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Nuclear pore complexes (NPCs) are the gateways of the nuclear envelope mediating transport between cytoplasm and nucleus. They form huge complexes of 125 MDa in vertebrates and consist of about 30 different nucleoporins present in multiple copies in each complex. Here, we describe pathogenic variants in the nucleoporin 93 (NUP93) associated with an autosomal recessive form of congenital ataxia. Two rare compound heterozygous variants of NUP93 were identified by whole exome sequencing in two brothers with isolated cerebellar atrophy: one missense variant (p.R537W) results in a protein which does not localize to NPCs and cannot functionally replace the wild type protein, whereas the variant (p.F699L) apparently supports NPC assembly. In addition to its recently described pathological role in steroid-resistant nephrotic syndrome, our work identifies NUP93 as a candidate gene for non-progressive congenital ataxia.

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Neurodevelopmental disorders can be caused by many different genetic abnormalities that are individually rare but collectively common. Specific genetic causes, including certain copy number variants and single-gene mutations, are shared among disorders that are thought to be clinically distinct. This evidence of variability in the clinical manifestations of individual genetic variants and sharing of genetic causes among clinically distinct brain disorders is consistent with the concept of developmental brain dysfunction, a term we use to describe the abnormal brain function underlying a group of neurodevelopmental and neuropsychiatric disorders and to encompass a subset of various clinical diagnoses. Although many pathogenic genetic variants are currently thought to be variably penetrant, we hypothesise that when disorders encompassed by developmental brain dysfunction are considered as a group, the penetrance will approach 100%. The penetrance is also predicted to approach 100% when the phenotype being considered is a specific trait, such as intelligence or autistic-like social impairment, and the trait could be assessed using a continuous, quantitative measure to compare probands with non-carrier family members rather than a qualitative, dichotomous trait and comparing probands with the healthy population.

South America has a complex demographic history shaped by multiple migration and admixture events in pre- and post-colonial times. Settled over 14,000 years ago by Native Americans, South America has experienced migrations of European and African individuals, similar to other regions in the Americas. However, the timing and magnitude of these events resulted in markedly different patterns of admixture throughout Latin America. We use genome-wide SNP data for 437 admixed individuals from 5 countries (Colombia, Ecuador, Peru, Chile, and Argentina) to explore the population structure and demographic history of South American Latinos. We combined these data with population reference panels from Africa, Asia, Europe and the Americas to perform global ancestry analysis and infer the subcontinental origin of the European and Native American ancestry components of the admixed individuals. By applying ancestry-specific PCA analyses we find that most of the European ancestry in South American Latinos is from the Iberian Peninsula; however, many individuals trace their ancestry back to Italy, especially within Argentina. We find a strong gradient in the Native American ancestry component of South American Latinos associated with country of origin and the geography of local indigenous populations. For example, Native American genomic segments in Peruvians show greater affinities with Andean indigenous peoples like Quechua and Aymara, whereas Native American haplotypes from Colombians tend to cluster with Amazonian and coastal tribes from northern South America. Using ancestry tract length analysis we modeled post-colonial South American migration history as the youngest in Latin America during European colonization (9-14 generations ago), with an additional strong pulse of European migration occurring between 3 and 9 generations ago. These genetic footprints can impact our understanding of population-level differences in biomedical traits and, thus, inform future medical genetic studies in the region.

Hispanic/Latino populations possess a complex genetic structure that reflects recent admixture among and potentially ancient substructure within Native American, European, and West African source populations. Here, we quantify genome-wide patterns of SNP and haplotype variation among 100 individuals with ancestry from Ecuador, Colombia, Puerto Rico, and the Dominican Republic genotyped on the Illumina 610-Quad arrays and 112 Mexicans genotyped on Affymetrix 500K platform. Intersecting these data with previously collected high-density SNP data from 4,305 individuals, we use principal component analysis and clustering methods FRAPPE and STRUCTURE to investigate genome-wide patterns of African, European, and Native American population structure within and among Hispanic/Latino populations. Comparing autosomal, X and Y chromosome, and mtDNA variation, we find evidence of a significant sex bias in admixture proportions consistent with disproportionate contribution of European male and Native American female ancestry to present-day populations. We also find that patterns of linkage-disequilibria in admixed Hispanic/Latino populations are largely affected by the admixture dynamics of the populations, with faster decay of LD in populations of higher African ancestry. Finally, using the locus-specific ancestry inference method LAMP, we reconstruct fine-scale chromosomal patterns of admixture. We document moderate power to differentiate among potential subcontinental source populations within the Native American, European, and African segments of the admixed Hispanic/Latino genomes. Our results suggest future genome-wide association scans in Hispanic/Latino populations may require correction for local genomic ancestry at a subcontinental scale when associating differences in the genome with disease risk, progression, and drug efficacy, as well as for admixture mapping.

