11 research outputs found

    Comparative genetic analysis: the utility of mouse genetic systems for studying human monogenic disease

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    One of the long-term goals of mutagenesis programs in the mouse has been to generate mutant lines to facilitate the functional study of every mammalian gene. With a combination of complementary genetic approaches and advances in technology, this aim is slowly becoming a reality. One of the most important features of this strategy is the ability to identify and compare a number of mutations in the same gene, an allelic series. With the advent of gene-driven screening of mutant archives, the search for a specific series of interest is now a practical option. This review focuses on the analysis of multiple mutations from chemical mutagenesis projects in a wide variety of genes and the valuable functional information that has been obtained from these studies. Although gene knockouts and transgenics will continue to be an important resource to ascertain gene function, with a significant proportion of human diseases caused by point mutations, identifying an allelic series is becoming an equally efficient route to generating clinically relevant and functionally important mouse models

    A global reference for human genetic variation

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    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

    How many seals were there? The global shelf loss during the Last Glacial Maximum and its effect on the size and distribution of grey seal populations

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    The tagging studies were funded by the Natural Environment Research Council, UK; the Atlantic seal research program, Department of Fisheries and Oceans, Canada and NSERCD Discovery grants, Canada. This work also received funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland) and their support is gratefully acknowledged. MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Predicting how marine mammal populations act to habitat changes will be essential for developing conservation management strategies by marine mammal ecologists in the 21st century. Responses to previous environmental change may be informative in the development of predictive models. Here we describe the likely effects of the last ice age on grey seal population size and distribution. We use satellite telemetry data to define grey seal foraging habitat in terms of the temperature and depth ranges exploited by the contemporary populations. We estimate the available extent of such habitat in the North Atlantic at present and at the last glacial maximum (LGM); taking account of glacial and seasonal sea-ice coverage, estimated reductions of sea-level (123m) and seawater temperature hind-casts from GLAMAP-2000. Most of the extensive continental shelf waters (North Sea, Baltic Sea and Scotian Shelf), currently supporting >95% of grey seals, were unavailable at the LGM. A combination of lower sea-level and extensive ice-sheets, massively increased seasonal sea-ice coverage and southerly extent of cold water would have pushed grey seals into areas with no significant shelf waters. The habitat during the LGM might have been as small as 4%, when compared to today’s extent and grey seal populations may have fallen to similarly. An alternative scenario involving a major change to a pelagic/bathy-pelagic foraging niche cannot be discounted. However, hooded seals that appear to out-compete and effectively exclude grey seals from such habitat currently dominate that niche. If as seems likely, the grey seal population fell to very low levels it would have remained low for several thousand years before expanding into current habitats over the last 12000 years or so.Publisher PDFPeer reviewe

    Investigating annual diving behaviour by Hooded seals (Cystophora cristata) within the Northwest Atlantic Ocean

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    This work was funded through the Atlantic Seal Research Programme, International Governance Programme (DFO), the Greenland Institute of Natural Resources, and a CFI grant to YFW. The authors also acknowledge the support of the Marine Alliance for Science and Technology for Scotland (MASTS) pooling initiative in the completion of this study. MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.With the exception of relatively brief periods when they reproduce and moult, hooded seals, Cystophora cristata, spend most of the year in the open ocean where they undergo feeding migrations to either recover or prepare for the next fasting period. Valuable insights into habitat use and diving behaviour during these periods have been obtained by attaching Satellite Relay Data Loggers (SRDLs) to 51 Northwest (NW) Atlantic hooded seals (33 females and 18 males) during ice-bound fasting periods (2004−2008). Using General Additive Models (GAMs) we describe habitat use in terms of First Passage Time (FPT) and analyse how bathymetry, seasonality and FPT influence the hooded seals’ diving behaviour described by maximum dive depth, dive duration and surface duration. Adult NW Atlantic hooded seals exhibit a change in diving activity in areas where they spend >20 h by increasing maximum dive depth, dive duration and surface duration, indicating a restricted search behaviour. We found that male and female hooded seals are spatially segregated and that diving behaviour varies between sexes in relation to habitat properties and seasonality. Migration periods are described by increased dive duration for both sexes with a peak in May, October and January. Males demonstrated an increase in dive depth and dive duration towards May (post-breeding/pre-moult) and August–October (post-moult/pre-breeding) but did not show any pronounced increase in surface duration. Females dived deepest and had the highest surface duration between December and January (post-moult/pre-breeding). Our results suggest that the smaller females may have a greater need to recover from dives than that of the larger males. Horizontal segregation could have evolved as a result of a resource partitioning strategy to avoid sexual competition or that the energy requirements of males and females are different due to different energy expenditure during fasting periods.Publisher PDFPeer reviewe

    A risk assessment review of mercury exposure in Arctic marine and terrestrial mammals

