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KAPA RNA Library Preparation Kits for Illumina

Kapa Biosystems, Inc.Available: Worldwide

KAPA Stranded mRNA-Seq Kits includes all the enzymes and buffers required for cDNA library preparation for Illumina Next-Generation Sequencing, utilizing 100 ng – 4 µg of total RNA. KAPA mRNA Capture Beads are included for isolation of poly(A)-tailed RNA. Kits provides precise measurement of strand orientation (>99%), uniform coverage, and high-confidence mapping of alternate transcripts, and are optimized for the improved…

Kapa Biosystems, Inc.

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KAPA Stranded mRNA-Seq Kits includes all the enzymes and buffers required for cDNA library preparation for Illumina Next-Generation Sequencing, utilizing 100 ng – 4 µg of total RNA.

KAPA mRNA Capture Beads are included for isolation of poly(A)-tailed RNA. Kits provides precise measurement of strand orientation (>99%), uniform coverage, and high-confidence mapping of alternate transcripts, and are optimized for the improved coverage of GC-rich and low-abundance transcripts. Kits contain KAPA HiFi for high-efficiency and low bias library amplification, as well as KAPA mRNA Capture Beads and a streamlined, “with-bead” protocol.

KAPA Stranded RNA-Seq Kits include all the enzymes and buffers required for cDNA library preparation for Illumina Next-Generation Sequencing, but do not contain the KAPA mRNA Capture Beads. Kits can be used to prepare libraries from 10-400 ng of either poly(A)-selected, ribosomally-depleted, or total RNA.

Features:

Uncover challenging transcripts

  • Improved coverage of GC-rich transcripts
  • Enhanced identification of exonic regions

Detect low-abundance transcripts

  • Enables identification of transcripts missed by competitor kits, even with high input
  • High uniformity across varying amounts of sample input

Identify more genes

  • Higher percentage of uniquely mapped reads compared to Illumina TruSeq™ Stranded mRNA Sample Prep Kits
  • Lower duplication rates yield better coverage

Maintain high coverage uniformity

  • Minimal 5′–3′ bias across transcripts
  • More uniform distribution of reads over each transcript

Applications:

  • Gene expression
  • Single nucleotide variation (SNV) discovery
  • Post-transcriptional SNVs
  • Fusion gene identification
  • Targeted transcriptome
  • Whole transcriptome

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