Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel

Imputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced at low depth (average 7x), aiming to exhaustively characterize genetic variation down to 0.1% minor allele frequency in the British population. Here we demonstrate the value of this resource for improving imputation accuracy at rare and low-frequency variants in both a UK and an Italian population. We show that large increases in imputation accuracy can be achieved by re-phasing WGS reference panels after initial genotype calling. We also present a method for combining WGS panels to improve variant coverage and downstream imputation accuracy, which we illustrate by integrating 7,562 WGS haplotypes from the UK10K project with 2,184 haplotypes from the 1000 Genomes Project. Finally, we introduce a novel approximation that maintains speed without sacrificing imputation accuracy for rare variants

Understanding the genetic complexity of puberty timing across the allele frequency spectrum

Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease

TCTEX1D2 mutations underlie Jeune asphyxiating thoracic dystrophy with impaired retrograde intraflagellar transport

Tiina Paunio on työryhmän UK10K jäsen.The analysis of individuals with ciliary chondrodysplasias can shed light on sensitive mechanisms controlling ciliogenesis and cell signalling that are essential to embryonic development and survival. Here we identify TCTEX1D2 mutations causing Jeune asphyxiating thoracic dystrophy with partially penetrant inheritance. Loss of TCTEX1D2 impairs retrograde intraflagellar transport (IFT) in humans and the protist Chlamydomonas, accompanied by destabilization of the retrograde IFT dynein motor. We thus define TCTEX1D2 as an integral component of the evolutionarily conserved retrograde IFT machinery. In complex with several IFT dynein light chains, it is required for correct vertebrate skeletal formation but may be functionally redundant under certain conditions.Peer reviewe

Open Dataset for Predicting Pilgrim Activities for Crowd Management During Hajj Using Wearable Sensors

This study aims to create and examine a multimodal dataset to enhance crowd management during the Hajj seasons. Sixty-four participants were engaged in Hajj rituals such as Tawaf, Saai, prayer, and Doaa providing location and peripheral physiological data, collected and annotated using a custom-made smartphone application. The collected data was leveraged to conduct a comprehensive analysis, specifically focusing on the classification of the type of Hajj activity, level of fatigue, and emotional states based on peripheral physiological signals. Three deep learning classification models were developed and validated using feedforward neural networks. The models achieved satisfactory accuracy scores in classifying the type of Hajj activity (41.71%), level of fatigue (85.27%), and emotional states (82.47%). While presenting a straightforward use case, this research chiefly provides decision makers and the scientific community with a statistically significant open data set aside with a deep learning architecture capable of characterizing crowd behavior for the purpose of automating crowd management and monitoring

Exploring the Associations and Molecular Impacts of miR-146a/rs2910164 and miR-196a2/rs185070757 with Rheumatoid Arthritis in a Pakistani Population

Introduction: MicroRNAs (miRNAs) are a new class of molecules that participate in post-transcriptional regulation of gene expression and hence have been reported to have a crucial role in the pathogenesis of rheumatoid arthritis (RA). We aimed to investigate the association of miR-146a rs2910164 (G/C) and miR-196a2 rs185070757 (T/G) with RA susceptibility in Pakistani patients and to bioinformatically predict the molecular function of these miRNAs. Methods: A case-control study on 600 individuals was conducted, including 300 RA patients and 300 matching healthy controls. Genotyping was performed by tetra-primer amplification of refractory mutation system-polymerase chain reaction, and the association between variants and RA was statistically determined using different models. Results: For the variant rs2910164 (G/C) in miR-146a, no difference in genotype distribution was observed between RA cases and controls, as determined using co-dominant (χ2 = 4.33; p = 0.114), homozygous dominant (C/C vs. G/G + C/G) (OR = 0.740 [0.531–1.032]; p = 0.091), homozygous recessive (G/G vs. C/C + G/C) (odds ratio [OR] = 01.432 [0.930–2.206]; p = 0.126), heterozygous (G/C vs. C/C + G/G) (OR = 1.084 [0.786–1.494]; p = 0.682), and additive (OR 0.778 [0.617–0.981]; p = 0.039) models. Similarly, the GT genotype in the rs185070757 (T/G) miR-196a2 variant did not differ between cases and controls with any models (p > 0.05). For the first time, we report no association of miR-146a rs2910164 (G/C) and miR-196a2 rs185070757 (T/G) with RA in a Pakistani population. A subsequent bioinformatic analysis revealed that the CC genotype of miR-146a rs2910164 might have a protective role against RA pathogenesis, with no effect observed with the miR-196a2 rs185070757. Conclusion: Our findings suggest that these miRNAs might have little-to-no impact on the RA pathogenesis in the Pakistani population

Workflow of the study.

