Genome Browsers

Genome Browsers

Tyra G. Wolfsberg

Introduction

The first complete sequence of a eukaryotic genome – that of Saccharomyces cerevisiae – was published in 1996 (Goffeau et al. 1996). The chromosomes of this organism, which range in size from 270 to 1500 kb, presented an immediate challenge in data management, as the upper limit for single database entries in GenBank at the time was 350 kb. To better manage the yeast genome sequence, as well as other chromosome and genome-length sequences being deposited into GenBank around that time, the National Center for Biotechnology Information (NCBI) at the National Institutes of Health (NIH) established the Genomes division of Entrez (Benson et al. 1997). Entries in this division were organized around a reference sequence onto which all other sequences from that organism were aligned. As these reference sequences have no size limit, “virtual” reference sequences of large genomes or chromosomes could be assembled from shorter GenBank sequences. For partially sequenced chromosomes, NCBI developed methods to integrate genetic, physical, and cytogenetic maps onto the framework of the whole chromosome. Thus, Entrez Genomes was able to provide the first graphical views of large-scale genomic sequence data.

The working draft of the human genome, completed in February 2001 (Lander et al. 2001), generated virtual reference sequences for each human chromosome, ranging in size from 46 to 246 Mb. NCBI created the first version of its human Map Viewer (Wheeler et al. 2001) shortly thereafter, in order to display these longer sequences. Around the same time, the University of California, Santa Cruz (UCSC) Genome Bioinformatics Group was developing its own human genome browser, based on software originally designed for displaying the much smaller Caenorhabditis elegans genome (Kent and Zahler 2000). Similarly, the Ensembl project at the European Molecular Biology Laboratory’s European Bioinformatics Institute (EMBL-EBI) was also producing a system to automatically annotate the human genome sequence, as well as store and visualize the data (Hubbard et al. 2002). The three genome browsers all came online at about the same time, and researchers began using them to help navigate the human genome (Wolfsberg et al. 2002). Today, each site provides free access not only to human sequence data but also to a myriad of other assembled genomic sequences, from commonly used model organisms such as mouse to more recently released assemblies such as those of the domesticated turkey. Although the NCBI’s Map Viewer is not being further developed and will be replaced by its new Genome Data Viewer (Sayers et al. 2019), the UCSC and Ensembl Genome Browsers continue to be popular resources, used by most members of the bioinformatics and genomics communities. This chapter will focus on the last two genome browsers.

The reference human genome was sequenced in a clone-by-clone shotgun sequencing strategy and was declared complete in April 2003, although sequencing of selected regions is still continuing. This strategy includes constructing a bacterial artificial chromosome (BAC) tiling map for each human chromosome, then sequencing each BAC using a shotgun sequencing approach (reviewed in Green 2001).

Genome Browsers

The sequences of individual BACs were deposited into the High Throughput Genomic (HTG) division of GenBank as they became available. UCSC began assembling these BAC sequences into longer contigs in May 2000 (Kent and Haussler 2001), followed by assembly efforts undertaken at NCBI (Kitts 2003). These contigs, which contained gaps and regions of uncertain order, became the basis for the development of the genome browsers. Over time, as the genome sequence was finished, the human genome assembly was updated every few months. After UCSC stopped producing its own human genome assemblies in August 2001, NCBI built eight reference human genome assemblies for the bioinformatics community, culminating with a final assembly in March 2006. Subsequently, an international collaboration that includes the Wellcome Trust Sanger Institute (WTSI), the Genome Institute at Washington University, EBI, and NCBI formed the Genome Reference Consortium (GRC), which took over responsibility for subsequent assemblies of the human genome. This consortium has produced two human genome assemblies, namely GRCh37 in February 2009 and GRCh38 in December 2013. As one might expect, each new genome assembly leads to changes in the sequence coordinates of annotated features. In between the release of major assemblies, GRC creates patches, which either correct errors in the assembly or add alternate loci. These alternate loci are multiple representations of regions that are too variable to be represented by a single reference sequence, such as the killer cell immunoglobulin-like receptor (KIR) gene cluster on chromosome 19 and the major histocompatibility complex (MHC) locus on chromosome 6. Unlike new genome assemblies, patches do not affect the chromosomal coordinates of annotated features. GRCh38.p10 has 282 alternate loci or patches.

While the GRC also assembles the mouse, zebrafish, and chicken genomes, other genomes are sequenced and assembled by specialized sequencing consortia. The panda genome sequence, published in 2009, was the first mammalian genome to abandon the clone-based sequencing strategies used for human and mouse, relying entirely on next generation sequencing methodologies (Li et al. 2010). Subsequent advances in sequencing technologies have led to rapid increases in the number of complete genome sequences. At the time of this writing, both the UCSC Genome Browser and the main Ensembl web site host genome assemblies of over 100 organisms. The look and feel of each genome browser is the same regardless of the species displayed; however, the types of annotation differ depending on what data are available for each organism.

The backbone of each browser is an assembled genomic sequence. Although the underlying genomic sequence is, with a few exceptions, the same in both genome browsers, each team calculates its annotations independently. Depending on the type of analysis, a user may find that one genome browser has more relevant information than the other. The location of genes, both known and predicted, is a central focus of both genome browsers. For human, at present, both browsers feature the GENCODE gene predictions, an effort that is aimed at providing robust evidence-based reference gene sets (Harrow et al. 2012). Other types of genomic data are also mapped to the genome assembly, including NCBI reference sequences, single-nucleotide polymorphisms (SNPs) and other variants, gene regulatory regions, and gene expression data, as well as homologous sequences from other organisms. Both genome browsers can be accessed through a web interface that allows users to navigate through a graphical view of the genome. However, for those wishing to carry out their own calculations, sequences and annotations can also be retrieved in text format. Each browser also provides a sequence search tool – BLAT (Kent 2002) or BLAST (Camacho et al. 2009) – for interrogating the data via a nucleotide or protein sequence query. (Additional information on both BLAT and BLAST is provided in Chapter 3.)

In order to provide stability and ensure that old analyses can be reproduced, both genome browsers make available not only the current version of the genome assemblies but older ones as well. In addition, annotation tracks, such as the GENCODE gene track and the SNP track, may be based on different versions of the underlying data. Thus, users are encouraged to verify the version of all data (both genome assembly and annotations) when comparing a region of interest between the UCSC and Ensembl Genome Browsers.

The UCSC Genome Browser

This chapter presents general guidelines for accessing the genome sequence and annotations using the UCSC and Ensembl Genome Browsers. Although similar analyses could be carried out with either browser, we have chosen to use different examples at the two sites to illustrate different types of questions that a researcher might want to ask. We finish with a short description of JBrowse (Buels et al. 2016), another web-based genome browser that users can set up on their own servers to share custom genome assemblies and annotations. All of the resources discussed in this chapter are freely available.

Stopped before the next real section heading: "The UCSC Genome Browser".

This chapter presents general guidelines for accessing the genome sequence and annotations

using the UCSC and Ensembl Genome Browsers. Although similar analyses could be carried

out with either browser, we have chosen to use different examples at the two sites to illustrate

different types of questions that a researcher might want to ask. We finish with a short descrip-

tion of JBrowse (Buels et al. 2016), another web-based genome browser that users can set up

on their own servers to share custom genome assemblies and annotations. All of the resources

discussed in this chapter are freely available.

The UCSC Genome Browser

After starting in 2000 with just a display of an early draft of the human genome assembly,

the UCSC Genome Browser now provides access to assemblies and annotations from over 100

organisms (Haeussler et al. 2019). The majority of assemblies are of mammalian genomes, but

other vertebrates, insects, nematodes, deuterostomes, and the Ebola virus are also included.

The assemblies from some organisms, including human and mouse, are available in multiple

versions. New organisms and assembly versions are added regularly.

The UCSC Browser presents genomic annotation in the form of tracks. Each track provides a

different type of feature, from genes to SNPs to predicted gene regulatory regions to expression

data. Each organism has its own set of tracks, some created by the UCSC Genome Bioinformat-

ics team and others provided by members of the bioinformatics community. Over 200 tracks are

available for the GRCh37 version of the human genome assembly. The newer human genome

assembly, GRCh38, has fewer tracks, as not all the data have been remapped from the older

assembly. Other genomes are not as well annotated as human; for example, fewer than 20

tracks are available for the sea hare. Some tracks, such as those created from NCBI transcript

data, are updated weekly, while others, such as the SNP tracks created from NCBI variant data

(Sayers et al. 2019), are updated less frequently, depending on the release schedule of the under-

lying data. For ease of use, tracks are organized into subsections. For example, depending on

the organism, the Genes and Gene Predictions section may include evidence-based gene pre-

dictions, ab initio gene predictions, and/or alignment of protein sequences from other species.

The home page of the UCSC Genome Browser provides a stepping-off point for many of the

resources developed by the Genome Bioinformatics group at UCSC, including the Genome

Browser, BLAT, and the Table Browser, which will be described in detail later in this chapter.

The Tools menu provides a link to liftOver, a widely used tool that converts genomic coordinates

from one assembly to another. Using this tool, it is possible to update annotation files so that old

data can be integrated into a new genome assembly. The Download menu provides an option

to download all the sequence and annotation data for each genome assembly hosted by UCSC,

as well as some of the source code. The What’s New section provides updates on new genome

assemblies, as well as new tools and features. Finally, there is an extensive Help menu, with

detailed documentation as well as videos. Users may also submit questions to a mailing list,

and most queries are answered within a day.

The UCSC Genome Browser provides multiple ways for both individual users and larger

genome centers to share data with collaborators or even the entire bioinformatics commu-

nity. These sharing options are available on the My Data link on the home page. Custom

Tracks allow users to display their own data as a separate annotation track in the browser.

User data must be formatted in a standard data structure in order to be interpreted correctly by

the browser. Many commonly used file formats are supported, including Browser Extensible

Data (BED), Binary Alignment/Map (BAM), and Variant Call Format (VCF; Box 4.1). Small

data files can be uploaded or pasted into the Genome Browser for personal use. Larger files

must be saved on the user’s web server and accessed by URL through the Genome Browser.

