The native tree at risk of
disappearing into its invader

A tree can go extinct without anything dying

Red mulberry (Morus rubra) is native to eastern North America, from Ontario and Vermont south to Florida and west to Texas and South Dakota. White mulberry (Morus alba) was brought from Asia for silkworm culture and is now one of the commonest weedy trees on the continent.

The two species hybridise readily, and the hybrids are fertile. Where they grow together, the hybrids carry more white mulberry ancestry than red, and that bias is stronger where white mulberry is more abundant. Each generation of backcrossing dilutes the native genome further, and the endpoint is not a dead tree — it is a stand whose red mulberry ancestry survives only as fragments inside increasingly white-mulberry-like genomes.

The measurement everyone cites comes from Burgess, Morgan, Deverno and Husband, published in Molecular Ecology in 2005.1 They genotyped 184 trees from four populations in southern Ontario where both species grow together, using nuclear markers alongside chloroplast sequence.

That last line shapes everything that follows. Stated the other way round: 32% of those hybrids carried a red mulberry chloroplast. It is the reason no chloroplast test — including the good one below — can ever be the whole answer.

Michigan lists red mulberry as state threatened.2 In Ontario, where the species sits at its northern range edge and hybridisation pressure is worst, most known red mulberry sites have white mulberry growing in them.2

Everything after this is about the second question — given that you need a test, which one, and what will it settle? The answer is more constrained than it first appears — worth understanding before you spend anything.

What you can actually see from the ground

The two pure species are distinguishable by eye. The trouble starts with everything in between — so it matters which characters actually separate the species and which are folklore.

The character to learn is where the hairs sit on the underside — not whether hairs are present. Red mulberry carries erect hairs spread across the whole blade, soft to the touch. White mulberry has them only along the ribs and in the little tufts where veins meet the midrib.

Three things widely believed that are not true

Fruit colour means nothing. Nepal and colleagues put it bluntly: fruit colour is "highly variable within M. alba and non-diagnostic. In fact, in wild populations, fruits of M. alba are usually red to black rather than white."9 The Flora of North America gives white mulberry syncarps as "black, purple, or nearly white."8 More confident misidentification traces to this one piece of folklore than to anything else.

Style length is not diagnostic. This one circulates widely in identification guides. Both species effectively lack a style — Nepal's genus-wide key places M. alba and M. rubra together in the short-or-absent-style half of the genus.10 What older sources call "style length" is a measurement of the stigma arms, and even that is contested.

Whether a tree is male, female or both tells you nothing. Both species are subdioecious, with roughly one tree in ten bearing both sexes,9 and a similar fraction switching sex from one year to the next.10 Treating breeding system as a species character is precisely the error that produced a spurious mulberry species, M. murrayana, later dismantled by exactly that observation.9

One more caution that undercuts almost everything in the table: these characters are read from mature leaves on ordinary shoots. Juvenile growth, stump sprouts and vigorous water shoots converge between the species, and as Nepal puts it, "nearly all of the unique characteristics of M. rubra fail in juvenile leaves."9

Morphology sees species. It barely sees ancestry

Burgess and colleagues measured six morphological characters alongside their genetic markers, and found that the pure and hybrid classes differed on all six.1 That sounds like good news for field identification. It is close to the opposite.

The reason is in which classes the characters separate. Of the six, only leaf area and leaf perimeter told all three groups apart. For the other four — number of lobes, sinus depth, and trichome density on both leaf surfaces — white mulberry and the hybrids were statistically indistinguishable from each other, and both differed from red mulberry.1

This is better news than it sounds for one job and much worse for another. Morphology is a decent tool for finding the trees that are not red mulberry — which is what a removal programme needs. It is close to useless for whether a good-looking tree is pure, because the hybrids that most resemble red mulberry are exactly the ones the characters fail on.

Trees that fooled the experts

The clearest example comes from a Kansas population studied by Nepal, where trees were first assigned by an expert on leaf, bud and bark characters and then genotyped.10 The morphological calls did not survive:

Of nine trees that morphology had flagged as possible hybrids, only six were confirmed. And the two marker systems agreed with each other on only 44% of the hybrids they found — a reminder that even the genetic answer depends on which markers you use.10

Conservation practice has already absorbed this. Canada's recovery strategy designates critical habitat for trees "confirmed as pure-strain Red Mulberry trees through genetic testing," and lists confirming the genetic purity of morphologically-identified trees as outstanding work.13 The status report records the consequence plainly: "a few of trees previously counted as Red Mulberry were determined to be hybrids and were excluded from subsequent surveys."12

The one quantitative consolation: of everything measurable on a leaf, hair density on the underside is the best single predictor of what the genome actually says. Regressed on its own against hybrid index it explains about 30% of the variation, and in a combined regression of the four characters that individually tracked hybrid index, it was the only one that stayed significant, with the model reaching 40%.1 Thirty percent is a good morphological character. It is not a test.

So morphology can't settle it; a molecular test has to. And which test is the right one is not a matter of preference.

Two things decide what a test can possibly see

Before comparing methods on price or convenience, most of the answer is already fixed by two things: how the marker is inherited, and how many generations of backcrossing have happened. Neither is negotiable, and together they rule out whole categories of test before you spend a dollar.

