315 research outputs found
Characterising and Predicting Haploinsufficiency in the Human Genome
No full textNi Huang is with the Wellcome Trust Sanger Institute, Insuk Lee is with UT Austin and Yonsei University, Edward M. Marcotte is with UT Austin, Matthew E. Hurles is with the Wellcome Trust Sanger Institute.Haploinsufficiency, wherein a single functional copy of a gene is insufficient to maintain normal function, is a major cause of dominant disease. Human disease studies have identified several hundred haploinsufficient (HI) genes. We have compiled a map of 1,079 haplosufficient (HS) genes by systematic identification of genes unambiguously and repeatedly compromised by copy number variation among 8,458 apparently healthy individuals and contrasted the genomic, evolutionary, functional, and network properties between these HS genes and known HI genes. We found that HI genes are typically longer and have more conserved coding sequences and promoters than HS genes. HI genes exhibit higher levels of expression during early development and greater tissue specificity. Moreover, within a probabilistic human functional interaction network HI genes have more interaction partners and greater network proximity to other known HI genes. We built a predictive model on the basis of these differences and annotated 12,443 genes with their predicted probability of being haploinsufficient. We validated these predictions of haploinsufficiency by demonstrating that genes with a high predicted probability of exhibiting haploinsufficiency are enriched among genes implicated in human dominant diseases and among genes causing abnormal phenotypes in heterozygous knockout mice. We have transformed these gene-based haploinsufficiency predictions into haploinsufficiency scores for genic deletions, which we demonstrate to better discriminate between pathogenic and benign deletions than consideration of the deletion size or numbers of genes deleted. These robust predictions of haploinsufficiency support clinical interpretation of novel loss-of-function variants and prioritization of variants and genes for follow-up studies.NH and MEH are funded by the Wellcome Trust [grant number 077014/Z/05/Z]. IL is funded by grants from the National Research Foundation of Korea (NRF) funded by the Korea government (MEST) (No. 2010-0017649, 2010-0015754, 2009-0087951) and EMM by the NIH, Welch (F-1515), and Packard Foundations, by the Texas Institute for Drug and Diagnostic Development, and by the Texas Advanced Research Program. This study makes use of data provided by the Genetic Association Information Network (GAIN) and the Wellcome Trust Case Control Consortium 2 (WTCCC2), through work funded by NIH and the Wellcome Trust. This study also makes use of data generated by the DECIPHER consortium, which is funded by the Wellcome Trust. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Cellular and Molecular Biolog
Data analysis methods for copy number discovery and interpretation
No full textCopy
number
variation
(CNV)
is
an
important
type
of
genetic
variation
that
can
give
rise
to
a
wide
variety
of
phenotypic
traits.
Differences
in
copy
number
are
thought
to
play
major
roles
in
processes
that
involve
dosage
sensitive
genes,
providing
beneficial,
deleterious
or
neutral
modifications
to
individual
phenotypes.
Copy
number
analysis
has
long
been
a
standard
in
clinical
cytogenetic
laboratories.
Gene
deletions
and
duplications
can
often
be
linked
with
genetic
Syndromes
such
as:
the
7q11.23
deletion
of
Williams-‐Bueren
Syndrome,
the
22q11
deletion
of
DiGeorge
syndrome
and
the
17q11.2
duplication
of
Potocki-‐Lupski
syndrome.
Interestingly,
copy
number
based
genomic
disorders
often
display
reciprocal
deletion
/
duplication
syndromes,
with
the
latter
frequently
exhibiting
milder
symptoms.
Moreover,
the
study
of
chromosomal
imbalances
plays
a
key
role
in
cancer
research.
The
datasets
used
for
the
development
of
analysis
methods
during
this
project
are
generated
as
part
of
the
cutting-‐edge
translational
project,
Deciphering
Developmental
Disorders
(DDD).
This
project,
the
DDD,
is
the
first
of
its
kind
and
will
directly
apply
state
of
the
art
technologies,
in
the
form
of
ultra-‐high
resolution
microarray
and
next
generation
sequencing
(NGS),
to
real-‐time
genetic
clinical
practice.
It
is
collaboration
between
the
Wellcome
Trust
Sanger
Institute
(WTSI)
and
the
National
Health
Service
(NHS)
involving
the
24
regional
genetic
services
across
the
UK
and
Ireland.
Although
the
application
of
DNA
microarrays
for
the
detection
of
CNVs
is
well
established,
individual
change
point
detection
algorithms
often
display
variable
performances.
