1. Get a General Sense of How Clean the Sequence Is
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How clear are the nucleotide peaks, in general?
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You should see evenly-spaced peaks, each with only one color. Peak
heights may vary 3-fold, which is normal. "Noise" (baseline) peaks
may be present, but with good template and primer they will be quite
minimal. If your results do not fit this description, consult our
Troubleshooting pages.
Here's an example of excellent sequence. Note the evenly-spaced
peaks and the lack of baseline 'noise' (see further down for examples
of higher baseline noise):
The next example has a little baseline noise, but the 'real' peaks are
still easy to call, so there's no problem with this sample:
Now we get to an example that has a bit too much noise. Note the multicolored
peaks at 271, 273 and 279, the oddly-spaced interstitial peaks near 291 and
301, and it is impossible to determine the real nucleotide is at 310.
Noise like the above most commonly arises when the sample itself is too dim. Check
the 'Signal Intensity' numbers for your chromatogram. They are usually available
in a separate pull-up window via your chromatogram viewing program, or if you've
printed the chromatogram, they may be printed at the top. Here are some example
signal strength numbers, reflecting arbitrary "relative fluorescence units":
Signal G:131 A:140 T:98 C:78
In our lab, we usually just look at the first number, the 'G' signal, for simplicity.
On a 3730, this number should ideally be between 500 and 2000 for best sensitivity
and low noise (although this can vary significantly from instrument to instrument,
or depending on the alignment procedures used to 'tune' the sequencer). Signals
between 50 and 100 SOMETIMES give reasonable data (and sometimes give poor data, as
depicted in the above window), but you'll definitely see baseline noise that would
never trouble you on a bright sample.
Note that the 3730 tends to have low baseline noise early in the chromatogram, but
it may increase modestly towards the end of the run. This is normal, and is a
consequence of the capillary electrophoresis technology currently in use. The
presence of salt in your samples exacerbates this effect.
II. Check For Mis-Called Nucleotides
- Are there obvious errors in the basecalling?
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Sometimes the computer will mis-call a nucleotide when a human could do better.
Most often, this occurs when the basecaller calls a specific nucleotide, when
the peak really was ambiguous and should have been called as 'N'. Occasionally,
the computer will call an 'N' when a human would be confident in making a more
specific basecall. Such mis-calls can occur even in the most error-free regions
of the gel. Quickly scan the gel for extremely small peaks, 'N' calls, and any
mis-spaced peaks or nucleotides.
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Mis-spaced peaks:
One good way to detect artifacts or errors in a sequencing chromatogram is
to scan through it, looking for mis-spaced peaks. At the same time, watch
for mis-spaced letters in the text sequence along the top. Nucleotides that
have been erroneously inserted into a sequence will often appear to be
oddly spaced relative to their neighboring bases, often too close.
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3730 sequencers (and probably other current-generation
capillary sequencers) have predictable errors in base
spacing. A common one for us is a G-A dinucleotide, which
leaves a little extra space between them. Often, it's
ignored by the basecaller, as in this example at right:
Note the extra space between the letters G and A (nt's
271 and 272) correspsonding to the mis-spaced peaks just
below them. No harm done, in this case; the sequence is
fine.
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Sometimes, however, those spaces get mis-interpreted
as missing nucleotides. In the example at right, note
the 'N' called in the space between the G-A pair. That
is an erroneous call; there is no missing base 'N' at
that position.
You can spot this by scanning the text sequence at the
top of the window, looking for oddly-spaced letters.
Of course, you may also spot this simply by looking
for 'N' nucleotides.
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The real problem comes when the basecaller attempts to
interpret a gap as a real nucleotide, such as in the
example at right. The typical scenario is a sequence
with noticeable baseline noise, and a gap is called as
if the baseline noise were a real peak. Often it's those
aforementioned G-A gaps, but not necessarily, as the
example here shows.
Note the real T peak (nt 58) and the real C peak (nt 60),
with the G barely visible between them. Despite it size,
the baseline-noise G peak was picked as if it were real.
The clues to spot are (i) the oddly-spaced letters, with
the G squeezed in, and (ii) the gap in the 'real' peaks,
containing a low noise peak.
This is a great example of why a weak sample, with its
consequent noisy chromatogram, is untrustworthy.
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Heterozygous (double) peaks:
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A single peak position within a trace may have but two peaks of different
colors instead of just one. This is common when sequencing a PCR product
derived from diploid genomic DNA, where polymorphic positions will show
both nucleotides simultaneously. Note that the basecaller may list that
base position as an 'N', or it may simply call the larger of the two peaks.