As anyone with the URL can access the data, this method can be used to share data with col-

laborators. Alternatively, Custom Tracks, along with track configurations and settings, can be

shared with selected collaborators using a named Session. Some groups choose to make their

Sessions available to the world at large in My Data →Public Sessions. Finally, groups with very

large datasets can host their data in the form of a Track Hub so that it can be viewed on the

UCSC Genome Browser. When a Track Hub is paired with an Assembly Hub, it can be used to

create a browser for a genome assembly not already hosted by UCSC.

Box 4.1 Common File Types for Genomic Data

Both the UCSC and Ensembl Genome Browsers allow users to upload their own data so

that they can be viewed in context with other genome-scale data. User data must be

formatted in a commonly used data structure in order to be interpreted correctly by the

browser.

Browser Extensible Data (BED) format is a tab-delimited format that is flexible enough to

display many types of data. It can be used to display fairly simple features like the

location of transcription binding factor sites, as well more complex ones like transcripts

and their exons.

Binary Alignment/Map (BAM) format is the compressed binary version of the Sequence Align-

ment/Map (SAM) format. It is a compact format designed for use with very large files of

nucleotide sequence alignments. Because it can be indexed, only the portion of the file

that is needed for display is transferred to the browser. Many tools for next generation

sequence analysis use BAM format as output or input.

Variant Call Format (VCF) is a flexible format for large files of variation data including

single-nucleotide variants, insertions/deletions, copy number variants, and structural

variants. Like BAM format, it is compressed and indexed, and only the portion of the file

that is needed for display is transferred to the browser. Many tools for variant analysis

use VCF format as output or input.

The UCSC Genome Browser home page lists commonly accessed tools, as well as a

frequently updated news section that highlights major data and software updates. To reach

the Genome Browser Gateway, the main entry point for text-based searches, click on the

Gateway link on the home page (Figure 4.1). The default assembly is the most recent

human assembly, GRCh38, from December 2013. The genomes of other species can be

selected from the phylogenetic tree on the left side of the Gateway page, or by typing

their name in the selection box. On the human Gateway page, there is also the option to

select one of four older human genome assemblies. Details about the GRCh38 assembly

and instructions for searching are available on the Gateway page.

To perform a search, enter text into the Position/Search Term box. If the query maps to a

unique position in the genome, such as a search for a particular chromosome and position, the

Go button links directly to the Genome Browser. However, if there is more than one hit for the

query, such as a search for the term metalloprotease, the resulting page will contain a list

of results that all contain that term. For some species, the terms have been indexed, and typing

a gene symbol into the search box will bring up a list of possible matches. In this example, we

will search for the human hypoxia inducible factor 1 alpha subunit (HIF1A) gene (Figure 4.1),

which produces a single hit on GRCh38.

The default Genome Browser view showing the genomic context of the HIF1A gene is shown

in Figure 4.2. The navigation controls are presented across the top of the display. The arrows

move the window to the left and right along the chromosome. Alternatively, the user can

move the display left and right by holding down the mouse button and dragging the window.

To zoom in and out, use the buttons at the top of the display. The base button zooms in so

far that individual nucleotides are displayed, while the zoom out 100× button will show the

entire chromosome if it is pressed a few times. The current genomic position and the length

of window (in nucleotides) is shown above a schematic of chromosome 14, where the current

The UCSC Genome Browser

Figure 4.1 The home page of the UCSC Genome Browser, showing a query for the gene HIF1A on the human GRCh38 genome assembly.

The organism can be selected by clicking on its name in the phylogenetic tree. For many organisms, more than one genome assembly is

available. Typing a term into the Position/Search Term box returns a list of matching gene symbols.

genomic position is highlighted with a red box. A new search term can be entered into the

search box.

Below the browser window illustrated in Figure 4.2, one would find a list of tracks that

are available for display on the assembly. The tracks are separated into nine categories: Map-

ping and Sequencing, Genes and Gene Predictions, Phenotype and Literature, mRNA and

Expressed Sequence Tag (EST), Expression, Regulation, Comparative Genomics, Variation,

and Repeats. Clicking on a track name opens the Track Settings page for that track, provid-

ing a description of the data displayed in that track. Most tracks can be displayed in one of the

following five modes.

1. Hide: the track is not displayed at all.
2. Dense: all features are collapsed into a single line; features are not labeled.
3. Squish: each feature is shown separately, but at 50% the height of full mode; features are

not labeled.

1. Pack: each feature is shown separately, but not necessarily on separate lines; features are

labeled.

1. Full: each feature is labeled and displayed on a separate line.

Figure 4.2 The default view of the UCSC Genome Browser, showing the genomic context of the human HIF1A gene.

In order to simplify the display, most tracks are in hide mode by default. To change the

mode, use the pull-down menu below the track name or on the Track Settings page. Other

settings, such as color or annotation details, can also be configured on the Track Settings page.

For example, the NCBI RefSeq track allows users to select if they want to view all reference

sequences or only those that are curated or predicted (Box 1.2). One possible point of confusion

is that the UCSC Genome Browser will “remember” the mode in which each track is displayed

from session to session. Custom settings can be cleared by selecting Reset all User Settings under

the Genome Browser pull-down menu at the top of any page.

The annotation tracks in the window below the chromosome are the focus of the Genome

Browser (Figure 4.2). Tracks are depicted horizontally, with a title above the track and labels

on the left. The first two lines show the scale and chromosomal position. The term that was

searched for and matched (HIF1A in this case) is highlighted on the annotation tracks. The

next tracks shown by default are gene prediction tracks. The default gene track on GRCh38

is the GENCODE Genes set, which replaces the UCSC Genes track that is still displayed on

GRCh37 and older human assemblies. GENCODE genes are annotated using a combination

of computational analysis and manual curation, and are used by the ENCODE Consortium

and other groups as reference gene sets (Box 4.2). The GENCODE v24 track depicts all of the

gene models from the GENCODE v24 release, which includes both protein-coding genes and

non-coding RNA genes.

The UCSC Genome Browser

Box 4.2 GENCODE

The GENCODE gene set was originally developed by the ENCODE Consortium as a com-

prehensive source of high-quality human gene annotations (Harrow et al. 2012). It has

now been expanded to include the mouse genome (Mudge and Harrow 2015). The goal of

the GENCODE project is to include all alternative splice variants of protein-coding loci, as

well as non-coding loci and pseudogenes. The GENCODE Consortium uses computational

methods, manual curation, and experimental validation to identify these gene features.

The first step is carried out by the same Ensembl gene annotation pipeline that is used

to annotate all vertebrate genomes displayed at Ensembl (Aken et al. 2016). This pipeline

aligns cDNAs, proteins, and RNA-seq data to the human genome in order to create can-

didate transcript models. All Ensembl transcript models are supported by experimental

evidence; no models are created solely from ab initio predictions. The Human and Verte-

brate Analysis and Annotation (HAVANA) group produces manually curated gene sets for

several vertebrate genomes, including mouse and human. These manually curated genes

are merged with the Ensembl transcript models to create the GENCODE gene sets for

mouse and human. A subset of the human models has been confirmed by an experimental

validation pipeline (Howald et al. 2012).

The consortium makes available two types of GENCODE gene sets. The Comprehen-

sive set encompasses all gene models, and may include many alternatively spliced tran-

scripts (isoforms) for each gene. The Basic set includes a subset of representative tran-

scripts for each gene that prioritizes full-length protein-coding transcripts over partial- or

non-protein-coding transcripts. The Ensembl Genome Browser displays the Comprehen-

sive set by default. Although the UCSC Genome Browser displays the Basic set by default,

the Comprehensive set can be selected by changing the GENCODE track settings. At the

time of this writing, Ensembl is displaying GENCODE v27, released in August 2017. The

GENCODE version available by default at the UCSC Genome Browser is v24, from Decem-

ber 2015. More recent versions of GENCODE can be added to the browser by selecting

them in the All GENCODE super-track.

GENCODE and RefSeq both aim to provide a comprehensive gene set for mouse and

human. Frankish et al. (2015) have shown that, in human, the RefSeq gene set is more

similar to the GENCODE Basic set, while the GENCODE Comprehensive set contains more

alternative splicing and exons, as well as more novel protein-coding sequences, thus cov-

ering more of the genome. They also sought to determine which gene set would provide

the best reference transcriptome for annotating variants. They found that the GENCODE

Comprehensive set, because of its better genomic coverage, was better for discovering new

variants with functional potential, while the GENCODE Basic set may be better suited for

applications where a less complex set of transcripts is needed. Similarly, Wu et al. (2013)

compared the use of different gene sets to quantify RNA-seq reads and determine gene

expression levels. Like Frankish et al., they recommend using less complex gene anno-

tations (such as the RefSeq gene set) for gene expression estimates, but more complex

gene annotations (such as GENCODE) for exploratory research on novel transcriptional or

regulatory mechanisms.

In the GENCODE track, as well as other gene tracks, exons (regions of the transcript that

align with the genome) are depicted as blocks, while introns are drawn as the horizontal

lines that connect the exons. The direction of transcription is indicated by arrowheads on

the introns. Coding regions of exons are depicted as tall blocks, while non-coding exons

are shorter. In this example, the GENCODE track depicts five alternatively spliced tran-

scripts, labeled HIF1A on the left, for the HIF1A gene. As shown by the arrowheads, all

transcripts are transcribed from left to right. The 5′-most exon of each transcript (on the

left side of the display) is shorter on the left, indicating an untranslated region (UTR), and

(Continued)

Box 4.2 (Continued)

taller on the right, indicating a coding sequence. The reverse is true for the 3′-most exon

of each transcript. A very close visual inspection of the Genome Browser shows that the

last four HIF1A transcripts have a different pattern of exons from each other; a BLAST

search (not shown) reveals that first two transcripts differ by only three nucleotides in

one exon. There is also a transcript labeled HIF1A-AS2, an anti-sense HIF1A transcript that

is transcribed from right to left. Another transcript, labeled RP11-618G20.1, is a synthetic

construct DNA. Zooming the display out by 3× allows a view of the genes immediately

upstream and downstream of HIF1A (Figure 4.3). A second HIF1A antisense transcript,

HIF1A-AS1, is also visible.

