Hundreds of variants clustered in genomic loci and biological pathways affect human height

Molecular Characterization and Expression of SPP1, LAP3 and LCORL and Their Association with Growth Traits in Sheep

The SPP1, LAP3, and LCORL are located on chromosome 6 of sheep and a domain of 36.15-38.56 Mb, which plays an essential role in tissue and embryonic growth. In this study, we cloned the complete coding sequences of SPP1 and partial coding regions of LAP3 and LCORL from Hu sheep (Gansu Province, China) and analyzed their genomic structures. The RT-qPCR showed that the three genes were expressed widely in the different tissues of Hu sheep. The SPP1 expression was significantly higher in the kidney (p < 0.01) and LAP3 expression was significantly higher in the spleen, lung, kidney, and duodenum than in the other tissues (heart, liver, rumen, muscle, fat, and ovary; p < 0.05). The LCORL was preferentially expressed in the spleen, duodenum, and lung (p < 0.05). In addition, the nucleotide substitution NM_001009224.1:c.132A>C was found in SPP1; an association analysis showed that it was associated with birth weight and yearling weight (p < 0.05), and NM_001009224.1:c.132C was the dominant allele. Two mutations XM_012179698.3:c.232C>G and XM_012179698.3:c.1154C>T were identified in LAP3. The nucleotide substitution XM_012179698.3:c.232C>G was confirmed to be associated with birth weight, 1-month weight, 3-month weight (p < 0.05), and 2-month weight (p < 0.01). The nucleotide substitution XM_012179698.3:c.1154C>T was associated with birth weight (p < 0.01), 1-month weight, and 2-month weight (p < 0.05). The LAP3 gene XM_012179698.3:c.232C>G mutation with the C allele has higher body weight than other sheep, and CC genotype individuals show higher birth weight, 1-month weight, and weaning weight than the GG genotype individuals (p < 0.05). Our results support the conclusion that the mutations on ovine SPP1 and LAP3 successfully track functional alleles that affect growth in sheep, and these genes could be used as candidate genes for improving the growth traits of sheep during breeding.

Efficient pathway enrichment and network analysis of GWAS summary data using GSA-SNP2

Pathway-based analysis in genome-wide association study (GWAS) is being widely used to uncover novel multi-genic functional associations. Many of these pathway-based methods have been used to test the enrichment of the associated genes in the pathways, but exhibited low powers and were highly affected by free parameters. We present the novel method and software GSA-SNP2 for pathway enrichment analysis of GWAS P-value data. GSA-SNP2 provides high power, decent type I error control and fast computation by incorporating the random set model and SNP-count adjusted gene score. In a comparative study using simulated and real GWAS data, GSA-SNP2 exhibited high power and best prioritized gold standard positive pathways compared with six existing enrichment-based methods and two self-contained methods (alternative pathway analysis approach). Based on these results, the difference between pathway analysis approaches was investigated and the effects of the gene correlation structures on the pathway enrichment analysis were also discussed. In addition, GSA-SNP2 is able to visualize protein interaction networks within and across the significant pathways so that the user can prioritize the core subnetworks for further studies. GSA-SNP2 is freely available at https://sourceforge.net/projects/gsasnp2.

A genome-wide association study identifies genetic loci associated with specific lobar brain volumes

Brain lobar volumes are heritable but genetic studies are limited. We performed genome-wide association studies of frontal, occipital, parietal and temporal lobe volumes in 16,016 individuals, and replicated our findings in 8,789 individuals. We identified six genetic loci associated with specific lobar volumes independent of intracranial volume. Two loci, associated with occipital (6q22.32) and temporal lobe volume (12q14.3), were previously reported to associate with intracranial and hippocampal volume, respectively. We identified four loci previously unknown to affect brain volumes: 3q24 for parietal lobe volume, and 1q22, 4p16.3 and 14q23.1 for occipital lobe volume. The associated variants were located in regions enriched for histone modifications (DAAM1 and THBS3), or close to genes causing Mendelian brain-related diseases (ZIC4 and FGFRL1). No genetic overlap between lobar volumes and neurological or psychiatric diseases was observed. Our findings reveal part of the complex genetics underlying brain development and suggest a role for regulatory regions in determining brain volumes.

Genetic variants in Barrett's esophagus and esophageal adenocarcinoma: a literature review

Surveillance of Barrett's esophagus (BE) is a clinical challenge; metaplasia of the distal esophagus increases a patient's risk of esophageal adenocarcinoma (EAC) significantly but the actual percentage of patients who progress is low. The current screening recommendations require frequent endoscopy and biopsy, which has inherent risk, high cost, and operator variation. Identifying BE patients genetically who are at high risk of progressing could deemphasize the role of endoscopic screening and create an opportunity for early therapeutic intervention. Genetic alterations in germline DNA have been identified in other disease processes and allow for early intervention or surveillance well before disease develops. The genetic component of BE remains mostly unknown and only a few genome-wide association studies exist on this topic. This review summarizes the current literature available that examines genetic alterations in BE and EAC with a particular emphasis on clinical implications.

From genome-wide association studies to Mendelian randomization: novel opportunities for understanding cardiovascular disease causality, pathogenesis, prevention, and treatment

The Mendelian randomization approach is an epidemiological study design incorporating genetic information into traditional epidemiological studies to infer causality of biomarkers, risk factors, or lifestyle factors on disease risk. Mendelian randomization studies often draw on novel information generated in genome-wide association studies on causal associations between genetic variants and a risk factor or lifestyle factor. Such information can then be used in a largely unconfounded study design free of reverse causation to understand if and how risk factors and lifestyle factors cause cardiovascular disease. If causation is demonstrated, an opportunity for prevention of disease is identified; importantly however, before prevention or treatment can be implemented, randomized intervention trials altering risk factor levels or improving deleterious lifestyle factors needs to document reductions in cardiovascular disease in a safe and side-effect sparse manner. Documentation of causality can also inform on potential drug targets, more likely to be successful than prior approaches often relying on animal or cell studies mainly. The present review summarizes the history and background of Mendelian randomization, the study design, assumptions for using the design, and the most common caveats, followed by a discussion on advantages and disadvantages of different types of Mendelian randomization studies using one or more samples and different levels of information on study participants. The review also provides an overview of results on many of the risk factors and lifestyle factors for cardiovascular disease examined to date using the Mendelian randomization study design.

Chromatin accessibility and the regulatory epigenome

Physical access to DNA is a highly dynamic property of chromatin that plays an essential role in establishing and maintaining cellular identity. The organization of accessible chromatin across the genome reflects a network of permissible physical interactions through which enhancers, promoters, insulators and chromatin-binding factors cooperatively regulate gene expression. This landscape of accessibility changes dynamically in response to both external stimuli and developmental cues, and emerging evidence suggests that homeostatic maintenance of accessibility is itself dynamically regulated through a competitive interplay between chromatin-binding factors and nucleosomes. In this Review, we examine how the accessible genome is measured and explore the role of transcription factors in initiating accessibility remodelling; our goal is to illustrate how chromatin accessibility defines regulatory elements within the genome and how these epigenetic features are dynamically established to control gene expression.

Analysis of the genetic basis of height in large Jewish nuclear families

Despite intensive study, most of the specific genetic factors that contribute to variation in human height remain undiscovered. We conducted a family-based linkage study of height in a unique cohort of very large nuclear families from a founder (Jewish) population. This design allowed for increased power to detect linkage, compared to previous family-based studies. Loci we identified in discovery families could explain an estimated lower bound of 6% of the variance in height in validation families. We showed that these loci are not tagging known common variants associated with height. Rather, we suggest that the observed signals arise from variants with large effects that are rare globally but elevated in frequency in the Jewish population.

Rare variants with large effects have been suggested to account for some of the missing heritability of height, but detection of such variants in genome-wide association studies (GWAS) requires very large sample sizes due to their low frequencies. Here, we designed a unique study of height, in which we sought to increase the effective frequency of rare variants in our sample. This was done by assembling a cohort of very large nuclear families, with an average of 12 and a maximum of 20 siblings per nuclear family. In this design, any variant segregating in our cohort has a minimum expected frequency of ~1%, regardless of its frequency in the general population. In addition, we recruited all participants from a founder (Jewish) population, in which some variants that are rare in a cosmopolitan population can rise to high frequencies. To further increase power, we developed methods to obtain highly accurate height measurements, genotype calls, and inheritance pattern reconstructions. These factors allowed us to detect many more QTLs than previous family-based studies of height, despite a modest sample size of only 397 participants. The approach described in this paper provides insights into the genetic basis of height and the roles of population-specific vs. cosmopolitan variants, and may serve as a complement to GWAS for genetic investigations of other complex traits.

