Sex differences among children, adolescents and young adults for mental health service use within inpatient and outpatient settings, before and during the COVID-19 pandemic: a population-based study in Ontario, Canada

Objectives The pandemic and public health response to contain the virus had impacts on many aspects of young people’s lives including disruptions to daily routines, opportunities for social, academic, recreational engagement and early employment. Consequently, children, adolescents and young adults may have experienced mental health challenges that required use of mental health services. This study compared rates of use for inpatient and outpatient mental health services during the pandemic to pre-pandemic rates. Design Population-based repeated cross-sectional study. Setting Publicly delivered mental healthcare in primary and secondary settings within the province of Ontario, Canada. Participants All children 6–12 years of age (n=2 043 977), adolescents 13–17 years (n=1 708 754) and young adults 18–24 years (n=2 286 544), living in Ontario and eligible for provincial health insurance between March 2016 and November 2021. Primary outcome measures Outpatient mental health visits to family physicians and psychiatrists for: mood and anxiety disorders, alcohol and substance abuse disorders, other non-psychotic mental health disorders and social problems. Inpatient mental health visits to emergency departments and hospitalisations for: substance-related and addictive disorders, anxiety disorders, assault-related injuries, deliberate self-harm and eating disorders. All outcomes were analysed by cohort and sex. Results During the pandemic, observed outpatient visit rates were higher among young adults by 19.01% (95% CI: 15.56% to 22.37%; 209 vs 175 per 1000) and adolescent women 24.17% (95% CI: 18.93% to 29.15%; 131 vs 105 per 1000) for mood and anxiety disorders and remained higher than expected. Female adolescents had higher than expected usage of inpatient care for deliberate self-harm, eating disorders and assault-related injuries. Conclusions Study results raise concerns over prolonged high rates of mental health use during the pandemic, particularly in female adolescents and young women, and highlights the need to better monitor and identify mental health outcomes associated with COVID-19 containment measures and to develop policies to address these concerns

Glycan repositioning of influenza hemagglutinin stem facilitates the elicitation of protective cross-group antibody responses.

The conserved hemagglutinin (HA) stem has been a focus of universal influenza vaccine efforts. Influenza A group 1 HA stem-nanoparticles have been demonstrated to confer heterosubtypic protection in animals; however, the protection does not extend to group 2 viruses, due in part to differences in glycosylation between group 1 and 2 stems. Here, we show that introducing the group 2 glycan at Asn38 to a group 1 stem-nanoparticle (gN38 variant) based on A/New Caledonia/20/99 (H1N1) broadens antibody responses to cross-react with group 2 HAs. Immunoglobulins elicited by the gN38 variant provide complete protection against group 2 H7N9 virus infection, while the variant loses protection against a group 1 H5N1 virus. The N38 glycan thus is pivotal in directing antibody responses by controlling access to group-determining stem epitopes. Precise targeting of stem-directed antibody responses to the site of vulnerability by glycan repositioning may be a step towards achieving cross-group influenza protection.We thank D. Scorpio, A. Taylor, H. Bao, C. Chiedi, M. Dillon, L. Gilliam, and G. Sarbador (VRC) for help with animal studies; H. Andersen (Bioqual, Inc.) for mouse challenge studies; C. Case (Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc.) for help with challenge study coordination; A. Kumar (VRC) for producing RSV proteins; and members of Viral Pathogenesis Laboratory and Universal Influenza Vaccine Program (VRC) for helpful discussion. Support for this work was provided by the Intramural Research Program of the Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health. Electron microscopy data collection and analyses were funded by federal funds from the Frederick National Laboratory for Cancer Research, National Institutes of Health, under contract number HHSN261200800001E, and by Leidos Biomedical Research, Inc. (Y.T. and T.S.)

