HERC1 deficiency causes osteopenia through transcriptional program dysregulation during bone remodeling.

Bone remodeling is a continuous process between bone-forming osteoblasts and bone-resorbing osteoclasts, with any imbalance resulting in metabolic bone disease, including osteopenia. The HERC1 gene encodes an E3 ubiquitin ligase that affects cellular processes by regulating the ubiquitination of target proteins, such as C-RAF. Of interest, an association exists between biallelic pathogenic sequence variants in the HERC1 gene and the neurodevelopmental disorder MDFPMR syndrome (macrocephaly, dysmorphic facies, and psychomotor retardation). Most pathogenic variants cause loss of HERC1 function, and the affected individuals present with features related to altered bone homeostasis. Herc1-knockout mice offer an excellent model in which to study the role of HERC1 in bone remodeling and to understand its role in disease. In this study, we show that HERC1 regulates osteoblastogenesis and osteoclastogenesis, proving that its depletion increases gene expression of osteoblastic makers during the osteogenic differentiation of mesenchymal stem cells. During this process, HERC1 deficiency increases the levels of C-RAF and of phosphorylated ERK and p38. The Herc1-knockout adult mice developed imbalanced bone homeostasis that presented as osteopenia in both sexes of the adult mice. By contrast, only young female knockout mice had osteopenia and increased number of osteoclasts, with the changes associated with reductions in testosterone and dihydrotestosterone levels. Finally, osteocytes isolated from knockout mice showed a higher expression of osteocytic genes and an increase in the Rankl/Opg ratio, indicating a relevant cell-autonomous role of HERC1 when regulating the transcriptional program of bone formation. Overall, these findings present HERC1 as a modulator of bone homeostasis and highlight potential therapeutic targets for individuals affected by pathological HERC1 variants.

Annotating and prioritizing genomic variants using the Ensembl Variant Effect Predictor-A tutorial.

The Ensembl Variant Effect Predictor (VEP) is a freely available, open-source tool for the annotation and filtering of genomic variants. It predicts variant molecular consequences using the Ensembl/GENCODE or RefSeq gene sets. It also reports phenotype associations from databases such as ClinVar, allele frequencies from studies including gnomAD, and predictions of deleteriousness from tools such as Sorting Intolerant From Tolerant and Combined Annotation Dependent Depletion. Ensembl VEP includes filtering options to customize variant prioritization. It is well supported and updated roughly quarterly to incorporate the latest gene, variant, and phenotype association information. Ensembl VEP analysis can be performed using a highly configurable, extensible command-line tool, a Representational State Transfer application programming interface, and a user-friendly web interface. These access methods are designed to suit different levels of bioinformatics experience and meet different needs in terms of data size, visualization, and flexibility. In this tutorial, we will describe performing variant annotation using the Ensembl VEP web tool, which enables sophisticated analysis through a simple interface.

Prioritising positively selected variants in whole-genome sequencing data using FineMAV.

BACKGROUND: In population genomics, polymorphisms that are highly differentiated between geographically separated populations are often suggestive of Darwinian positive selection. Genomic scans have highlighted several such regions in African and non-African populations, but only a handful of these have functional data that clearly associates candidate variations driving the selection process. Fine-Mapping of Adaptive Variation (FineMAV) was developed to address this in a high-throughput manner using population based whole-genome sequences generated by the 1000 Genomes Project. It pinpoints positively selected genetic variants in sequencing data by prioritizing high frequency, population-specific and functional derived alleles. RESULTS: We developed a stand-alone software that implements the FineMAV statistic. To graphically visualise the FineMAV scores, it outputs the statistics as bigWig files, which is a common file format supported by many genome browsers. It is available as a command-line and graphical user interface. The software was tested by replicating the FineMAV scores obtained using 1000 Genomes Project African, European, East and South Asian populations and subsequently applied to whole-genome sequencing datasets from Singapore and China to highlight population specific variants that can be subsequently modelled. The software tool is publicly available at https://github.com/fadilla-wahyudi/finemav . CONCLUSIONS: The software tool described here determines genome-wide FineMAV scores, using low or high-coverage whole-genome sequencing datasets, that can be used to prioritize a list of population specific, highly differentiated candidate variants for in vitro or in vivo functional screens. The tool displays these scores on the human genome browsers for easy visualisation, annotation and comparison between different genomic regions in worldwide human populations.

