Method and Device For Detection of Splice Form and Alternative Splice Forms in Dna or Rna Sequences

• US 20080255767A1
• Filed: 05/25/2005
• Published: 10/16/2008
• Est. Priority Date: 05/26/2004
• Status: Abandoned Application

• Current Assignee: Fraunhofer Gesellschaft Zur Foerderung Der Angewandten Forsching E.V., Max-Planck-Gesellschaft Zur Foerderung Der Wissenschaften e.V. (Max-Planck-Gesellschaft zur Frderung der Wissenschaften e)
• Original Assignee: Fraunhofer-Gesellschaft ZUR Forderung Der Angewandten Forschung EV, Max-Planck-Gesellschaft Zur Foerderung Der Wissenschaften e.V. (Max-Planck-Gesellschaft zur Frderung der Wissenschaften e)
• Inventors: Scholkopf, Bernhard, Muller, Klaus-Robert, Ratsch, Gunnar, Sonnenburg, Soren
• Application Number:
  US11/597,218
• Publication Number:
  US 20080255767A1
• Time in Patent Office: Days
• US Class Current: 702/20
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• CPC Class Codes: G16B 20/20 Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
• CPC Class Codes: G16B 20/30 Detection of binding sites or motifs
• CPC Class Codes: G16B 30/00 ICT specially adapted for sequence analysis involving nucleotides or amino acids
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

The invention relates to a method and a device for detection of splice sites in DNA or RNA sequences comprising three steps: a) examining a training set of sequences comprising DNA or RNA sequences with known splice sites by an automated, discriminative training device for detecting splicing patterns, especially in a predetermined window around the known splice sites; b) scanning a sequence comprising DNA or RNA sequences containing unknown splice sites for the occurrence of the splicing patterns detected in step a); and c) calculation of a cumulative splice score in dependence of a maximization of the margin between the true splice forms and all wrong splice forms in the sequence. The invention also relates to a method and a device for detection of splice forms and alternative splice forms in DNA or RNA sequences.

Claims

1-33. -33. (canceled)

34. A method for the detection of a splice form in a DNA or RNA sequences, comprising:

a) examining a training set of sequences comprising DNA or RNA sequences with known splice sites by an automated, discriminative training device for detecting splicing patterns in a predetermined window around the known splice sites;

b) scanning a sequence comprising DNA or RNA sequences containing unknown splice sites for the occurrence of the splicing patterns detected in step a); and

c) calculating automatically a splice score in dependence of a maximization of the margin between the scores of true splice forms and all wrong splice forms in the sequence, wherein true splice forms refer to known splice forms and wrong splice forms refer to variations of known splice forms.

35. A method for the identification of one splice form and/or several alternative splice forms each comprising predictions of exon locations in DNA or RNA sequences, comprising:

a) examining a training set of DNA or RNA sequences with putative splice sites by an automated, discriminative training device for detecting splicing patterns using predetermined windows around the putative splice sites, wherein the splicing patterns can include information of alternative splice events, such as exon skipping or intron retention, alternative exon start or end usage or existence of regulative elements;

b) examining a second training set of DNA or RNA sequences with putative splice forms by an automated, discriminative training device using splice patterns detected in step a), leading to a calculation device to automatically assign scores to a splice form and/or a group of alternative splice forms in dependence of the maximization of the margin between the putative splice forms or groups of them and putatively wrong splice forms of sequences or groups of them in the training set, wherein a Large Margin based Learning algorithm is applied;

c) scanning a sequence comprising RNA or DNA with unknown and/or putative splice sites for the occurrence of the splicing patterns detected in step a); and

d) predicting a splice form or group of alternative splice forms, using the device that assigns scores in dependence of the result of step c), in dependence of the said scores by maximizing or minimizing a function of the scores, comprising a set of splice forms associated with a RNA or DNA sequence when used to identify several alternative or only one mRNAs and/or proteins associates with a RNA or DNA sequence.

36. The method according to claim 35, whereby steps a) and b) and/or c) and d) are integrated into one combined step.

37. The method according to claim 35, wherein partial information about the sequences of the training set is used in order to improve the prediction accuracy, and is used repetitively in order to complete missing information about the training sequences.

38. The method according to claim 35, wherein a combination with putative transcription starts, especially promoters or trans-splice sites, and ends, especially a polyA signal, is used to infer sets of mRNA sequences and/or proteins associated with one or several locations on the RNA or DNA sequence.

39. The method according to claim 38, wherein information about existing annotations of a RNA or DNA sequence comprising putative transcript starts and ends is used in order to identify sets of mRNA sequences and/or proteins from the RNA and/or DNA sequence.

40. A method for the detection of at least one splice form and/or at least one alternative splice form in RNA and DNA sequences, each comprising predictions of exon locations in DNA or RNA sequences, comprising:

a) examining a first training set of DNA or RNA sequences with putative splice sites by an automated training device for detecting splicing patterns;

b) examining a second training set of DNA or RNA sequences with putative splice forms by an automated, discriminative training device using splice patterns detected in step a), leading to an automatic assignment of scores to at least one splice form and/or a group of alternative splice forms by a calculation device;

c) scanning a sequence comprising RNA or DNA with unknown and/or putative splice sites for the occurrence of the splicing pattern(s) detected in step a); and

d) calculating at least one splice form and/or at least one alternative splice form in dependence of the step b) assigned scores by using the calculation device and in dependence of the results obtained in step c), wherein at least one set of splice forms associated with a RNA or DNA sequence is provided.

41. The method according to claim 40, wherein an automated discriminative training device is used for detecting splice patterns in step a).