APOL1 Kidney-Risk Variants Induce Mitochondrial Fission

IntroductionAPOL1 G1 and G2 nephropathy-risk variants cause mitochondrial dysfunction and contribute to kidney disease. Analyses were performed to determine the genetic regulation of APOL1 and elucidate potential mechanisms in APOL1-nephropathy.MethodsA global gene expression analysis was performed in human primary renal tubule cell lines derived from 50 African American individuals. Follow-up gene knock out, cell-based rescue, and microscopy experiments were performed.ResultsAPOL1 genotypes did not alter APOL1 expression levels in the global gene expression analysis. Expression quantitative trait locus (eQTL) analysis in polyinosinic-polycytidylic acid (poly IC)-stimulated renal tubule cells revealed that single nucleotide polymorphism (SNP) rs513349 adjacent to BAK1 was a trans eQTL for APOL1 and a cis eQTL for BAK1; APOL1 and BAK1 were co-expressed in cells. BAK1 knockout in a human podocyte cell line resulted in diminished APOL1 protein, supporting a pivotal effect for BAK1 on APOL1 expression. Because BAK1 is involved in mitochondrial dynamics, mitochondrial morphology was examined in primary renal tubule cells and HEK293 Tet-on cells of various APOL1 genotypes. Mitochondria in APOL1 wild-type (G0G0) tubule cells maintained elongated morphology when stimulated by low-dose poly IC, whereas those with G1G1, G2G2, and G1G2 genotypes appeared to fragment. HEK293 Tet-on cells overexpressing APOL1 G0, G1, and G2 were created; G0 cells appeared to promote mitochondrial fusion, whereas G1 and G2 induced mitochondrial fission. The mitochondrial dynamic regulator Mdivi-1 significantly preserved cell viability and mitochondrial cristae structure and reversed mitochondrial fission induced by overexpression of G1 and G2.ConclusionResults suggest the mitochondrial fusion/fission pathway may be a therapeutic target in APOL1-nephropathy

Artificial-intelligence-based molecular classification of diffuse gliomas using rapid, label-free optical imaging

Molecular classification has transformed the management of brain tumors by enabling more accurate prognostication and personalized treatment. However, timely molecular diagnostic testing for patients with brain tumors is limited, complicating surgical and adjuvant treatment and obstructing clinical trial enrollment. In this study, we developed DeepGlioma, a rapid ($< 90$ seconds), artificial-intelligence-based diagnostic screening system to streamline the molecular diagnosis of diffuse gliomas. DeepGlioma is trained using a multimodal dataset that includes stimulated Raman histology (SRH); a rapid, label-free, non-consumptive, optical imaging method; and large-scale, public genomic data. In a prospective, multicenter, international testing cohort of patients with diffuse glioma ($n=153$) who underwent real-time SRH imaging, we demonstrate that DeepGlioma can predict the molecular alterations used by the World Health Organization to define the adult-type diffuse glioma taxonomy (IDH mutation, 1p19q co-deletion and ATRX mutation), achieving a mean molecular classification accuracy of $93.3\pm 1.6\%$. Our results represent how artificial intelligence and optical histology can be used to provide a rapid and scalable adjunct to wet lab methods for the molecular screening of patients with diffuse glioma.Comment: Paper published in Nature Medicin

