Introduction to Apollo for i5k

Introduction to Apollo Collaborative genome annotation editing A webinar for the i5K Research Community - Hemiptera

Monica Munoz-Torres | @monimunozto Berkeley Bioinformatics Open-Source Projects (BBOP) Environmental Genomics & Systems Biology Division, Lawrence Berkeley National Laboratory i5k Pilot Project Species Calls | 9 February, 2016

http://GenomeArchitect.org

Outline

•  Today you will discover effective ways to extract valuable information about a genome through curation efforts. Apollo Collabora've Cura'on and

Interac've Analysis of Genomes

After this talk you will... •  Better understand ‘curation’ in the context of genome annotation:

assembled genome à automated annotation à manual annotation

•  Become familiar with Apollo’s environment and functionality.

•  Learn to identify homologs of known genes of interest in your newly sequenced genome.

•  Learn how to corroborate and modify automatically annotated gene models using all available evidence in Apollo.

Experimental design, sampling.

Comparative analyses

Official / Merged Gene Set

Manual Annotation

Automated Annotation

Sequencing Assembly

Synthesis & dissemination.

This is our focus.

We must care about curation

Marbach et al. 2011. Nature Methods | Shutterstock.com | Alexander Wild

The gene set of an organism informs a variety of studies: •  Characterization: Gene number, GC%, TEs, repeats. •  Functional assignments. •  Molecular evolution, sequence conservation. •  Gene families. •  Metabolic pathways. •  What makes an organism what it is?

What makes a bee a “bee”?

Genome Curation

Identifies elements that best represent the underlying biology and eliminates elements that reflect systemic errors of automated analyses.

Assigns function through comparative analysis of similar genome elements from closely

related species using literature, databases, and experimental

data.

Apollo

Gene Ontology Resources

A few things to rememberwhen conducting manual annotation

To remember… Biological concepts to be;er understand manual annota'on

7 BIO-REFRESHER

•  KEEP A GLOSSARY HANDY from con$g to splice site

•  WHAT IS A GENE?

defining your goal

•  TRANSCRIPTION mRNA in detail

•  TRANSLATION

reading frames, etc.

•  GENOME CURATION steps involved

The gene: a “moving target”

“The gene is a union of genomic

sequences encoding a coherent set of

potentially overlapping

functional products.”

Gerstein et al., 2007. Genome Res

9

"Gene structure" by Daycd- Wikimedia Commons

BIO-REFRESHER

mRNA

•  Although of brief existence, understanding mRNAs is crucial, as they will become the center of your work.

10 BIO-REFRESHER

Reading frames

v  In eukaryotes, only one reading frame per section of DNA is biologically relevant at a time: it has the potential to be transcribed into RNA and translated into protein. This is called the OPEN READING FRAME (ORF) •  ORF = Start signal + coding sequence (divisible by 3) + Stop signal

11 BIO-REFRESHER

Splice sites

v  The spliceosome catalyzes the removal of introns and the ligation of flanking exons.

v  Splicing signals (from the point of view of an intron): •  One splice signal (site) on the 5’ end: usually GT (less common: GC) •  And a 3’ end splice site: usually AG •  Canonical splice sites look like this: …]5’-GT/AG-3’[…

12 BIO-REFRESHER

Exons and Introns

v  Introns can interrupt the reading frame of a gene by inserting a sequence between two consecutive codons

v  Between the first and second nucleotide of a codon

v  Or between the second and third nucleotide of a codon

"Exon and Intron classes”. Licensed under Fair use via Wikipedia

Predic'on & Annota'on

14 GENE PREDICTION & ANNOTATION

PREDICTION & ANNOTATION

v  Iden'fica'on and annota'on of genome features:

•  primarily focuses on protein-‐coding genes. •  also iden'fies RNAs (tRNA, rRNA, long and small non-‐coding

RNAs (ncRNA)), regulatory mo'fs, repe''ve elements, etc.

•  happens in 2 phases: 1.  Computa'on phase 2.  Annota'on phase


COMPUTATION PHASE

a.   Experimental data are aligned to the genome: expressed sequence tags, RNA-‐sequencing reads, proteins (also from other species).

b.   Gene predic;ons are generated: -‐ ab ini$o: based on nucleo'de sequence and composi'on e.g. Augustus, GENSCAN, geneid, fgenesh, etc.

-‐ evidence-‐driven: iden'fying also domains and mo'fs e.g. SGP2, JAMg, fgenesh++, etc.

