarium specimens as old as 80 years and using as little as 500 pg of degraded starting DNA.

Conclusions

The routine plastome sequencing from herbarium specimens is feasible and cost-effective (compare with Sanger sequencing or plastome-enrichment approaches), and can be performed with limited sample destruction.

Keywords: Degraded DNA, Herbarium specimens, Genome skimming, Plastid genome, rDNA, DNA barcoding

Background

Herbaria are collections of preserved plant specimens stored for scientific study. There are approximately 3400 herbaria in the world, containing around 350 million specimens, collected over the past 400 years (http://sciweb.nybg.org/science2/indexHerbariorum.asp). These collections cover most of the world’s plant species, including many rare and endangered local endemics, and species collected from places that are currently expensive or difficult to access [1]. The recovery of DNA from this vast resource of already collected expertly-verified herbarium specimens represent a highly efficient way of building a DNA-based identification resource of the world’s plant species (DNA barcoding) and increasing knowledge of phylogenetic relationships.

The ‘unlocking’ of preserved natural history specimens for DNA barcoding/species discrimination is of particular relevance. In the first decade of DNA barcoding, it became clear that obtaining material from expertly verified is a key rate-limiting step in the construction of a global DNA reference library [2]. The millions of samples that are required for this endeavor, each needing corresponding voucher specimens and meta-data, create a strong impetus for making best-use of previously collected material.

DNA degradation in herbarium samples followed by subsequent diffusion from the sample creates challenges for DNA recovery [3]. In addition, different preservation methods can negatively affect the ability of extract, amplify and sequence DNA [4–6]. PCR amplification of historical DNA is, therefore, generally restricted to short amplicons (< 200 bp) and is further vulnerable to contamination by recent DNA and PCR products from the study species. The cumulative damage to the DNA can also cause incorrect bases to be inserted during enzymatic amplification. The main sources for these alterations are single nucleotide misincorporations [7, 8]. Above all, PCR-based Sanger sequencing by using herbarium samples to generate standard DNA barcodes can be challenging. A recent large-scale study by Kuzmina et al. 2017 [9] examined 20,816 specimens representing 5076 of 5190 vascular plant species in Canada. Kuzmina et al. found that specimen age and method of preservation had significant effects on sequence recovery for all barcode markers. However, massively-parallel short-read Next-generation sequencing (NGS) protocols have the potential to greatly increase the success of herbarium sequencing projects, as many new sequencing approaches do not rely on large, intact DNA templates and instead are well-suited for sequencing low concentrations of short (100-400 bp) fragmented molecules [3, 10].

Straub et al. [11], described how “genome skimming”, involving a shallow-pass genome sequence using NGS, could recover highly repetitive genome regions such as rDNA or organelle genomes, and yield highly useful sequence data at relatively low sequence depth, and these regions include the usual suite of DNA barcoding markers [12, 13]. The genome skimming approach using NGS has been used to recover plastid DNA and rDNA sequences from 146 herbarium specimens [14], to produce the entire nuclear genome of a 43-year-old Arabidopsis thaliana herbarium specimen [15], the complete plastome, the mitogenome, nuclear ribosomal DNA clusters, and partial sequences of low-copy genes from an herbarium specimen of an extinct species of Hesperelaea [16, 17], and the complete plastome, nuclear ribosomal DNA clusters, and partial sequences of low-copy genes from three grass herbarium specimens [18].

However, sequencing small, historical specimens may be especially challenging if a specimens is unique, or nearly so, with no alternative specimens available for study should the first specimen fail. Methods used to extract and prepare DNA for sequencing must both be more or less guaranteed to work, and, in many cases, allow for preservation of DNA for future study [19]. In recent studies that report successfully sequencing of historical specimens from 1 ng to 1 μg of input DNA (for example, up to 1 μg in Bakker et al. [14]; ∽ 600 ng in Staats et al. [15]; 33 ng in Zadane et al. [17]; 8.25–537 ng in Kanda et al. [20]; 5.8–200 ng in Blaimer et al. [21]; less than 10 ng in Besnard et al. [18]; 1–10 ng in Sproul and Maddison [19]). But a number of studies also report abandoning a subset of specimens for which too little input DNA was available (i.e. below 10 ng in Kanda et al. [20]; below 5 ng in Blaimer et al. [21]). To better understand ideal approaches of sample preparation for specimens with minimal DNA, we intentionally limited DNA input to 500 pg per specimen.

In this paper we provide a further practical test of the genome skimming methodology applied to herbarium specimens. As part of the China Barcode of Life project, and our wider phylogenomic studies, our aim was to assess whether the success reported in these early genome skimming studies could be repeated in other laboratories.

We evaluated the success and failure rates of rDNA and plastid genome sequencing from genome skims of 25 different species from herbarium specimens, and explored the impacts of parameters such as amount of input DNA and PCR cycle numbers.

Methods

Specimen sampling

25 herbarium specimens were selected from 16 Angiosperm families covering 22 genera, with specimen ages up to 80 years old. All 25 species were taken from the specimens housed in the Herbarium of the Institute of Botany, Chinese Academy of Sciences (KUN). The samples were selected to represent the major clades of APG III system (Table 1).

Table 1.

List of the specimen materials, DNA yields used in our study

Sample ID Species Family Collection Age ng/ul Volume (ul) DNA yield (ng)
01 Manglietia fordiana Magnoliaceae 19780402 39 0.894 36 32.184
02 Manglietia fordiana Magnoliaceae 19541027 63 2.35 37 86.95
03 Schisandra henryi Schisandraceae 19821108 35 1.87 33 61.71
04 Schisandra henryi Schisandraceae 19840528 33 0.909 33 29.997
05 Phoebe neurantha Lauraceae 1938 79 0.507 36 18.252
06 Cinnamomum bodinieri Lauraceae 1960 57 2.26 36 81.36
08 Holboellia latifolia Lardizabalaceae 1982 35 1.29 34 43.86
09 Chloranthus erectus Chloranthaceae 1973 44 4.18 36 150.48
10 Sarcandra glabra Chloranthaceae 1988 29 4.35 31.5 137.025
11 Meconopsis racemosa Papaveraceae 1976 41 4.35 22 95.7
12 Macleaya microcarpa Papaveraceae 1986 31 1.97 35.5 69.935
13 Hodgsonia macrocarpa Cucurbitaceae 1982 35 2.18 34 74.12
14 Malus yunnanensis Rosaceae 1939 78 0.834 35 29.19
15 Elaeagnus loureirii Elaeagnaceae 1993 24 9.75 34 331.5
16 Rhododendron rex subsp. fictolacteum Ericaceae 1979 38 8.15 20.5 167.075
17 Swertia bimaculata Gentianaceae 19840823 33 1.67 35 58.45
18 Primula sinopurpurea Primulaceae 19400907 77 0.974 32 31.168
19 Paederia scandens Araceae 19550331 62 0.344 34 11.696
20 Colocasia esculenta Araceae 19741001 43 1.46 36 52.56
21 Pholidota chinensis Orchidaceae 1959 58 0.107 34 3.638
22 Otochilus porrectus Orchidaceae 1990 27 0.344 35 12.04
23 Indosasa sinica Poaceae 2007 10 1.65 35 57.75
24 Camellia gymnogyna Theaceae 19340617 83 0.417 36 15.012
25 Camellia sinensis var. assamica Theaceae 2002 15 4.03 23 92.69
26 Panicum incomtum Poaceae 20001017 17 1.63 36 58.68
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All vouchers are deposited in the herbarium of the Kunming Institute of Botany (KUN)

DNA extraction

Approximately 1 cm2 sections of leaf or 20 mg of leaf tissue were used for each DNA extraction. Genomic DNA was extracted using Tiangen DNAsecure Plant Kit (DP320). Yield and integrity (size distribution) of genomic DNA extracts were quantified by fluorometric quantification on the Qubit (Invitrogen, Carlsbad, California, USA) using the dsDNA HS kit, as well as by visual assessment on a 1% agarose gel.