Mendelian randomisation study of height and body mass index as modifiers of ovarian cancer risk in 22,588 BRCA1 and BRCA2 mutation carriers

BACKGROUND

Height and body mass index (BMI) are associated with higher ovarian cancer risk in the general population, but whether such associations exist among BRCA1/2 mutation carriers is unknown.

METHODS

We applied a Mendelian randomisation approach to examine height/BMI with ovarian cancer risk using the Consortium of Investigators for the Modifiers of BRCA1/2 (CIMBA) data set, comprising 14,676 BRCA1 and 7912 BRCA2 mutation carriers, with 2923 ovarian cancer cases. We created a height genetic score (height-GS) using 586 height-associated variants and a BMI genetic score (BMI-GS) using 93 BMI-associated variants. Associations were assessed using weighted Cox models.

RESULTS

Observed height was not associated with ovarian cancer risk (hazard ratio [HR]: 1.07 per 10-cm increase in height, 95% confidence interval [CI]: 0.94-1.23). Height-GS showed similar results (HR = 1.02, 95% CI: 0.85-1.23). Higher BMI was significantly associated with increased risk in premenopausal women with HR = 1.25 (95% CI: 1.06-1.48) and HR = 1.59 (95% CI: 1.08-2.33) per 5-kg/m2 increase in observed and genetically determined BMI, respectively. No association was found for postmenopausal women. Interaction between menopausal status and BMI was significant (Pinteraction < 0.05).

CONCLUSION

Our observation of a positive association between BMI and ovarian cancer risk in premenopausal BRCA1/2 mutation carriers is consistent with findings in the general population.

Dog10K: an international sequencing effort to advance studies of canine domestication, phenotypes and health

Dogs are the most phenotypically diverse mammalian species, and they possess more known heritable disorders than any other non-human mammal. Efforts to catalog and characterize genetic variation across well-chosen populations of canines are necessary to advance our understanding of their evolutionary history and genetic architecture. To date, no organized effort has been undertaken to sequence the world's canid populations. The Dog10K Consortium (http://www.dog10kgenomes.org) is an international collaboration of researchers from across the globe who will generate 20× whole genomes from 10 000 canids in 5 years. This effort will capture the genetic diversity that underlies the phenotypic and geographical variability of modern canids worldwide. Breeds, village dogs, niche populations and extended pedigrees are currently being sequenced, and de novo assemblies of multiple canids are being constructed. This unprecedented dataset will address the genetic underpinnings of domestication, breed formation, aging, behavior and morphological variation. More generally, this effort will advance our understanding of human and canine health.

Correlations between relatives: From Mendelian theory to complete genome sequence

It is 100 years since R. A. Fisher proposed that a Mendelian model of genetic variant effects, additive over loci, could explain the patterns of observed phenotypic correlations between relatives. His loci were hypothetical and his model theoretical. It is only about 50 years since the first genetic markers allowed the detection of even variants with major effects on phenotype, and only 20 years since the development of single-nucleotide polymorphism technology provided dense markers over the genome. Then both mappings in defined pedigrees and population-based genome-wide association studies samples allowed the detection of multiple contributing variants of smaller effect. Finally, with methods based on genotypic correlations between individuals, or on allelic associations between loci, the additive heritability contributions of the genome can be estimated from large population samples. In this review we trace, from 1918 to 2018, the analysis of observed phenotypic correlations between relatives to estimate underlying genetic components of traits in human populations. As with studies from 1918 onward, we use height as the example trait where not only data are readily available, but where Fisher's model of large numbers of variants of infinitesimal effect appears to provide a good approximation to reality. However, we also trace the use of phenotypic and genotypic correlations between relatives in mapping causal variants and resolving genetic contributions to more complex human traits. With the availability of DNA sequence data, we can hope to not only estimate the total genetic contribution to a trait, but to resolve effects of individual genetic variants on biological function.

Meta-Analysis of Genomewide Association Studies Reveals Genetic Variants for Hip Bone Geometry

Hip geometry is an important predictor of fracture. We performed a meta-analysis of GWAS studies in adults to identify genetic variants that are associated with proximal femur geometry phenotypes. We analyzed four phenotypes: (i) femoral neck length; (ii) neck-shaft angle; (iii) femoral neck width, and (iv) femoral neck section modulus, estimated from DXA scans using algorithms of hip structure analysis. In the Discovery stage, 10 cohort studies were included in the fixed-effect meta-analysis, with up to 18,719 men and women ages 16 to 93 years. Association analyses were performed with ∼2.5 million polymorphisms under an additive model adjusted for age, body mass index, and height. Replication analyses of meta-GWAS significant loci (at adjusted genomewide significance [GWS], threshold p ≤ 2.6 × 10-8 ) were performed in seven additional cohorts in silico. We looked up SNPs associated in our analysis, for association with height, bone mineral density (BMD), and fracture. In meta-analysis (combined Discovery and Replication stages), GWS associations were found at 5p15 (IRX1 and ADAMTS16); 5q35 near FGFR4; at 12p11 (in CCDC91); 11q13 (near LRP5 and PPP6R3 (rs7102273)). Several hip geometry signals overlapped with BMD, including LRP5 (chr. 11). Chr. 11 SNP rs7102273 was associated with any-type fracture (p = 7.5 × 10-5 ). We used bone transcriptome data and discovered several significant eQTLs, including rs7102273 and PPP6R3 expression (p = 0.0007), and rs6556301 (intergenic, chr.5 near FGFR4) and PDLIM7 expression (p = 0.005). In conclusion, we found associations between several genes and hip geometry measures that explained 12% to 22% of heritability at different sites. The results provide a defined set of genes related to biological pathways relevant to BMD and etiology of bone fragility. © 2019 American Society for Bone and Mineral Research.

Epigenetics as a New Frontier in Orthopedic Regenerative Medicine and Oncology

Skeletal regenerative medicine aims to repair or regenerate skeletal tissues using pharmacotherapies, cell-based treatments, and/or surgical interventions. The field is guided by biological principles active during development, wound healing, aging, and carcinogenesis. Skeletal development and tissue maintenance in adults represent highly intricate biological processes that require continuous adjustments in the expression of cell type-specific genes that generate, remodel, and repair the skeletal extracellular matrix. Errors in these processes can facilitate musculoskeletal disease including cancers or injury. The fundamental molecular mechanisms by which cell type-specific patterns in gene expression are established and retained during successive mitotic divisions require epigenetic control, which we review here. We focus on epigenetic regulatory proteins that control the mammalian epigenome at the level of chromatin with emphasis on proteins that are amenable to drug intervention to mitigate skeletal tissue degeneration (e.g., osteoarthritis and osteoporosis). We highlight recent findings on a number of druggable epigenetic regulators, including DNA methyltransferases (e.g., DNMT1, DNMT3A, and DNMT3B) and hydroxylases (e.g., TET1, TET2, and TET3), histone methyltransferases (e.g., EZH1, EZH2, and DOT1L) as well as histone deacetylases (e.g., HDAC3, HDAC4, and HDAC7) and histone acetyl readers (e.g., BRD4) in relation to the development of bone or cartilage regenerative drug therapies. We also review how histone mutations lead to epigenomic catastrophe and cause musculoskeletal tumors. The combined body of molecular and genetic studies focusing on epigenetic regulators indicates that these proteins are critical for normal skeletogenesis and viable candidate drug targets for short-term local pharmacological strategies to mitigate musculoskeletal tissue degeneration. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 37:1465-1474, 2019.