The track below the GENCODE track is the RefSeq gene predictions from NCBI track. This is

a composite track showing human protein-coding and non-protein-coding genes taken from

the NCBI RNA reference sequences collection (RefSeq; Box 1.2). By default, the RefSeq track

is shown in dense mode, with the exons of the individual transcripts condensed into a single

line (Figure 4.2). Note that, in this dense mode, the exons are displayed as blocks, as in the

GENCODE track, but there are no arrowheads on the gene model to show the direction of

transcription. To change the display of the RefSeq track to view individual transcripts, open

the Track Settings page for the NCBI RefSeq track by clicking on the track name in the first row

Figure 4.3 The genomic context of the human HIF1A gene, after clicking on zoom out 3×. The genes immediately upstream (FLJ22447) and

downstream (SNAPC1) of HIF1A are now visible.

The UCSC Genome Browser

Figure 4.4 The RefSeq Track Settings page. The track settings pages are used to configure the display of annotation tracks. By default, all

of the RefSeq tracks are set to display in dense mode, with all features condensed into a single line. In this example, the Curated RefSeqs

are being set to display in full mode, in which each RefSeq transcript will be labeled and displayed on a separate line. The remainder of

the RefSeqs will be displayed in dense mode. The types of RefSeqs, curated and predicted, are described in Box 1.2. After changing the

settings, press the submit button to apply them.

of the Genes and Gene Predictions section (below the graphical view shown in Figure 4.2). The

resulting Track Settings page (Figure 4.4) allows the user to choose which type of RefSeqs to

display (e.g. all, curated only, or predicted only). In this example, we change the mode of the

RefSeq Curated track from dense to full, and the resulting graphical view (Figure 4.5) displays

each curated RefSeq as a separate transcript. In contrast to the GENCODE track, there are

only three RefSeq transcripts for the HIF1A gene, and the HIF1A-AS2 RefSeq transcript is

much shorter than the GENCODE transcript with the same name. These discrepancies are

due to differences in how the RefSeq and GENCODE transcript sets are assembled (Boxes 1.2

and 4.2).

Additional information about each transcript in the GENCODE and RefSeq tracks is avail-

able by clicking on the gene symbol (HIF1A, in this case); as the original search was for HIF1A,

Figure 4.5 The genomic context of the human HIF1A gene, after displaying RefSeq Curated genes in full mode. Each RefSeq transcript is

now drawn on a separate line, so that individual exons, as well as the direction of transcription, are visible. Compare this rendition with

Figure 4.2, where all RefSeq transcripts are condensed on a single line.

Figure 4.6 The Get Genomic Sequence page that provides an interface for users to retrieve the sequence for a feature of interest. Click on

an individual transcript in the GENCODE or RefSeq track to open a page with additional details for that transcript. On either of those details

pages, click the link for Genomic Sequence to open the page displayed here, which provides choices for retrieving sequences upstream

or downstream of the transcript, as well as intron or exon sequences. In this example, retrieve the sequence 1000 nt upstream of the

annotated transcription start site. Shown in the inset is the result of retrieving the FASTA-formatted sequence 1000 nt upstream of the

HIF1A transcript.

the gene name is highlighted in inverse type. For GENCODE genes, UCSC has collected infor-

mation from a variety of public sources and includes a text description, accession numbers,

expression data, protein structure, Gene Ontology terms, and more. For RefSeq transcripts,

UCSC provides links to NCBI resources. Both GENCODE and RefSeq details pages provide a

link to Genomic Sequence in the Sequence and Links section, allowing users to retrieve genomic

sequences connected to an individual transcript. From the selection menu (Figure 4.6), users

can choose whether to download the sequence upstream or downstream of the gene, as well

as the exon or intron sequence. The sequence is returned in FASTA format.

Further down on the graphical view shown in Figure 4.3 are tracks from the ENCODE

Regulation super-track: Layered H3K27Ac and DNase Clusters. These data were generated

by the Encyclopedia of DNA Elements (ENCODE) Consortium between 2003 and 2012

(ENCODE Project Consortium 2012). The ENCODE Consortium has developed reagents

and tools to identify all functional elements in the human genome sequence. The Layered

H3K27Ac track indicates regions where there are modified histones that may indicate active

enhancers (Box 4.3).

The UCSC Genome Browser

Box 4.3 Histone Marks

Histone proteins package DNA into chromosomes. Post-translational modifications of

these histones can affect gene expression, as well as DNA replication and repair, by

changing chromatin structure or recruiting histone modifiers (Lawrence et al. 2016).

The post-translational modifications include methylation, phosphorylation, acetylation,

ubiquitylation, and sumoylation. Histone H3 is primarily acetylated on lysine residues,

methylated at arginine or lysine, or phosphorylated on serine or threonine. Histone H4

is primarily acetylated on lysine, methylated at arginine or lysine, or phosphorylated on

serine.

Histone modification (or “marking”) is identified by the name of the histone, the residue

on which it is marked, and the type of mark. Thus, H3K27Ac is histone H3 that is acetylated

on lysine 27, while H3K79me2 is histone H3 that is dimethylated on lysine 79. Different

histone marks are associated with different types of chromatin structure. Some are more

likely found near enhancers and others near promoters and, while some cause an increase

of expression from nearby genes, others cause less. For example, H3K4me3 is associ-

ated with active promoters, and H3K27me3 is associated with developmentally controlled

repressive chromatin states.

The DNase Clusters track depicts regions where chromatin is hypersensitive to cutting

by the DNaseI enzyme. In these hypersensitive regions, the nucleosome structure

is less compacted, meaning that the DNA is available to bind transcription factors.

Thus, regulatory regions, especially promoters, tend to be DNase sensitive. The track

settings for the ENCODE Regulation super-track allows other ENCODE tracks to be

added to the browser window, including additional histone modification and DNa-

seI hypersensitivity data. Changing the display of the H3K4Me3 peaks from hide to

full highlights the peaks in the H3K4Me3 track near the 5′ ends of the HIF1A and

SNAPC1 transcripts that overlap with DNase hypersensitive sites (Figure 4.7, blue

highlights). These peaks may represent promoter elements that regulate the start of

transcription.

The UCSC Genome Browser displays data from NCBI’s Single Nucleotide Polymorphism

Database (dbSNP) in four SNP tracks. Common SNPs contains SNPs and small insertions and

deletions (indels) from NCBI’s dbSNP that have a minor allele frequency of at least 1% and

are mapped to a single location in the genome. Researchers looking for disease-causing SNPs

can use this track to filter their data, hypothesizing that their variant of interest will be rare

and therefore not displayed in this track. Flagged SNPs are those that are deemed by NCBI to

be clinically associated, while Mult. SNPs have been mapped to more than one region in the

genome. NCBI filters out most multiple-mapping SNPs as they may not be true SNPs, so there

are not many variants in this track. All SNPs includes all SNPs from the three subcategories.

dbSNP is in a continuous state of growth, and new data are incorporated a few times each year

as a new release, or new build, of dbSNP. These four SNP tracks are available for a few of the

most recent builds of dbSNP, indicated by the number in the track name. Thus, for example,

Common SNPs (150) are SNPs found in ≥1% of samples from dbSNP build 150.

By default, the Common SNPs (150) track is displayed in dense mode, with all variants in the

region compressed onto a single line. Variants in the Common SNPs track are color coded by

function. Open the Track Settings for this track in order to modify the display (Figure 4.8). Set

the Display mode to pack in order to show each variant separately. At the same time, modify the

Coloring Options so that SNPs in UTRs of transcripts are set to blue and SNPs in coding regions

of transcripts are set to green if they are synonymous (no change to the protein sequence) or

red if they are non-synonymous (altering the protein sequence), with all remaining classes of

SNPs set to display in black. Note the changes in the resulting browser window, with the green

synonymous and blue untranslated SNPs clearly visible (Figure 4.9).

Figure 4.7 The genomic context of the human HIF1A gene, after changing the display of the H3K4Me3 peaks from hide to full. The H3K4Me3

track is part of the ENCODE Regulation super-track. Below the graphic display window in Figure 4.5, open up the ENCODE Regulation

Super-track, in the Regulation menu. Change the track display from hide to full to reproduce the page shown here. Note that the H3K4Me3

peaks, which can indicate promoter regions (Box 4.3), overlap with the transcription starts of the SNAPC1 and HIF1A genes (light blue

highlight). These regions also overlap with the DNase HS track, indicating that the chromatin should be available to bind transcription

factors in this region. The highlights were added within the Genome Browser using the Drag-and-select tool. This tool is accessed by

clicking anywhere in the Scale track at the top of the Genome Browser display and dragging the selection window across a region of

interest. The Drag-and-select tool provides options to Highlight the selected region or Zoom directly to it.

Figure 4.8 Configuring the track settings for the Common SNPs(150) track. Set the Coloring Options so that all SNPs are black, except for

untranslated SNPs (blue), coding-synonymous SNPs (green), and coding-non-synonymous SNPs (red). In addition, change the Display mode

of the track from dense to pack so that the individual SNPs can be seen. By default, the function of each variant is defined by its position

within transcripts in the GENCODE track. However, the track used for annotation can be changed in the settings called Use Gene Tracks for

Functional Annotation.

The UCSC Genome Browser

Figure 4.9 The genomic context of the human HIF1A gene, after changing the colors and display mode of the Common SNPs(150) track as

shown in Figure 4.8. The SNPs in the 5′ and 3′ untranslated regions of the HIF1A GENCODE transcripts are now colored blue, while the

coding-synonymous SNP is colored green.

