Translational Genomics 2019
Summary LC 1.1: Introduction to Translational Genomics
The near future
- Genome sequencing at birth (for everyone)
- Monogenic diseases immediately diagnosed
- Use of genomic data in personalized treatment protocols
- Predictive profiles (+health advice) for late-onset diseases
Genome sequencing from birth is already being done (the genome of 1500 babies was already sequenced
in 2013).
The NSIGHT key questions
- Ethical
- Legal
- Economic
Personalized medicine says nothing more than looking of the baseline risk of your genome. The baseline
risk is the risk that is there before the disease begins. If we can predict preclinical progression from the
baseline, we don’t need to bother about the disease progression.
In genetic you have this waiting time before final diagnosis. In rare disorders only 26% of the patients get a
diagnosis in less than 3 months. In the case of “super” difficult patients around 19% gets a diagnosis in 5 to
20 years. The number of doctors that are consulted goes up if you have a disease that cannot be diagnosed.
With genetics it is easier to get a diagnosis, so, in this case you only have to see 1 or 2 doctors.
Genomics is all hereditary information of a complete organism.
Milestones in genomics
- 1940 discovery of haploid genome by Hans Winkler
- 1977 discovery of Sanger sequencing by Walter Gilbert and Fedrick Sanger
- 1983 discovery of the PCR by Kary Mullis
- 1986 discovery of the automated sequencer by Leroy Hood
Readable “sanger sequence that is not on a gel, were you can better distinguish the A, T, C and G.
- 1991 discovery of expressed sequence tags (ESTs à little pieces of RNA) by J. Craig Venter
Why do you think that small pieces of RNA are important?
|-| = exome
Purple = little pieces of DNA that define the
gene
They are important because they define
the genes by doing expressed sequence
tags.
- 1996 discovery of the whole genome of the yeast
- 1998 discovery of the whole genome of the worm
- 1999 discovery of the whole genome of the fruit fly
- 2000 discovery of the whole genome of the human
- 2002 discovery of the whole genome of the mouse
All of these discoveries are technology driven (very important)
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The main learning outcome of the course: After this course, you can use genome information to predict,
diagnose, make a prognosis, and suggest treatment options and measure for disease prevention, in an
individual patient.
- Infer the effects of genome variations on human disease
i. Describe the different types of genetic variation by using the correct terminology (LC 2)
ii. Describe the causes of spontaneous and environmental-induced genomic variation
iii. Infer the Mendelian inheritance pattern of a disease based upon family anamnesis and
calculate the recurrence risk (LC 4)
iv. Extract genome variation data from genome browsers and use this information to predict
the effect of SNVs, indel, and repeat expansions, on RNA and protein level (LC 1, SSA1)
v. Choose an animal to model a human disease based in disease-, and animal-specific
characteristics
vi. Describe the effect of chromosomal abnormalities, CNVs, and imprinting on disease (LC 1,
SSA1, CP1)
vii. Describe the molecular and cellular basis of trinucleotide expansion, mosaicism, and
heteroplasmy, and explain the consequences of these three processes for a patients and
her/his family (LC 7, 8)
viii. Predict for a disease which developmental step from mitotic division to birth is involved in
the occurrence of transmission ration distortion
- Describe the strengths and weaknesses of the different techniques to study the human genome
and can apply these techniques according to the specific research question at hand
i. Choose the right disease-gene identification strategy to find the genetic defect in a patient
with a monogenic disorder (LC 5)
ii. Select the most efficient techniques to determine genome-wide and local mutations
iii. Interpret data generated by DNA techniques in the content of human disease
iv. Describe the potential and limitations of invasive and non-invasive methods for prenatal
diagnosis
- Predict the effect of genetic factors on the efficacy of medication
i. Discuss the contribution if the different aspects of a valid pharmacogenic test
ii. Argue whether a drug dose should be adjusted based upon a specific genetic variant
iii. Indicate for a disease whether it would be a target for mutagenic chain reaction (MCR)
- Describe the complex interaction between heritability and environment resulting in common
multifactorial disease (report; 20%)
i. Explain the influence of genetic variation on a multifactorial disease by using the liability.