Simultaneous inference of phenotype-associated genes and relevant tissues from GWAS data via Bayesian integration of multiple tissue-specific gene networks

Although genome-wide association studies (GWAS) have successfully identified thousands of genomic loci associated with hundreds of complex traits in the past decade, the debate about such problems as missing heritability and weak interpretability has been appealing for effective computational methods to facilitate the advanced analysis of the vast volume of existing and anticipated genetic data. Towards this goal, gene-level integrative GWAS analysis with the assumption that genes associated with a phenotype tend to be enriched in biological gene sets or gene networks has recently attracted much attention, due to such advantages as straightforward interpretation, less multiple testing burdens, and robustness across studies. However, existing methods in this category usually exploit non-tissue-specific gene networks and thus lack the ability to utilize informative tissue-specific characteristics. To overcome this limitation, we proposed a Bayesian approach called SIGNET (Simultaneously Inference of GeNEs and Tissues) to integrate GWAS data and multiple tissue-specific gene networks for the simultaneous inference of phenotype-associated genes and relevant tissues. Through extensive simulation studies, we showed the effectiveness of our method in finding both associated genes and relevant tissues for a phenotype. In applications to real GWAS data of 14 complex phenotypes, we demonstrated the power of our method in both deciphering genetic basis and discovering biological insights of a phenotype. With this understanding, we expect to see SIGNET as a valuable tool for integrative GWAS analysis, thereby boosting the prevention, diagnosis, and treatment of human inherited diseases and eventually facilitating precision medicine.

Identity informative SNP associations in the UK Biobank

Single nucleotide polymorphisms (SNPs) are amenable to genotyping DNA from degraded, inhibited, and/or ancient substrates due to their relatively small amplicon size. Though they have clear advantages over traditional short tandem repeat (STR) typing for specific casework scenarios, the advances in massively parallel sequencing (MPS) have drastically increased the utility of this marker type. The biallelic nature of SNPs makes them individually less informative than STRs due to limited heterozygosity; however, in sufficiently large multiplexes, identity informative SNPs (iiSNPs) may produce combined random match probabilities comparable to STR typing. Multiple MPS library preparation kits now include iiSNPs and similar to STRs, these loci have been rigorously characterized during multiplex development. The relative accessibility of genome-wide association study (GWAS) summary statistics enables re-investigation of forensically relevant targets in high-quality datasets. Here, 4085 GWASs from the UK Biobank European datasets (UKB; 787 ≤ N ≤ 361,194) were mined for iiSNPs typed by the ForenSeq DNA Signature Prep Kit (Verogen). Seven iiSNPs had genome-wide association (p ≤ 5 × 10^-8) with 17 phenotypes in UKB Europeans. Most notably, these relationships involve two outwardly visible characteristics: standing height (rs907100; β = 0.011, p = 1.35 × 10^-10) and hair/balding patterns (rs2399332; β = -0.009, p = 3.83 × 10^-8). The remaining associations involve red blood cell characteristics and measures of lung function. Though these traits are highly polygenic and the individual SNP effects described here have been refuted empirically, we describe the importance and ease of exploring high-quality, freely accessible data to continuously and robustly characterize new and existing forensically relevant loci.

Genome-wide scan reveals genetic divergence and diverse adaptive selection in Chinese local cattle

Background

Understanding the population structure and genetic bases of well-adapted cattle breeds to local environments is one of the most essential tasks to develop appropriate genetic improvement programs.

Results

We performed a comprehensive study to investigate the population structure, divergence and selection signatures at genome-wide level in diverse Chinese local cattle using Bovine HD SNPs array, including two breeds from North China, one breed from Northwest China, three breeds from Southwest China and two breeds from South China. Population genetic analyses revealed the genetic structures of these populations were mostly related to the geographic locations. Notably, we detected 294 and 1263 candidate regions under selection using the di and iHS approaches, respectively. A series of group-specific and breed-specific candidate genes were identified, which are involved in immune response, sexual maturation, stature related, birth and bone weight, embryonic development, coat colors and adaptation. Furthermore, haplotype diversity and network pattern for candidate genes, including LPGAT1, LCORL, PPP1R8, RXFP2 and FANCA, suggest that these genes have been under differential selection pressures in various environmental conditions.

Conclusions

Our results shed insights into diverse selection during breed formation in Chinese local cattle. These findings may promote the application of genome-assisted breeding for well-adapted local breeds with economic and ecological importance.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5822-y) contains supplementary material, which is available to authorized users.

Genome-wide association study reveals candidate genes associated with body measurement traits in Chinese Wagyu beef cattle

We performed a genome-wide association study to identify candidate genes for body measurement traits in 463 Wagyu beef cattle typed with the Illumina Bovine HD 770K SNP array. At the genome-wide level, we detected 18, five and one SNPs associated with hip height, body height and body length respectively. In total, these SNPs are within or near 11 genes, six of which (PENK, XKR4, IMPAD1, PLAG1, CCND2 and SNTG1) have been reported previously and five of which (CSMD3, LAP3, SYN3, FAM19A5 and TIMP3) are novel candidate genes that we found to be associated with body measurement traits. Further exploration of these candidate genes will facilitate genetic improvement in Chinese Wagyu beef cattle.

Geographic Variation and Bias in the Polygenic Scores of Complex Diseases and Traits in Finland

Polygenic scores (PSs) are becoming a useful tool to identify individuals with high genetic risk for complex diseases, and several projects are currently testing their utility for translational applications. It is also tempting to use PSs to assess whether genetic variation can explain a part of the geographic distribution of a phenotype. However, it is not well known how the population genetic properties of the training and target samples affect the geographic distribution of PSs. Here, we evaluate geographic differences, and related biases, of PSs in Finland in a geographically well-defined sample of 2,376 individuals from the National FINRISK study. First, we detect geographic differences in PSs for coronary artery disease (CAD), rheumatoid arthritis, schizophrenia, waist-hip ratio (WHR), body-mass index (BMI), and height, but not for Crohn disease or ulcerative colitis. Second, we use height as a model trait to thoroughly assess the possible population genetic biases in PSs and apply similar approaches to the other phenotypes. Most importantly, we detect suspiciously large accumulations of geographic differences for CAD, WHR, BMI, and height, suggesting bias arising from the population's genetic structure rather than from a direct genotype-phenotype association. This work demonstrates how sensitive the geographic patterns of current PSs are for small biases even within relatively homogeneous populations and provides simple tools to identify such biases. A thorough understanding of the effects of population genetic structure on PSs is essential for translational applications of PSs.

Update on the predictability of tall stature from DNA markers in Europeans

Predicting adult height from DNA has important implications in forensic DNA phenotyping. In 2014, we introduced a prediction model consisting of 180 height-associated SNPs based on data from 10,361 Northwestern Europeans enriched with tall individuals (770 > 1.88 standard deviation), which yielded a mid-ranged accuracy (AUC = 0.75 for binary prediction of tall stature and R² = 0.12 for quantitative prediction of adult height). Here, we provide an update on DNA-based height predictability considering an enlarged list of subsequently-published height-associated SNPs using data from the same set of 10,361 Europeans. A prediction model based on the full set of 689 SNPs showed an improved accuracy relative to previous models for both tall stature (AUC = 0.79) and quantitative height (R² = 0.21). A feature selection analysis revealed a subset of 412 most informative SNPs while the corresponding prediction model retained most of the accuracy (AUC = 0.76 and R² = 0.19) achieved with the full model. Over all, our study empirically exemplifies that the accuracy for predicting human appearance phenotypes with very complex underlying genetic architectures, such as adult height, can be improved by increasing the number of phenotype-associated DNA variants. Our work also demonstrates that a careful sub-selection allows for a considerable reduction of the number of DNA predictors that achieve similar prediction accuracy as provided by the full set. This is forensically relevant due to restrictions in the number of SNPs simultaneously analyzable with forensically suitable DNA technologies in the current days of targeted massively parallel sequencing in forensic genetics.