42. The method according to claim 40, wherein the splice patterns are detected in step a) by using a predetermined window around the putative splice sites.

43. The method according to claim 40, wherein the splicing patterns detected in step a) comprise sequence patterns, alternative start and end of exon(s), skipping of exon(s) and retaining of intron(s) and/or existence of regulative element(s).

44. The method according to claim 40, wherein the DNA or RNA sequences with putative splice forms are examined in step b) in dependence of the maximization of the margin between the putative splice forms or groups of splice forms and putative wrong splice forms of sequences in the training set.

45. The method according to claim 40, wherein at least one splice form and/or at least one alternative splice form is calculated in step d) by maximizing or minimizing a function of the step c) assigned scores.

46. The method according to claim 40, wherein in step d) at least one mRNA, several alternatively spliced mRNA'"'"'s and/or proteins associated with a splice RNA and/or DNA sequence are provided.

47. The method according to claim 40, wherein steps a) and b) and/or c) and d) are integrated into one combined step.

48. The method according to claim 40, wherein the training set(s) comprise partial sequence information in order to improve the prediction accuracy.

49. The method according to claim 40, further comprising providing missing information of the training set(s) by an iterating application.

50. The method according to claim 40, wherein information of putative transcriptional starts such as promoters and/or trans-splice sites, and transcriptional ends such as polyA-signals, is used to infer sets of mRNA sequences and/or proteins associated with one or several locations on the RNA or DNA sequence.

51. The method according to claim 50, wherein information of existing annotations or RNA or DNA sequences comprising transcriptional starts and ends is used.

52. The method according to claim 40, wherein at least one training set is analyzed with a Support Vector Machine.

53. A device for the detection of at least one splice site in a DNA or RNA, comprising:

a) an automated, discriminative training device for detecting splicing patterns in a predetermined window around the known splice sites, in a training set of sequences comprising EST, RNA sequence and/or DNA with known splice sites;

b) a scanning device for scanning another sequence comprising DNA or RNA sequences containing unknown splice sites for the occurrence of the splicing patterns detected in step a); and

c) a calculation device for automatically calculating a splice score in dependence of a maximization of the margin between the true splice forms and all wrong splice forms.

54. A device for the detection of at least one splice form in a DNA or RNA sequence, comprising:

a) an automated, discriminative training device for detecting splicing patterns in a predetermined window around putative splice sites in a training set comprising RNA or DNA sequences with putative splice sites, wherein splicing patterns can include information about alternative splice events such as exon skipping or intron retention, alternative exon start or end usage;

b) a discriminative training device leading to a calculation device that automatically assigns scores to a splice form and/or a group of splice forms in dependence of the maximization of the margin between putative splice forms or groups of them and putatively wrong splice forms associated with sequences in a second training set of DNA or RNA sequences with putative splice forms;

c) a scanning device for scanning a RNA and/or DNA sequence containing unknown and/or putative splice sites for the occurrence of the splicing patterns detected by the device in step a); and

d) a calculation device for automatically calculating a score generated by the device in step b) to splice forms and/or groups of splice forms in a RNA and/or DNA sequence in dependence of the device in step c), wherein it is used to identify a set of splice forms such as mRNAs and/or proteins associated to a RNA or DNA sequence.

55. A device for the detection of at least one splice form in a DNA or RNA sequence, comprising:

a) an automated training device for detecting splicing patterns in a training set comprising RNA or DNA sequences with putative splice sites;

b) a discriminative training device leading to a calculation device automatically assigning scores to at least one splice form and/or a group of splice forms and putatively wrong splice forms associated with sequences in a second training set of RNA or DNA sequences with putative splice forms;

c) a scanning device for scanning a RNA and/or DNA sequence containing unknown and/or putative splice sites for the occurrence of the splicing pattern(s) detected in step a); and

d) a calculation device for automatically calculating a score generated by the device in step b) of at least one splice form and/or groups of splice forms in a RNA or DNA sequence in dependence on the device in c).

56. The device according to claim 55, wherein an automated discriminative training device is used for detecting splice patterns in step a).

57. the device according to claim 55, wherein the splice patterns are detected in step a) by using a predetermined window around the putative splice sites.

58. The device according to claim 55, wherein the splicing patterns detected in step a) comprise sequence patterns, alternative starts or ends of exon(s), skipping of exon(s), retention of intron(s) and/or existence of regulative element(s).

59. The device according to claim 55, wherein the DNA or RNA sequences with putative splice forms are examined in step b) in dependence of the maximization of the margin between the putative splice forms or groups of splice forms and putative wrong splice forms of sequences in the training set.

60. The device according to claim 55, wherein in step d) at least one mRNA, several alternatively splice mRNAs, a set of splice forms and/or proteins associated with a splice RNA and/or DNA sequence are provided.

61. The device according to claim 55, wherein steps a) and b) and/or c) and d) are integrated into one combined step.

62. The device according to claim 55, wherein the training set(s) comprise partial sequence information in order to improve the prediction accuracy.

63. The device according to claim 55, wherein an iterating application of the device provides missing information of the training set(s).

64. The device according to claim 55, wherein information of putative transcriptional starts, promoters and/or trans-splice sites, and transcriptional ends such as polyA-signals, is used for the device to infer sets of mRNA sequences and/or proteins associated with one or several locations on the RNA or DNA sequence.

65. The device according to claim 64, wherein information of existing annotations or RNA or DNA sequences comprising transcriptional starts and ends is used for the device.

66. The device according to claim 55, wherein the training device comprises a support vector machine.