Genomics and Personalized Care Lab Session Leming Zhou

Genomics and Personalized Care Lab Session Leming Zhou, Ph. D School of Health and Rehabilitation Sciences Department of Health Information Management

Outline • Nucleotide, protein, genetic variation, gene and disease association databases – NCBI • Gen. Bank; protein structure; db. SNP; OMIM • Pairwise sequence alignment • BLAST search • UCSC genome browser

NCBI • Created as a part of National Library of Medicine in 1988 – Establish public databases – Perform research in computational biology – Develop software tools for sequence analysis – Disseminate biomedical information • Databases – Sequence, such as Gene. Bank, Ref. Seq, db. SNP – Literature, such as Pub. Med, OMIM • Tools – Entrez. Blast, Cn 3 D, etc.

NCBI Homepage

Gen. Bank • Nucleotide only sequence database • Gen. Bank Data – Direct submissions individual records (Bank. It, Sequin) – Batch submissions via email (EST, GSS, STS) – ftp accounts established for sequencing centers • Data shared nightly amongst three collaborating databases: – Gen. Bank – DNA Database of Japan (DDBJ). – European Molecular Biology Laboratory Database (EMBL)

Gen. Bank Record (Header) LOCUS NM_001963 4913 bp m. RNA linear PRI 20 -SEP-2009 DEFINITION Homo sapiens epidermal growth factor (beta-urogastrone) (EGF), m. RNA. ACCESSION NM_001963 VERSION NM_001963. 3 GI: 166362727 KEYWORDS . SOURCE Homo sapiens (human) ORGANISM REFERENCE AUTHORS TITLE JOURNAL Homo sapiens Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi; Mammalia; Eutheria; Euarchontoglires; Primates; Haplorrhini; Catarrhini; Hominidae; Homo. 1 (bases 1 to 4913) Hosgood, H. D. III, Menashe, I. , He, X. , Chanock, S. and Lan, Q. PTEN identified as important risk factor of chronic obstructive pulmonary disease Respir Med (2009) In press PUBMED 19625176 REMAKR Gene. RIF: Observational study of gene-disease association.

Gen. Bank Record (Features) FEATURES source Location/Qualifiers 1. . 4913 /organism="Homo sapiens" /mol_type="m. RNA" /db_xref="taxon: 9606" /chromosome="4" /map="4 q 25" gene 1. . 4913 /gene="EGF" /gene_synonym="HOMG 4; URG" / note="epidermal growth factor (beta-urogastrone)" /db_xref="Gene. ID: 1950" /db_xref="HGNC: 3229" /db_xref="HPRD: 00578" /db_xref="MIM: 131530" exon 1. . 579 /gene="EGF" /gene_synonym="HOMG 4; URG" /inference="alignment: Splign" /number=1 CDS 453. . 4076 /gene="EGF" /gene_synonym="HOMG 4; URG" /note="beta-urogastrone" /codon_start=1 /product="epidermal growth factor precursor" /protein_id="NP_001954. 2" /db_xref="GI: 166362728" /db_xref="CCDS: CCDS 3689. 1" /db_xref="Gene. ID: 1950" /db_xref="HGNC: 3229" /db_xref="HPRD: 00578" /db_xref="MIM: 131530" /translation="MLLTLIILLPVVSKFSFVSLSAPQHWSCPEGTLAGNGNSTCVGP APFLIFSHGNSIFRIDTEGTNYEQLVVDAGVSVIMDFHYNEKRIYWVDLERQLLQRVF

Gen. Bank Record (Sequence) ORIGIN 1 aaaaagagaa 61 caagggttgt 121 gccttgctct 181 cataagggtg 241 ctgtggcttc 301 ggacaacagc 361 ccgcatctgg 421 ttttcttttg 481 cagtagtttc 541 aaggtactct 601 tctcccatgg 661 tggtggatgc 721 gggtggattt 781 gagtatgtaa 841 ttatttggtc 901 cccacattct 961 ggtttatatt actgttggga agctggaact gtcacagtga tcaggtattt ccttggcagg acaacaggag ggtcaatcat aaagttcaaa aaaatttagt cgcaggaaatagtatc tggtgtctca agaaagacaa tatagagaaa aaatcaacag tttaagtgct ttggtcttca gaggaatcgt ttccatcagt agtcagccag cttactggct ctgcattcag agtaaaagat actcaccttg ctcatcaaga tttgttagtc gggaattcta tttaggattg gtgatcatgg cttttgcaaa aatgtttctg gaaggaatca ttaaaatatc gaggtggctg atctccatat tcttcctttc agcagggctg tccaaagaaa aaggtctctc gccccagggc cccgggccat ttatgctgct tctcagcacc cttgtgtggg acacagaagg attttcatta gagtttttct gaatggcaat ttacagtaac ctgcaaatgt gaagccttta ttcttctttc tttttcctct ttaaactctg catagataaa agttgaagaa tgaggcctcc gctccagcaa cactcttatc gcagcactgg tcctgcaccc aaccaattat taatgagaaa gaatgggtca aaattggata agatatgaaa agcagttgat tagagcagat agccccaatc ctaagccttt tgaaatttgt gaaatctttc agagcttgga gctcaggcag aatcaagctg attctgttgc agctgtcctg ttcttaattt gagcaattgg agaatctatt aggcaagaga aatgaagaag ggaaataatt ccagtagaaa ctcgatggtg