Low IGF-I Bioavailability Impairs Growth and Glucose Metabolism in a Mouse Model of Human PAPPA2 p.Ala1033Val Mutation

Bioactive free IGF-I is critically important for growth. The bioavailability of IGF-I is modulated by the IGF-binding proteins (IGFBPs) and their proteases, such as pregnancy-associated plasma protein-A2 (PAPP-A2). We have created a mouse model with a specific mutation in PAPPA2 identified in a human with PAPP-A2 deficiency. The human mutation was introduced to the mouse genome via a knock-in strategy, creating knock-in mice with detectable protein levels of Papp-a2 but without protease activities. We found that the Pappa2 mutation led to significant reductions in body length (10%), body weight (10% and 20% in males and females, respectively), and relative lean mass in mice. Micro-CT analyses of Pappa2 knock-in femurs from adult mice showed inhibited periosteal bone expansion leading to more slender bones in both male and female mice. Furthermore, in the Pappa2 knock-in mice, insulin resistance correlated with decreased serum free IGF-I and increased intact IGFBP-3 concentrations. Interestingly, mice heterozygous for the knock-in mutation demonstrated a growth rate for body weight and length as well as a biochemical phenotype that was intermediate between wild-type and homozygous mice. This study models a human PAPPA2 mutation in mice. The mouse phenotype closely resembles that of the human patients, and it provides further evidence that the regulation of IGF-I bioavailability by PAPP-A2 is critical for human growth and for glucose and bone metabolism.

Cdc42 Effector Protein 3 Interacts With Cdc42 in Regulating Xenopus Somite Segmentation

Somitogenesis is a critical process during vertebrate development that establishes the segmented body plan and gives rise to the vertebra, skeletal muscles, and dermis. While segmentation clock and wave front mechanisms have been elucidated to control the size and time of somite formation, regulation of the segmentation process that physically separates somites is not understood in detail. Here, we identified a cytoskeletal player, Cdc42 effector protein 3 (Cdc42ep3, CEP3) that is required for somite segmentation in Xenopus embryos. CEP3 is specifically expressed in somite tissue during somite segmentation. Loss-of-function experiments showed that CEP3 is not required for the specification of paraxial mesoderm, nor the differentiation of muscle cells, but is required for the segmentation process. Live imaging analysis further revealed that CEP3 is required for cell shape changes and alignment during somitogenesis. When CEP3 was knocked down, somitic cells did not elongate efficiently along the mediolateral axis and failed to undertake the 90° rotation. As a result, cells remained in a continuous sheet without an apparent segmentation cleft. CEP3 likely interacts with Cdc42 during this process, and both increased and decreased Cdc42 activity led to defective somite segmentation. Segmentation defects caused by Cdc42 knockdown can be partially rescued by the overexpression of CEP3. Conversely, loss of CEP3 resulted in the maintenance of high levels of Cdc42 activity at the cell membrane, which is normally reduced during and after somite segmentation. These results suggest that there is a feedback regulation between Cdc42 and CEP3 during somite segmentation and the activity of Cdc42 needs to be fine-tuned to control the coordinated cell shape changes and movement required for somite segmentation.

Quantification of Facial Traits

Measuring facial traits by quantitative means is a prerequisite to investigate epidemiological, clinical, and forensic questions. This measurement process has received intense attention in recent years. We divided this process into the registration of the face, landmarking, morphometric quantification, and dimension reduction. Face registration is the process of standardizing pose and landmarking annotates positions in the face with anatomic description or mathematically defined properties (pseudolandmarks). Morphometric quantification computes pre-specified transformations such as distances. Landmarking: We review face registration methods which are required by some landmarking methods. Although similar, face registration and landmarking are distinct problems. The registration phase can be seen as a pre-processing step and can be combined independently with a landmarking solution. Existing approaches for landmarking differ in their data requirements, modeling approach, and training complexity. In this review, we focus on 3D surface data as captured by commercial surface scanners but also cover methods for 2D facial pictures, when methodology overlaps. We discuss the broad categories of active shape models, template based approaches, recent deep-learning algorithms, and variations thereof such as hybrid algorithms. The type of algorithm chosen depends on the availability of pre-trained models for the data at hand, availability of an appropriate landmark set, accuracy characteristics, and training complexity. Quantification: Landmarking of anatomical landmarks is usually augmented by pseudo-landmarks, i.e., indirectly defined landmarks that densely cover the scan surface. Such a rich data set is not amenable to direct analysis but is reduced in dimensionality for downstream analysis. We review classic dimension reduction techniques used for facial data and face specific measures, such as geometric measurements and manifold learning. Finally, we review symmetry registration and discuss reliability.

Meta-analysis of genome-wide association studies for height and body mass index in ∼700000 individuals of European ancestry

Recent genome-wide association studies (GWAS) of height and body mass index (BMI) in ∼250000 European participants have led to the discovery of ∼700 and ∼100 nearly independent single nucleotide polymorphisms (SNPs) associated with these traits, respectively. Here we combine summary statistics from those two studies with GWAS of height and BMI performed in ∼450000 UK Biobank participants of European ancestry. Overall, our combined GWAS meta-analysis reaches N ∼700000 individuals and substantially increases the number of GWAS signals associated with these traits. We identified 3290 and 941 near-independent SNPs associated with height and BMI, respectively (at a revised genome-wide significance threshold of P < 1 × 10-8), including 1185 height-associated SNPs and 751 BMI-associated SNPs located within loci not previously identified by these two GWAS. The near-independent genome-wide significant SNPs explain ∼24.6% of the variance of height and ∼6.0% of the variance of BMI in an independent sample from the Health and Retirement Study (HRS). Correlations between polygenic scores based upon these SNPs with actual height and BMI in HRS participants were ∼0.44 and ∼0.22, respectively. From analyses of integrating GWAS and expression quantitative trait loci (eQTL) data by summary-data-based Mendelian randomization, we identified an enrichment of eQTLs among lead height and BMI signals, prioritizing 610 and 138 genes, respectively. Our study demonstrates that, as previously predicted, increasing GWAS sample sizes continues to deliver, by the discovery of new loci, increasing prediction accuracy and providing additional data to achieve deeper insight into complex trait biology. All summary statistics are made available for follow-up studies.

A guinea fowl genome assembly provides new evidence on evolution following domestication and selection in galliformes

The helmeted guinea fowl Numida meleagris belongs to the order Galliformes. Its natural range includes a large part of sub‐Saharan Africa, from Senegal to Eritrea and from Chad to South Africa. Archaeozoological and artistic evidence suggest domestication of this species may have occurred about 2,000 years BP in Mali and Sudan primarily as a food resource, although villagers also benefit from its capacity to give loud alarm calls in case of danger, of its ability to consume parasites such as ticks and to hunt snakes, thus suggesting its domestication may have resulted from a commensal association process. Today, it is still farmed in Africa, mainly as a traditional village poultry, and is also bred more intensively in other countries, mainly France and Italy. The lack of available molecular genetic markers has limited the genetic studies conducted to date on guinea fowl. We present here a first‐generation whole‐genome sequence draft assembly used as a reference for a study by a Pool‐seq approach of wild and domestic populations from Europe and Africa. We show that the domestic populations share a higher genetic similarity between each other than they do to wild populations living in the same geographical area. Several genomic regions showing selection signatures putatively related to domestication or importation to Europe were detected, containing candidate genes, most notably EDNRB2, possibly explaining losses in plumage coloration phenotypes in domesticated populations.

[Etiology and genetic diagnosis of short stature in children]

OBJECTIVE

To study the etiology and genetic diagnosis of children with short stature.

METHODS

A retrospective analysis was performed to study the etiological distribution and clinical features of 86 children with short stature.

RESULTS

A total of 6 causes were observed in these children, among which idiopathic short stature (ISS, 41%) and growth hormone deficiency (GHD, 29%) were the most common causes, followed by genetic diseases (14%). There were no significant differences in age at the time of diagnosis, body height, body length and weight at birth, body height of parents and insulin-like growth factor-1 levels between the genetic disease group and the ISS/GHD groups (P>0.05). Compared with the ISS group, the genetic disease group had significantly lower deviation from the 3rd percentile for the height of children of the same age and sex (ΔP3) and height standard deviation score (P<0.05), while there were no significant differences between the genetic disease and GHD groups (P>0.05). The analysis of the clinical manifestations for the genetic disease group showed heterogeneity and phenotypic overlap in children with different genetic diseases.

CONCLUSIONS

ISS, GHD and genetic diseases are major causes of short stature in children. For children with severe short stature, genetic testing should be performed to make a definitive diagnosis after GHD has been excluded.

