Fully unsupervised deep mode of action learning for phenotyping high-content cellular images

MOTIVATION

The identification and discovery of phenotypes from high content screening (HCS) images is a challenging task. Earlier works use image analysis pipelines to extract biological features, supervised training methods or generate features with neural networks pretrained on non-cellular images. We introduce a novel unsupervised deep learning algorithm to cluster cellular images with similar Mode-of-Action (MOA) together using only the images' pixel intensity values as input. It corrects for batch effect during training. Importantly, our method does not require the extraction of cell candidates and works from the entire images directly.

RESULTS

The method achieves competitive results on the labelled subset of the BBBC021 dataset with an accuracy of 97.09% for correctly classifying the MOA by nearest neighbors matching. Importantly, we can train our approach on unannotated datasets. Therefore, our method can discover novel MOAs and annotate unlabelled compounds. The ability to train end-to-end on the full resolution images makes our method easy to apply and allows it to further distinguish treatments by their effect on proliferation.

AVAILABILITY

Our code is available at https://github.com/Novartis/UMM-Discovery.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Dose and Schedule Determine Distinct Molecular Mechanisms Underlying the Efficacy of the p53-MDM2 Inhibitor HDM201

Activation of p53 by inhibitors of the p53-MDM2 interaction is being pursued as a therapeutic strategy in p53 wild-type cancers. Here, we report distinct mechanisms by which the novel, potent, and selective inhibitor of the p53-MDM2 interaction HDM201 elicits therapeutic efficacy when applied at various doses and schedules. Continuous exposure of HDM201 led to induction of p21 and delayed accumulation of apoptotic cells. By comparison, high-dose pulses of HDM201 were associated with marked induction of PUMA and a rapid onset of apoptosis. shRNA screens identified PUMA as a mediator of the p53 response specifically in the pulsed regimen. Consistent with this, the single high-dose HDM201 regimen resulted in rapid and marked induction of PUMA expression and apoptosis together with downregulation of Bcl-xL in vivo Knockdown of Bcl-xL was identified as the top sensitizer to HDM201 in vitro, and Bcl-xL was enriched in relapsing tumors from mice treated with intermittent high doses of HDM201. These findings define a regimen-dependent mechanism by which disruption of MDM2-p53 elicits therapeutic efficacy when given with infrequent dosing. In an ongoing HDM201 trial, the observed exposure-response relationship indicates that the molecular mechanism elicited by pulse dosing is likely reproducible in patients. These data support the clinical comparison of daily and intermittent regimens of p53-MDM2 inhibitors.Significance: Pulsed high doses versus sustained low doses of the p53-MDM2 inhibitor HDM201 elicit a proapoptotic response from wild-type p53 cancer cells, offering guidance to current clinical trials with this and other drugs that exploit the activity of p53. Cancer Res; 78(21); 6257-67. ©2018 AACR.

The genetic ancestry of African Americans, Latinos, and European Americans across the United States

Over the past 500 years, North America has been the site of ongoing mixing of Native Americans, European settlers, and Africans (brought largely by the trans-Atlantic slave trade), shaping the early history of what became the United States. We studied the genetic ancestry of 5,269 self-described African Americans, 8,663 Latinos, and 148,789 European Americans who are 23andMe customers and show that the legacy of these historical interactions is visible in the genetic ancestry of present-day Americans. We document pervasive mixed ancestry and asymmetrical male and female ancestry contributions in all groups studied. We show that regional ancestry differences reflect historical events, such as early Spanish colonization, waves of immigration from many regions of Europe, and forced relocation of Native Americans within the US. This study sheds light on the fine-scale differences in ancestry within and across the United States and informs our understanding of the relationship between racial and ethnic identities and genetic ancestry.

Reducing pervasive false-positive identical-by-descent segments detected by large-scale pedigree analysis

Analysis of genomic segments shared identical-by-descent (IBD) between individuals is fundamental to many genetic applications, from demographic inference to estimating the heritability of diseases, but IBD detection accuracy in nonsimulated data is largely unknown. In principle, it can be evaluated using known pedigrees, as IBD segments are by definition inherited without recombination down a family tree. We extracted 25,432 genotyped European individuals containing 2,952 father-mother-child trios from the 23andMe, Inc. data set. We then used GERMLINE, a widely used IBD detection method, to detect IBD segments within this cohort. Exploiting known familial relationships, we identified a false-positive rate over 67% for 2-4 centiMorgan (cM) segments, in sharp contrast with accuracies reported in simulated data at these sizes. Nearly all false positives arose from the allowance of haplotype switch errors when detecting IBD, a necessity for retrieving long (>6 cM) segments in the presence of imperfect phasing. We introduce HaploScore, a novel, computationally efficient metric that scores IBD segments proportional to the number of switch errors they contain. Applying HaploScore filtering to the IBD data at a precision of 0.8 produced a 13-fold increase in recall when compared with length-based filtering. We replicate the false IBD findings and demonstrate the generalizability of HaploScore to alternative data sources using an independent cohort of 555 European individuals from the 1000 Genomes project. HaploScore can improve the accuracy of segments reported by any IBD detection method, provided that estimates of the genotyping error rate and switch error rate are available.