Library preparation

All samples were subsequently built into blunt-end DNA libraries in the laboratories using the NEBNext Ultra II DNA library Prep kit for Illumina (New England BIolabs) which has been optimized for as little as 5 ng starting DNA and Illumina-specific adapters [22]. The library protocol was performed as per the manufacturer’s instructions with four modifications: (i) 500 pg of input DNA was selected to accommodate low starting DNA quantities, (ii) DNA was not fragmented by sonication because the DNA was highly degraded; (iii) The NEBNext library was generated without any size selection; (iv) DNA libraries were then amplified in an indexing PCR, which barcoded each library and discriminated each sample. Five PCR cycles was suggested by the manufacturer’s instruction for 5 ng of input DNA. As only 500 pg of starting DNA was used, we tested use of increasing numbers of PCR cycles (namely × 6, × 8, × 10, × 12, × 14 PCR cycles). Concentration and size profiles of the final indexed libraries (125 libraries, representing 25 specimens at 5 different numbers of PCR cycles) were assessed on a Bioanalyzer 2100 using a high sensitivity DNA chip.

Library pooling

The final indexed libraries were then pooled (33 or 34 samples per lane) in equimolar ratios and sequenced on three lanes on an Illumina XTen sequencing system (Illumina Inc.) using paired and chemistry at the Cloud health Medical Group Ltd.

Analyses

Successfully sequenced samples were assembled into chloroplast genomes and nuclear rDNAs. Here the rDNAs comprise the complete sequence of 26S, 18S, and 5.8S and internal transcribed spacers (ITS1 and ITS2). We did not assemble the internal gene spacer (IGS) because of the complexity of this region which is rich in duplications and inversions.

The raw sequence reads were filtered for primer/adaptor sequences and low-quality reads with the NGS QC Toolkit [23]. The cut-off value for percentage of read length was 80, and that for PHRED quality score was 30. Then the filtered high-quality pair-end reads were assembled into contigs with Spades 3.0 [24]. Next, we identified highly similar genome sequences using the Basic Local Alignment Search Tool (BLAST: http://blast.ncbi.nlm.gov/). The procedures and parameters for setting the sequence quality control, de novo assembly, and blast search were followed as in Yang et al. [25]. Next, we determined the proper orders of the aligned contigs using the highly similar genome sequences identified in the BLAST search as references. At this point, the target contigs were assembled into complete plastid genomes and nuclear rDNAs.

Annotation of the plastomes was performed using the plastid genome annotation package DOGMA [26] (http://dogma.ccbb.utexas.edu/). Start and stop codons of protein-coding genes, as well as intron/exon positions, were manually adjusted. The online tRNAscan-SE service [27] was used to further determine tRNA genes. The final complete plastomes and rDNAs were deposited into GenBank (Accession numbers: MH394344-MH394431; MH270450-MH270494).

Fungi or other plants may be co-isolated during the DNA extraction process resulting in DNA contamination [1]. This is particularly important where starting DNA concentrations are extremely low. We thus sub-sampled our data to check for contamination. To check for contamination in the plastid DNA sequences, for each species we extracted its rbcL sequence and blasted it against GenBank to check that it grouped with related species. BLAST1 (implemented in the BLAST program, version 2.2.17) was used to search the reference database for each query sequence with an E value < 1 × 10−5. Likewise, to check for plant and fungal contamination in the rDNA sequences, we took the final assembled ITS sequences (or partial ITS sequences where complete ITS was not recovered) and blasted the sequences against the NCBI database to check that it grouped with related species.

Results

All 25 species yielded amounts of DNA suitable for library preparation and further processing. Total yields varied between 3 ng and 400 ng from on average 20 mg of dried leaf tissue, usually the equivalent of 1 cm2 of leaf tissue (Table 1). We found a negative correlation between specimen age and DNA yield (Fig. 1).

Fig. 1.

Fig. 1

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DNA yield against specimen age

We successfully enriched and sequenced DNA libraries constructed from herbarium material. Despite only 500 pg of input DNA, good quality libraries were produced from 100 of 125 samples (25 species, with × 8, × 10, × 12, × 14 PCR cycles). The concentration of the final indexed libraries based on six PCR cycles per species was too low to be further sequenced. Between 15,877,478 and 44,724,436 high-quality paired-end reads were produced, with the total number of bases ranging from 2,381,621,700 bp (2.38 giga base pairs, Gbp) to 6,708,665,400 bp (6.71 Gbp) (Table 2). These were then assembled into contigs, and using a blast search into plastid genomes and rDNA arrays.

Table 2.

