WO2011070155A1 - Procédé analytique concernant l'arn - Google Patents

Procédé analytique concernant l'arn Download PDF

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Publication number
WO2011070155A1
WO2011070155A1 PCT/EP2010/069382 EP2010069382W WO2011070155A1 WO 2011070155 A1 WO2011070155 A1 WO 2011070155A1 EP 2010069382 W EP2010069382 W EP 2010069382W WO 2011070155 A1 WO2011070155 A1 WO 2011070155A1
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nucleic acid
subpools
sequence
nucleic acids
rna
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PCT/EP2010/069382
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English (en)
Inventor
Alexander Seitz
Lukas Paul
Max Jan van Min
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Lexogen Gmbh
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Application filed by Lexogen Gmbh filed Critical Lexogen Gmbh
Priority to AU2010329825A priority Critical patent/AU2010329825B2/en
Priority to CA2782766A priority patent/CA2782766A1/fr
Priority to US13/511,961 priority patent/US20120238457A1/en
Priority to EP10788340.7A priority patent/EP2510114B1/fr
Priority to JP2012542561A priority patent/JP5926189B2/ja
Priority to CN2010800561858A priority patent/CN102782152A/zh
Publication of WO2011070155A1 publication Critical patent/WO2011070155A1/fr

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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6869—Methods for sequencing
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6809—Methods for determination or identification of nucleic acids involving differential detection
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6806—Preparing nucleic acids for analysis, e.g. for polymerase chain reaction [PCR] assay

Definitions

  • the present invention relates to the field of analyzing complex mixtures of nucleic acids and sample preparation for characteri ⁇ zation methods and sequencing, especially high throughput se ⁇ quencing techniques, such as Next Generation Sequencing (NGS) .
  • NGS Next Generation Sequencing
  • NGS is currently the foremost complete analyzing method.
  • Next Generation Sequencing is a generic term for parallelized sequencing through polymerization as high-throughput DNA sequencing method.
  • NGS reads sequences of up to many million frag ⁇ ments which are typically between 10 to several hundred base- pairs long. The complete sequence is obtained by alignment of those reads which is a challenging task.
  • Some NGS methods rely on a consensus blue print held in genomic and/or transcriptomic databases. The quality of the results depends on length and num ⁇ ber of reads, reading accuracy, quality of information in the reference database and applied bioinformatics algorithms. To date many reads provide just limited information. For instance many of the reads cannot be assigned uniquely and therefore are discarded. The two basic underlying reasons for this assignment uncertainty is that a) one read can align with two or more genes and b) that one read can originate from different tran- scriptvariants of the same gene.
  • RNA in samples, which contain a multitude of different RNA molecules of different cells or cell popula ⁇ tions or disease organisms, rare RNA or parts thereof are less likely to be retrieved. In fact, in transcriptomics rare RNA transcripts of even a simple organism are less likely to be de ⁇ tected and quantified.
  • RNA molecules or their DNA copy In more detail, for generating detectable signals most NGS approaches must amplify individual RNA molecules or their DNA copy.
  • Another method for in vitro clonal amplification is bridge PCR, where fragments are ampli ⁇ fied upon primers attached to a solid surface. Another option is to skip this amplification step, directly fixing DNA molecules to a surface. Such DNA molecules or above mentioned DNA coated beads are immobilized to a surface, and sequenced in parallel.
  • Sequencing by synthesis uses a DNA polymerase to determine the base sequence.
  • Reversible terminator methods use reversible versions of dye-terminators, adding one nucleotide at a time, detecting fluorescence at each position, by repeated removal of the blocking group to allow polymerization of another nucleotide.
  • Pyrosequencing also uses DNA polymerization, adding one nucleotide species at a time and detecting and quantifying the number of nucleotides added to a given location through the light emitted by the release of attached pyrophosphates.
  • the se ⁇ quencing by ligation method uses a DNA ligase to determine the target sequence.
  • oligonucleo ⁇ tides of a fixed length, labeled according to the sequenced po ⁇ sition. Oligonucleotides are annealed and ligated. The preferen ⁇ tial ligation by DNA ligase for matching sequences results in a dinucleotide encoded colour space signal at that position.
  • NGS technologies are essentially based on random amplifica ⁇ tion of input DNA. This simplifies preparation but the sequenc ⁇ ing remains undirected.
  • the sheer complexity of the sample in ⁇ formation - simultaneously obtained - is the key hindrance for unambiguous alignment of the reads. Therefore, complexity reduc ⁇ tion is essential for increasing the quality of the results.
  • BAC Bacte ⁇ rial artificial chromosome
  • Another option to reduce complexity is to first select poly- nucleic acids based on their respective sizes.
  • Different ap ⁇ proaches include, but are not limited to, agarose gel electro ⁇ phoresis or size exclusion chromatography for fractionation.
  • RNA sequencing approaches employ this method in order to obtain e.g. a fraction of RNA molecules called micro RNA (miRNA) sized between 15 and 30 nucleotides.
  • miRNA micro RNA
  • a different method for reducing the amount of input nucleic acid to below the amount contained within a single cell some ⁇ times is termed limited dilution.
  • a genomic nucleic acid sample is first fragmented and then diluted to an extent where spatial distribution of the nucleic acid fragments within the sample volume becomes significant. Then subpools are created by taking such small volumes from the total sample volume that most sub- pools contain no nucleic acids, a few subpools contain one nu ⁇ cleic acid each and even less subpools contain two nucleic ac ⁇ ids. This leads to singularization of nucleic acids and there ⁇ fore to complexity reduction compared to the full length genome as each singularized nucleic acid is a fragment of a genome.
  • a further option is to sequence-specifically reject RNA, e.g. in a hybridization-based approach that removes ribosomal RNA from the entire RNA sample.
  • RNA fractiona ⁇ tion methods that rely either on prior sequence information or are directed towards a certain RNA fraction (e.g. polyA selec ⁇ tion)
  • removal of rRNA does not bias the sequencing sample if e.g. mRNA is investigated.
  • Methods that deplete rRNA from total RNA samples are used to increase the number of reads that cover mRNA and other transcripts.
  • the complexity of read al- capitamt to a certain gene or transcripts of a gene is only not reduced .
  • sequence-specific selection methods e.g. by targeted sequencing of genomic regions such as particular exons .
  • the idea behind such capture arrays is to in ⁇ sert a selection step prior to sequencing. Those arrays are pro ⁇ grammed to capture only the genomic regions of interest and thus enabling users to utilize the full capacity of the NGS machines in the sequencing of the specific genomic regions of interest. Low density, on array capture hybridization is used for sequenc ⁇ ing approaches. Such technology is not "hypothesis neutral", as specific sequence information is required for the selection pro ⁇ cess.
  • a similar positive selection can be used for targeted re- sequencing.
  • biotinylated RNA strands of high specificity for their complementary genomic targets can be used to extract DNA fragments for subsequent amplification and sequence determi ⁇ nation. This form of complexity reduction is necessarily based on available sequence information and therefore not hypothesis neutral .
  • Sequencing of 16S rDNA or 16S rRNA sequences from mixed samples of microorganisms is in general employed for detection of rare species within these samples. By restricting the sequencing approach to a specific signature of microorganisms both complex ⁇ ity and information content are reduced. Frequently only phy- logenetic information is obtained.
  • Tag-based identification of transcripts includes SAGE (Se ⁇ rial Analysis of Gene Expression) wherein sequence tags of de ⁇ fined length are extracted and sequenced. Since the initial creation of tag concatemers is a disadvantage for NGS, derived protocols are used omitting this step.
