Transcript Discovery
Contents
1. 2 Identify regions of coverage A region of coverage is a region in the mappings that contains events that are close enough to belong to the same gene Regions of coverage are identified by iterating through the predicted events while calculating the distance between the current and the next event If this is less than the Maximum distance between events value see figure 3 5 the current region is extended If not a new region is started If the Use annotations option is ticked the annotated gene regions take priority over the distance between events requirement that is if the next event lies within a region of an annotated gene that is different to that of the current event a new region of coverage is started even though the events are closer than the maximum distance between events value Please note that a region of coverage is not a gene region it may contain more gene genes The potential gene regions within a region of coverage are found in a later step see step 6 below 3 First round of merging events To reduce the number of events before proceeding with the analysis we merge events that unequivocally Support the same splice sites While doing CHAPTER 3 TRANSCRIPT DISCOVERY 12 this the Supporting read counts for the merged events are summarized In this first round of merging we merge strictly overlapping events Two events are strictly overlapping if 1 the events overlap 2 all introns and exons of th2. User manual for Transcript Discovery Plugin 2 0 Windows Mac OS X and Linux December 12 2014 This software is for research purposes only CLC bio a QIAGEN Company Silkeborgvej 2 Prismet DK 8000 Aarhus C Denmark CC big A QIAGEN company Contents 1 Introduction to the Transcript Discovery Plugin 4 2 Large gap mapper 5 2 1 Overview bk Ge REE ee RE ee ee EE E Pot POE oe 6 aw ew dd be ee eee bee ee we a ew DD 5 3 Transcript discovery 8 3 1 Algorithm and parameter description sos oaoa oaoa ee ee ee ee ee WON es wo tee eh ene ee ea ee ee eee eee ee eH 16 3 2 1 Annotations on the read mappingS 0 0 2 eee eee ee ee 16 3 2 2 Predicted genes table aie eee nh be eR N ES ee a 17 3 2 3 Regions and events table assassinar ir AS 18 gA SUNA ODOT ok ee wee ee a ee eee ke Rh ae we ee Ee de we 19 3 2 5 Extract annotated reference sequences 0 000 8 wens 19 See Wi NONO amas E oe ao Boe ee we ee a ae ee ee Ee we ce ee a a 19 4 Installation 21 5 Uninstall 23 BIDNORIS PNY lt a ade Eca Gwe ee Em oe ee at ee ee ow we ee we a 24 Chapter 1 Introduction to the Transcript Discovery Plugin The Transcript Discovery Plugin is designed to discover transcripts by mapping RNA Seq sequenc ing reads to a genomic reference allowing large gaps for introns followed by a transcript discovery process where transcripts are inferred from the read mappings Relying heavily on reads mapped with a gap as evidence
3. or whether you prefer running the transcript discovery with default parameters see figure 3 3 If you select Manual you will be able to adjust all the filters explained below The filters are mainly in place to eliminate as much noise as possible and provide thresholds for defining valid genes and transcripts If you select Automatic default settings will be used Since the result is quite sensitive to the values used in the filters it will often be beneficial to adjust these Often it will require running the analysis a few times inspecting the results and adjusting the filters accordingly CHAPTER 3 TRANSCRIPT DISCOVERY 10 Set parameters e Choose where to run N Select read mapping ee Specify general mode of analysis gt Set filtering mode Noise filtering e Automatic Manual 2711S Previous Next Cancel Figure 3 3 Specifying if filtering should be automatic or manual Before proceeding with describing all the filters some introduction to the underlying algorithm is needed It consists of ten steps outlined below The step wise examination will be supplemented with explanations of the options in the dialogs 1 Define events This step examines each mapped read and converts it to a predicted event In this first version of the plugin paired reads are treated as two single reads so that two independent events are created for reads in a pair An event has a region defined by the mapping region
4. merische mathematik 1 1 269 271 24
5. they are treated as single reads Chapter 2 Large gap mapper 2 1 Overview The large gap mapper maps reads to a reference while allowing for large gaps in the mapping It is developed to support transcript discovery using RNA seq data since it is able to map RNA seq reads that span introns without requiring prior transcript annotations The large gap mapper works by iteratively applying the standard read mapper of the CLC Genomics Workbench to each read as follows 1 Find the best match for the read 2 If the match is good enough according to the settings see below the read is mapped to this position 3 If there is an unaligned end which is long enough for the mapper to handle 17 bp for standard mapping 18 bp for mapping in color space this part of the read is used as input to step 1 4 This continues until no reads have unaligned ends that are longer than 17 18 bp Usually for 100 bp reads it will be maximum three rounds of mapping corresponding to spanning two introns The matched region of the read identified in the first round of the mapping is called the seed segment or just seed Matched regions found in later rounds are called non seed segments 2 2 Parameters The large gap mapper is started from the Toolbox Toolbox Transcriptomics Analysis RNA Seq Analysis Large Gap Mapper After having specified the reads and the reference to which the reads should be mapped the user must spec