The
definition
of
an
optimal
set
of
parameters
for
achieving
a
certain
level
of
performance
is
rarely
straightforward,
especially
where
data
qualities
vary ... [cont.]
Gene conversion homogenizes the CMT1A paralogous repeats
No full textAbstract Background Non-allelic homologous recombination between paralogous repeats is increasingly being recognized as a major mechanism causing both pathogenic microdeletions and duplications, and structural polymorphism in the human genome. It has recently been shown empirically that gene conversion can homogenize such repeats, resulting in longer stretches of absolute identity that may increase the rate of non-allelic homologous recombination. Results Here, a statistical test to detect gene conversion between pairs of non-coding sequences is presented. It is shown that the 24 kb Charcot-Marie-Tooth type 1A paralogous repeats (CMT1A-REPs) exhibit the imprint of gene conversion processes whilst control orthologous sequences do not. In addition, Monte Carlo simulations of the evolutionary divergence of the CMT1A-REPs, incorporating two alternative models for gene conversion, generate repeats that are statistically indistinguishable from the observed repeats. Bounds are placed on the rate of these conversion processes, with central values of 1.3 × 10-4 and 5.1 × 10-5 per generation for the alternative models. Conclusions This evidence presented here suggests that gene conversion may have played an important role in the evolution of the CMT1A-REP paralogous repeats. The rates of these processes are such that it is probable that homogenized CMT1A-REPs are polymorphic within modern populations. Gene conversion processes are similarly likely to play an important role in the evolution of other segmental duplications and may influence the rate of non-allelic homologous recombination between them.</p
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Modeling Rare Protein-Coding Variation to Identify Mutation-Intolerant Genes With Application to Disease
No full textSequencing exomes—the 1% of the genome that codes for proteins—has increased the rate at which the genetic basis of a patient’s disease is determined. Unfortunately, when a patient does not carry a well-established pathogenic variant, it is extremely challenging to establish which of the tens of thousands of variants identified in that individual is contributing to their disease. In these situations, variants must be prioritized to make further investigation more manageable. In this thesis, we have focused on creating statistical frameworks and models to aid in the interpretation of rare variants and towards establishing gene-level metrics for variant prioritization.
We developed a sensitive and specific workflow to detect newly arising (de novo) variants from exome sequencing data of parent-child trios, and created a sequence-context based mutational. This mutational model was the basis of a rigorous statistical framework to evaluate the significance of de novo variant burden not only globally, but also per gene. When we applied this framework to de novo variants identified in patients with an autism spectrum disorder, we found a global excess of de novo loss-of-function variants as well as two genes that harbored significantly more de novo loss-of-function variants than expected.
We also used the mutational model to predict the expected number of rare (minor allele frequency < 0.1%) variants in exome sequencing datasets of reference individuals. We found a significant depletion of missense and loss-of-function variants in a subset of genes, indicating that these genes are under strong evolutionary constraint. Specifically, we identified 3,230 genes that are intolerant of loss-of-function variation and that set of genes is enriched for established dominant and haploinsufficient disease genes. Similarly, we searched for regions within genes that were intolerant of missense variation. The most missense depleted 15% of the exome contains 83% of reported pathogenic variants found in haploinsufficient disease genes that cause severe disease. Additionally, both gene-level and region-level constraint metrics highlight a set of de novo variants from patients with a neurodevelopmental disorder that are more likely to be pathogenic, supporting the utility of these metrics when interpreting rare variants within the context of disease.Medical SciencesMedical Sciencesgenomics; exome; sequencing; mutation; de novo; autism; constrain
Contribution of retrotransposition to developmental disorders
No full textMobile genetic Elements (MEs) are segments of DNA which can copy themselves and other transcribed sequences through the process of retrotransposition (RT). In humans several disorders have been attributed to RT, but the role of RT in severe developmental disorders (DD) has not yet been explored. Here we identify RT-derived events in 9738 exome sequenced trios with DD-affected probands. We ascertain 9 de novo MEs, 4 of which are likely causative of the patient’s symptoms (0.04%), as well as 2 de novo gene retroduplications. Beyond identifying likely diagnostic RT events, we estimate genome-wide germline ME mutation rate and selective constraint and demonstrate that coding RT events have signatures of purifying selection equivalent to those of truncating mutations. Overall, our analysis represents a comprehensive interrogation of the impact of retrotransposition on protein coding genes and a framework for future evolutionary and disease studies.</p
High-throughput haplotype determination over long distances by haplotype fusion PCR and ligation haplotyping
No full text
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