Heritability and genome-wide association study of benign prostatic hyperplasia (BPH) in the eMERGE network

Benign prostatic hyperplasia (BPH) results in a significant public health burden due to the morbidity caused by the disease and many of the available remedies. As much as 70% of men over 70 will develop BPH. Few studies have been conducted to discover the genetic determinants of BPH risk. Understanding the biological basis for this condition may provide necessary insight for development of novel pharmaceutical therapies or risk prediction. We have evaluated SNP-based heritability of BPH in two cohorts and conducted a genome-wide association study (GWAS) of BPH risk using 2,656 cases and 7,763 controls identified from the Electronic Medical Records and Genomics (eMERGE) network. SNP-based heritability estimates suggest that roughly 60% of the phenotypic variation in BPH is accounted for by genetic factors. We used logistic regression to model BPH risk as a function of principal components of ancestry, age, and imputed genotype data, with meta-analysis performed using METAL. The top result was on chromosome 22 in SYN3 at rs2710383 (p-value = 4.6 × 10-7; Odds Ratio = 0.69, 95% confidence interval = 0.55-0.83). Other suggestive signals were near genes GLGC, UNCA13, SORCS1 and between BTBD3 and SPTLC3. We also evaluated genetically-predicted gene expression in prostate tissue. The most significant result was with increasing predicted expression of ETV4 (chr17; p-value = 0.0015). Overexpression of this gene has been associated with poor prognosis in prostate cancer. In conclusion, although there were no genome-wide significant variants identified for BPH susceptibility, we present evidence supporting the heritability of this phenotype, have identified suggestive signals, and evaluated the association between BPH and genetically-predicted gene expression in prostate.

Predicting adult height from DNA variants in a European-Asian admixed population

Accurate genomic profiling for adult height is of high practical relevance in forensics genetics. Adult height is a classical reference trait in the field of human complex trait genetics characterized by highly polygenic nature and relatively high heritability. A meta-analysis of genome-wide association studies by the Genetic Investigation of Anthropocentric Traits (GIANT) consortium has identified 697 DNA variants associated with adult height in Europeans; however, whether these variants will still be informative in non-Europeans is still in question. The present study investigated the predictive power of these 697 height-associated SNPs in 687 Uyghurs of European-Asian admixed origin. Among all GIANT SNPs, 11% showed nominally significant association (6.78 × 10^-4 < p < 0.05) with adult height in the Uyghur population and among the significant SNPs 77% of allele effects were in the same direction as those in Europeans reported in the GIANT study. Fitting linear and logistic models using a polygenic score consisting of all GIANT SNPs resulted in an 80-20 cross-validated mean R² of 10.08% (95% CI 3.16-18.40%) for quantitative height prediction and a mean AUC value of 0.65 (95% CI 0.57-0.72%) for qualitative "above average" prediction. Fine-tuning the SNP set using their association p values considerably improved the prediction results (number of SNPs = 62, R² = 15.59%, 95% CI 6.80-25.71%; AUC = 0.70, 95% CI 62-0.77) in the Uyghurs. Overall, our findings demonstrate substantial differences between the European and Asian populations in the genetics of adult height, emphasizing the importance of population heterogeneity underlying the genetic architecture of adult height.

Whole genome sequencing of canids reveals genomic regions under selection and variants influencing morphology

Domestic dog breeds are characterized by an unrivaled diversity of morphologic traits and breed-associated behaviors resulting from human selective pressures. To identify the genetic underpinnings of such traits, we analyze 722 canine whole genome sequences (WGS), documenting over 91 million single nucleotide and small indels, creating a large catalog of genomic variation for a companion animal species. We undertake both selective sweep analyses and genome wide association studies (GWAS) inclusive of over 144 modern breeds, 54 wild canids and a hundred village dogs. Our results identify variants of strong impact associated with 16 phenotypes, including body weight variation which, when combined with existing data, explain greater than 90% of body size variation in dogs. We thus demonstrate that GWAS and selection scans performed with WGS are powerful complementary methods for expanding the utility of companion animal systems for the study of mammalian growth and biology.

Height and Body Mass Index as Modifiers of Breast Cancer Risk in BRCA1/2 Mutation Carriers: A Mendelian Randomization Study

BACKGROUND

BRCA1/2 mutations confer high lifetime risk of breast cancer, although other factors may modify this risk. Whether height or body mass index (BMI) modifies breast cancer risk in BRCA1/2 mutation carriers remains unclear.

METHODS

We used Mendelian randomization approaches to evaluate the association of height and BMI on breast cancer risk, using data from the Consortium of Investigators of Modifiers of BRCA1/2 with 14 676 BRCA1 and 7912 BRCA2 mutation carriers, including 11 451 cases of breast cancer. We created a height genetic score using 586 height-associated variants and a BMI genetic score using 93 BMI-associated variants. We examined both observed and genetically determined height and BMI with breast cancer risk using weighted Cox models. All statistical tests were two-sided.

RESULTS

Observed height was positively associated with breast cancer risk (HR = 1.09 per 10 cm increase, 95% confidence interval [CI] = 1.0 to 1.17; P = 1.17). Height genetic score was positively associated with breast cancer, although this was not statistically significant (per 10 cm increase in genetically predicted height, HR = 1.04, 95% CI = 0.93 to 1.17; P = .47). Observed BMI was inversely associated with breast cancer risk (per 5 kg/m2 increase, HR = 0.94, 95% CI = 0.90 to 0.98; P = .007). BMI genetic score was also inversely associated with breast cancer risk (per 5 kg/m2 increase in genetically predicted BMI, HR = 0.87, 95% CI = 0.76 to 0.98; P = .02). BMI was primarily associated with premenopausal breast cancer.

CONCLUSION

Height is associated with overall breast cancer and BMI is associated with premenopausal breast cancer in BRCA1/2 mutation carriers. Incorporating height and BMI, particularly genetic score, into risk assessment may improve cancer management.

Methods for the Analysis and Interpretation for Rare Variants Associated with Complex Traits

With the advent of Next Generation Sequencing (NGS) technologies, whole genome and whole exome DNA sequencing has become affordable for routine genetic studies. Coupled with improved genotyping arrays and genotype imputation methodologies, it is increasingly feasible to obtain rare genetic variant information in large datasets. Such datasets allow researchers to gain a more complete understanding of the genetic architecture of complex traits caused by rare variants. State-of-the-art statistical methods for the statistical genetics analysis of sequence-based association, including efficient algorithms for association analysis in biobank-scale datasets, gene-association tests, meta-analysis, fine mapping methods that integrate functional genomic dataset, and phenome-wide association studies (PheWAS), are reviewed here. These methods are expected to be highly useful for next generation statistical genetics analysis in the era of precision medicine. © 2019 by John Wiley & Sons, Inc.

Nonclassical GH Insensitivity: Characterization of Mild Abnormalities of GH Action

GH insensitivity (GHI) presents in childhood with growth failure and in its severe form is associated with extreme short stature and dysmorphic and metabolic abnormalities. In recent years, the clinical, biochemical, and genetic characteristics of GHI and other overlapping short stature syndromes have rapidly expanded. This can be attributed to advancing genetic techniques and a greater awareness of this group of disorders. We review this important spectrum of defects, which present with phenotypes at the milder end of the GHI continuum. We discuss their clinical, biochemical, and genetic characteristics. The objective of this review is to clarify the definition, identification, and investigation of this clinically relevant group of growth defects. We also review the therapeutic challenges of mild GHI.

Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies

Genetic predictions of height differ among human populations and these differences have been interpreted as evidence of polygenic adaptation. These differences were first detected using SNPs genome-wide significantly associated with height, and shown to grow stronger when large numbers of sub-significant SNPs were included, leading to excitement about the prospect of analyzing large fractions of the genome to detect polygenic adaptation for multiple traits. Previous studies of height have been based on SNP effect size measurements in the GIANT Consortium meta-analysis. Here we repeat the analyses in the UK Biobank, a much more homogeneously designed study. We show that polygenic adaptation signals based on large numbers of SNPs below genome-wide significance are extremely sensitive to biases due to uncorrected population stratification. More generally, our results imply that typical constructions of polygenic scores are sensitive to population stratification and that population-level differences should be interpreted with caution.