6. 0 9 Colorspace Settings Paired reads M q Previous Next Cancel Figure 2 2 Specifying parameters for the large gap mapper Here you can specify the mapping settings We refer to the user manual of CLC Genomics Workbench for further detail you can find the manual in the Help menu or at http www clcbio com usermanuals However the minimum similarity and length fractions need some CHAPTER 2 LARGE GAP MAPPER F more explanation The similarity fraction is the required similarity between a mapped segment and the reference This means that all segments must fulfill this requirement Since segments can be as short as 1 bp this threshold should not be set too strict setting the threshold at 0 9 means that two errors for a segment of 17 bp would discard the match The length fraction is the required fraction of the full read that should be mapped In addition to these user specified mapping settings the large gap mapper requires that each mapped segment must comprise at least 10 of the read and must be of minimum length 17 bp 18 for color space Click Next to specify output options In addition to the read mapping the user can specify that a report on the mapping should be created and that lists of unmapped and invalid mapped reads should be produced The mapping report contains various statistics on the mapping such as the distribution of number of segments per read matching the reference match parts the distribution
7. Annotations on the read mappings It can be very handy to see annotations reflecting the various steps in the transcript discovery directly in the read mapping view An example is shown in figure 3 10 There are different kinds of annotations shown Event An Event annotation is added for each event that is used in the graph building procedure in the step Predicting transcript annotations Event filtered An Event filtered annotation is added for each event that was filtered in the Step Filter events CHAPTER 3 TRANSCRIPT DISCOVERY Event Filtered Event Event Filtered Event Filtered iEvent Filtered iSpliced Event Event Filtered Event Gene 17 Event Filtered Gene 17 Event Event Filtere Gene 17 Spliced Event Event Filtered Event Filtered Event Filtered Event Filtered Spliced Event Event Filtered Spliced Event Event vent Event Filtere d Spliced Event o Filtered d Event Filtered E om ja q pa a e e fa mn as O o Ili i fj a ee eee eee eee eee eee eee sees ee eee it dana sand dad opina Tah o SI dUDcs assbicon usado no can am Figure 3 10 All the annotations showing final predictions and the intermediate events Event region filtered An Event region filtered annotation is added for each gene region that was filtered in the step Identifying genes Predicted gene A Predicted gene annotation is added for each predicted gene tha
8. for transcripts it is primarily developed for eukaryotic genomes The proposed work flow for using the Transcript Discovery Plugin in combination with the existing RNA Seq tool in the CLC Genomics Workbench is this 1 Run the large gap mapper using all your RNA Seq reads and a genomic reference sequence 2 Run the transcript discovery algorithm on the resulting read mapping to predict transcripts and genes 3 Inspect the results and if necessary re run the transcript discovery to refine the settings to produce the desired result 4 Part of the result from the transcript discovery is a copy of the reference genome including the new transcript and gene annotations This can now be used as a common reference for measuring gene expression using the existing RNA Seq tool in the Workbench If you have sequenced several samples that need to be compared we suggest using the reads from all samples for the large gap mapping and subsequent transcript discovery In this way you can establish a common set of reference transcripts and genes that makes it possible to compare gene expression levels across samples using the RNA Seq tool in the CLC Genomics Workbench The initial read mapping created by the large gap mapper is then no longer used and can be deleted unless you wish to be able to go back and double check the basis of the prediction The current release is a beta version with full functionality for single reads If you have paired reads
