What are the risks of low cDNA yield, and how should it be addressed?

Answer:
Low cDNA yield can significantly affect sequencing output, sensitivity, and the accuracy of biological interpretation.

1. Risks to data quantity and quality:

• Insufficient sequencing output:
  cDNA serves as the foundation for library construction. Low cDNA concentration may result in low library yield, leading to insufficient cluster generation on the sequencing platform and inadequate total data output. 
• Reduced detection sensitivity (dropout effect):
  Low cDNA yield often indicates low starting mRNA input or significant loss, leading to the loss of low-abundance transcripts.
  This results in genes appearing falsely unexpressed (false negatives). 
• Low proportion of usable data:
  Poor-quality libraries may generate a higher fraction of reads that cannot be mapped to the genome, reducing overall data efficiency. 

2. Distortion of biological signals:

• Amplification bias is amplified:
  When starting template quantity is low, stochastic bias introduced during PCR amplification becomes more pronounced.
  This may lead to over-amplification of high-abundance genes and under-representation of medium- and low-abundance genes, distorting the true gene expression profile. 
• Increased technical noise:
  Low-yield samples typically have a low signal-to-noise ratio, making it difficult to distinguish real biological heterogeneity from technical variation. 

3. Risks in downstream data analysis:

• Reduced number of usable cells:
  Low cDNA yield samples are often classified as low-quality and filtered out during analysis, reducing statistical power. 
• Increased batch effects:
  Significant variation in cDNA yield between samples can introduce batch effects during data integration, requiring additional computational correction, which may not fully resolve the issue. 

Recommended actions:

• First, verify whether the observed cDNA concentration falls within the expected range defined by the kit 
• If slightly below the recommended range:
  Proceed with caution, and consider increasing sequencing depth or applying more stringent downstream analysis 
• For inherently low-RNA samples (e.g., neutrophils, resting T cells):
  Increasing PCR cycles by 1–2 cycles may improve yield
  ⚠️ Excessive amplification may increase duplication rate and chimeric products 

If cDNA concentration is significantly below expectations:
Perform systematic troubleshooting and consider repeating the experiment