Editorial note

This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

An association study using imputed whole-genome sequence data identifies novel significant loci for growth-related traits in a Duroc × Erhualian F2 population

The average daily gain (ADG) and body weight (BW) are very important traits for breeding programs and for the meat production industry, which have attracted many researchers to delineate the genetic architecture behind these traits. In the present study, single- and multi-trait genome-wide association studies (GWAS) were performed between imputed whole-genome sequence data and the traits of the ADG and BW at different stages in a large-scale White Duroc × Erhualian F₂ population. A bioinformatics annotation analysis was used to assist in the identification of candidate genes that are associated with these traits. Five and seven genome-wide significant quantitative trait loci (QTLs) were identified by single- and multi-trait GWAS, respectively. Furthermore, more than 40 genome-wide suggestive loci were detected. On the basis of the whole-genome sequence association study and the bioinformatics analysis, NDUFAF6, TNS1 and HMGA1 stood out as the strongest candidate genes. The presented single- and multi-trait GWAS analysis using imputed whole-genome sequence data identified several novel QTLs for pig growth-related traits. Integrating the GWAS with bioinformatics analysis can facilitate the more accurate identification of candidate genes. Higher imputation accuracy, time-saving algorithms, improved models and comprehensive databases will accelerate the identification of causal genes or mutations, which will contribute to genomic selection and pig breeding in the future.

Interrogation of human hematopoiesis at single-cell and single-variant resolution

Widespread linkage disequilibrium and incomplete annotation of cell-to-cell state variation represent substantial challenges to elucidating mechanisms of trait-associated genetic variation. Here, we perform genetic fine-mapping for blood cell traits in the UK Biobank to identify putative causal variants. These variants are enriched in genes encoding for proteins in trait-relevant biological pathways and in accessible chromatin of hematopoietic progenitors. For regulatory variants, we explore patterns of developmental enhancer activity, predict molecular mechanisms, and identify likely target genes. In several instances, we localize multiple independent variants to the same regulatory element or gene. We further observe that variants with pleiotropic effects preferentially act in common progenitor populations to direct the production of distinct lineages. Finally, we leverage fine-mapped variants in conjunction with continuous epigenomic annotations to identify trait-cell type enrichments within closely related populations and in single cells. Our study provides a comprehensive framework for single-variant and single-cell analyses of genetic associations.

Fine mapping of blood cell traits in UK Biobank identifies putative causal variants and enrichment of fine-mapped variants in accessible chromatin of hematopoietic progenitor cells. The study provides an analytical framework for single-variant and single-cell analyses of genetic associations.

IGF-axis confers transformation and regeneration of fallopian tube fimbria epithelium upon ovulation

Background

The fallopian tube fimbria is regarded as the main tissue of origin and incessant ovulation as the main risk factor of ovarian high-grade serous carcinoma. Previously, we discovered the tumorigenesis activity of human ovulatory follicular fluid (FF) upon injection to the mammary fat pad of Trp53-null mice. We also found a mutagenesis activity of FF-ROS and a apoptosis-rescuing activity of Hb from retrograde menstruation. However, neither of them can explain the tumorigenesis activities of FF.

Methods

From two cohorts of ovulatory FF retrieved from IVF patients, the main growth factor responsible for the transformation of human fimbrial epithelial cells was identified. Mechanism of activation, ways of signal transduction of the growth factor, as well as the cellular and genetic phenotypes of the malignant transformation was characterized.

Findings

In this study, we showed that insulin-like growth factor (IGF)-axis proteins, including IGFBP-bound IGF2 as well as the IGFBP-lytic enzyme PAPP-A, are abundantly present in FF. Upon engaging with glycosaminoglycans on the membrane of fimbrial epithelial cells, PAPP-A cleaves IGFBPs and releases IGF2 to bind with IGF-1R. Through the IGF-1R/AKT/mTOR and IGF-1R/AKT/NANOG pathways, FF-IGF leads to stemness and survival, and in the case of TP53/Rb or TP53/CCNE1 loss, to clonal expansion and malignant transformation of fimbrial epithelial cells. By depleting each IGF axis component from FF, we proved that IGF2, IGFBP2/6, and PAPP-A are all essential and confer the majority of the transformation and regeneration activities.

Interpretation

This study revealed that the FF–IGF axis functions to regenerate tissue damage after ovulation and promote the transformation of fimbrial epithelial cells that have been initiated by p53- and Rb-pathway disruptions.

Fund

The study was supported by grants of the Ministry of Science and Technology, Taiwan (MOST 106-2314-B-303-001-MY2; MOST 105-2314-B-303-017-MY2; MOST 107-2314-B-303-013-MY3), and Buddhist Tzu Chi General Hospital, Taiwan (TCMMP104-04-01).

Analysis of a large dataset reveals haplotypes carrying putatively recessive lethal and semi-lethal alleles with pleiotropic effects on economically important traits in beef cattle

BACKGROUND

In livestock, deleterious recessive alleles can result in reduced economic performance of homozygous individuals in multiple ways, e.g. early embryonic death, death soon after birth, or semi-lethality with incomplete penetrance causing reduced viability. While death is an easy phenotype to score, reduced viability is not as easy to identify. However, it can sometimes be observed as reduced conception rates, longer calving intervals, or lower survival for live born animals.

METHODS

In this paper, we searched for haplotypes that carry putatively recessive lethal or semi-lethal alleles in 132,725 genotyped Irish beef cattle from five breeds: Aberdeen Angus, Charolais, Hereford, Limousin, and Simmental. We phased the genotypes in sliding windows along the genome and used five tests to identify haplotypes with absence of or reduced homozygosity. Then, we associated the identified haplotypes with 44,351 insemination records that indicated early embryonic death, and postnatal survival records. Finally, we assessed haplotype pleiotropy by estimating substitution effects on estimates of breeding value for 15 economically important traits in beef production.

RESULTS

We found support for one haplotype that carries a putatively recessive lethal (chromosome 16 in Simmental) and two haplotypes that carry semi-lethal alleles (chromosome 14 in Aberdeen Angus and chromosome 19 in Charolais), with population frequencies of 8.8, 15.2, and 14.4%, respectively. These three haplotypes showed pleiotropic effects on economically important traits for beef production. Their allele substitution effects are €2.30, €3.42, and €1.47 for the terminal index and €1.03, - €3.11, and - €0.88 for the replacement index, where the standard deviations for the terminal index are €22.52, €18.65, and €22.70 and for the replacement index they are €31.35, €29.82, and €35.79. We identified ZFAT as the candidate gene for semi-lethality in Aberdeen Angus, several candidate genes for the lethal Simmental haplotype, and no candidate genes for the semi-lethal Charolais haplotype.

CONCLUSIONS

We analysed genotype, reproduction, survival, and production data to detect haplotypes that carry putatively recessive lethal or semi-lethal alleles in Irish beef cattle and identified one lethal and two semi-lethal haplotypes, which have pleiotropic effects on economically important traits in beef production.

Osteogenesis depends on commissioning of a network of stem cell transcription factors that act as repressors of adipogenesis

Mesenchymal (stromal) stem cells (MSCs) constitute populations of mesodermal multipotent cells involved in tissue regeneration and homeostasis in many different organs. Here we performed comprehensive characterization of the transcriptional and epigenomic changes associated with osteoblast and adipocyte differentiation of human MSCs. We demonstrate that adipogenesis is driven by considerable remodeling of the chromatin landscape and de novo activation of enhancers, whereas osteogenesis involves activation of preestablished enhancers. Using machine learning algorithms for in silico modeling of transcriptional regulation, we identify a large and diverse transcriptional network of pro-osteogenic and antiadipogenic transcription factors. Intriguingly, binding motifs for these factors overlap with SNPs related to bone and fat formation in humans, and knockdown of single members of this network is sufficient to modulate differentiation in both directions, thus indicating that lineage determination is a delicate balance between the activities of many different transcription factors.