Result: the single most likely coding sequence, no UTRs, no isoforms. Yandell & Ence. Nature Rev 2012 doi:10.1038/nrg3174


ANNOTATION PHASE

Experimental data (evidence) and predic'ons are synthe'zed into gene annota'ons.

Result: gene models that generally include UTRs, isoforms, evidence trails.

Yandell & Ence. Nature Rev 2012 doi:10.1038/nrg3174

5’ UTR 3’ UTR

17

In some cases algorithms and metrics used to generate consensus sets may actually reduce the accuracy of the gene’s representa'on.

CONSENSUS GENE SETS

Gene models may be organized into sets using: v  combiners for automa'c integra'on of predicted sets

e.g: GLEAN, EvidenceModeler

or v  tools packaged into pipelines

e.g: MAKER, PASA, Gnomon, Ensembl, etc.

GENE PREDICTION & ANNOTATION

ANNOTATIONneeds some refinement

No one is perfect, least of all automated annotation. 18

New technologies bring new challenges: •  Assembly errors can cause fragmented

annota'ons •  Limited coverage makes precise

iden'fica'on a difficult task

Image: www.BroadInstitute.org

MANUAL ANNOTATIONimproving predictions

Precise elucida;on of biological features encoded in the genome requires careful

examina;on and review.

Schiex et al. Nucleic Acids 2003 (31) 13: 3738-‐3741

Automated Predictions

Experimental Evidence

Manual Annotation – to the rescue. 19

cDNAs, HMM domain searches, RNAseq, genes from other species.

GENOME CURATIONan inherently collaborative task

GENE PREDICTION & ANNOTATION 20

So many sequences, not enough hands.

Apis mellifera | Alexander Wild | www.alexanderwild.com

We have provided continuous training and support for hundreds of geographically dispersed scientists to conduct manual annotations efforts in order to recover coding sequences in agreement with all available biological evidence.

21

Lessons learned

APOLLO

•  Collaborative work distills invaluable knowledge.

•  A little training goes a long way! Wet lab scientists can easily learn to maximize the generation of accurate, biologically supported gene models.

Apollo

APOLLO: versatile genome annotation editing •  Apollo is a web-based genome annotation editor, integrated with JBrowse

•  Supports real time collaboration & generates analysis-ready data

USER-CREATED ANNOTATIONS

EVIDENCE TRACKS

ANNOTATOR PANEL

BECOMING ACQUAINTED WITH APOLLO 24

General process of curation

1.  Select or find a region of interest, e.g. scaffold. 2.  Select appropriate evidence tracks to review the gene model.

3.  Determine whether a feature in an exis'ng evidence track will provide a reasonable gene model to start working.

4.  If necessary, adjust the gene model.

5.  Check your edited gene model for integrity and accuracy by comparing it with available homologs.

6.   Comment and finish.

Apollo - version at i5K Workspace@NAL

25 4. Becoming Acquainted with Web Apollo.

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The Sequence Selec'on Window

Sort

Apollo - version at i5K Workspace@NAL

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“Old Track Select Page”

4. Becoming Acquainted with Web Apollo.

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APOLLOannotation editing environment

BECOMING ACQUAINTED WITH APOLLO

Color by CDS frame, toggle strands, set color scheme and highlights.

-‐ Upload evidence files (GFF3, BAM, BigWig), -‐ combina;on track -‐ sequence search track

Query the genome using BLAT.

Naviga'on and zoom.

Search for a gene model or a scaffold.

Get coordinates and “rubber band” selec'on for zooming.

Login

User-‐created annota'ons. New

annotator panel.

Evidence Tracks

Stage and cell-‐type specific transcrip'on data.

h;p://genomearchitect.org/web_apollo_user_guide

28 | 28 BECOMING ACQUAINTED WITH APOLLO

USER NAVIGATION

Annotator panel.

•  Choose appropriate evidence from list of “Tracks” on annotator panel.

•  Select & drag elements from evidence track into the ‘User-‐created Annota$ons’ area.

•  Hovering over annota'on in progress brings up an informa'on pop-‐up.

•  Crea'ng a new annota'on

Adding a gene model

Adding a gene model

Adding a gene model

Editing functionality

Editing functionality Example: Adding an exon supported by experimental data

•  RNAseq reads show evidence in support of a transcribed product that was not predicted. •  Add exon by dragging up one of the RNAseq reads.

Editing functionality Example: Adjusting exon boundaries supported by experimental data

Cura'ng with Apollo

36 | 36

USER NAVIGATION


•  ‘Zoom to base level’ reveals the DNA Track.

