Using the results of genetic studies

Question 1

Large data genetic analysis techniques

Answer 1

GWAS - identify loci in genome associated with a phenotype/disease

RNAseq - provides a snapshot of gene expression levels

Question 2

difficulties using GWAS data

Answer 2

large GWAS for complex diseases detect many loci = prioritisation

90% of GWAS sap’s are in non-coding regions of the genome

Question 3

RNA seq data

Answer 3

relative expression data for everyone

need to set significance threshold = p value, fold change

novel, allele specific expression and alternative transcripts may be identified

Question 4

osteocyte transcriptome

Answer 4

same cell type at diff locations show diff transcriptomes

> 100 novel transcripts identified

distinct pattern of diff expressed genes in diff tissues/cell types

Question 5

RNAseq other applications

Answer 5

cell populations response to treatment

how gene expression changes through development or under disease conditions

single cell transcriptome analysis

Question 6

what are the difficulties using RNAseq data

Answer 6

many expression changes likely to be found = difficult to differentiate real from methodological artifacts

transcriptome is a snapshot of expression in a specific cell/tissue and at a specific time

identification of differential expression does not provide biological reasoning

Question 7

what do GWAS do

Answer 7

identifies associations across whole genome
large number of loci
doesn’t identify causal variants or genes
doesn’t identify cell type/tissue/developmental stage

Question 8

what does RNA sequencing do

Answer 8

transcriptome of single cell/tissue type
large number of differentially expressed genes
misses changes in other cell types or stages of development
doesn’t identify reason for differential gene expression

Question 9

describe osteocytes

Answer 9

embedded in lacunae in mature bone

connected via processes through canalicular channels

form a mechanosensory network throughout bone

Question 10

describe pathway analysis

Answer 10

generate a gene set and compare database

gene ontology and kyoto encyclopaedia of genes and gnomes

allows you to identify new biology by determining the type of genes with association/differential expression

Question 11

personalised medicine.

Answer 11

applying the results of genetic studies to the healthcare management of an individual

predict and prevent disease
diagnosis
personalised interventions

Question 12

difficulties linking loci to gene

Answer 12

linkage disequilibrium makes it difficult to distinguish causal variant

90% of GWAS SNPs are in non-coding regions

may act at a distance from effected genes

need to determine relevant cells/tissues

Question 13

fine mapping

Answer 13

high resolution study of loci attempting to pinpoint individual variants directly effecting trait

statistical and probabilistic methods or comparison to a SNP correlation

Question 14

assigning causal genes

Answer 14

proximity

non synonymous exonic change

chromatin conformation capture

Question 15

what is the relevant cell type

Answer 15

often unclear what are the causal cells

SNP enrichment analysis

• gene expression
• regulatory elements
• open chromatin

Question 16

GWAS to biological reasoning

Answer 16

100s of GWAS loci, 90% in non-coding regions
fine mapping to attempt to define causal variants at loci
analysis of causal SNP location to predict causal gene
cell type SNP enrichment analysis to determine relevant cell types

Question 17

explanations for locus overlap

Answer 17

GWAS and eQTL loci can overlap for 3 reasons:

independent causal variant in LD

a single causal SNP

pleiotropy

Question 18

transcriptome wide association studies

Answer 18

• directly test for associations between gene expression levels and phenotype
• overcomes most issues with GWAS and RNAseq
• currently generally
• gene expression is highly heritable = tissue specific eQTL maps

you can use genotype to predict gene expression levels = GWAS studies give us the SNP genotypes

Question 19

prioritising from GWAS results

Answer 19

use knowledge of genome and gene expression to prioritise loci/genes for further investigations

eQTLs = expression quantitative trait loci

colocalisation analysis to annotate causal genes

TWAS to directly associate gene expression to trait phenotype

Question 20

functional analysis - model animals

Answer 20

knockout animals =
total knockout 
cell specific 
inducible 
gene editing

Question 21

reverse genetics with modern tools

Answer 21

classical reverse genetics

• cloning to introduce mutations in target gene
• observe phenotypic outcome

targeted genetics-

• gene targeting and trapping
• gene editing

Question 22

international mouse phenotypic consortium

Answer 22

98% of human genes have a homolog in the mouse genome

IMPC is generating knockout mice strains for each mouse gene = 20,000 genes

all mice are same background, kept under the same conditions

• basic phenotypic
• results freely available