One: a maternal marker can only ever name one parent

Chloroplasts are inherited maternally in most flowering plants — those in a tree came from the ovule, not the pollen. Burgess and colleagues relied on exactly this when they used mulberry chloroplast DNA to read the maternal lineage of each hybrid.1 It makes chloroplast DNA a superb species marker and a fundamentally limited hybrid marker.

If a red mulberry flower is pollinated by white mulberry, the seedling is a 50/50 nuclear hybrid carrying a pure red mulberry chloroplast. Every chloroplast test ever devised will call that tree red mulberry — correctly, and uselessly. This is not a hypothetical failure mode. It is about a third of the hybrids Burgess found — with a 95% interval running from 17% to 52%, because that result rests on 25 sequenced trees and its 68:32 split could not be distinguished from an even one.1 computed here No amount of money spent on a better chloroplast assay recovers those trees, because the information is not in the molecule.

What a chloroplast test is excellent at is the other direction. A tree that looks like red mulberry but returns a white mulberry chloroplast is definitively not pure, and you have found that out for the price of one PCR — polymerase chain reaction, a routine lab method that makes millions of copies of a target stretch of DNA, enough to work with. Here, that stretch carries the differences between red and white mulberry. Most of the hybrids Burgess sequenced carried a white-type chloroplast, so this catches most of them — though not all, and by a margin the small sample could not pin down.

Two: detection decays by half with every backcross

Closing the maternal blind spot needs a marker inherited from both parents. But a biparental marker has its own ceiling, and it is arithmetic rather than chemistry.

At a locus where the two species are fixed for different variants, a first-generation hybrid carries one copy of each — heterozygous, unmistakable, detectable with certainty at a single locus. Backcross that hybrid to white mulberry and each offspring has a one-in-two chance of inheriting the red variant at that locus. Backcross again and it is one in four. With n independent fixed-difference markers, the chance a first backcross slips through looking pure is 0.5ⁿ:

The first column is the one people miss. In principle, a single biparental fixed difference detects a first-generation hybrid every time — no probability is involved, because an F1 inherits one copy from each parent and must therefore carry both variants. What one locus cannot do is see deep backcrosses. Ten markers catch first-generation hybrids and first backcrosses. Fifty make it unlikely that anything within three generations slips past. Thousands — which is what sequencing gives you — let you estimate the actual ancestry fraction rather than answering yes or no.

Real markers rarely meet those ideal assumptions, which is why the practical guidance asks for many of them. A simulation study by Vähä and Primmer concluded that efficient detection of first-generation hybrids needs 12 to 24 markers, and that "separating backcrosses from purebred parental individuals requires a considerable genotyping effort (at least 48 loci), even when divergence between parental populations is high."6

That is the measure for everything below: what a method resolves on those two counts, and nothing more.

What already exists, and why none is yet a validated panel

The obvious move is to find the published marker panel for this species pair and use it. I went looking and found several partial precedents and no finished one. That needs stating precisely, because "no panel exists" is easy to say and easy to get wrong.

The foundational study used markers that don't transfer between labs

Burgess and colleagues' 2005 paper is still the reference measurement for mulberry hybridisation, and it is where the 53.7% comes from. The nuclear markers were RAPDs — randomly amplified polymorphic DNA — read alongside chloroplast sequence.1 RAPDs are dominant, so a heterozygote is indistinguishable from a homozygote for the present allele, and they are anonymous: the bands are not tied to known sequence. They are also notoriously sensitive to reaction conditions, which is why results generally do not transfer between laboratories. As a published measurement the study stands. The paper even gives its five primers and reaction conditions — but for the reproducibility reason just noted, it is not a protocol you can pick up and rely on.

The numbers underneath set the resolution of the best measurement anyone has. They screened 100 RAPD primers and kept five. Those yielded nine species-diagnostic fragments — five for white mulberry, four for red — plus 34 that were polymorphic but not diagnostic, for the 43 that were scored.1 The hybrid classifications did not rest on the nine alone: they came from a maximum-likelihood index built on all 43 fragments. And because these are dominant, anonymous markers never tested on known crosses, their sensitivity does not follow from the ideal single-locus arithmetic in File 04. The reference sets were cleanly separated — the red set averaged 0.89 on the index (95% interval 0.79–0.93), the white 0.09 (0.05–0.20); the means fall short of 1 and 0 only because most fragments are polymorphic rather than fixed and the index is a probability.1

The microsatellite work exists, and was not designed for this question

There are two relevant efforts. Nepal's 2008 dissertation ran both microsatellites and RAPDs on a Kansas population — the analysis behind File 03, where ten morphologically pure trees came back admixed.10 The more recent one is Schreier and Nepal's survey of 78 trees across six Upper Midwest populations, posted to bioRxiv in July 2026 and not yet peer reviewed.20 preprint They screened 12 markers originally developed in Asian Morus — M. indica, which their paper treats as synonymous with M. alba although Kew currently accepts it as distinct, and M. boninensis. Five amplified cleanly in M. rubra and were used for the analysis.

