Simultaneous amplicon sequencing to explore co- occurrence patterns of bacterial, archaeal and eukaryotic microorganisms in rumen microbial communities

Ruminants rely on a complex rumen microbial community to convert dietary plant material to energy-yielding products. Here we developed a method to simultaneously analyze the community's bacterial and archaeal 16S rRNA genes, ciliate 18S rRNA genes and anaerobic fungal internal transcribed spacer 1 genes using 12 DNA samples derived from 11 different rumen samples from three host species (Ovis aries, Bos taurus, Cervus elephas) and multiplex 454 Titanium pyrosequencing. We show that the mixing ratio of the group-specific DNA templates before emulsion PCR is crucial to compensate for differences in amplicon length. This method, in contrast to using a non-specific universal primer pair, avoids sequencing non-targeted DNA, such as plant- or endophyte-derived rRNA genes, and allows increased or decreased levels of community structure resolution for each microbial group as needed. Communities analyzed with different primers always grouped by sample origin rather than by the primers used. However, primer choice had a greater impact on apparent archaeal community structure than on bacterial community structure, and biases for certain methanogen groups were detected. Co-occurrence analysis of microbial taxa from all three domains of life suggested strong within- and between-domain correlations between different groups of microorganisms within the rumen. The approach used to simultaneously characterize bacterial, archaeal and eukaryotic components of a microbiota should be applicable to other communities occupying diverse habitats

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

Identifying invasive species threats, pathways, and impacts to improve biosecurity

Managing invasive species with prevention and early-detection strategies can avert severe ecological and economic impacts. Horizon scanning, an evidence-based process combining risk screening and consensus building to identify threats, has become a valuable tool for prioritizing invasive species management and prevention. We assembled a working group of experts from academic, government, and nonprofit agencies and organizations, and conducted a multi-taxa horizon scan for Florida, USA, the first of its kind in North America. Our primary objectives were to identify high-risk species and their introduction pathways, to detail the magnitude and mechanism of potential impacts, and, more broadly, to demonstrate the utility of horizon scanning. As a means to facilitate future horizon scans, we document the process used to generate the list of taxa for screening. We evaluated 460 taxa for their potential to arrive, establish, and cause negative ecological and socioeconomic impacts, and identified 40 potential invaders, including alewife, zebra mussel, crab-eating macaque, and red swamp crayfish. Vertebrates and aquatic invertebrates posed the greatest invasion threat, over half of the high-risk taxa were omnivores, and there was high confidence in the scoring of high-risk taxa. Common arrival pathways were ballast water, biofouling of vessels, and escape from the pet/aquarium/horticulture trade. Competition, predation, and damage to agriculture/forestry/aquaculture were common impact mechanisms. We recommend full risk analysis for the high-risk taxa; increased surveillance at Florida's ports, state borders, and high-risk pathways; and periodic review and revision of the list. Few horizon scans detail the comprehensive methodology (including list-building), certainty estimates for all scoring categories and the final score, detailed pathways, and the magnitude and mechanism of impact. Providing this information can further inform prevention efforts and can be efficiently replicated in other regions. Moreover, harmonizing methodology can facilitate data sharing and enhance interpretation of results for stakeholders and the general public.</p

Sea-ice-free Arctic during the Last Interglacial supports fast future loss

The Last Interglacial (LIG), a warmer period 130-116 ka before present, is a potential analog for future climate change. Stronger LIG summertime insolation at high northern latitudes drove Arctic land summer temperatures 4-5 °C higher than the preindustrial era. Climate model simulations have previously failed to capture these elevated temperatures, possibly because they were unable to correctly capture LIG sea-ice changes. Here, we show the latest version of the fully-coupled UK Hadley Center climate model (HadGEM3) simulates a more accurate Arctic LIG climate, including elevated temperatures. Improved model physics, including a sophisticated sea-ice melt-pond scheme, result in a complete simulated loss of Arctic sea ice in summer during the LIG, which has yet to be simulated in past generations of models. This ice-free Arctic yields a compelling solution to the longstanding puzzle of what drove LIG Arctic warmth and supports a fast retreat of future Arctic summer sea ice

Genome-wide association study of lifetime cannabis use based on a large meta-analytic sample of 32330 subjects from the International Cannabis Consortium

Cannabis is the most widely produced and consumed illicit psychoactive substance worldwide. Occasional cannabis use can progress to frequent use, abuse and dependence with all known adverse physical, psychological and social consequences. Individual differences in cannabis initiation are heritable (40-48%). The International Cannabis Consortium was established with the aim to identify genetic risk variants of cannabis use. We conducted a meta-analysis of genome-wide association data of 13 cohorts (N=32 330) and four replication samples (N=5627). In addition, we performed a gene-based test of association, estimated single-nucleotide polymorphism (SNP)-based heritability and explored the genetic correlation between lifetime cannabis use and cigarette use using LD score regression. No individual SNPs reached genome-wide significance. Nonetheless, gene-based tests identified four genes significantly associated with lifetime cannabis use: NCAM1, CADM2, SCOC and KCNT2. Previous studies reported associations of NCAM1 with cigarette smoking and other substance use, and those of CADM2 with body mass index, processing speed and autism disorders, which are phenotypes previously reported to be associated with cannabis use. Furthermore, we showed that, combined across the genome, all common SNPs explained 13-20% (P<0.001) of the liability of lifetime cannabis use. Finally, there was a strong genetic correlation (rg=0.83; P=1.85 × 10(-8)) between lifetime cannabis use and lifetime cigarette smoking implying that the SNP effect sizes of the two traits are highly correlated. This is the largest meta-analysis of cannabis GWA studies to date, revealing important new insights into the genetic pathways of lifetime cannabis use. Future functional studies should explore the impact of the identified genes on the biological mechanisms of cannabis use

Genome-wide association study of lifetime cannabis use based on a large meta-analytic sample of 32330 subjects from the International Cannabis Consortium

Cannabis is the most widely produced and consumed illicit psychoactive substance worldwide. Occasional cannabis use can progress to frequent use, abuse and dependence with all known adverse physical, psychological and social consequences. Individual differences in cannabis initiation are heritable (40-48%). The International Cannabis Consortium was established with the aim to identify genetic risk variants of cannabis use. We conducted a meta-analysis of genome-wide association data of 13 cohorts (N=32 330) and four replication samples (N=5627). In addition, we performed a gene-based test of association, estimated single-nucleotide polymorphism (SNP)-based heritability and explored the genetic correlation between lifetime cannabis use and cigarette use using LD score regression. No individual SNPs reached genome-wide significance. Nonetheless, gene-based tests identified four genes significantly associated with lifetime cannabis use: NCAM1, CADM2, SCOC and KCNT2. Previous studies reported associations of NCAM1 with cigarette smoking and other substance use, and those of CADM2 with body mass index, processing speed and autism disorders, which are phenotypes previously reported to be associated with cannabis use. Furthermore, we showed that, combined across the genome, all common SNPs explained 13-20% (P&lt;0.001) of the liability of lifetime cannabis use. Finally, there was a strong genetic correlation (rg=0.83; P=1.85 × 10(-8)) between lifetime cannabis use and lifetime cigarette smoking implying that the SNP effect sizes of the two traits are highly correlated. This is the largest meta-analysis of cannabis GWA studies to date, revealing important new insights into the genetic pathways of lifetime cannabis use. Future functional studies should explore the impact of the identified genes on the biological mechanisms of cannabis use.</p