9. s of the read If the read mapping is un gapped the event is just called an event and its region consists of a single interval If the read mapping has gaps the predicted event will be called a spliced event and its region will consist of more intervals If you have specified canonical splice sites see figure 3 1 the mapping will be checked to see if the gap is placed at or without cost can be moved to one of these Events also have supporting read counts of spliced and un spliced reads At this point they are 1 and O for spliced reads and O and 1 for un spliced reads The supporting read counts are used in later steps for filtering and merging events If the Use existing annotations option is selected a gene region is defined for each annotated gene and an event is produced for each annotated transcript These are referred to as known events The Read filtering options in the Event filtering step are related to defining events Ignore match duplicates For reads that are 100 identical only one copy is used to define events This is relevant for the supporting read counts that are used when filtering events When ticked identical reads will only be counted as 1 in the read counts Ignore non specific matches Reads that have an equally good match elsewhere on the reference genome these reads are colored yellow in the mapping view can be ignored in the analysis Whether you include these reads or not will be a tr
10. PT DISCOVERY 14 T Filter events Some events in the gene regions may be supported by just a few reads To remove these noise events you can apply a number of event filters set noise filtering to manual see figure 3 4 Spliced events Minimum unique observations Filtering of spliced events with weak ev idence The minimum number of unique spliced reads that must support an spliced event Events that do not meet this requirement are ignored A read is unique if it counts as specified by the Read filtering options in 3 1 If the Ignore duplicate reads option is ticked identical spliced reads are counted as 1 and if the Ignore non specific matches is ticked non specific matches are not counted Minimum coverage ratio Filtering of spliced events with weak relative evidence The spliced coverage of a region is calculated as the number of spliced reads in the gene region divided by the total length of the region consisting of the union of the exons in the events in the region Similarly the spliced coverage of an event is calculated as the number of spliced reads supporting the event divided by the length of the exon regions of the event If the spliced coverage of the event divided by the spliced coverage of the region is smaller than the user specified value the event is ignored Compared to the filter on absolute read count above the coverage ratio filter allows filtering of events with weak evidence in regions of h
11. adeoff between sensitivity and specificity Including them may lead to the prediction of transcripts that are not correct whereas excluding them may mean that you will loose some true transcripts The rest of the event filter settings in figure 3 4 will be explained further when the event filters are described below step 7 Figure 3 5 shows the transcript and gene filters These will be explained in more detail in under step 10 CHAPTER 3 TRANSCRIPT DISCOVERY 11 Set parameters par Choose where to run N Select read mapping Lo Specify general mode of analysis D Set filtering mode Ira Ww Set event filters V Ignore duplicate reads V Ignore non specific matches Spliced events Minimum unique observations 11 Minimum coverage ratio 0 05 4 Un spliced events Minimum unique observations Sils Minimum coverage ratio 0 05 A Previous Next Cancel p Figure 3 4 Specifying event filters Set parameters m Choose where to run N Select read mapping Lo Specify general mode of analysis D Set filtering mode Ww Set event filters Gene discovery E gene and transcript Maximum distance between events 1 000 ilters o Minimum observations in gene 10 5 Minimum length of gene 250 Spliced transcripts only Open ended exons Maximum joining distance 100 Q Previous Next Cancel lt Figure 3 5 Specifying transcript and gene filters
12. alW and MUSCLE Ones Daal Annotate with GFF file Q CLC bio suppor t dcbio com Version 2 2 6 Build 131211 2143 102901 Using this plug in it is possible to annotate a sequence from list of annotations found in a GFF file Located in the Toolbox CLC Microbial Genome Finishing Module CLC bio support dcbio com Version 1 3 2 Build 140318 1029 Various tools for genome finishing aimed to dose and produce high quality genomes in sequencing projects CLC Workbench Client Plugin Q CLC bio suppor t dcbio com Version 6 0 Build 140207 0940 105889 Client plugin for connecting to a CLC Genomics Server CLC Science Server CLC Drug Discovery Server or Bioinformatics Database The plug in also includes Grid Engine Integration Proxy Settings Check for Updates Install from Fie dose Figure 5 1 The plugin manager with plugins installed The installed plugins are shown in this dialog To uninstall Click the Transcript Discovery Plugin Uninstall If you do not wish to completely uninstall the plugin but you don t want it to be used next time you start the Workbench click the Disable button When you close the dialog you will be asked whether you wish to restart the workbench The plugin will not be uninstalled until the workbench is restarted 23 Bibliography Dijkstra 1959 Dijkstra E 1959 A note on two problems in connexion with graphs Nu