A Positively Selected MAGEE2 LoF Allele Is Associated with Sexual Dimorphism in Human Brain Size and Shows Similar Phenotypes in Magee2 Null Mice.

A nonsense allele at rs1343879 in human MAGEE2 on chromosome X has previously been reported as a strong candidate for positive selection in East Asia. This premature stop codon causing ∼80% protein truncation is characterized by a striking geographical pattern of high population differentiation: common in Asia and the Americas (up to 84% in the 1000 Genomes Project East Asians) but rare elsewhere. Here, we generated a Magee2 mouse knockout mimicking the human loss-of-function mutation to study its functional consequences. The Magee2 null mice did not exhibit gross abnormalities apart from enlarged brain structures (13% increased total brain area, P = 0.0022) in hemizygous males. The area of the granular retrosplenial cortex responsible for memory, navigation, and spatial information processing was the most severely affected, exhibiting an enlargement of 34% (P = 3.4×10-6). The brain size in homozygous females showed the opposite trend of reduced brain size, although this did not reach statistical significance. With these insights, we performed human association analyses between brain size measurements and rs1343879 genotypes in 141 Chinese volunteers with brain MRI scans, replicating the sexual dimorphism seen in the knockout mouse model. The derived stop gain allele was significantly associated with a larger volume of gray matter in males (P = 0.00094), and smaller volumes of gray (P = 0.00021) and white (P = 0.0015) matter in females. It is unclear whether or not the observed neuroanatomical phenotypes affect behavior or cognition, but it might have been the driving force underlying the positive selection in humans.

Accessing Livestock Resources in Ensembl.

Genome assembly is cheaper, more accurate and more automated than it has ever been. This is due to a combination of more cost-efficient chemistries, new sequencing technologies and better algorithms. The livestock community has been at the forefront of this new wave of genome assembly, generating some of the highest quality vertebrate genome sequences. Ensembl's goal is to add functional and comparative annotation to these genomes, through our gene annotation, genomic alignments, gene trees, regulatory, and variation data. We run computationally complex analyses in a high throughput and consistent manner to help accelerate downstream science. Our livestock resources are continuously growing in both breadth and depth. We annotate reference genome assemblies for newly sequenced species and regularly update annotation for existing genomes. We are the only major resource to support the annotation of breeds and other non-reference assemblies. We currently provide resources for 13 pig breeds, maternal and paternal haplotypes for hybrid cattle and various other non-reference or wild type assemblies for livestock species. Here, we describe the livestock data present in Ensembl and provide protocols for how to view data in our genome browser, download via it our FTP site, manipulate it via our tools and interact with it programmatically via our REST API.

How well do we understand the basis of classic selective sweeps in humans?

Classic selective sweeps occur when positive selection increases a variant's frequency from low to high in a population, and underlie some long-studied human characteristics such as variation in skin, hair or eye colour. In such well-studied 'gold standard' examples, a known variant has been associated with a plausible phenotype and underlying selective force. Signatures of classic sweeps have more recently been detected in population-genetic data independently of any prior information about the corresponding phenotype or selective force, and usually without suggesting any insights into these. Motivated by the need to understand such candidates, we first review the gold standards and show that our understanding of them is often incomplete or unconvincing; only two of the examples we consider are compellingly explained. We assess approaches for large-scale association of classic sweep candidate variants to phenotypes and selective forces, test these on the gold standards, and discuss the standards of evidence needed to adequately understand a selective sweep.

FineMAV: prioritizing candidate genetic variants driving local adaptations in human populations.

We present a new method, Fine-Mapping of Adaptive Variation (FineMAV), which combines population differentiation, derived allele frequency, and molecular functionality to prioritize positively selected candidate variants for functional follow-up. We calibrate and test FineMAV using eight experimentally validated "gold standard" positively selected variants and simulations. FineMAV has good sensitivity and a low false discovery rate. Applying FineMAV to the 1000 Genomes Project Phase 3 SNP dataset, we report many novel selected variants, including ones in TGM3 and PRSS53 associated with hair phenotypes that we validate using available independent data. FineMAV is widely applicable to sequence data from both human and other species.

Continuity and Admixture in the Last Five Millennia of Levantine History from Ancient Canaanite and Present-Day Lebanese Genome Sequences.

