Forest ecosystems maintain a large share of Northern Hemisphere biodiversity. Boreal forests comprise roughly 30% of global forest area 1 and contain the highest tree density among climate zones 2 . Moreover, boreal regions are undergoing extensive climate change. Annual temperature increases exceeding 1.5 °C are projected to result in a warming of 4-11 °C by the end of this century, with little concomitant increase in precipitation 1 . At this pace, climate zones will shift northward at a greater speed than trees can migrate 3 . To understand how future populations of forest trees may respond to climate change, it is essential to uncover past and present signatures of molecular adaptation in their genomes. Silver birch, B. pendula, is a pioneer species in boreal forests of Eurasia. Flowering of the species can be artificially accelerated 4 , giving it an advantage over other tree species with published genome sequences (such as poplar 5 , spruce 6 , and pine 7 ) for the optimization of fiber and biomass production.Here we sequenced 150 birch individuals and assembled a B. pendula reference genome from a fourth-generation inbred line, resulting in a high-quality assembly of 435 Mb that was linked to chromosomes using a dense genetic map. We analyzed SNPs in the genomes of 80 birch individuals spanning most of the geographic range of B. pendula, as well as seven other members of Betulaceae. Population genomic analyses of these data provide insights into the deep-time evolution of the birch family and on recent natural selection acting on silver birch.Genome sequencing and population genomic analyses provide insights into the adaptive landscape of silver birch Silver birch (Betula pendula) is a pioneer boreal tree that can be induced to flower within 1 year. Its rapid life cycle, small (440-Mb) genome, and advanced germplasm resources make birch an attractive model for forest biotechnology. We assembled and chromosomally anchored the nuclear genome of an inbred B. pendula individual. Gene duplicates from the paleohexaploid event were enriched for transcriptional regulation, whereas tandem duplicates were overrepresented by environmental responses. Population resequencing of 80 individuals showed effective population size crashes at major points of climatic upheaval. Selective sweeps were enriched among polyploid duplicates encoding key developmental and physiological triggering functions, suggesting that local adaptation has tuned the timing of and cross-talk between fundamental plant processes. Variation around the tightlylinked light response genes PHYC and FRS10 correlated with latitude and longitude and temperature, and with precipitation for PHYC. Similar associations characterized the growth-promoting cytokinin response regulator ARR1, and the wood development genes KAK and MED5A.A full list of affiliations appears at the end of the paper.

Asthma prevalence has increased in epidemic proportions with urbanization, but growing up on traditional farms offers protection even today. 1 The asthma-protective effect in farms appears to be associated with rich home dust microbiota, 2,3 which could be used to model a health-promoting indoor microbiome. Here we show by modelling differences in house dust microbiota composition between farm and non-farm homes of Finnish birth cohorts 4 that in children who grow up in non-farm homes asthma risk decreases as the similarity of their home bacterial microbiota composition to that of farm homes increases. The protective microbiota had a low abundance of Streptococcaceae relative to outdoor-associated bacterial taxa. The protective effect was independent of richness and total bacterial load and was associated with reduced proinflammatory cytokine responses against bacterial cell wall components ex vivo. We were able to reproduce these findings in a study among rural German children 2 and showed that children living in German non-farm homes with an indoor microbiota more similar to Finnish farm homes have decreased asthma risk. The indoor dust microbiota composition appears as a definable, reproducible predictor of asthma risk and a potential modifiable target for asthma prevention. MAIN TEXTFrom ancient times, humans have adapted to rich microbial exposures in early life. Changes in these exposures in modern urbanized environments may drive the epidemic increases in asthma and allergies. 5,6 Many studies describe and identify protective microbial exposures but with heterogeneity in the specific microbial signals. Thus microbial exposures that could be exploited for preventive interventions remain unidentified. Here, we tested whether it is possible to circumvent this issue with an anchor-based method, drawing on the well-characterized asthma-protective effect of growing up on animal farms that appears associated with their particular indoor dust microbiota composition. 2,3 If the indoor microbiota in farm homes causally protects from asthma, as suggested by experimental data, 3,7,8 similar microbiota in non-farm homes should also have a protective effect despite the different surrounding environment and life-style.We characterized the indoor microbiota from living-room floor dust collected from the homes of Finnish birth cohorts, LUKAS1 and LUKAS2, 4,9 at the index child age of 2 months. At this age infants who crawl are constantly exposed to floor dust via the respiratory tract, skin and mouth. 10,11 The characteristics of the farm home microbiota were defined within LUKAS1, which includes only

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Background Eukaryotes are ubiquitous in natural environments such as soil and freshwater. Little is known of their presence in drinking water distribution systems (DWDSs) or of the environmental conditions that affect their activity and survival. Methods Eukaryotes were characterized by Illumina high-throughput sequencing targeting 18S rRNA gene (DNA) that estimates the total community and the 18S rRNA gene transcript (RNA) that is more representative of the active part of the community. DWDS cold water ( N = 124), hot water ( N = 40), and biofilm ( N = 16) samples were collected from four cities in Finland. The sampled DWDSs were from two waterworks A–B with non-disinfected, recharged groundwater as source water and from three waterworks utilizing chlorinated water (two DWDSs of surface waterworks C–D and one of ground waterworks E). In each DWDS, samples were collected from three locations during four seasons of 1 year. Results A beta-diversity analysis revealed that the main driver shaping the eukaryotic communities was the DWDS (A–E) ( R = 0.73, P < 0.001, ANOSIM). The kingdoms Chloroplastida (green plants and algae), Metazoa (animals: rotifers, nematodes), Fungi (e.g., Cryptomycota ), Alveolata (ciliates, dinoflagellates), and Stramenopiles (algae Ochrophyta ) were well represented and active—judging based on the rRNA gene transcripts—depending on the surrounding conditions. The unchlorinated cold water of systems (A–B) contained a higher estimated total number of taxa (Chao1, average 380–480) than chlorinated cold water in systems C–E (Chao1 ≤ 210). Within each DWDS, unique eukaryotic communities were identified at different locations as was the case also for cold water, hot water, and biofilms. A season did not have a consistent impact on the eukaryotic community among DWDSs. Conclusions This study comprehensively characterized the eukaryotic community members within the DWDS of well-maintained ground and surface waterworks providing good quality water. The study gives an indication that each DWDS houses a unique eukaryotic community, mainly dependent on the raw water source and water treatment processes in place at the corresponding waterworks. In particular, disinfection as well as hot water temperature seemed to represent a strong selection pressure that controlled the number of active eukaryotic species. Electronic supplementary material The online version of this article (10.1186/s40168-019-0715-5) contains supplementary material, which is available to authorized users.

rRNA-based methods may be better than rDNA-based methods for evaluating human health implications as rRNA methods can be used to describe the active bacterial fraction. This study indicates that copper as a pipeline material might have an adverse impact on the occurrence of Mycobacterium spp. The activity of Legionella spp. maybe questionable when detected solely by using DNA-based methods.