GC content calculator

What is GC content?

GC content measures the percentage of guanine (G) and cytosine (C) bases in a nucleic acid sequence. This fundamental metric provides insight into sequence stability, gene density, and experimental behavior in molecular biology workflows.

GC base pairs form three hydrogen bonds compared to two for AT/AU pairs, making GC-rich regions more thermally stable. This property affects DNA melting temperature, PCR primer design, and sequencing success rates.

How is GC content calculated?

GC content is calculated by dividing the sum of guanine and cytosine bases by the total number of nucleotides, then multiplying by 100:

$$GC\% = \frac{G + C}{A + T + G + C} \times 100$$

For RNA sequences, uracil (U) replaces thymine (T) in the denominator:

$$GC\% = \frac{G + C}{A + U + G + C} \times 100$$

Ambiguous bases like N are excluded from both the numerator and denominator to ensure accurate calculations.

How does our GC content calculator work?

The calculator automatically identifies sequences as DNA, RNA, or Unknown based on nucleotide content:

• DNA: Contains thymine (T) but no uracil (U)
• RNA: Contains uracil (U) but no thymine (T)
• Unknown: Contains neither, or contains both (ambiguous)

Input sequences are cleaned before analysis. Whitespace, numbers, and newlines are removed. Ambiguous nucleotides (N) are excluded from calculations, and invalid characters are counted separately with a warning.

Input parameters

• Input sequences: DNA or RNA sequences in FASTA format. Supports single sequences or multi-FASTA files. Accepts .txt, .fasta, .fa, .fas, and .seq extensions.
• Result format: Choose Per sequence for individual statistics on each sequence, or Combined total for aggregate statistics across all sequences.
• Output format: Text for human-readable output, CSV for comma-separated values, or Tab-separated for TSV format.

Understanding the results

The calculator provides comprehensive nucleotide statistics for each sequence:

Interpreting GC content

GC content varies widely across organisms and genomic regions:

For PCR primers, optimal GC content is 40-60%, with 50-55% preferred for balanced annealing temperatures.

CpG islands

A CpG island is a GC-rich DNA region where the CpG dinucleotide frequency is significantly higher than the surrounding genome. These regions are defined as being at least 200 bp long, with GC content ≥50% and a CpG observed-to-expected ratio >0.6.

CpG islands are often associated with promoter regions and play important roles in gene regulation. Identifying GC-rich regions can help locate potential CpG islands in your sequences.

Frequently asked questions

How much GC content is best?

Optimal GC content depends on the application. Most eukaryotic genomes range from 30-50%, with humans averaging 41%. For PCR primers, 40-60% GC is recommended to ensure proper annealing. Coding regions typically have higher GC content than intergenic sequences. There is no universal ideal—appropriate GC content varies by organism, genomic region, and experimental context.

What is considered high GC content?

Sequences with GC content above 60% are generally considered high. These GC-rich regions form stronger secondary structures due to three hydrogen bonds per GC pair versus two for AT pairs. High GC content is common in promoter regions, CpG islands, and certain bacterial genomes like Streptomyces (over 70%). Such regions can pose challenges for PCR amplification and DNA sequencing.

Is high or low GC content better?

Neither is inherently better—each has distinct properties. High GC content increases thermal stability and melting temperature, beneficial for thermostable primers but problematic for sequencing. Low GC (AT-rich) sequences denature more easily and may form fewer secondary structures. The optimal balance depends on your application: primer design favors 40-60%, while genomic studies must account for natural variation across organisms.

Related tools

After analyzing GC content, you may want to use these related tools:

• DNA to RNA — Transcribe your DNA sequences to RNA
• DNA to Protein — Translate DNA sequences to protein
• Reverse Complement — Generate the reverse complement of DNA/RNA sequences
• DNA Mutator — Introduce mutations into DNA sequences
• Random DNA — Generate random DNA sequences with specified GC content
• Random RNA — Generate random RNA sequences