Crop Updates 2002 - Oilseeds

This session covers twenty seven papers from different authors: 1. Forward and acknowledgements, Dave Eksteen, ACTING MANAGER OILSEEDS PRODUCTIVITY AND INDUSTRY DEVELOPMENT Department of Agriculture PLENARY SESSION 2. GMO canola - Track record in Canada, K. Neil Harker and George W. Clayton,Agriculture and Agri-Food Canada, Lacombe Research Centre, Lacombe, Alberta, R. Keith Downey, Agriculture and Agri-Food Canada, Saskatoon Research Centre, Saskatoon, Saskatchewan 3. GMO canola – Prospects in Western Australia farming systems, Keith Alcock, Crop Improvement Institute, Department of Agriculture 4. Diamondback moth (DBM) in canola, Kevin Walden, Department of Agriculture CANOLA AGRONOMY 5. Getting the best out of canola in the low rainfall central wheatbelt, Bevan Addison and Peter Carlton, Elders Ltd 6. Canola variety performance in Western Australia, Kevin Morthorpe, Stephen Addenbrooke and Alex Ford, Pioneer Hi-Bred Australia P/L 7. Relative performance of new canola varieties in Department of Agriculture variety trials in 2000 and 2001, S. Hasan Zaheer, GSARI, Department of Agriculture, G. Walton, Crop Improvement Institute, Department of Agriculture 8. Which canola cultivar should I sow? Imma Farré, CSIRO Plant Industry, Floreat, Bill Bowden,Western Australia Department of Agriculture 9. The effect of seed generation and seed source on yield and quality of canola, Paul Carmody, Department of Agriculture 10. The accumulation of oil in Brassica species, J.A. Fortescue and D.W. Turner, Plant Biology, Faculty of Natural and Agricultural Sciences, The University of Western Australia, B. Tan, PO Box 1249, South Perth 11. Potential and performance of alternative oilseeds in WA, Margaret C. Campbell, Centre for Legumes in Mediterranean Agriculture 12. Comparison of oilseed crops in WA, Ian Pritchard and Paul Carmody, Department of Agriculture, Centre for Cropping Systems, Margaret Campbell, Centre for Legumes in Mediterranean Agriculture 13. Identifying constraints to canola production, Dave Eksteen, Canola Development Officer, Department of Agriculture 14. Boron – should we be worried about it? Richard W. BellA, K. FrostA, Mike WongB, and Ross BrennanC , ASchool of Environmental Science, Murdoch University, BCSIRO Land and Water, CDepartment of Agriculture PEST AND DISEASE 15. Yield losses caused when Beet Western Yellows Virus infects canola, Roger Jones and Jenny Hawkes, Department of Agriculture, and Centre for Legumes in Mediterranean Agriculture 16. Influence of climate on aphid outbreaks and virus epidemics in canola, Debbie Thackray, Jenny Hawkes and Roger Jones, Centre for Legumes in Mediterranean Agriculture and Department of Agriculture 17. The annual shower of blackleg ascospores in canola: Can we predict and avoid it? Moin U. Salam, Ravjit K. Khangura, Art J. Diggle and Martin J. Barbetti, Department of Agriculture 18. Environmental influences on production and release of ascospores of blackleg and their implications in blackleg management in canola, Ravjit K. Khangura, Martin J. Barbetti , Moin U. Salam and Art J. Diggle, Department of Agriculture 19. WA blackleg resistance ratings on canola varieties form 2002, Ravjit Khangura, Martin J. Barbetti and Graham Walton, Department of Agriculture 20. Bronzed field beetle management in canola, Phil Michael, Department of Agriculture 21. DBM control in canola: Aerial versus boom application, Paul Carmody, Department of Agriculture 22. Effect of single or multiple spray trearments on the control of Diamondback moth (Plutella xylostella) and yield of canola at Wongan Hills, Françoise Berlandier, Paul Carmody and Christiaan Valentine, Department of Agriculture ESTABLISHMENT 23. GrainGuardÔ - A biosecurity plan for the canola industry, Greg Shea, Department of Agriculture 24. Large canola seed is best, particularly for deep sowing, Glen Riethmuller, Rafiul Alam, Greg Hamilton and Jo Hawksley, Department of Agriculture 25. Canola establishment with seed size, tines and discs, with and without stubble, Glen Riethmuller, Rafiul Alam, Greg Hamilton and Jo Hawksley, Department of Agriculture WEEDS 26. Role of Roundup ReadyÒ canola in the farming system, Art Diggle1, Patrick Smith2, Paul Neve3, Felicity Flugge4, Amir Abadi5, Stephen Powles3 1Department of Agriculture, 2CSIRO, Sustainable Ecosystems, 3Western Australian Herbicide Resistance Initiative, University of Western Australia, 4Centre for Legumes in Mediterranean Agriculture, University of Western Australia, 5Touchstone Consulting, Mt Hawthorn FEED 27. Getting value from canola meals in the animal feed industries: Aquaculture, Brett Glencross and John Curnow, Department of Fisheries - Government of Western Australia and Wayne Hawkins, Department of Agricultur

Design of Nanoparticulate Group 2 Influenza Virus Hemagglutinin Stem Antigens That Activate Unmutated Ancestor B Cell Receptors of Broadly Neutralizing Antibody Lineages.