FASTA: Sequence Format

Protein Structure

Crystal Structure of a Protein

Protein Structure Databases • Proteins take on 3 D structure • 3 D data for some proteins is available due to techniques such as NMR and X-Ray crystallography – PDB http: //www. pdb. org/ – SCOP http: //scop. mrc-lmb. cam. ac. uk/scop – MMDB http: //www. ncbi. nlm. nih. gov/Structure/

Genetic Variations

Polymorphisms • Genomic sequences from two unrelated individuals are 99. 9% identical. • The 0. 1% difference is due to genetic variations, and mainly (~90%) one form of variation called Single Nucleotide Polymorphisms (SNPs, singlebase variations).

Importance of Genetic Variations • Genetic variations underlie phenotypic differences among different individuals • Genetic variations determine our predisposition to diseases and responses to drugs, therapies, and environmental insults such as bacteria, virus, and chemicals • Genetic variations reveal clues of ancestral human migration history

Major Types of Genetic Variations • Single nucleotide mutation – Majority of SNPs do NOT directly contribute to any phenotypes • Insertion or deletion of one or more nucleotides – Tandem repeat polymorphisms (Genomic regions consisting of variable length, usually 1 -100 bases long, of sequence motifs repeating in tandem with variable copy number) • Used as genetic markers for DNA finger printing (forensic, parentage testing) • Many cause genetic diseases – Insertion/Deletion polymorphisms (Often resulted from localized rearrangements between homologous tandem repeats) • Gross chromosomal aberration – Deletions, inversions, or translocation of large DNA fragments – Often causing serious genetic diseases

The Effect of SNPs • The phenotypic consequence of a SNP is significantly affected by the location where it occurs (gene or nongene), as well as the nature of the mutation (synonymous or non-synonymous) – No consequence – Affect gene transcription quantitatively or qualitatively – Affect gene translation quantitatively or qualitatively – Change protein structure and functions – Change gene regulation at different steps

Simple/Complex Genetic Diseases and SNPs • Simple genetic diseases (Mendelian diseases) are often caused by mutations in a single gene – e. g. Huntington’s, Cystic fibrosis, etc. • Many complex diseases are the result of mutations in multiple genes, the interactions among them as well as between the environmental factors – e. g. cancers, heart diseases, Alzheimer's, diabetes, asthmas, obesity, etc.

Genetic Variations Databases • db. SNP – http: //www. ncbi. nlm. nih. gov/SNP/ • Online Mendelian Inheritance in Man (OMIM) – http: //www. ncbi. nlm. nih. gov/omim • International Hap. Map Project – http: //www. hapmap. org/ • Genome Variation Server (Seattle SNPs) – http: //gvs. gs. washington. edu/GVS/

db. SNP • The Single Nucleotide Polymorphism database (db. SNP) is a publicdomain archive for a broad collection of simple genetic variations • This collection of polymorphisms includes: – Single-base nucleotide substitutions (or single nucleotide polymorphisms -SNPs) • Roughly 10 million in human population or on average 1 per 300 bps • Less than half of these SNPs are identified and stored in the database – Microsatellite repeat variations (or short tandem repeats - STRs) • In sillico estimation of potentially polymorphic variable number tandem repeats (VNTR) are over 100, 000 across the human genome – Small-scale multi-base deletions or insertions • The short insertion/deletions are difficult to quantify and the number is likely to fall in between SNPs and VNTR