Assembly statistics of plastid genome for all specimens used in this study

Sample ID PCR cycles Species Family Total sequences Raw data (gb) #contigs Total assembly length (bp) Completed GenBank accession number
01D ×8 Manglietia fordiana Magnoliaceae 22404632 3.36 9 158993 1059 bp gap MH394393
01E ×10 Manglietia fordiana Magnoliaceae 25869654 3.88 32 159759 349 bp gap MH394394
01A ×12 Manglietia fordiana Magnoliaceae 35201972 5.28 14 158241 1840 bp gap MH394391
01B ×14 Manglietia fordiana Magnoliaceae 30007234 4.5 14 158221 1840 bp gap MH394392
02D ×8 Manglietia fordiana Magnoliaceae 22829038 3.42 8 161497 1040 bp gap MH394397
02E ×10 Manglietia fordiana Magnoliaceae 32497068 4.87 21 160113 Y MH394398
02A ×12 Manglietia fordiana Magnoliaceae 29637182 4.45 12 158315 1802 bp gap MH394395
02B ×14 Manglietia fordiana Magnoliaceae 31089730 4.66 22 160113 Y MH394396
03D ×8 Schisandra henryi Schisandraceae 29691984 4.45 5 145963 94 bp gap MH394365
03E ×10 Schisandra henryi Schisandraceae 25141160 3.77 4 145616 54 bp gap MH394366
03A ×12 Schisandra henryi Schisandraceae 32511344 4.88 11 146031 18 bp gap MH394363
03B ×14 Schisandra henryi Schisandraceae 29856636 4.48 9 145993 63 bp gap MH394364
04D ×8 Schisandra henryi Schisandraceae 24039822 3.61 4 146212 53 bp gap MH394369
04E ×10 Schisandra henryi Schisandraceae 23870902 3.58 4 146243 53 bp gap MH394370
04A ×12 Schisandra henryi Schisandraceae 33190158 4.98 15 146218 63 bp gap MH394367
04B ×14 Schisandra henryi Schisandraceae 30498044 4.57 6 145893 45 bp gap MH394368
05D ×8 Phoebe neurantha Lauraceae 29040850 4.36 11 152782 Y MH394354
05E ×10 Phoebe neurantha Lauraceae 27831254 4.17 15 152782 Y MH394355
05A ×12 Phoebe neurantha Lauraceae 44724436 6.71 17 152781 1 bp gap MH394352
05B ×14 Phoebe neurantha Lauraceae 35264634 5.29 13 152781 1 bp gap MH394353
06D ×8 Cinnamomum bodinieri Lauraceae 30188820 4.53 9 152778 Y MH394417
06E ×10 Cinnamomum bodinieri Lauraceae 32065328 4.81 13 152719 Y MH394418
06A ×12 Cinnamomum bodinieri Lauraceae 24488292 3.67 7 152719 Y MH394415
06B ×14 Cinnamomum bodinieri Lauraceae 35035602 5.26 11 152719 Y MH394416
08D ×8 Holboellia latifolia Lardizabalaceae 26229946 3.93 5 157817 Y MH394377
08E ×10 Holboellia latifolia Lardizabalaceae 28273022 4.24 9 157818 Y MH394378
08A ×12 Holboellia latifolia Lardizabalaceae 33873136 5.08 13 157614 204 bp gap MH394375
08B ×14 Holboellia latifolia Lardizabalaceae 34021360 5.1 10 157818 Y MH394376
09D ×8 Chloranthus erectus Chloranthaceae 21843512 3.28 4 157812 43 bp gap MH394413
09E ×10 Chloranthus erectus Chloranthaceae 18044364 2.71 5 157812 47 bp gap MH394414
09A ×12 Chloranthus erectus Chloranthaceae 30022162 4.5 13 157852 Y MH394411
09B ×14 Chloranthus erectus Chloranthaceae 28656686 4.3 11 157852 Y MH394412
10D ×8 Sarcandra glabra Chloranthaceae 18893508 2.83 5 158733 119 bp gap MH394361
10E ×10 Sarcandra glabra Chloranthaceae 20662770 3.1 7 159007 22 bp gap MH394362
10A ×12 Sarcandra glabra Chloranthaceae 27510166 4.13 9 158900 Y MH394360
10B ×14 Sarcandra glabra Chloranthaceae 29545206 4.43 9 158900 Y MH394431
11D ×8 Meconopsis racemosa Papaveraceae 24351884 3.65 5 153762 Y MH394401
11E ×10 Meconopsis racemosa Papaveraceae 29160582 4.37 5 153762 Y MH394402
11A ×12 Meconopsis racemosa Papaveraceae 33763340 5.06 6 153763 Y MH394399
11B ×14 Meconopsis racemosa Papaveraceae 35990358 5.4 4 153728 1 bp gap MH394400
12D ×8 Macleaya microcarpa Papaveraceae 26265548 3.94 11 161064 48 bp gap MH394385
12E ×10 Macleaya microcarpa Papaveraceae 25100372 3.77 11 161064 48 bp gap MH394386 
12A ×12 Macleaya microcarpa Papaveraceae 29491952 4.42 13 161118 Y MH394383
12B ×14 Macleaya microcarpa Papaveraceae 28462338 4.27 12 161110 2 bp gap MH394384
13D ×8 Hodgsonia macrocarpa Cucurbitaceae 26886870 4.03 26 155027 1300 bp gap MH394428
13E ×10 Hodgsonia macrocarpa Cucurbitaceae 34179418 5.13 16 154855 1298 bp gap MH394429
13A ×12 Hodgsonia macrocarpa Cucurbitaceae 37182144 5.58 18 156015 20 bp gap MH394426
13B ×14 Hodgsonia macrocarpa Cucurbitaceae 36782268 5.52 17 156146 Y MH394427
14D ×8 Malus yunnanensis Rosaceae 22107718 3.32 16 158955 820 bp gap MH394389
14E ×10 Malus yunnanensis Rosaceae 25720160 3.86 5 160071 Y MH394390
14A ×12 Malus yunnanensis Rosaceae 37501036 5.63 5 160067 Y MH394387
14B ×14 Malus yunnanensis Rosaceae 33776058 5.07 5 160068 Y MH394388
15D ×8 Elaeagnus loureirii Elaeagnaceae 15195822 2.28 5 152196 8 bp gap MH394424
15E ×10 Elaeagnus loureirii Elaeagnaceae 16862680 2.53 5 152196 8 bp gap MH394425
15A ×12 Elaeagnus loureirii Elaeagnaceae 21511050 3.23 4 152199 5 bp gap MH394422
15B ×14 Elaeagnus loureirii Elaeagnaceae 20556860 3.08 6 152199 5 bp gap MH394423
16D ×8 Rhododendron rex subsp. fictolacteum Ericaceae 23623070 3.54
16E ×10 Rhododendron rex subsp. fictolacteum Ericaceae 28092596 4.21
16A ×12 Rhododendron rex subsp. fictolacteum Ericaceae 31352560 4.7
16B ×14 Rhododendron rex subsp. fictolacteum Ericaceae 30525730 4.58
17D ×8 Swertia bimaculata Gentianaceae 18303136 2.77 53 152808 266 bp gap MH394373
17E ×10 Swertia bimaculata Gentianaceae 16559554 2.48 41 153443 406 bp gap MH394374
17A ×12 Swertia bimaculata Gentianaceae 15877478 2.38 30 143977 9947 bp gap MH394371
17B ×14 Swertia bimaculata Gentianaceae 18448302 2.77 48 153602 341 bp gap MH394372
18D ×8 Primula sinopurpurea Primulaceae 22890598 3.43 5 151945 50 bp gap MH394358
18E ×10 Primula sinopurpurea Primulaceae 26618684 3.99 5 151945 50 bp gap MH394359
18A ×12 Primula sinopurpurea Primulaceae 24107472 3.62 3 151945 50 bp gap MH394356
18B ×14 Primula sinopurpurea Primulaceae 25834066 3.88 3 151945 50 bp gap MH394357
19D ×8 Paederia scandens Araceae 25307356 3.8 15 162267 247 bp gap MH394346
19E ×10 Paederia scandens Araceae 24658068 3.7 7 162268 247 bp gap MH394347
19A ×12 Paederia scandens Araceae 23850180 3.58 8 162282 253 bp gap MH394344
19B ×14 Paederia scandens Araceae 24064764 3.61 10 162139 253 bp gap MH394345
20D ×8 Colocasia esculenta Araceae 29284270 4.39 4 162350 155 bp gap MH394430
20E ×10 Colocasia esculenta Araceae 25045978 3.77 5 162350 155 bp gap MH394421
20A ×12 Colocasia esculenta Araceae 23560322 3.53 6 162414 155 bp gap MH394419
20B ×14 Colocasia esculenta Araceae 24533656 3.68 4 162414 155 bp gap MH394420
21D ×8 Pholidota chinensis Orchidaceae 21688990 3.25
21E ×10 Pholidota chinensis Orchidaceae 20880950 3.13
21A ×12 Pholidota chinensis Orchidaceae 23548018 3.53
21B ×14 Pholidota chinensis Orchidaceae 27148284 4.07
22D ×8 Otochilus porrectus Orchidaceae 15550512 2.33
22E ×10 Otochilus porrectus Orchidaceae 22638772 3.4
22A ×12 Otochilus porrectus Orchidaceae 21572196 3.23
22B ×14 Otochilus porrectus Orchidaceae 28960858 4.34
23D ×8 Indosasa sinica Gramineae 18793020 2.82 6 139848 18 bp gap MH394381
23E ×10 Indosasa sinica Gramineae 17903432 2.69 10 139740 Y MH394382
23A ×12 Indosasa sinica Gramineae 19106404 2.87 9 139740 Y MH394379
23B ×14 Indosasa sinica Gramineae 19668682 2.95 8 139740 Y MH394380
24D ×8 Camellia gymnogyna Theaceae 17176632 2.58 4 156402 Y MH394405
24E ×10 Camellia gymnogyna Theaceae 24532196 3.68 7 156590 Y MH394406
24A ×12 Camellia gymnogyna Theaceae 26478224 3.97 4 156590 Y MH394403
24B ×14 Camellia gymnogyna Theaceae 29768770 4.47 4 156590 Y MH394404
25D ×8 Camellia sinensis var. assamica Theaceae 23291572 3.49 4 157028 Y MH394409
25E ×10 Camellia sinensis var. assamica Theaceae 18698814 2.8 5 157028 Y MH394410
25A ×12 Camellia sinensis var. assamica Theaceae 21788776 3.27 4 157029 Y MH394407
25B ×14 Camellia sinensis var. assamica Theaceae 26155342 3.92 8 157028 Y MH394408
26D ×8 Panicum incomtum Gramineae 16865102 2.53 61 139986 Y MH394350
26E ×10 Panicum incomtum Gramineae 20465942 3.07 21 139999 Y MH394351
26A ×12 Panicum incomtum Gramineae 20004364 3 18 139999 Y MH394348
26B ×14 Panicum incomtum Gramineae 20672642 3.1 17 139999 Y MH394349
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After de novo assembly, two species (Otochilus porrectus and Pholidota chinensis) generated poor plastid assemblies, with the longest contigs being 6705 bp with 2 × coverage and 1325 bp with 3 × coverage respectively. The other 23 species yielded useful plastid assemblies drawn from 3 to 61 contigs assembled into plastid genomes with depths ranged from 459 × to 2176 ×. Of these 23 species, 14 were assembled into complete plastid genomes. Eight species were assembled into nearly complete plastid genomes, but with gaps ranged from 5 to 349 bp (Table 2). However, although Rhododendron rex subsp. fictolacteum yielded useful plastid assemblies, many gaps were detected among contigs when the species Vaccinium macrocarpon was used as reference data.

