Alignment and Assembly

Sequence alignment

The process of arranging DNA, RNA, or protein sequences to identify regions of similarity

Importance of alignment in NGS

Reads are short and fragmented; alignment maps them to a reference genome for interpretation

Downstream analyses requiring alignment

Variant calling, gene annotation, gene expression analysis

Global alignment

Aligns entire sequences end-to-end (e.g., Needleman–Wunsch)

Local alignment

Aligns best matching subsequences (e.g., Smith–Waterman)

Example of local alignment tool

BLAST

Dot plot purpose

Visualises all possible alignments; diagonals indicate similarity

Dynamic programming in alignment

Computes optimal scores using match, mismatch, and gap penalties

Indexing in alignment

Preprocessing the reference genome to speed up sequence searching

Features of a high-quality alignment

Many matches, few mismatches, few gaps

SAM acronym

Sequence Alignment/Map

What a SAM file contains

Information on where and how each read aligns to the reference genome

Why BAM files are used

Binary compressed SAM files that save space

Examples of analyses using SAM/BAM

Mutation detection, genome assembly, gene expression studies

Genome assembly

Reconstructing a genome from short reads

De novo assembly

Building a genome from scratch without a reference

Reference-guided assembly

Aligning reads to an existing reference genome; faster and less computationally intensive

Reads definition

Short DNA fragments produced by a sequencer

Contigs definition

Contiguous sequences formed from overlapping reads

Scaffolds definition

Ordered and oriented groups of contigs

DNA features making assembly difficult

High GC content and repeat regions

Recommended read depth for bacterial assembly

About 50×

Solution to poor coverage

Repeat sequencing to increase depth

Hybrid assembly

Combining short and long reads for improved assembly

N50 definition

Length of the smallest contig such that 50% of the genome is in contigs of that length or longer

L50 definition

Number of contigs whose combined length makes up 50% of the genome

Largest contig size

Longest continuous assembled DNA sequence

Total assembly length expectation

Should approximate the organism’s true genome size

Illumina read length

50–600 bp

Nanopore read length

Kilobases to megabases

Why Illumina requires fragmentation

Read length is limited by the number of sequencing cycles

Advantage of Nanopore sequencing

Real-time long-read sequencing

Why long reads help assembly

They span repetitive regions more easily

Bioinformatics pipeline

A sequence of connected steps that transform input data into results

Example hybrid assembly tools

Unicycler and Hybracter

Three phases of the Human Genome Project

Mapping, sequencing, bioinformatics

Mapping techniques used in HGP

Restriction mapping, FISH, linkage maps, BAC/YAC libraries

2001 draft human genome

Covered 83% of the genome; error rate <1/1000

2003 finished genome

Covered 99% of gene-containing regions; error rate ~1/20,000

Information gained from alignment to a reference

Variants, structural differences, expression levels, mapping quality

Three alignment methods

Dot plots, dynamic programming, BLAST