Whereas efficient and sensitive nanoheaters and nanothermometers are demanding tools in modern bio- and nanomedicine, joining both features in a single nanoparticle still remains a real challenge, ...despite the recent progress achieved, most of it within the last year. Here we demonstrate a successful realization of this challenge. The heating is magnetically induced, the temperature readout is optical, and the ratiometric thermometric probes are dual-emissive Eu3+/Tb3+ lanthanide complexes. The low thermometer heat capacitance (0.021·K–1) and heater/thermometer resistance (1 K·W–1), the high temperature sensitivity (5.8%·K–1 at 296 K) and uncertainty (0.5 K), the physiological working temperature range (295–315 K), the readout reproducibility (>99.5%), and the fast time response (0.250 s) make the heater/thermometer nanoplatform proposed here unique. Cells were incubated with the nanoparticles, and fluorescence microscopy permits the mapping of the intracellular local temperature using the pixel-by-pixel ratio of the Eu3+/Tb3+ intensities. Time-resolved thermometry under an ac magnetic field evidences the failure of using macroscopic thermal parameters to describe heat diffusion at the nanoscale.
Local-ancestry inference is an important step in the genetic analysis of fully sequenced human genomes. Current methods can only detect continental-level ancestry (i.e., European versus African ...versus Asian) accurately even when using millions of markers. Here, we present RFMix, a powerful discriminative modeling approach that is faster (∼30×) and more accurate than existing methods. We accomplish this by using a conditional random field parameterized by random forests trained on reference panels. RFMix is capable of learning from the admixed samples themselves to boost performance and autocorrect phasing errors. RFMix shows high sensitivity and specificity in simulated Hispanics/Latinos and African Americans and admixed Europeans, Africans, and Asians. Finally, we demonstrate that African Americans in HapMap contain modest (but nonzero) levels of Native American ancestry (∼0.4%).
The human genetics community needs robust protocols that enable secure sharing of genomic data from participants in genetic research. Beacons are web servers that answer allele-presence queries—such ...as “Do you have a genome that has a specific nucleotide (e.g., A) at a specific genomic position (e.g., position 11,272 on chromosome 1)?”—with either “yes” or “no.” Here, we show that individuals in a beacon are susceptible to re-identification even if the only data shared include presence or absence information about alleles in a beacon. Specifically, we propose a likelihood-ratio test of whether a given individual is present in a given genetic beacon. Our test is not dependent on allele frequencies and is the most powerful test for a specified false-positive rate. Through simulations, we showed that in a beacon with 1,000 individuals, re-identification is possible with just 5,000 queries. Relatives can also be identified in the beacon. Re-identification is possible even in the presence of sequencing errors and variant-calling differences. In a beacon constructed with 65 European individuals from the 1000 Genomes Project, we demonstrated that it is possible to detect membership in the beacon with just 250 SNPs. With just 1,000 SNP queries, we were able to detect the presence of an individual genome from the Personal Genome Project in an existing beacon. Our results show that beacons can disclose membership and implied phenotypic information about participants and do not protect privacy a priori. We discuss risk mitigation through policies and standards such as not allowing anonymous pings of genetic beacons and requiring minimum beacon sizes.
Demographic models built from genetic data play important roles in illuminating prehistorical events and serving as null models in genome scans for selection. We introduce an inference method based ...on the joint frequency spectrum of genetic variants within and between populations. For candidate models we numerically compute the expected spectrum using a diffusion approximation to the one-locus, two-allele Wright-Fisher process, involving up to three simultaneous populations. Our approach is a composite likelihood scheme, since linkage between neutral loci alters the variance but not the expectation of the frequency spectrum. We thus use bootstraps incorporating linkage to estimate uncertainties for parameters and significance values for hypothesis tests. Our method can also incorporate selection on single sites, predicting the joint distribution of selected alleles among populations experiencing a bevy of evolutionary forces, including expansions, contractions, migrations, and admixture. We model human expansion out of Africa and the settlement of the New World, using 5 Mb of noncoding DNA resequenced in 68 individuals from 4 populations (YRI, CHB, CEU, and MXL) by the Environmental Genome Project. We infer divergence between West African and Eurasian populations 140 thousand years ago (95% confidence interval: 40-270 kya). This is earlier than other genetic studies, in part because we incorporate migration. We estimate the European (CEU) and East Asian (CHB) divergence time to be 23 kya (95% c.i.: 17-43 kya), long after archeological evidence places modern humans in Europe. Finally, we estimate divergence between East Asians (CHB) and Mexican-Americans (MXL) of 22 kya (95% c.i.: 16.3-26.9 kya), and our analysis yields no evidence for subsequent migration. Furthermore, combining our demographic model with a previously estimated distribution of selective effects among newly arising amino acid mutations accurately predicts the frequency spectrum of nonsynonymous variants across three continental populations (YRI, CHB, CEU).