A db. SNP Record >gnl|db. SNP|ss 5586300|allele. Pos=214|len=475|taxid=960 6|alleles='A/G'|mol=Genomic ATAAACATGG ATCAAGTCAT CTTTGAGGAA TTCCAAGTAC TTTAAAGRAG R CTCAAGCAAT GTATTAATGA AGAAACAGAG ACCTGAGGTC AAATAAAAAA TTCTCTCCAT ACTTTTACAA YTGTTAAAAC CATTCAATRT AGTGAGCACA CCA AACCCATATC TAAATGTAAG CACCTGAAAG ATTAGCCGTA GTATACCACC AAAAATCTGC AGAAATGGGA ATAACATTAG ACTTTTTCCC TAGAGGAAAA AATGAGAACA AGAAAATGTT ATTAATGAAG AATAGGTTCC GGCCAAAATT TATAAACAAA GCAAGAATAT A TAGGTTCCAG AGTGATGAAA GAATGCTATG GTCTTCCTGG GAAGAAGTAG TACTAATGAA ACATTCAAGC CTTAGATTAG AAGTAATTGT TTCAGACTGT GTGGGCTCCA AGAACTAGGT GGGTTTTGCA AAGCATCCTG TAATACAGAT

Different Ways to Search SNPs in db. SNP • db. SNP web site – Direct search of SS record; batch search; allow SNP record submission; No search limit • Entrez SNP – http: //www. ncbi. nlm. nih. gov/sites/entrez? db=Snp – Search limits options allows precise retrieval • Entrez Gene Record’s SNP Links Out Feature – Direct links to corresponding SNP records; access to genotype and linkage disequilibrium data • NCBI’s Map. Viewer – Visualize SNPs in the genomic context along with other types of genetic data

Search SNPs from db. SNP Web Page • http: //www. ncbi. nlm. nih. gov/SNP/index. html

Search SNPs from Entrez SNP Web Page • http: //www. ncbi. nlm. nih. gov/sites/entrez? db=Snp • The db. SNP is a part of the Entrez integrated information retrieval system and may be searched using either qualifiers or a combination search limits from 14 different categories

Gene and Disease

Disease Causing Genes Disease centric databases: • OMIM: http: //www. ncbi. nlm. nih. gov/omim/ • CDC Huge. Navigator: http: //hugenavigator. net/ • HGMD: https: //portal. biobaseinternational. com/hgmd/pro/start. php • A Catalog of Published Genome-Wide Association Studies: http: //www. genome. gov/26525384

Online Mendelian Inheritance in Man (OMIM) • http: //www. ncbi. nlm. nih. gov/entrez/query. fcgi? db=OMIM • OMIM is a human genetic disorders database built and curated using results from published studies • Each OMIM record provides a summary of the current state of knowledge of the genetic basis of a disorder, which contains the following information: – description and clinical features of a disorder or a gene involved in genetic disorders; – biochemical and other features; – cytogenetics and mapping; – molecular and population genetics; – diagnosis and clinical management; – animal models for the disorder; – allelic variants. • OMIM is searchable via NCBI Entrez, and its records are cross-linked to other NCBI resources.

OMIM: Variant • The OMIM database includes genetic disorders caused by various mutation/variation, from SNPs to large-scale chromosomal abnormalities • Variants are represented by a 10 -digit OMIM number, and can be searched in two ways – Search for a gene or a disease, when retrieved, view its variants

Variants in OMIM Records • For most genes, only selected mutations are included – Criteria for inclusion include: the first mutation to be discovered, high population frequency, distinctive phenotype, historic significance, unusual mechanism of mutation, unusual pathogenetic mechanism, and distinctive inheritance. • Most of the variants represent disease-producing mutations, NOT polymorphisms. • A few polymorphisms are included, many of which show a positive statistical correlation with particular common disorders. • Few neutral polymorphisms are included in OMIM • Some SNPs in the db. SNP records are not linked to the corresponding OMIM records.

Similarity Search • Find statistically significant matches to a protein or DNA sequence of interest. • Obtain information on inferred function of the gene • Sequence identity/similarity is a quantitative measurement of the number of nucleotides / amino acids which are identical /similar in two aligned sequences – Calculated from a sequence alignment – Can be expressed as a percentage – In proteins, some residues are chemically similar but not identical

Sequence Alignment • A linear, one-to-one correspondence between some of the symbols in one sequence with some of the symbols in another sequence – Four possible outcomes in aligning two sequences • Identity; mismatch; gap in one sequence; gap in the other sequence • May be DNA or protein sequences.