  • CAGE Cap Analysis of Gene Expression
  • Armour et al . (Nature Methods, 6 (9) (2009): 647) relates to the generation of a cDNA from an RNA pool for sequencing.
  • NSR not-so-random
  • the present invention provides a method of order ⁇ ing nucleic acid molecule fragment sequences derived from a pool of potentially diverse RNA molecules comprising
  • nucleic acids • optionally once or more further segregating nucleic acids from said template RNA or cDNA, selectively segregating nu ⁇ cleic acids with a different distinctive nucleic acid fea ⁇ ture, thereby providing one or more further subpool (s) of nucleic acids,
  • the inventive segregation step has the advantage that sub- pools of nucleic acids are provided and this subpool information can be used to improve further sequencing reactions, e.g. Next Generation Sequencing which is based on obtaining reads of small fragments of the nucleic acids or other nucleic acid characteri ⁇ zation methods. It is possible with the inventive method that the subpool information can accompany the nucleic acids and the fragments and this information is used for alignment of the se ⁇ quencing reads and the determination of the concentration of an individual nucleic acid sequence within the subpool.
  • Next Generation Sequencing which is based on obtaining reads of small fragments of the nucleic acids or other nucleic acid characteri ⁇ zation methods. It is possible with the inventive method that the subpool information can accompany the nucleic acids and the fragments and this information is used for alignment of the se ⁇ quencing reads and the determination of the concentration of an individual nucleic acid sequence within the subpool.
  • subpooling can reduce complexity to such a degree that transcripts of an organism and/or transcripts of different cells or cell populations and/or transcripts of different organisms that are present in a sample in different concentrations can be segregated in order to increase the likelihood of detecting rare nucleic acids within the sample of abundant RNA entities.
  • Fur ⁇ thermore it allows the detection and identification of sequenc ⁇ ing reads belonging to different transcript variants, such as splice variants.
  • ii) provide means for coupling the sub-pool specific in ⁇ formation to the nucleic acids and fragments thereof
  • the method is suitable to measure quantitatively sequences and fragments thereof from the very rare to the highly abundant forms.
  • the core of this invention is the sorting of a nucleic acid pool into sub-pools prior the fragmentation step (e.g. required by NGS) , where all nucleic acids fragments acquire the addi ⁇ tional sub-pool information of their parental molecule.
  • This in ⁇ formation can be maintained throughout the sequence reading, e.g. partial sequence determination.
  • every read contains the sequence and the sub-pool information, which provides main advantages during the read alignment procedures.
  • the sub-pooling of transcript pools can be achieved through sub-pools with different additional information content.
  • the gained benefits depend on the chosen methods.
  • Segregation into subpools can be performed by exploiting transcript properties as distinctive nucleic acid feature which are directly or indirectly sequence related.
  • Such properties are for example the affinity to adsorbing matters like various col ⁇ umn materials (e.g. silica gel) or the solubility in the pres ⁇ ence of salts, polymers or other additives.
  • the required information on the sample nucleic acids is limited, e.g. precipitation depends pre ⁇ dominantly on length, the GC-content and secondary structures.
  • the distinctive nucleic acid feature can be an adsorption or solubility property.
  • sub-pools can be generated through methods which utilize distinctive sequence information like i) partial internal or terminal sequences or/and ii) tran ⁇ script size.
  • a distictive nucleic acid feature can be a partial sequence of the nucleic acids stemming from the template RNA or cDNA.
  • the dis ⁇ tinctive sequence can be a single nucleotide type (e.g selected from A, T, U, G or C) or more at a specific position within the nucleic acids to be segregated.
  • nucleotides can be segre ⁇ gated for the presence of one or more nucleotide types or se ⁇ quences at either the 5' or 3 ' terminus or in a given distance from said terminus.
  • probes which covers one or more sequence possibilities of said distinctive portion of the nucleic acid, can be used to create sub-pools. Even if sub-pools contain different nucleic acids and some nucleic acids will be present in several sub-pools, such segregation approach already reduces the complexity of the orig ⁇ inal pool.
  • the transcripts After collecting all reads it is known to the alig ⁇ nment algorithm that the transcripts contain the subpool specific sequence (s), preferably the alignment algorithm must ensure, that all transcripts display at least one sub-pool specific se ⁇ quence .
  • Segregation by selecting for a distinctive nucleic acid fea ⁇ ture like a distinctive sequence can be performed by either selecting such nucleic acids with the distinctive sequence or by specifically amplifying nucleic acids with said distinctive sequence and further utilising these am- plicons in the inventive method.
  • a preferred segregation method uses the sequence information of both termini, thus start and end site of the nucleic acids. After termini-specific amplification and if the redundancy in the sequence specificity is zero (no mismatch allowed) , then all sub-pools contain amplicons, e.g. PCR products, with exactly those termini. Hence, sub-pools can contain several nucleic ac ⁇ ids of RNA molecules such as transcripts, but each nucleic acid is only presented in one sub-pool. By this means, the complexity of the alignment procedure is largely reduced.
  • RNA molecule size can be exploited to segregate the RNA according to the number of nucleotides per RNA via electro ⁇ phoresis techniques (gel or capillary electrophoresis) , or other methods.
  • electro ⁇ phoresis techniques gel or capillary electrophoresis
  • the later alignment of the different reads per sub-pool can benefit from the boundary condition of a certain rather narrow size range.
  • nucleic acid molecule derived from an RNA molecule refers to a nucleic acid of any type with the same se ⁇ quence as the RNA from the sample.
  • full length or complete nucleic acids are segregated or selected from the template RNA or cDNA pool.
  • Segregation of full length or complete nucleic acids at this step, prior to fragmenting, has the benefit that each segregated pool contains the sequence in ⁇ formation of entire nucleic acids - even after fragmenting - which improves assembly of the sequence after sequence determi ⁇ nation.
  • sequence variation such as RNA editing or concentration differences between such transcript variants can be detected.
  • differences can be compared between different samples. Of particular relevance are such comparisons between phenotypically different samples, to investigate the underlying causalities for this phenotype.
  • “Full length” or “complete” in this context reads on the com ⁇ plete nucleic acids that are to be sequenced, e.g. as obtained after reverse transcription. It may comprise sequences of RNA starting from the 5' cap end up to the, but in most cases ex ⁇ cluding the poly A tail, but may also relate to nucleic acids that are incompletely (reverse) transcribed, however without be ⁇ ing artificially cut, e.g. by using endonucleases .
  • the RNA was degraded or fragmented or digested by nuclease activity and the cDNA molecules derived from such RNA is only a partial sequence.
  • the cDNA can be a partial copy of the RNA, e.g. oligo dT primed reverse transcription of mRNA is stopped before a full length cDNA copy is polymerized. This can be achieved through e.g. time restriction or through conditions where the reverse transcriptase stops polymerization at regions of secondary structure.
  • a fragment can then be segregated by a common feature, e.g. the sequence preceding the poly A tail of an mRNA.
  • the pool of cDNA con ⁇ tains nucleotides of the transcription start and/or end site, e.g. the first 25 and/or last 25 nucleotides.
  • the pool of cDNA may also only consist of such first and/or end nucleotides.
  • CAGE Shiraki-2003
  • 20 nucleotide tags are created that represent the 5' end of mRNAs .
  • such an approach will preclude the assembly of full length transcripts or the de ⁇ termination of their concentration.
  • tags can be used to determine expression on a whole gene level, meaning the concentration of all transcription start sites can be measured.
  • RNA sequencing depth increases and low level expressed genes will be more like ⁇ ly represented in the reads.
