A global reference for human genetic variation

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.We thank the many people who were generous with contributing their samples to the project: the African Caribbean in Barbados; Bengali in Bangladesh; British in England and Scotland; Chinese Dai in Xishuangbanna, China; Colombians in Medellin, Colombia; Esan in Nigeria; Finnish in Finland; Gambian in Western Division – Mandinka; Gujarati Indians in Houston, Texas, USA; Han Chinese in Beijing, China; Iberian populations in Spain; Indian Telugu in the UK; Japanese in Tokyo, Japan; Kinh in Ho Chi Minh City, Vietnam; Luhya in Webuye, Kenya; Mende in Sierra Leone; people with African ancestry in the southwest USA; people with Mexican ancestry in Los Angeles, California, USA; Peruvians in Lima, Peru; Puerto Ricans in Puerto Rico; Punjabi in Lahore, Pakistan; southern Han Chinese; Sri Lankan Tamil in the UK; Toscani in Italia; Utah residents (CEPH) with northern and western European ancestry; and Yoruba in Ibadan, Nigeria. Many thanks to the people who contributed to this project: P. Maul, T. Maul, and C. Foster; Z. Chong, X. Fan, W. Zhou, and T. Chen; N. Sengamalay, S. Ott, L. Sadzewicz, J. Liu, and L. Tallon; L. Merson; O. Folarin, D. Asogun, O. Ikpwonmosa, E. Philomena, G. Akpede, S. Okhobgenin, and O. Omoniwa; the staff of the Institute of Lassa Fever Research and Control (ILFRC), Irrua Specialist Teaching Hospital, Irrua, Edo State, Nigeria; A. Schlattl and T. Zichner; S. Lewis, E. Appelbaum, and L. Fulton; A. Yurovsky and I. Padioleau; N. Kaelin and F. Laplace; E. Drury and H. Arbery; A. Naranjo, M. Victoria Parra, and C. Duque; S. Däkel, B. Lenz, and S. Schrinner; S. Bumpstead; and C. Fletcher-Hoppe. Funding for this work was from the Wellcome Trust Core Award 090532/Z/09/Z and Senior Investigator Award 095552/Z/11/Z (P.D.), and grants WT098051 (R.D.), WT095908 and WT109497 (P.F.), WT086084/Z/08/Z and WT100956/Z/13/Z (G.M.), WT097307 (W.K.), WT0855322/Z/08/Z (R.L.), WT090770/Z/09/Z (D.K.), the Wellcome Trust Major Overseas program in Vietnam grant 089276/Z.09/Z (S.D.), the Medical Research Council UK grant G0801823 (J.L.M.), the UK Biotechnology and Biological Sciences Research Council grants BB/I02593X/1 (G.M.) and BB/I021213/1 (A.R.L.), the British Heart Foundation (C.A.A.), the Monument Trust (J.H.), the European Molecular Biology Laboratory (P.F.), the European Research Council grant 617306 (J.L.M.), the Chinese 863 Program 2012AA02A201, the National Basic Research program of China 973 program no. 2011CB809201, 2011CB809202 and 2011CB809203, Natural Science Foundation of China 31161130357, the Shenzhen Municipal Government of China grant ZYC201105170397A (J.W.), the Canadian Institutes of Health Research Operating grant 136855 and Canada Research Chair (S.G.), Banting Postdoctoral Fellowship from the Canadian Institutes of Health Research (M.K.D.), a Le Fonds de Recherche duQuébec-Santé (FRQS) research fellowship (A.H.), Genome Quebec (P.A.), the Ontario Ministry of Research and Innovation – Ontario Institute for Cancer Research Investigator Award (P.A., J.S.), the Quebec Ministry of Economic Development, Innovation, and Exports grant PSR-SIIRI-195 (P.A.), the German Federal Ministry of Education and Research (BMBF) grants 0315428A and 01GS08201 (R.H.), the Max Planck Society (H.L., G.M., R.S.), BMBF-EPITREAT grant 0316190A (R.H., M.L.), the German Research Foundation (Deutsche Forschungsgemeinschaft) Emmy Noether Grant KO4037/1-1 (J.O.K.), the Beatriu de Pinos Program grants 2006 BP-A 10144 and 2009 BP-B 00274 (M.V.), the Spanish National Institute for Health Research grant PRB2 IPT13/0001-ISCIII-SGEFI/FEDER (A.O.), Ewha Womans University (C.L.), the Japan Society for the Promotion of Science Fellowship number PE13075 (N.P.), the Louis Jeantet Foundation (E.T.D.), the Marie Curie Actions Career Integration grant 303772 (C.A.), the Swiss National Science Foundation 31003A_130342 and NCCR “Frontiers in Genetics” (E.T.D.), the University of Geneva (E.T.D., T.L., G.M.), the US National Institutes of Health National Center for Biotechnology Information (S.S.) and grants U54HG3067 (E.S.L.), U54HG3273 and U01HG5211 (R.A.G.), U54HG3079 (R.K.W., E.R.M.), R01HG2898 (S.E.D.), R01HG2385 (E.E.E.), RC2HG5552 and U01HG6513 (G.T.M., G.R.A.), U01HG5214 (A.C.), U01HG5715 (C.D.B.), U01HG5718 (M.G.), U01HG5728 (Y.X.F.), U41HG7635 (R.K.W., E.E.E., P.H.S.), U41HG7497 (C.L., M.A.B., K.C., L.D., E.E.E., M.G., J.O.K., G.T.M., S.A.M., R.E.M., J.L.S., K.Y.), R01HG4960 and R01HG5701 (B.L.B.), R01HG5214 (G.A.), R01HG6855 (S.M.), R01HG7068 (R.E.M.), R01HG7644 (R.D.H.), DP2OD6514 (P.S.), DP5OD9154 (J.K.), R01CA166661 (S.E.D.), R01CA172652 (K.C.), P01GM99568 (S.R.B.), R01GM59290 (L.B.J., M.A.B.), R01GM104390 (L.B.J., M.Y.Y.), T32GM7790 (C.D.B., A.R.M.), P01GM99568 (S.R.B.), R01HL87699 and R01HL104608 (K.C.B.), T32HL94284 (J.L.R.F.), and contracts HHSN268201100040C (A.M.R.) and HHSN272201000025C (P.S.), Harvard Medical School Eleanor and Miles Shore Fellowship (K.L.), Lundbeck Foundation Grant R170-2014-1039 (K.L.), NIJ Grant 2014-DN-BX-K089 (Y.E.), the Mary Beryl Patch Turnbull Scholar Program (K.C.B.), NSF Graduate Research Fellowship DGE-1147470 (G.D.P.), the Simons Foundation SFARI award SF51 (M.W.), and a Sloan Foundation Fellowship (R.D.H.). E.E.E. is an investigator of the Howard Hughes Medical Institute