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    There has been a considerable number of reports on Hg concentrations in Arctic mammals since the last Arctic Monitoring and Assessment Programme (AMAP) effort to review biological effects of the exposure to mercury (Hg) in Arctic biota in 2010 and 2018. Here, we provide an update on the state of the knowledge of health risk associated with Hg concentrations in Arctic marine and terrestrial mammal species. Using available population-specific data post-2000, our ultimate goal is to provide an updated evidence-based estimate of the risk for adverse health effects from Hg exposure in Arctic mammal species at the individual and population level. Tissue residues of Hg in 13 species across the Arctic were classified into five risk categories (from No risk to Severe risk) based on critical tissue concentrations derived from experimental studies on harp seals and mink. Exposure to Hg lead to low or no risk for health effects in most populations of marine and terrestrial mammals, however, subpopulations of polar bears, pilot whales, narwhals, beluga and hooded seals are highly exposed in geographic hotspots raising concern for Hg-induced toxicological effects. About 6% of a total of 3500 individuals, across different marine mammal species, age groups and regions, are at high or severe risk of health effects from Hg exposure. The corresponding figure for the 12 terrestrial species, regions and age groups was as low as 0.3% of a total of 731 individuals analyzed for their Hg loads. Temporal analyses indicated that the proportion of polar bears at low or moderate risk has increased in East/West Greenland and Western Hudson Bay, respectively. However, there remain numerous knowledge gaps to improve risk assessments of Hg exposure in Arctic mammalian species, including the establishment of improved concentration thresholds and upscaling to the assessment of population-level effects

    A risk assessment review of mercury exposure in Arctic marine and terrestrial mammals

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    There has been a considerable number of reports on Hg concentrations in Arctic mammals since the last Arctic Monitoring and Assessment Programme (AMAP) effort to review biological effects of the exposure to mercury (Hg) in Arctic biota in 2010 and 2018. Here, we provide an update on the state of the knowledge of health risk associated with Hg concentrations in Arctic marine and terrestrial mammal species. Using available population-specific data post-2000, our ultimate goal is to provide an updated evidence-based estimate of the risk for adverse health effects from Hg exposure in Arctic mammal species at the individual and population level. Tissue residues of Hg in 13 species across the Arctic were classified into five risk categories (from No risk to Severe risk) based on critical tissue concentrations derived from experimental studies on harp seals and mink. Exposure to Hg lead to low or no risk for health effects in most populations of marine and terrestrial mammals, however, subpopulations of polar bears, pilot whales, narwhals, beluga and hooded seals are highly exposed in geographic hotspots raising concern for Hg-induced toxicological effects. About 6% of a total of 3500 individuals, across different marine mammal species, age groups and regions, are at high or severe risk of health effects from Hg exposure. The corresponding figure for the 12 terrestrial species, regions and age groups was as low as 0.3% of a total of 731 individuals analyzed for their Hg loads. Temporal analyses indicated that the proportion of polar bears at low or moderate risk has increased in East/West Greenland and Western Hudson Bay, respectively. However, there remain numerous knowledge gaps to improve risk assessments of Hg exposure in Arctic mammalian species, including the establishment of improved concentration thresholds and upscaling to the assessment of population-level effects

    Current state of knowledge on biological effects from contaminants on arctic wildlife and fish

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    Since the last Arctic Monitoring and Assessment Programme (AMAP) effort to review biological effects of the exposure to organohalogen compounds (OHCs) in Arctic biota, there has been a considerable number of new Arctic effect studies. Here, we provide an update on the state of the knowledge of OHC, and also include mercury, exposure and/or associated effects in key Arctic marine and terrestrial mammal and bird species as well as in fish by reviewing the literature published since the last AMAP assessment in 2010. We aimed at updating the knowledge of how single but also combined health effects are or can be associated to the exposure to single compounds or mixtures of OHCs. We also focussed on assessing both potential individual as well as population health impacts using population-specific exposure data post 2000. We have identified quantifiable effects on vitamin metabolism, immune functioning, thyroid and steroid hormone balances, oxidative stress, tissue pathology, and reproduction. As with the previous assessment, a wealth of documentation is available for biological effects in marine mammals and seabirds, and sentinel species such as the sledge dog and Arctic fox, but information for terrestrial vertebrates and fish remain scarce. While hormones and vitamins are thoroughly studied, oxidative stress, immunotoxic and reproductive effects need further investigation. Depending on the species and population, some OHCs and mercury tissue contaminant burdens post 2000 were observed to be high enough to exceed putative risk threshold levels that have been previously estimated for non-target species or populations outside the Arctic. In this assessment, we made use of risk quotient calculations to summarize the cumulative effects of different OHC classes and mercury for which critical body burdens can be estimated for wildlife across the Arctic. As our ultimate goal is to better predict or estimate the effects of OHCs and mercury in Arctic wildlife at the individual, population and ecosystem level, there remain numerous knowledge gaps on the biological effects of exposure in Arctic biota. These knowledge gaps include the establishment of concentration thresholds for individual compounds as well as for realistic cocktail mixtures that in fact indicate biologically relevant, and not statistically determined, health effects for specific species and subpopulations. Finally, we provide future perspectives on understanding Arctic wildlife health using new in vivo, in vitro, and in silico techniques, and provide case studies on multiple stressors to show that future assessments would benefit from significant efforts to integrate human health, wildlife ecology and retrospective and forecasting aspects into assessing the biological effects of OHC and mercury exposure in Arctic wildlife and fish
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