For the nuclear rDNAs, 21 species gave ribosomal DNA sequences assemblies > 4.3 kb drawn from 1 to 2 contigs with sequencing depths ranging from 3 × to 567 × (no nrDNA sequences could be assembled for Phodidota chinensis, Paederia scandens, Otochilus porrectus, and Camellia gymnogyna) (Table 3). Of these 21 species, 18 resulted in assembled nrDNAs consisting of partial sequences of 18S and 26S, along with the complete sequence of 5.8S and the internal transcribed spacers ITS1 and ITS2. However, 3 species (2 samples of Manglietia fordiana (Sample ID 01 and 02), Phoebe neurantha (Sample ID 05), were difficult to assemble, resulting in only partial recovery of 5.8S and the internal transcribed spacers ITS1 and ITS2.

Table 3.

Assembly statistics of rDNAs for all specimens used in this study

Sample ID PCR Cycles Species Family #contigs Total assembly length (bp) (mean) Coverage (×) Reference genome GenBank accession number
01A ×12 Manglietia fordiana Magnoliaceae 2 10343 406 KJ414477_Chrysobalanus icaco MH270473
02A ×12 Manglietia fordiana Magnoliaceae 2 8637 67 MH270474
03A ×12 Schisandra henryi Schisandraceae 1 15487 47 MH270475
04A ×12 Schisandra henryi Schisandraceae 1 10747 78 MH270476
05A ×12 Phoebe neurantha Lauraceae 2 7516 19 MH270477
06A ×12 Cinnamomum bodinieri Lauraceae 1 10926 32 MH270478
08A ×12 Holboellia latifolia Lardizabalaceae 1 9298 160 MH270479
09A ×12 Chloranthus erectus Chloranthaceae 1 9094 54 MH270480 
10A ×12 Sarcandra glabra Chloranthaceae 1 9062 51 MH270481
11A ×12 Meconopsis racemosa Papaveraceae 1 7577 60 MH270482
12A ×12 Macleaya microcarpa Papaveraceae 1 12587 458 MH270483
13A ×12 Hodgsonia macrocarpa Cucurbitaceae 1 10172 567 MH270484
14A ×12 Malus yunnanensis Rosaceae 1 5953 249 MH270485
15A ×12 Elaeagnus loureirii Elaeagnaceae 1 7901 428 MH270486
16A ×12 Rhododendron rex subsp. fictolacteum Ericaceae 1 6825 380 MH270487
17A ×12 Swertia bimaculata Gentianaceae 1 9644 48 MH270488
18A ×12 Primula sinopurpurea Primulaceae 1 5539 15 MH270489
19A ×12 Paederia scandens Araceae
20A ×12 Colocasia esculenta Araceae 1 4399 5 MH270490
21A ×12 Pholidota chinensis Orchidaceae – – – –
22A ×12 Otochilus porrectus Orchidaceae
23A ×12 Indosasa sinica Gramineae 1 17306 93 MH270491
24A ×12 Camellia gymnogyna Theaceae
25A ×12 Camellia sinensis var. assamica Theaceae 1 11212 46 MH270493
26A ×12 Panicum incomtum Gramineae 1 8446 74 MH270494
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To check the quality of the plastid sequences, all gene regions were translated. No stop codons that would be indicative of sequencing errors were detected within the assembled contigs. We then extracted about 1400 bp of rbcL sequence from 23 of the samples to check for contamination (for Rhododendron rex subsp. fictolacteum (Sample ID 16), the plastid genome was not assembled successfully but we could nevertheless extract the rbcL sequence from the plastid contigs). These rbcL sequences were subjected to a blast search against the NCBI database. The rbcL sequences contained no insertions or deletions and matched the correct genus or family in each case (Table 4). Likewise, we blasted the final assembled rDNA ITS sequences (or partial ITS sequences) from 24 samples against the NCBI database. In all cases, the closest match to the sequence was from the family of the sequenced sample. No matches with fungi were detected (Table 5).