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USER NAVIGATION


•  Color exons by CDS from the ‘View’ menu.

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Zoom in/out with keyboard: shio + arrow keys up/down

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USER NAVIGATION


•  Toggle reference DNA sequence and transla;on frames in forward strand. Toggle models in either direc'on.

annota'ng simple cases

“Simple case”: -‐ the predicted gene model is correct or nearly correct, and

-‐ this model is supported by evidence that completely or mostly agrees with the predic'on.

-‐ evidence that extends beyond the predicted model is assumed to be non-‐coding sequence.

The following are simple modifica'ons.

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ANNOTATING SIMPLE CASES

BECOMING ACQUAINTED WITH APOLLO SIMPLE CASES

•  A confirma'on box will warn you if the receiving transcript is not on the same strand as the feature where the new exon originated.

•  Check ‘Start’ and ‘Stop’ signals aoer each edit.

41

ADDING EXONS


If transcript alignment data are available & extend beyond your original annota'on, you may extend or add UTRs.

1.  Right click at the exon edge and ‘Zoom to base level’.

2.  Place the cursor over the edge of the exon un$l it becomes a black arrow then click and drag the edge of the exon to the new coordinate posi'on that includes the UTR.

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ADDING UTRs

To add a new spliced UTR to an exis'ng annota'on also follow the procedure for adding an exon.


To modify an exon boundary and match data in the evidence tracks: select both the [offending] exon and the feature with the expected boundary, then right click on the annota'on to select ‘Set 3’ end’ or ‘Set 5’ end’ as appropriate.

In some cases all the data may disagree with the annota'on, in other cases some data support the annota'on and some of the

data support one or more alterna've transcripts. Try to annotate as many alterna've transcripts as are well supported by the data.

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MATCHING EXON BOUNDARY TO EVIDENCE


Non-‐canonical splice sites flags. Double click: selec'on of feature and sub-‐features

Evidence Tracks Area

‘User-‐created Annota$ons’ Track

Edge-‐matching

Apollo’s edi'ng logic (brain): §  selects longest ORF as CDS §  flags non-‐canonical splice sites

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ORFs AND SPLICE SITES


Non-‐canonical splices are indicated by an orange circle with a white exclama'on point inside, placed over the edge of the offending exon.

Canonical splice sites:

3’-‐…exon]GA / TG[exon…-‐5’

5’-‐…exon]GT / AG[exon…-‐3’ reverse strand, not reverse-‐complemented:

forward strand

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SPLICE SITES

Zoom to review non-‐canonical splice site warnings. Although these may not always have to be corrected (e.g GC donor), they should be flagged with a comment.

Exon/intron splice site error warning

Curated model


Apollo calculates the longest possible open reading frame (ORF) that includes canonical ‘Start’ and ‘Stop’ signals within the predicted exons.

If ‘Start’ appears to be incorrect, modify it by selec'ng an in-‐frame ‘Start’ codon further up or downstream, depending on evidence (proteins, RNAseq).

It may be present outside the predicted gene model, within a region supported by another evidence track.

In very rare cases, the actual ‘Start’ codon may be non-‐canonical (non-‐ATG).

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‘Start’ AND ‘Stop’ SITES


1.  Two exons from different tracks sharing the same start/end coordinates display a red bar to indicate matching edges.

2.  Selec'ng the whole annota'on or one exon at a 'me, use this edge-‐matching func'on and scroll along the length of the annota'on, verifying exon boundaries against available data. Use square [ ] brackets to scroll from exon to exon. User curly { } brackets to scroll from annota'on to annota'on.

3.  Check if cDNA / RNAseq reads lack one or more of the annotated exons or include addi'onal exons.

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CHECKING EXON INTEGRITY


annota'ng complex cases

Evidence may support joining two or more different gene models. Warning: protein alignments may have incorrect splice sites and lack non-‐conserved regions!

1.  In ‘User-‐created Annota<ons’ area shio-‐click to select an intron from each gene model and right click to select the ‘Merge’ op'on from the menu.

2.  Drag suppor'ng evidence tracks over the candidate models to corroborate overlap, or review edge matching and coverage across models.

3.  Check the resul'ng transla'on by querying a protein database e.g. UniProt, NCBI nr. Add comments to record that this annota'on is the result of a merge.

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Red lines around exons: ‘edge-‐matching’ allows annotators to confirm whether the evidence is in agreement without examining each exon at the base level.

