PaperPlayer biorxiv genetics

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.10.245175v1?rss=1

Authors: Peterson, T., Zuo, T., Su, W.

Abstract:

Transposable elements (TEs) are DNA sequences that can mobilize and proliferate throughout eukaryotic genomes. Previous studies have shown that in plant genomes, TEs can influence gene expression in various ways such as inserting in introns or exons to alter transcript structure and content, and providing novel promoters and regulatory elements to generate new regulatory patterns. Furthermore, TEs can also regulate gene expression at the epigenetic level by modifying chromatin structure, changing DNA methylation status and generating small RNAs. In this study, we demonstrated that Ac/fAc transposable elements are able to induce ectopic gene expression by duplicating and shuffling enhancer elements. Ac/fAc elements belong to the hAT family of Class II TEs. They can undergo standard transposition events, which involve the two termini of a single transposon, or alternative transposition events which involve the termini of two different, nearby elements. Our previous studies have shown that alternative transposition can generate various genome rearrangements such as deletions, duplications, inversions, translocations and Composite Insertions (CIs). We identified over 50 independent cases of CIs generated by Ac/fAc alternative transposition and analyzed 10 of them in detail. We show that these CIs induced ectopic expression of the maize pericarp color 2 (p2) gene, which encodes a Myb-related protein. All the CIs analyzed contain sequences including a transcriptional enhancer derived from the nearby p1 gene, suggesting that the CI-induced activation of p2 is effected by mobilization of the p1 enhancer. This is further supported by analysis of a mutant in which the CI is excised and p2 expression is lost. These results show that alternative transposition events are not only able to induce genome rearrangements, but also generate Composite Insertions that can control gene expression.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.06.240721v1?rss=1

Authors: Belonogova, N. M., Zorkoltseva, I. V., Tsepilov, Y. A., Axenovich, T. I.

Abstract:

Recent genome-wide studies have reported about 600 genes potentially in[fl]uencing neuroticism. Little is known about the mechanisms of their action. Here, we aimed to conduct a more detailed analysis of genes whose polymorphisms can regulate the level of neuroticism. Using UK Biobank-based GWAS summary statistics, we performed a gene-based association analysis using four sets of genetic variants within a gene differing in their protein coding properties. To guard against the influence of strong GWAS signals outside the gene, we used the specially designed procedure. As a result, we identified 190 genes associated with neuroticism due to their polymorphisms. Thirty eight of these genes were novel. Within all genes identified, we distinguished two slightly overlapping groups comprising genes that demonstrated association when using protein-coding and non-coding SNPs. Many genes from the first group included potentially pathogenic variants. For some genes from the second group, we found evidence of pleiotropy with gene expression. We demonstrated that the association of almost two hundred known genes could be inflated by the GWAS signals outside the gene. Using bioinformatics analysis, we prioritized the neuroticism genes and showed that the genes influencing the trait by their polymorphisms are the most appropriate candidate genes.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.06.239178v1?rss=1

Authors: Tubbs, J. D., Hwang, L.-D., Luong, J., Evans, D. M., Sham, P. C.

Abstract:

Disaggregation and estimation of genetic effects from offspring and parents has long been of interest to statistical geneticists. Recently, technical and methodological advances have made the genome-wide and loci-specific estimation of direct offspring and parental genetic nurture effects more possible. However, unbiased estimation using these methods requires datasets where both parents and at least one child have been genotyped, which are relatively scarce. Our group has recently developed a method and accompanying software (IMPISH; Hwang et al., 2020) which is able to impute missing parental genotypes from observed data on sibships and estimate their effects on an offspring phenotype conditional on the effects of genetic transmission. However, this method is unable to disentangle maternal and paternal effects, which may differ in magnitude and direction. Here, we introduce an extension to the original IMPISH routine which takes advantage of all available nuclear families to impute parent-specific missing genotypes and obtain asymptotically unbiased estimates of genetic effects on offspring phenotypes. We apply this this method to data from related individuals in the UK Biobank, showing concordance with previous estimates of maternal genetic effects on offspring birthweight. We also conduct the first GWAS jointly estimating offspring-, maternal-, and paternal-specific genetic effects on body-mass index.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.07.242214v1?rss=1

Authors: Marcus, J. H., Ha, W., Barber, R. F., Novembre, J.