The real limitation is narrower and the authors state it themselves. The study was designed as an M. rubra population survey, and its own limitations section names "the absence of reference M. alba and confirmed hybrid genotypes," concluding that "additional highly informative nuclear markers are therefore needed to resolve the extent, directionality, and demographic consequences of introgression."20 So whether those five loci are ancestry-informative is not answered in the negative — it is unmeasured, because the design could not measure it.

Where individuals showed extra allelic peaks — the pattern that looks most like introgression — the authors decline to call it: such profiles "do not independently demonstrate allopolyploidy or introgression from M. alba," and what is needed is "species-diagnostic nuclear SNPs or genome-scale data."20

One risk worth flagging without overstating it. Observed heterozygosity came in below expected at every locus in every population, a mean of 0.34 against 0.65, and the authors list null alleles and allele dropout among the possible causes.20 If a primer silently fails on one species' allele, a heterozygous hybrid can read as a homozygous pure tree. But a heterozygote deficit on its own does not establish that — inbreeding, population subdivision (the Wahlund effect) and sampling structure all produce the same signature, and the authors name those too. Since the dataset contained no confirmed hybrids, nothing here shows dropout actually converting hybrids into pure calls. It is a specific failure mode to test for with known crosses, not an observed outcome.

The older result is the more pointed one. In Nepal's data the microsatellite and RAPD systems agreed on only 44% of the hybrids they found.10 Two marker sets, one population, and the ancestry calls largely disagreed — which is a clear demonstration that an unvalidated panel produces answers whose reliability you cannot assess.

Two operational efforts, neither publicly specified

Canada runs the most serious red mulberry identification programme anywhere. Leaf samples go to the University of Guelph Arboretum for genetic testing to call each tree red, white or hybrid, and the recovery strategy designates critical habitat only for trees "confirmed as pure-strain Red Mulberry trees through genetic testing."13 The programme has enough confidence in its calls to exclude trees from surveys on the strength of them.12 But neither the recovery strategy nor the Arboretum's published material names the markers, the loci or the technique. not disclosed in any source I could find

Separately, a US SARE-funded citizen-science project — Red Mulberry Search and Rescue — collected over 100 leaf samples nationally, had DNA extracted at the Ohio University Genomics Facility, and worked with Los Alamos National Laboratory to begin building an M. rubra genome to compare samples against the existing M. alba one.21 It reports classifying samples as rubra, alba or hybrid "with a high degree of accuracy" — while stating the limitation itself: because no complete rubra genome existed, "the results are not necessarily indicative of complete purity of species."21 That is a genome-comparison approach rather than a marker panel, and its classifier is not published in a form anyone can rerun.

Neither of these is a criticism. A conservation programme has no obligation to publish a protocol, and a farmer-grant project has no obligation to release a classifier. It does mean the two most-used methods for this exact question cannot be picked up by a third party.

Which sets the target for what follows. The most useful thing to look for is a fixed difference — a position where every red mulberry carries one variant and every white mulberry another, tied to known sequence so anyone can check the claim, and readable without specialist equipment. The rest of this page derives two, one maternal and one biparental. Neither has been validated against known crosses either, and that is flagged where it matters.

Where the two genomes actually differ

Deriving a fixed difference used to mean a sequencing project. It no longer does — enough Morus sequence is already public that the marker can be found by measurement rather than by bench work, and checked by anyone who wants to repeat it.

In 2025 a group at South Dakota State University published complete chloroplast genomes for 45 mulberry trees collected across eight US states, deposited as GenBank accessions PQ309062–PQ309106.3 That dataset makes it possible to stop guessing and measure which piece of DNA to look at.

I downloaded all 45 and analysed them directly. computed here

Aligning a red mulberry genome (159,423 bp) against a white mulberry one (159,293 bp) gives 421 single-base differences and 696 insertion or deletion events. The largest single indel is 36 bp, and the ten largest are mostly tandem-repeat expansions — a short motif repeated one extra time. Those expand and contract on their own, are prone to assembly error, and make unreliable species markers.

That rules out the laziest possible test. There is no big clean length difference you could see by running a PCR product straight onto a gel. The dependable signal is in substitutions, and substitutions have to be either sequenced or cut with an enzyme.

Which region carries the signal

For each candidate region I counted positions where all 33 unambiguous red mulberries were fixed for one base and all 10 unambiguous white mulberries fixed for another.

Two results stand out. First, the standard plant barcodes do work — rbcL and matK carry five and four fixed differences respectively. That is unusual for two species in the same genus, and it means a conventional barcoding workflow is not useless here. But with only four or five informative positions, one sequencing error costs you a quarter of your evidence.

That is also, in effect, what Burgess used. Their chloroplast work sequenced an 802 bp window of rbcL and found the two species differing at three fixed sites, with no variation within either species.1 Three sites across 42 trees was enough to call maternal lineage, and it is consistent with the five this analysis finds across the whole gene. The point of what follows is not that rbcL fails — it is that rpl32–trnL carries roughly forty times more signal, which is what makes a restriction digest possible instead of a sequencing run.