13. ce set The default value for the Maximum joining distance parameters is 100bp 10 Identifying genes Finally a gene is predicted if the sum of the read counts of the events in the transcripts for the gene is above the Minimum observations in gene value see figure 3 5 and the length of the gene from beginning of first exon to the end of the last exon is larger than the Minimum length of gene value see figure 3 5 If the option Spliced transcripts only is selected genes without spliced transcripts will be ignored and only genes with spliced transcripts are predicted 11 CDS annotation The CDS annotation functionality of the Transcript Discovery tool simply reports the largest open reading frame ORF found in the predicted transcript Note that this may lead to a shorter CDS annotations than the original CDS annotations if specified 3 2 Results Before clicking Finish you can decide which forms of output you want see 3 9 Result handling a Choose where to run N Select read mapping Ww Specify general mode of analysis Set filtering mode Output options V Annotate read mappings Ww Result handlin g V Create gene table V Create region table V Create summary report Extract annotated reference sequences Result handling Open e Save Log handling Open log q Previous Next Cancel Figure 3 9 Output options The various outputs are described in the sections below 3 2 1
14. d Exclude external External events without spliced reads are excluded if their coverage is less than 25 of that of the event with maximum coverage in the gene region External events are those that lie upstream or downstream of all events with splice evidence This ensures that spurious weak expression most upstream or downstream in the region of coverage is ignored 8 Third merging of events Having excluded events in the filtering step some events may now be mergable that were not before the filtering We thus apply a third round of merging of Strictly overlapping events described above CHAPTER 3 TRANSCRIPT DISCOVERY 15 Event Filtered Event Event Filtered ant Filtered Event Filtered Event Filtered Spliced Event Event Filtered ad Spliced Event Event Event Filtered a inote filter Intron exon coverage ratio 7 inote coverage 0 07446808510638298 inote unspliced reads 7 spliced reads O aii oo e j e co e _ i e a lt jm p ee ee DD ees l S E _ oo om mE ee ee ee ee ee ee ee ee e me o oO O ee ee O OO TO e O af HH KT PP PP RB RR PP BPP BP Pe a ee 0 0 o ee Figure 3 8 Event filtered on intron exon ratio 9 Predicting transcript annotations For each gene region transc
15. e events in the overlapping region are the same and 3 the non overlapping parts of the events do not extend across any splice site positions of any other events in the coverage region The requirement 3 ensures that we do not merge an event with another event in cases where there are more events supporting different splice sites with which it could be merged 4 Fix end and splice points Many events will have end points that are slightly off mostly because the first few respectively last bases of the intron and the end of the following respectively preceding exon are identical or because they really should have been mapped with a gap but a too short part of the read was present on one side of the gap for the mapper to map it so instead it was mapped possibly with a few nucleotides into an intron and an unaligned end see an example in figure 3 6 PCCCTIGTCCTCCT TCAGTCAAGTGTGCATICT TAACAAGAGGGAAAAG TCCCTGTCCTCCTTCAGTCAAGTGTGCAT CT TAACAAGAGGGAAAAGC TCCCTGTCCTCCTTCAGTCAAGTGTGCATICTT TCCCTGTCCTCCT TCAGTCAAGTGTGCATICTT TCCCTGTCCTCCTTCAGTCAAGTGTGCATICTT TCCCTGTCCTCCTTCAGTCAAGTGTGCATICTT TCCCTGTCCT TGCAT CT TAACAAGAGGGAAAAG ECCCTGTCCTCCTTCAGTCAAGTGTGCATICTT ER ge ere ee ee TCCCTGTCCTCCTTCAGTCAAGTGTGCAT ICT TAACAAGAGGGAAAAC TCCCTGTCCTCCTTCAGTCAAGTGTGCATICTTAACAAGAGGGAATAC TCCCTGTCCTCCTTCAGTCAAGTGTGCATICTT Figure 3 6 The four reads at the top and the read at the bottom all have aligned three nucleotides into the intr
16. e mappings It means that all existing gene and mRNA annotations will be kept and new ones added only when the mapped reads suggest a new transcript or gene When this option is not selected existing gene and MRNA annotations if present will be ignored and annotations will be generated solely based on the mapping of the reads Splice sites The algorithm will examine each gap in the read mapping to see if the gap is placed at or without cost can be moved to a valid splice site based on the ones you select in this list Gaps that are placed at or moved to one of these splice sites are defined as certain Splice sites Exclude uncertain splice sites For some gaps it will not be possible to place the gap at one of the defined splice sites and these will be considered as gaps with uncertain splice sites and can be ignored by selecting this option predict open reading frames When ticked predicted transcripts will be examined for valid open reading frames CDS annotations will be created for open reading frames that are longer than the user specified Minimum length of ORF Gen Gene 1 Event Filtered Gen Filtered Event ed note filter Uncertain C4 note cov note unspliced rea iced rea EE i uu EEE EE Figure 3 2 Events with certain and uncertain splice sites Click Next allows you to choose whether you wish to adjust a whole range of filtering parameters
