Yingleong Chan

Distribution and Medical Impact of Loss-of-Function Variants in the Finnish Founder Population.

Exome sequencing studies in complex diseases are challenged by the allelic heterogeneity, large number and modest effect sizes of associated variants on disease risk and the presence of large numbers of neutral variants, even in phenotypically relevant genes. Isolated populations with recent bottlenecks offer advantages for studying rare variants in complex diseases as they have deleterious variants that are present at higher frequencies as well as a substantial reduction in rare neutral variation. To explore the potential of the Finnish founder population for studying low-frequency (0.5–5%) variants in complex diseases, we compared exome sequence data on 3,000 Finns to the same number of non-Finnish Europeans and discovered that, despite having fewer variable sites overall, the average Finn has more low-frequency loss-of-function variants and complete gene knockouts. We then used several well-characterized Finnish population cohorts to study the phenotypic effects of 83 enriched loss-of-function variants across 60 phenotypes in 36,262 Finns. Using a deep set of quantitative traits collected on these cohorts, we show 5 associations (p<5×10−8) including splice variants in LPA that lowered plasma lipoprotein(a) levels (P = 1.5×10−117). Through accessing the national medical records of these participants, we evaluate the LPA finding via Mendelian randomization and confirm that these splice variants confer protection from cardiovascular disease (OR = 0.84, P = 3×10−4), demonstrating for the first time the correlation between very low levels of LPA in humans with potential therapeutic implications for cardiovascular diseases. More generally, this study articulates substantial advantages for studying the role of rare variation in complex phenotypes in founder populations like the Finns and by combining a unique population genetic history with data from large population cohorts and centralized research access to National Health Registers.

Synthesizing genome-wide association studies and expression microarray reveals novel genes that act in the human growth plate to modulate height

Previous meta-analysis of genome-wide association (GWA) studies has identified 180 loci that influence adult height. However, each GWA locus typically comprises a set of contiguous genes, only one of which presumably modulates height. We reasoned that many of the causative genes within these loci influence height because they are expressed in and function in the growth plate, a cartilaginous structure that causes bone elongation and thus determines stature. Therefore, we used expression microarray studies of mouse and rat growth plate, human disease databases and a mouse knockout phenotype database to identify genes within the GWAS loci that are likely required for normal growth plate function. Each of these approaches identified significantly more genes within the GWA height loci than at random genomic locations (P < 0.0001 each), supporting the validity of the approach. The combined analysis strongly implicates 78 genes in growth plate function, including multiple genes that participate in PTHrP-IHH, BMP and CNP signaling, and many genes that have not previously been implicated in the growth plate. Thus, this analysis reveals a large number of novel genes that regulate human growth plate chondrogenesis and thereby contribute to the normal variations in human adult height. The analytic approach developed for this study may be applied to GWA studies for other common polygenic traits and diseases, thus providing a new general strategy to identify causative genes within GWA loci and to translate genetic associations into mechanistic biological insights.

Common Variants Show Predicted Polygenic Effects on Height in the Tails of the Distribution, Except in Extremely Short Individuals

Common genetic variants have been shown to explain a fraction of the inherited variation for many common diseases and quantitative traits, including height, a classic polygenic trait. The extent to which common variation determines the phenotype of highly heritable traits such as height is uncertain, as is the extent to which common variation is relevant to individuals with more extreme phenotypes. To address these questions, we studied 1,214 individuals from the top and bottom extremes of the height distribution (tallest and shortest ∼1.5%), drawn from ∼78,000 individuals from the HUNT and FINRISK cohorts. We found that common variants still influence height at the extremes of the distribution: common variants (49/141) were nominally associated with height in the expected direction more often than is expected by chance (p<5×10−28), and the odds ratios in the extreme samples were consistent with the effects estimated previously in population-based data. To examine more closely whether the common variants have the expected effects, we calculated a weighted allele score (WAS), which is a weighted prediction of height for each individual based on the previously estimated effect sizes of the common variants in the overall population. The average WAS is consistent with expectation in the tall individuals, but was not as extreme as expected in the shortest individuals (p<0.006), indicating that some of the short stature is explained by factors other than common genetic variation. The discrepancy was more pronounced (p<10−6) in the most extreme individuals (height<0.25 percentile). The results at the extreme short tails are consistent with a large number of models incorporating either rare genetic non-additive or rare non-genetic factors that decrease height. We conclude that common genetic variants are associated with height at the extremes as well as across the population, but that additional factors become more prominent at the shorter extreme.