Second, rpl32–trnL(UAG) is far ahead at 131 fixed differences. It separated all 43 unambiguous trees perfectly: every red mulberry scored 131 out of 131 red-type positions, every white mulberry 131 out of 131 white-type. No intermediates, no ambiguity.

Two things keep that honest. “Unambiguous” here means the 43 of the 45 whose plastome agrees with their GenBank label; the discordant remainder — a tree labelled one species but carrying the other's plastome — is set aside and discussed in File 07. So “separates all 43 perfectly” describes the accessions that were kept, not a marker no record ever contradicts. And these trees come from eight states rather than the whole range, so the 131 positions are fixed across the genomes sampled here — strong candidate diagnostics, not differences proven fixed across either species everywhere.

The marker that wasn't, and the reference that misleads

A perfect 69 bp marker, which does not exist

Early in the analysis a different region looked ideal. The spacer between rps15 and ycf1 came out at 333 bp in every white mulberry and 405–407 bp in every red mulberry — a 70 bp gap, trivially readable on a gel, no enzyme needed.

It is an artifact. The ycf1 gene is annotated as starting 69 bp further along in the white mulberry records than in the red mulberry ones. The same physical DNA therefore falls inside the gene in one set of records and inside the spacer in the other, and comparing "spacer lengths" compares two different things. Searching all 199 Morus chloroplast genomes in GenBank for the supposedly red-mulberry-specific 69 bp block found it in every one, including all 101 white mulberries. computed here

It is an easy and completely invisible way to invent a marker. Any length difference derived from annotation coordinates rather than from the sequence itself deserves this check.

The NCBI red mulberry reference carries a white-type plastome

Scored against the diagnostic positions it comes out 12 white-type to 2 red-type. Its length, 159,289 bp, sits with white mulberry (159,293 bp) and nowhere near the red mulberry range of 159,396–159,423 bp. GenBank records it as identical to accession OP161259.4 The authors of the 2025 study independently noticed that this accession falls among the Asian species in their phylogeny.3 computed here

Note what that does and does not say about the tree it came from. Everything in File 04 applies here too: a plastome reports maternal lineage, not nuclear ancestry. The source specimen could be a largely M. rubra tree that carries a white mulberry chloroplast through introgression — the gene flow that repeated backcrossing produces — which is not a rare event, it is the majority of the hybrids Burgess sequenced. So the defensible statement is that the record is taxonomically discordant, not that the plant was misidentified.

Either way the practical consequence is the same. Anyone comparing a sample against "the M. rubra reference genome" is comparing it against a white mulberry–type plastome and will get the wrong answer. Use the vouchered PQ309073–PQ309106 series instead.

The same check turned up the mirror image. Accession PQ309072, deposited as M. alba, carries a 131-out-of-131 red mulberry–type plastome — a tree identified as white mulberry whose maternal line was red. computed here That is exactly the bidirectional introgression Burgess described, caught in a modern dataset by accident — the clearest example of why a plastome names a maternal lineage rather than a species.

One PCR, one enzyme, one gel

The 131 fixed differences in rpl32–trnL(UAG) can be read by sequencing. They can also be read for a few dollars with a restriction enzyme, because some of those differences create or destroy an enzyme's recognition site.

I searched the amplicon — the stretch of DNA the PCR copies — for enzymes whose cut count differs consistently between the species, then computed the predicted fragments for all 43 unambiguous trees. One is close to ideal.

HpyCH4III

Across those 43 trees, red mulberry carries one cut site in the amplicon and white mulberry carries three. computed here The resulting patterns are not subtle size shifts needing careful measurement — they are different pictures.

Read it as a shape rather than a measurement. Red mulberry gives one heavy band high on the gel. White mulberry gives a band slightly below it plus an obvious small band near the bottom. A hybrid whose maternal line is white mulberry gives the white mulberry pattern; one whose maternal line is red gives the red pattern. The test reports the maternal chloroplast lineage, and only that.

If HpyCH4III is hard to source, HinfI (cheaper, more widely stocked) separates the two with a busier pattern — red mulberry shows bands near 228 and 168 bp where white shows a single ~425 bp band; SspI and BfaI work too. computed here

The second assay, and this one is biparental

Everything above reads the chloroplast, so it hits the first limit from File 04: it names the maternal chloroplast lineage and nothing else, and is blind to the third of hybrids with a red-type chloroplast. Closing that gap needs a locus inherited from both parents — and there is one that can be run in the same afternoon, on the same DNA extraction.

ITS sits in the nuclear genome, so a tree inherits it from both parents. If the two species carry different ITS variants, a hybrid carries both at once, and both are visible on a gel. That is the codominant signal — both parental variants visible at once — that the arithmetic in File 04 requires: a first-generation hybrid must carry both, so in principle a single locus flags that class — subject to the multicopy caveat in File 04.