Realize, too, that it's easy for a human to miss these. If you want to be
sure you've detected all of the polymorphic positions, you should be using
a computer program to scan your chromatograms!
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Here's a great example of a PCR amplicon from genomic DNA,
with a clear heterozygous single-nucleotide polymorphism
(SNP). In this case, one allele carries a C, while the
other has a T. Both peaks are present, but at roughly half
the height they would show if they were homozygous.
Note that the peak was called an 'N' by the basecaller. A
comparison of text sequences would probably notify you
of the presence of a SNP here.
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Now we see a het that was missed by the basecaller. The
text sequence simply shows a 'C'. If all of your other
sequences also had a 'C' here, you would never realize
that you had a het SNP ... unless you scanned your
chromatograms.
In fact, it can be difficult to go through reams of
sequencing chromatograms, looking for het peaks like this.
It's fine for small projects - just look for the nested
multicolor peak. For big SNP-detection projects, though,
you should be using a computer program that can detect
these for you. Examples are:
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III. Loss of resolution later in the gel
- Even normal chromatograms stop giving accurate data after some distance:
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As the gel progresses, it loses resolution. This is normal; peaks broaden and shift,
making it harder to make them out and call the bases accurately. The sequencer will
continue attempting to "read" this data, but errors become more and more frequent.
Here are three snapshots representing data from progressively later regions in a
normal chromatogram:
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This is a typical example of data from a very good sample analyzed by an ABI
Model 3730XL DNA Analyzer. In this case, it is pGEM3 DNA sequenced with the T7
primer, and we are looking at a prime, high-quality portion of the sequence.
Note the crisp, clean bands, well separated and with no ambiguity as to the
proper basecall. You could easily call this sequence manually.
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If we scroll the above chromatogram further to the right (to higher-numbered
nucleotides), we see the frame depicted at left. It is evident that, here at
800 nucleotides, the sequence is still quite reliable. The peaks are broader
and clearly less well-resolved, but there still is evident separation between
them, and no casecalls with which I would disagree.
Note that the spacing between the basecall letters at top is regular, which
is often a good indication of the reliability of the data. When that spacing
becomes irregular, be careful!
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Here, we are out at the very limit of resolution, around 900-1000 nt on a
3730XL. We get only a general sense of the sequence here; I personally would
not design a primer from this sequence, for fear of wasting time on a
non-functional primer. There are only a few basecalls that can be considered
reliable. The G at 981 may in fact be two G's, the N could be a G or an A,
and who knows how many A's there are afterwards.
If you aligned the sequence with a known pGEM sequence, you might discover that
it is correct, so this is what we sometimes call "useable" data, but certainly
not accurate data.
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General take-home conclusions: Late in the chromatogram, watch for multiple bases of
any one nucleotide where there really should be only one. Watch, too, for wide peaks
mis-counted by the program as two nucleotides, when it should have been just one.
Wide peaks may also obscure smaller adjacent peaks (no example shown here).
The 3730 can read as far out as 1100 or 1200 nucleotides, but you should expect only
900-950 nt of really good sequence (and even then only if it was a very good sample!),
and useable sequence (i.e. error-prone but informative) out to perhaps 1000-1100.
IV. Truncate the sequence when problems become too frequent for YOUR purposes:
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What data quality do you need, in order to accomplish your goals?
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As the gel progresses, the errors described above become more and more frequent. Where
this occurs will primarily depend on the quality of your template. Our sequencers will
usually read GOOD templates out to 900 or 950 nucleotides with very low error rates.
Ignore the remaining data when the error rate is too high for your purposes.
An investigator trying to locate intron-exon boundaries won't mind fairly high error
rates, but one who needs publishable sequence can accept only the best sequence. One
who is doing a BLAST search to identify a coding sequence can accept fairly high error
rates, and still obtain a match, but if you want to spot SNPs, you can use only the
highest-quality sequence.
The Core technicians do not know your needs, and therefore cannot trim the sequence
data for you. We may return as much as 1100 nucleotides of sequence, but it is your
responsibility to trim off that which is too error-prone for YOUR purposes.
V. In Case of Problems:
If your chromatograms aren't as good as described here, or in case you see something that
needs further explanation, please refer to our
Troubleshooting Guide.
You will find descriptions of many common artifacts (e.g. Taq slip, loss of resolution,
dye blobs, sec-structure stops, etc).
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