Table 4.

BLAST results with extracted rbcL sequence against GenBank

Query Information BLAST results
Query_Sample ID Query_Species (Family) PCR cycles Gene name Length (bp) Reference_Species_Accession number (Family) Query coverage (%) Identities (%) Identify level
01A Manglietia fordiana (Magnoliaceae) 12 rbcL 1428 Magnolia cathcartii_JX280392.1 (Magnoliaceae) 100 99 Family
Magnolia biondii_KY085894.1 (Magnoliaceae) 100 99
Michelia odora_JX280398.1 (Magnoliaceae) 100 99
Manglietia fordiana_L12658.1 (Magnoliaceae) 98 100
02A Manglietia fordiana (Magnoliaceae) 12 rbcL 1428 Magnolia cathcartii_JX280392.1 (Magnoliaceae) 100 99 Family
Magnolia biondii_KY085894.1 (Magnoliaceae) 100 99
Michelia odora_JX280398.1 (Magnoliaceae) 100 99
Manglietia fordiana_L12658.1 (Magnoliaceae) 98 100
03A Schisandra henryi (Schisandraceae) 12 rbcL 1428 Schisandra chinensis_KY111264.1 (Schisandraceae) 100 99 Genus
Schisandra chinensis_KU362793.1 (Schisandraceae) 100 99
Schisandra sphenanthera_L12665.2 (Schisandraceae) 98 99
04A Schisandra henryi (Schisandraceae) 12 rbcL 1428 Schisandra chinensis_KY111264.1 (Schisandraceae) 100 99 Genus
Schisandra chinensis_KU362793.1 (Schisandraceae) 100 99
Schisandra sphenanthera_L12665.2 (Schisandraceae) 98 99
05A Phoebe neurantha (Lauraceae) 12 rbcL 1428 Phoebe omeiensis_KX437772.1 (Lauraceae) 100 99 Family
Persea Americana_KX437771.1 (Lauraceae) 100 99
Persea sp. _JF966606.1 (Lauraceae) 100 99
06A Cinnamomum bodinieri (Lauraceae) 12 rbcL 1428 Phoebe bournei_KY346512.1 (Lauraceae) 100 99 Family
Phoebe chekiangensis_KY346511.1 (Lauraceae) 100 99
Phoebe sheareri_KX437773.1 (Lauraceae) 100 99
Cinnamomum verum_KY635878.1 (Lauraceae) 100 99
08A Holboellia latifolia (Lardizabalaceae) 12 rbcL 1428 Akebia quinata_KX611091.1 (Lardizabalaceae) 100 99 Family
Stauntonia hexaphylla_L37922.2 (Lardizabalaceae) 99 99
Akebia trifoliate_KU204898.1 (Lardizabalaceae) 100 99
Holboellia latifolia_L37918.2 (Lardizabalaceae) 99 99
09A Chloranthus erectus (Chloranthaceae) 12 rbcL 1428 Chloranthus spicatus_EF380352.1 (Chloranthaceae) 100 100 Genus
Chloranthus japonicas_KP256024.1 (Chloranthaceae) 100 99
Chloranthus spicatus_AY236835.1 (Chloranthaceae) 98 99
Chloranthus erectus_AY236834.1 (Chloranthaceae) 98 99
10A Sarcandra glabra (Chloranthaceae) 12 rbcL 1428 Chloranthus spicatus_EF380352.1 (Chloranthaceae) 100 99 Family
Chloranthus japonicas_KP256024.1 (Chloranthaceae) 100 98
Chloranthus nervosus_AY236841.1 (Chloranthaceae) 97 98
Sarcandra glabra_HQ336522.1 (Chloranthaceae) 89 100
11A Meconopsis racemosa (Papaveraceae) 12 rbcL 1428 Meconopsis horridula_JX087717.1 (Papaveraceae) 97 100 Genus
Meconopsis horridula_ JX087712.1 (Papaveraceae) 97 99
Meconopsis delavayi_JX087688.1 (Papaveraceae) 97 99
12A Macleaya microcarpa (Papaveraceae) 12 rbcL 1428 Macleaya microcarpa_FJ626612.1 (Papaveraceae) 97 99 Family
Macleaya cordata_U86629.1 (Papaveraceae) 97 99
Coreanomecon hylomeconoides_KT274030.1 (Papaveraceae) 100 98
13A Hodgsonia macrocarpa (Cucurbitaceae) 12 rbcL 1449 Cucumis sativus var. hardwickii_KT852702.1 (Cucurbitaceae) 100 98 Family
Cucumis sativus_KX231330.1 (Cucurbitaceae) 100 98
Cucumis sativus_KX231329.1 (Cucurbitaceae) 100 98
14A Malus yunnanensis (Rosaceae) 12 rbcL 1428 Cotoneaster franchetii_KY419994.1 (Rosaceae) 100 99 Family
Vauquelinia californica_KY419925.1 (Rosaceae) 100 99
Cotoneaster horizontalis_KY419917.1 (Rosaceae) 100 99
Malus doumeri_KX499861.1 (Rosaceae) 100 99
15A Elaeagnus loureirii (Elaeagnaceae) 12 rbcL 1428 Elaeagnus macrophylla_KP211788.1 (Elaeagnaceae) 100 99 Order
Elaeagnus sp._KY420020.1 (Elaeagnaceae) 100 99
Toricellia angulate_KX648359.1 (Cornaceae) 99 99
16A Rhododendron rex subsp. Fictolacteum (Ericaceae) 12 rbcL 1428 Rhododendron simsii_GQ997829.1 (Ericaceae) 100 99 Family
Rhododendron ponticum_KM360957.1 (Ericaceae) 98 99
Epacris sp._ L01915.2 (Ericaceae) 97 99
17A Swertia bimaculata (Gentianaceae) 12 rbcL 1443 Swertia mussotii_KU641021.1 (Gentianaceae) 98 99 Family
Gentianopsis ciliate_KM360802.1 (Gentianaceae) 97 98
Gentianella rapunculoides_Y11862.1 (Gentianaceae) 97 99
18A Primula sinopurpurea (Primulaceae) 12 rbcL 1428 Primula poissonii_KX668176.1 (Primulaceae) 100 99 Genus
Primula chrysochlora_KX668178.1 (Primulaceae) 100 99
Primula poissonii_KF753634.1 (Primulaceae) 100 99
19A Paederia scandens (Araceae) 12 rbcL 1443 Pothos scandens_AM905732.1 (Araceae) 96 99 Family
Pedicellarum paiei_AM905733.1 (Araceae) 96 99
Pothoidium lobbianum_AM905734.1 (Araceae) 96 99
20A Colocasia esculenta (Araceae) 12 rbcL 1443 Colocasia esculenta_JN105690.1 (Araceae) 100 100 Species
Colocasia esculenta_JN105689.1 (Araceae) 100 99
Pinellia pedatisecta_KT025709.1 (Araceae) 100 99
21A Pholidota chinensis (Orchidaceae) 12 rbcL – – –
22A Otochilus porrectus (Orchidaceae) 12 rbcL – – –
23A Indosasa sinica (Poaceae) 12 rbcL 1434 Pleioblastus maculatus_JX513424.1 (Poaceae) 100 100 Family
Oligostachyum shiuyingianum_JX513423.1 (Poaceae) 100 100
Indosasa sinica_JX513422.1 (Poaceae) 100 100
24A Camellia gymnogyna (Theaceae) 12 rbcL 1428 Camellia szechuanensis_KY406778.1 (Theaceae) 100 100 Family
Pyrenaria menglaensis_KY406747.1 (Theaceae)
Camellia luteoflora_KY626042.1 (Theaceae)
25A Camellia sinensis var. assamica (Theaceae) 12 rbcL 1428 Camellia szechuanensis_KY406778.1 (Theaceae) 100 100 Family
Pyrenaria menglaensis_KY406747.1 (Theaceae) 100 100
Camellia luteoflora_KY626042.1 (Theaceae) 100 100
Camellia sinensis var. assamica_JQ975030.1 (Theaceae) 100 100
26A Panicum incomtum (Poaceae) 12 rbcL 1434 Lecomtella madagascariensis_HF543599.2 (Poaceae) 99 99 Family
Chasechloa madagascariensis_KX663838.1 (Poaceae) 99 99
Amphicarpum muhlenbergianum_KU291489.1 (Poaceae) 99 99
Panicum virgatum_HQ731441.1 (Poaceae) 100 99
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Table 5.