Rates, distribution and implications of postzygotic mosaic mutations in autism spectrum disorder

We systematically analyzed postzygotic mutations (PZMs) in whole-exome sequences from the largest collection of trios (5,947) with autism spectrum disorder (ASD) available, including 282 unpublished trios, and performed resequencing using multiple independent technologies. We identified 7.5% of de novo mutations as PZMs, 83.3% of which were not described in previous studies. Damaging, nonsynonymous PZMs within critical exons of prenatally expressed genes were more common in ASD probands than controls (P < 1 × 10−6), and genes carrying these PZMs were enriched for expression in the amygdala (P = 5.4 × 10−3). Two genes (KLF16 and MSANTD2) were significantly enriched for PZMs genome-wide, and other PZMs involved genes (SCN2A, HNRNPU and SMARCA4) whose mutation is known to cause ASD or other neurodevelopmental disorders. PZMs constitute a significant proportion of de novo mutations and contribute importantly to ASD risk.

An Excess of Risk-Increasing Low-Frequency Variants Can Be a Signal of Polygenic Inheritance in Complex Diseases

In most complex diseases, much of the heritability remains unaccounted for by common variants. It has been postulated that lower-frequency variants contribute to the remaining heritability. Here, we describe a method to test for polygenic inheritance from lower-frequency variants by using GWAS summary association statistics. We explored scenarios with many causal low-frequency variants and showed that there is more power to detect risk variants than to detect protective variants, resulting in an increase in the ratio of detected risk to protective variants (R/P ratio). Such an excess can also occur if risk variants are present and kept at lower frequencies because of negative selection. The R/P ratio can be falsely elevated because of reasons unrelated to polygenic inheritance, such as uneven sample sizes or asymmetric population stratification, so precautions to correct for these confounders are essential. We tested our method on published GWAS results and observed a strong signal in some diseases (schizophrenia and type 2 diabetes) but not others. We also explored the shared genetic component in overlapping phenotypes related to inflammatory bowel disease (Crohn disease [CD] and ulcerative colitis [UC]) and diabetic nephropathy (macroalbuminuria and end-stage renal disease [ESRD]). Although the signal was still present when both CD and UC were jointly analyzed, the signal was lost when macroalbuminuria and ESRD were jointly analyzed, suggesting that these phenotypes should best be studied separately. Thus, our method may also help guide the design of future genetic studies of various traits and diseases.

Genome-wide Analysis of Body Proportion Classifies Height-Associated Variants by Mechanism of Action and Implicates Genes Important for Skeletal Development

Human height is a composite measurement, reflecting the sum of leg, spine, and head lengths. Many common variants influence total height, but the effects of these or other variants on the components of height (body proportion) remain largely unknown. We studied sitting height ratio (SHR), the ratio of sitting height to total height, to identify such effects in 3,545 African Americans and 21,590 individuals of European ancestry. We found that SHR is heritable: 26% and 39% of the total variance of SHR can be explained by common variants in European and African Americans, respectively, and global European admixture is negatively correlated with SHR in African Americans (r(2) ≈ 0.03). Six regions reached genome-wide significance (p < 5 × 10(-8)) for association with SHR and overlapped biological candidate genes, including TBX2 and IGFBP3. We found that 130 of 670 height-associated variants are nominally associated (p < 0.05) with SHR, more than expected by chance (p = 5 × 10(-40)). At these 130 loci, the height-increasing alleles are associated with either a decrease (71 loci) or increase (59 loci) in SHR, suggesting that different height loci disproportionally affect either leg length or spine/head length. Pathway analyses via DEPICT revealed that height loci affecting SHR, and especially those affecting leg length, show enrichment of different biological pathways (e.g., bone/cartilage/growth plate pathways) than do loci with no effect on SHR (e.g., embryonic development). These results highlight the value of using a pair of related but orthogonal phenotypes, in this case SHR with height, as a prism to dissect the biology underlying genetic associations in polygenic traits and diseases.

