The present disclosure relates to a method for constructing a whole genome high-throughput sequencing library comprising the following steps: (1) extracting a sample gDNA; (2) fragmenting said sample gDNA by enzyme cleavage, filling ends of the gDNA and adding A base to the gDNA fragments to obtain an A-added gDNA; (3) connecting the A-added gDNA with a linker combination to obtain a connected produce, said linker combination comprises two parts: a Y-shaped reverse linker and a high GC clamp linker; (4) purifying said connected product to obtain a purified product; and (5) screening the fragment of said purified product to obtain a sequencing library. The present disclosure also relates to a kit for constructing a whole genome high-throughput sequencing library.

The invention is directed to a method to obtain the spatial location and sequence information of an m-RNA target sequence on a tissue sample comprising providing a solid surface, attaching anchor molecules, binding scaffolding molecules, incorporating adenine, guanine, cytosine and thymine, incorporating thymine to the anchor molecules, removing the scaffolding, providing a tissue sample, reverser transcrining to create c-DNA, removing the c-DNA and obtaining the sequence information of the c-DNA.

The invention is directed to a method to obtain the spatial location and sequence information of an m-RNA target sequence on a tissue sample comprising providing a solid surface, attaching anchor molecules, binding scaffolding molecules, incorporating adenine, guanine, cytosine and thymine, incorporating thymine to the anchor molecules, removing the scaffolding, providing a tissue sample, reverser transcrining to create c-DNA, removing the c-DNA and obtaining the sequence information of the c-DNA.

The present disclosure provides compositions, methods, systems, and devices for polynucleotide processing. Such polynucleotide processing may be useful for a variety of applications, including polynucleotide sequencing.

The present disclosure provides compositions and methods for template-free double stranded geometric enzymatic nucleic acid synthesis of arbitrarily programmed nucleic acid sequences.

The present disclosure provides compositions and methods for template-free double stranded geometric enzymatic nucleic acid synthesis of arbitrarily programmed nucleic acid sequences.

Disclosed are methods of targeted sequencing by using gRNA-endonuclease complexes and methods of designing pools of gRNAs. The disclosure also provides sequencing adapters that that comprise a double-stranded nucleic acid having a single-stranded overhang with degenerate overhanging bases. In a first aspect, methods for Dephosphorylate targeted sequencing of double-stranded nucleic acids comprises cleaving dephosphorylated double-stranded nucleic acids with a plurality of endonuclease-guide ribonucleic acid (gRNA) complexes to generate double-stranded nucleic acid fragments having phosphorylated 5′ end overhangs at targeted sites.

Disclosed are methods of targeted sequencing by using gRNA-endonuclease complexes and methods of designing pools of gRNAs. The disclosure also provides sequencing adapters that that comprise a double-stranded nucleic acid having a single-stranded overhang with degenerate overhanging bases. In a first aspect, methods for Dephosphorylate targeted sequencing of double-stranded nucleic acids comprises cleaving dephosphorylated double-stranded nucleic acids with a plurality of endonuclease-guide ribonucleic acid (gRNA) complexes to generate double-stranded nucleic acid fragments having phosphorylated 5′ end overhangs at targeted sites.

Next Generation DNA sequencing promises to revolutionize clinical medicine and basic research. However, while this technology has the capacity to generate hundreds of billions of nucleotides of DNA sequence in a single experiment, the error rate of approximately 1% results in hundreds of millions of sequencing mistakes. These scattered errors can be tolerated in some applications but become extremely problematic when “deep sequencing” genetically heterogeneous mixtures, such as tumors or mixed microbial populations. To overcome limitations in sequencing accuracy, a method Duplex Consensus Sequencing (DCS) is provided. This approach greatly reduces errors by independently tagging and sequencing each of the two strands of a DNA duplex. As the two strands are complementary, true mutations are found at the same position in both strands. In contrast, PCR or sequencing errors will result in errors in only one strand. This method uniquely capitalizes on the redundant information stored in double-stranded DNA, thus overcoming technical limitations of prior methods utilizing data from only one of the two strands.

Next Generation DNA sequencing promises to revolutionize clinical medicine and basic research. However, while this technology has the capacity to generate hundreds of billions of nucleotides of DNA sequence in a single experiment, the error rate of approximately 1% results in hundreds of millions of sequencing mistakes. These scattered errors can be tolerated in some applications but become extremely problematic when “deep sequencing” genetically heterogeneous mixtures, such as tumors or mixed microbial populations. To overcome limitations in sequencing accuracy, a method Duplex Consensus Sequencing (DCS) is provided. This approach greatly reduces errors by independently tagging and sequencing each of the two strands of a DNA duplex. As the two strands are complementary, true mutations are found at the same position in both strands. In contrast, PCR or sequencing errors will result in errors in only one strand. This method uniquely capitalizes on the redundant information stored in double-stranded DNA, thus overcoming technical limitations of prior methods utilizing data from only one of the two strands.