We report on a genome-wide scan for introgression between the house mouse (Mus musculus domesticus) and the Algerian mouse (Mus spretus), using samples from the ranges of sympatry and allopatry in Africa and Europe. Our analysis reveals wide variability in introgression signatures along the genomes, as well as across the samples. We find that fewer than half of the autosomes in each genome harbor all detectable introgression, whereas the X chromosome has none. Further, European mice carry more M. spretus alleles than the sympatric African ones. Using the length distribution and sharing patterns of introgressed genomic tracts across the samples, we infer, first, that at least three distinct hybridization events involving M. spretus have occurred, one of which is ancient, and the other two are recent (one presumably due to warfarin rodenticide selection). Second, several of the inferred introgressed tracts contain genes that are likely to confer adaptive advantage. Third, introgressed tracts might contain driver genes that determine the evolutionary fate of those tracts. Further, functional analysis revealed introgressed genes that are essential to fitness, including the Vkorc1 gene, which is implicated in rodenticide resistance, and olfactory receptor genes. Our findings highlight the extent and role of introgression in nature and call for careful analysis and interpretation of house mouse data in evolutionary and genetic studies.Mus musculus | Mus spretus | hybridization | adaptive introgression | PhyloNet-HMM C lassical laboratory mouse strains, as well as newly established wild-derived ones, are widely used by geneticists for answering a diverse array of questions (1). Understanding the genome contents and architecture of these strains is important for studies of natural variation and complex traits, as well as evolutionary studies in general (2). Mus spretus, a sister species of Mus musculus, impacts the findings in M. musculus investigations for at least two reasons. First, it was deliberately interbred with laboratory M. musculus strains to introduce genetic variation (3). Second, Mus musculus domesticus is partially sympatric (naturally cooccurring) with M. spretus (Fig. 1).Recent studies have examined admixture between subspecies of house mice (5-8), but have not studied introgression with M. spretus. In at least one case (5), the introgressive descent of the mouse genome was hidden due to data postprocessing that masked introgressed genomic regions as missing data. In another study reporting whole-genome sequencing of 17 classical laboratory strains (6), M. spretus was used as an outgroup for phylogenetic analysis. The authors were surprised to find that 12.1% of loci failed to place M. spretus as an outgroup to the M. musculus clade. The authors concluded that M. spretus was not a reliable outgroup but did not pursue their observation further. On the other hand, in a 2002 study (9), Orth et al. compiled data on allozyme, microsatellite, and mitochondrial variation in house mice from Spain (sympatry) and...
The diagnosis of Mendelian disorders requires labor-intensive literature research. Trained clinicians can spend hours looking for the right publication(s) supporting a single gene that best explains a patient’s disease. AMELIE (Automatic Mendelian Literature Evaluation) greatly accelerates this process. AMELIE parses all 29 million PubMed abstracts and downloads and further parses hundreds of thousands of full-text articles in search of information supporting the causality and associated phenotypes of most published genetic variants. AMELIE then prioritizes patient candidate variants for their likelihood of explaining any patient’s given set of phenotypes. Diagnosis of singleton patients (without relatives’ exomes) is the most time-consuming scenario, and AMELIE ranked the causative gene at the very top for 66% of 215 diagnosed singleton Mendelian patients from the Deciphering Developmental Disorders project. Evaluating only the top 11 AMELIE-scored genes of 127 (median) candidate genes per patient resulted in a rapid diagnosis in more than 90% of cases. AMELIE-based evaluation of all cases was 3 to 19 times more efficient than hand-curated database–based approaches. We replicated these results on a retrospective cohort of clinical cases from Stanford Children’s Health and the Manton Center for Orphan Disease Research. An analysis web portal with our most recent update, programmatic interface, and code is available at AMELIE.stanford.edu.
Eye tracking has been widely used for decades in vision research, language and usability. However, most prior research has focused on large desktop displays using specialized eye trackers that are expensive and cannot scale. Little is known about eye movement behavior on phones, despite their pervasiveness and large amount of time spent. We leverage machine learning to demonstrate accurate smartphone-based eye tracking without any additional hardware. We show that the accuracy of our method is comparable to state-of-the-art mobile eye trackers that are 100x more expensive. Using data from over 100 opted-in users, we replicate key findings from previous eye movement research on oculomotor tasks and saliency analyses during natural image viewing. In addition, we demonstrate the utility of smartphone-based gaze for detecting reading comprehension difficulty. Our results show the potential for scaling eye movement research by orders-of-magnitude to thousands of participants (with explicit consent), enabling advances in vision research, accessibility and healthcare.
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