Abstract:

An important feature in spatial population genetic data is often "isolation-by-distance," where genetic differentiation tends to increase as individuals become more geographically distant. Recently, Petkova et al. (2016) developed a statistical method called Estimating Effective Migration Surfaces (EEMS) for visualizing spatially heterogeneous isolation-by-distance on a geographic map. While EEMS is a powerful tool for depicting spatial population structure, it can suffer from slow runtimes. Here we develop a related method called Fast Estimation of Effective Migration Surfaces (FEEMS). FEEMS uses a Gaussian Markov Random Field in a penalized likelihood framework that allows for efficient optimization and output of effective migration surfaces. Further, the efficient optimization facilitates the inference of migration parameters per edge in the graph, rather than per node (as in EEMS). When tested with coalescent simulations, FEEMS accurately recovers effective migration surfaces with complex gene-flow histories, including those with anisotropy. Applications of FEEMS to population genetic data from North American gray wolves shows it to perform comparably to EEMS, but with solutions obtained orders of magnitude faster. Overall, FEEMS expands the ability of users to quickly visualize and interpret spatial structure in their data.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.07.241554v1?rss=1

Authors: Methorst, R., de Borst, G. J., Pasterkamp, G., van der Laan, S. W.

Abstract:

Background and aims: Atherosclerosis is a lipid-driven inflammatory disease presumably initiated by endothelial activation. Low vascular shear stress is known for its ability to activate endothelial cells. Differential DNA methylation (DNAm) is a relatively unexplored player in atherosclerotic disease development and endothelial dysfunction. Literature search revealed that expression of 11 genes have been found to be associated with differential DNAm due to low shear stress in endothelial cells. We hypothesized a causal relationship between DNAm of shear stress associated genes in human carotid plaque and increased risk of cardiovascular disease. Methods: Using Mendelian randomisation (MR) analysis, we explored the potential causal role of DNAm of shear stress associated genes on cardiovascular disease risk. We used genetic and DNAm data of 442 carotid endarterectomy derived advanced plaques from the Athero-Express Biobank Study for quantitative trait loci (QTL) discovery and performed MR analysis using these QTLs and GWAS summary statistics of coronary artery disease (CAD) and ischemic stroke (IS). Results: We discovered 9 methylation QTLs in plaque for differentially methylated shear stress associated genes. We found no significant effect of shear stress gene promotor methylation and increased risk of CAD and IS. Conclusions: Differential methylation of shear stress associated genes in advanced atherosclerotic plaques in unlikely to increase cardiovascular risk.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.07.239103v1?rss=1

Authors: Lyu, B., Tsvetanov, K. A., Tyler, L. K., Clarke, A., Cam-CAN,, Amos, W.

Abstract:

Identifying the genetic variations impacting human brain structure and further affecting cognitive functions, will enhance our understanding of the fundamental bases of cognition. In this study, we take two different approaches to this issue: classical genome-wide association analysis (GWAS) and a relatedness-based regression approach (REL) to search for associations between genotype and brain structural measures of gray matter and white matter. Instead of searching genetic variants by testing the association between a phenotype trait and the genotype of each single-nucleotide polymorphism (SNP) as in GWAS, REL takes advantage of multiple SNPs within a genomic window as a single measure, which potentially find associations wherever the functional SNP is in linkage disequilibrium (LD) with SNPs that have been sampled. We also conducted a simulation analysis to systemically compare GWAS and REL with respect to different levels of LD. Both methods succeed in identifying genetic variations associated with regional and global brain structural measures, though they tend to give complementary results due to the very different aspects of genetic properties used. Simulation results suggest that GWAS outperforms REL when the signal is relatively weak. However, the collective effects due to local LD boost the performance of REL with increasing signal strength, resulting in better performance than GWAS. Our study suggests that the optimal approach may vary across the genome and that pre-testing for LD could allow GWAS to be preferred where LD is high and REL to be used where LD is low, or the local pattern of LD is complex.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.07.240887v1?rss=1

Authors: Martell, H. J., Griffin, D. K., Wass, M. N.