Influenza vaccines targeting the highly conserved stem of the hemagglutinin (HA) surface glycoprotein have the potential to protect against pandemic and drifted seasonal influenza viruses not covered by current vaccines. While HA stem-based immunogens derived from group 1 influenza A viruses have been shown to induce intragroup heterosubtypic protection, HA stem-specific antibody lineages originating from group 2 may be more likely to possess broad cross-group reactivity. We report the structure-guided development of mammalian-cell-expressed candidate vaccine immunogens based on influenza A virus group 2 H3 and H7 HA stem trimers displayed on self-assembling ferritin nanoparticles using an iterative, multipronged approach involving helix stabilization, loop optimization, disulfide bond addition, and side-chain repacking. These immunogens were thermostable, formed uniform and symmetric nanoparticles, were recognized by cross-group-reactive broadly neutralizing antibodies (bNAbs) with nanomolar affinity, and elicited protective, homosubtypic antibodies in mice. Importantly, several immunogens were able to activate B cells expressing inferred unmutated common ancestor (UCA) versions of cross-group-reactive human bNAbs from two multidonor classes, suggesting they could initiate elicitation of these bNAbs in humans. Current influenza vaccines are primarily strain specific, requiring annual updates, and offer minimal protection against drifted seasonal or pandemic strains. The highly conserved stem region of hemagglutinin (HA) of group 2 influenza A virus subtypes is a promising target for vaccine elicitation of broad cross-group protection against divergent strains. We used structure-guided protein engineering employing multiple protein stabilization methods simultaneously to develop group 2 HA stem-based candidate influenza A virus immunogens displayed as trimers on self-assembling nanoparticles. Characterization of antigenicity, thermostability, and particle formation confirmed structural integrity. Group 2 HA stem antigen designs were identified that, when displayed on ferritin nanoparticles, activated B cells expressing inferred unmutated common ancestor (UCA) versions of human antibody lineages associated with cross-group-reactive, broadly neutralizing antibodies (bNAbs). Immunization of mice led to protection against a lethal homosubtypic influenza virus challenge. These candidate vaccines are now being manufactured for clinical evaluation

