Testing the role of predicted gene knockouts in human anthropometric trait variation

National Heart, Lung, and Blood Institute (NHLBI) S.L. is funded by a Canadian Institutes of Health Research Banting doctoral scholarship. G.L. is funded by Genome Canada and Génome Québec; the Canada Research Chairs program; and the Montreal Heart Institute Foundation. C.M.L. is supported by Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A); and the Li Ka Shing Foundation. N.S. is funded by National Institutes of Health (grant numbers HL088456, HL111089, HL116747). The Mount Sinai BioMe Biobank Program is supported by the Andrea and Charles Bronfman Philanthropies. GO ESP is supported by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO, RC2 HL-102924 to WHISP). The ESP exome sequencing was performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL- 102926 to SeattleGO). EGCUT work was supported through the Estonian Genome Center of University of Tartu by the Targeted Financing from the Estonian Ministry of Science and Education (grant number SF0180142s08); the Development Fund of the University of Tartu (grant number SP1GVARENG); the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and through FP7 (grant number 313010). EGCUT were further supported by the US National Institute of Health (grant number R01DK075787). A.K.M. was supported by an American Diabetes Association Mentor-Based Postdoctoral Fellowship (#7-12-MN- 02). The BioVU dataset used in the analyses described were obtained from Vanderbilt University Medical Centers BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Genome-wide genotyping was funded by NIH grants RC2GM092618 from NIGMS/OD and U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access publication charges for this article was provided by a block grant from Research Councils UK to the University of Cambridge

Testing the role of predicted gene knockouts in human anthropometric trait variation

National Heart, Lung, and Blood Institute (NHLBI) S.L. is funded by a Canadian Institutes of Health Research Banting doctoral scholarship. G.L. is funded by Genome Canada and Génome Québec; the Canada Research Chairs program; and the Montreal Heart Institute Foundation. C.M.L. is supported by Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A); and the Li Ka Shing Foundation. N.S. is funded by National Institutes of Health (grant numbers HL088456, HL111089, HL116747). The Mount Sinai BioMe Biobank Program is supported by the Andrea and Charles Bronfman Philanthropies. GO ESP is supported by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO, RC2 HL-102924 to WHISP). The ESP exome sequencing was performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL- 102926 to SeattleGO). EGCUT work was supported through the Estonian Genome Center of University of Tartu by the Targeted Financing from the Estonian Ministry of Science and Education (grant number SF0180142s08); the Development Fund of the University of Tartu (grant number SP1GVARENG); the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and through FP7 (grant number 313010). EGCUT were further supported by the US National Institute of Health (grant number R01DK075787). A.K.M. was supported by an American Diabetes Association Mentor-Based Postdoctoral Fellowship (#7-12-MN- 02). The BioVU dataset used in the analyses described were obtained from Vanderbilt University Medical Centers BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Genome-wide genotyping was funded by NIH grants RC2GM092618 from NIGMS/OD and U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access publication charges for this article was provided by a block grant from Research Councils UK to the University of Cambridge

Testing the role of predicted gene knockouts in human anthropometric trait variation

National Heart, Lung, and Blood Institute (NHLBI) S.L. is funded by a Canadian Institutes of Health Research Banting doctoral scholarship. G.L. is funded by Genome Canada and Génome Québec; the Canada Research Chairs program; and the Montreal Heart Institute Foundation. C.M.L. is supported by Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A); and the Li Ka Shing Foundation. N.S. is funded by National Institutes of Health (grant numbers HL088456, HL111089, HL116747). The Mount Sinai BioMe Biobank Program is supported by the Andrea and Charles Bronfman Philanthropies. GO ESP is supported by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO, RC2 HL-102924 to WHISP). The ESP exome sequencing was performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL- 102926 to SeattleGO). EGCUT work was supported through the Estonian Genome Center of University of Tartu by the Targeted Financing from the Estonian Ministry of Science and Education (grant number SF0180142s08); the Development Fund of the University of Tartu (grant number SP1GVARENG); the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and through FP7 (grant number 313010). EGCUT were further supported by the US National Institute of Health (grant number R01DK075787). A.K.M. was supported by an American Diabetes Association Mentor-Based Postdoctoral Fellowship (#7-12-MN- 02). The BioVU dataset used in the analyses described were obtained from Vanderbilt University Medical Centers BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Genome-wide genotyping was funded by NIH grants RC2GM092618 from NIGMS/OD and U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access publication charges for this article was provided by a block grant from Research Councils UK to the University of Cambridge

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

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Species Richness and Range Size of the Terrestrial Mammals of the World: Biological Signal within Mathematical Constraints

We explore global spatial diversity patterns for terrestrial mammals using as a tool range-diversity plots. These plots display simultaneously information about the number of species in localities and their spatial covariance in composition. These are highly informative, as we show by linking range-diversity plots with maps and by highlighting the correspondences between well defined regions of the plots with geographical regions or with taxonomic groups. Range-diversity plots are mathematically constrained by the lines of maximum and minimum mean covariance in species composition. We show how regions in the range-diversity plot corresponding to the line of maximum covariance correspond to large continental masses, and regions near the lower limit of the range-diversity plot correspond to archipelagos and mountain ranges. We show how curves of constant covariance correspond to nested faunas. Finally, we show that the observed distribution of the covariance range has significantly longer tails than random, with clear geographic correspondences. At the scale of our data we found that range-diversity plots reveal biodiversity patterns that cannot be replicated by null models, and correspond to conspicuous terrain features and taxonomic groupings

Persistent C-peptide secretion in Type 1 diabetes and its relationship to the genetic architecture of diabetes

