Evidence of widespread selection on standing variation in Europe at height-associated SNPs.

Strong signatures of positive selection at newly arising genetic variants are well documented in humans(1-8), but this form of selection may not be widespread in recent human evolution(9). Because many human traits are highly polygenic and partly determined by common, ancient genetic variation, an alternative model for rapid genetic adaptation has been proposed: weak selection acting on many pre-existing (standing) genetic variants, or polygenic adaptation(10-12). By studying height, a classic polygenic trait, we demonstrate the first human signature of widespread selection on standing variation. We show that frequencies of alleles associated with increased height, both at known loci and genome wide, are systematically elevated in Northern Europeans compared with Southern Europeans (P < 4.3 × 10(-4)). This pattern mirrors intra-European height differences and is not confounded by ancestry or other ascertainment biases. The systematic frequency differences are consistent with the presence of widespread weak selection (selection coefficients ∼10(-3)-10(-5) per allele) rather than genetic drift alone (P < 10(-15))

Whole exome sequencing to identify genetic causes of short stature

BACKGROUND/AIMS: Short stature is a common reason for presentation to pediatric endocrinology clinics. However, for most patients, no cause for the short stature can be identified. As genetics plays a strong role in height, we sought to identify known and novel genetic causes of short stature. METHODS: We recruited 14 children with severe short stature of unknown etiology. We conducted whole exome sequencing of the patients and their family members. We used an analysis pipeline to identify rare non-synonymous genetic variants that cause the short stature. RESULTS: We identified a genetic cause of short stature in 5 of the 14 patients. This included cases of floating-harbor syndrome, Kenny-Caffey syndrome, the progeroid form of Ehlers-Danlos syndrome, as well as 2 cases of the 3-M syndrome. For the remaining patients, we have generated lists of candidate variants. CONCLUSIONS: Whole exome sequencing can help identify genetic causes of short stature in the context of defined genetic syndromes, but may be less effective in identifying novel genetic causes of short stature in individual families. Utilized in the clinic, whole exome sequencing can provide clinically relevant diagnoses for these patients. Rare syndromic causes of short stature may be underrecognized and underdiagnosed in pediatric endocrinology clinics

Genetic Signatures of Strong Recent Positive Selection at the Lactase Gene

In most human populations, the ability to digest lactose contained in milk usually disappears in childhood, but in European-derived populations, lactase activity frequently persists into adulthood (Scrimshaw and Murray 1988). It has been suggested (Cavalli-Sforza 1973; Hollox et al. 2001; Enattah et al. 2002; Poulter et al. 2003) that a selective advantage based on additional nutrition from dairy explains these genetically determined population differences (Simoons 1970; Kretchmer 1971; Scrimshaw and Murray 1988; Enattah et al. 2002), but formal population-genetics–based evidence of selection has not yet been provided. To assess the population-genetics evidence for selection, we typed 101 single-nucleotide polymorphisms covering 3.2 Mb around the lactase gene. In northern European–derived populations, two alleles that are tightly associated with lactase persistence (Enattah et al. 2002) uniquely mark a common (∼77%) haplotype that extends largely undisrupted for >1 Mb. We provide two new lines of genetic evidence that this long, common haplotype arose rapidly due to recent selection: (1) by use of the traditional FST measure and a novel test based on pexcess, we demonstrate large frequency differences among populations for the persistence-associated markers and for flanking markers throughout the haplotype, and (2) we show that the haplotype is unusually long, given its high frequency—a hallmark of recent selection. We estimate that strong selection occurred within the past 5,000–10,000 years, consistent with an advantage to lactase persistence in the setting of dairy farming; the signals of selection we observe are among the strongest yet seen for any gene in the genome

Phenotype-genotype association grid: a convenient method for summarizing multiple association analyses

BACKGROUND: High-throughput genotyping generates vast amounts of data for analysis; results can be difficult to summarize succinctly. A single project may involve genotyping many genes with multiple variants per gene and analyzing each variant in relation to numerous phenotypes, using several genetic models and population subgroups. Hundreds of statistical tests may be performed for a single SNP, thereby complicating interpretation of results and inhibiting identification of patterns of association. RESULTS: To facilitate visual display and summary of large numbers of association tests of genetic loci with multiple phenotypes, we developed a Phenotype-Genotype Association (PGA) grid display. A database-backed web server was used to create PGA grids from phenotypic and genotypic data (sample sizes, means and standard errors, P-value for association). HTML pages were generated using Tcl scripts on an AOLserver platform, using an Oracle database, and the ArsDigita Community System web toolkit. The grids are interactive and permit display of summary data for individual cells by a mouse click (i.e. least squares means for a given SNP and phenotype, specified genetic model and study sample). PGA grids can be used to visually summarize results of individual SNP associations, gene-environment associations, or haplotype associations. CONCLUSION: The PGA grid, which permits interactive exploration of large numbers of association test results, can serve as an easily adapted common and useful display format for large-scale genetic studies. Doing so would reduce the problem of publication bias, and would simplify the task of summarizing large-scale association studies