Two types of Expression tracks display data from the NIH Genotype-Tissue Expression

(GTEx) project (GTEx Consortium 2015). The GTEx Gene track displays gene expression

levels in 51 tissues and two cell lines, based on RNA-seq data from 8555 samples. The GTEx

Transcript track provides additional analysis of the same data and displays median transcript

expression levels. By default, the GTEx Gene track is shown in pack mode, while the GTEx

Transcript track is hidden. Figure 4.10 shows the Gene track in pack display mode, in the

region of the phenylalanine hydroxylase (PAH) gene. The height of each bar in the bar graph

represents the median expression level of the gene across all samples for a tissue, and the

bar color indicates the tissue. The PAH gene is highly expressed in kidney and liver (the two

brown bars). The expression is more clearly visible in the details page for the GTEx track

(Figure 4.10, inset, purple box). The GTEx Transcript track is similar, but depicts expression

for individual transcripts rather than an average for the gene.

An alternate entry point to the UCSC Genome Browser is via a BLAT search (see Chapter 3),

where a user can input a nucleotide or protein sequence to find an aligned region in a

selected genome. BLAT excels at quickly identify a matching sequence in the same or highly

similar organism. We will attempt to use BLAT to find a lizard homolog of the human gene

Figure 4.10 The GTEx Gene track, which depicts median gene expression levels in 51 tissues and two cell lines, based on RNA-seq data

from the GTEx project from 8555 tissue samples. The main browser window depicts the GTEx Gene track for the human PAH gene, showing

high expression in the two tissues colored brown (liver and kidney) but low or no expression in others. Clicking on the GTEx track opens it

in a larger window, shown in the inset.

disintegrin and metalloproteinase domain-containing protein 18 (ADAM18). The ADAM18

protein sequence is copied in FASTA format from the NCBI view of accession number

NP_001307242.1 and pasted into the BLAT Search box that can be accessed from the Tools

pull-down menu; the method for retrieving this sequence in the correct format is described

in Chapter 2. Select the lizard genome and assembly AnoCar2.0/anoCar2. BLAT will auto-

matically determine that the query sequence is a protein and will compare it with the lizard

genome translated in all six reading frames. A single result is returned (Figure 4.11a). The

alignment between the ADAM18 protein sequence and lizard chromosome Un_GL343418

runs from amino acid 368 to amino acid 383, with 81.3% identity. The browser link depicts

the genomic context of this 48 nt hit (Figure 4.11b). Although the ADAM18 protein sequence

aligns to a region in which other human ADAM genes have also been aligned, the other

human genes are represented by a thin line, indicating a gap in their alignment. The details

link shown in Figure 4.11a produces the alignment between the ADAM18 protein and lizard

chromosome Un_GL343418 (Figure 4.11c). The top section of the results shows the protein

query sequence, with the blue letters indicating the short region of alignment with the

genome. The bottom section shows the pairwise alignment between the protein and genomic

sequence translated in six frames. Vertical black lines indicate identical sequences. Taken

together, the BLAT results show that only 16 amino acids of the 715 amino acid ADAM18

protein align to the lizard genome (Figure 4.11c). This alignment is short and likely does not

represent a homologous region between the ADAM18 protein and the lizard genome. Thus,

the BLAT algorithm, although fast, is not always sensitive enough to detect cross-species

orthologs. The BLAST algorithm, described in the Ensembl Genome Browser section, is more

sensitive, and is a better choice for identifying such homologs.

The UCSC Genome Browser

(a)

(b)

Figure 4.11 BLAT search at the UCSC Genome Browser. (a) This page shows the results of running a BLAT search against the lizard

genome, using as a query the human protein sequence of the gene ADAM18, accession NP_001307242.1. The ADAM18 protein sequence

is available from NCBI at www.ncbi.nlm.nih.gov/protein/NP_001307242.1?report=fasta. At the UCSC Genome Browser, the web inter-

face to the BLAT search is in the Tools menu at the top of each page. The BLAT search was run against the lizard genome assembly from

May 2010, also called anoCar2. The columns on the results page are as follows: ACTIONS, links to the browser (Figure 4.11b) and details

(Figure 4.11c); QUERY, the name of the query sequence; SCORE, the BLAT score, determined by the number of matches vs. mismatches

in the final alignment of the query to the genome; START, the start coordinate of the alignment, on the query sequence; END, the end

coordinate of the alignment, on the query sequence; QSIZE, the length of the query; IDENTITY, the percent identity between the query

and the genomic sequences; CHRO, the chromosome to which the query sequence aligns; STRAND, the chromosome strand to which

the query sequence aligns; START; the start coordinate of the alignment, on the genomic sequence; END, the end coordinate of the

alignment, on the genomic sequence; and SPAN, the length of the alignment, on the genomic sequence. Note that, in this example,

there is a single alignment; searches with other sequences may result in many alignments, each shown on a separate line. It is possible

to search with up to 25 sequences at a time, but each sequence must be in FASTA format. (b) This page shows the browser link from the

BLAT summary page. The alignment between the query and genome is shown as a new track called Your Sequence from BLAT Search.

(c) The details link from the BLAT summary page, showing the alignment between the query (human ADAM18 protein) and the lizard

genome, translated in six frames. The protein query sequence is shown at the top, with the blue letters indicating the amino acids

that align to the genome. The bottom section shows the pairwise alignment between the protein and genomic sequence translated in

six frames. Black lines indicate identical sequences; red and green letters indicate where the genomic sequence encodes a different

amino acid. Although the ADAM18 protein sequence has a length of 715 amino acids, only 16 amino acids align as a single block to

the lizard genome.

(c)

Figure 4.11 (Continued)

UCSC Table Browser

The Table Browser tool provides users a text-based interface with which to query, inter-

sect, filter, and download the data that are displayed graphically in the Genome Browser.

These data can then be saved in a spreadsheet for further analysis, or used as input into a

different program. Using a web-based interface, users select a genome assembly, track, and

position, then choose how to manipulate that track data and what fields to return. This

example will demonstrate how to retrieve a list of all NCBI mRNA reference sequences that

overlap with an SNP from the Genome-Wide Association Study (GWAS) Catalog track, which

identifies genetic loci associated with common diseases or traits. The GWAS Catalog is a

manually curated collection of published genome-wide association studies that assayed at

least 100 000 SNPs, in which all SNP-trait associations have p values of <1 × 10−5 (Buniello

et al. 2019).

The Table Browser landing page is accessible from either the UCSC Genome Browser home

page or the Tools pull-down menu. First, reset all user cart settings by clicking on the click here

link at the bottom of the Table Browser settings section.

Then, select the NCBI RefSeq track on the GRCh38 genome assembly (Figure 4.12a). Create

a filter to limit the search to curated mRNA reference sequences in the NM_ accession series

(Box 1.2; Figure 4.12b). Next, intersect the RefSeq track with variants from the GWAS Catalog

(Figure 4.12c). Finally, on the Table Browser form, change the output format to hyperlinks to

Genome Browser, then click get output. The output is a list of 3000+ RefSeq mRNAs that overlap

with a variant from the GWAS Catalog (Figure 4.12d). The Genome Browser view of one of the

transcripts, from the gene arginine–glutamic acid dipeptide (RE) repeats (RERE), and the six

SNPs from the GWAS Catalog that it overlaps, can be found by clicking on the first link in the

results list and is shown in Figure 4.12e.

(c)

Figure 4.11 (Continued)

UCSC Table Browser

The Table Browser tool provides users a text-based interface with which to query, inter-

sect, filter, and download the data that are displayed graphically in the Genome Browser.

These data can then be saved in a spreadsheet for further analysis, or used as input into a

different program. Using a web-based interface, users select a genome assembly, track, and

position, then choose how to manipulate that track data and what fields to return. This

example will demonstrate how to retrieve a list of all NCBI mRNA reference sequences that

overlap with an SNP from the Genome-Wide Association Study (GWAS) Catalog track, which

identifies genetic loci associated with common diseases or traits. The GWAS Catalog is a

manually curated collection of published genome-wide association studies that assayed at

least 100 000 SNPs, in which all SNP-trait associations have p values of <1 × 10−5 (Buniello

et al. 2019).

The Table Browser landing page is accessible from either the UCSC Genome Browser home

page or the Tools pull-down menu. First, reset all user cart settings by clicking on the click here

link at the bottom of the Table Browser settings section.

Then, select the NCBI RefSeq track on the GRCh38 genome assembly (Figure 4.12a). Create

a filter to limit the search to curated mRNA reference sequences in the NM_ accession series

(Box 1.2; Figure 4.12b). Next, intersect the RefSeq track with variants from the GWAS Catalog

(Figure 4.12c). Finally, on the Table Browser form, change the output format to hyperlinks to

Genome Browser, then click get output. The output is a list of 3000+ RefSeq mRNAs that overlap

with a variant from the GWAS Catalog (Figure 4.12d). The Genome Browser view of one of the

transcripts, from the gene arginine–glutamic acid dipeptide (RE) repeats (RERE), and the six

SNPs from the GWAS Catalog that it overlaps, can be found by clicking on the first link in the

results list and is shown in Figure 4.12e.

UCSC Table Browser

(a)

(b)

(c)

Figure 4.12 Configuring the UCSC Table Browser. The link to the Table Browser is in the Tools menu at

the top of each page. (a) On the Table Browser home page, first reset all previous selections by clicking

on the reset button at the bottom of the window. Next, select the track called NCBI RefSeq in the group

Genes and Gene Predictions on the human GRCh38 genome assembly. The region should be set to genome

and the output format to hyperlinks to Genome Browser. (b) Create a filter to limit the search to curated

mRNA reference sequences in the NM_ accession series (see Box 1.2). Click on the filter button shown in

Figure 4.12a and enter the term NM_* in the name field. The asterisk is a wildcard character that matches

any text. Thus, this setting will limit the results to those curated RefSeqs whose name contains the term

NM_. (c) Create an intersection between the RefSeq track and the variants from the GWAS Catalog. Click

on the intersection button shown in Figure 4.12a and select the appropriate track. The group is Phenotype

and Literature and the track is called GWAS Catalog. Leave other selections set to the default. (d) Click

on the get output button shown in Figure 4.12a. The output is a list of more than 3000 RefSeq mRNAs

that overlap with a variant from the GWAS Catalog. Each RefSeq is hyperlinked to the Genome Browser.

(e) The first link is to NM_001042682.1, a transcript of the gene arginine–glutamic acid dipeptide (RE)

repeats (RERE). The genomic context of RERE shows the eight SNPs from the GWAS Catalog that it

overlaps.

