Page 93 - ASHG 2013 Program Guide

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Wednesday, October 23
Concurrent Invited Session I (3-9)
SESSION 8 – Insights from Large Scale Sequencing
Hall B2, Level 0 (Lower Level), Convention Center
Goncalo R. Abecasis, Univ. of Michigan
Sch. of Publ. Hlth.; Gabor Marth, Boston Col.
Large-scale genomic sequencing studies are fueling
rapid advances in many areas of human genetics.
Many of the opportunities (such as our ability to
conveniently access rare and even private variants in
many individuals) and challenges (such as the large
volumes of data that must be managed) are shared
across many areas of application. It is also clear
that different fields have elected to focus on quite
different strategies for data generation, ranging from
deep whole genome sequencing, to deep targeted
sequencing of exomes or even smaller regions, to
shallow whole genome sequencing. Approaches
to data analysis also vary, including both analysis
based on mapping (where interpretation is guided
by the reference genome) and emerging assembly-
based analytical approaches (where interpretation
might eventually become independent of the
reference). In this session, we will compare and
contrast advances in studies of Mendelian disorders,
cancer sequencing, complex trait analysis, genome
informatics and population genetics and discuss how
they are deploying sequencing-based approaches,
examples of success for each area, and challenges
and opportunities for the future. The goal of this set of
presentations is to show how different people can look
at the same interesting, new data and come up with
very different (and valuable) interpretations.
Mechanistic and clinical advances from
sequencing cancer patients.
N. Rahman. Inst. of
Cancer Res., Sutton, U.K.
Accelerating Mendelian genetics.
Nickerson. Univ. of Washington Sch. of Med.
Whole genome mapping, assembly and
H. Li. Broad Inst. of Harvard and MIT.
Population genetic insights from 10,000s
of human samples.
J. Novembre. Univ. of Chicago.
Wednesday, October 23
Concurrent Invited Session I (3-9)
SESSION 9 – Population-Based Animal Models for
Discovery of Complex Traits
Room 258, Level 2, Convention Center
John French, and Kimberly McAllister,
NIEHS/NIH, Research Triangle Park
Understanding human gene by environment
interactions is difficult due to uncontrolled individual
differences in host susceptibility to individual variation
in multiple stressors (chemicals, infections, etc.) over a
lifetime. Appropriate experimental models can be used
to identify morbidity and disease for epidemiology
research or confirm observations from epidemiology
under controlled conditions with multiple variables.
Over the past decade, members of the complex traits
community have led the development of new and
powerful mouse resources for quantitative genetics.
These new mouse populations are designed to model
human genetic diversity with approximately 45 million
segregating SNPs, CNV, and structural variants. The
Collaborative Cross (CC) is a population of advanced
intercross recombinant inbred lines (AIRILs) created
from a randomized eight-way intercross of inbred
strains and subsequently inbred to fix each genetically
diverse genome. Selected generations of breeders
from the CC AIRILs were then used to create the
diversity outbred (DO) mice. The CC AIRILs and the
DO mice are critical tools for mapping and validating
candidate genes identified from QTLs using molecular
biology and reverse genetics approaches. New
research results will be presented in this session
that demonstrate a discovery approach that can
facilitate identification of genetic or epigenetic variants
associated with factors that interact to determine
phenotypic outcome to environmental and genetic
variations at the population level. Experimental and
quantitative genetic approaches will likely enable the
identification of genetic variants that contribute to
differential responses in humans to environmental
exposures and thus corroborate genetic epidemiology
and provide new targets for human investigation.
High-resolution genetic mapping using
the mouse collaborative cross and diversity
outbred populations.
G. Churchill. The Jackson Lab.
Genomic characterization of house
dust mite-induced allergic airway disease in mice.
S. Kelada. Univ. of North Carolina at Chapel Hill.
Host genetics and modulation of the
gut microbiome as a means to understanding
metabolic function.
A. Benson. Univ. of
Mapping susceptibility QTLs for gene-
environment interactions and environmental
J. French. NIEHS/NIH, Research Triangle