I pulled every full-length Morus ITS sequence from GenBank — 90 labelled M. rubra and 90 labelled M. alba — and aligned them. computed here There are 22 near-fixed differences between the species, and one of them creates a restriction site:

The amplicon uses the universal ITS1 and ITS4 primers published by White and colleagues in 1990,16 which are among the most widely used ITS primers across plants and fungi and match Morus directly. verified against the sequences The enzyme is NEB MboI, R0147S, 500 units for $88.00. confirmed

ITS1  TCCGTAGGTGAACCTGCGG
ITS4  TCCTCCGCTTATTGATATGC

Both parental variants have been recovered from a real hybrid

The prediction above would be worth little on its own. A group at the University of Central Missouri did a relevant experiment in 2010, and the result is sitting in GenBank — though what it does and does not show needs stating exactly.

They took a herbarium-vouchered M. alba × M. rubra hybrid — specimen KANU:361918 — cloned its ITS, and sequenced four clones from that one tree.17 I downloaded all four and scored them at my diagnostic site. computed here

I scored their pure reference trees too: all eight red mulberry clones carry one MboI site, all three white mulberry clones carry two. computed here The separation is clean.

A second variant at the same locus, from a published study

While checking this, I found a second polymorphism at the same locus. A 2025 paper in Plants genotyped 542 mulberry accessions across the ribosomal region, recovering 158 SNPs and 15 indels, and built a CAPS marker — a PCR-and-enzyme test like the ones here — on a 13 bp insertion in ITS1.18 In my own downloaded set that insertion is present in red mulberry and absent in white. The insertion creates an MstI site; FspI is an isoschizomer recognising the same TGCGCA sequence, and is the more commonly stocked of the two, so it is the one worth ordering.

Be clear about what that paper did and did not do, because it is easy to read it as more supportive than it is. Its CAPS assay was built to separate M. alba and M. notabilis from other Morus species — a taxonomic discrimination — using BstEII and MstI. It was not a red-versus-white hybrid test, it did not use FspI, and it did not measure whether the assay detects mixed parental repeat classes in an F1 or a backcross.18 What it does establish is that the locus carries real, scoreable variation and that a restriction assay on it works at the bench.

Scored against my own downloaded set, the insertion is present in 88 of 88 clean red mulberry sequences and 1 of 90 white mulberry. computed here So the ITS region carries two diagnostic variants, at different positions, each readable with its own enzyme.

That paper also publishes mulberry-specific ITS primers, which are worth preferring over the universal ones if you are ordering fresh.

The same GenBank check turned up the now-familiar problem: two of the 90 sequences deposited as M. rubra carry pure white mulberry ITS at every diagnostic position. computed here They are OR251260 and FJ605516 — and the literature search reached the same two by a different route.

The protocol

1. Collect and dry

   Young, fully expanded sun leaves. Dry them immediately in silica gel at roughly ten times the tissue mass. This single step matters more than anything else in the workflow — properly dried tissue yields good DNA for years at room temperature, and a leaf left in a warm bag overnight may yield none. Photograph the tree, the bark and both leaf surfaces, and take a GPS point.

2. Extract DNA

   A silica-column plant kit, or CTAB if you prefer to mix your own. Mulberry leaves are high in polysaccharides and phenolics, so add PVP to a CTAB prep or use a kit with an inhibitor-removal step. A generic animal-tissue kit will disappoint you.

3. Amplify rpl32–trnL(UAG)

   Published universal primers from Shaw and colleagues.5 I checked both against the actual Morus sequences: computed here

   rpL32-F  CAGTTCCAAAAAAACGTACTTC
   One mismatch to Morus, which reads …CCG… where the primer has …CCA…. It sits at position 8, far from the 3′ end, and will amplify normally.

   trnL(UAG)  CTGCTTCCTAAGAGCAGCGT
   Exact match in both species.

   Expect roughly 1,800 bp. Run 5 µL on a gel to confirm a single clean product before digesting.

4. Amplify ITS as well

   Same DNA, second tube, primers ITS1 and ITS4. Expect roughly 700 bp. Running both loci from one extraction costs one extra tube and doubles what the afternoon tells you.

5. Digest

   Take 10 µL of each product, add buffer and about 5 units of enzyme — HpyCH4III for the chloroplast amplicon, MboI for the ITS amplicon — and hold at 37 °C for an hour. Both enzymes work at the same temperature, so they can share a water bath. Digesting unpurified product straight from the PCR usually works for a yes/no readout, but the leftover PCR components can inhibit the enzyme — NEB recommends cleaning the product up first, and if a digest looks incomplete, dilute or purify it and repeat.

6. Run and read

   1.5% agarose, alongside a 100 bp ladder, a known white mulberry as a positive control, and a no-template (water) reaction to catch contamination. White mulberry is everywhere; find one in a hedgerow and use it to prove your assay works before you trust it on anything rare. Run an uncut aliquot of each PCR product beside its digest, too — a failed or partial digest can otherwise pass for a genotype. That trap is worst for the ITS assay: uncut ~700 bp product sits almost exactly where a fully cut red mulberry band does, so an under-digested white or hybrid can read as pure red.

   Read the two lanes together. The chloroplast lane names the maternal chloroplast lineage. The ITS lane says whether both species are represented in the nuclear genome. Three bands in the ITS lane is the result you are looking for and hoping not to find.