17. ed with the other event meaning that the supporting read counts of the contained event is added to those of the containing event An event is contained in CHAPTER 3 TRANSCRIPT DISCOVERY 13 Event Spliced Event inote Supported by 1 reads 1 spliced 5 inote Used in path 5 inote Coverage number of reads length 0 01 inote Boundaries are moved based on events in the vicinity inote Splice evidence inote Gene NRIP 1 e a Figure 3 7 The annotation tells you that the boundaries for this event were moved in the Fix end and splice points step another event if all its introns and exons are present in the other event An event can be contained in several other events which means that the supporting read counts will be added to each of those events Merge strictly overlapping events see above First round of merging 6 Split in genes As some genes lie close and or overlap a coverage region may contain more genes The next step is to split the events within a region of coverage into possibly several potential gene regions If no annotations are used the split in genes step just splits the events on strands a Assign all events that are on the forward strand to a forward strand region b Assign all events that are on the reverse strand to a reverse strand region c For an un stranded event if it intersects with the region spanned by the forward stranded events and not with that of t
18. enome Trax Download CLC bio support cicbio com Version 2 0 11 Build 140103 1322 103719 Create tracks with various data from Biobase Genome Trax Plugin requires registration Blast2GO PRO Q BioBam Bioinformatics pluginsupport blast2go com GD additional Alignments This module allows for use of two other alignment methods which are otherwise not distributed with the CLC Workbench When the plug in is installed you will see the new alignment methods in the Toolbox under Alignments and Trees gt Additional Alignments When you run the alignments there are a number of parameters that can be set You can also specify command line instructions E da prato EE Create Alignment EE Join Alignments EB Create Pairwise Comparison at Create Tree The selo alignments in the toolbox Allignment methods Three different alignment methods are included in this extension ClustalW ClustalO and Muscle For more detailed information on each of Figure 4 1 The plugins that are available for download 22 Chapter 5 Uninstall Plugins are uninstalled using the plugin manager Help in the Menu Bar Plugins and Resources or Plugins ES in the Toolbar This will open the dialog shown in figure 5 1 am A Download Plugins Manage Resources r Manage Plugins and Resources GD CLC bio suppor t dcbio com Version 1 5 1 Build 131211 2142 102901 Perform alignments with ClustalO Clust
19. he mitochondrion genome and this quickly becomes a problem for the transcript discovery The high coverage means that there can often be millions CHAPTER 3 TRANSCRIPT DISCOVERY 20 of events that will take a very long time to analyze For this reason the transcript discovery will skip the reference sequences that have an average coverage higher than 1000 For a standard human data set this limit will target the mitochondrion genome specifically Please note that it is not recommended to exclude the mitochondrion genome as reference for the mapping since all the reads that map well on this reference sequence will try to find matches on other chromosomes This will lead to false positive matches Chapter 4 Installation The Transcript Discovery Plugin is installed as a plugin Plugins are installed using the plugin manager Help in the Menu Bar Plugins and Resources E or Plugins 4 in the Toolbar The plugin manager has three tabs at the top e Manage Plugins This is an overview of plugins that are installed e Download Plugins This is an overview of available plugins on CLC bio s server e Manage Resources This is an overview of resources that are installed To install a plugin click the Download Plugins tab This will display an overview of the plugins that are available for download and installation see figure 4 1 Clicking a plugin will display additional information at the right side of the dialog This wil
20. he reverse stranded event assign it to the forward strand region It the opposite is the case assign it to the reverse strand region Else assign it to the region whose events have the highest summed read count d Create a gene region for the events assigned to the forward strand and another for those assigned to the reverse lf annotations are used the procedure is more complicated a Create a list of the regions of the known genes in the coverage region b For each event in the region collect a list of those of the known genes that it might belong to the possible genes If the event is stranded this list contains all of the known genes in the region that have the same strand as the event and whose region intersects with the event If the event is un stranded the list contains all genes whose region intersects with the event If there is just one possible gene for an event we assign it to that gene If there are more possible events we prefer a gene that completely overlaps with the event If there are more of these we prefer the shortest If there are no possible genes for an event but it intersects with an event that has been assigned to a gene and that is not on a different strand assign it to the gene of that event If there are events left after this that have not been assigned to a gene use the split on strand procedure described above to create gene regions for them CHAPTER 3 TRANSCRI
