What are the challenges of RNA-seq?

Although RNA-seq offers several advantages over other sequencing technologies, there are a few challenges that still need to be resolved. Challenges of RNA-seq include:

• Not enough high-quality RNA: High-quality RNA in sufficient quantities is essential for successful RNA-seq. Poor-quality or degraded RNA can lead to inaccurate results or failure during library preparation. Low-level transcripts are often lost from the sequenced population altogether.
• Impact of sample pooling: Pooling samples before sequencing can reduce the associated costs and efforts, and also enable sequencing with limited quantities. However, the pooled sample must be treated as a single biological replicate as variations among pooled samples can lead to statistical issues and misleading results. This can be overcome by taking into consideration possible consequences during the experimental design process.
• Balancing sequencing depth and sample number: Increasing the number of samples in a sequencing run may seem appealing. However, this can reduce the read depth for each sample, which may compromise the accuracy and reliability of the data. Finding the right balance between sample number and sequencing depth is crucial for meaningful results.
• Time consuming & expensive: With several time-intensive processes such as assay designing, sample and library preparation, data analysis, and others, RNA-seq can be time-consuming and expensive. 
• Analyzing difficulties: It can be difficult to analyze a single type of RNA as cells typically contain several different types of RNA. Isolating and classifying the different types is inherently difficult.