(d)

(e)

Figure 4.12 (Continued)

UCSC also provides a related tool called the Data Integrator. The Data Integrator has a more

sophisticated intersection function than does the Table Browser, as it can intersect data from up

to five separate tracks, and output fields from both the selected tracks and related tables. Thus,

for example, output from the Data Integrator could include the gene symbol in addition to the

accession number for each transcript on the RefSeq track, along with the dbSNP identifier for

the variants in the GWAS Catalog. However, the Data Integrator does not allow for filtering,

so it is not possible to restrict the output to only RefSeq mRNA genes.

The Ensembl Genome Browser (Cunningham et al. 2019) got its start in 1999 (Hubbard et al.

1. with the display of the human genome assembly. Like the UCSC Genome Browser, it has

grown significantly over the years. The main Ensembl site focuses on vertebrates and includes

assemblies from almost 90 species. Ensembl has also created specialized sibling databases for

other groups of organisms, including EnsemblPlants (nearly 50 species), EnsemblMetazoa

(nearly 70 species), EnsemblProtist (more than 100 species), and EnsemblFungi (more than

800 species), and the very large EnsemblBacteria, with around 44 000 species. The amount of

available genome data and annotations varies by organism, but the general browser navigation

principles are the same for all. An additional resource is Pre!Ensembl, which displays genomes

that are in the process of being annotated. Genomes on this site have an assembly and BLAST

interface but, for the most part, no gene predictions.

Like the UCSC Genome Browser, the Ensembl Browser makes available multiple versions

of genome assemblies. Integrated into the assemblies may be gene, genome variation, gene

regulation, and comparative genomics annotation. Annotations are organized as sets of tracks.

Ensembl incorporates data from a variety of public sources, including NCBI, UCSC, model

organism databases, and more, and updates data and software in a formal release process,

which can be tracked by release number. Importantly, previous Ensembl releases are archived

on the web site and are available for view. Thus, even after a genome assembly or annotation

set has been updated, it is possible to view the older data using all the regular functions of

the Ensembl web site. This archive process sets Ensembl apart from UCSC, where the genome

assembly remains stable, but the annotations may change on a weekly basis. Each Ensembl

page has a link at the bottom called View in archive site. The archive site provides links to older

versions of that page, including previous annotation sets on the same genome assembly, as

well as prior genome assemblies.

The Ensembl Browser provides many of the same types of resources and tools as does the

UCSC Genome Browser. Sequences can be aligned to the assembled genomes using either

ENSEMBL Genome Browser

BLAT or BLAST, and data can be returned in various tabular formats using BioMart (Kinsella

et al. 2011). Data and software can be retrieved from the Downloads menu, available from

most browser pages. In the Tools menu, Ensembl provides a number of additional tools to

manipulate data, including the Variant Effect Predictor (VEP) (McLaren et al. 2016), which

predicts functional consequences of known and unknown variants, File Chameleon, which

reformats files available on the Ensembl FTP site, and Assembly Converter, which is like

UCSC’s liftOver and is used to convert coordinates between genome assemblies. The Help &

Documentation menu provides substantial written and video-based information about how

to navigate and interpret the Ensembl site, far beyond the level of detail presented in this

chapter.

Ensembl also provides ways for users to upload their data into the browser. Properly format-

ted tracks can be added to the display by selecting the Custom tracks option from the left side of

any species-specific page. The data can be uploaded to Ensembl from a file on the user’s com-

puter or, if it is saved on a web server, the browser can read it from a URL. Users who create an

account at Ensembl can save track data to the Ensembl database server and view them later

from any computer. To share custom tracks or even a customized view of the Genome Browser

Figure 4.13 The home page of the Ensembl Genome Browser, showing a query for the human gene PAH. The browser suggests results

based on the search term submitted. By default, the search box interfaces with the most recent version of the genome assembly, GRCh38,

at the time of this writing. A link to the previous human genome assembly, GRCh37, is provided at the bottom of the page. Older assemblies

from other organisms are available in the Ensembl archives.

Figure 4.14 The Gene tab for the human PAH gene. This landing page provides links to many gene-specific resources.

with colleagues, click on the Share this Page link on the left sidebar. Ensembl also supports

Track Hubs, both public ones that are registered on the EMBL-EBI Track Hub Registry as well

as private ones.

Like the UCSC Genome Browser home page, the home page of Ensembl is a stepping-off

point for many Ensembl resources. Links to commonly used tools, such as BLAST and BLAT,

are provided on the top and middle sections of the page, and recent data updates are high-

lighted in the right column. The home page for each genome can be accessed by selecting the

organism name in the pull-down menu in the Browse a Genome section in the center of the

page. A search box at the top of the page provides access to Ensembl. To search for the human

PAH gene, select Human from the pull-down menu and type the term PAH in the search box.

Ensembl will provide several suggested hits, including a direct link to the human PAH gene

(Figure 4.13).

Ensembl data displays are organized in tabs. The Gene tab (Figure 4.14) has links to a

number of gene-specific views and resources. For example, from the index on the left side of

the Gene tab view, the Comparative Genomics →Orthologues link lists the computationally

predicted orthologs of the selected gene that Ensembl has identified among the available

genome assemblies (Herrero et al. 2016; Figure 4.15). The Location tab provides a graphical

view of the genomic context of the gene, similar to the view available at UCSC. The link to the

Location tab is at the top of the Gene tab view in Figure 4.14. The Location tab view is shown

in Figure 4.16 and depicts, at three different zoom levels, the genomic context of the PAH gene

on the GRCh38 genome assembly. The PAH gene has been mapped to chromosome 12, and

the top panel shows a cartoon of that chromosome, with the region surrounding the PAH gene

outlined in a red box. This red box is expanded in the middle panel of the figure, which shows

∼1 Mb of chromosome 12 around the PAH gene. The genes are shown as colored blocks, with

their identifiers noted below them. The region outlined in red in this middle section is further

ENSEMBL Genome Browser

Figure 4.15 Computationally predicted orthologs of the human PAH gene, from the Comparative Genomics →Orthologues link in Figure 4.14.

Ensembl provides a detailed analysis of the orthologs calculated for each gene. Orthologs are grouped by species, such as primates, rodents,

and sauropsids. Links to individual orthologs are shown at the bottom of the page.

expanded in the large bottom panel, which zooms in on the PAH gene itself. Individual tracks

are visible in this view. Note the track called Contigs, a blue bar that represents the underlying

assembled contigs. By convention, any transcripts shown above this track are transcribed

from left to right. Transcripts drawn below the Contigs track, such as the PAH transcripts, are

transcribed on the opposite strand, from right to left.

The default human gene set used by Ensembl is the GENCODE Comprehensive set

(Box 4.2). Ensembl displays 18 PAH isoforms, each with a slightly different pattern of exons

(Figure 4.16). Coding exons are depicted as solid blocks, non-coding exons as outlined blocks,

and introns are the lines that connect them. The transcripts are color coded to indicate their

status: gold transcripts are protein coding and have been annotated by both the Ensembl

and HAVANA team at the WTSI, red transcripts are protein coding and have been annotated

by either Ensembl or HAVANA, and blue transcripts are processed transcripts that are

non-protein coding. Clicking on a transcript pops up a box with additional information about

that feature, including its accession number, and, for a transcript, the transcript type and gene

prediction source (Box 4.4; Figure 4.16).

Figure 4.16 The Location tab for the human PAH gene. The Location tab is divided into three sections. The top section shows a cartoon of

human chromosome 12, with the region surrounding the PAH gene outlined in a red box. Other red and green lines on the cartoon indicate

assembly exceptions, or regions of alternative sequence that differ from the primary assembly because of allelic sequence or incorrect

sequence, as determined by the Genome Reference Consortium. The Region in detail shows a zoomed-in view of the region outlined by the

red box in the top section of the page. Genes are indicated by rectangles, colored as described in the gene legend below the graphic. The

gene identifiers, along with the direction of transcription, are shown below the rectangles. The bottom section shows a zoomed-in view

of the region surrounded by the red box in the Region in detail. The blue bar represents the genomic contig in this region. In the Genes

track, genes above the bar are transcribed from left to right; those below the contig are transcribed from right to left. A few of the PAH

transcripts, which are transcribed from right to left, are visible in this view. Gold transcripts are merged HAVANA/Ensembl transcripts; red

are Ensembl protein-coding transcripts; blue transcripts are non-protein-coding processed transcripts. The pop-up display, activated when

clicking on a particular transcript, shows the details for the first transcript in the Genes track, PAH-215.

Box 4.4 Ensembl Stable IDs

Ensembl assigns accession numbers to many data types in its database. Each identifier

begins with the organism prefix; for human, the prefix is ENS; for mouse, it is ENSMUS; and

for anole lizard, it is ENSACA. Next comes an abbreviation for the feature type: G for gene,

T for transcript, P for protein, R for regulatory, and so forth. This is followed by a series of

digits, and an optional version. The version number increments when there is a change

ENSEMBL Genome Browser

in the underlying data. The gene version changes when the underlying transcripts are

updated, and the transcript and protein versions increment when the sequence changes.

For example, the human PAH gene has the following identifiers:

ENSG00000171759.9: the identifier of the human PAH gene

ENST00000553106.5: the identifier of one transcript of the human PAH gene,

transcript PAH-215

ENSP00000448059.1: the identifier of the protein translation of

transcript PAH-215, ENST00000553106.5

ENSR00000056420: the identifier of a promoter of several PAH transcripts

Navigation controls between the second and third panels of the Location tab allow the

display to be zoomed or moved to the left or right. The blue bar at the top of the Region in

detail allows users to toggle between Drag and Select. When the Drag option is highlighted,

click on the graphical view window and drag it to the left or right to change the location.