High-throughput creation and functional profiling of DNA sequence variant libraries using CRISPR–Cas9 in yeast

Construction and characterization of large genetic variant libraries is essential for understanding genome function, but remains challenging. Here, we introduce a Cas9-based approach for generating pools of mutants with defined genetic alterations (deletions, substitutions, and insertions) with an efficiency of 80–100% in yeast, along with methods for tracking their fitness en masse. We demonstrate the utility of our approach by characterizing the DNA helicase SGS1 with small tiling deletion mutants that span the length of the protein and a series of point mutations against highly conserved residues in the protein. In addition, we created a genome-wide library targeting 315 poorly characterized small open reading frames (smORFs, <100 amino acids in length) scattered throughout the yeast genome, and assessed which are vital for growth under various environmental conditions. Our strategy allows fundamental biological questions to be investigated in a high-throughput manner with precision.

An enhanced CRISPR repressor for targeted mammalian gene regulation

The RNA-guided endonuclease Cas9 can be converted into a programmable transcriptional repressor, but inefficiencies in target-gene silencing have limited its utility. Here we describe an improved Cas9 repressor based on the C-terminal fusion of a rationally designed bipartite repressor domain, KRAB–MeCP2, to nuclease-dead Cas9. We demonstrate the system’s superiority in silencing coding and noncoding genes, simultaneously repressing a series of target genes, improving the results of single and dual guide RNA library screens, and enabling new architectures of synthetic genetic circuits.The fusion of dead Cas9 with KRAB and the transcriptional repressor domain of the chromatin modifier MeCP2 leads to an efficient transcriptional silencer that can be applied to genome-scale screens and genetic circuits.

High-throughput creation and functional profiling of eukaryotic DNA sequence variant libraries using CRISPR/Cas9

Construction of genetic variant libraries with phenotypic measurement is central to advancing today’s functional genomics, and remains a grand challenge. Here, we introduce a Cas9-based approach for generating pools of mutants with defined genetic alterations (deletions, substitutions and insertions), along with methods for tracking their fitness en masse. We demonstrate the utility of our approach in performing focused analysis of hundreds of mutants of a single protein and in investigating the biological function of an entire family of poorly characterized genetic elements. Our platform allows fundamental biology questions to be investigated in a quick, easy and affordable manner.

An unbiased index to quantify participant’s phenotypic contribution to an open-access cohort

The Personal Genome Project (PGP) is an effort to enroll many participants to create an open-access repository of genome, health and trait data for research. However, PGP participants are not enrolled for studying any specific traits and participants choose the phenotypes to disclose. To measure the extent and willingness and to encourage and guide participants to contribute phenotypes, we developed an algorithm to score and rank the phenotypes and participants of the PGP. The scoring algorithm calculates the participation index (P-index) for every participant, where 0 indicates no reported phenotypes and 100 indicate complete phenotype reporting. We calculated the P-index for all 5,015 participants in the PGP and they ranged from 0 to 96.7. We found that participants mainly have either high scores (P-index > 90, 29.5%) or low scores (P-index < 10, 57.8%). While, there are significantly more males than female participants (1,793 versus 1,271), females tend to have on average higher P-indexes (P = 0.015). We also reported the P-indexes of participants based on demographics and states like Missouri and Massachusetts have better P-indexes than states like Utah and Minnesota. The P-index can therefore be used as an unbiased way to measure and rank participant’s phenotypic contribution towards the PGP.