21. ify two parameters related to the mapped segments of a read See figure 2 1 Maximum number of hits is the maximum number of hits that a segment is allowed to have in order for the read to be mapped If for a non seed segment this number is exceeded the 5 CHAPTER 2 LARGE GAP MAPPER 6 Set parameters 1 Choose where to run 2 Select reads 3 Select references References xx Selected 25 elements yo Mapped segment settings Maximum number of hits 10 Maximum distance from seed 50000 Non specific matches Random Ignore q Previous Next Cancel Figure 2 1 Specifying parameters for the large gap mapper read is classified as unmapped If it is not exceeded all the multiple hit positions will be considered If the seed makes up the full read it may map in up to Maximum number of hits positions Maximum distance from seed is the maximum distance allowed between seed and non seed segments Matches that are found further away from the seed that this value are discarded You can also specify whether non specific matches should be distributed randomly or ignored Click Next to specify parameters related to the mapping quality This is done in the Mapping settings step see figure 2 2 Set parameters Choose where to run Select reads Select references Mapping Settings gt Ww N Mapping settings Mismatch cost 2 lv Insertion cost 3 Deletion cost 3 ils Similarity 0 9 Length fraction
22. igh coverage Un spliced events Minimum unique observations Filtering of events with weak evidence The minimum number of unique un spliced reads that must support an un spliced event Events that do not meet this requirement are ignored Minimum coverage ratio Filtering of events with weak relative evidence The un spliced coverage of a region is calculated as the number of un spliced reads in the transcript event region divided by the total length of the region consisting of the union of the exons in the events in the region Similarly the un spliced coverage of an event is calculated as the number of un spliced reads supporting the event divided by the length of the exon regions of the event If the un spliced coverage of the event divided by the un spliced coverage of the region is smaller than the user specified value the event is ignored In addition to these user controlled filters the algorithm applies three more filters Exclude intron exon events For each un spliced event it is examined if there are spliced events with which it is incompatible if there is the un spliced event is an event that extends across an exon intron boundary but that does not have an alternative splice site If so the un spliced event is ignored see 3 8 Exclude internal un spliced All events that lie within introns of other events and do not overlap with any other event are excluded This ensures that spurious expression within introns is ignore
23. l also display a button Download and Install Click the Transcript Discovery Plugin and press Download and Install A dialog displaying progress is now shown and the plugin is downloaded and installed If the Transcript Discovery Plugin is not shown on the server and you have it on your computer e g if you have downloaded it from our web site you can install it by clicking the Install from File button at the bottom of the dialog This will open a dialog where you can browse for the plugin The plugin file should be a file of the type cpa When you close the dialog you will be asked whether you wish to restart the CLC Workbench The plugin will not be ready for use until you have restarted tin order to install plugins on Windows the Workbench must be run in administrator mode Right click the program shortcut and choose Run as Administrator Then follow the procedure described below 21 CHAPTER 4 INSTALLATION Manage Plugins and Resources Ds support cichio com Version 1 5 1 Build 131211 2142 102901 Perform alignments with ClustalO ClustalW and MUSCLE ak de ora a annotations found in a GFF file Located in the Toolbox Batch Rename CLC bio support cicbio com Version 1 3 1 Build 131211 2144 102901 Rename files in batch by adding a prefix or a number Biobase Genome Annotate CLC bio su Version 2 0 11 Build aes aa 103719 Create tracks with various data from Biobase Genome Trax Biobase G
24. large gap mapper and click Nextt You are now presented with choices regarding the overall mode of analysis as shown in figure 3 1 80900 Transcript Discovery Set parameters Choose where to run Protocol Select read mapping Strand specific w N m Specify general mode of A Annotations analysis M Extend existing annotations Splice sites exon GT intron AG exon exon GC intron AG exon exon GC intron TG exon exon GC intron AA exon exon GC intron GG exon exon GT intron TG exon exon GT intron AA exon exon AT intron AC exon exon AT intron AA exon exon AT intron AG exon exon AT intron AT exon EEE MECC MEE MESES M Exclude uncertain splice sites Coding sequences M Predict open reading frames Minimum length of ORF 100 q Previous Cancel O CC ee Qe Figure 3 1 Specifying the overall mode of analysis Please note that if your mapping used paired data the reads will be treated as single reads 8 CHAPTER 3 TRANSCRIPT DISCOVERY 9 Protocol If a strand specific protocol was used for generating the reads in the mapping select this option It means that the strandedness of the predicted exons and splice sites will be defined by the strands on which the reads map If a strand specific protocol was not used the splice sites See below will be used to determine the strandedness Use existing annotations This option allows you to enrich existing gene and mRNA annotations on the reference sequences of th