When the Select option is highlighted, click on a region of interest in the graphical view,

then, holding the mouse button down, scroll to the left or right to highlight the region

(Figure 4.17a). The highlight can be left on for visualization purposes or, alternatively,

select Jump to region to zoom in to the selected region. Figure 4.17b shows the results of

zooming in to the last exon of transcript PAH-203; since the gene is transcribed from right

to left, the last exon is on the left. Note the track called All phenotype-associated short

variants (SNPs and indels) that contains those variants that have been associated with a

phenotype or disease. SNPs are color coded by function, with dark green indicating coding

sequence variants. Select the dark green SNP, highlighted with a red box near the left end

of the window, and follow the link for additional information. The resulting Variant tab

provides links to SNP-related resources. For example, the Phenotype Data for this SNP

(rs76296470; Figure 4.18a) shows that this variant is pathogenic and is associated with

the disease phenylketonuria. The most severe consequence for this SNP is a stop gained.

Further details about the consequences are available under the Genes and regulation link

(Figure 4.18b) on the left sidebar. This variant is found in 10 transcripts of the PAH gene.

In five of those transcripts, it alters one nucleotide in a codon, changing an arginine to a

stop codon, thus truncating the PAH protein. In the other five transcripts, either the variant

is downstream of the gene or the transcript is non-coding.

Ensembl makes available many annotation tracks through the Configure this page link on the

left sidebar. There are over 500 tracks available for display on GRCh38, with the majority falling

in the categories of Variation, Regulation, and Comparative Genomics. The Ensembl Regula-

tory Build includes regions that are likely to be involved in gene regulation, including pro-

moters, promoter flanking regions, enhancers, CCCTC-binding factor (CTCF) binding sites,

transcription factor binding sites (TFBS), and open chromatin regions (Zerbino et al. 2016).

A summary Regulatory Build track is turned on by default in the Location tab, and the display

of individual features can be adjusted in the Configure this page menu. In the UCSC Genome

Browser, the GTEx track shows that the PAH gene is highly expressed in liver and kidney

(Figure 4.10); the epigenetic factors that may be controlling this activity can be viewed in

Ensembl Regulatory Build. To view these factors, navigate to Regulation →Histones & poly-

merases on the Configure this page menu, mouse over the HepG2 human liver carcinoma line,

and select All features for HepG2 (Figure 4.19a). In addition, navigate to Regulation →Open

chromatin & TFBS and confirm that the DNase1 track is in its default state for HepG2; the dark

blue indicates that the track is shown. Close the Configure this page menu by clicking on the

check mark in the upper right corner of the pop-up window. Notice that the Regulatory Build

track has now expanded to include the selected gene regulatory marks in the HepG2 cell line.

Zoom in on the first exon of transcript PAH-215 to see the promoter region of this gene, being

mindful of the orientation of the gene (Figure 4.19b). The solid red rectangle in the Regulatory

(a)

(b)

Figure 4.17 Zooming in on the bottom section of the Location tab from Figure 4.16. (a) Highlight a region of interest, the final exon of PAH

transcript PAH-203, by clicking the mouse and then scrolling to the left or right. In order to highlight the region, the Drag/Select toggle in

the blue bar at the top of the section must first be set to Select. (b) To zoom in to the highlighted region, select Jump to region. It may take

a few iterations to create the view in this figure. At the bottom of the window is a track labeled All phenotype-associated – short variants

(SNPs and indels). In this track, the SNP rs76296470 has been manually highlighted in red.

ENSEMBL Genome Browser

(a)

(b)

Figure 4.18 The Ensembl Variant tab. (a) To get more details about SNP rs76296470, click on the dark

green SNP that is highlighted in red in the All phenotype-associated – short variants (SNPs and indels) track

in Figure 4.17b. On the pop-up menu, click on more about rs76296470. The Phenotype Data section of the

Variant tab is available from the link in the blue sidebar. This variant is pathogenic for phenylketonuria.

(b) The Genes and regulation section of the Variant tab shows the location and function of the variant

in the transcripts that overlap it. Depending on the transcript, the SNP can change a codon to a stop

codon (stop gained), map downstream of a gene, or map to a non-coding transcript. The transcripts in

this view represent alternatively spliced forms of the gene PAH.

(b)

(a)

Figure 4.19 The Ensembl Regulatory Build track. (a) Go to Configure this page on the left side of the

Location tab and select Regulation →Histones & polymerases. Scroll to the right to find the HepG2 (human

liver cancer) cell type. Mouse over the text HepG2 and turn on all features. Clicking on the box under the

cell type will change the track style; leave that set to the default of Peaks. Click on the black check mark

on the upper right corner of the configuration window to save the settings and exit the setup. To turn on

the DNase1 (DNaseI hypersensitive sites track), select Regulation →Open chromatin & TFBS and ensure

that the DNase1 box in the HepG2 column is colored dark blue so that it is in the Shown configuration.

Click on the black check mark on the upper right corner of the configuration window to save the settings

again. (b) Back on the Region in detail section of the Location tab, zoom in to the first exon of transcript

PAH-215. Note that the first exon is on the right end of the transcript, as the gene is transcribed from

right to left. The resulting display shows the details of the Regulatory Build track. The figure legend (not

shown) explains that the solid red box is a promoter. The DNaseI hypersensitive site and histone marks

are also shown as colored boxes.

ENSEMBL Genome Browser

Build track shows the location of the PAH promoter. The presence of a DNaseI hypersensitive

site along with the activating histone marks of H3K27Ac, H3K4me1, H3K4me2, H3K4me3,

H3K79me2, and H3K9Ac may help to explain why this gene is highly expressed in liver cells

(Box 4.3). Detailed information about features in the Regulatory Build track, such as the source

of the data, is available under the Regulation tab. Click on the feature and select its identifier

(the letters ENSR, followed by numbers) to open this tab.

The left sidebar of the Location tab links to a number of additional useful resources. One

of those, Comparative Genomics →Synteny displays blocks of synteny between the human

chromosome featured in the Location tab and chromosomes from about 30 different organ-

isms. In these syntenic blocks, the order of genes and other sequence features is conserved

(a)

Figure 4.20 The Synteny view at Ensembl. (a) An overview of the syntenic blocks shared between human chromosome 12 and the mouse

genome. The human chromosome is drawn in the middle of the display as a thick white box. The syntenic mouse chromosomes are repre-

sented by thinner white boxes along the side. The colored rectangles highlight regions of synteny between the human and mouse. A red

outline illustrates the position of the PAH gene on the blue region of human chromosome 12 and on the blue region of mouse chromosome

1. (b) The Location tab for the PAH gene showing both the human and mouse syntenic regions. This is similar to the three-panel location

tab shown in Figure 4.16, except that both the human and mouse genomes are depicted. The top panel (not shown) displays the full length

human chromosome 12 and mouse chromosome 10. The second panel shows an overview of the genes in the region. The third panel

focuses in on the PAH gene. Note that the regions in human and mouse appear to be presented in opposite orientations; in human, the

PAH and IGF1 genes are both transcribed from right to left, while in mouse they are transcribed from left to right.

(b)

Figure 4.20 (Continued)

across the genomes being compared. Figure 4.20a shows the synteny between human chro-

mosome 12 and the mouse genome. A cartoon of the human chromosome 12 is shown in the

center of the display as a thick white rectangle, and mouse chromosomes are drawn on the sides

as thinner white rectangles. Colored rectangles indicate regions of synteny between the human

and mouse. For example, the light blue region on human chromosome 12 is syntenic to the

light blue region on mouse chromosome 10. The region surrounding the PAH gene is outlined

in red on both human chromosome 12 and mouse chromosome 10. Below the cartoon is a

list of the human genes and corresponding mouse orthologs in the region of PAH. Selecting

Region Comparison next to one of the genes opens a new Location tab that depicts the syntenic

human and mouse chromosomes stacked on top of each other so that surrounding features

can be compared directly (Figure 4.20b). The upper panel shows the genomic context of the

ENSEMBL Genome Browser

Figure 4.21 Ensembl BLAST output, showing an alignment between the human ADAM18 protein and

the lizard genome translated in all six reading frames. On the BLAST/BLAT page at Ensembl, paste the

FASTA-formatted sequence of human ADAM18, accession NP_001307242.1, into the Sequence data box.

This sequence can be found at www.ncbi.nlm.nih.gov/protein/NP_001307242.1/?report=fasta. Select

Genomic sequence from the anole lizard as the DNA database. On the results page, select the Alignment

link next to the highest scoring hit in order to view the sequence alignment. The human protein sequence

is on top, and the translated lizard genomic sequence is below. Lines indicate identical amino acids.

PAH gene on human chromosome 12 (top) and mouse chromosome 10 (bottom). Note that the

genes are transcribed in opposite directions, so the order of the surrounding genes is flipped.

The bottom panel is zoomed in on the PAH gene itself. The Regulatory Build track on the mouse

assembly shows several regulatory features in this region. Further inspection of the regulatory

feature that overlaps with the 5′ end of the mouse Pah gene reveals activating histone marks

in liver and kidney cells, but not in other cell types (not shown), implying that the mouse Pah

gene has similar expression patterns to its human ortholog. To reset the settings back to the

default view, go to Configure this page in the left sidebar and select Reset configuration.

The Ensembl sequence data can also be queried via a BLAT or BLAST search by following

the link at the top of any page. Earlier in this chapter, Figure 4.11 outlined how to use BLAT

to look for a lizard homolog of the human ADAM18 gene. Ensembl data can be searched by

the more sensitive BLAST algorithm, including the TBLASTN program that is used to com-

pare a protein query with a nucleotide database translated in all six reading frames. Copy

and paste the FASTA-formatted protein sequence of NCBI RefSeq NP_001307242.1 into the

Sequence data box on the BLAST page and carry out a TBLASTN search against the anole

lizard genomic sequence. The sequence alignment of the top hit is shown in Figure 4.21. The

human protein query is on the top line, and the translated lizard genomic sequence on the

second. The sequences share only 32% sequence identity, but the alignment spans 650 amino

acids, and some key sequence features are conserved; note the alignment of almost every cys-

teine residue. Thus, this lizard genomic sequence is indeed a homolog of human ADAM18.

The BLAST algorithm, although about two orders of magnitude slower than BLAT for the

same query, is able to find a lizard ortholog of the human protein.

PAH gene on human chromosome 12 (top) and mouse chromosome 10 (bottom). Note that the

genes are transcribed in opposite directions, so the order of the surrounding genes is flipped.