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.

There is great scientific and popular interest in understanding the genetic history of populations in the Americas. We wish to understand when different regions of the continent were inhabited, where settlers came from, and how current inhabitants relate genetically to earlier populations. Recent studies unraveled parts of the genetic history of the continent using genotyping arrays and uniparental markers. The 1000 Genomes Project provides a unique opportunity for improving our understanding of population genetic history by providing over a hundred sequenced low coverage genomes and exomes from Colombian (CLM), Mexican-American (MXL), and Puerto Rican (PUR) populations. Here, we explore the genomic contributions of African, European, and especially Native American ancestry to these populations. Estimated Native American ancestry is 48% in MXL, 25% in CLM, and 13% in PUR. Native American ancestry in PUR is most closely related to populations surrounding the Orinoco River basin, confirming the Southern American ancestry of the Taíno people of the Caribbean. We present new methods to estimate the allele frequencies in the Native American fraction of the populations, and model their distribution using a demographic model for three ancestral Native American populations. These ancestral populations likely split in close succession: the most likely scenario, based on a peopling of the Americas 16 thousand years ago (kya), supports that the MXL Ancestors split 12.2kya, with a subsequent split of the ancestors to CLM and PUR 11.7kya. The model also features effective populations of 62,000 in Mexico, 8,700 in Colombia, and 1,900 in Puerto Rico. Modeling Identity-by-descent (IBD) and ancestry tract length, we show that post-contact populations also differ markedly in their effective sizes and migration patterns, with Puerto Rico showing the smallest effective size and the earlier migration from Europe. Finally, we compare IBD and ancestry assignments to find evidence for relatedness among European founders to the three populations.

Naturally blond hair in Solomon Islanders maps to a missense mutation in a gene associated with pigmentation. Naturally blond hair is rare in humans and found almost exclusively in Europe and Oceania. Here, we identify an arginine-to-cysteine change at a highly conserved residue in tyrosinase-related protein 1 (TYRP1) as a major determinant of blond hair in Solomon Islanders. This missense mutation is predicted to affect catalytic activity of TYRP1 and causes blond hair through a recessive mode of inheritance. The mutation is at a frequency of 26% in the Solomon Islands, is absent outside of Oceania, represents a strong common genetic effect on a complex human phenotype, and highlights the importance of examining genetic associations worldwide.

An ultrasound-assisted method was used for the extraction of phenolics from defatted black cumin seeds (Nigella sativa L.), and the effects of several extraction factors on the total phenolic content and DPPH radical scavenging activity were investigated. To improve the extraction efficiency of phenolics from black cumin seed by ultrasonic-assisted extraction, the optimal extraction conditions were determined as follows: ethanol concentration of 59.1%, extraction temperature of 44.6 °C and extraction time of 32.5 min. Under these conditions, the total phenolic content and DPPH radical scavenging activity increased by about 70% and 38%, respectively, compared with conventional extraction. Furthermore, a complementary quantitative analysis of individual phenolic compounds was carried out using the HPLC-UV technique. The phenolic composition revealed high amounts of epicatechin (1.88–2.37 mg/g) and rutin (0.96–1.21 mg/g) in the black cumin seed extracts. Ultrasonic-assisted extraction can be a useful extraction method for the recovery of polyphenols from defatted black cumin seeds.

International policies and targets to globally reduce carbon dioxide emissions have contributed to increasing penetration of distributed energy resources (DER) in low‐voltage distribution networks. The growth of technologies such as rooftop photovoltaic (PV) systems and electric vehicles (EV) has, to date, not been rigorously monitored and record keeping is deficient. Non‐intrusive load monitoring (NILM) methods contribute to the effective integration of clean technologies within existing distribution networks. In this study, a novel NILM method is developed for the identification of DER electrical signatures from smart meter net‐demand data. Electrical profiles of EV and PV systems are allocated within aggregated measurements including conventional electrical appliances. Data from several households in the United States are used to train and test classification and regression models. The usage of conventional machine learning techniques provides the proposed algorithm with fast processing times and low system complexity, key factors needed to differentiate highly variable DER power profiles from other loads. The results confirm the effectiveness of the proposed methodology to individually classify DER with performance metrics of 96% for EV and 99% for PV. This demonstrates the potential of the proposed method as an embedded function of smart meters to increase observability in distribution networks.