What the bench actually costs

Both assays can be bought as a service — see the next file — so owning the equipment is a choice rather than a requirement. It is worth making when you expect to run many samples, because the cost per tree collapses to a few dollars and the turnaround drops from weeks to an afternoon. Below what it costs, so the comparison is concrete.

Everything this needs was, twenty years ago, a university facility. It is now four appliances and a shoebox of reagents, and nothing below requires a licence, an institution, or an address that looks like a laboratory.

Before buying anything

Two cheaper routes are worth considering first.

Community biology labs already own all of this and will let members run their own projects. Verified monthly rates: BosLab, Somerville MA — $50; SoundBio, Seattle — $55, or $135 to lead your own project; ChiTownBio, Chicago — $75; Counter Culture Labs, Oakland — $100; BUGSS, Baltimore — $100; Genspace, Brooklyn — $110 community, $220 for full project access. confirmed Most ask for a short project proposal and a safety session.

Counter Culture Labs is the notable one for this project: it runs a standing plant biology group, and its fungal group already does ITS extraction and sequencing — which is precisely the second assay on this page.

Or send the reading out. Sequence the amplicon instead of digesting it, and you read all 131 chloroplast positions rather than one enzyme's worth. Psomagen charges $3.50 a reaction; Quintara from $4.00; Eurofins SimpleSeq prepaid kits work out at $6.10; Plasmidsaurus sequences an unpurified amplicon for $15 and takes a credit card with no minimum. confirmed Azenta/GENEWIZ confirms in its own FAQ that individuals can register and pay by card, though it publishes no price.

So the fair comparison is not "sequencing versus the bench". It is the thermocycler plus a few dollars a read, against the thermocycler plus the gel rig plus enzymes. At three to fifteen dollars a read the sequencing route wins on information per tree and loses on turnaround, and it lowers the equipment bill by roughly the $309 gel rig and the $171 of enzymes rather than by the whole $1,599.

What each method buys you

Now line every method up side by side. Each costs something and resolves something, and the two are not proportional — the cheapest useful step is nearly free, and the last bit of certainty is what costs real money.

The useful reading: the two gel assays are not a cheap approximation of sequencing. They answer a different question. The chloroplast assay rejects trees; the ITS assay is aimed at exactly the class of hybrid a first-generation cross produces. What neither can catch is the tree several generations into backcrossing — red-type chloroplast, ITS homogenised, and a quarter of its genome still foreign.

One column is missing from that table, and its absence matters more than anything in it: a sensitivity figure for each row. Nobody has measured how often these assays miss a hybrid that is there, because that requires known crosses and, per File 05, nobody has assembled that reference set for this species pair. The "detects" column describes what each method is designed to reach, not a measured hit rate. Read it that way, and read File 11 before attaching a confidence number to any of it.

For the deeply backcrossed tree, and for anyone who needs a number rather than a flag, you need the last row.

When you need genome-wide ancestry: genome skimming

Send extracted DNA for low-coverage whole-genome sequencing. At one or two times coverage you recover the complete chloroplast genome as a free byproduct — it is present in thousands of copies per cell — and enough nuclear variants to place the tree on a triangle plot of hybrid index against heterozygosity, which distinguishes first-generation hybrids from backcrosses and from pure trees — though placing a tree confidently on that plot, and on the heterozygosity axis in particular, takes appreciably more coverage than recovering the chloroplast does.7 One experiment, potentially both answers, and no wet-lab marker panel to build — though it still needs per-individual genotypes called at many ancestry-informative sites, and a trustworthy set of pure-parent references to define them — which, as File 05 found, does not yet exist in validated form for this species pair.

What it costs, for a real tree, today: Plasmidsaurus publishes $250 for 1 Gb, $500 for 5 Gb, $1,000 for 15 Gb, and lists plants among the organisms the service covers. confirmed Read the tiers rather than the headline, though. The $250 tier is specified for genomes of 20–60 Mb; a 340 Mb mulberry sits in the 300–750 Mb band, which is the $1,000 tier. A gigabase against 340 Mb is about 3× coverage and would probably carry a hybrid index, but it is not the configuration they sell for a genome that size.

The obstacle is not the vendor. It is the DNA. Plasmidsaurus does not accept any intact tissues or organs from animals, plants, insects, fungi, etc. confirmed A leaf in an envelope is refused. Plant material is taken only as protoplasts with the cell walls stripped, or as high-molecular-weight genomic DNA you extracted yourself — RNase-treated, and never touched by phenol or chloroform.

SeqCenter is the same story approached from the other side. It posts nanopore ligation prices in the open — $150 for 300 Mb, $175 for 600 Mb, $225 for 1.2 Gb, library prep included confirmed — with no quote gate and no institutional account required, which makes it cheaper per gigabase than the tier above. But it wants 60 µL at 40 ng/µL of clean double-stranded DNA, and its own extraction service covers only certain microbes.

So the sequencing is cheap and buyable off a web page. Turning mulberry leaf into a tube of sequenceable DNA is the step that still needs a lab bench or a core facility willing to do the extraction for you, and that step — not the sequencer — is what stands between a private individual and a plant genome.