Ancient structure in Africa unlikely to explain Neanderthal and non-African genetic similarity

Neanderthals have been shown to share more genetic variants with present-day non-Africans than Africans. Recent admixture between Neanderthals and modern humans outside of Africa was proposed as the most parsimonious explanation for this observation. However, the hypothesis of ancient population structure within Africa could not be ruled out as an alternative explanation. We use simulations to test whether the site frequency spectrum, conditioned on a derived Neanderthal and an ancestral Yoruba (African) nucleotide (the doubly conditioned site frequency spectrum [dcfs]), can distinguish between models that assume recent admixture or ancient population structure. We compare the simulations to the dcfs calculated from data taken from populations of European, Chinese, and Japanese descent in the Complete Genomics Diversity Panel. Simulations under a variety of plausible demographic parameters were used to examine the shape of the dcfs for both models. The observed shape of the dcfs cannot be explained by any set of parameter values used in the simulations of the ancient structure model. The dcfs simulations for the recent admixture model provide a good fit to the observed dcfs for non-Africans, thereby supporting the hypothesis that recent admixture with Neanderthals accounts for the greater similarity of Neanderthals to non-Africans than Africans.

Genetic signature of population fragmentation varies with mobility in seven bird species of a fragmented Kenyan cloud forest

Habitat fragmentation can restrict geneflow, reduce neighbourhood effective population size, and increase genetic drift and inbreeding in small, isolated habitat remnants. The extent to which habitat fragmentation leads to population fragmentation, however, differs among landscapes and taxa. Commonly, researchers use information on the current status of a species to predict population effects of habitat fragmentation. Such methods, however, do not convey information on species-specific responses to fragmentation. Here, we compare levels of past population differentiation, estimated from microsatellite genotypes, with contemporary dispersal rates, estimated from multi-strata capture-recapture models, to infer changes in mobility over time in seven sympatric, forest-dependent bird species of a Kenyan cloud forest archipelago. Overall, populations of sedentary species were more strongly differentiated and clustered compared to those of vagile ones, while geographical patterning suggested an important role of landscape structure in shaping genetic variation. However, five of seven species with broadly similar levels of genetic differentiation nevertheless differed substantially in their current dispersal rates. We conclude that post-fragmentation levels of vagility, without reference to past population connectivity, may not be the best predictor of how forest fragmentation affects the life history of forest-dependent species. As effective conservation strategies often hinge on accurate prediction of shifts in ecological and genetic relationships among populations, conservation practices based solely upon current population abundances or movements may, in the long term, prove to be inadequate.

Testing for ancient admixture between closely related populations

One enduring question in evolutionary biology is the extent of archaic admixture in the genomes of present-day populations. In this paper, we present a test for ancient admixture that exploits the asymmetry in the frequencies of the two nonconcordant gene trees in a three-population tree. This test was first applied to detect interbreeding between Neandertals and modern humans. We derive the analytic expectation of a test statistic, called the D statistic, which is sensitive to asymmetry under alternative demographic scenarios. We show that the D statistic is insensitive to some demographic assumptions such as ancestral population sizes and requires only the assumption that the ancestral populations were randomly mating. An important aspect of D statistics is that they can be used to detect archaic admixture even when no archaic sample is available. We explore the effect of sequencing error on the false-positive rate of the test for admixture, and we show how to estimate the proportion of archaic ancestry in the genomes of present-day populations. We also investigate a model of subdivision in ancestral populations that can result in D statistics that indicate recent admixture.

Genetic history of an archaic hominin group from Denisova Cave in Siberia

Using DNA extracted from a finger bone found in Denisova Cave in southern Siberia, we have sequenced the genome of an archaic hominin to about 1.9-fold coverage. This individual is from a group that shares a common origin with Neanderthals. This population was not involved in the putative gene flow from Neanderthals into Eurasians; however, the data suggest that it contributed 4-6% of its genetic material to the genomes of present-day Melanesians. We designate this hominin population 'Denisovans' and suggest that it may have been widespread in Asia during the Late Pleistocene epoch. A tooth found in Denisova Cave carries a mitochondrial genome highly similar to that of the finger bone. This tooth shares no derived morphological features with Neanderthals or modern humans, further indicating that Denisovans have an evolutionary history distinct from Neanderthals and modern humans.

A draft sequence of the Neandertal genome

Neandertals, the closest evolutionary relatives of present-day humans, lived in large parts of Europe and western Asia before disappearing 30,000 years ago. We present a draft sequence of the Neandertal genome composed of more than 4 billion nucleotides from three individuals. Comparisons of the Neandertal genome to the genomes of five present-day humans from different parts of the world identify a number of genomic regions that may have been affected by positive selection in ancestral modern humans, including genes involved in metabolism and in cognitive and skeletal development. We show that Neandertals shared more genetic variants with present-day humans in Eurasia than with present-day humans in sub-Saharan Africa, suggesting that gene flow from Neandertals into the ancestors of non-Africans occurred before the divergence of Eurasian groups from each other.