The Canaanites inhabited the Levant region during the Bronze Age and established a culture that became influential in the Near East and beyond. However, the Canaanites, unlike most other ancient Near Easterners of this period, left few surviving textual records and thus their origin and relationship to ancient and present-day populations remain unclear. In this study, we sequenced five whole genomes from ∼3,700-year-old individuals from the city of Sidon, a major Canaanite city-state on the Eastern Mediterranean coast. We also sequenced the genomes of 99 individuals from present-day Lebanon to catalog modern Levantine genetic diversity. We find that a Bronze Age Canaanite-related ancestry was widespread in the region, shared among urban populations inhabiting the coast (Sidon) and inland populations (Jordan) who likely lived in farming societies or were pastoral nomads. This Canaanite-related ancestry derived from mixture between local Neolithic populations and eastern migrants genetically related to Chalcolithic Iranians. We estimate, using linkage-disequilibrium decay patterns, that admixture occurred 6,600-3,550 years ago, coinciding with recorded massive population movements in Mesopotamia during the mid-Holocene. We show that present-day Lebanese derive most of their ancestry from a Canaanite-related population, which therefore implies substantial genetic continuity in the Levant since at least the Bronze Age. In addition, we find Eurasian ancestry in the Lebanese not present in Bronze Age or earlier Levantines. We estimate that this Eurasian ancestry arrived in the Levant around 3,750-2,170 years ago during a period of successive conquests by distant populations.

The occurrence of PAHs and faecal sterols in Dublin Bay and their influence on sedimentary microbial communities.

The source, concentration, and potential impact of sewage discharge and incomplete organic matter (OM) combustion on sedimentary microbial populations were assessed in Dublin Bay, Ireland. Polycyclic aromatic hydrocarbons (PAHs) and faecal steroids were investigated in 30 surface sediment stations in the bay. Phospholipid fatty acid (PLFA) content at each station was used to identify and quantify the broad microbial groups present and the impact of particle size, total organic carbon (%TOC), total hydrogen (%H) and total nitrogen (%N) was also considered. Faecal sterols were found to be highest in areas with historical point sources of sewage discharge. PAH distribution was more strongly associated with areas of deposition containing high %silt and %clay content, suggesting that PAHs are from diffuse sources such as rainwater run-off and atmospheric deposition. The PAHs ranged from 12 to 3072ng/g, with 10 stations exceeding the suggested effect range low (ERL) for PAHs in marine sediments. PAH isomer pair ratios and sterol ratios were used to determine the source and extent of pollution. PLFAs were not impacted by sediment type or water depth but were strongly correlated to, and influenced by PAH and sewage levels. Certain biomarkers such as 10Me16:0, i17:0 and a17:0 were closely associated with PAH polluted sediments, while 16:1ω9, 16:1ω7c, Cy17:0, 18:1ω6, i16:0 and 15:0 all have strong positive correlations with faecal sterols. Overall, the results show that sedimentary microbial communities are impacted by anthropogenic pollution.

Mountain gorilla genomes reveal the impact of long-term population decline and inbreeding.

Mountain gorillas are an endangered great ape subspecies and a prominent focus for conservation, yet we know little about their genomic diversity and evolutionary past. We sequenced whole genomes from multiple wild individuals and compared the genomes of all four Gorilla subspecies. We found that the two eastern subspecies have experienced a prolonged population decline over the past 100,000 years, resulting in very low genetic diversity and an increased overall burden of deleterious variation. A further recent decline in the mountain gorilla population has led to extensive inbreeding, such that individuals are typically homozygous at 34% of their sequence, leading to the purging of severely deleterious recessive mutations from the population. We discuss the causes of their decline and the consequences for their future survival.

Fine mapping of type 1 diabetes susceptibility loci and evidence for colocalization of causal variants with lymphoid gene enhancers.

Genetic studies of type 1 diabetes (T1D) have identified 50 susceptibility regions, finding major pathways contributing to risk, with some loci shared across immune disorders. To make genetic comparisons across autoimmune disorders as informative as possible, a dense genotyping array, the Immunochip, was developed, from which we identified four new T1D-associated regions (P < 5 × 10(-8)). A comparative analysis with 15 immune diseases showed that T1D is more similar genetically to other autoantibody-positive diseases, significantly most similar to juvenile idiopathic arthritis and significantly least similar to ulcerative colitis, and provided support for three additional new T1D risk loci. Using a Bayesian approach, we defined credible sets for the T1D-associated SNPs. The associated SNPs localized to enhancer sequences active in thymus, T and B cells, and CD34(+) stem cells. Enhancer-promoter interactions can now be analyzed in these cell types to identify which particular genes and regulatory sequences are causal.