One complication: there is no red mulberry nuclear genome assembly. NCBI lists zero assemblies and six sequencing runs for the species, against four assemblies for white mulberry. computed here Nuclear reads therefore have to be mapped to the white mulberry reference, which is workable for ancestry estimation but introduces a mild bias and needs someone who knows what they are doing.

That gap is closing on two fronts. Schreier and Nepal state in their preprint that low-coverage genome-skimming data already exist for the species and that development of a high-quality nuclear reference genome is underway using PacBio long-read and Hi-C scaffolding data, alongside complete chloroplast and mitochondrial genomes from which hundreds of candidate organellar markers are undergoing validation.20 preprint Separately, the SARE citizen-science project has been working with Los Alamos National Laboratory towards an M. rubra assembly for the same purpose.21 Anyone starting this work now should check whether either has landed before mapping to white mulberry.

Which is a reasonable place to end up. A test that costs a few dollars and rules out most of the problem is worth having, and it is the difference between a shortlist and a guess. Send the survivors for sequencing.

Rejecting is cheap. Certifying never finishes

One question remains, and it is the one that decides what a screening programme costs: how many trees do you have to test? The answer depends entirely on which way you want to be wrong, and the two directions have very different price tags.

Suppose you are looking at a group that should be red mulberry — a stand, a seed lot, a batch of planting stock — and some unknown fraction p of it is admixed. Testing n individuals, the chance of catching at least one hybrid is 1 − (1 − p)ⁿ:

The left-hand column is not a pessimistic scenario. It is roughly what Burgess measured — 98 of 184 trees, in populations that had been sought out because they held red mulberry.1 Canada's recovery strategy repeats that same 53.7% figure for its core populations,13 which almost certainly makes it the same measurement rather than an independent confirmation — but it does mean the number is what the recovery programme itself plans around. Where that is the true rate, five tests settle it 97 times in 100.

Two cautions on borrowing that number, both from the authors. The sampling took every putative red mulberry but only about a quarter of the surrounding white and hybrid trees, so they warn the figure "is an overestimate of the frequency of hybrids (and underestimate of whites)".1 Pulling the other way, it counts only hybrids that survived to be sampled — "hybridization rates for Morus may be even higher at the time of fertilization."1 So treat 50% as a plausible working figure for a stand where both species grow together, not as a measured constant, and certainly not as transferable to a stand you have not sampled.

Now the other direction. Suppose all n come back clean. What have you proved? Only an upper bound, and it comes down slowly:

So design the programme to reject, not to certify. Test a handful from anything you are suspicious of and act on the first positive. Save the deep, expensive methods for the small number of trees that survive screening and actually matter — the ones you intend to collect seed from, or protect, or propagate.

And say what you found rather than what you wish you could say. Not this stock is pure red mulberry, which is not provable by any method on this page, but something a result actually supports: mother tree chloroplast red-type, both ITS variants red-type, twenty offspring screened with no hybrids detected by an assay of unmeasured sensitivity — so the detectable hybrid fraction is under 14% at 95% confidence. That is a much weaker claim. It is also the one the evidence carries.

What to do with a result

Voucher everything. A genetic result attached to a GPS point, a photograph set and a pressed specimen is evidence; the same result attached to a memory is an anecdote. Herbarium sheets can be deposited with a regional herbarium, and most are glad of material from a documented wild population.

Consider sending samples onward. Madhav Nepal's group at South Dakota State University generated the 45-genome dataset this page is built on, works directly on red mulberry hybridisation,3 and has recently posted a population-genetic survey of 78 red mulberries across Kansas, Iowa, Wisconsin and Nebraska as a preprint.20 Their sampling is concentrated in the central US; the eastern and southeastern parts of the range look thin. Contributing tissue from an uncovered population is a real contribution rather than a favour asked.

And if a population comes back clean, that is worth telling your state natural heritage program about, whether or not red mulberry is formally listed where you are.

The words, in one place

Each term is defined in passing where it first appears; gathered here for reference.