Threshold model
ii. Calculate odds ratios for genetic variants and use
these to predict the predisposition of a disease
- Write an argumentative, well-organized, concise report using
original research data (report; 20%)
Example question 1: Which mode of inheritance is most likely in the
pedigree?
Autosomal dominant, can skip a generation because of e.g. late onset
of disease.
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Example question 2: Cystic fibrosis (CF) is an autosomal recessive trait
caused by mutation in CFTR. A healthy couple has two children. The first
child has CF, and the second child is unaffected. What is the probability
that the second child is a carrier of a pathogenic mutation?
Summary LC 1.2: Genome Architecture
The cell
- DNA in the nucleus
- DNA in the mitochondria
The nucleus has 22 pairs of chromosomes, 2 sex chromosomes (XX of XY) and ± 20.000 proteins coding
genes.
To select a proper model system if you have a deletion in one chromosome of the human the model system
has to have the same deletion in the same chromosome (comes later in the course).
Why is exome difficult to sequence? It is because it has a high G-C content.
Components of the human genome
- 1.5% are protein coding genes (these contains most mutation)
- 25.9% are the intron
- 11.6% are Miscellaneous unique sequences Functional
- 8% are miscellaneous heterochromatin
- 5% are segmental duplications
- 3% are simple sequence repeats
- 2.9% are DNA transposons
- 8.3% are LTR retrotransposons
Junk
- 13.1% are SINEs
- 20.4% are LINEs
Functional DNA
- Protein coding genes
- Non-coding genes
i. LncdRNAs
ii. siRNA and miRNA
iii. piRNAs (only expressed during the development of germ cells because they are involved in
the control of transposon germ pitch) NOT IMPORTANT
- Regulatory elements
Genes have a promotor region that is at the
beginning of the gene. Then we have an exon which
contains the 5’ UTR region (G-C rich). We have
introns and at the end we have a 3’UTR region.
Human genome working graph is basically a visualization of the human genome.
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Small ncRNA: mechanism of action (noncoding)
We have a small RNA locus that undergoes translation
and processing. What we see then is that from a piece of
DNA we get some of these precursors (miRNA, esiRNA
and piRNA), they can be a hairpin or dsRNA. They all
undergo dicer-dependent processing to get formation of
RISK complex. Ultimately you will get a lot of proteins that
are involved in regulating the coding genes of the
genome. The RISK complex can inhibit translation of
initiation where ribosomal RNA cannot bind to your
mRNA. It can inhibit the translation of elongation (still an
unknown process) and it can inhibit the mRNA
deadenylation (most common). The RISK complex eats up
the polyA-tail, making mRNA vulnerable for degradation.
Feingold syndrome 2 is a disease caused by a miR-17~92
deletion. It is a skeletal dysplasia. It is the only disease
until know that is caused by a miRNA mutation/deletion.
Long non-coding RNA (lncRNA) types:
- Intronic lncRNA
- Intragenic lncRNA
- Natural antisense transcript (NATs)
In general, this non-coding RNA can protein bind and do some repression (bring protein to certain position),
DNA binding, RNA binding, miRNA binding. It can function as a scaffold.
NATs: mechanism of action
If you have DNA polymerase present at DNA level this
will automatically do its job. It is not logical to also start
another DNA polymerase from the antisense side
because these will clash in the middle. Thus, the NAT,
prevents this antisense transcription. Regulatory way
of looking at natural antisense transcripts. The NATs
can also influence splicing, because they are
complementary and regulatory. If these NATs binds to
exome 3, then we see that we only get exome 1 and 2
attach to one another. Because of binding with NATs,
you can also get RNA editing to get nuclear retention of chromatin remodeling and subsequently inhibition
of gene expression.
Regulatory sequences
A promotor (<1 kb) and contains a core promotor and
proximal promotor elements, this is what mainly
influences the genes regulation. You also have the
distal regulatory elements which consists of the locus
control region, the insulators, the silencer and the
enhancer. Taken together they regulate the gene
expression. The core promotor consists of different
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