BLAST results with extracted ITS sequence against GenBank

Query information BLAST results
Query_Sample ID Query_Species (Family) PCR cycles Gene name Length (bp) Reference_Species (Family) Query coverage Identities
01A Manglietia fordiana (Magnoliaceae) 12 ITS 369 Magnolia virginiana_DQ499097.1 (Magnoliaceae) 100% 95%
02A Manglietia fordiana (Magnoliaceae) 12 ITS 349 Magnolia virginiana_DQ499097.1 (Magnoliaceae) 100% 95%
03A Schisandra henryi (Schisandraceae) 12 ITS 676 Schisandra pubescens_AF263436.1 (Schisandraceae) 99% 100%
04A Schisandra henryi (Schisandraceae) 12 ITS 676 Schisandra pubescens_JF978533.1 (Schisandraceae) 99% 99%
05A Phoebe neurantha (Lauraceae) 12 ITS 518 Phoebe neurantha_FM957847.1 (Lauraceae) 100% 99%
06A Cinnamomum bodinieri (Lauraceae) 12 ITS 603 Cinnamomum micranthum f. kanehirae _KP218515.1 (Lauraceae) 100% 99%
08A Holboellia latifolia (Lardizabalaceae) 12 ITS 677 Holboellia angustifolia subsp. angustifolia_AY029790.1 (Lardizabalaceae) 100% 99%
09A Chloranthus erectus (Chloranthaceae) 12 ITS 663 Chloranthus erectus_AF280410.1 (Chloranthaceae) 99% 99%
10A Sarcandra glabra (Chloranthaceae) 12 ITS 667 Sarcandra glabra_KWNU91871 (Chloranthaceae) 100% 100%
11A Meconopsis racemosa (Papaveraceae) 12 ITS 671 Meconopsis racemosa_JF411034.1 (Papaveraceae) 100% 99%
12A Macleaya microcarpa (Papaveraceae) 12 ITS 612 Macleaya cordata_AY328307.1 (Papaveraceae) 99% 89%
13A Hodgsonia macrocarpa (Cucurbitaceae) 12 ITS 614 Hodgsonia heteroclita_HE661302.1 (Cucurbitaceae) 100% 98%
14A Malus yunnanensis (Rosaceae) 12 ITS 596 Malus prattii_JQ392445.1 (Rosaceae) 99% 99%
15A Elaeagnus loureirii (Elaeagnaceae) 12 ITS 649 Elaeagnus macrophylla_JQ062495.1 (Elaeagnaceae) 99% 99%
16A Rhododendron rex subsp. fictolacteum (Ericaceae) 12 ITS 646 Rhododendron rex subsp. fictolacteum_KM605995.1 (Ericaceae) 100% 100
17A Swertia bimaculata (Gentianaceae) 12 ITS 626 Swertia bimaculata _JF978819.2 (Gentianaceae) 100 99%
18A Primula sinopurpurea (Primulaceae) 12 ITS 631 Primula melanops_JF978004.1 (Primulaceae) 100% 99%
19A Paederia scandens (Araceae) 12 ITS – – – –
20A Colocasia esculenta (Araceae) 12 ITS 552 Colocasia esculenta_AY081000.1 (Araceae) 99% 99%
21A Pholidota chinensis (Orchidaceae) 12 ITS – – – –
22A Otochilus porrectus (Orchidaceae) 12 ITS – – – –
23A Indosasa sinica (Poaceae) 12 ITS 604 Oligostachyum sulcatum_EU847131.1 (Poaceae) 98 99
24A Camellia gymnogyna (Theaceae) 12 ITS – – – –
25A Camellia sinensis var. assamica (Theaceae) 12 ITS 645 Camellia sinensis var. sinensis_FJ004871.1 (Theaceae) 99% 99%
26A Panicum incomtum (Poaceae) 12 ITS 795 Chasechloa egregia_LT593967.1 (Poaceae) 100 98
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One-way analyses of variance (ANOVA) were performed to test the total reads against PCR cycles, PCR cycles against plastid contig numbers, PCR cycles against plastid genome assembly length, PCR cycles against plastid mean-depth, and PCR cycles against plastid coverage. We found that was no significant correlation between PCR cycles and plastid contig numbers, PCR cycles and plastid genome assembly length, and PCR cycles and plastid coverage. There was, however, a significant positive correlation between the number of PCR cycles and the total number of reads, and PCR cycles and the plastid mean-depth (Fig. 2).

Fig. 2.

Fig. 2

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PCR cycles with raw data, contigs, and assembly length

Finally, when comparing plastome assembly coverage with C values of the species concerned we find a slight negative bit not significant correlation (Fig. 3), which would suggest, at least for our sampling, that plastome assembly coverage is not affected by nuclear genome size of the specimen concerned.

Fig. 3.

Fig. 3

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Plastome coverage versus C value (pg DNA per 1C) of all samples assembled in this study

Discussion

Sequencing herbarium specimens from low amounts of starting DNA

Our current study successfully demonstrated the recovery of plastid genome sequences and rDNA sequences from herbarium specimens, some up to 80 years old. Our study used small amounts of starting tissue (c 1 cm2) and extremely low initial concentrations (500 pg) of degraded starting DNA. This success with a small amount of starting tissue is important, and demonstrates the practical feasibility of organelle genome and rDNA recovery with minimal impacts on specimens. These findings, in the context of studies by others (e.g. Bakker et al. [14]) confirm that genome skimming can be performed with limited sample destruction enabling relatively straightforward access to high-copy number DNA in preserved herbarium specimens spanning a wide phylogenetic coverage.