COMPLEX CASES merge two gene predictions on the same scaffold

BECOMING ACQUAINTED WITH APOLLO COMPLEX CASES

One or more splits may be recommended when: -‐ different segments of the predicted protein align to two or more different gene families -‐ predicted protein doesn’t align to known proteins over its en're length -‐ Transcript data may support a split, but first verify whether they are alterna've transcripts.

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COMPLEX CASES split a gene prediction


DNA Track

‘User-‐created Annota;ons’ Track

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COMPLEX CASES annotate frameshifts and correct single-base errors

Always remember: when annota'ng gene models using Apollo, you are looking at a ‘frozen’ version of the genome assembly and you will not be able to modify the assembly itself.


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COMPLEX CASES correcting selenocysteine containing proteins


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COMPLEX CASES correcting selenocysteine containing proteins


1.  Apollo allows annotators to make single base modifica'ons or frameshios that are reflected in the sequence and structure of any transcripts overlapping the modifica'on. These manipula'ons do NOT change the underlying genomic sequence.

2.  If you determine that you need to make one of these changes, zoom in to the nucleo'de level and right click over a single nucleo'de on the genomic sequence to access a menu that provides op'ons for crea'ng inser'ons, dele'ons or subs'tu'ons.

3.  The ‘Create Genomic Inser<on’ feature will require you to enter the necessary string of nucleo'de residues that will be inserted to the right of the cursor’s current loca'on. The ‘Create Genomic Dele<on’ op'on will require you to enter the length of the dele'on, star'ng with the nucleo'de where the cursor is posi'oned. The ‘Create Genomic Subs<tu<on’ feature asks for the string of nucleo'de residues that will replace the ones on the DNA track.

4.  Once you have entered the modifica'ons, Apollo will recalculate the corrected transcript and protein sequences, which will appear when you use the right-‐click menu ‘Get Sequence’ op'on. Since the underlying genomic sequence is reflected in all annota'ons that include the modified region you should alert the curators of your organisms database using the ‘Comments’ sec'on to report the CDS edits.

5.  In special cases such as selenocysteine containing proteins (read-‐throughs), right-‐click over the offending/premature ‘Stop’ signal and choose the ‘Set readthrough stop codon’ op'on from the menu.

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COMPLEX CASES annotating frameshifts and correcting single-base errors & selenocysteines


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USER NAVIGATION


•  Information Editor

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The Annota'on Informa;on Editor

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USER NAVIGATION


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The Annota'on Informa;on Editor

•  Add PubMed IDs •  Include GO terms as appropriate

from any of the three ontologies •  Write comments sta'ng how you

have validated each model.

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USER NAVIGATION


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USER NAVIGATION


•  Keeping track of each edit

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Annota'ons, annota'on edits, and History: stored in a centralized database.

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USER NAVIGATION


Follow the checklist un'l you are happy with the annota'on!

And remember to… –  comment to validate your annota'on, even if you made no changes to an exis'ng model. Think of comments as your vote of confidence.

–  or add a comment to inform the community of unresolved issues you think this model may have.

60 | 60

Always Remember: Apollo cura'on is a community effort so please use comments to communicate the reasons for your

annota'on. Your comments will be visible to everyone.

COMPLETING THE ANNOTATION


Checklist

•  Check ‘Start’ and ‘Stop’ sites.

•  Check splice sites: most splice sites display these residues …]5’-‐GT/AG-‐3’[…

•  Check if you can annotate UTRs, for example using RNA-‐Seq data: – align it against relevant genes/gene family – blastp against NCBI’s RefSeq or nr

•  Check for gaps in the genome.

•  Addi'onal func'onality may be necessary: – merging 2 gene predic'ons -‐ same scaffold – merging 2 gene predic'ons -‐ different scaffolds

– spli`ng a gene predic'on – annota'ng frameshias – annota'ng selenocysteines, correc'ng single-‐base and other assembly errors, etc.

62 | 62

•  Add: –  Important project informa'on in the form of

comments –  IDs from public databases e.g. GenBank (via

DBXRef), gene symbol(s), common name(s), synonyms, top BLAST hits, orthologs with species names, and everything else you can think of, because you are the expert.

–  Comments about the kinds of changes you made to the gene model of interest, if any.

–  Any appropriate func'onal assignments, e.g. via BLAST, RNA-‐Seq data, literature searches, etc.