A Selective Sweep on a Deleterious Mutation in CPT1A in Arctic Populations.

Arctic populations live in an environment characterized by extreme cold and the absence of plant foods for much of the year and are likely to have undergone genetic adaptations to these environmental conditions in the time they have been living there. Genome-wide selection scans based on genotype data from native Siberians have previously highlighted a 3 Mb chromosome 11 region containing 79 protein-coding genes as the strongest candidates for positive selection in Northeast Siberians. However, it was not possible to determine which of the genes might be driving the selection signal. Here, using whole-genome high-coverage sequence data, we identified the most likely causative variant as a nonsynonymous G>A transition (rs80356779; c.1436C>T [p.Pro479Leu] on the reverse strand) in CPT1A, a key regulator of mitochondrial long-chain fatty-acid oxidation. Remarkably, the derived allele is associated with hypoketotic hypoglycemia and high infant mortality yet occurs at high frequency in Canadian and Greenland Inuits and was also found at 68% frequency in our Northeast Siberian sample. We provide evidence of one of the strongest selective sweeps reported in humans; this sweep has driven this variant to high frequency in circum-Arctic populations within the last 6-23 ka despite associated deleterious consequences, possibly as a result of the selective advantage it originally provided to either a high-fat diet or a cold environment.

A bacterial enrichment study and overview of the extractable lipids from paleosols in the Dry Valleys, Antarctica: implications for future Mars reconnaissance.

The Dry Valleys of Antarctica are one of the coldest and driest environments on Earth with paleosols in selected areas that date to the emplacement of tills by warm-based ice during the Early Miocene. Cited as an analogue to the martian surface, the ability of the Antarctic environment to support microbial life-forms is a matter of special interest, particularly with the upcoming NASA/ESA 2018 ExoMars mission. Lipid biomarkers were extracted and analyzed by gas chromatography--mass spectrometry to assess sources of organic carbon and evaluate the contribution of microbial species to the organic matter of the paleosols. Paleosol samples from the ice-free Dry Valleys were also subsampled and cultivated in a growth medium from which DNA was extracted with the explicit purpose of the positive identification of bacteria. Several species of bacteria were grown in solution and the genus identified. A similar match of the data to sequenced DNA showed that Alphaproteobacteria, Gammaproteobacteria, Bacteriodetes, and Actinobacteridae species were cultivated. The results confirm the presence of bacteria within some paleosols, but no assumptions have been made with regard to in situ activity at present. These results underscore the need not only to further investigate Dry Valley cryosols but also to develop reconnaissance strategies to determine whether such likely Earth-like environments on the Red Planet also contain life.

Predicting sorption of pharmaceuticals and personal care products onto soil and digested sludge using artificial neural networks.

A comprehensive analytical investigation of the sorption behaviour of a large selection of over-the-counter, prescribed pharmaceuticals and illicit drugs to agricultural soils and freeze-dried digested sludges is presented. Batch sorption experiments were carried out to identify which compounds could potentially concentrate in soils as a result of biosolid enrichment. Analysis of aqueous samples was carried out directly using liquid chromatography-tandem mass spectrometry (LC-MS/MS). For solids analysis, combined pressurised liquid extraction and solid phase extraction methods were used prior to LC-MS/MS. Solid-water distribution coefficients (K(d)) were calculated based on slopes of sorption isotherms over a defined concentration range. Molecular descriptors such as log P, pK(a), molar refractivity, aromatic ratio, hydrophilic factor and topological surface area were collected for all solutes and, along with generated K(d) data, were incorporated as a training set within a developed artificial neural network to predict K(d) for all solutes within both sample types. Therefore, this work represents a novel approach using combined and cross-validated analytical and computational techniques to confidently study sorption modes within the environment. The logarithm plots of predicted versus experimentally determined K(d) are presented which showed excellent correlation (R(2) > 0.88), highlighting that artificial neural networks could be used as a predictive tool for this application. To evaluate the developed model, it was used to predict K(d) for meclofenamic acid, mefenamic acid, ibuprofen and furosemide and subsequently compared to experimentally determined values in soil. Ratios of experimental/predicted K(d) values were found to be 1.00, 1.00, 1.75 and 1.65, respectively.