  • highly abundant tran ⁇ scripts will still be more often sequenced than low abundant transcripts. Therefore a segregation approach will increase the likelihood of low abundant start sites to be detected.
  • the short 5' tag sequences that are used to prepare a CAGE library can be segregated into fields of a matrix according to nucleotides on the 5' and/or 3' ends of such tag sequences.
  • RNA, a cDNA thereof or other nucleic acids e.g. RNA fragments, cDNA fragments or amplified nucleic acids therefrom.
  • the segregation step can be optionally repeated to obtain a different subpool with a different characterizing nucleic acid feature.
  • This generation of further subpools can be performed sequentially or parallel to the generation of the first or other subpools .
  • the present invention in essence is a combination of select ⁇ ing a pool of diverse RNA molecules, optionally generating cDNA, segregating the RNA or the cDNA, or any other nucleic acid derived therefrom, e.g. after amplification, optionally repeating the segregation for different parameters and fragmenting these segregated nucleic acids obtaining a pool of fragments.
  • a frag ⁇ ment is considered a nucleic acid portion of shorter length than the complete nucleic acid molecule from which it is derived.
  • Such fragments can be e.g. forwarded to Next Generation Sequenc ⁇ ing approaches or other nucleic acid characterization methods.
  • NGS is currently the foremost complete analyzing method. How ⁇ ever, the present invention is neither limited nor dependent on NGS.
  • Other sequencing technologies can similarly benefit from the inventive segregation method.
  • nucleic ac ⁇ ids Often not solely the complete sequencing of the nucleic ac ⁇ ids is required to clearly characterize a certain sub-pool dis ⁇ tribution. Any other methods like specific interaction with molecular probes or melting behavior can be applied to describe the original nucleic acid pool through a unique signature.
  • molecular probes can be hybridization probes such as oligonucleotides that can hybridize to complementary se ⁇ quences.
  • hybridization probes such as oligonucleotides that can hybridize to complementary se ⁇ quences.
  • Such principle is used in microarray analysis to inves ⁇ tigate the expression of a large number of genes simultaneously.
  • the most detailed analysis of gene (DNA) expression possible with such cDNA or oligonucleotide microarrays are exome or spli- cosome analysis.
  • the assignment of a signal to a particular transcriptvariant of a gene is not possible.
  • each subpool can be analyzed separately with a microarray.
  • the signal must belong to at least two different transcripts. This is of particular relevance when comparing the expression of different samples. Some differences in expression that cannot be distinguished without segregation prior to analysis can be de ⁇ tected if segregated. For instance a probe selective for a splice junction of a gene yields a relative signal of 100 in a first sample and 100 in a second sample. Therefore the expres ⁇ sion ratio is 1 and not difference would be attributed. After segregating each sample into, e.g.
  • transcriptome segregating the transcriptome in terms of segregat ⁇ ing transcripts from different genes as well as transcripts from the same gene into defined subpools is also a powerfull tool for the assembly of rather short sequence reads to longer or even full length sequences.
  • the invention improves the alignment of large numbers of individual sequencing reads to determine the sequence of nucleic acids and/or their copy num ⁇ ber .
  • the generation of fragment (partial) se- quences is done during the sequencing step, rather than first fragmenting and then sequencing such fragments.
  • a random (universal) primer is used to prime the sequencing reaction within a single molecule. Therefore the sequencing reaction will in most cases create a fragment sequence from within the mole ⁇ cule. If the molecule had a subpool specific label this label could be read out after the sequencing reaction, providing the fragment sequence with the subpool specific label.
  • the same mol ⁇ ecule could be subjected to further sequencing, thus providing a multitude of fragment sequences that can be assembled to a con- tig or a full length sequence of the nucleic acid molecule, the RNA or transcribed cDNA.
  • nucleic acid can be pre ⁇ sent in multiple copies, such sequencing could be done also in parallel.
  • a multitude of random (or universal) primers prime the sequencing reaction of a multitude of nucleic acid molecules producing a multitude of fragment sequences that as a whole can be used to align or assemble the sequence of the seg ⁇ regated nucleic acids.
  • fragments are ligated to each other prior to sequencing.
  • Nucleic acids are linear polymers of single nucleotides. These molecules carry genetic information (see triplet code) or form structures which fulfill other functions in the cell (e.g. regulation) .
  • the nucleic acids which are analyzed by the present invention are ribonucleic acid (RNA) .
  • RNA (sequencing) analytics is a particular difficult task due to the complexity of RNA pop ⁇ ulations in single cells.
  • the invention relates to the identifi ⁇ cation (particular sequence determination) of all types of RNA in a cell, including mRNA (transcripts) , microRNA, ribosomal RNA, siRNA, snoRNA.
  • the transcriptome is the set of all RNA molecules, or "tran ⁇ scripts", produced in cells. Unlike the genome, which is roughly fixed for a given cell line, the transcriptome varies with the kind of cell, tissue, organ and the stage of development. It can alter with external environmental conditions. Because it in ⁇ cludes all transcripts in the cell, the transcriptome reflects the genes that are being actively expressed at any given time, and it includes degradation phenomena such as transcriptional attenuation. Transcriptomics is the study of transcripts, also referred to as expression profiling.
  • An inventive benefit in us- ing the inventive segregation method on RNA samples is that transcripts with low copy numbers or any other type of RNA which is present in the sample in a low concentration has an increased chance to be sequenced and analyzed in the subpool.
  • One drawback of Next Generation Sequencing is that highly abundant nucleic acids reduce the chance that fragments of low concentration are sequenced.
  • the inventive segregation allows the differentiation of high copy number entities with low copy nucleic acids. Thus preventing that such low copy nucleic acids are excluded from detection - or in any other preceding step such as e.g. during amplification .
  • the general principle is to reduce the complexity of a pool of nucleic acids by sequencing smaller segregated portions.
  • the ⁇ se smaller portions are called sub-pools.
  • all sub-pools together contain all nucleic acids to be ana ⁇ lyzed of the original pool.
  • the first factor is determined by the combined length of the individual different sequences. Because the sequence is encoded through 4 bases (T and U are considered equivalent for carrying the same information) the complexity increases as a variation, equal to four to the power of length. However genomes contain redundant information like repeats or any other kind of order, e.g. that arises through the evolution of genes. Therefore dif ⁇ ferent genes can contain stretches of the same or very similar sequences. This creates ambiguity in the de novo assembly of contigs or full length transcript sequences and limits the length of contigs that can be built. Even in alignment processes where a reference sequence is available such ambiguity restricts the alignment of individual reads. This ambiguity increases with decreasing read length of the sequencing process.
  • transcripts from the same gene sometimes referred to as tran ⁇ scriptvariants
  • splice variants are very similar in terms of sequence composition. Therefore most reads arising from transcriptvariants cannot uniquely be assigned. E.g. even if a splice junction is detected, it is not known if such a junction belongs to one or more transcripts.
  • the second factor is determined by the number of different sequences within a sample.
  • the complexity increases with the number of permutations, therefore with the factorial of differ ⁇ ent sequences.
  • Two sequences have two possibilities to arrange, three sequences have six possibilities and so forth.
  • the third factor is the difference in copy numbers (tran ⁇ script concentrations) and to lesser degree the amount of pre ⁇ cognition about these differences, e.g. if it is known that the difference of certain copies is in the order of 1/1.000.
  • Each different sequence belongs to a group which is characterized of having one particular copy number. The level of distribution of these groups determines the complexity which is introduced through concentration differences.
  • the inventive segregation can help to distinguish different RNA molecules of the original sample pool.
  • This segregation step can also be repeated once or more.
