Graphical Analysis of Spatio-Temporal Patterns in Forage Quality

Due to the highly structured topography in Switzerland, crop growth conditions vary within short distances. Differences in altitude are one of the major causes for climatic variation resulting in significant spatio-temporal effects on forage quality in terms of nutrient content and feeding value, particularly in grassland dominated regions. It is one of the goals of the Swiss feed database to support queries that visualize and quantify the temporal and spatial influence on feed quality

Regional genetic correlations highlight relationships between neurodegenerative disease loci and the immune system

Neurodegenerative diseases, including Alzheimer’s and Parkinson’s disease, are devastating complex diseases resulting in physical and psychological burdens on patients and their families. There have been important efforts to understand their genetic basis leading to the identification of disease risk-associated loci involved in several molecular mechanisms, including immune-related pathways. Regional, in contrast to genome-wide, genetic correlations between pairs of immune and neurodegenerative traits have not been comprehensively explored, but could uncover additional immune-mediated risk-associated loci. Here, we systematically assess the role of the immune system in five neurodegenerative diseases by estimating regional genetic correlations between these diseases and immune-cell-derived single-cell expression quantitative trait loci (sc-eQTLs). We also investigate correlations between diseases and protein levels. We observe significant (FDR < 0.01) correlations between sc-eQTLs and neurodegenerative diseases across 151 unique genes, spanning both the innate and adaptive immune systems, across most diseases tested. With Parkinson’s, for instance, RAB7L1 in CD4+ naïve T cells is positively correlated and KANSL1-AS1 is negatively correlated across all adaptive immune cell types. Follow-up colocalization highlight candidate causal risk genes. The outcomes of this study will improve our understanding of the immune component of neurodegeneration, which can warrant repurposing of existing immunotherapies to slow disease progression

Local genetic correlations exist among neurodegenerative and neuropsychiatric diseases

Genetic correlation ([Formula: see text]) between traits can offer valuable insight into underlying shared biological mechanisms. Neurodegenerative diseases overlap neuropathologically and often manifest comorbid neuropsychiatric symptoms. However, global [Formula: see text] analyses show minimal [Formula: see text] among neurodegenerative and neuropsychiatric diseases. Importantly, local [Formula: see text] s can exist in the absence of global relationships. To investigate this possibility, we applied LAVA, a tool for local [Formula: see text] analysis, to genome-wide association studies of 3 neurodegenerative diseases (Alzheimer's disease, Lewy body dementia and Parkinson's disease) and 3 neuropsychiatric disorders (bipolar disorder, major depressive disorder and schizophrenia). We identified several local [Formula: see text] s missed in global analyses, including between (i) all 3 neurodegenerative diseases and schizophrenia and (ii) Alzheimer's and Parkinson's disease. For those local [Formula: see text] s identified in genomic regions containing disease-implicated genes, such as SNCA, CLU and APOE, incorporation of expression quantitative trait loci identified genes that may drive genetic overlaps between diseases. Collectively, we demonstrate that complex genetic relationships exist among neurodegenerative and neuropsychiatric diseases, highlighting putative pleiotropic genomic regions and genes. These findings imply sharing of pathogenic processes and the potential existence of common therapeutic targets

Analysis of subcellular RNA fractions demonstrates significant genetic regulation of gene expression in human brain post-transcriptionally

Gaining insight into the genetic regulation of gene expression in human brain is key to the interpretation of genome-wide association studies for major neurological and neuropsychiatric diseases. Expression quantitative trait loci (eQTL) analyses have largely been used to achieve this, providing valuable insights into the genetic regulation of steady-state RNA in human brain, but not distinguishing between molecular processes regulating transcription and stability. RNA quantification within cellular fractions can disentangle these processes in cell types and tissues which are challenging to model in vitro. We investigated the underlying molecular processes driving the genetic regulation of gene expression specific to a cellular fraction using allele-specific expression (ASE). Applying ASE analysis to genomic and transcriptomic data from paired nuclear and cytoplasmic fractions of anterior prefrontal cortex, cerebellar cortex and putamen tissues from 4 post-mortem neuropathologically-confirmed control human brains, we demonstrate that a significant proportion of genetic regulation of gene expression occurs post-transcriptionally in the cytoplasm, with genes undergoing this form of regulation more likely to be synaptic. These findings have implications for understanding the structure of gene expression regulation in human brain, and importantly the interpretation of rapidly growing single-nucleus brain RNA-sequencing and eQTL datasets, where cytoplasm-specific regulatory events could be missed

Regulatory sites for splicing in human basal ganglia are enriched for disease-relevant information

