M 1, V1

sequenziertes Fragment

statistical procedure ,convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components.

a collection of the total genomic DNA from a single organism.

single nucleotide polymorphisms
 

1. De novo genome project:
 

2. Re-sequencing project
 

• map reads onto reference sequence

• identify minor changes compared to reference,

e.g. single nucleotide polymorphisms (SNPs)

• simple, fast, cheap, but selective analysis

--

-find minor changes, cheaper (selective analysis), use reference sequence

-assumption: almost identical to data base reference

• assembly of sequence reads without reference

• identify major changes compared to known sequences

a)genomic rearrangements

(e.g. cancer genomics), not new, just changed expression

• new sequences not present in reference

(e.g. ‘genomic islands’ encoding antibiotic resistance

in bacteria), not present in reference because integrated in genome, can be identifierd by de -novo project

--

-find major changes to known sequences but no reference does exist

-complicated, expensive
 

1. Whole-genome sequencing:
 

2. Targeted genome sequencing:
 

• huge technical, bioinformatic + financial effort

• especially for human genome sequencing
 

• regions with known phenotypic relevance e.g.

BRCA1/2 (breast cancer susceptibility)

• exome sequencing

• e.g.: 23andMe
 

 globally, compare cancer mutation frequency(mind: cancer vs. background influence)

-->MOST STUDIES ON GENOMICS ARE GWAS

-(microbiota analysis)

• >90% of microbiome projects

• “Who’s there?” but not: “What are they doing?”
 

Targeted genome sequencing
(Human exome = gesamtheit der exons), coding for genes/protein sequences
(Intron/ noncoding DNA is important for regulation but not so much in sequencing, so its cheaper not to focus on everuthing
 

•fungal equivalent of bacterial 16S rRNA analysis

internal transcribed spacer’ (ITS)
 

•housekeeping genes (= turned on under all conditions, used by all cells)

•higher resolution than 16S rRNA sequencing"

(e.g. to differentiate + epidemiologically characterize multiple

E. coli isolates)

---

-eg. salmonella, 7patients, same bacteria? → 7 regions, compare, are they the same?
 

Exome seq.(coding for genes/protein sequences)

16S rRNA amplicon seq. (microbiota analysis “Who’s there?”)

ITS amplicon sequencing (fungal equivalent of bacterial 16S rRNA analysis)
 

Multi-locus sequence typing (MLST) (housekeeping genes
, same salmonella in patients?)
 

-high-throughput short read sequencing

• DNA synthesis progression by position,

•Problem: speed
 

Single-Molecule Real Time (SMRT) sequencing

• no need for template amplification

• fast progression, long read lengths

• detection of methylated bases possible
 

Promised results:

• fast, cheap, long reads
 

Illumina sequencing (-high-throughput short read sequencing)

Pacific Biosciences sequencing (Single-Molecule Real Time (SMRT) sequencing)

Oxford Nanopore sequencing (Promised results fast, cheap, long reads)

= RNA-Seq

-if genome sequence is available (reference-guided analysis)

-sequencing depth is more critical than read length
 

-need to be sure to only deal with mRNA (small persantage), always has poly(A)tail

-take reverse transcriptase to build DNAstrang based on RNA strang
 

-random oligomers

-cDNA synthesis not as easy, as it does not have an poly(A)tail, random oligomers bind randomly, cannot differentiate between r,t,m,RNA
 

“Heritable changes in gene expression not attributable to

nucleotide sequence variation.”

(Murrell et al. [2005] Hum Mol Genet)

“Heritable changes in gene expression not attributable to

nucleotide sequence variation.”

(Murrell et al. [2005] Hum Mol Genet)

• coding sequence (+ rRNA + tRNA)

actually expressed genes

• suitable for

comparative analysis of different

physiological conditions (cells or microbes)

• coding sequence

•

potentially available gene functions

(

no information about actual gene expression!)

• 0.01 x

reduced sequencing effort

• everything: coding + non-coding sequence

• including regulatory units

• difficult interpretation:

what is relevant?