Interleukin-17F (IL-17F), considered a pro-inflammatory cytokine, has been shown to contribute to skeletal tissue degradation and hence chronic inflammation in rheumatoid arthritis (RA). In this study we utilized bioinformatics tools to analyze the effect of three exonic SNPs (rs2397084, rs11465553, and rs763780) on the structure and function of the IL-17F gene, and evaluated their association with RA in Pakistani patients. The predicted deleterious and damaging effects of identified genetic variants were assessed through the utilization of multiple bioinformatics tools including PROVEAN, SNP&GO, SIFT, and PolyPhen2. Structural and functional effects of these variants on protein structures were evaluated through the use of additional tools such as I-Mutant, MutPred, and ConSurf. Three-dimensional (3D) models of both the wild-type and mutant proteins were constructed through the utilization of I-TASSER software, with subsequent structural comparisons between the models conducted through the use of the TM-align score. A total of 500 individuals, 250 cases and 250 controls, were genotyped through Tri-ARMS-PCR method and the resultant data was statistically analyzed using various inheritance models. Our bioinformatics analysis showed significant structural differences for wild type and mutant protein (TM-scores and RMSD values were 0.85934 and 2.34 for rs2397084 (E126G), 0.87388 and 2.49 for rs11465553 (V155I), and 0.86572 and 0.86572 for rs763780 (H161R) with decrease stability for the later. Overall, these tools enabled us to predict that these variants are crucial in causing disease phenotypes. We further tested each of these single nucleotide variants for their association with RA. Our analysis revealed a strong positive association between the genetic variant rs763780 and the risk of developing rheumatoid arthritis (RA) at both the genotypic and allelic levels. The genotypic association was statistically significant[χ2 = 111.8; P value χ2 = 25.24; P value = 0.0001]. However, this variant did not show a significant association with RA at the allelic level [OR = 1.194 (0.930–1.531); P value = 0.183]. However, the distribution of variant rs2397084 was more or less random across our sample with no significant association either at genotypic and or allelic level. Put together, our association study and in silico prediction of decreasing of IL17-F protein stabilty confirmed that two SNPs, rs11465553 and rs763780 are crucial to the suscetibility of and showed that these RA in Pakistani patients.</div

Tri-Primer ARMS-PCR Gel Pattern of IL17-F Gene, a) IL-17F rs2397084 Genotypes, b) IL-17F <i>rs</i>11465553 Genotypes, and c) IL-17F rs763780 Genotypes.

Tri-Primer ARMS-PCR Gel Pattern of IL17-F Gene, a) IL-17F rs2397084 Genotypes, b) IL-17F rs11465553 Genotypes, and c) IL-17F rs763780 Genotypes.</p

Fig 2 -

3-D structural models visualized in Chimera 1.11 (a). wild type IL-17F protein (b). IL-17F superimposed with E126G mutant (c). IL-17F superimposed with V155I mutant (d). IL-17F superimposed with H161R mutant.</p

Statistical models used in association analysis.

Interleukin-17F (IL-17F), considered a pro-inflammatory cytokine, has been shown to contribute to skeletal tissue degradation and hence chronic inflammation in rheumatoid arthritis (RA). In this study we utilized bioinformatics tools to analyze the effect of three exonic SNPs (rs2397084, rs11465553, and rs763780) on the structure and function of the IL-17F gene, and evaluated their association with RA in Pakistani patients. The predicted deleterious and damaging effects of identified genetic variants were assessed through the utilization of multiple bioinformatics tools including PROVEAN, SNP&GO, SIFT, and PolyPhen2. Structural and functional effects of these variants on protein structures were evaluated through the use of additional tools such as I-Mutant, MutPred, and ConSurf. Three-dimensional (3D) models of both the wild-type and mutant proteins were constructed through the utilization of I-TASSER software, with subsequent structural comparisons between the models conducted through the use of the TM-align score. A total of 500 individuals, 250 cases and 250 controls, were genotyped through Tri-ARMS-PCR method and the resultant data was statistically analyzed using various inheritance models. Our bioinformatics analysis showed significant structural differences for wild type and mutant protein (TM-scores and RMSD values were 0.85934 and 2.34 for rs2397084 (E126G), 0.87388 and 2.49 for rs11465553 (V155I), and 0.86572 and 0.86572 for rs763780 (H161R) with decrease stability for the later. Overall, these tools enabled us to predict that these variants are crucial in causing disease phenotypes. We further tested each of these single nucleotide variants for their association with RA. Our analysis revealed a strong positive association between the genetic variant rs763780 and the risk of developing rheumatoid arthritis (RA) at both the genotypic and allelic levels. The genotypic association was statistically significant[χ2 = 111.8; P value χ2 = 25.24; P value = 0.0001]. However, this variant did not show a significant association with RA at the allelic level [OR = 1.194 (0.930–1.531); P value = 0.183]. However, the distribution of variant rs2397084 was more or less random across our sample with no significant association either at genotypic and or allelic level. Put together, our association study and in silico prediction of decreasing of IL17-F protein stabilty confirmed that two SNPs, rs11465553 and rs763780 are crucial to the suscetibility of and showed that these RA in Pakistani patients.</div