Biomedical Engineering Reference
In-Depth Information
L
å
100
´
x
i
()
=
i
=
1
LC
%
,
E
where
i
L
î
si s
-+ <-+
³-+
141
441
,
i
å
1
E
=
,
i
i
,
s
i
i
=
é
ê
s
ù
ú
æ
ç
ö
÷
+
L
=
log
1
.
4
3
For example, the sequence 5′-ACACACACACACACAC,
16 nt (
L
= 3), contains two nucleotides (A, C), but expected
E
= 4
variants; two variants of dinucleotides (AC, CA), but expected
E
= (16−1) variants; two variants of trinucleotides (ACA, CAC),
and expected
E
= (16−2) variants. The complexity value is
LC = 100(2 + 2 + 2)/(4 + 16 − 1 + 16 − 2) = 18.2
%
.
The LC tries to describe the “uniqueness” (“vocabulary rich-
ness”) of a sequence and the likelihood of PCR success of each
primer; this value varies from 100 for the best to 5 (e.g., poly(
N
))
for the worst primers. LC values of 80 and higher allow for the
rapid choice of the best primer or probe sequences.
4.4 Primer Quality
(Virtual PCR
Efficiency)
Determination
Our experimental data showed that the primer nucleotide
composition and melting temperature of the 12 bases at the 3′ end
of the primers are important factors for PCR efficiency. The melting
temperature of the 12 bases at the 3′ terminus is calculated
preferably by nearest neighbor thermodynamic parameters [
13
].
The composition of the sequence at the 3′ terminus is important;
primers with two terminal C/G bases are recommended for
increased PCR efficiency [
22
]. Nucleotide residues C and G form
a strong pairing structure in the duplex DNA strands. Stability at
the 3′ end in primer template complexes will improve the
polymerization efficiency.
We specify an abstract parameter called primer quality (PQ)
that can help to estimate the efficiency of primers for PCR. PQ is
calculated by the consecutive summation of the points according
to the parameters of total sequence and purine-pyrimidine
sequence complexity and of the melting temperatures of the whole
primer and of the terminal 12 bases at both the 3′ and 5′ ends.
Self-complementarity, which gives rise to possible primer-dimer
and hairpin structures, reduces the final value. The PQ tries to
describe the likelihood of PCR success of each primer; this value
varies from 100 for the best to 0 for the worst primers. To meet
multiplexing demands, it is possible in the program to select the
best primer with an optimal temperature range, allowing the design
of qualified primers or probes for any target sequence with any CG