Powerful gene set analysis in GWAS with the Generalized Berk-Jones statistic

A common complementary strategy in Genome-Wide Association Studies (GWAS) is to perform Gene Set Analysis (GSA), which tests for the association between one phenotype of interest and an entire set of Single Nucleotide Polymorphisms (SNPs) residing in selected genes. While there exist many tools for performing GSA, popular methods often include a number of ad-hoc steps that are difficult to justify statistically, provide complicated interpretations based on permutation inference, and demonstrate poor operating characteristics. Additionally, the lack of gold standard gene set lists can produce misleading results and create difficulties in comparing analyses even across the same phenotype. We introduce the Generalized Berk-Jones (GBJ) statistic for GSA, a permutation-free parametric framework that offers asymptotic power guarantees in certain set-based testing settings. To adjust for confounding introduced by different gene set lists, we further develop a GBJ step-down inference technique that can discriminate between gene sets driven to significance by single genes and those demonstrating group-level effects. We compare GBJ to popular alternatives through simulation and re-analysis of summary statistics from a large breast cancer GWAS, and we show how GBJ can increase power by incorporating information from multiple signals in the same gene. In addition, we illustrate how breast cancer pathway analysis can be confounded by the frequency of FGFR2 in pathway lists. Our approach is further validated on two other datasets of summary statistics generated from GWAS of height and schizophrenia.

Genetic regulation of linear growth

Linear growth occurs at the growth plate. Therefore, genetic defects that interfere with the normal function of the growth plate can cause linear growth disorders. Many genetic causes of growth disorders have already been identified in humans. However, recent genome-wide approaches have broadened our knowledge of the mechanisms of linear growth, not only providing novel monogenic causes of growth disorders but also revealing single nucleotide polymorphisms in genes that affect height in the general population. The genes identified as causative of linear growth disorders are heterogeneous, playing a role in various growth-regulating mechanisms including those involving the extracellular matrix, intracellular signaling, paracrine signaling, endocrine signaling, and epigenetic regulation. Understanding the underlying genetic defects in linear growth is important for clinicians and researchers in order to provide proper diagnoses, management, and genetic counseling, as well as to develop better treatment approaches for children with growth disorders.

Cachexia does not induce loss of myonuclei or muscle fibres during xenografted prostate cancer in mice

AIM

Cachexia is a severe wasting disorder involving loss of body- and muscle mass reducing survival and quality of life in cancer patients. We aim at determining if cachexia is a mere perturbation of the protein balance or if the condition also involves a degenerative loss of myonuclei within the fibre syncytia or loss of whole muscle fibres.

METHODS

We induced cachexia by xenografting PC3 prostate cancer cells in nu/nu mice. Six weeks later, we counted myonuclei by in vivo microscopic imaging of single live fibres in the extensor digitorum longus muscle (EDL), and the EDL, soleus and tibialis anterior muscles were also harvested for ex vivo histology.

RESULTS

The mice lost on average 15% of the whole-body wt. The muscle wet weight of the glycolytic, fast EDL was reduced by 14%, the tibialis anterior by 17%, and the slow, oxidative soleus by 6%. The fibre cross-sectional area in the EDL was reduced by 21% with no loss of myonuclei or any significant reduction in the number of muscle fibres. TUNEL-positive nuclei or fibres with embryonic myosin were rare both in cachectic and control muscles, and haematoxylin-eosin staining revealed no clear signs of muscle pathology.

CONCLUSION

The data suggest that the cachexia induced by xenografted prostate tumours induces a pronounced atrophy not accompanied by a loss of myonuclei or a loss of muscle fibres. Thus, stem cell related treatment might be redundant, and the quest for treatment options should rather focus on intervening with intracellular pathways regulating muscle fibre size.

Efficient Signal Inclusion With Genomic Applications

This paper addresses the challenge of efficiently capturing a high proportion of true signals for subsequent data analyses when sample sizes are relatively limited with respect to data dimension. We propose the signal missing rate as a new measure for false negative control to account for the variability of false negative proportion. Novel data-adaptive procedures are developed to control signal missing rate without incurring many unnecessary false positives under dependence. We justify the efficiency and adaptivity of the proposed methods via theory and simulation. The proposed methods are applied to GWAS on human height to effectively remove irrelevant SNPs while retaining a high proportion of relevant SNPs for subsequent polygenic analysis.

A Multivariate Genome-Wide Association Study of Wing Shape in Drosophila melanogaster

Due to the complexity of genotype-phenotype relationships, simultaneous analyses of genomic associations with multiple traits will be more powerful and informative than a series of univariate analyses. However, in most cases, studies of genotype-phenotype relationships have been analyzed only one trait at a time. Here, we report the results of a fully integrated multivariate genome-wide association analysis of the shape of the Drosophila melanogaster wing in the Drosophila Genetic Reference Panel. Genotypic effects on wing shape were highly correlated between two different laboratories. We found 2396 significant SNPs using a 5% false discovery rate cutoff in the multivariate analyses, but just four significant SNPs in univariate analyses of scores on the first 20 principal component axes. One quarter of these initially significant SNPs retain their effects in regularized models that take into account population structure and linkage disequilibrium. A key advantage of multivariate analysis is that the direction of the estimated phenotypic effect is much more informative than a univariate one. We exploit this fact to show that the effects of knockdowns of genes implicated in the initial screen were on average more similar than expected under a null model. A subset of SNP effects were replicable in an unrelated panel of inbred lines. Association studies that take a phenomic approach, considering many traits simultaneously, are an important complement to the power of genomics.

Association of genetic polymorphisms with age at menarche in Russian women

OBJECTIVES

Examine the association of genetic polymorphisms with age at menarche (AAM) in Russian women.

STUDY DESIGN

A total of 1613 Russian females were recruited for the study. Fifty two polymorphisms were analyzed for their association with AAM, height, and BMI. The associations were analyzed assuming the additive, dominant, and recessive models and using the log-linear regression as implemented in PLINK v. 2.050. The 2-, 3-, and 4-loci models of gene-gene interactions were analyzed using the MB-MDR method and validated by the permutation test.

MAIN OUTCOME MEASURES

Genetic polymorphism rs6438424 3q13.32 was independently associated with AAM in Russian women. In addition, 14 SNPs were determined as possible contributors to this trait through gene-gene interactions.

RESULTS

The obtained results suggest that 14 out of 52 studied polymorphisms may contribute to AAM in Russian women. The rs6438424 3q13.32 polymorphism was associated with AAM according to both additive and dominant models (рperm = 0.005). In total 12 two-, three-, and four-locus models of gene-gene interactions were determined as contributing to AAM (pperm ≤ 0.006). Nine of the 14 AAM-associated SNPs are also associated with height and BMI (pperm ≤ 0.003). Among 14 AAM-associated SNPs (a priori all having regulatory significance), the highest regulatory potential was determined for rs4633 COMT, rs2164808 POMC, rs2252673INSR, rs6438424 3q13.32, and rs10769908 STK33. Eleven loci are cis-eQTL and affect expression of 14 genes in various tissues and organs (FDR < 0.05). The neuropeptide-encoding genes were overrepresented among the AAM-associated genes (pbonf = 0.039).

CONCLUSIONS

The rs6438424 polymorphism is independently associated with AAM in Russian females in this study. The other 14 SNPs manifest this association through gene-gene interactions.

LiDARPheno - A Low-Cost LiDAR-Based 3D Scanning System for Leaf Morphological Trait Extraction

The ever-growing world population brings the challenge for food security in the current world. The gene modification tools have opened a new era for fast-paced research on new crop identification and development. However, the bottleneck in the plant phenotyping technology restricts the alignment in geno-pheno development as phenotyping is the key for the identification of potential crop for improved yield and resistance to the changing environment. Various attempts to making the plant phenotyping a "high-throughput" have been made while utilizing the existing sensors and technology. However, the demand for 'good' phenotypic information for linkage to the genome in understanding the gene-environment interactions is still a bottleneck in the plant phenotyping technologies. Moreover, the available technologies and instruments are inaccessible, expensive, and sometimes bulky. This work attempts to address some of the critical problems, such as exploration and development of a low-cost LiDAR-based platform for phenotyping the plants in-lab and in-field. A low-cost LiDAR-based system design, LiDARPheno, is introduced in this work to assess the feasibility of the inexpensive LiDAR sensor in the leaf trait (length, width, and area) extraction. A detailed design of the LiDARPheno, based on low-cost and off-the-shelf components and modules, is presented. Moreover, the design of the firmware to control the hardware setup of the system and the user-level python-based script for data acquisition is proposed. The software part of the system utilizes the publicly available libraries and Application Programming Interfaces (APIs), making it easy to implement the system by a non-technical user. The LiDAR data analysis methods are presented, and algorithms for processing the data and extracting the leaf traits are developed. The processing includes conversion, cleaning/filtering, segmentation and trait extraction from the LiDAR data. Experiments on indoor plants and canola plants were performed for the development and validation of the methods for estimation of the leaf traits. The results of the LiDARPheno based trait extraction are compared with the SICK LMS400 (a commercial 2D LiDAR) to assess the performance of the developed system.

