Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1–4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (giving an increase of 1–2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.

Background: DNA methylation is an epigenetic modification that plays an important role during mammalian development. Around birth in humans, the main site of red blood cell production moves from the fetal liver to the bone marrow. DNA methylation changes at the β-globin locus and a switch from fetal to adult hemoglobin production characterize this transition. Understanding this globin switch may improve the treatment of patients with sickle cell disease and β-thalassemia, two of the most common Mendelian diseases in the world. The goal of our study was to describe and compare the genome-wide patterns of DNA methylation in fetal and adult human erythroblasts. Methods: We used the Illumina HumanMethylation 450 k BeadChip to measure DNA methylation at 402,819 CpGs in ex vivo-differentiated erythroblasts from 12 fetal liver and 12 bone marrow CD34+ donors. Results: We identified 5,937 differentially methylated CpGs that overlap with erythroid enhancers and binding sites for erythropoiesis-related transcription factors. Combining this information with genome-wide association study results, we show that erythroid enhancers define particularly promising genomic regions to identify new genetic variants associated with fetal hemoglobin (HbF) levels in humans. Many differentially methylated CpGs are located near genes with unanticipated roles in red blood cell differentiation and proliferation. For some of these new candidate genes, we confirm the correlation between DNA methylation and gene expression levels in red blood cell progenitors. We also provide evidence that DNA methylation and genetic variation at the β-globin locus independently control globin gene expression in adult erythroblasts. Conclusions: Our DNA methylome maps confirm the widespread dynamic changes in DNA methylation that occur during human erythropoiesis. These changes tend to happen near erythroid enhancers, further highlighting their importance in erythroid regulation and HbF production. Finally, DNA methylation may act independently of the transcription factor BCL11A to repress fetal hemoglobin production. This provides cues on strategies to more efficiently re-activate HbF production in sickle cell disease and β-thalassemia patients.

Genome-wide association studies (GWASs) have successfully uncovered thousands of robust associations between common variants and complex traits and diseases. Despite these successes, much of the heritability of these traits remains unexplained. Because low-frequency and rare variants are not tagged by conventional genome-wide genotyping arrays, they may represent an important and understudied component of complex trait genetics. In contrast to common variant GWASs, there are many different types of study designs, assays and analytic techniques that can be utilized for rare variant association studies (RVASs). In this review, we briefly present the different technologies available to identify rare genetic variants, including novel exome arrays. We also compare the different study designs for RVASs and argue that the best design will likely be phenotype-dependent. We discuss the main analytical issues relevant to RVASs, including the different statistical methods that can be used to test genetic associations with rare variants and the various bioinformatic approaches to predicting in silico biological functions for variants. Finally, we describe recent rare variant association findings, highlighting the unexpected conclusion that most rare variants have modest-to-small effect sizes on phenotypic variation. This observation has major implications for our understanding of the genetic architecture of complex traits in the context of the unexplained heritability challenge.

Guillaume Lettre, Alexander Reiner, George Diaz and colleagues use an exome array to identify rare and low-frequency coding variants influencing hematological traits. They find several missense variants in CXCR2 associated with reduced white blood cell counts, and, in a separate family-based study, they identify a homozygous CXCR2 frameshift mutation in two siblings with congenital neutropenia. Hematological traits are important clinical parameters. To test the effects of rare and low-frequency coding variants on hematological traits, we analyzed hemoglobin concentration, hematocrit levels, white blood cell (WBC) counts and platelet counts in 31,340 individuals genotyped on an exome array. We identified several missense variants in CXCR2 associated with reduced WBC count (gene-based P = 2.6 × 10−13). In a separate family-based resequencing study, we identified a CXCR2 frameshift mutation in a pedigree with congenital neutropenia that abolished ligand-induced CXCR2 signal transduction and chemotaxis. We also identified missense or splice-site variants in key hematopoiesis regulators (EPO, TFR2, HBB, TUBB1 and SH2B3) associated with blood cell traits. Finally, we were able to detect associations between a rare somatic JAK2 mutation (encoding p.Val617Phe) and platelet count (P = 3.9 × 10−22) as well as hemoglobin concentration (P = 0.002), hematocrit levels (P = 9.5 × 10−7) and WBC count (P = 3.1 × 10−5). In conclusion, exome arrays complement genome-wide association studies in identifying new variants that contribute to complex human traits.