CHECKLIST for accuracy and integrity

MANUAL ANNOTATION CHECKLIST

Genome cura'on with i5k

64 i5K Workspace@NAL

The collaborative curation process at i5k

1.  A computa'onally predicted consensus gene set has been generated using mul'ple lines of evidence; e.g. HVIT_v0.5.3-‐Models

2.  i5K Projects will integrate consensus computa'onal predic'ons with

manual annota'ons to produce an updated Official Gene Set (OGS):

Achtung! •  If it’s not on either track, it won’t make the OGS! •  If it’s there and it shouldn’t, it will s'll make the OGS!

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The ‘Replace Models’ rules

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BECOMING ACQUAINTED WITH APOLLO http://tinyurl.com/apollo-i5k-replace

66 i5K Workspace@NAL

3.  In some cases algorithms and metrics used to generate consensus sets may actually reduce the accuracy of the gene’s representa'on. Use your judgment, try choosing a different model to begin the annota'on.

4.   Isoforms: drag original and alterna'vely spliced form to ‘User-‐created Annota<ons’ area.

5.  If an annota'on needs to be removed from the consensus set, drag it to the ‘User-‐created Annota<ons’ area and label as ‘Delete’ on the Informa$on Editor.

6.  Overlapping interests? Collaborate to reach agreement.

7.  Follow guidelines for i5K Pilot Species Projects, at h;p://goo.gl/LRu1VY

The collaborative curation process at i5k

Example

What’s new?... finding inspiration in PubMed.

Example 68

“Molecular analysis of bed bug populations from across the USA and Europe found that >80% and >95% of the respective populations contained V419L and/or L925I mutations in the voltage-gated sodium channel gene, indicating widespread distribution of target-site-based pyrethroid resistance.”

Homalodisca vitripennis | Alexander Wild | www.alexanderwild.com Halyomorpha halys | Fondazione Edmund Mach - Italy

Now for our species of interest. . .

Example

Example 69

Cura'on example using the Hyalella azteca genome (amphipod crustacean).

What do we know about this genome?

•  Currently publicly available data at NCBI: •  >37,000 nucleo'de seqsà scaffolds, mitochondrial genes •  344 amino acid seqsà mitochondrion •  47 ESTs •  0 conserved domains iden'fied •  0 “gene” entries submi;ed

•  Data at i5K Workspace@NAL (annota'on hosted at USDA) -‐ 10,832 scaffolds: 23,288 transcripts: 12,906 proteins

Example 70

PubMed Search: what’s new?

Example 71

PubMed Search: what’s new?

Example 72

“Ten popula'ons (3 cultures, 7 from California water bodies) differed by at least 550-‐fold in sensi;vity to pyrethroids.”

“By sequencing the primary pyrethroid target site, the voltage-‐gated sodium channel (vgsc), we show that point muta'ons and their spread in natural popula'ons were responsible for differences in pyrethroid sensi'vity.”

“The finding that a non-‐target aqua'c species has acquired resistance to pes'cides used only on terrestrial pests is troubling evidence of the impact of chronic pes;cide transport from land-‐based applica'ons into aqua'c systems.”

How many sequences are there, publicly available, for our gene of interest?

Example 73

•  Para, (voltage-‐gated sodium channel alpha subunit; Nasonia vitripennis).

•  NaCP60E (Sodium channel protein 60 E; D. melanogaster). –  MF: voltage-‐gated ca'on channel ac'vity (IDA, GO:0022843).

–  BP: olfactory behavior (IMP, GO:0042048), sodium ion transmembrane transport (ISS,GO:0035725).

–  CC: voltage-‐gated sodium channel complex (IEA, GO:0001518).

And what do we know about them?

Retrieving sequences for a sequence similarity search.

Example 74

>vgsc-‐Segment3-‐DomainII RVFKLAKSWPTLNLLISIMGKTVGALGNLTFVLCIIIFIFAVMGMQLFGKNYTEKVTKFKWSQDGQMPRWNFVDFFHSFMIVFRVLCGEWIESMWDCMYVGDFSCVPFFLATVVIGNLVVSFMHR

BLAT search

input

Example 75


BLAT search

results

Example 76

•  High-‐scoring segment pairs (hsp) are listed in tabulated format.

•  Clicking on one line of results sends you to those coordinates.

BLAST at i5K heps://i5k.nal.usda.gov/blast

Example 77


BLAST at i5K heps://i5k.nal.usda.gov/blast

Example 78

BLAST at i5K: hsps in “BLAST+ Results” track

Example 79

Creating a new gene model: drag and drop

Example 80

•  Apollo automa'cally calculates longest ORF.