  • Repetition herein shall not be interpreted that additional segregation steps have to be per ⁇ formed after the first segregation step - which is of course one option - but also relates to performing one or more segregation steps simultaneously.
  • one or more subpools are generated and in each subpool specific nucleic acids are present (or en ⁇ riched) which share a common feature and all other nucleic acids without that shared distinctive nucleic acid feature can be ex ⁇ cluded from each pool (or at least are not enriched) .
  • the general principal of the present invention is the constituting of sub-pools where these factors can be controlled, and simultaneously the complex ⁇ ity of the pool reduced, before sequencing reads are generated.
  • the method simplifies the in-line sequence alignment.
  • Sub- pools emerge through segregation methods which are within the scope of this invention.
  • the meth ⁇ od further comprises determining the sequence or a partial se ⁇ quence of the fragments of the first subpool and optionally fur ⁇ ther subpools.
  • This sequence of the fragments or a portion thereof can be determined by any suitable method known in the art. Preferred are sequence determination methods that can be scaled to high throughput sequencing methods, in particular Next Generation Sequencing. In such a method sequence length of at least 5, preferably at least 8, at least, 10, at least 15, at least 18, at least 20, at least 22 nucleotides of the fragments or more can be determined. Preferably the full length sequence of the fragments are determined. If only portions of the frag ⁇ ments are sequenced this can be either portions of the 5' or the 3 ' end or internal portions which can be selected for with spe ⁇ cific or unspecific (e.g. random) primers.
  • Determining a partial sequence of a nucleic acid preferably comprises determining a sequence portion of at least 10, pref ⁇ erably at least 15, at least 18, in particular preferred at least 20, even more preferred at least 25, nucleotides but ex ⁇ cludes determining the complete sequence of the nucleic acid. According to the present invention it is possible to either generate fragments of the segregated nucleic acid molecules by fragmenting or obtaining fragment copies (e.g.
  • amplifying portions of the nucleic acid molecules and subsequently determine the sequences thereof or to determine a sequence or partial se ⁇ quence of a fragment of said segregated nucleic acid molecule and, preferably align at least 2, preferably at least 3, in par ⁇ ticular preferred at least 4, at least 6 or at least 8 sequences or partial sequences to a joined sequence.
  • it is not necessary to physically provide such fragments but possible to only obtain sequence portions which can be de ⁇ termined from the nucleic acid molecules themselves without a physical fragmenting step and create a joined sequence by align ⁇ ing such partial sequences.
  • the information about the sub-pool origin escorts the nucleic acid molecule and each of its fragments during the sequencing run.
  • the sub-pool information can be passed on through labeling. Every fragment may receive an identifying nucleotide sequence (e.g. adding a subpool specific se ⁇ quence tag of e.g. 1, 2, 3, 4, 5, 6, 7, 8 or more subpool re ⁇ lated nucleotides) , reporter module like a fluorescent dye, na- no-dots, or others.
  • the subpool specific label is a nucleotide sequence (barcode) that is added to the fragment.
  • the barcode is read out after or during sequencing the nucleic acid fragment.
  • the sub-pool information can be perpetuated through spatial or temporal separation, which means that each sub-pool is sequenced in a different area (cluster on a slide) in the ma ⁇ chine or discriminating time slot, e.g. each subpool may be se ⁇ quenced sequentially. No additional process conduct is needed for most of those procedures.
  • the reporter signal has to be identi ⁇ fied and connected to the read.
  • the individual sub-pools can be sequenced separately. Reads of each sub-pool are aligned either to the genomic blue print, or they are aligned de novo by comparing them with all other reads within the same sub-pool and not the total pool. There ⁇ fore, the complexity of the original sample pool is greatly re ⁇ cuted .
  • RNA molecules in particular transcripts, interfere only in one sub-pool of their appearance and so compromise its reading depth, but not the rest of the subpools. Because the probability of reading individual fragments is proportional to their relative concentration within the pool or sub-pool respec ⁇ tively, fragments which are present in just a thousandth will on average only be read once while having read the other frag ⁇ ment (s) thousand times.
  • all reads are grouped, and where possible oriented according to their sub-pool address.
  • all reads are aligned to each other or to the blue-print se ⁇ quence data base.
  • the alignment must fulfill all boundary condi ⁇ tions, if e.g. further information of the complete sequence such as length is known in addition to the sub-pool information.
  • fragments i.e. smaller nucleic acid mol ⁇ ecules with portions of the original nucleic acid, and determine the sequence or a portion therefrom.
  • "Generating fragments of said segmented nucleic acid molecules" thus, also relates to ob ⁇ taining a fragment which contains any kind of sequence portion. Fragmenting can be by e.g. physical means be either in a se ⁇ quence dependent way, e.g by endonuclease digestion or by se ⁇ quence independent means such as by a physical means like soni- cation or shearing. Generating the fragments further relates to obtaining fragment copies.
  • the nucleic acid molecule can be e.g. amplified to further copies which are in turn fragmented. If a random fragmenting process is used this can result in generation of different fragments for each nucleic acid molecule.
  • a sequence dependent method e.g. re ⁇ striction endonuclease digestion or sequence specific amplifica ⁇ tion all fragments of one nucleic acid molecule will be the same.
  • Example sizes of the frag ⁇ ments or determined partial sequences are e.g. at least 10, at least 20, at least 25, at least 30, at least 35, at least 40 nu ⁇ cleotides.
  • Fragments or determined partial sequences can be up to 20,000, up to 10,000, up to 5,000, up to 4,000, up to 3,000, up to 2,000, up to 1,000, up to 800, up to 700, up to 600, up to 500, or up to 400 nucleotides long.
  • the preferred ranges are of 10 to 10,000 nucleotides, preferably of 25 to 500 nucleotides.
  • fragments are joined prior to sequencing. It is preferred that such joined fragments are interspersed by different sequence stretches that allow sequencing primers to prime consecutive rounds of sequenc ⁇ ing .
  • the segregated nucleic acid molecule or the nucleic acid molecule to be segregated can be either single stranded or dou ⁇ ble stranded.
  • single stranded molecules are seg ⁇ regated the strandedness of a fragment in relation to its parent molecule is clear as it has a 5' and a 3' end.
  • double stranded nucleic acid molecules are used then there needs to be a distinguishing property on one strand but not the other (e.g. methylation) as the double strand has a 5' and 3' end on both strands.
  • one of the two strands can be used for fragmentation.
  • One of the two strands can be se ⁇ lected for by any means known to the art.
  • the end of one strand can be labeled during the segregation.
  • one of the PCR primers may contain a labeling group such as biotin and be selected for afterwards using column chromatography with an avidin coupled matrix.
  • Another possibility is to use one primer that has a 5' phosphate and another primer that has no 5' phosphate and subject the PCR products to a lambda exonuclease that preferentially will digest the strand that has a 5' phos ⁇ phate.
  • a lambda exonuclease that preferentially will digest the strand that has a 5' phos ⁇ phate.
  • the strandedness or strand information is preserved, preferably by selecting for one strand, e.g. through a lambda nuclease digest of the other strand. It is possible during segregation to select one strand to be segregated (either the sense or anti-sense strand) or to label the selected strand in order to maintain strand informa ⁇ tion. Preferably the fragments of the selected strand are la ⁇ beled according to the strand information and possibly also for pooling information (e.g. bar-coding as mentioned above).
  • At least 2, 4, 5, 6, 7, 8, 9, 10, 12, 14, 16, 18, or at least 20 nucleotides, in particular consecutive nucleotides of these fragments are sequenced.
  • the original pool of potentially diverse RNA molecules can be of any source, in particular of any biological sample, pref ⁇ erably of a virus, prokaryote or eukaryote.