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The vast majority of genome-wide association studies (GWASs) are performed in Europeans, and their transferability to other populations is dependent on many factors (e.g., linkage disequilibrium, ...allele frequencies, genetic architecture). As medical genomics studies become increasingly large and diverse, gaining insights into population history and consequently the transferability of disease risk measurement is critical. Here, we disentangle recent population history in the widely used 1000 Genomes Project reference panel, with an emphasis on populations underrepresented in medical studies. To examine the transferability of single-ancestry GWASs, we used published summary statistics to calculate polygenic risk scores for eight well-studied phenotypes. We identify directional inconsistencies in all scores; for example, height is predicted to decrease with genetic distance from Europeans, despite robust anthropological evidence that West Africans are as tall as Europeans on average. To gain deeper quantitative insights into GWAS transferability, we developed a complex trait coalescent-based simulation framework considering effects of polygenicity, causal allele frequency divergence, and heritability. As expected, correlations between true and inferred risk are typically highest in the population from which summary statistics were derived. We demonstrate that scores inferred from European GWASs are biased by genetic drift in other populations even when choosing the same causal variants and that biases in any direction are possible and unpredictable. This work cautions that summarizing findings from large-scale GWASs may have limited portability to other populations using standard approaches and highlights the need for generalized risk prediction methods and the inclusion of more diverse individuals in medical genomics.
Most ancient specimens contain very low levels of endogenous DNA, precluding the shotgun sequencing of many interesting samples because of cost. Ancient DNA (aDNA) libraries often contain <1% ...endogenous DNA, with the majority of sequencing capacity taken up by environmental DNA. Here we present a capture-based method for enriching the endogenous component of aDNA sequencing libraries. By using biotinylated RNA baits transcribed from genomic DNA libraries, we are able to capture DNA fragments from across the human genome. We demonstrate this method on libraries created from four Iron Age and Bronze Age human teeth from Bulgaria, as well as bone samples from seven Peruvian mummies and a Bronze Age hair sample from Denmark. Prior to capture, shotgun sequencing of these libraries yielded an average of 1.2% of reads mapping to the human genome (including duplicates). After capture, this fraction increased substantially, with up to 59% of reads mapped to human and enrichment ranging from 6- to 159-fold. Furthermore, we maintained coverage of the majority of regions sequenced in the precapture library. Intersection with the 1000 Genomes Project reference panel yielded an average of 50,723 SNPs (range 3,062–147,243) for the postcapture libraries sequenced with 1 million reads, compared with 13,280 SNPs (range 217–73,266) for the precapture libraries, increasing resolution in population genetic analyses. Our whole-genome capture approach makes it less costly to sequence aDNA from specimens containing very low levels of endogenous DNA, enabling the analysis of larger numbers of samples.
Networks are ubiquitous in biology where they encode connectivity patterns at all scales of organization, from molecular to the biome. However, biological networks are noisy due to the limitations of ...measurement technology and inherent natural variation, which can hamper discovery of network patterns and dynamics. We propose Network Enhancement (NE), a method for improving the signal-to-noise ratio of undirected, weighted networks. NE uses a doubly stochastic matrix operator that induces sparsity and provides a closed-form solution that increases spectral eigengap of the input network. As a result, NE removes weak edges, enhances real connections, and leads to better downstream performance. Experiments show that NE improves gene-function prediction by denoising tissue-specific interaction networks, alleviates interpretation of noisy Hi-C contact maps from the human genome, and boosts fine-grained identification accuracy of species. Our results indicate that NE is widely applicable for denoising biological networks.