Abstract:

The availability of thousands of individual genomes provides many opportunities to understand genetic variation and the relationship to phenotype, particularly disease. However, this remains challenging as it is often difficult to identify if a non-synonymous variant alters protein structure and function. Many computational methods have been developed but they typically interpret individual variants in isolation, despite the possibility of variant-variant interactions. Here, we combine the genetic variation data present in the 1000 genome project with protein structural data to identify variant-variant interactions within individual human genomes. We find more than 4,000 combinations of variants that located close in 3D dimensional structure and more than 1,200 in protein-protein interfaces. Many variant combinations include amino acid changes that are compensatory such as maintaining charges or functional groups, thus supporting that these are coevolutionary events. This highlights the need for variant interpretation and precision medicine to consider the gestalt effects of variants.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.05.239087v1?rss=1

Authors: Joshi, B. D., Singh, V. K., Singh, H., Singh, A., Singh, S. K., Chandra, K., Sharma, L. K., Thakur, M.

Abstract:

In the present study, we explored the intraspecific genetic variation and phylogeographic relationship among all the reported species in the genus Naemorhedus distributed in a wide range of habitats. The Bayesian based phylogeny demonstrated that Himalayan goral, is a highly diverged species from the other reported species of gorals. We claim the presence of two valid sub-species of Himalayan goral, i.e. N. g. bedfordi and N. g. goral, distributed in the western and central Himalaya, respectively. The comparative analysis with the inclusion of data available from different ranges, suggests the presence of plausibly six species of gorals across the distribution with a few valid subspecies. Further, we report that N. griseus is a valid species and not the synonyms of N. goral considering the observed discrepancy in the available sequences. We recommend all the sub-species present at distant locations may be considered as Evolutionary Significant Units (ESUs) and, therefore, appeal to provide them special attention for long term conservation and management.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.06.239137v1?rss=1

Authors: Genty, G., Guarnizo, C. E., Ramirez, J. P., Barrientos, L., Crawford, A. J.

Abstract:

The complex topography of the species-rich northern Andes creates heterogeneous environmental landscapes that are hypothesized to have promoted population fragmentation and diversification by vicariance, gradients and/or the adaptation of species. Previous phylogenetic work on the Palm Rocket Frog (Anura: Aromobatidae: Rheobates spp.), endemic to mid-elevation forests of Colombia, suggested valleys were important in promoting divergence between lineages. In this study, we use a spatially, multi-locus population genetic approach of two mitochondrial and four nuclear genes from 25 samples representing the complete geographic range of the genus to delimit species and test for landscape effects on genetic divergence within Rheobates. We tested three landscape genetic models: isolation by distance, isolation by resistance, and isolation by environment. Bayesian species delimitation (BPP) and a Poisson Tree Process (PTP) model both recovered five highly divergent genetic lineages within Rheobates, rather than the three inferred in a previous study. We found that an isolation by environment provided the only variable significantly correlated with genetic distances for both mitochondrial and nuclear genes, suggesting that local adaptation may have a role driving the genetic divergence within this genus of frogs. Thus, genetic divergence in Rheobates may be driven by the local environments where these frogs live, even more so that by the environmental characteristics of the intervening regions among populations (i.e., geographic barriers).

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.05.238162v1?rss=1

Authors: Shi, Q., Jiang, X., Zhang, Y., Gao, J., Zhang, H., Ali, A., Zhao, D., Bao, J., Iqbal, F., Jiang, L.

Abstract:

Exploring the genetic basis of human infertility is currently under intensive investigation. However, only a handful of genes are validated in animal models as disease-causing genes in infertile men. Thus, to better understand the genetic basis of spermatogenesis in human and to bridge the knowledge gap between human and other animal species, we have constructed FertilityOnline database, which is a resource that integrates the functional genes reported in literature related to spermatogenesis into an existing spermatogenic database, SpermatogenesisOnline 1.0. Additional features like functional annotation and statistical analysis of genetic variants of human genes, are also incorporated into FertilityOnline. By searching this database, users can focus on the top candidate genes associated with infertility and can perform enrichment analysis to instantly refine the number of candidates in a user-friendly web interface. Clinical validation of this database is established by the identification of novel causative mutations in SYCE1 and STAG3 in azoospermia men. In conclusion, FertilityOnline is not only an integrated resource for analysis of spermatogenic genes, but also a useful tool that facilitates to study underlying genetic basis of male infertility. Availability: FertilityOnline can be freely accessed at http://mcg.ustc.edu.cn/bsc/spermgenes2.0/index.html.

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