Background: The objective of this cross-sectional study was to explore the relationship of detectable C-peptide secretion in type 1 diabetes to clinical features and to the genetic architecture of diabetes. Methods: C-peptide was measured in an untimed serum sample in the SDRNT1BIO cohort of 6076 Scottish people with clinically diagnosed type 1 diabetes or latent autoimmune diabetes of adulthood. Risk scores at loci previously associated with type 1 and type 2 diabetes were calculated from publicly available summary statistics. Results: Prevalence of detectable C-peptide varied from 19% in those with onset before age 15 and duration greater than 15 years to 92% in those with onset after age 35 and duration less than 5 years. Twenty-nine percent of variance in C-peptide levels was accounted for by associations with male gender, late age at onset and short duration. The SNP heritability of residual C-peptide secretion adjusted for gender, age at onset and duration was estimated as 26%. Genotypic risk score for type 1 diabetes was inversely associated with detectable C-peptide secretion: the most strongly associated loci were the HLA and INS gene regions. A risk score for type 1 diabetes based on the HLA DR3 and DQ8-DR4 serotypes was strongly associated with early age at onset and inversely associated with C-peptide persistence. For C-peptide but not age at onset, there were strong associations with risk scores for type 1 and type 2 diabetes that were based on SNPs in the HLA region but not accounted for by HLA serotype. Conclusions: Persistence of C-peptide secretion varies widely in people clinically diagnosed as type 1 diabetes. C-peptide persistence is influenced by variants in the HLA region that are different from those determining risk of early-onset type 1 diabetes. Known risk loci for diabetes account for only a small proportion of the genetic effects on C-peptide persistence

Distinct gene subsets in pterygia formation and recurrence: dissecting complex biological phenomenon using genome wide expression data

<p>Abstract</p> <p>Background</p> <p>Pterygium is a common ocular surface disease characterized by fibrovascular invasion of the cornea and is sight-threatening due to astigmatism, tear film disturbance, or occlusion of the visual axis. However, the mechanisms for formation and post-surgical recurrence of pterygium are not understood, and a valid animal model does not exist. Here, we investigated the possible mechanisms of pterygium pathogenesis and recurrence.</p> <p>Methods</p> <p>First we performed a genome wide expression analysis (human Affymetrix Genechip, >22000 genes) with principal component analysis and clustering techniques, and validated expression of key molecules with PCR. The controls for this study were the un-involved conjunctival tissue of the same eye obtained during the surgical resection of the lesions. Interesting molecules were further investigated with immunohistochemistry, Western blots, and comparison with tear proteins from pterygium patients.</p> <p>Results</p> <p>Principal component analysis in pterygium indicated a signature of matrix-related structural proteins, including fibronectin-1 (both splice-forms), collagen-1A2, keratin-12 and small proline rich protein-1. Immunofluorescence showed strong expression of keratin-6A in all layers, especially the superficial layers, of pterygium epithelium, but absent in the control, with up-regulation and nuclear accumulation of the cell adhesion molecule CD24 in the pterygium epithelium. Western blot shows increased protein expression of beta-microseminoprotein, a protein up-regulated in human cutaneous squamous cell carcinoma. Gene products of 22 up-regulated genes in pterygium have also been found by us in human tears using nano-electrospray-liquid chromatography/mass spectrometry after pterygium surgery. Recurrent disease was associated with up-regulation of sialophorin, a negative regulator of cell adhesion, and <it>never in mitosis a</it>-5, known to be involved in cell motility.</p> <p>Conclusion</p> <p>Aberrant wound healing is therefore a key process in this disease, and strategies in wound remodeling may be appropriate in halting pterygium or its recurrence. For patients demonstrating a profile of 'recurrence', it may be necessary to manage as a poorer prognostic case and perhaps, more adjunctive treatment after resection of the primary lesion.</p

CCAAT/Enhancer Binding Protein alpha uses distinct domains to prolong pituitary cells in the Growth 1 and DNA Synthesis phases of the cell cycle

BACKGROUND: A number of transcription factors coordinate differentiation by simultaneously regulating gene expression and cell proliferation. CCAAT/enhancer binding protein alpha (C/EBPα) is a basic/leucine zipper transcription factor that integrates transcription with proliferation to regulate the differentiation of tissues involved in energy balance. In the pituitary, C/EBPα regulates the transcription of a key metabolic regulator, growth hormone. RESULTS: We examined the consequences of C/EBPα expression on proliferation of the transformed, mouse GHFT1-5 pituitary progenitor cell line. In contrast to mature pituitary cells, GHFT1-5 cells do not contain C/EBPα. Ectopic expression of C/EBPα in the progenitor cells resulted in prolongation of both growth 1 (G1) and the DNA synthesis (S) phases of the cell cycle. Transcription activation domain 1 and 2 of C/EBPα were required for prolongation of G1, but not of S. Some transcriptionally inactive derivatives of C/EBPα remained competent for G1 and S phase prolongation. C/EBPα deleted of its leucine zipper dimerization functions was as effective as full-length C/EBPα in prolonging G1 and S. CONCLUSION: We found that C/EBPα utilizes mechanistically distinct activities to prolong the cell cycle in G1 and S in pituitary progenitor cells. G1 and S phase prolongation did not require that C/EBPα remained transcriptionally active or retained the ability to dimerize via the leucine zipper. G1, but not S, arrest required a domain overlapping with C/EBPα transcription activation functions 1 and 2. Separation of mechanisms governing proliferation and transcription permits C/EBPα to regulate gene expression independently of its effects on proliferation