The Diversity of REcent and Ancient huMan (DREAM): a new microarray for genetic anthropology and genealogy, forensics, and personalized medicine

The human population displays wide variety in demographic history, ancestry, content of DNA derived from hominins or ancient populations, adaptation, traits, copy number variation (CNVs), drug response, and more. These polymorphisms are of broad interest to population geneticists, forensics investigators, and medical professionals. Historically, much of that knowledge was gained from population survey projects. While many commercial arrays exist for genome-wide single-nucleotide polymorphism (SNP) genotyping, their design specifications are limited and they do not allow a full exploration of biodiversity. We thereby aimed to design the Diversity of REcent and Ancient huMan (DREAM) - an all-inclusive microarray that would allow both identification of known associations and exploration of standing questions in genetic anthropology, forensics, and personalized medicine. DREAM includes probes to interrogate ancestry informative markers obtained from over 450 human populations, over 200 ancient genomes, and 10 archaic hominins. DREAM can identify 94% and 61% of all known Y and mitochondrial haplogroups, respectively and was vetted to avoid interrogation of clinically relevant markers. To demonstrate its capabilities, we compared its FST distributions with those of the 1000 Genomes Project and commercial arrays. Although all arrays yielded similarly shaped (inverse J) FST distributions, DREAM's autosomal and X-chromosomal distributions had the highest mean FST, attesting to its ability to discern subpopulations. DREAM performances are further illustrated in biogeographical, identical by descent (IBD), and CNV analyses. In summary, with approximately 800,000 markers spanning nearly 2,000 genes, DREAM is a useful tool for genetic anthropology, forensic, and personalized medicine studies

Integrating precision cancer medicine into healthcare—policy, practice, and research challenges

Abstract Precision medicine (PM) can be defined as a predictive, preventive, personalized, and participatory healthcare service delivery model. Recent developments in molecular biology and information technology make PM a reality today through the use of massive amounts of genetic, ‘omics’, clinical, environmental, and lifestyle data. With cancer being one of the most prominent public health threats in developed countries, both the research community and governments have been investing significant time, money, and efforts in precision cancer medicine (PCM). Although PCM research is extremely promising, a number of hurdles still remain on the road to an optimal integration of standardized and evidence-based use of PCM in healthcare systems. Indeed, PCM raises a number of technical, organizational, ethical, legal, social, and economic challenges that have to be taken into account in the development of an appropriate health policy framework. Here, we highlight some of the more salient issues regarding the standards needed for integration of PCM into healthcare systems, and we identify fields where more research is needed before policy can be implemented. Key challenges include, but are not limited to, the creation of new standards for the collection, analysis, and sharing of samples and data from cancer patients, and the creation of new clinical trial designs with renewed endpoints. We believe that these issues need to be addressed as a matter of priority by public health policymakers in the coming years for a better integration of PCM into healthcare

Mapping QTL for resistance to new virulent races of wheat stripe rust from two argentinean wheat cultivars

During the last two decades, new virulent and aggressive races of Puccinia striiformis Westend. f. sp. tritici (Pst) have spread worldwide, causing devastating epidemics and prompting the search for new sources of resistance in wheat (Triticum aestivum L.). Between 2012 and 2017, we mapped four stripe rust resistance quantitative trait loci (QTL) effective against the Pst races present in California, USA, using recombinant inbred lines (RILs) developed from the cross between the Argentinean cultivars ‘Klein Proteo’ and ‘Klein Chajá’. The RIL population showed transgressive segregation in all six growing seasons relative to the parental lines, which showed moderate levels of Pst resistance. Analyses by year detected QTL conferring adult plant resistance on chromosomes 1BL, 2BS, 3D centromeric (from Klein Chajá), and 4DL (from Klein Proteo). QYr.ucw-1BL, mapped in the Yr29 resistance gene region, was significant in all seasons (P < 0.01) and explained on average 31.0 to 32.8% of the observed variation. QYr.ucw-2BS showed a stronger effect than QYr.ucw-1BL in 2013 but was ineffective in 2014 and 2016. This QTL also conferred seedling resistance, suggesting that it is an all-stage resistance gene. Centromeric QYr.ucw-3D and QYr.ucw-4DL showed smaller effects than the previous QTL and were significant only in some of the experiments. No significant interactions were detected among QTL, indicating the absence of digenic epistatic effects. The molecular markers identified in this study can be used to combine these genes and accelerate their deployment in wheat breeding programs

zCall: a rare variant caller for array-based genotyping

Summary: zCall is a variant caller specifically designed for calling rare single-nucleotide polymorphisms from array-based technology. This caller is implemented as a post-processing step after a default calling algorithm has been applied. The algorithm uses the intensity profile of the common allele homozygote cluster to define the location of the other two genotype clusters. We demonstrate improved detection of rare alleles when applying zCall to samples that have both Illumina Infinium HumanExome BeadChip and exome sequencing data available. Availability: http://atguweb.mgh.harvard.edu/apps/zcall. Contact: [email protected] Supplementary Information: Supplementary data are available at Bioinformatics online