To accommodate the use of only 500 pg of input DNA, we modified the library protocol to remove the step of DNA fragmentation by sonication because the DNA was already highly degraded, we did not undertake any size selection, and we increased the number of PCR cycles to enrich the indexed library. After library preparation and Illumina paired-end sequencing, a sufficient number of read pairs (> 15,000,000) were generated for our 25 specimens and 100 libraries. This strategy allowed the generation of complete or near complete plastid genomes with depths ranging from 459 × to 2176 ×, and nuclear ribosomal units with a high sequencing depth (3 × to 567 ×) for 23 and 24 specimens respectively. Despite the low starting concentration, no plant or fungal contaminants were obviously detectable in the assembled plastomes and rDNA sequences.

For herbarium plastome assembly, the procedures and parameters for setting the sequence quality control, de novo assembly, blast search and genome annotation were followed as in Yang et al. [25]. The rate of our 25 specimens with 100 libraries was c. 5 h per specimen on a 3-TB RAM Linux workstation with 32 cores. It was not different significantly between fresh and herbarium specimens.

Recovery of widely used loci in plant molecular systematics

A benefit of the genome skimming approach is that it can recover loci widely used in previous molecular systematics studies (e.g. Coissac et al. 2016 [12]). Here we recovered the standard rbcL DNA barcode region from 23/25 samples, the standard matK DNA barcode region from 23/25 specimens, the standard trnH-psbA DNA barcode region from 23/25 samples, the trnL intron from 23/25 samples, and the ITS1 and ITS2 from 20/25 to 19/25 samples respectively. In addition to the recovery of these standard DNA barcoding loci, we also recovered many other regions used as supplementary barcode markers (e.g. atpF-H, psbK-I). The data produced with this approach can thus contribute towards standard and extended DNA barcode reference libraries [12], in helping identify additional regions which are informative for any given clade [28], as well as producing data for phylogenomic investigations to elucidate the relationships amongst plant groups.

Practical benefits

A primary motivation for this study was our own experiences with suboptimal DNA recovery from herbarium specimens using Sanger sequencing coupled with difficulty in accessing fresh material of some species. The success of this method using only small amounts of starting tissue from herbarium specimens is an important step to addressing these challenges. It makes sequencing type specimens a realistic proposition, which can further serves to integrate genetic data into the existing taxonomic framework. A second practical benefit is that field work is often not possible in some geographical regions where past collections have been made. Political instability and/or general inaccessibility can preclude current collecting activities, and where habitats have been highly degraded or destroyed, the species concerned may simply be no longer available for collection. Mining herbaria to obtain sequences from previously collected material can circumvent this problem. Thirdly, sequencing plastid genomes and rDNA arrays from specimens that are many decades old enables a baseline to be established for haplotype and ribotype diversity. This baseline can then be used to assess evidence for genetic diversity loss or change due to recent population declines or environmental change.

Conclusions

This study confirms the practical and routine application of genome skimming for recovering sequences from plastid genomes and rDNA from small amounts of starting tissue from preserved herbarium specimens. The ongoing development of new sequencing technologies is creating a fundamental shift in the ease of recovery of nucleotide sequences enabling ‘new uses’ for the hundreds of millions of existing herbarium specimens [1, 10, 14, 16, 29]. This shift from Sanger sequencing to NGS approaches has now firmly moved herbarium specimens into the genomic era.

Authors’ contributions

BY and DZL organized the project. CXZ performed the experiments, analyzed the data, and wrote the paper; PMH wrote and edited the paper; JY, ZSH, and ZRZ extracted DNA, prepared library. All authors read and approved the final manuscript.

Acknowledgements

We are very grateful to Mr. Wei Fang (Kunming Institute of Botany, Chinese Academy of Sciences) for kindly providing the materials. We would like to thank Ms. Chun-Yan Lin and Mr. Shi-Yu Lv (Kunming Institute of Botany, Chinese Academy of Sciences) for their help with the experiments.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

The datasets supporting the conclusions of this article are available in the NCBI SRA repository, SRP142448 and hyperlink to datasets in http://www.ncbi.nlm.nih.gov/home/submit.shtml.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

Funding

This work was funded by a program for basic scientific and technological data acquisition of the Ministry of Science of Technology of China (Grant No. 2013FY112600), the Large-scale Scientific Facilities of the Chinese Academy of Sciences (Grant No: 2017-LSF-GBOWS-02), and Biodiversity Conservation Strategy Program of Chinese Academy of Sciences (ZSSD-011).

Publisher’s Note

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

Footnotes

Chun-Xia Zeng and Peter M. Hollingsworth contributed equally to this work

Contributor Information

Chun-Xia Zeng, Email: zengcx@mail.kib.ac.cn.

Peter M. Hollingsworth, Email: p.hollingsworth@rbge.org.uk

Jing Yang, Email: yangjingb@mail.kib.ac.cn.

Zheng-Shan He, Email: hezhengshan@126.com.

Zhi-Rong Zhang, Email: fagus@126.com.

De-Zhu Li, Email: dzl@mail.kib.ac.cn.

Jun-Bo Yang, Email: jbyang@mail.kib.ac.cn.

