63 research outputs found
Changes in Range Condition in the Arid Shrublands of Western Australia: Application of Spatialand Temporal Analysis to Long‐Term Monitoring Data
Agribusiness Sheep Updates - 2004 part 2
Precision Pastures Using Species Diversity to Improve Pasture Performance Anyou Liu and Clinton Revell, Department of Agriculture, Western Australia New Annual Pasture Legumes for Sheep Graziers Phil Nichols, Angelo Loi, Brad Nutt and Darryl McClements Department of Agriculture Western Australia Pastures from Space – Can Satellite Estimates of Pasture Growth Rate be used to Increase Farm Profit? Lucy Anderton, Stephen Gherardi and Chris Oldham Department of Agriculture Western Australia Summer-active Perennial Grasses for Profitable Sheep Production Paul Sanford and John Gladman, Department of Agriculture, Western Australia Pastures From Space – Validation Of Predictions Of Pasture Growth Rates DONALD, G.E.A, EDIRISINGHE, A.A, HENRY, D.A.A, MATA, G.A, GHERARDI, S.G.B, OLDHAM, C.M.B, GITTINS, S.P.B AND SMITH, R. C. G.C ACSIRO, Livestock Industries, PMB 5, Wembley, WA, 6913. BDepartment of Agriculture Western Australia, Bentley, WA, 6983. C Department of Land Information Western Australia, Floreat, WA, 6214. Production and Management of Biserrula Pasture - Managing the Risk of Photosensitivity Dr Clinton Revell and Roy Butler, Department of Agriculture Western Australia Meat Quality of Sheep Grazed on a Saltbush-based Pasture Kelly Pearce1,2, David Masters1, David Pethick2, 1 CSIRO LIVESTOCK INDUSTRIES, WEMBLEY, WA 2 SCHOOL OF VETERINARY AND BIOMEDICAL SCIENCE, MURDOCH UNIVERSITY, MURDOCH, WA Precision Sheep Lifetime Wool – Carryover Effects on Subsequent Reproduction of the Ewe Flock Chris Oldham, Department of Agriculture Western Australia Andrew Thompson, Primary Industries Research Victoria (PIRVic), Dept of Primary Industries, Hamilton, Vic Ewe Productivity Trials - a Linked Analysis Ken Hart, Johan Greeff, Department of Agriculture Western Australia, Beth Paganoni, School of Animal Biology, Faculty of Natural and Agricultural Sciences, University of Western Australia. Grain Finishing Systems For Prime Lambs Rachel Kirby, Matt Ryan, Kira Buttler, Department of Agriculture, Western Australia The Effects of Nutrition and Genotype on the Growth and Development, Muscle Biochemistry and Consumer Response to Lamb Meat David Pethick, Department of Veterinary Science, Murdoch University, WA, Roger Heggarty and David Hopkins, New South Wales Agriculture ‘Lifetime Wool’ - Effects of Nutrition During Pregnancy and Lactation on Mortality of Progeny to Hogget Shearing Samantha Giles, Beth Paganoni and Tom Plaisted, Department of Agriculture Western Australia, Mark Ferguson and Darren Gordon, Primary Industries Research Victoria (PIRVic), Dept of Primary Industries, Hamilton, Vic Lifetime Wool - Target Liveweights for the Ewe Flock J. Young, Farming Systems Analysis Service, Kojonup, C. Oldham, Department of Agriculture Western Australia, A. Thompson, Primary Industries Research Victoria (PIRVic), Hamilton, VIC Lifetime Wool - Effects of Nutrition During Pregnancy and Lactation on the Growth and Wool Production of their Progeny at Hogget Shearing B. Paganoni, University of Western Australia, Nedlands WA, C. Oldham, Department of Agriculture Western Australia, M. Ferguson, A. Thompson, Primary Industries Research Victoria (PIRVic), Hamilton, VIC RFID Technology – Esperance Experiences Sandra Brown, Department of Agriculture Western Australia The Role of Radio Frequency Identification (RFID) Technology in Prime Lamb Production - a Case Study. Ian McFarland, Department of Agriculture, Western Australia. John Archer, Producer, Narrogin, Western Australia Win with Twins from Merinos John Milton, Rob Davidson, Graeme Martin and David Lindsay The University of Western Australia Precision Sheep Need Precision Wool Harvesters Jonathan England, Castle Carrock Merinos, Kingston SE, South Australia Business EBVs and Indexes – Genetic Tools for your Toolbox Sandra Brown, Department of Agriculture Western Australia Green Feed Budget Paddock Calculator Mandy Curnow, Department of Agriculture Western Australia Minimising the Impact of Drought - Evaluating Flock Recovery Options using the ImPack Model Karina P. Wood, Ashley K. White, B. Lloyd Davies, Paul M. Carberry, NSW Department of Primary Industries (NSW DPI), Lifetime Wool - Modifying GrazFeed® for WA Mike Hyder, Department of Agriculture Western Australia , Mike Freer, CSIRO Plant Industry, Canberra, A.C.T. , Andrew van Burgel, and Kazue Tanaka, Department of Agriculture Western Australia Profile Calculator – A Way to Manage Fibre Diameter Throughout the Year to Maximise Returns Andrew Peterson, Department of Agriculture, Western Australia Pasture Watch - a Farmer Friendly Tool for Downloading and Analysing Pastures from Space Data Roger Wiese,Fairport Technologies International, South Perth, WA, Stephen Gherardi, BDepartment of Agriculture Western Australia, Gonzalo Mata, CCSIRO, Livestock Industries, Wembley, Western Australia, and Chris Oldham, Department of Agriculture Western Australia Sy Sheep Cropping Systems An Analysis of a Cropping System Containing Sheep in a Low Rainfall Livestock System. Evan Burt, Amanda Miller, Anne Bennett, Department of Agriculture, Western Australia Lucerne-based Pasture for the Central Wheatbelt – is it Good Economics? Felicity FluggeA, Amir AbadiA,B and Perry DollingA,B,A CRC for Plant-based