The bottom panel is zoomed in on the PAH gene itself. The Regulatory Build track on the mouse

assembly shows several regulatory features in this region. Further inspection of the regulatory

feature that overlaps with the 5′ end of the mouse Pah gene reveals activating histone marks

in liver and kidney cells, but not in other cell types (not shown), implying that the mouse Pah

gene has similar expression patterns to its human ortholog. To reset the settings back to the

default view, go to Configure this page in the left sidebar and select Reset configuration.

The Ensembl sequence data can also be queried via a BLAT or BLAST search by following

the link at the top of any page. Earlier in this chapter, Figure 4.11 outlined how to use BLAT

to look for a lizard homolog of the human ADAM18 gene. Ensembl data can be searched by

the more sensitive BLAST algorithm, including the TBLASTN program that is used to com-

pare a protein query with a nucleotide database translated in all six reading frames. Copy

and paste the FASTA-formatted protein sequence of NCBI RefSeq NP_001307242.1 into the

Sequence data box on the BLAST page and carry out a TBLASTN search against the anole

lizard genomic sequence. The sequence alignment of the top hit is shown in Figure 4.21. The

human protein query is on the top line, and the translated lizard genomic sequence on the

second. The sequences share only 32% sequence identity, but the alignment spans 650 amino

acids, and some key sequence features are conserved; note the alignment of almost every cys-

teine residue. Thus, this lizard genomic sequence is indeed a homolog of human ADAM18.

The BLAST algorithm, although about two orders of magnitude slower than BLAT for the

same query, is able to find a lizard ortholog of the human protein.

Ensembl Biomart

The BioMart tool at Ensembl is akin to the Table Browser at UCSC, in that it provides a

web-based interface through which to access the data underlying the Ensembl Genome

Browser. Results are returned as text or HTML-formatted tables. Ensembl hosts several mart

databases that are described in the online documentation. The Ensembl Genes database

contains the Ensembl gene set and integrates Ensembl genes, transcripts, and proteins with

a number of resources, including external references, protein domains, sequences, variants,

and homology data. After choosing a Database (e.g. Genes) and Dataset (genome assembly,

e.g. Homo sapiens), the user specifies the Filters (basically, the input data) and the Attributes

(the output data). Users can choose from among seven types of filters, including Region and

Gene. A Region could be a chromosomal position, while a Gene could be an accession number,

gene name, or even microarray probeset. The list of possible Attributes is long, and includes

Ensembl data such as gene and transcript identifiers and positions, links to external data

sources including RefSeq, UCSC, Pfam (protein families), and Gene Ontology (GO) terms, as

well as mapping to orthologs in the Ensembl genome databases.

In this example, we will identify the mouse orthologs of the human mRNA reference

sequences that are associated with common diseases or traits. To do this, we will start with

the output of the UCSC Table Browser, the mRNA reference sequences that overlap with a

variant from the GWAS Catalog, pull out the corresponding Ensembl gene and transcript

identifiers, and then link to the mouse orthologs. The initial step is to retrieve the RefSeq

accession numbers that overlap with a variant from the GWAS Catalog by reproducing the

search shown in Figure 4.12d, this time changing the output format to sequence. Copy

and paste the output from the Table Browser into your favorite text editor to create a list that

contains only the accession numbers. Note that BioMart does not accept the accession.version

format used by NCBI, so an accession number like NM_001042682.1 would need to be

rewritten as NM_001042682.

At BioMart, the first step is to enter these accession numbers as Filters into the Human Genes

(GRCh38.p10) Dataset. RefSeq mRNA accession numbers are entered in the filter called Gene

Ensembl Biomart

(a)

(b)

(c)

Figure 4.22 Using BioMart to retrieve the mouse orthologs of the human RefSeqs from the GWAS Cat-

alog. (a) Enter the input RefSeq accession numbers into BioMart. First, create a list of RefSeq accession

numbers from the UCSC Table Browser output in Figure 4.12d. BioMart does not accept the acces-

sion.version format, so all of the text after the accession number itself will need to be removed. This step

can be implemented using a text editor that can perform a wildcard search and replace. For example,

to remove the period and all following text from each line, replace ..* with an empty string. Although

the resulting list of accession numbers will contain duplicates, as some RefSeqs have been mapped to

alternate loci, any redundancy will be removed from the final BioMart results. At BioMart, click on Filters

in the left sidebar, open the Gene menu, and click on Input external references ID list. In the pull-down

menu, select RefSeq mRNA IDs as the type of identifier. Paste in the list of accession numbers, which

should be of the form NM_001042682. Although BioMart instructions recommend limiting the number

of access numbers to 500, the interface will process the 3000+ RefSeq accession numbers from the

UCSC Table Browser output. (b) Set the BioMart Attributes (fields to be included in the output). Click on

the Attributes in the left sidebar, select Features at the top of the page, then open the Gene menu. Gene

stable ID and Transcript stable ID should be selected by default, and will return the Ensembl gene (ENSG)

and transcript (ENST) identifiers. Also select Gene name to return the gene symbols (e.g. ADAM18). (c) Set

additional Attributes. Close the Gene menu and open the External menu. Navigate to External References

and select RefSeq mRNA ID. This step is needed to return the input RefSeq accession numbers so that

they can be correlated later with the Ensembl identifiers. (d) BioMart output, including the identifiers

requested above. Click on the Results button at the top of the page to retrieve the output. Check the box

Unique results only to ensure that duplicated RefSeqs are returned only once. The order of the columns

in the results file depends on the order in which the items were added to the list of Attributes. The net

result is that each human RefSeq accession from the Table Browser is correlated with its Ensembl Gene

and Transcript ID, as well as a gene symbol. (e) BioMart output, with human Ensembl Gene ID and gene

symbol, as well as the orthologous mouse Ensembl Gene ID and gene symbol. Start a new query by

clicking the New box at the top of the BioMart window. Select the same Database, Dataset, and Filters

as before. Under Attributes, select the Homologues radio button. The human Ensembl Gene ID and gene

symbol are in the Gene →Ensembl menu, called Gene stable ID and Gene name. The mouse Ensembl Gene

ID and gene symbol are in the Orthologues →Mouse Orthologues menu, called Mouse gene stable ID

and Mouse gene name. This step outputs the orthologous mouse Ensembl Gene ID and symbol for each

human Ensembl Gene ID and symbol. The BioMart output from (d) and (e) can be merged to list the

mouse ortholog of each human RefSeq from the GWAS Catalog (Figure 4.12d).

(d)

(e)

Figure 4.22 (Continued)

→Input external references ID list (Figure 4.22a). The Attributes could be the Ensembl Gene

and Transcript identifiers, as well as the Gene name, in the Features →Gene →Ensembl section

(Figure 4.22b). To correlate the output with the RefSeq accession numbers entered as Filters,

it is necessary to also select the RefSeq accession as an attribute, in the Features →Gene →

External References section (Figure 4.22c). After the Filters and Attributes have been set, click

on the Results button in the upper left to return the BioMart output (Figure 4.22d). Data can be

returned as a text file or as a formatted page in the web browser, with hyperlinks to Ensembl

resources. Because of the differences in gene annotation strategies, the mapping of NCBI Ref-

Seq accession numbers to Ensembl gene and transcript identifiers is not one to one; some

RefSeq accessions map to more than one Ensembl gene and/or transcript, and some Ensembl

genes map to more than one RefSeq identifier.

Retrieving the mouse orthologs of the NCBI reference sequences must be done as a sepa-

rate step, as it is not possible to return an external identifier (i.e. the starting RefSeq accession

number) and an ortholog in the same BioMart query. Starting with the same Filter and human

RefSeq accession numbers as before, choose the Homologues section of the Attributes and select

the human Ensembl gene identifier and gene name under Gene →Ensembl, as well as the

mouse Ensembl gene identifier and gene name under Orthologues →Mouse Orthologues. The

results are shown in Figure 4.22e. Note that not all of the human gene identifiers have been

mapped to a corresponding mouse ortholog. The goal of this exercise was to identify the mouse

orthologs of the human RefSeq accession numbers from the GWAS Catalog. Using the human

Ensembl gene identifiers as a key, the human RefSeq accession numbers can be added to the

list of mouse orthologs. This can be carried out by using the VLOOKUP function in Microsoft

Excel, or by writing a script in your favorite programming language, and is left as an exercise

for the reader.

JBrowse

While the UCSC and Ensembl Genome Browsers provide user-friendly interfaces for viewing

genomic data from well-characterized organisms, there are fewer applications for displaying

genome assemblies and annotations for newly sequenced organisms or non-standard assem-

blies. The source code and executables for the UCSC Genome Browser are freely available for

academic, non-profit, and personal use, and can be set up to display custom data, not just

JBrowse

those provided by UCSC. Thus, one option is for researchers to host their own UCSC Genome

Browser and use it to share custom genomes with the bioinformatics community. An alternate

method for sharing novel genome assemblies is to set up an Assembly Hub. Researchers host

the specially formatted genomic sequence and data tracks on their own web site, and anyone

with the URL can view the assembly though the UCSC Genome Browser.

Another way to share novel genome assemblies is to use JBrowse (Buels et al. 2016), a

web-based genome browser that is part of the Generic Model Organism Database (GMOD)

project, a suite of tools for generating genomic databases. JBrowse can handle data in a

variety of formats, and is relatively easy to install on a Linux- or Mac OS X-based web server

(Skinner and Holmes 2010). JBrowse browsers support plant genomes (e.g. Phytozome),

animal genomes (e.g. the Rat Genome Database), and disease-related databases of human

data (e.g. the COSMIC Genome Browser).

