RNA sequencing (RNA-seq) has advanced significantly in recent years, enabling comprehensive characterization of transcriptomes. This review discusses recent developments in RNA-seq methods, including improved transcription start site mapping, strand-specific measurements, gene fusion detection, small RNA characterization, and alternative splicing analysis. These advancements have enhanced the ability to quantify and understand RNA transcripts, particularly in complex biological systems. RNA-seq has revolutionized transcriptomics by allowing large-scale RNA analysis through cDNA sequencing, overcoming limitations of microarray technologies. Current RNA-seq platforms, such as those from Illumina, Roche 454, Helicos BioSciences, and Life Technologies, offer varying capabilities in terms of throughput, read length, and error rates. New methodologies are improving RNA-seq applications, including direct RNA sequencing (DRS) and techniques for quantifying RNA from very small samples. DRS, which directly sequences RNA without cDNA conversion, offers advantages for low-input RNA samples and provides more accurate transcriptome profiles. However, challenges remain in quantifying RNA transcripts, particularly for small RNAs, due to biases in sample preparation and sequencing. Strand-specific RNA-seq methods are crucial for distinguishing sense and antisense transcripts, but issues such as primer dimers and template switching can affect accuracy. Alternative splicing patterns are also important for understanding gene function and disease, with RNA-seq enabling the identification of novel splice sites and isoforms. Gene fusion detection is critical in cancer research, with RNA-seq providing insights into translocations and other genomic rearrangements. Targeted RNA-seq approaches allow focused analysis of specific transcripts, improving the efficiency and cost-effectiveness of sequencing. Small RNA profiling has been enhanced by NGS technologies, although quantification remains challenging. Emerging technologies, such as DRS and microfluidics, are improving the ability to analyze low-quantity RNA samples, enabling studies of rare cell types and tissues. These advancements are transforming transcriptomics, providing deeper insights into gene expression, regulation, and disease mechanisms, with potential applications in clinical diagnostics and personalized medicine.RNA sequencing (RNA-seq) has advanced significantly in recent years, enabling comprehensive characterization of transcriptomes. This review discusses recent developments in RNA-seq methods, including improved transcription start site mapping, strand-specific measurements, gene fusion detection, small RNA characterization, and alternative splicing analysis. These advancements have enhanced the ability to quantify and understand RNA transcripts, particularly in complex biological systems. RNA-seq has revolutionized transcriptomics by allowing large-scale RNA analysis through cDNA sequencing, overcoming limitations of microarray technologies. Current RNA-seq platforms, such as those from Illumina, Roche 454, Helicos BioSciences, and Life Technologies, offer varying capabilities in terms of throughput, read length, and error rates. New methodologies are improving RNA-seq applications, including direct RNA sequencing (DRS) and techniques for quantifying RNA from very small samples. DRS, which directly sequences RNA without cDNA conversion, offers advantages for low-input RNA samples and provides more accurate transcriptome profiles. However, challenges remain in quantifying RNA transcripts, particularly for small RNAs, due to biases in sample preparation and sequencing. Strand-specific RNA-seq methods are crucial for distinguishing sense and antisense transcripts, but issues such as primer dimers and template switching can affect accuracy. Alternative splicing patterns are also important for understanding gene function and disease, with RNA-seq enabling the identification of novel splice sites and isoforms. Gene fusion detection is critical in cancer research, with RNA-seq providing insights into translocations and other genomic rearrangements. Targeted RNA-seq approaches allow focused analysis of specific transcripts, improving the efficiency and cost-effectiveness of sequencing. Small RNA profiling has been enhanced by NGS technologies, although quantification remains challenging. Emerging technologies, such as DRS and microfluidics, are improving the ability to analyze low-quantity RNA samples, enabling studies of rare cell types and tissues. These advancements are transforming transcriptomics, providing deeper insights into gene expression, regulation, and disease mechanisms, with potential applications in clinical diagnostics and personalized medicine.