  • the inventive com ⁇ plexity reduction method is important for any sorts of RNA se ⁇ quencing approach, even when using a single cell which contains a diverse transcriptome but of course also samples which contain more than one cell, in particular samples of diverse origin, e.g. containing many different cells of diverse organisms or similar cells with different or modified gene expression (e.g. tumor cells) .
  • the nucleic acid feature used for segregation is a given nucleotide type, preferably selected from any one of A, T, U, G, C, at a certain position in the nucleic acid molecule, prefera ⁇ bly the position being within 100 nucleotides from either the 5' or 3' terminus or both of the nucleic acid molecule.
  • the inventive segregation step may thus comprise seg ⁇ regating nucleic acids from said template RNA or cDNA pool, se ⁇ lecting for potentially different templates with at least one given nucleotide type at a certain position being within 100 nucleotides from either the 5' or 3 ' terminus of the full length template nucleic acid molecule sequence shared by the segregated templates, thereby providing at least a first subpool of nucleic acids .
  • RNA or cDNA containing one or more further nucleotides specificities which act to segregate the nucleic acid molecules according to the complementary nu ⁇ cleotides after the (universal or wobble) primer portion.
  • primer specific for the ends, e.g.
  • the primers can be specific for the next 1 to 100, pref ⁇ erably 1 to 10 nucleotides, e.g. the next 1, 2, 3, 4, 5, 6, 7, 8, 9 or 10 nucleotides.
  • the specific distinguishing nucleo ⁇ tides are within the first 100 nucleotides from either the 5' or 3' terminus of the nucleic acid molecule. It is of course also possible to use primers to select any internal region wherein the nucleic acid molecules can be separated in the segregation step .
  • the nucleic acid molecules are selected for com ⁇ mon nucleotides within the 10 nucleotides next to the 5' and/or 3' terminus, preferably for one or more common 5' and/or 3' ter ⁇ minal nucleotide types.
  • primers or probes preferably are used in combination with primers or probes which are selected for a different nu ⁇ cleic acid feature.
  • Such primers can e.g. be used separately or sequentially to generate subpools specific for the nucleic acid feature.
  • primers or oligonucleotides used in a combination can e.g. be primers which have a universal part and a distinguishing part wherein the distinguishing part is e.g. A in the first primer, T in the second primer, G in the third primer and C in the fourth primer.
  • the combination can e.g.
  • nucleic acid feature contains 3 or more, e.g. 4, 5, 6, 7, 8, or more specific nucleotide types.
  • combinations of primers are oligonucleotides select ⁇ ing for distinguishing nucleotides at both the 5' and/or 3' terminus, e.g. both primers or probes being specific for the two or more 5' nucleotides and the two or more 3' nucleotides.
  • the nucleic acid feature that is used for segregation is used during the assembly (or alignment) of short reads as a qualifying property of the assembled (or aligned) sequence. For instance if the nucleic acid feature was a certain length or length range then the qualifier for a correctly assembled sequence would be such length or length range. If the nucleic acid feature was a certain sequence then when se ⁇ quencing fragments of this nucleic acid, that are e.g. 36 bases long, then in addition to the 36 bases another n bases are known for each fragment, where n is the number of bases of the nucleic acid feature.
  • nucleic acid feature was 6 known bases on the 5' side and 6 bases on the 3' side of the molecule then in addition to the 36 bases of each fragment 2x6 bases are known to be within a certain distance (the length of the fragmented molecule) from the sequenced fragment. Therefore if the nucleic acid feature was a certain sequence then this se ⁇ quence must be again contained within the assembled sequence. It is preferred that the nucleic acid feature is at a certain posi ⁇ tion of the segregated nucleic acids, preferably at a certain distance from the 5' or 3' end of the template RNA or cDNA.
  • the nucleic acid feature is a sequence and the se ⁇ quence is used during assembly.
  • the nucleic acid feature may comprise two sequence portions, e.g. of 2, 3, 4, 5, 6, 7, 8, 9, or 10 known nucleotides, positioned in a certain base distance, e.g. in a distance of e.g. 20 to 10000 nts, preferably 30 to 5000 nts, in particular preferred 50 to 1000 nts.
  • the segregated nucleic acids con ⁇ tain the full length sequence of the template RNA or cDNA. This will greatly increase the de novo assembly of contigs or even full length sequences as all fragment reads generated during a sequencing process can be aligned within a subpool, i.e. with the fragment or partial sequences obtained from one subpool.
  • the nucleotides of the 5' and/or 3' end of the template full length RNA were used as the nucleic acid feature ( s ) for seg ⁇ regation, the nucleotides of the start and/or end site of the full length RNA molecule are known for all fragments of such subpool. Such information allows e.g. to position fragments or their assembled contigs correctly on the plus or minus strand of the genomic DNA, thus separating sense and antisense transcripts of a gene.
  • the RNA molecule used ac ⁇ cording to the inventive method is a full length RNA. Full length RNA can e.g. be selected with the above mentioned method.
  • full length RNA or “full length cDNA” is defined as RNA or DNA that includes a se ⁇ quence complementary to the RNA sequence from the first base to the last base of the RNA.
  • a method is e.g. disclosed in WO 2007/062445 (incorporated by reference) and comprises amplifica ⁇ tion selective for end specific nucleic acid features e.g. by performing a segregated amplification or selection (as described herein) on full length RNA.
  • full length RNA is defined as RNA that includes a sequence complementary to the RNA sequence for the first base after the cap e.g. the RNA 7-methylguanusin cap to the last base before the tail, polyA-tail, of the RNA template.
  • RNA molecules By ordering a pool of RNA molecules into the inventive sub- pools it is possible to highly decrease complexity of the origi ⁇ nal sample, generating subpools with fewer nucleic acid entities and therefore increase the chance of detecting nucleic acids or successful sequencing and assembling afterwards.
  • the nucleic acids are divided into subpools wherein at least 10% of all subpools comprise the aver ⁇ age amount of nucleic acids of all subpools +/- 50%.
  • ⁇ a suitable segregation method for the given sample to divide the nucleic acids evenly into the subpools the complexity reduc ⁇ tion method is sufficiently used.
  • further subpools may exist wherein fewer nucleic acids are present, e.g. even empty subpools without any nucleic acids of the original pool which can be used as control reference.
  • at least 15%, at least 20%, at least 25%, at least 30%, at least 35%, at least 40% of all subpools comprise the average amount of nucleic acids of all subpools +/- 50%.
  • This error margin of +/- 50% is in preferred embodiment up to +/- 50%, up to +/- 45%, up to +/- 40%, up to +/- 35%, up to +/- 30%, up to +/- 25%, up to +/- 20%.
  • the sample comprises at least one, preferably two, 3, 4, 5, 6, 7 or 8 rare RNA molecules.
  • Rare can mean a con ⁇ centration of below 1%, below 0.5%, below 0.1%, below 0.05%, below 0.01% (lOOppm), preferably below 50ppm, below lOppm, below 5ppm, below lppm, below 500ppb, below lOOppb or below 50ppb.
  • at least 1, preferably 2, at least 4, at least 6 or at least 8 rare nucleic acids are in the sample to be analyzed.
  • nucleic acids are divided in subpools wherein at least 10% of subpools contain 2 or less nu ⁇ cleic acids, preferably 1 nucleic acid.
  • Such a high dilution is in particular favorable for very rare nucleic acids that would be hard to detect if further nucleic acids would be present from the original pool, in particular in the original concentration.
  • the step of segregating the nucleic acids comprises specifically amplifying the nucleic acids from said template pool.
