Pooled animal and plant DNA barcodes
We have very briefly reviewed the output of each of the animal and plant markers, noting some have no sequences at the THAPBI PICT default minimum abundance threshold. Now we discuss the pooled results.
Sample report
Please open the summary/pooled.samples.onebp.xlsx sample report, zoomed
out you should have something like this:
The final column is the unknowns - and even at this zoom it is possible to see a solid red region for the two traditional medicine samples (wide green background bands).
Read report
To look at the unknown reads see summary/pooled.reads.onebp.xlsx. Sorting
be the species prediction and zooming out should show something like this
where the top half of the rows are those sequences with a species prediction.
It is clear that the majority of the unknown sequences are from the two
traditional medicine samples (wide green bands):
Overall the replicates are reassuringly consistent - look at neighbouring rows/columns within the colour bands in the two reports.
Pooled classifier assessment
The automated model assessment output in summary/pooled.assess.onebp.tsv
is also worth review. Note this only looks at the experimental mixtures where
there is a ground truth (S1, S2, S4, S5, S6, S7, S9 and S10) - not the
traditional medicine samples where the true species content is unknown.
$ cut -f 1-5,9,11 summary/pooled.assess.onebp.tsv
<SEE TABLE BELOW>
Working at the command line or using Excel should show the following:
#Species |
TP |
FP |
FN |
TN |
F1 |
Ad-hoc-loss |
|---|---|---|---|---|---|---|
OVERALL |
1058 |
727 |
240 |
7699 |
0.69 |
0.478 |
Acipenser schrenckii |
0 |
20 |
0 |
123 |
0.00 |
1.000 |
Aloe reynoldsii |
0 |
114 |
0 |
29 |
0.00 |
1.000 |
Aloe variegata |
110 |
0 |
25 |
8 |
0.90 |
0.185 |
Anguilla anguilla |
3 |
0 |
3 |
137 |
0.67 |
0.500 |
Beta vulgaris |
0 |
0 |
16 |
127 |
0.00 |
1.000 |
Bos taurus |
139 |
2 |
0 |
2 |
0.99 |
0.014 |
Brassica juncea |
0 |
127 |
0 |
16 |
0.00 |
1.000 |
Brassica napus |
7 |
0 |
9 |
127 |
0.61 |
0.562 |
Brassica nigra |
0 |
127 |
0 |
16 |
0.00 |
1.000 |
Brassica oleracea |
128 |
6 |
0 |
9 |
0.98 |
0.045 |
Brassicaceae (misc) |
0 |
70 |
0 |
73 |
0.00 |
1.000 |
Cactaceae (misc) |
0 |
3 |
0 |
140 |
0.00 |
1.000 |
Carica papaya |
16 |
0 |
0 |
127 |
1.00 |
0.000 |
Crocodylus niloticus |
122 |
0 |
12 |
9 |
0.95 |
0.090 |
Cullen sp. |
0 |
16 |
0 |
127 |
0.00 |
1.000 |
Cycas revoluta |
3 |
0 |
3 |
137 |
0.67 |
0.500 |
Dendrobium sp. |
131 |
0 |
3 |
9 |
0.99 |
0.022 |
Echinocactus sp. |
6 |
0 |
0 |
137 |
1.00 |
0.000 |
Euphorbia sp. |
3 |
0 |
3 |
137 |
0.67 |
0.500 |
Gallus gallus |
6 |
1 |
0 |
136 |
0.92 |
0.143 |
Glycine max |
16 |
0 |
0 |
127 |
1.00 |
0.000 |
Gossypium hirsutum |
16 |
0 |
0 |
127 |
1.00 |
0.000 |
Homo sapiens |
0 |
2 |
0 |
141 |
0.00 |
1.000 |
Huso dauricus |
112 |
0 |
16 |
15 |
0.93 |
0.125 |
Lactuca altaica |
0 |
66 |
0 |
77 |
0.00 |
1.000 |
Lactuca sativa |
74 |
2 |
0 |
67 |
0.99 |
0.026 |
Lactuca serriola |
0 |
66 |
0 |
77 |
0.00 |
1.000 |
Lactuca tatarica |
0 |
39 |
0 |
104 |
0.00 |
1.000 |
Lactuca virosa |
0 |
66 |
0 |
77 |
0.00 |
1.000 |
Meleagris gallopavo |
16 |
0 |
0 |
127 |
1.00 |
0.000 |
Parapenaeopsis sp. |
0 |
0 |
6 |
137 |
0.00 |
1.000 |
Pieris brassicae |
6 |
0 |
0 |
137 |
1.00 |
0.000 |
Pleuronectes platessa |
64 |
0 |
0 |
79 |
1.00 |
0.000 |
Solanum lycopersicum |
16 |
0 |
0 |
127 |
1.00 |
0.000 |
Sus scrofa |
64 |
0 |
0 |
79 |
1.00 |
0.000 |
Triticum aestivum |
0 |
0 |
16 |
127 |
0.00 |
1.000 |
Zea mays |
0 |
0 |
128 |
15 |
0.00 |
1.000 |
OTHER 31 SPECIES IN DB |
0 |
0 |
0 |
4433 |
0.00 |
0.000 |
Most of the false positives (FP) are alternative genus level matches in Brassica and Lactuca (as discussed in the paper). The two sequences we recorded in the Mini-rbcL reference set as the family Brassicaceae are likely also Brassica. The trnL-P6-loop marker had references for Aloe reynoldsii but these matches are most likely from Aloe variegata.
A couple of the unique sequences are in the Mini-rbcL reference as the family Cactaceae, and since they only appeared in the experimental mixes, these are likely Echinocactus sp. or Euphorbia sp.
There are more interesting FP for Acipenser schrenckii (the authors found this was accidentally included from the Huso dauricus caviar used), human (Homo sapiens, presumed laboratory contamination), and finally Lactuca sativa, cow (Bos taurus) and chicken (Gallus gallus) which the authors traced to cross-contamination during sample preparation or DNA isolation.
Why do Cullen sp. show up in S1 from the trnL P6 loop marker (as well
as S3 which the authors found too, see their Table 8)?
If the sample database had been more inclusive there would have been many more false positives. For example, the trnL-UAA sequence perfectly matching AP007232.1 Lactuca sativa is also a perfect match for MK064549.1 Luisia teres. Similarly, the Mini-rbcL sequence perfectly matching AP012989.1 Brassica nigra and MG872827.1 Brassica juncea also matches MN056359.2 Raphanus sativus (and more). This demonstrates the difficulties in curating an appropriate marker database - and the content should depend in part on your target samples.
Currently the provided references sequences (and thus classification databases used) lack any markers for Beta vulgaris, Parapenaeopsis sp., Triticum aestivum or Zea mays. Most of these were present at only a few percent dry weight, and are likely present below the default minimum abundance threshold. This explains the false negatives.
Conclusion
It appears that the THAPBI PICT default minimum abundance threshold of 100 reads is too stringent for detecting all the markers in a complex pool like this. Including negative sequencing controls would help set an objective lower bound.
There also appear to be marker sequences in these control samples which have not yet been published, which would help by filling in gaps in the reference set used for classification.
Also note we did not look at the multi-primer COI long marker, and perhaps the
default onebp classifier is not appropriate for the Mini-rbcL marker.