•  In this case, ORF includes the high-‐scoring segment pairs (hsp), marked here in blue.

•  Note that gene is transcribed from reverse strand.

Available Tracks

Example 81

Get Sequence

Example 82

http://blast.ncbi.nlm.nih.gov/Blast.cgi

Also, flanking sequences (other gene models) vs. NCBI nr

Example 83

In this case, two gene models upstream, at 5’ end.

BLAST hsps

Review alignments

Example 84

HaztTmpM006234

HaztTmpM006233

HaztTmpM006232

Hypothesis for vgsc gene model

Example 85

Editing: merge the three models

Example 86

Merge by dropping an exon or gene model onto another.

Merge by selec'ng two exons (holding down “Shio”) and using the right click menu.

or…

Result of merging the gene models:

Example 87

Editing: correct offending splice site

Example 88

Modify exon / intron boundary: -‐  Drag the end of the

exon to the nearest canonical splice site.

or

-‐  Use right-‐click menu.

Editing: set translation start

Example 89

Editing: delete exon not supported by evidence

Example 90

Delete first exon from HaztTmpM006233

Editing: add an exon supported by RNAseq

Example 91

•  RNAseq reads show evidence in support of transcribed product, which was not predicted. •  Add exon at coordinates 97946-‐98012 by dragging up one of the RNAseq reads.

Editing: adjust offending splice site using evidence

Example 92

Editing: adjust other boundaries supported by evidence

Example 93

Finished model

Example 94

Corroborate integrity and accuracy of the model: -‐ Start and Stop -‐ Exon structure and splice sites …]5’-‐GT/AG-‐3’[… -‐ Check the predicted protein product vs. NCBI nr, UniProt, etc.

Information Editor

•  DBXRefs: e.g. NP_001128389.1, N. vitripennis, RefSeq

•  PubMed iden'fier: PMID: 24065824

•  Gene Ontology IDs: GO:0022843, GO:0042048, GO:0035725, GO:0001518.

•  Comments

•  Name, Symbol

•  Approve / Delete radio bu;on

Example 95

Comments (if applicable)

Go play!

PUBLIC DEMO 97 | 97

APOLLO ON THE WEBinstructions

At i5K 1.  Register for access to Apollo at the i5K Workspace@NAL at

h;ps://i5k.nal.usda.gov/web-‐apollo-‐registra'on

2.  Contact the coordinator for each species community to receive more informa'on about how to contribute. Contact info is available on each organism’s page.

PUBLIC DEMO 98 | 98

APOLLO ON THE WEBinstructions

Public Honey bee demo available at: h;p://GenomeArchitect.org/WebApolloDemo

Username: [email protected]

Password: demo

APOLLOdemonstration

PUBLIC DEMO 99

Demonstra'on video is available at h;ps://youtu.be/VgPtAP_fvxY

OUTLINE

Apollo Collabora've Cura'on and Interac've Analysis of Genomes

100 OUTLINE

•  BIO-‐REFRESHER biological concepts for cura'on

•  ANNOTATION automa'c predic'ons

•  MANUAL ANNOTATION necessary, collabora've

•  APOLLO

advancing collabora've cura'on •  EXAMPLE

demos

Apollo Development

Nathan Dunn Eric Yao

Christine Elsik’s Lab, University of Missouri

Suzi Lewis Principal Investigator

BBOP

Moni Munoz-Torres Colin Diesh Deepak Unni

JBrowse. Ian Holmes’ Lab University of California, Berkeley

•  Berkeley Bioinformatics Open-source Projects (BBOP), Berkeley Lab: Apollo and Gene Ontology teams. Suzanna E. Lewis (PI).

•  § Christine G. Elsik (PI). University of Missouri. •  * Ian Holmes (PI). University of California Berkeley. •  Arthropod genomics community & i5K Steering

Committee. •  Stephen Ficklin, GenSAS, Washington State University •  Apollo is supported by NIH grants 5R01GM080203

from NIGMS, and 5R01HG004483 from NHGRI. Also supported by the Director, Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231

•  For your attention, thank you!

Apollo Nathan Dunn Colin Diesh § Deepak Unni §

Gene Ontology

Chris Mungall

Seth Carbon

Heiko Dietze

BBOP

Learn more about Apollo at http://GenomeArchitect.org

Thank you!

NAL at USDA

Monica Poelchau

Mei-Ju Chen

Christopher Childers

Gary Moore

HGSC at BCM

fringy Richards

Kim Worley

JBrowse Eric Yao *