400 lec 1b & 2a

large scale sequencing

• random fragmentation ( cut dna and add tags for genome lib)

• sequence fragments

• asemble (resequence) —> de novo

• gap filling/error check

• redundant = more accurate

what is required for DNA sequencing

DNA

primer

nucleotides

dna poly

nucleotide analogs (terminators) ddNTPs

de novo assembly

build genome w out reference

redundancy

reduces sequencing erros

improves assebmly

helps resolve repeates

DNA sequencing - SANGER (requirements)

• interrupt dna synthesis OR chain termination

• use mixture of ddNTPs and dNTPs

• higly accuate

• need dna template, primer, nucleotides, and dna polymerase

• nucleotide analogs (terminators) stop the reaction at each base

dNTPs

normal nucleotides

- have 3’ OH group

ddNTPs

terminator sequences

- lack 3’ OH group (have H insted)

DNA sequencing - SANGER (mechanism)

• ddNTPs lack a 3′-OH group

• Once incorporated → chain termination

Produces fragments that differ by exactly one base

ddNTP vs dNTP

ddNTP = terminate DNA synthesis bc lack 3-OH group

dNTP = continued DNA chain elongation bc they HAVE 3-OH group

sanger pros and cons

Result

• A mixture of DNA fragments of varying lengths

• Fragment length identifies base position
  
  

Strengths

• Extremely low error rate (<0.1%)

• Gold standard for sequence confirmation

• Ideal for single-gene studies
  
  

Limitations

• Low throughput

Short read lengths (<800 bp)
**good for confirming sequences

NGS Next gen sequencing

• Extremely high throughput (~1.8 trillion bases / 72 hrs)

• Produces >1 billion reads

• Read length: ~150 bp (up to ~100 kb with Nanopore)

• Higher error rate (~0.26–15%)

• Used for:

  • Whole-genome resequencing

  • Population genomics

  • Metagenomics

***SCALE AND DISCOVERY

Oxford Nanopore (MinION)

• Very long reads (up to ~100 kb)

• Higher error rate than other methods

• Useful for:

  • Genome assembly

  • Structural variants

  • Scaffolding

  • FOR NUC ACID

***ACCURACY & CONFIRMATION

de Bruijn Graphs (Short Reads)

• Reads are broken into k-mers

• Overlapping k-mers form a graph

• Paths through graph = assembled sequence

Efficient but sensitive to sequencing errors

stages of genome assembly

1. Reads – raw sequencing output

2. Contigs – continuous assembled sequences

3. Scaffolds – ordered contigs with gaps (“NNNN”)

4. Chromosome-level assembly – near-complete genome

Reference genome – official, annotated version used by the community

contig N50

60 kbp

• The shortest contig length such that 50% of the genome is contained in contigs of that size or larger

• sequence length of the shortest contig at 50% of the total genome

BUSCO

• Benchmarking Universal Single Copy Orthologs

• Measures genome completeness

>95% score = high-quality assembly

genome annotation tools

• Phylosift

• Blast2GO

• Use annotated reference genomes as a guide

• Comparative genomics (evolutionary conservation)

• Transcript (RNA-seq) evidence + Protein homology

**provides a roadmap for the genome

databases

• Primary databases: raw data archives (e.g., sequence reads)

• Secondary databases: curated, interpreted data

• Relational databases: link information across databases

• Local databases: built from your own NGS data (next gen sequencing)

genetic database landmarks

• 1965: Atlas of Protein Sequences (Dayhoff)

• Protein Information Resource (PIR)

• EMBL (1982)

• Human Genome Project

• GenBank + DDBJ + EMBL collaboration

NCBI Entrez → integrated database access

genbank fila anatomy

1. Header – metadata, organism, accession number

2. Features – genes, CDS, regulatory elements

3. Nucleotide sequence

FASTA Format

• > header line

• Sequence lines below

Simple, widely used for alignment and analysis

database errors

sources

• PCR introduces mutations

• PCR amplifies the wrong organism

• Gene families → homology confusion

Incorrect taxonomic assignment

PCR

lab tech that makes millions of copies of specific DNA segments (photocopies)

FASTA N

any nucleotide

FASTA R

purine

A

G

FASTA Y

pyrimidines

C

T/U

FATSA -

gaps of intermediate length

FATSA *

translation stop

**amino acids

linear model of progressive evolution

 (old view): evolution was once thought of as a straight line from “simple → complex.

linear model modern view

 genomes change in a branching, tree-like pattern, reflecting common ancestry and divergence over time

**evo represed w phylo trees not ladders

newick nomenclature

• A text-based format for representing phylogenetic trees.

• Uses parentheses and commas to show branching relationships.

Common in computational biology and tree-building software.

dichotomy

• Modern phylogenetics focuses on relationships and ancestry, not ranking organisms

types of phylo trees

• cladogram

• phylogram

  • dendrogram

cladogram

• Shows branching order only.

• Branch lengths have no meaning.

Emphasizes shared ancestry.

phylogram

• Branch lengths are proportional to the amount of evolutionary change.

• Reflects genetic distance

• Dendrogram (Ultrametric tree)

• All tips are the same distance from the root.

• Assumes a molecular clock (equal rates of evolution)

homology

• Similarity due to shared ancestry.

• Example: shared genes between cats and whales despite different functions.

• Function ≠ homology; ancestry matters more than what the gene currently does.
  
  

homoplasy

• Similarity not due to shared ancestry.

• Arises from convergent evolution or reversals.

gene dupe & homology

• Gene duplication complicates homology because multiple copies exist.

• After duplication, copies can evolve independently and take on new functions.

• orthologs

• paralogs

  • xenolog

Example: Human Hemoglobin (Hb) Gene Family

• Originated through gene duplication events.

• Different Hb genes are paralogs.

Functional diversification allows different hemoglobins to act at different developmental stages (e.g., fetal vs adult Hb).

ortholog

• Genes in different species that diverged via speciation.

Usually retain similar function.
gene copy

paralog

gene copy

• genes related by duplication within a genome.

Often evolve new or specialized functions.

xenolog

gene copy

• Genes acquired via horizontal gene transfer.