An example of using JBrowse to view a customized genome assembly and associated anno-

tations is at the Mnemiopsis Genome Project (MGP) Portal at the National Human Genome

Research Institute (NHGRI) of the US National Institutes of Health (NIH). Mnemiopsis leidyi is

a type of ctenophore, or comb jelly, a phylum of gelatinous zooplankton found in all the world’s

seas. The members of this phylum are called comb jellies because of their highly ciliated comb

rows, providing their primary means of locomotion, and these early branching metazoans have

proven to be an important model organism for understanding the diversity and complexity

seen in the early evolution of animals. The Mnemiopsis data featured in this portal are the

first set of whole genome sequencing data on any ctenophore species to be published and

made available to the scientific community (Moreland et al. 2014). The portal provides not

only genomic and protein model sequence data, but also a BLAST search interface, pathway

and protein domain analysis, and a customized genome browser, implemented in JBrowse, to

display the annotation data.

The Mnemiopsis genome was assembled into 5100 scaffolds using next generation sequence

data from the Roche 454 and Illumina GA-II methods of sequencing (Ryan et al. 2013). The

Mnemiopsis protein-coding gene models were predicted by integrating the results of ab initio

gene prediction programs with RNA-seq transcript data and sequence similarity to other

protein datasets. A view of one of those scaffolds is shown in Figure 4.23. As with the UCSC

and Ensembl Genome Browsers, data are organized in horizontal tracks, and exons are shown

as colored boxes. The first track, SCF, is the scaffold. The gene model track, labeled 2.2,

displays the exons of the predicted gene models. The next track, called PFAM2.2, highlights

Pfam domains found in the gene model. The Mnemiopsis RNA-seq reads were assembled into

transcripts using the Cufflinks program (Trapnell et al. 2010), and the CL2 track shows the

alignment of those transcripts to the genomic scaffold. The MASK track highlights repetitive

regions. The EST and GBNT tracks show, respectively, the alignment of publicly available

Mnemiopsis EST and other RNA sequences from GenBank. These two tracks are empty in this

region, so the gene in the gene model track is a novel gene prediction. The overlap between

the exons on the Pfam and gene model tracks shows that the predicted gene contains known

protein domains. The CL2 track lends further support to the gene prediction, as the exons of

the experimentally derived Mnemiopsis transcripts overlap the exons on the gene model track.

Navigation in JBrowse is fairly straightforward, especially for those already accustomed to

using the UCSC or Ensembl Genome Browsers. Tracks can be added or removed from display

by using the checkboxes on the left side of the window. On the display window, click on a

track name and drag it to move the track up or down. To shift the focus of the display window

upstream or downstream, click on the display and drag it to the left or right. The left and right

arrows at the top of the page also move the display window. JBrowse provides multiple ways

to zoom in and out. One option is to use the plus and minus magnifying glasses at the top of

the page. Alternatively, place the mouse in the sequence coordinates above the top track and

click and drag to highlight a region and zoom in on it. Double clicking on a region also zooms

in. Clicking on a track feature opens a window with additional information about that feature.

For example, on the MGP Portal, clicking on a gene model in the 2.2 track opens the Gene Wiki

Figure 4.23 JBrowse display of a predicted Mnemiopsis gene (ML05372a) from the Mnemiopsis Genome Project Portal at the National Human

Genome Research Institute. Seven tracks are shown on this display: SCF, assembled genomic regions are solid black and intermittent gaps

are shaded bright pink; 2.2, consensus Mnemiopsis gene models; PFAM2.2, non-redundant Mnemiopsis protein domains derived from Pfam;

CL2, RNA-seq reads derived from Mnemiopsis embryos, assembled into transcripts using Cufflinks (Trapnell et al. 2010); MASK, genomic

regions that have been repeat-masked using VMatch are shaded in light blue; EST, Mnemiopsis expressed sequence tags (ESTs) from

GenBank; GBNT, Mnemiopsis mRNAs and other non-EST RNAs from GenBank.

for that model, a detailed page that includes nucleotide and protein sequences, pre-computed

BLAST searches, and annotated Pfam domains. Note that although the general look and feel

of JBrowse will remain similar across different genomes, individual JBrowse developers will

create tracks and customizations that are specific to their genome project.

Summary

The UCSC and Ensembl Genome Browsers are sophisticated tools that provide free, web-based

access to genome assemblies and annotations. This chapter has focused on examples from

the human genome and a subset of the annotation tracks available for it. By adding tracks

to the default view, users are able to view annotated genes, sequence variants, gene regulatory

regions, gene expression data, and much more. The displays are highly customizable, and users

can choose which data to view, the display style, and, in some cases, even change the colors of

the annotated features. Both browsers can be accessed not only by text-based queries, such as

gene symbol or chromosomal position, but also by searches with either nucleotide or protein

sequences. The UCSC Genome Browser supports the BLAT search engine, while Ensembl sup-

ports both BLAT and BLAST, depending on the analysis type. Furthermore, the UCSC Table

Browser and Ensembl’s BioMart provide alternate entry points into the underlying data at each

site, in which queries can be constructed using a web-based interface and data returned as text

that can be downloaded and further manipulated. Although the examples illustrated in this

Summary

chapter all derive from the GRCh38 assembly of the human genome, both UCSC and Ensembl

host assemblies from many other organisms. The genomes may be assembled in shorter scaf-

folds, rather than chromosomes, and the variety of annotation types may be much smaller, but

the basic look and feel of the genome browser will remain the same across different species.

With new developments in sequencing technology, even smaller laboratories are now able

to generate whole genome sequencing data, including ChIP-Seq and RNA-seq, exome and

genome sequencing, and even novel genome assemblies. Starting in 2015, genomic data shar-

ing policies now require that all NIH-funded research that generates large-scale genomic data

be submitted to a public database in a timely manner. While human data must be submitted to

an NIH-designated data repository, as of this writing, non-human data may be made available

through any widely used data repository. Viewing and sharing these data with the larger com-

munity of biologists may best be done with a genome browser. Both the UCSC and Ensembl

Genome Browsers provide the option for users to upload their own annotations and view

them in the context of the public genome data. Using Sessions or Track Hubs, users can share

these data with colleagues. The Assembly Hubs feature at UCSC now allows users to share

novel genomes using the Genome Browser framework. Furthermore, the source code for the

UCSC Genome Browser is publicly available, so others are free to set up their own browsers to

host their own annotations, or even their own genomes. Alternatively, researchers who want

to host their own genome browser should consider JBrowse. This freely available software

tool can be easily installed on a web server and used to host custom genomes and annotations.

The UCSC and Ensembl teams start with the same source of data, a genome assembly, often

provided by the GRC. Each team then layers on its own annotations from different sources,

including the location of genes, from GENCODE, RefSeq, and other gene prediction pipelines,

and variants, from NCBI’s dbSNP. Both browsers also include the location of experimentally

determined epigenetic marks, including histone modifications, as well as DNaseI hypersen-

sitive sites, both of which can inform predictions of gene regulatory regions. The regulatory

tracks at UCSC come from the ENCODE project, while Ensembl provides a Regulatory Build,

which includes data from ENCODE as well as other sources. Although individual researchers

may have personal preferences about which interface is easier to use, or which site provides

information that is more relevant to the biological question they are studying, most members

of the bioinformatics community will undoubtedly use a genome browser at some point in

their research career.

Internet Resources

UCSC Genome Browser

Main page

genome.ucsc.edu

Genome Browser User’s Guide

genome.ucsc.edu/goldenPath/help/hgTracksHelp.html

Table Browser User’s Guide

genome.ucsc.edu/goldenPath/help/hgTablesHelp.html

Displaying custom annotation data

genome.ucsc.edu/goldenPath/help/customTrack.html

Data file formats for custom annotation

genome.ucsc.edu/FAQ/FAQformat.html

Sessions User’s Guide

genome.ucsc.edu/goldenPath/help/hgSessionHelp.html

Using UCSC Genome Browser Track

Hubs

genome.ucsc.edu/goldenPath/help/hgTrackHubHelp.html

Assembly Hubs wiki

genomewiki.ucsc.edu/index.php/Assembly_Hubs

Contact information

genome.ucsc.edu/contacts.html

Ensembl Genome Browser

Main page

www.ensembl.org

Ensembl Stable IDs

www.ensembl.org/info/genome/stable_ids

Ensembl Archives

www.ensembl.org/info/website/archives

BioMart

www.ensembl.org/biomart/martview

pre!Ensembl

pre.ensembl.org

Help & Documentation

www.ensembl.org/info

BioMart documentation

www.ensembl.org/info/data/biomart

Displaying custom annotation data

www.ensembl.org/info/website/upload

Data file formats for custom annotation

www.ensembl.org/info/website/upload/index.html#formats

Contact information

www.ensembl.org/info/about/contact

JBrowse

JBrowse Genome Browser

jbrowse.org

COSMIC Genome Browser

cancer.sanger.ac.uk/cosmic/browse/genome

Mnemiopsis

Genome Project Portal (MGAP)

research.nhgri.nih.gov/mnemiopsis

Phytozome

phytozome.jgi.doe.gov

Rat Genome Database

rgd.mcw.edu

Other genome resources

GENCODE

www.gencodegenes.org

Genome Reference Consortium

www.ncbi.nlm.nih.gov/grc

GWAS Catalog

www.ebi.ac.uk/gwas

National Center for Biotechnology

Information (NCBI) Genome Data

Viewer

www.ncbi.nlm.nih.gov/genome/gdv

National Institutes of Health (NIH)

Genomic Data Sharing Policyies

osp.od.nih.gov/scientific-sharing/policies

NIH Genotype-Tissue Expression

(GTEx) Portal

www.gtexportal.org

Track Hub Registry

www.trackhubregistry.org

Further Reading

The best way to learn about the data and tools available in the UCSC and Ensembl Genome

Browsers is to read the relevant sections of the online documentation that accompanies each

browser. The documentation on both sites is extensive and up to date, and will likely answer the

user’s questions. Alternatively, specialized questions can be addressed by contacting the web site

development teams. URLs are listed in the Internet Resources section of this chapter.

The Database issue of Nucleic Acids Research, published in January of each year, usually

includes articles that provide a broad overview of each Genome Browser as well as a description of

new data and resources. The references for 2019 are listed below, and additional information can

be found in Chapter 1.

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This chapter was written by Dr. Tyra G. Wolfsberg in her private capacity. No official support or

endorsement by the National Institutes of Health or the United States Department of Health

and Human Services is intended or should be inferred.