Seed Survival at Low Temperatures: A Potential Selecting Factor Influencing Community Level Changes in High Altitudes under Climate Change

In alpine ecosystems, imbibed seeds are often exposed to temperatures as low as −35 °C, challenging their survival in the soil. Here, we show that seeds have mechanisms to survive cold climate prevalent in alpine ecosystems and have identified three such mechanisms from existing literature, including two forms of freezing avoidance (the presence of water impermeable seed coats, and the supercooling of seed tissues) and one form of freezing tolerance (by extracellular-freezing). Experimentally-derived published data on the lowest temperature recorded at which 50% of a seed sample survived (i.e., lethal temperature; LT50) was used to generate a dataset of 24 species across low altitude, boreal and alpine environments. We assumed that the ability of seeds to maintain viability at very low temperatures would increase in species associated with higher altitudes conferring a competitive advantage that would be lost under projected climate change. However, our results reveal to underpin that seeds from boreal species survive relatively better at lower temperatures than those of alpine species. Paradoxically, a warming climate could lead to alpine seed death due to extremes of cold at the soil surface resulting from snow cover loss, whilst the declining snow cover may facilitate boreal forest colonization above the current treeline

Comparison of Population-Based Association Study Methods Correcting for Population Stratification

Population stratification can cause spurious associations in population–based association studies. Several statistical methods have been proposed to reduce the impact of population stratification on population–based association studies. We simulated a set of stratified populations based on the real haplotype data from the HapMap ENCODE project, and compared the relative power, type I error rates, accuracy and positive prediction value of four prevailing population–based association study methods: traditional case-control tests, structured association (SA), genomic control (GC) and principal components analysis (PCA) under various population stratification levels. Additionally, we evaluated the effects of sample sizes and frequencies of disease susceptible allele on the performance of the four analytical methods in the presence of population stratification. We found that the performance of PCA was very stable under various scenarios. Our comparison results suggest that SA and PCA have comparable performance, if sufficient ancestral informative markers are used in SA analysis. GC appeared to be strongly conservative in significantly stratified populations. It may be better to apply GC in the stratified populations with low stratification level. Our study intends to provide a practical guideline for researchers to select proper study methods and make appropriate inference of the results in population-based association studies

Population genomics of domestic and wild yeasts

The natural genetics of an organism is determined by the distribution of sequences of its genome. Here we present one- to four-fold, with some deeper, coverage of the genome sequences of over seventy isolates of the domesticated baker's yeast, _Saccharomyces cerevisiae_, and its closest relative, the wild _S. paradoxus_, which has never been associated with human activity. These were collected from numerous geographic locations and sources (including wild, clinical, baking, wine, laboratory and food spoilage). These sequences provide an unprecedented view of the population structure, natural (and artificial) selection and genome evolution in these species. Variation in gene content, SNPs, indels, copy numbers and transposable elements provide insights into the evolution of different lineages. Phenotypic variation broadly correlates with global genome-wide phylogenetic relationships however there is no correlation with source. _S. paradoxus_ populations are well delineated along geographic boundaries while the variation among worldwide _S. cerevisiae_ isolates show less differentiation and is comparable to a single _S. paradoxus_ population. Rather than one or two domestication events leading to the extant baker's yeasts, the population structure of _S. cerevisiae_ shows a few well defined geographically isolated lineages and many different mosaics of these lineages, supporting the notion that human influence provided the opportunity for outbreeding and production of new combinations of pre-existing variation

Accounting for Population Stratification in Practice: A Comparison of the Main Strategies Dedicated to Genome-Wide Association Studies

Genome-Wide Association Studies are powerful tools to detect genetic variants associated with diseases. Their results have, however, been questioned, in part because of the bias induced by population stratification. This is a consequence of systematic differences in allele frequencies due to the difference in sample ancestries that can lead to both false positive or false negative findings. Many strategies are available to account for stratification but their performances differ, for instance according to the type of population structure, the disease susceptibility locus minor allele frequency, the degree of sampling imbalanced, or the sample size. We focus on the type of population structure and propose a comparison of the most commonly used methods to deal with stratification that are the Genomic Control, Principal Component based methods such as implemented in Eigenstrat, adjusted Regressions and Meta-Analyses strategies. Our assessment of the methods is based on a large simulation study, involving several scenarios corresponding to many types of population structures. We focused on both false positive rate and power to determine which methods perform the best. Our analysis showed that if there is no population structure, none of the tests led to a bias nor decreased the power except for the Meta-Analyses. When the population is stratified, adjusted Logistic Regressions and Eigenstrat are the best solutions to account for stratification even though only the Logistic Regressions are able to constantly maintain correct false positive rates. This study provides more details about these methods. Their advantages and limitations in different stratification scenarios are highlighted in order to propose practical guidelines to account for population stratification in Genome-Wide Association Studies

