GC content is the percentage of guanine (G) and cytosine (C) bases in a nucleic acid sequence, calculated as GC% = (G + C) / (A + T + G + C) × 100. It is a useful first-pass indicator for duplex stability, melting temperature, secondary-structure risk, and sequence balance before primer design or oligo pool review.
In PCR primer design, primers with very low GC content can bind weakly and produce low Tm values, while very high-GC primers can form stable hairpins, dimers, or G-rich structures that interfere with amplification. The distribution of GC bases matters as well: a short 3' GC clamp can support priming, but long G/C runs near the 3' end should be reviewed for primer-dimer risk.
Use this GC composition and sequence-balance page when you need to calculate GC percentage, base composition, GC distribution, or GC outlier risk before primer design, oligo pool ordering, adapter design, or batch QC. Use the Primer Analyzer when GC outliers need all-in-one primer review, and use Batch Sequence QC, CRISPR, NGS, or adapter pages when the broader design decision is still open.
Example input: paste one primer, adapter, sgRNA insert, or batch candidate list before ordering. Treat 40-60% GC as the comfortable design zone, 30-70% as reviewable, and <30% or >70% as a GC risk check before ordering/design that should move to Batch QC or Primer Analyzer when other risks are present.
If a GC result raises a broader design concern, move the sequence into the Primer Analyzer rather than stretching this single-metric page into an all-in-one oligo analyzer. Primer Analyzer is the right next step when the same primer needs Tm, GC%, molecular weight, hairpin, self-dimer, hetero-dimer, mismatch, BLAST review, and lab interpretation together.
For oligo pool synthesis and sequencing applications, GC uniformity helps keep sequences within a more consistent design window. Use batch analysis to flag outliers, then review extreme sequences with Batch Sequence QC or Primer Analyzer when length, homopolymers, secondary structure, or primer-pair context may also affect performance.