  • the amplification is performed by nucleotide extension from a primer, preferably by PCR, in particular preferred wherein the amplification is performed by nucleotide extension from a primer, preferably by PCR, in particular preferred wherein the amplification is performed by using primers which select for at least one, prefera ⁇ bly at least two, in particular at least two adjacent, different nucleotides after an unspecific primer portion whereby nucleic acid molecules are amplified which comprise the selected nucleo ⁇ tide as the nucleic acid feature specific for a subpool.
  • the above mentioned fragmentation step of the inventive method may be the first step used for sequence determination steps.
  • Determining the sequence of the nucleic acids of the sub- pool may comprise, fragmenting the nucleotide molecules of the subpool as mentioned above, attaching a subpool specific label to each fragment of a given subpool, determining nucleotide se ⁇ quences of fragmented polynucleotides of combined pools (or al ⁇ ternatively determining nucleotide sequences of separate pools with or without attaching a label) , assigning fragment sequences to a nucleotide molecule depending on a subpool-specific label and overlapping sequences with other fragments, thereby deter ⁇ mining the sequence of the nucleic acids.
  • subpool-specific labels are attached to the fragments.
  • the subpool-specific labels can be nucleotides, which are preferably co-determined during sequence determination .
  • nucleic acids of the original pool are divided into at least 2, preferably at least 3, at least 4, at least 5, at least 6, at least 7, at least 8 subpools during the segregation step, which nucleotides each share a different nucleotide characteristic for each subpool.
  • primers or probes used for select ⁇ ing nucleic acids in the segregation step are preferably immobi ⁇ lized on a solid surface, in particular a microarray or chip.
  • the same type of segregation as described above for the distin ⁇ guishing the nucleic acids can also be performed for distin ⁇ guishing different fragments during the sequencing step.
  • the inventive method further comprises amplifying the nucleic acid molecules, pref ⁇ erably after segregation, prior to determining the sequence, in particular preferred wherein said amplification is by PCR and at least one nucletide molecule is amplified to the saturation phase of the PCR. In particular preferred at least 10% of the different nucleotide molecules are amplified to the saturation phase of the PCR.
  • Such an amplification reaction can be used to normalise the concentration of nucleic acid molecules in the pool or sub-pool.
  • a PCR reaction e.g. has an exponential phase in which the nucleic acid molecules are essentially doubled in each PCR cycle.
  • reaction components such as primers, dNTPs are used up. This phase is called the saturation phase.
  • telomeres Preferably, highly abundant nucleic acid molecules reach this saturation phase and are inhibited from amplification whereas low abundant molecules continue amplifying exponen ⁇ tially. Preferably at least 10%, in particular preferably at least 20% of the different nucleic acid molecules enter this saturation phase.
  • qPCR quantitative PCR
  • said re ⁇ actions occur in normal PCR reactions (but may be unmonitored) or other amplification reactions with self inhibition, e.g. after 20, 22, 24, 26, 28, or 30 amplification cycle, which are preferred minimum cycle numbers for the inventive amplification.
  • the inventive sub-pooling procedure can also be used to re ⁇ move high copy transcripts, e.g. exclude sub-pools with high abundant nucleic acid molecules from sequence determination.
  • such sub-pools with high abundant nucleic acid mole ⁇ cules that are excluded from sequence determination are sub- pools comprising more than 100%, particularly preferred more than 150%, even more preferred than 200%, particularly preferred more than 300%, e.g. more than 400%, such as more than 500%, particular preferred more than 1000%, nucleic acid molecules above the average amount of all sub-pools which may contain all the nucleic acid molecules of the sample.
  • Such sub-pools can e.g. be subpools which comprise nucleic acid molecules that con ⁇ stitute e.g.
  • Abundant transcripts to be excluded or normalized by this way are e.g. of housekeeping genes, GAPDH, actin, tubulin, RPL1, ribosomal proteins, or PGK1.
  • Fig. 1 Workflow of the Segregation-NGS method for RNA.
  • Fig. 2 Simulation of the number of genes as function of the mRNAs (total copy numbers of all gene transcripts) through a log-log-normal function. Active genes G, 16,657, total tran ⁇ scripts T, 3.8 Mio, most common transcript number, 10, scale value of the log-log-normal function ⁇ , 1 and shape parameter ⁇ , 0.4.
  • Fig. 3 Exponential decay function describing qualitatively the relationship of the number of transcripts vs. genes accord ⁇ ing to parameters t sta rt / 33, t en c 1/ the sum of all genes, 25, 200 and a 4-fold amount of transcripts (100,269) .
  • Fig. 4 Exponential decay function describing dependency of the mRNAs (copy number) vs. transcripts according to parmeters cstart, 10, 000, c e nc 1 / decay constant ⁇ of 0.0522, the sum of all transcripts is 100,128 and the sum of all copy numbers is 3.8 Mio.
  • Fig. 5 General subpooling and fragmentation workflow.
  • Fig. 6 General principle using nucleotide specific amplifi ⁇ cation (segregation) .
  • the first two nucleotides at the 5' end used to define the subpools also become the se ⁇ quence tag.
  • Fig. 7 RNA matrix segregation.
  • fragments F2 and F4 are sequence identical and could not be distinguished unless the segregation into the sub-pools was performed (see step 10) .
  • Adding a linker sequence to the 5' end of the mRNA as shown in step 2 can be done by any methods known in the art, such as Oligo capping (Maruyama 1994) .
  • Fig. 8 Creating fragments by random primed polymerization Steps 1 to 4 are the same as in Fig 9. Shown is only subpool n.
  • Sn in step 6 represents the subpool specific tag.
  • Fig. 9 Random primed sequencing, producing fragment reads. Steps 1 to 4 are the same as in Fig 7. In this example the mole ⁇ cule x of the subpool n is double stranded, each strand can serve as a template for sequencing. The random primer is bound to the surface of the sequencing chip. Single strands of each molecule of a subpool are hybridized to the primers on the chip. As the random primers can hybridize to any part of the molecule, the sequencing will produce "fragment" reads from the molecule.
  • Fig. 10 Comparison of mouse genomic coverage which has been obtained by NGS read alignment from one non-segregated sample (set A) and one segregated sample (set B) of a 6 out of 12 sub- pool matrix (lxl) .
  • the consensus length (y-axis) describes the total length of uniquely detected sequences. On the x-axis the sum of reads in gigabases is depicted. The average read length was 65 nucleotides.
  • the dashed line connects data points which have been obtained by randomized drawing read subclasses and aligning them separately to the mouse genome. The solid line is on inter- and extrapolation of the data points.
  • GC genomic coverage .
  • Fig. 11 Scatter-plot comparing expression of genes in one subpool (subpool 6) versus the 6 combined subpools from set B in example 1.
  • Gene expression is depicted in snRPKM, that is RPKM (Mortazavi 2008) normalized to the sum of all reads in all 6 subpools. A randomized draw of 10% of all values was chosen to dilute the number of datapoints for better visualization.
  • the diagonal lines in the double logarithmic scale depict the seg ⁇ ments of the sixth parts. Shown in the graph is the central sec ⁇ tion with snRPKM values between 0.01 and 1000. The 6 values above the 6/6 line are caused by the ambiguity of the alignment algorithm used by CLC software.
  • Fig. 12 The subpool distribution of the 15 most abundant genes of set B in example 1 is shown. Genes are represented in different concentrations in different subpools, showing that transcript variants of different genes are segregated represent- ing different transcript variant concentrations.
  • Fig. 13 Transcription start site analysis of gene Nmnt with start sites assigned by reads of RNA-seq, 0 and lxl matrix ex ⁇ periments.
