The Caribbean basin is home to some of the most complex interactions in recent history among previously diverged human populations. Here, we investigate the population genetic history of this region by characterizing patterns of genome-wide variation among 330 individuals from three of the Greater Antilles (Cuba, Puerto Rico, Hispaniola), two mainland (Honduras, Colombia), and three Native South American (Yukpa, Bari, and Warao) populations. We combine these data with a unique database of genomic variation in over 3,000 individuals from diverse European, African, and Native American populations. We use local ancestry inference and tract length distributions to test different demographic scenarios for the pre- and post-colonial history of the region. We develop a novel ancestry-specific PCA (ASPCA) method to reconstruct the sub-continental origin of Native American, European, and African haplotypes from admixed genomes. We find that the most likely source of the indigenous ancestry in Caribbean islanders is a Native South American component shared among inland Amazonian tribes, Central America, and the Yucatan peninsula, suggesting extensive gene flow across the Caribbean in pre-Columbian times. We find evidence of two pulses of African migration. The first pulse—which today is reflected by shorter, older ancestry tracts—consists of a genetic component more similar to coastal West African regions involved in early stages of the trans-Atlantic slave trade. The second pulse—reflected by longer, younger tracts—is more similar to present-day West-Central African populations, supporting historical records of later transatlantic deportation. Surprisingly, we also identify a Latino-specific European component that has significantly diverged from its parental Iberian source populations, presumably as a result of small European founder population size. We demonstrate that the ancestral components in admixed genomes can be traced back to distinct sub-continental source populations with far greater resolution than previously thought, even when limited pre-Columbian Caribbean haplotypes have survived.

Full sequencing of individual human genomes has greatly expanded our understanding of human genetic variation and population history. Here, we present a systematic analysis of 50 human genomes from 11 diverse global populations sequenced at high coverage. Our sample includes 12 individuals who have admixed ancestry and who have varying degrees of recent (within the last 500 years) African, Native American, and European ancestry. We found over 21 million single-nucleotide variants that contribute to a 1.75-fold range in nucleotide heterozygosity across diverse human genomes. This heterozygosity ranged from a high of one heterozygous site per kilobase in west African genomes to a low of 0.57 heterozygous sites per kilobase in segments inferred to have diploid Native American ancestry from the genomes of Mexican and Puerto Rican individuals. We show evidence of all three continental ancestries in the genomes of Mexican, Puerto Rican, and African American populations, and the genome-wide statistics are highly consistent across individuals from a population once ancestry proportions have been accounted for. Using a generalized linear model, we identified subtle variations across populations in the proportion of neutral versus deleterious variation and found that genome-wide statistics vary in admixed populations even once ancestry proportions have been factored in. We further infer that multiple periods of gene flow shaped the diversity of admixed populations in the Americas-70% of the European ancestry in today's African Americans dates back to European gene flow happening only 7-8 generations ago.

BackgroundDuctal carcinoma in situ (DCIS) is the earliest stage of breast cancer. During DCIS, tumor cells remain inside the mammary duct, growing under a microenvironment characterized by hypoxia, nutrient starvation, and waste product accumulation; this harsh microenvironment promotes genomic instability and eventually cell invasion. However, there is a lack of biomarkers to predict what patients will transition to a more invasive tumor or how DCIS cells manage to survive in this harsh microenvironment.MethodsIn this work, we have developed a microfluidic model that recapitulates the DCIS microenvironment. In the microdevice, a DCIS model cell line was grown inside a luminal mammary duct model, embedded in a 3D hydrogel with mammary fibroblasts. Cell behavior was monitored by confocal microscopy and optical metabolic imaging. Additionally, metabolite profile was studied by NMR whereas gene expression was analyzed by RT-qPCR.FindingsDCIS cell metabolism led to hypoxia and nutrient starvation; revealing an altered metabolism focused on glycolysis and other hypoxia-associated pathways. In response to this starvation and hypoxia, DCIS cells modified the expression of multiple genes, and a gradient of different metabolic phenotypes was observed across the mammary duct model. These genetic changes observed in the model were in good agreement with patient genomic profiles; identifying multiple compounds targeting the affected pathways. In this context, the hypoxia-activated prodrug tirapazamine selectively destroyed hypoxic DCIS cells.InterpretationThe results showed the capacity of the microfluidic model to mimic the DCIS structure, identifying multiple cellular adaptations to endure the hypoxia and nutrient starvation generated within the mammary duct. These findings may suggest new potential therapeutic directions to treat DCIS. In summary, given the lack of in vitro models to study DCIS, this microfluidic device holds great potential to find new DCIS predictors and therapies and translate them to the clinic.

Fine-scale population structure characterizes most continents and is especially pronounced in non-cosmopolitan populations. Roughly half of the world's population remains non-cosmopolitan and even populations within cities often assort along ethnic and linguistic categories. Barriers to random mating can be ecologically extreme, such as the Sahara Desert, or cultural, such as the Indian caste system. In either case, subpopulations accumulate genetic differences if the barrier is maintained over multiple generations. Genome-wide polymorphism data, initially with only a few hundred autosomal microsatellites, have clearly established differences in allele frequency not only among continental regions, but also within continents and within countries. We review recent evidence from the analysis of genome-wide polymorphism data for genetic boundaries delineating human population structure and the main demographic and genomic processes shaping variation, and discuss the implications of population structure for the distribution and discovery of disease-causing genetic variants, in the light of the imminent availability of sequencing data for a multitude of diverse human genomes.

BackgroundEnsuring genetic stability in pluripotent stem cell (PSC) cultures is essential for the development of successful cell therapies. Although most instances lead to failed experiments and go unreported in the literature, many laboratories have found the emergence of genetic abnormalities in PSCs when cultured in vitro for prolonged amounts of time. These cells are primarily cultured in non-physiological stiff substrates like tissue culture polystyrene (TCPS) which raises the possibility that the cause of these abnormalities may be influenced by substrate mechanics.FindingsIn order to investigate this, human PSCs were grown on substrates of varying stiffness such as a range of polyacrylamide formulations, TCPS, and borosilicate glass coverslips. These substrates allowed for the testing of a stiffness range from 5kPa to 64GPa. Two human induced PSC (iPSC) lines were analyzed in this study: 19-9-11 iPSCs and 19.7 clone F iPSCs. Centrosome and DNA staining revealed that 19-9-11 iPSCs range from 1–8.5 % abnormal mitoses under the different culture conditions. A range of 4.4–8.1 % abnormal mitoses was found for 19.7 clone F iPSCs.ConclusionsAbnormal cell division was not biased towards one particular substrate. It was confirmed by Analysis of Variance (ANOVA) and Tukey’s Honest Significant Difference test that there was no statistically significant difference between passage numbers, cell lines, or substrates.Electronic supplementary materialThe online version of this article (doi:10.1186/s12952-015-0042-8) contains supplementary material, which is available to authorized users.