A Genome-Wide Pharmacogenetic Study of Growth Hormone Responsiveness

Individual patients vary in their response to growth hormone (GH). No large-scale genome-wide studies have looked for genetic predictors of GH responsiveness. To identify genetic variants associated with GH responsiveness. Genome-wide association study (GWAS). Cohorts from multiple academic centers and a clinical trial. A total of 614 individuals from 5 short stature cohorts receiving GH: 297 with idiopathic short stature, 276 with isolated GH deficiency, and 65 born small for gestational age. Association of more than 2 million variants was tested. Primary analysis: individual single nucleotide polymorphism (SNP) association with first-year change in height standard deviation scores. Secondary analyses: SNP associations in clinical subgroups adjusted for clinical variables; association of polygenic score calculated from 697 genome-wide significant height SNPs with GH responsiveness. No common variant associations reached genome-wide significance in the primary analysis. The strongest suggestive signals were found near the B4GALT4 and TBCE genes. After meta-analysis including replication data, signals at several loci reached or retained genome-wide significance in secondary analyses, including variants near ST3GAL6. There was no significant association with variants previously reported to be associated with GH response nor with a polygenic predicted height score. We performed the largest GWAS of GH responsiveness to date. We identified 2 loci with a suggestive effect on GH responsiveness in our primary analysis and several genome-wide significant associations in secondary analyses that require further replication. Our results are consistent with a polygenic component to GH responsiveness, likely distinct from the genetic regulators of adult height

A CLK3-HMGA2 Alternative Splicing Axis Impacts Human Hematopoietic Stem Cell Molecular Identity throughout Development

While gene expression dynamics have been extensively cataloged during hematopoietic differentiation in the adult, less is known about transcriptome diversity of human hematopoietic stem cells (HSCs) during development. To characterize transcriptional and post-transcriptional changes in HSCs during development, we leveraged high-throughput genomic approaches to profile miRNAs, lincRNAs, and mRNAs. Our findings indicate that HSCs manifest distinct alternative splicing patterns in key hematopoietic regulators. Detailed analysis of the splicing dynamics and function of one such regulator, HMGA2, identified an alternative isoform that escapes miRNA-mediated targeting. We further identified the splicing kinase CLK3 that, by regulating HMGA2 splicing, preserves HMGA2 function in the setting of an increase in let-7 miRNA levels, delineating how CLK3 and HMGA2 form a functional axis that influences HSC properties during development. Collectively, our study highlights molecular mechanisms by which alternative splicing and miRNA-mediated post-transcriptional regulation impact the molecular identity and stage-specific developmental features of human HSCs. Human hematopoietic stem cells (HSCs) display substantial transcriptional diversity during development. Here, we investigated the contribution of alternative splicing to such diversity by analyzing the dynamics of a key hematopoietic regulator, HMGA2. Next, we showed that CLK3, by regulating the splicing pattern of HMGA2, reinforces an HSC-specific program

The Metabochip, a Custom Genotyping Array for Genetic Studies of Metabolic, Cardiovascular, and Anthropometric Traits

PMCID: PMC3410907This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Comprehensive population-based genome sequencing provides insight into hematopoietic regulatory mechanisms

Genetic variants affecting hematopoiesis can influence commonly measured blood cell traits. To identify factors that affect hematopoiesis, we performed association studies for blood cell traits in the population-based Estonian Biobank using high-coverage whole-genome sequencing (WGS) in 2,284 samples and SNP genotyping in an additional 14,904 samples. Using up to 7,134 samples with available phenotype data, our analyses identified 17 associations across 14 blood cell traits. Integration of WGS-based fine-mapping and complementary epigenomic datasets provided evidence for causal mechanisms at several loci, including at a previously undiscovered basophil count-associated locus near the master hematopoietic transcription factor CEBPA. The fine-mapped variant at this basophil count association near CEBPA overlapped an enhancer active in common myeloid progenitors and influenced its activity. In situ perturbation of this enhancer by CRISPR/Cas9 mutagenesis in hematopoietic stem and progenitor cells demonstrated that it is necessary for and specifically regulates CEBPA expression during basophil differentiation. We additionally identified basophil count-associated variation at another more pleiotropic myeloid enhancer near GATA2, highlighting regulatory mechanisms for ordered expression of master hematopoietic regulators during lineage specification. Our study illustrates how population-based genetic studies can provide key insights into poorly understood cell differentiation processes of considerable physiologic relevance.Peer reviewe