References

  • 1.Särkinen T, Staats M, Richardson JE, Cowan RS, Bakker FT. How to open the treasure chest? Optimizing DNA extraction from herbarium specimens. PLoS ONE. 2012;7(8):e43808. doi: 10.1371/journal.pone.0043808. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Hebert PDN, Hollingsworth PM, Hajibabaei M. From writing to reading the encyclopedia of life. Philos Trans R Soc B. 2016;371(1702):20150321. doi: 10.1098/rstb.2015.0321. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Kistler L, Ware R, Smith O, Collins M, Allaby RG. A new model for ancient DNA decay based on paleogenomic meta-analysis. Nucleic Acids Res. 2017;45(11):6310–6320. doi: 10.1093/nar/gkx361. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Hall LM, Wollcox MS, Jones DS. Association of enzyme inhibition with methods of museum skin preparation. Biotechniques. 1997;22(5):928–934. doi: 10.2144/97225st07. [DOI] [PubMed] [Google Scholar]
  • 5.Hedmark E, Ellegren H. Microsatellite genotyping of DNA isolated from claws left on tanned carnivore hides. Int J Legal Med. 2005;119(6):370–373. doi: 10.1007/s00414-005-0521-4. [DOI] [PubMed] [Google Scholar]
  • 6.Tang EPY. Path to effective recovering of DNA from formalin-fixed biological samples in natural history collections: workshop summary. Washington: The National Academies Press; 2006. [Google Scholar]
  • 7.Groombridge JJ, Jones CG, Bruford MW, Nichols RA. ‘Ghost’ alleles of the Mauritius kestrel. Nature. 2000;403(6770):616. doi: 10.1038/35001148. [DOI] [PubMed] [Google Scholar]
  • 8.Stiller M, Green RE, Ronan M, Simons JF, Du L, He W, Egholm M, Rothberg JM, Keates SG, Ovodov ND, Antipina EE, Baryshnikov GF, Kuzmin YV, Vasilevski AA, Wuenschell GE, Termini J, Hofreiter M, Jaenicke-Després V, Pääbo S. Patterns of nucleotide misincorporations during enzymatic amplification and direct large-scale sequencing of ancient DNA. Proc Natl Acad Sci USA. 2006;103(37):13578–13584. doi: 10.1073/pnas.0605327103. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Kuzmina ML, Braukmann TWA, Fazekas AJ, Graham SW, Dewaard SL, Rodrigues A, Bennett BA, Dickinson TA, Saarela JM, Catling PM, Newmaster SG, Percy DM, Fenneman E, Lauron-Moreau A, Ford B, Gillespie L, Subramanyam R, Whitton J, Jennings L, Metsger D, Warne CP, Brown A, Sears E, Dewaard JR, Zakharov EV, Hebert PDN. Using herbarium-drived DNAs to assemble a large-scale DNA barcode library for the vascular plants of Canada. Appl Plant Sci. 2017;5(12):1700079. doi: 10.3732/apps.1700079. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Smith O, Palmer SA, Gutaker R, Allaby RG. An NGS approach to archaeobotanical museum specimens as genetic resources in systematics research. In: Olson PD, Hughes J, Cotton JA, editors. Next generation systematics. Cambridge: Cambridge University Press; 2016. pp. 282–304. [Google Scholar]
  • 11.Straub SCK, Parks M, Weithmier K, Fishbein M, Cronn RC, Liston A. Navigating the tip of the genomic iceberg: next-generation sequencing for plant systematics. Am J Bot. 2012;99(2):349–364. doi: 10.3732/ajb.1100335. [DOI] [PubMed] [Google Scholar]
  • 12.Coissac E, Hollingsworth PM, Lavergne S, Taberlet P. From barcodes to genomes: extending the concept of DNA barcoding. Mol Ecol. 2016;25(7):1423–1428. doi: 10.1111/mec.13549. [DOI] [PubMed] [Google Scholar]
  • 13.Hollingsworth PM, Li DZ, van der Bank M, Twyford AD. Telling plant species apart with DNA: from barcodes to genomes. Philos Trans R Soc B. 2016;371(1702):20150338. doi: 10.1098/rstb.2015.0338. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Bakker FT, Lei D, Yu JY, Mohammadin S, Wei Z, van de Kerke S, Gravendeel B, Nieuwenhuis M, Staats M, Alquezar-Planas DE, Holmer R. Herbarium genomics: plastome sequence assembly from a range of herbarium specimens using an Iterative Organelle Genome Assembly pipeline. Biol J Lin Soc. 2016;117(1):33–43. doi: 10.1111/bij.12642. [DOI] [Google Scholar]
  • 15.Staats M, Erkens RHJ, van de Vossenberg B, Wieringa JJ, Kraaijeveld K, Stielow B, Geml J, Richardson JE, Bakker FT. Genomic treasure troves: complete genome sequencing of herbarium and insect museum specimens. PLoS ONE. 2013;8(7):e69189. doi: 10.1371/journal.pone.0069189. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Van de Paer C, Hong-Wa C, Jeziorski C, Besnard G. Mitogenomics of Hesperelaea, an extinct genus of Oleaceae. Gene. 2016;594(2):197–202. doi: 10.1016/j.gene.2016.09.007. [DOI] [PubMed] [Google Scholar]
  • 17.Zedane L, Hong-Wa C, Murienne J, Jeziorsky C, Baldwin BG, Besnard G. Museomics Illuminate the history of an extinct, paleoendemic plant lineage (Hesperelaea, Oleaceae) known from an 1875 collection from Guadalupe Island, Mexico. Biol J Linnea Soc. 2015;117(1):44–57. doi: 10.1111/bij.12509. [DOI] [Google Scholar]
  • 18.Besnard G, Christin PA, Malé PJG, Lhuillier E, Lauzeral C, Coissac E, Vorontsova MS. From museums to genomics: old herbarium specimens shed light on a C3 to C4 transition. J Exp Bot. 2014;65(22):6711–6721. doi: 10.1093/jxb/eru395. [DOI] [PubMed] [Google Scholar]
  • 19.Sproul JS, Maddison DR. Sequencing historical specimens: successful preparation of small specimens with low amounts of degraded DNA. Mol Ecol Resour. 2017;17:1183–1201. doi: 10.1111/1755-0998.12660. [DOI] [PubMed] [Google Scholar]
  • 20.Kanda K, Pflug JM, Sproul JS, Dasenko MA, Maddison DE. Successful recovery of nuclear protein-coding genes from small insects in museums using Illumina sequencing. PLoS ONE. 2015;10:30143929. doi: 10.1371/journal.pone.0143929. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Blaimer BB, Lloyd MW, Guillory WX, SnG B. Sequence capture and phylogenetic utility of genomic ultraconserved elements obtained from pinned insect specimens. PLoS ONE. 2016;11:e0161531. doi: 10.1371/journal.pone.0161531. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Meyer M, Kircher M. Illumina sequencing library preparation for highly multiplexed target capture and sequencing. Cold Spring Harb Protoc. 2010 doi: 10.1101/pdb.prot5448. [DOI] [PubMed] [Google Scholar]
  • 23.Patel RK, Jain M. NGS QC toolkit: a toolkit for quality control of next generation sequencing data. PLoS ONE. 2012;7(2):e30619. doi: 10.1371/journal.pone.0030619. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, Lesin VM, Nikolenko SI, Pham S, Prjibelski AD, Pyshkin AV, Sirotkin AV, Vyahhi N, Tesler G, Alekseyev MA, Pevzner PA. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19(5):455–477. doi: 10.1089/cmb.2012.0021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Yang JB, Li DZ, Li HT. Highly effective sequencing whole chloroplast genomes of angiosperms by nine novel universal primer pairs. Mol Ecol Resour. 2014;14(5):1024–1031. doi: 10.1111/1755-0998.12251. [DOI] [PubMed] [Google Scholar]
  • 26.Wyman SK, Jansen RK, Boore JL. Automatic annotation of organellar genomes with DOGMA. Bioinformatics. 2004;20(17):3252–3255. doi: 10.1093/bioinformatics/bth352. [DOI] [PubMed] [Google Scholar]
  • 27.Schattner P, Brooks AN, Lowe TM. The tRNAscan-SE, snoscan and snoGPS web servers for the detection of tRNAs and snoRNAs. Nucleic Acids Res. 2005;33(Suppl_2):W686–W689. doi: 10.1093/nar/gki366. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Li XW, Yang Y, Henry RJ, Rossetto M, Wang YT, Chen SL. Plant DNA barcoding: from gene to genome. Biol Rev. 2015;90(1):157–166. doi: 10.1111/brv.12104. [DOI] [PubMed] [Google Scholar]
  • 29.Hart ML, Forrest LL, Nicholls JA, Kidner CA. Retrieval of hundreds of nuclear loci from herbarium specimens. Taxon. 2016;65(5):1081–1092. doi: 10.12705/655.9. [DOI] [Google Scholar]

Associated Data

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

Data Availability Statement

The datasets supporting the conclusions of this article are available in the NCBI SRA repository, SRP142448 and hyperlink to datasets in http://www.ncbi.nlm.nih.gov/home/submit.shtml.

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