Management of Dryland Salinity: BDept. of Agriculture, WA Sheep and Biserrula can Control Annual Ryegrass Dean Thomas, John Milton, Mike Ewing and David Lindsay, The University of WA, Clinton Revell, Department of Agriculture, Western Australia Sustainable Management Pasture Utilisation, Fleece Weight and Weaning Rate are Integral to the Profitability of Dohnes and SAMMs. Emma Kopke,Department of Agriculture Western Australia, John Young, Farming Systems Analysis Service Environmental Impact of Sheep Confinement Feeding Systems E A Dowling and E K Crossley, Department of Agriculture, Western Australia Smart Grazing Management for Production and Environmental Outcomes Dr Brien E (Ben) Norton, Centre for the Management of Arid Environments, Curtin University of Technology, WA Common Causes of Plant Poisoning in the Eastern Wheatbelt of Western Australia. Roy Butler, Department of Agriculture, Western Australia Selecting Sheep for Resistance to Worms and Production Trait Responses John Karlsson, Johan Greeff, Department of Agriculture, Western Australia, Geoff Pollott, Imperial College, London UK Production and Water Use of Lucerne and French Serradella in Four Soil Types, Diana Fedorenko1,4, Darryl McClements2,4 and Robert Beard3,4, 12Department of Agriculture, Western Australia; 3Farmer, Meckering; 4CRC for Plant-based Management of Dryland Salinity. Worm Burdens in Sheep at Slaughter Brown Besier, Department of Agriculture Western Australia, Una Ryan, Caroline Bath, Murdoch Universit
Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects
Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (OR=1.11, P=5.7×10−15), which persisted after excluding loci implicated in previous studies (OR=1.07, P=1.7 ×10−6). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 ×10−11) and neurobehavioral phenotypes in mouse (OR = 1.18, P= 7.3 ×10−5). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by non-allelic homologous recombination
No Reliable Association between Runs of Homozygosity and Schizophrenia in a Well-Powered Replication Study
It is well known that inbreeding increases the risk of recessive monogenic diseases, but it is less certain whether it contributes to the etiology of complex diseases such as schizophrenia. One way to estimate the effects of inbreeding is to examine the association between disease diagnosis and genome-wide autozygosity estimated using runs of homozygosity (ROH) in genome-wide single nucleotide polymorphism arrays. Using data for schizophrenia from the Psychiatric Genomics Consortium (n = 21,868), Keller et al. (2012) estimated that the odds of developing schizophrenia increased by approximately 17% for every additional percent of the genome that is autozygous (β = 16.1, CI(β) = [6.93, 25.7], Z = 3.44, p = 0.0006). Here we describe replication results from 22 independent schizophrenia case-control datasets from the Psychiatric Genomics Consortium (n = 39,830). Using the same ROH calling thresholds and procedures as Keller et al. (2012), we were unable to replicate the significant association between ROH burden and schizophrenia in the independent PGC phase II data, although the effect was in the predicted direction, and the combined (original + replication) dataset yielded an attenuated but significant relationship between Froh and schizophrenia (β = 4.86,CI(β) = [0.90,8.83],Z = 2.40,p = 0.02). Since Keller et al. (2012), several studies reported inconsistent association of ROH burden with complex traits, particularly in case-control data. These conflicting results might suggest that the effects of autozygosity are confounded by various factors, such as socioeconomic status, education, urbanicity, and religiosity, which may be associated with both real inbreeding and the outcome measures of interest
Gene expression imputation across multiple brain regions provides insights into schizophrenia risk
Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression
Age at first birth in women is genetically associated with increased risk of schizophrenia
Prof. Paunio on PGC:n jäsenPrevious studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is -0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health.Peer reviewe
Genetic correlation between amyotrophic lateral sclerosis and schizophrenia
A. Palotie on työryhmän Schizophrenia Working Grp Psychiat jäsen.We have previously shown higher-than-expected rates of schizophrenia in relatives of patients with amyotrophic lateral sclerosis (ALS), suggesting an aetiological relationship between the diseases. Here, we investigate the genetic relationship between ALS and schizophrenia using genome-wide association study data from over 100,000 unique individuals. Using linkage disequilibrium score regression, we estimate the genetic correlation between ALS and schizophrenia to be 14.3% (7.05-21.6; P = 1 x 10(-4)) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS (P = 8.4 x 10(-7)). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08-1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies.Peer reviewe
Mapping genomic loci implicates genes and synaptic biology in schizophrenia
Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies
Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders
Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe
Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors
Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe
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