References

1. Burgess, K. S., Morgan, M., Deverno, L. & Husband, B. C. (2005). Asymmetrical introgression between two Morus species (M. alba, M. rubra) that differ in abundance. Molecular Ecology 14: 3471–3483. pubmed.ncbi.nlm.nih.gov/16156816
2. Penskar, M. R. (2009). Special Plant Abstract for Morus rubra (red mulberry). Michigan Natural Features Inventory, Lansing, MI. mnfi.anr.msu.edu
3. Adhikari, B., Parajuli, S. & Nepal, M. P. (2025). Reporting complete chloroplast genome of endangered red mulberry, useful for understanding hybridization and phylogenetic relationships. Scientific Reports. GenBank PQ309062–PQ309106. pmc.ncbi.nlm.nih.gov/articles/PMC12008415
4. Zeng, Q., Chen, M., Wang, S., Xu, X., Li, T., Xiang, Z. & He, N. (2022). Comparative and phylogenetic analyses of the chloroplast genome. Frontiers in Plant Science 13: 1047592. Source of accession OP161259, from which RefSeq NC_070233 is derived. ncbi.nlm.nih.gov/nuccore/NC_070233
5. Shaw, J., Lickey, E. B., Schilling, E. E. & Small, R. L. (2007). Comparison of whole chloroplast genome sequences to choose noncoding regions for phylogenetic studies in angiosperms: the tortoise and the hare III. American Journal of Botany 94: 275–288. Source of the rpL32-F and trnL(UAG) primers. doi.org/10.3732/ajb.94.3.275
6. Vähä, J.-P. & Primmer, C. R. (2006). Efficiency of model-based Bayesian methods for detecting hybrid individuals under different hybridization scenarios and with different numbers of loci. Molecular Ecology 15: 63–72. pubmed.ncbi.nlm.nih.gov/16367830
7. Wiens, B. J. & Colella, J. P. (2025). triangulaR: an R package for identifying AIMs and building triangle plots using SNP data from hybrid zones. Heredity. nature.com/articles/s41437-025-00760-2
8. Wunderlin, R. P. (1997). Moraceae: Morus. In Flora of North America North of Mexico, vol. 3. Oxford University Press. efloras.org — genus key, M. rubra, M. alba
9. Nepal, M. P., Mayfield, M. H. & Ferguson, C. J. (2012). Identification of eastern North American Morus: taxonomic status of M. murrayana. Phytoneuron 2012-26: 1–6. The clearest published character comparison, and the source of the statement that fruit colour is non-diagnostic. phytoneuron.net (PDF)
10. Nepal, M. P. (2008). Systematics and reproductive biology of the genus Morus L. (Moraceae). PhD dissertation, Kansas State University. Source of the Konza Prairie morphology-versus-genotype comparison. krex.k-state.edu
11. Burgess, K. S. (2004). The genetic and demographic consequences of hybridization in small plant populations. PhD thesis, University of Guelph. The fuller analysis behind Burgess et al. 2005; listed for further reading. atrium.lib.uoguelph.ca
12. COSEWIC (2014). Assessment and Status Report on the Red Mulberry Morus rubra in Canada. Listed under COSEWIC assessments on the species page. Species at Risk Public Registry — Red Mulberry
13. Parks Canada Agency (2013). Recovery Strategy for the Red Mulberry (Morus rubra) in Canada. Species at Risk Act Recovery Strategy Series. Listed under Recovery strategies on the same species page. Species at Risk Public Registry — Red Mulberry
14. New England Biolabs product catalogue, prices confirmed 2 August 2026: HpyCH4III R0618S, HinfI R0155S, OneTaq 2X Master Mix M0482S, 100 bp DNA Ladder N3231S
15. miniPCR bio (Amplyus LLC) store, prices confirmed 2 August 2026. minipcr.com/store
16. White, T. J., Bruns, T., Lee, S. & Taylor, J. (1990). Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. In PCR Protocols: A Guide to Methods and Applications, pp. 315–322. Academic Press. The source of the ITS1 and ITS4 primers, now used across plants as well as fungi. doi.org/10.1016/B978-0-12-372180-8.50042-1
17. Nikaido, S., Salah, S. M., Ely, J. S., Wolf, H. J. & Raveill, J. A. (2010). Mulberry (Morus: Moraceae) hybridization in eastern North America: morphological and molecular evidence. University of Central Missouri. Unpublished; data deposited as GenBank HQ144170–HQ144187, including four cloned ITS sequences from the vouchered hybrid KANU:361918. ncbi.nlm.nih.gov/nuccore/HQ144170
18. Xu, X., Zhang, L., Bi, C., Qin, M., Wang, S., Li, D., He, N. & Zeng, Q. (2025). Extensive nrDNA polymorphism in Morus L. and its application. Plants 14(16): 2570, published 18 August 2025. Open access. 158 SNPs and 15 indels across 542 accessions. Source of the 13 bp ITS1 indel and of the evidence that concerted evolution in Morus is incomplete. Its CAPS assay uses BstEII and MstI and was built to separate M. alba and M. notabilis from other Morus species — a taxonomic discrimination, not a red–white hybrid test. doi.org/10.3390/plants14162570
19. Xuan, Y., Wu, Y., Li, P., Liu, R., Luo, Y., Yuan, J., Xiang, Z. & He, N. (2019). Molecular phylogeny of mulberries reconstructed from ITS and two cpDNA sequences. PeerJ 7: e8158. doi.org/10.7717/peerj.8158
20. Schreier, S. J. & Nepal, M. P. (2026). Population genetics of native red mulberry at its northwestern boundary suggests postglacial founder effects. bioRxiv preprint, posted 14 July 2026, not certified by peer review. 78 M. rubra individuals across six populations in Kansas, Iowa, Wisconsin and Nebraska. doi.org/10.64898/2026.07.11.737963
21. Cornett, J. (2022–2024). Red Mulberry Search and Rescue: preserving genetic diversity for the future of sustainable agroforestry. USDA SARE Farmer/Rancher grant FNC22-1338. Citizen-collected leaf samples, extraction at the Ohio University Genomics Facility, genome comparison against M. alba with Los Alamos National Laboratory. Reports rubra / alba / hybrid calls but states the results are "not necessarily indicative of complete purity of species." projects.sare.org/sare_project/fnc22-1338