Efficient cross-trait penalized regression increases prediction accuracy in large cohorts using secondary phenotypes

We introduce cross-trait penalized regression (CTPR), a powerful and practical approach for multi-trait polygenic risk prediction in large cohorts. Specifically, we propose a novel cross-trait penalty function with the Lasso and the minimax concave penalty (MCP) to incorporate the shared genetic effects across multiple traits for large-sample GWAS data. Our approach extracts information from the secondary traits that is beneficial for predicting the primary trait based on individual-level genotypes and/or summary statistics. Our novel implementation of a parallel computing algorithm makes it feasible to apply our method to biobank-scale GWAS data. We illustrate our method using large-scale GWAS data (~1M SNPs) from the UK Biobank (N = 456,837). We show that our multi-trait method outperforms the recently proposed multi-trait analysis of GWAS (MTAG) for predictive performance. The prediction accuracy for height by the aid of BMI improves from R² = 35.8% (MTAG) to 42.5% (MCP + CTPR) or 42.8% (Lasso + CTPR) with UK Biobank data.

Information of genetic architectures of complex traits can be leveraged for predicting phenotypes. Here, the authors develop CTPR (Cross-Trait Penalized Regression), a method for multi-trait polygenic risk prediction using individual-level genotypes and/or summary statistics from large cohorts.

GARFIELD classifies disease-relevant genomic features through integration of functional annotations with association signals

Loci discovered by genome-wide association studies predominantly map outside protein-coding genes. The interpretation of the functional consequences of non-coding variants can be greatly enhanced by catalogs of regulatory genomic regions in cell lines and primary tissues. However, robust and readily applicable methods are still lacking by which to systematically evaluate the contribution of these regions to genetic variation implicated in diseases or quantitative traits. Here we propose a novel approach that leverages genome-wide association studies' findings with regulatory or functional annotations to classify features relevant to a phenotype of interest. Within our framework, we account for major sources of confounding not offered by current methods. We further assess enrichment of genome-wide association studies for 19 traits within Encyclopedia of DNA Elements- and Roadmap-derived regulatory regions. We characterize unique enrichment patterns for traits and annotations driving novel biological insights. The method is implemented in standalone software and an R package, to facilitate its application by the research community.

Differential methylation of the type 2 diabetes susceptibility locus KCNQ1 is associated with insulin sensitivity and is predicted by CpG site specific genetic variation

AIMS

Epigenetic mechanisms regulate gene expression and may influence the pathogenesis of type 2 diabetes through the loss of insulin sensitivity. The aims of this study were to measure variation in DNA methylation at the type 2 diabetes locus KCNQ1 and assess its relationship with metabolic measures and with genotype.

METHODS

DNA methylation from whole blood DNA was quantified using pyrosequencing at 5 CpG sites at the KCNQ1 locus in 510 individuals without diabetes from the 'Relationship between Insulin Sensitivity and Cardiovascular disease' (RISC) cohort. Genotype data was analysed at the same locus in 1119 individuals in the same cohort. Insulin sensitivity was assessed by euglycaemic-hyperinsulinaemic clamp.

RESULTS

DNA methylation at the KCNQ1 locus was inversely associated with insulin sensitivity and serum adiponectin. This association was driven by a methylation-altering Single Nucleotide Polymorphism (SNP) (rs231840) which ablated a methylation site and reduced methylation levels. A second SNP (rs231357), in weak Linkage Disequilibrium (LD) with rs231840, was also associated with insulin sensitivity and DNA methylation. These SNPs have not been previously reported to be associated with type 2 diabetes risk or insulin sensitivity.

CONCLUSION

Evidence indicates that genetic and epigenetic determinants at the KCNQ1 locus influence insulin sensitivity.

A modified association test for rare and common variants based on affected sib-pair design

Current genome-wide association analysis has identified a great number of rare and common variants associated with common complex traits, however, more effective approaches for detecting associations between rare and common variants with common diseases are still demanded. Approaches for detecting rare variant association analysis will compromise the power when detecting the effects of rare and common variants simultaneously. In this paper, we extend an existing method of testing for rare variant association based on affected sib pairs (TOW-sib) and propose a variable weight test for rare and common variants association based on affected sib pairs (abbreviated as VW-TOWsib). The VW-TOWsib can be used to achieve the purpose of detecting the association of rare and common variants with complex diseases. Simulation results in various scenarios show that our proposed method is more powerful than existing methods for detecting effects of rare and common variants. At the same time, the VW-TOWsib also performs well as a method for rare variant association analysis.

Evaluation of an HMGA2 variant for pleiotropic effects on height and metabolic traits in ponies

BACKGROUND

Ponies are highly susceptible to metabolic derangements including hyperinsulinemia, insulin resistance, and adiposity.

HYPOTHESIS/OBJECTIVES

Genetic loci affecting height in ponies have pleiotropic effects on metabolic pathways and increase the susceptibility to equine metabolic syndrome (EMS).

ANIMALS

Two hundred ninety-four Welsh ponies and 529 horses.

METHODS

Retrospective study of horses phenotyped for metabolic traits. Correlations between height and metabolic traits were assessed by Pearson's correlation coefficients. Complementary genome-wide analysis methods were used to identify a region of interest (ROI) for height and metabolic traits, determine the fraction of heritability contributed by the ROI, and identify candidate genes.

RESULTS

There was an inverse relationship between height and baseline insulin (-0.26) in ponies. Genomic signature of selection and association analyses for both height and insulin identified the same ~1.3 megabase region on chromosome 6 that contained a shared ancestral haplotype between these traits. The ROI contributed ~40% of the heritability for height and ~20% of the heritability for insulin. High-mobility group AT-hook 2 was identified as a candidate gene, and Sanger sequencing detected a c.83G>A (p.G28E) variant associated with height in Shetland ponies. In our cohort of ponies, the A allele had a frequency of 0.76, was strongly correlated with height (-0.75), and was low to moderately correlated with metabolic traits including: insulin (0.32), insulin after an oral sugar test (0.25), non-esterified fatty acids (0.19), and triglyceride (0.22) concentrations.

CONCLUSIONS AND CLINICAL IMPORTANCE

These data have important implications for identifying individuals at risk for EMS.

Association between adult height, myocardial infarction, heart failure, stroke and death: a Korean nationwide population-based study

Background

The association between adult height and cardiovascular (CV) events and mortality has been suggested, albeit inconsistently. We sought to discover the comprehensive relationship between height, CV-related morbidity and all-cause death according to age.

Methods

We investigated the association between adult height and myocardial infarction (MI), heart failure (HF), stroke incidence and mortality in 16 528 128 Korean patients who underwent regular health check-ups (2005-08). Height was stratified by decile according to age (20-39 years, 40-59 years and ≥60 years) and gender.

Results

During a 9-year follow-up period, 590 346 participants died and 232 093 were admitted to hospital for MI, 201 411 for HF and 267 566 for stroke. An inverse relationship between height and MI, HF, stroke and all-cause death was observed in the overall cohort analysis. The association was unchanged after adjusting for CV risk and behavioural and adulthood socioeconomic factors. Both male and female sex showed an inverse relationship with height in adulthood, CV events and mortality. Adult height showed an inverse association in all CV events and mortality, especially in the older groups (≥40 years). In a subgroup analysis of body mass index, there was an inverse relationship between height, CV events and mortality in each group.

Conclusions

Shorter height in adulthood was strongly related to an increased risk of MI, HF, stroke and all-cause death. A suitable environment and appropriate nutrition early in life could influence adult height and eventually reduce the risk of CV events and mortality.