25. of gaps between the match parts and paired read mapping statistics In the mapping report Unaligned internal gaps are small unmapped parts of the read between mapped segments whereas gap between match parts is the distance between the mapped read segments on the reference For cDNA reads mapped to genomic sequences these distances correspond to intron size The unmapped read list contains the reads which the large gap mapper was not able to map The reads for which the large gap mapper was able to find a mapping but for which the mappings of the segments where incompatible are put in the invalid mapped reads list The mappings of the segments of a read are incompatible if their positions are not consecutive along the reference or if they do not have the same direction Chapter 3 Transcript discovery The Transcript discovery tool is the second component in the set of tools in the Transcript Discovery Plugin The tool takes read mappings as input and produces gene and mRNA annotations The annotations are generated by examining the read mapping and identifying likely regions of genes their exons and splice sites and for each gene region a set of transcript annotations that explain the observed exons and splice sites in this region 3 1 Algorithm and parameter description To start the transcript discovery Toolbox Transcriptomics Analysis lx RNA Seq Analysis Transcript Discovery Select the read mapping produced by the
26. on based on the existing transcript annotation and with an unaligned end These nucleotides actually map perfectly at the next exon but the large gap mapper is not able to align parts that are smaller than 17 bp Also splice sites may not have been found due to errors in the read To account for this we fix end and splice points of the events This is done for each coverage region by collecting all the certain splice sites observed in the region based on the sequence of the splice site see figure 3 1 in a list For each event in the region it is then examined whether its end points or splice positions are close less than 9 bp to one of the sites in this list of observed certain splice sites If so the end or splice points of the event are moved and the event is given the note Boundaries are moved based on events in vicinity this can be seen on the event annotation as shown in figure 3 7 5 Second round of merging events The fixing of end and splice points above alters the set of events within a coverage region and typically causes events that were not mergable before the fixing took place to now be mergable To further reduce the number of events we carry out a second merging of events that unequivocally support the same splice sites while again adding read counts of merged events This time the merging consists of two steps Merge contained events For each event it is examined if it is contained in another event If so it is merg
27. ript annotations are created by a two step procedure Identifying events belonging to a transcript First we build a directed graph which has as nodes the events in the graph Events are sorted by starting positions A directed edge is added between nodes from the first to the last if the events are compatible Two events are compatible if they in their overlap Support the exact same splice junctions We use the Dijkstra algorithm Dijkstra 1959 to identify a set of paths through the graph that completely covers the nodes While building paths the supporting read counts of the events are used as weights and the path with the highest weight is preferred Each resulting path contains a set of events that belong to the same transcript Converting paths to transcripts For each path a transcript is defined by merging the events in the path Open ended exons are created when the algorithm cannot be certain of the start or end site of an exon This can occur when there is data missing or low coverage around an exon boundary If two open ended exons occur within a certain distance of each other the Maximum joining distance parameter see figure 3 5 then it may be likely that these actually originate from the same exon but due to low coverage or missing data CHAPTER 3 TRANSCRIPT DISCOVERY 16 the algorithm has reported it as two The next stage of the process will then merge these two open ended exons into one if they lie within the distan