Alignment Algorithms • Sequences often contain highly conserved regions • These regions can be used for an initial alignment

Alignments • Two sequences Seq 1: ACGGACT Seq 2: ATCGGATCT • There may be multiple ways of creating the alignment. Which alignment is the best? A – C – G G – A C T | | | A T C G G A T - C T A T C G G A T C T | | | A – C G G – A C T

BLAST • BLAST - Basic Local Alignment Search Tool: A sequence comparison algorithm optimized for speed used to search sequence databases for optimal local alignments to a query • Most widely used and referenced computational biology resource • The central idea of the BLAST algorithm is to confine attention to segment pairs that contain a word pair of length W with a score of at least T when compared to the query using a substitution matrix • Word hits are then extended in both directions to generate an alignment with score exceeding a given threshold S

Four Steps of a BLAST search • Enter query sequence • Select one BLAST program • Choose the database to search • Set optional parameters

Enter Query Sequence • Sequence can be pasted into a text field in FASTA format or as accession number • Sequence can also be uploaded as a file (FASTA format) • Users may indicate a sequence range of the query sequence instead of using the whole query sequence • Job title will be automatically generated from sequence header

Select one BLAST Program • BLAST Programs: – BLASTN: DNA query sequence against a DNA database – BLASTP: protein query sequence against a protein database – BLASTX: DNA query sequence, translated into all six reading frames, against a protein database – TBLASTN: protein query sequence against a DNA database, translated into all six reading frames – TBLASTX: DNA query sequence, translated into all six reading frames, against a DNA database, translated into all six reading frames • Choose the right one according to the purpose of the search

Choose the Database to Search • BLASTN

Optional Parameters • Specify the organism to search or exclude – Common name, taxonomy id, … • Exclude certain sequences – Exclude predicted sequences or sequences from metagenomics • Use Entrez query to select a subset of the blast database page 93

BLASTN Output (header)

BLASTN Output (Graphic Summary) matches to itself probable homologs distantly related homologs distant homolog with shared domain or motif

BLASTN Output (Descriptions)

BLASTN Output (Sequence Alignments)

Genome Browser • Genome Browser is a computer program which helps to display gene maps, browse the chromosomes, align genes or gene models with ESTs or contigs etc. • Big Three: – UCSC Genome Browser – NCBI Mapviewer – Ensemble

UCSC Genome Browser • http: //genome. ucsc. edu

Organization of Genomic Data Annotation Tracks sequence Genome backbone: base position number chromosome band sts sites microarray/expression data known genes predicted genes Links out to more data evolutionary conservation SNPs repeated regions more…

UCSC Genome Browser

UCSC Genome Browser sequence Annotation Tracks STS sites Known gene Expression Evolutionary conservation SNP Repeated regions

A Sample of the UCSC Genome Browser gene details sequence Annotation Tracks comparisons SNPs

Genome Browser Gateway • Use this Gateway to search by: – Gene names, symbols, IDs – Chromosome number: chr 7, or region: chr 11: 1038475 -1075482 – Keywords: kinase, receptor • See lower part of page for help with format

Genome Browser Gateway text/ID searches le p m xa d e e h rc provi a e d H s ples l u f m elp sa s

The Genome Browser Gateway 1 2 3 4 5 6 assembly Make your Gateway choices: 1. Select Clade 2. Select genome = species: search 1 species at a time 3. Assembly: the official backbone DNA sequence 4. Position: location in the genome to examine 5. Image width: how many pixels in display window; 5000 max 6. Configure: make fonts bigger + other choices

Different Species, Different Tracks • Species may have different data tracks • Layout, software, functions are the same

Sample Genome Viewer Image, TP 53 base position UCSC genes Ref. Seq genes MGC clones m. RNAs & ESTs many species compared single species compared SNPs repeats

Visual Cues on the Genome Browser Tick marks; a single location (STS, SNP) 3' UTR exon <<< exon < < < <ex 5' UTR Intron and direction of transcription <<< or >>> Track colors may have meaning—for example, UCSC Gene track: • If there is a corresponding PDB entry = black • If there is a corresponding reviewed/validated seq = dark blue • If there is a non-Ref. Seq seq = lightest blue For some tracks, the height of a bar is increased likelihood of an evolutionary relationship (conservation track) Alignment indications (Conservation pairs: “chain” or “net” style) • Alignments = boxes, Gaps = lines

Options for Changing Images: Upper Section Walk left or right Click to zoom 3 x and re-center Zoom in Specify a position Zoom out Fonts, window, next item, more • Change your view or location with controls at the top • Use “base” to get right down to the nucleotides • Configure: to change font, window size, more… – Next item, next exon navigation assistance can be turned on

Annotation Track Display Options Enforc enfor e ce chang s es Links to info and/or filters Change track view • Some data is ON or OFF by default • Menu links to info about the tracks: content, methods • You change the view with pulldown menus • After making changes, REFRESH to enforce the change

Annotation Track Options Defined • Hide: removes a track from view n Dense: all items collapsed into a single line n Squish: each item = separate line, but 50% height n Pack: each item separate, but efficiently stacked (full height) n Full: each item on separate line

Mid-page Options to Change Settings Flip display to Genomic 3’ 5’ Reset, back to defaults Start from scratch • You control the views • Use pulldown menus • Configure options page Enforce any changes (hide, full, squish…)

Base Level and Protein Sequences