International Parkinson’s Disease Genomics Consortium (IPDGC), UK Brain Expression Consortium (UKBEC).Genome-wide association studies have generated an increasing number of common genetic variants associated with neurological and psychiatric disease risk. An improved understanding of the genetic control of gene expression in human brain is vital considering this is the likely modus operandum for many causal variants. However, human brain sampling complexities limit the explanatory power of brain-related expression quantitative trait loci (eQTL) and allele-specific expression (ASE) signals. We address this, using paired genomic and transcriptomic data from putamen and substantia nigra from 117 human brains, interrogating regulation at different RNA processing stages and uncovering novel transcripts. We identify disease-relevant regulatory loci, find that splicing eQTLs are enriched for regulatory information of neuron-specific genes, that ASEs provide cell-specific regulatory information with evidence for cellular specificity, and that incomplete annotation of the brain transcriptome limits interpretation of risk loci for neuropsychiatric disease. This resource of regulatory data is accessible through our web server, http://braineacv2.inf.um.es/.Mina Ryten, David Zhang, and Karishma D’Sa were supported by the UK Medical Research Council (MRC) through the award of Tenure-track Clinician Scientist Fellowship to Mina Ryten (MR/N008324/1). Sebastian Guelfi was supported by Alzheimer’s Research UK through the award of a PhD Fellowship (ARUK-PhD2014-16). Regina Reynolds was supported through the award of a Leonard Wolfson Doctoral Training Fellowship in Neurodegeneration

Human-lineage-specific genomic elements are associated with neurodegenerative disease and APOE transcript usage.

Knowledge of genomic features specific to the human lineage may provide insights into brain-related diseases. We leverage high-depth whole genome sequencing data to generate a combined annotation identifying regions simultaneously depleted for genetic variation (constrained regions) and poorly conserved across primates. We propose that these constrained, non-conserved regions (CNCRs) have been subject to human-specific purifying selection and are enriched for brain-specific elements. We find that CNCRs are depleted from protein-coding genes but enriched within lncRNAs. We demonstrate that per-SNP heritability of a range of brain-relevant phenotypes are enriched within CNCRs. We find that genes implicated in neurological diseases have high CNCR density, including APOE, highlighting an unannotated intron-3 retention event. Using human brain RNA-sequencing data, we show the intron-3-retaining transcript to be more abundant in Alzheimer's disease with more severe tau and amyloid pathological burden. Thus, we demonstrate potential association of human-lineage-specific sequences in brain development and neurological disease

Human-lineage-specific genomic elements are associated with neurodegenerative disease and APOE transcript usage

Knowledge of genomic features specific to the human lineage may provide insights into brain-related diseases. We leverage high-depth whole genome sequencing data to generate a combined annotation identifying regions simultaneously depleted for genetic variation (constrained regions) and poorly conserved across primates. We propose that these constrained, non-conserved regions (CNCRs) have been subject to human-specific purifying selection and are enriched for brain-specific elements. We find that CNCRs are depleted from protein-coding genes but enriched within lncRNAs. We demonstrate that per-SNP heritability of a range of brain-relevant phenotypes are enriched within CNCRs. We find that genes implicated in neurological diseases have high CNCR density, including APOE, highlighting an unannotated intron-3 retention event. Using human brain RNA-sequencing data, we show the intron-3-retaining transcript to be more abundant in Alzheimer?s disease with more severe tau and amyloid pathological burden. Thus, we demonstrate potential association of human-lineage-specific sequences in brain development and neurological disease.FUNDING: Acknowledgements The authors are grateful to the participants in the Religious Order Study, the Memory and Aging Project. Z.C. and R.H.R. were supported by grants from the Leonard Wolfson Foundation. M.R. was supported by the United Kingdom Medical Research Council (MRC) through the award of a Tenure Track Clinician Scientist Fellowship (MR/ N008324/1). J.H. was supported by the UK Dementia Research Institute which receives its funding from DRI Limited, funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK. J.H. has also been funded by the Medical Research Council (award MR/N026004/1), Wellcome Trust (award 202903/Z/16/Z), Dolby Family Fund and National Institute for Health Research University College London Hospitals Biomedical Research Centre. J.B. is supported through the Science and Technology Agency, Séneca Foundation, CARM, Spain (research project 00007/COVI/20)

Importance of Different Types of Prior Knowledge in Selecting Genome‐Wide Findings for Follow‐Up

Biological plausibility and other prior information could help select genome‐wide association ( GWA ) findings for further follow‐up, but there is no consensus on which types of knowledge should be considered or how to weight them. We used experts’ opinions and empirical evidence to estimate the relative importance of 15 types of information at the single‐nucleotide polymorphism ( SNP ) and gene levels. Opinions were elicited from 10 experts using a two‐round Delphi survey. Empirical evidence was obtained by comparing the frequency of each type of characteristic in SNP s established as being associated with seven disease traits through GWA meta‐analysis and independent replication, with the corresponding frequency in a randomly selected set of SNP s. SNP and gene characteristics were retrieved using a specially developed bioinformatics tool. Both the expert and the empirical evidence rated previous association in a meta‐analysis or more than one study as conferring the highest relative probability of true association, whereas previous association in a single study ranked much lower. High relative probabilities were also observed for location in a functional protein domain, although location in a region evolutionarily conserved in vertebrates was ranked high by the data but not by the experts. Our empirical evidence did not support the importance attributed by the experts to whether the gene encodes a protein in a pathway or shows interactions relevant to the trait. Our findings provide insight into the selection and weighting of different types of knowledge in SNP or gene prioritization, and point to areas requiring further research.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/96262/1/gepi21705.pd