  • the genome annotation is schematically drawn and shows the start region of Nnmt . Individual reads are depicted with their respective position. The relative frequency of base reads corresponds to the dark grey area in the line "frequency of the read sequences".
  • Example 1 cDNA segregation by end-specific matrix separa ⁇ tion followed by NGS analysis.
  • oligonucleotides used see ta ⁇ ble 1.
  • RNA of a mouse (C57B1/6) liver sample was primed by an oligo that contains a V (being either C,G or A) anchored oligo-dT sequence (Seq-2; Linker2-T 2 7-V) at its 3' end and was reverse transcribed to generate cDNA.
  • a linker se ⁇ quence was added during the reverse transcription reaction to the 3' end of the cDNA through reverse transcribing a template switch oligo (Seq-1; Linkerl) (US 5962271, US 5962372) .
  • the 5' end of the generated cDNA comprises a polyT-stretch intro ⁇ pokerd by the oligo which corresponds to the mRNA' s original polyA-tail plus the Linker2 sequence.
  • the 3' end of the cDNA comprises the reverse complement to the Linkerl sequence pre ⁇ ceded by an additional C nucleotide that is added cap dependent. Two different sets of samples were prepared for sequencing.
  • the single sample of comparative set A (without segregation; 0 matrix) was prepared by PCR-amplifying in a 50 ⁇ reaction about 27 pg of cDNA to a level of about 800 ng using primers that hybridize to the template switch sequence (Seq-3; Linkerl) at the 3' end and the polyT sequence at the 5' end of the cDNA (Seq-4, Linker2-T27) .
  • the template switch sequence Seq-3; Linkerl
  • Seq-4 linker2-T27
  • Set B (with segregation) consists of 6 samples that corre- spond to 6 subpools of a 12 subpool matrix (lxl matrix) .
  • lxl matrix refers to 1 selective nucleotide at the 3' terminus of the cDNA and 1 selec ⁇ tive nucleotide at the 5' terminus of the cDNA. For each selec ⁇ tive nucleotide a segregation into pools for each of the four nucleotides is possible. However, if mRNA is used as template comprising a polyA-tail, the nucleotide next to the tail (or the corresponding polyT stretch on a cDNA) can only select for the other three nucleotides (thus this nucleotide can be used to segregate into 3 subpools) .
  • each of the 6 PCR samples of set B on average used a 1/12 of the cDNA as a template.
  • each of the PCR sample was fragmented (by sonica- tion) into fragments which were on average 200-1000 bp long. Af ⁇ terwards, the samples were subjected to a standard Illumina ge ⁇ nomic DNA sequencing sample preparation pipeline using an Illumina Genomic Prep Kit (#FC-102-1001; Illumina Inc., USA). In es ⁇ sence, adapters were added to the ends of the fragments, which were used to bind the samples to the flow cell. They allow for cluster generation and enable the hybridization of a sequencing primer to start the sequencing run.
  • the single sample of set A was loaded onto one channel of the flow cell and the 6 samples of set B mixed in equal amounts and loaded onto a second channel.
  • Cluster generation was carried out on a cBot Instrument (Illumina Inc., USA) using the Cluster generation Kit (#GD-203-2001, version 2; Illumina Inc., USA). Then a 76 bp sequencing run was carried out on a GenomeAnalyzer II (Illumina Inc.) using the Sequencing Reagent Kit (#FC-104- 3002, version 3; Illumina Inc., USA) .
  • the multiplex tags of the 6 samples of set B were read out using Multiplex Sequencing Primer and PhiX Control Kit (#PE400- 2002, version 2; Illumina Inc., USA).
  • the 5' primer sequences were trimmed off the reads, all er ⁇ roneous nucleotides (Ns) were clipped off the reads and reads below a threshold length of 20 nucleotides were excluded from further analysis.
  • the refMrna database was downloaded [1] on the 4 th of October 2009 from the UCSC Genome Browser webpage [6] and contains 24570 reference mRNA sequences that are based on the mouse genome as ⁇ sembly (mm9, NCBI built 37) . In order to investigate how many of these reference mRNAs could be detected without and with segre ⁇ gation an alignment of read set A and read set B to these refer ⁇ ence mRNAs was done.
  • 328358 GenBank mRNA sequences [5] were downloaded [2] on October 4 th , 2009 from the UCSC genomics browser database [6] . Applying the same CLC parameters as in a) set A and set B were aligned to these 328358 GenBank mRNA sequences. Using set A 83199 sequences could be detected and using set B 87794 sequences could be de ⁇ tected. This amounts to about 5% more mRNA molecules that could be detected when segregation was carried out before sequencing.
  • the complete reference mouse genome was downloaded [3] on the 4 tt of October 2009 from UCSC genome browser database [6] . Align ⁇ ments were made using the same CLC parameters as in a) and re ⁇ sulted in a genomic coverage of 0.494% for data set A and 0.561% for data set B (Fig. 10) . Therefore, set B detects about 13.5% percent more of the genome compared to set A. This translates to about 1835663 additionally mapped nucleotides. If the mean exon size for mouse is about 300-400 bases then about 4589 to 6118 additional exons can be detected.
  • fig. 10 demonstrates that the read alignment results in increased genomic coverage independent of the read depth, and that the same genomic coverage can be obtained with less read depth when using a segregated sample (set B) compared to a non-segregated sample.
  • set B segregated sample
  • transcript variants of individual genes are segre ⁇ gated into different subpools in relation to their concentration in the sample. For instance, a gene that is drawn in above the 5/6 line has one or more transcript variants in this subpool that account for more than 5/6 of the concentration of all tran ⁇ script variants of that gene.
  • Table 2 Distribution of the sum normalized RPKM (snRPKM) values per subpool resulting from respective 0.825 Mio reads in rela ⁇ tion to the sum normalized RPKM (snRPKM) values of entire 4.95
  • transcript variants into differ ⁇ ent subpools are different for each gene as shown exemplary in figure 12 for the subpool distribution of the 15 most abundant genes. This means that reads that map to the same gene and are found in different subpools belong to different transcript vari ⁇ ants that are potentially differentially expressed. f) Segregation of transcript variants of a single gene into subpools
  • Nnmt ENSMUSG00000032271
  • ENSMUST00000034808 the nicotinamide N-methyltransferase gene
  • RNA-seq protocol 185 reads could be mapped to the Nnmt gene of which none could be clearly attributed to a transcription start sequence (see figure 13) . Neither the two protein-coding transcripts nor any other transcripts could be distinguished with confidence.
  • a 0 matrix protocol (set A) mapped 3,266 reads re ⁇ sulting in a higher total RPKM value. Because of the linker se ⁇ quence tag (Linkerl), 105 reads were identified as start se ⁇ quences. 11 different starting sites were mapped with a 2 reads threshold. The remaining 3,161 reads, that had no Linkerl tag and thus are internal reads, could not be assigned to any of those 11 different transcript variations because of the missing segregation .
  • Linker se ⁇ quence tag (Linkerl)
  • Table 3 summarizes the detailed further analysis.
  • the 9 start sites distribute across 4 of the 6 subpools.
  • the number of start sites adds actually up to 11, but two of the start sites in related G/- and C/- subpools, G/G and G/C as well as C/C and C/G, are identical.
  • G/G and G/C As well as C/C and C/G, are identical.
  • C/C and C/G By investigating the identified start sites the assignment to subsequent larger matrices was in ⁇ vestigated.
  • a 2x1 has only 5 different start sites remaining in just 2 subpools, GT/C and GT/G. Expanding those two subpools into a 3x1 matrix enables the complete segregation of all de ⁇ tected start sites into 11 individual subpools.