Emerging and reemerging arboviruses: A new threat in Eastern Peru

Arboviral diseases are one of the most common causes of acute febrile illness (AFI) and a significant health problem in South America. In Peru, laboratory etiologic identification of these infections occurs in less than 50% of cases, leading to underdiagnoses of important emerging arboviruses.To assess the prevalence of the Dengue (DENV), Oropouche (OROV), Chikungunya (CHIKV), Mayaro (MAYV) and Zika (ZIKV) viruses in patients with acute febrile illness from Puerto Maldonado (Peru).Serum samples were obtained from patients with AFI during January 2016 to March 2016. A total of 139 specimens were analyzed for the presence of DENV, OROV, CHIKV, MAYV, and ZIKV using polymerase chain reaction (PCR).CHIKV in 9.4% and OROV in 8.6% were the most prevalent arboviruses, followed by DENV and ZIKV, with a prevalence of 6.5% and 5%, respectively. Among all patients, the most common symptoms accompanying fever were headaches 79.9%, muscle pain 65.5% and joint pain 63.3%.During this short 3-month period, 4 arboviruses were detected by PCR, CHIKV and OROV being the most common arboviruses in Puerto Maldonado (Peru). Thus, it is crucial to include OROV detection in the national health surveillance. Furthermore, the etiologic clinical diagnosis of arboviral infections is not possible due to the low specificity of symptoms; therefore an increase of cases confirmed by molecular diagnostic methods will enhance arboviral surveillance in Peru

The Effectiveness of Sedentary Behaviour Reduction Workplace Interventions on Cardiometabolic Risk Markers: A Systematic Review

Background Sedentary behaviour is a risk factor for type 2 diabetes and cardiovascular disease. Objectives The aims of this work were to systematically review the effects of workplace sedentary behaviour reduction interventions on cardiometabolic risk markers (primary aim) and identify the active behaviour change techniques (BCTs) by which these interventions work (secondary aim). Methods A systematic search of 11 databases for articles published up to 12 April 2019 yielded a total of 4255 unique titles, with 29 articles being identified for inclusion. Interventions were rated as very promising, quite promising or non-promising based on their effects on cardiometabolic risk markers compared with baseline and/or a comparison arm. Interventions were coded for BCTs used. To assess the relative effectiveness of BCTs, a promise ratio was calculated as the frequency of a BCT appearing in all promising interventions divided by its frequency of appearance in all non-promising interventions. Results A narrative synthesis included 29 published studies of varying study design and comprised of 30 interventions. Risk of bias was high for blinding and allocation concealment, moderate for random sequence generation, and low for outcome assessment. Nine interventions were very promising, 11 were quite promising, 10 were non-promising, and 10 active control groups did not experience cardiometabolic changes. Significant sedentary behaviour reductions were present in all but five studies where cardiometabolic risk markers improved. The BCTs of social comparison, problem solving, demonstration of the behaviour, goal setting (behaviour), behaviour substitution, and habit reversal, demonstrated moderate to high promise ratios. Conclusions Workplace interventions show promise for improving cardiometabolic risk markers. The BCTs with the greatest promise of cardiometabolic risk marker improvements included social comparison, those related to individual habits, and behaviour goals

Polarity, Planes of Cell Division, and the Evolution of Plant Multicellularity

Organisms as diverse as bacteria, fungi, plants, and animals manifest a property called polarity. The literature shows that polarity emerges as a consequence of different mechanisms in different lineages. However, across all unicellular and multicellular organisms, polarity is evident when cells, organs, or organisms manifest one or more of the following: orientation, axiation, and asymmetry. Here, we review the relationships among these three features in the context of cell division and the evolution of multicellular polarity primarily in plants (defined here to include the algae). Data from unicellular and unbranched filamentous organisms (e.g., Chlamydomonas and Ulothrix) show that cell orientation and axiation are marked by cytoplasmic asymmetries. Branched filamentous organisms (e.g., Cladophora and moss protonema) require an orthogonal reorientation of axiation, or a localized cell asymmetry (e.g., tip growth in pollen tubes and fungal hyphae). The evolution of complex multicellular meristematic polarity required a third reorientation of axiation. These transitions show that polarity and the orientation of the future plane(s) of cell division are dyadic dynamical patterning modules that were critical for multicellular eukaryotic organisms