Reversibly terminated nucleotides regulate incorporation during sequencing cycles. After a labeled nucleotide is incorporated into a growing DNA copy, imaging records its fluorescent signal before the next cycle proceeds. This cycle-resolved process links each detected color signal to a nucleotide position, allowing the instrument to build sequence information from repeated observations across clonally amplified fragments.
Clonal amplification creates groups of identical DNA fragments for analysis on the platform. Because the fragments share the same sequence, nucleotide incorporation across a group produces a corresponding fluorescent signal that imaging can record during each cycle. This arrangement connects the observed signal with the sequence of the amplified genetic material being examined.
Imaging captures the fluorescence emitted after labeled nucleotides are incorporated into DNA fragments. Each cycle therefore produces visual signal data associated with newly added bases. Software then interprets those signals and converts them into sequence data, connecting the chemical incorporation event with a digital representation that researchers can analyze for biological questions.
The workflow proceeds from genetic material to clonally amplified DNA fragments, followed by repeated incorporation and imaging cycles. Fluorescently labeled, reversibly terminated nucleotides provide the signals recorded during those cycles. Finally, software converts the collected signals into sequence data, which can be examined for genome content, expressed RNA, or genetic variation.
The choice depends on the biological material or question being investigated. Whole-genome sequencing supports examination of genetic material across the genome, whereas exome sequencing focuses on the genome’s exome. RNA sequencing provides information from RNA molecules. HiSeq 1000 systems support all three applications, enabling different views of genome content and gene-related biology.
The resulting datasets can support studies of gene expression, genome organization, disease-associated mutations, and other molecular features. Researchers interpret the sequence information in relation to the selected application, such as RNA sequencing for expression-related questions or genome and exome sequencing for genetic variation. These analyses connect nucleotide-level data with broader biological processes.