  • Table 3 5' -start site analysis of Nmnt assigned 135 start site reads in a lxl matrix. The extrapolation of the subsequent 2x1 and 3x1 matrices reveal that the complete start site segregation can be achieved with a 3x1 matrix. ⁇ TS (2+ ) / ⁇ , sum of transcription start site that are detected by 2 or more reads to the sum of all reads.
  • experiment 1 shows that segregating mRNAs employ ⁇ ing even a small matrix (12 subpools) and furthermore using only half of such a matrix (6 out of 12 subpools) the detection of mRNAs significantly improves in a genomic as well as transcrip- tomic context.
  • Example 2 cDNA segregation through selective precipitation and downstream NGS.
  • a first step purified mRNA of a tissue sample becomes reverse transcribed and pre-amplified .
  • the pre-amplified cDNA is precipitated into different fractions by increasing PEG concentrations [8] .
  • PEG concentrations [8] 10 pools are prepared which contain cDNA with different solubility.
  • the solu ⁇ bility is manly influenced through the length of the cDNA.
  • the cDNA of the 10 different sub-pools is processed sepa ⁇ rately which involves fragmentation and labeling of each sub- pool with a sub-pool specific sequence tag. All fragments are transferred to the NGS platform and sequenced, reading out in addition the tag.
  • the reads are segregated according to the 10 different sub- pool tags. Now, in a first assembly contigs are built by align ⁇ ing reads within each subpool. In comparison, in a second assembly contigs are built neglecting the sub-pool information. More and longer contigs can be assembled using in the first assembly when contig building was done within each subpool, compared to the second assembly, where the reads where not separated into subpools .
  • mRNA of a tissue sample is electrophoretically sepa ⁇ rated on an agarose gel. After the densitometric characteriza ⁇ tion of the gel picture 12 bands are cut out. The bands hold about the same amount of mRNA. Each band is defined through one lower and one higher cut-off length according to the weight marker. The bands segregate all mRNA according to 1) 25-100bp, 2) 100-500bp, ... 12) 12000- ⁇ bp. The mRNA is purified from the gel bands, prepared separately for NGS sequencing adding a sequence tag to each of the 12 subpools. The 12 tagged subpools are mixed in equal amounts and sequenced in one lane on an Illumina Genome Analyzer II instrument.
  • the NGS provides 12 times 0.8 Mio reads.
  • the reads are aligned to each other under guidance of the known consensus genome with the aim to construct complete transcripts.
  • Transcripts not only have to oblige the sequence matches, in addition, each transcript must have a certain lower length and is not allowed to exceed a maximum length with re ⁇ spect to its band size sub-pool.
  • a second align ⁇ ment is done neglecting the sub-pool and size information.
  • the mean contig length of the first alignment is higher and the first alignment contains more full length se ⁇ quences than the second alignment.
  • Example 4 Computerized calculation of improvement.
  • Random sequences were generated using a Random Letter Se ⁇ quence Generator (http://www.dave-reed.com/Nifty/randSeq.html) and arranged in a data base, e.g. because of the small size it could be done in a spreadsheet, assembling the genes of the mod ⁇ el genome. All randomized numbers (e.g. gene and number of tran ⁇ scripts) were generated using a randomizer. Then, the genes were used to generate the model transcriptome according to the sta ⁇ tistical requirements illustrated trough the graphs in fig.2 to 4. Their total number is listed in column "trans" in table 5. To simplify matter, all transcripts are complete copies of their parental gene, so no variants are introduced yet.
  • a Random Letter Se ⁇ quence Generator http://www.dave-reed.com/Nifty/randSeq.html
  • the transcripts were ordered into 16 ( 4 x 4 ) different pools according to their terminal bases (table 6) .
  • transcriptome (all reads align to the blue print) is selected and any reading errors are excluded
  • a simple alignment algorithm simple search function which provides the number of sequence matches) could be used to probe the genome/transcriptome . It selects all reads that have a perfect k-mer match to the reference sequence (transcriptome) . So, 24 permutations of 4bp fragments (without any base repeats like AATG) were taken and aligned, once against the entire model ge ⁇ nome/transcriptome (tab. 5) and once against the segregated ge ⁇ nome/transcriptome (tab. 6) . The number of unique hits is shown in both tables in the right column.

Abstract

La présente invention concerne un procédé de classement de séquences de fragments de molécules d'acides nucléiques, issues d'un ensemble de molécules d'ARN potentiellement diverses, ledit procédé comportant • facultativement la transcription inverse des molécules d'ARN pour fournir un ensemble de molécules d'ADNc, •la ségrégation d'acides nucléiques dudit ensemble d'ARN ou d'ADNc matrices, la sélection de matrices potentiellement différentes ayant une caractéristique d'acide nucléique distinctive partagée par les matrices ségrégées, fournissant au moins un premier sous-ensemble d'acides nucléiques • facultativement une ou plusieurs ségrégations supplémentaires des acides nucléiques dudit ARN ou ADNc matrice, la ségrégation sélective des acides nucléiques ayant une caractéristique d'acide nucléique distinctive différente, fournissant ainsi un ou plusieurs sous-ensembles supplémentaires d'acides nucléiques, • la production de fragments desdites molécules d'acides nucléiques ségrégées par la fragmentation ou l'obtention de copies de fragments desdites molécules d'acides nucléiques ségrégées, les fragments de chaque sous-ensemble ou de sous-ensembles combinés restant séparables des fragments d'autres sous-ensembles ou d'autres sous-ensembles combinés en séparant physiquement les sous-ensembles ou en fixant un marqueur aux fragments des sous-ensembles, le marqueur identifiant un sous-ensemble, ou la détermination d'une séquence partielle de ladite molécule d'acide nucléique ségrégée et préférablement l'alignement d'au moins deux séquences ou séquences partielles à une séquence jointe.
PCT/EP2010/069382 2009-12-11 2010-12-10 Procédé analytique concernant l'arn WO2011070155A1 (fr)

Priority Applications (6)

Application Number Priority Date Filing Date Title
AU2010329825A AU2010329825B2 (en) 2009-12-11 2010-12-10 RNA analytics method
CA2782766A CA2782766A1 (fr) 2009-12-11 2010-12-10 Procede analytique concernant l'arn
US13/511,961 US20120238457A1 (en) 2009-12-11 2010-12-10 Rna analytics method
EP10788340.7A EP2510114B1 (fr) 2009-12-11 2010-12-10 Procédé analytique pour ARN
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JP2015522277A (ja) * 2012-06-28 2015-08-06 カルドラ ヘルス リミテッドＣａｌｄｅｒａ Ｈｅａｌｔｈ Ｌｔｄ 前立腺癌の診断方法と診断用物質
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JP2015522277A (ja) * 2012-06-28 2015-08-06 カルドラ ヘルス リミテッドＣａｌｄｅｒａ Ｈｅａｌｔｈ Ｌｔｄ 前立腺癌の診断方法と診断用物質
EP3550033A1 (fr) * 2013-02-20 2019-10-09 Emory University Méthodes de séquençage d'acides nucléiques présents dans des mélanges et compositions associées
US11203750B2 (en) 2013-02-20 2021-12-21 Emory University Methods of sequencing nucleic acids in mixtures and compositions related thereto
EP3988671A1 (fr) * 2013-02-20 2022-04-27 Emory University Compositions de séquençage d'acides nucléiques présents dans des mélanges
EP2868752A1 (fr) 2013-10-31 2015-05-06 Lexogen GmbH Détermination du nombre de copies d'acide nucléique sur la base des estimations de fragment

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AU2010329825B2 (en) 2015-05-28
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