Final answer:
RNA-Seq uses RPKM to quantify gene expression, and while setting a threshold RPKM value is common to determine gene expression, the cutoff can vary. High-throughput screening aids in functional analysis. Post-transcriptional modifications also play a vital role in gene expression regulation.
Step-by-step explanation:
Understanding Gene Expression Analysis in RNA-Seq
In the realm of gene expression analysis, RNA-Seq is a powerful tool for quantifying transcript levels across the genome. A common metric used is RPKM (Reads Per Kilobase of transcript, per Million mapped reads) which normalizes the raw read count by both the gene length and the total number of reads. While it is common to use a threshold RPKM value to determine if a gene of interest is expressed in a sample, the exact cutoff can vary depending on the study and the tissue type. Care should be taken when setting these thresholds to ensure that biologically relevant changes are not disregarded as noise.
Determining the function of a gene can involve several strategies including reverse genetics and RNAi technology to silence the gene and observe resulting phenotypic changes. Moreover, advancements like high-throughput screening make it possible to perform thousands of experiments simultaneously, leading to more comprehensive understanding of gene functions and interactions.
It is also essential to recognize the value of post-transcriptional modifications and alternative splicing in post-transcriptional regulation of gene expression, which are not directly captured by RNA-Seq RPKM values but are crucial for understanding the full complexity of gene expression.