Cross-tissue immune cell analysis reveals tissue-specific adaptations and clonal architecture in humans

Despite their crucial role in health and disease, our knowledge of immune cells within human tissues remains limited. Here, we surveyed the immune compartment of 15 tissues of six deceased adult donors by single-cell RNA sequencing and paired VDJ sequencing. To systematically resolve immune cell heterogeneity across tissues, we developed CellTypist, a machine learning tool for rapid and precise cell type annotation. Using this approach, combined with detailed curation, we determined the tissue distribution of 45 finely phenotyped immune cell types and states, revealing hitherto unappreciated tissue-specific features and clonal architecture of T and B cells. In summary, our multi-tissue approach lays the foundation for identifying highly resolved immune cell types by leveraging a common reference dataset, tissue-integrated expression analysis and antigen receptor sequencing. One Sentence Summary We provide an immune cell atlas, including antigen receptor repertoire profiling, across lymphoid and non-lymphoid human tissues

Search for astronomical neutrinos from blazar TXS 0506+056 in super-kamiokande

We report a search for astronomical neutrinos in the energy region from several GeV to TeV in the direction of the blazar TXS 0506+056 using the Super-Kamiokande detector following the detection of a 100 TeV neutrinos from the same location by the IceCube collaboration. Using Super-Kamiokande neutrino data across several data samples observed from 1996 April to 2018 February we have searched for both a total excess above known backgrounds across the entire period as well as localized excesses on smaller timescales in that interval. No significant excess nor significant variation in the observed event rate are found in the blazar direction. Upper limits are placed on the electron- and muon-neutrino fluxes at the 90% confidence level as 6.0 × 10−7 and 4.5 × 10−7–9.3 × 10−10 [erg cm−2 s−1], respectively

Cells of the human intestinal tract mapped across space and time

The cellular landscape of the human intestinal tract is dynamic throughout life, developing in utero and changing in response to functional requirements and environmental exposures. Here, to comprehensively map cell lineages, we use single-cell RNA sequencing and antigen receptor analysis of almost half a million cells from up to 5 anatomical regions in the developing and up to 11 distinct anatomical regions in the healthy paediatric and adult human gut. This reveals the existence of transcriptionally distinct BEST4 epithelial cells throughout the human intestinal tract. Furthermore, we implicate IgG sensing as a function of intestinal tuft cells. We describe neural cell populations in the developing enteric nervous system, and predict cell-type-specific expression of genes associated with Hirschsprung’s disease. Finally, using a systems approach, we identify key cell players that drive the formation of secondary lymphoid tissue in early human development. We show that these programs are adopted in inflammatory bowel disease to recruit and retain immune cells at the site of inflammation. This catalogue of intestinal cells will provide new insights into cellular programs in development, homeostasis and disease

Nuclear Targeting of IGF-1 Receptor in Orbital Fibroblasts from Graves' Disease: Apparent Role of ADAM17

Insulin-like growth factor-1 receptor (IGF-1R) comprises two subunits, including a ligand binding domain on extra- cellular IGF-1Rα and a tyrosine phosphorylation site located on IGF-1Rβ. IGF-1R is over-expressed by orbital fibroblasts in the autoimmune syndrome, Graves' disease (GD). When activated by IGF-1 or GD-derived IgG (GD-IgG), these fibroblasts produce RANTES and IL-16, while those from healthy donors do not. We now report that IGF-1 and GD-IgG provoke IGF-1R accumulation in the cell nucleus of GD fibroblasts where it co-localizes with chromatin. Nuclear IGF-1R is detected with anti-IGF-1Rα-specific mAb and migrates to approximately 110 kDa, consistent with its identity as an IGF-1R fragment. Nuclear IGF-1R migrating as a 200 kDa protein and consistent with an intact receptor was undetectable when probed with either anti-IGF-1Rα or anti-IGF-1Rβ mAbs. Nuclear redistribution of IGF-1R is absent in control orbital fibroblasts. In GD fibroblasts, it can be abolished by an IGF-1R-blocking mAb, 1H7 and by physiological concentrations of glucocorticoids. When cell-surface IGF-1R is cross-linked with 125I IGF-1, 125I-IGF-1/IGF-1R complexes accumulate in the nuclei of GD fibroblasts. This requires active ADAM17, a membrane associated metalloproteinase, and the phosphorylation of IGF-1R. In contrast, virally encoded IGF-1Rα/GFP fusion protein localizes equivalently in nuclei in both control and GD fibroblasts. This result suggests that generation of IGF-1R fragments may limit the accumulation of nuclear IGF-1R. We thus identify a heretofore-unrecognized behavior of IGF-1R that appears limited to GD-derived fibroblasts. Nuclear IGF-1R may play a role in disease pathogenesis