Deciphering the impact of genetic variants on gene regulation is fundamental to understanding human disease. Although gene regulation often involves long-range interactions, it is unknown to what ...extent non-coding genetic variants influence distal molecular phenotypes. Here, we integrate chromatin profiling for three histone marks in lymphoblastoid cell lines (LCLs) from 75 sequenced individuals with LCL-specific Hi-C and ChIA-PET-based chromatin contact maps to uncover one of the largest collections of local and distal histone quantitative trait loci (hQTLs). Distal QTLs are enriched within topologically associated domains and exhibit largely concordant variation of chromatin state coordinated by proximal and distal non-coding genetic variants. Histone QTLs are enriched for common variants associated with autoimmune diseases and enable identification of putative target genes of disease-associated variants from genome-wide association studies. These analyses provide insights into how genetic variation can affect human disease phenotypes by coordinated changes in chromatin at interacting regulatory elements.
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•Analyses of variations in histone marks reveal histone QTLs in regulatory elements•Physically interacting loci show genetically coordinated chromatin levels•Regulatory elements sharing hQTLs are enriched in topologically associated domains•hQTLs are enriched for GWAS SNPs and enable identification of putative target genes
Genetic variation in regulatory elements can effect coordinate changes in chromatin state and gene expression at both local and distal sites, reflecting associations in a three-dimensional context. Integrating information from expression, chromatin modification, and chromosome contact analyses provides a framework for assessing disease-associated mutations.
North African populations are distinct from sub-Saharan Africans based on cultural, linguistic, and phenotypic attributes; however, the time and the extent of genetic divergence between populations ...north and south of the Sahara remain poorly understood. Here, we interrogate the multilayered history of North Africa by characterizing the effect of hypothesized migrations from the Near East, Europe, and sub-Saharan Africa on current genetic diversity. We present dense, genome-wide SNP genotyping array data (730,000 sites) from seven North African populations, spanning from Egypt to Morocco, and one Spanish population. We identify a gradient of likely autochthonous Maghrebi ancestry that increases from east to west across northern Africa; this ancestry is likely derived from "back-to-Africa" gene flow more than 12,000 years ago (ya), prior to the Holocene. The indigenous North African ancestry is more frequent in populations with historical Berber ethnicity. In most North African populations we also see substantial shared ancestry with the Near East, and to a lesser extent sub-Saharan Africa and Europe. To estimate the time of migration from sub-Saharan populations into North Africa, we implement a maximum likelihood dating method based on the distribution of migrant tracts. In order to first identify migrant tracts, we assign local ancestry to haplotypes using a novel, principal component-based analysis of three ancestral populations. We estimate that a migration of western African origin into Morocco began about 40 generations ago (approximately 1,200 ya); a migration of individuals with Nilotic ancestry into Egypt occurred about 25 generations ago (approximately 750 ya). Our genomic data reveal an extraordinarily complex history of migrations, involving at least five ancestral populations, into North Africa.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Genome-wide scans for positively selected genes (PSGs) in mammals have provided insight into the dynamics of genome evolution, the genetic basis of differences between species, and the functions of ...individual genes. However, previous scans have been limited in power and accuracy owing to small numbers of available genomes. Here we present the most comprehensive examination of mammalian PSGs to date, using the six high-coverage genome assemblies now available for eutherian mammals. The increased phylogenetic depth of this dataset results in substantially improved statistical power, and permits several new lineage- and clade-specific tests to be applied. Of approximately 16,500 human genes with high-confidence orthologs in at least two other species, 400 genes showed significant evidence of positive selection (FDR<0.05), according to a standard likelihood ratio test. An additional 144 genes showed evidence of positive selection on particular lineages or clades. As in previous studies, the identified PSGs were enriched for roles in defense/immunity, chemosensory perception, and reproduction, but enrichments were also evident for more specific functions, such as complement-mediated immunity and taste perception. Several pathways were strongly enriched for PSGs, suggesting possible co-evolution of interacting genes. A novel Bayesian analysis of the possible "selection histories" of each gene indicated that most PSGs have switched multiple times between positive selection and nonselection, suggesting that positive selection is often episodic. A detailed analysis of Affymetrix exon array data indicated that PSGs are expressed at significantly lower levels, and in a more tissue-specific manner, than non-PSGs. Genes that are specifically expressed in the spleen, testes, liver, and breast are significantly enriched for PSGs, but no evidence was found for an enrichment for PSGs among brain-specific genes. This study provides additional evidence for widespread positive selection in mammalian evolution and new genome-wide insights into the functional implications of positive selection.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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