28. ripts Also there are statistics on the filtering of events spliced events and genes These summaries can be used to get an overview of the overall performance of the generation of annotations and may give a rough indication of whether the filtering was appropriate for the user s particular aim 3 11 S Filtered events Dp Report Settings Table of Contents Filtered events 1 Annotations 100 1 1 Annotation summary 1 2 Annotation details 80 2 Event characteristics v 2 1 Read counts on events 60 2 1 1 Read counts on events befor 2 1 2 Read counts on events befor Events 2 1 3 Read counts on events befor 2 2 Read counts on spliced events 2 2 1 Read counts on spliced even 2 2 2 Read counts on spliced even 2 2 3 Read counts on spliced even 3 Filtered events 4 Filtered genes cn Text format E S In total 4 events were filtered Figure 3 11 An overview of the event filtering from the Ab initio transcript assembly report 3 2 5 Extract annotated reference sequences When ticked the reference sequences of the read mappings will be copied the predicted gene and transcript annotations will be added to them and they will be put in a sequence list These sequences can then be used as references in a subsequent RNA seq analysis New predicted annotations will have the note Predicted by CLC bio transcript discovery 3 3 Mitochondrion You will typically have very high coverage on t
29. scripts of the gene Unknown spliced events The number of unknown spliced events that is spliced events that are not contained in prior annotated transcripts for the transcripts of the gene Reads The sum of the read counts of the events from which the transcript annotations were built Spliced reads The sum of the spliced read counts of the events from which the transcript annotations were built New 5 sequence Yes if the gene region extends 5 of the prior gene annotation if there was one else no New 3 sequence Yes if the gene region extends 3 of the prior gene annotation if there was one else no Splicing description A summary of the types of new splice sites found for transcripts for the gene Alternative acceptor donor and or new exon When the Use annotations option was not used the columns Unknown Known transcripts Unknown transcripts Unknown events Unknown spliced events New 5 sequence New 3 sequence and Splicing description are not present Note that while predicting genes and CDS s the Transcript Discovery tool will also attempt to identify the strandedness The strandedness is determined from the canonical splice sites in the Spliced reads However sometimes that information is not present for some of the predicted genes This can be because there are no spliced reads or because those that are there do not use any of the canonical splice
30. sites In these instances the strand will be indicated with a because it can not be determined 3 2 3 Regions and events table This table has a row for each coverage region that has been examined for potential genes and transcripts see step 2 in section 3 1 It has the following columns Region the region of the coverage region Overlapping genes The names of overlapping genes if any Total reads The number of reads in the events of the coverage region Un spliced The number of spliced reads in the events of the coverage region Spliced The number of spliced reads in the events of the coverage region Events The number of events in the coverage region CHAPTER 3 TRANSCRIPT DISCOVERY 19 Events after filtering The number of events after filtering in the coverage region In addition for each gene region within the coverage region it will have a set of the following five columns Region The region of the gene Gene The name of the gene Events The number of events in the gene region before filtering Filtered The number of events in the gene region after filtering Filtered description A summary of how many event were filtered by each of the filters e g Observations 2 Uncertain 2 3 2 4 Summary report The summary report holds various statistics on the annotations generated in the analysis such as distributions of the lengths of genes the numbers of transcripts per gene and the numbers of exons per transc
31. t is for each gene region that passed the filter in the Identifying genes step Predicted MRNA A Predicted mRNA annotation is added for each predicted transcript for the predicted genes 3 2 2 Predicted genes table This table contains a row for each predicted gene If the Use existing annotations option is selected the existing gene annotations are also included in the table When the Use annotations option has been used the gene table has the following columns Reference The name of the mapping in which the gene was predicted Gene The name of the gene if it was annotated prior to the analysis If it is a new predicted gene the name will be Gene followed by a number e g Gene 1 Unknown No if the gene was annotated prior to the analysis yes if it is a new predicted gene Length The length of the gene region Start The start of the gene region End The end of the gene region Strand The strand on which the gene was predicted Transcript The number of transcripts for the gene including prior annotated as well as new predicted CHAPTER 3 TRANSCRIPT DISCOVERY 18 Known transcripts The number of prior annotated transcripts for the gene Unknown transcripts The number of new predicted transcripts for the gene Longest transcripts The length of the longest transcript for the gene Unknown events The number of unknown events that is events that are not contained in prior annotated transcripts for the tran
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