Crop Updates 2006 - Lupins and Pulses

This session covers sixty six papers from different authors: 2005 LUPIN AND PULSE INDUSTRY HIGHLIGHTS 1. Lupin Peter White, Department of Agriculture 2. Pulses Mark Seymour, Department of Agriculture 3. Monthly rainfall at experimental sites in 2005 4. Acknowledgements Amelia McLarty EDITOR 5. Contributors 6. Background Peter White, Department of Agriculture 2005 REGIONAL ROUNDUP 7. Northern agricultural region Wayne Parker, Department of Agriculture 8. Central agricultural region Ian Pritchard and Bob French, Department of Agriculture 9. Great southern and lakes Rodger Beermier, Department of Agriculture 10. South east region Mark Seymour, Department of Agriculture LUPIN AND PULSE PRODUCTION AGRONOMY AND GENETIC IMPROVEMENT 11. Lupin Peter White, Department of Agriculture 12. Narrow-leafed lupin breeding Bevan Buirchell, Department of Agriculture 13. Progress in the development of pearl lupin (Lupinus mutabilis) for Australian agriculture, Mark Sweetingham1,2, Jon Clements1, Geoff Thomas2, Roger Jones1, Sofia Sipsas1, John Quealy2, Leigh Smith1 and Gordon Francis1 1CLIMA, The University of Western Australia 2Department of Agriculture 14. Molecular genetic markers and lupin breeding, Huaan Yang, Jeffrey Boersma, Bevan Buirchell, Department of Agriculture 15. Construction of a genetic linkage map using MFLP, and identification of molecular markers linked to domestication genes in narrow-leafed lupin (Lupinus augustiflolius L) Jeffrey Boersma1,2, Margaret Pallotta3, Bevan Buirchell1, Chengdao Li1, Krishnapillai Sivasithamparam2 and Huaan Yang1 1Department of Agriculture, 2The University of Western Australia, 3Australian Centre for Plant Functional Genomics, South Australia 16. The first gene-based map of narrow-leafed lupin – location of domestication genes and conserved synteny with Medicago truncatula, M. Nelson1, H. Phan2, S. Ellwood2, P. Moolhuijzen3, M. Bellgard3, J. Hane2, A. Williams2, J. Fos‑Nyarko4, B. Wolko5, M. Książkiewicz5, M. Cakir4, M. Jones4, M. Scobie4, C. O’Lone1, S.J. Barker1, R. Oliver2, and W. Cowling1 1School of Plant Biology, The University of Western Australia, 2Australian Centre for Necrotrophic Fungal Pathogens, Murdoch University, 3Centre for Bioinformatics and Biological Computing, Murdoch University, 4School of Biological Sciences and Biotechnology, SABC, Murdoch University,5Institute of Plant Genetics, Polish Academy of Sciences, Poznań, Poland 17. How does lupin optimum density change row spacing? Bob French and Laurie Maiolo, Department of Agriculture 18. Wide row spacing and seeding rate of lupins with conventional and precision seeding machines Martin Harries, Jo Walker and Murray Blyth, Department of Agriculture 19. Influence of row spacing and plant density on lupin competition with annual ryegrass, Martin Harries, Jo Walker and Murray Blyth, Department of Agriculture 20. Effect of timing and speed of inter-row cultivation on lupins, Martin Harries, Jo Walker and Steve Cosh, Department of Agriculture 21. The interaction of atrazine herbicide rate and row spacing on lupin seedling survival, Martin Harries and Jo Walker Department of Agriculture 22. The banding of herbicides on lupin row crops, Martin Harries, Jo Walker and Murray Blyth, Department of Agriculture 23. Large plot testing of herbicide tolerance of new lupin lines, Wayne Parker, Department of Agriculture 24. Effect of seed source and simazine rate of seedling emergence and growth, Peter White and Greg Shea, Department of Agriculture 25. The effect of lupin row spacing and seeding rate on a following wheat crop, Martin Harries, Jo Walker and Dirranie Kirby, Department of Agriculture 26. Response of crop lupin species to row spacing, Leigh Smith1, Kedar Adhikari1, Jon Clements2 and Patrizia Guantini3, 1Department of Agriculture, 2CLIMA, The University of Western Australia, 3University of Florence, Italy 27. Response of Lupinus mutabilis to lime application and over watering, Peter White, Leigh Smith and Mark Sweetingham, Department of Agriculture 28. Impact of anthracnose on yield of Andromeda lupins, Geoff Thomas, Kedar Adhikari and Katie Bell, Department of Agriculture 29. Survey of lupin root health (in major production areas), Geoff Thomas, Ken Adcock, Katie Bell, Ciara Beard and Anne Smith, Department of Agriculture 30. Development of a generic forecasting and decision support system for diseases in the Western Australian wheatbelt, Tim Maling1, Art Diggle1,2, Debbie Thackray1, Kadambot Siddique1 and Roger Jones1,2 1CLIMA, The University of Western Australia, 2Department of Agriculture 31.Tanjil mutants highly tolerant to metribuzin, Ping Si1, Mark Sweetingham1,2, Bevan Buirchell1,2 and Huaan Yang l,2 1CLIMA, The University of Western Australia, 2Department of Agriculture 32. Precipitation pH vs. yield and functional properties of lupin protein isolate, Vijay Jayasena1, Hui Jun Chih1 and Ken Dods2 1Curtin University of Technology, 2Chemistry Centre 33. Lupin protein isolation with the use of salts, Vijay Jayasena1, Florence Kartawinata1,Ranil Coorey1 and Ken Dods2 1Curtin University of Technology, 2Chemistry Centre 34. Field pea, Mark Seymour, Department of Agriculture 35. Breeding highlights Kerry Regan1,2, Tanveer Khan1,2, Stuart Morgan1 and Phillip Chambers1 1Department of Agriculture, 2CLIMA, The University of Western Australia 36. Variety evaluation, Kerry Regan1,2, Tanveer Khan1,2, Jenny Garlinge1 and Rod Hunter1 1Department of Agriculture, 2CLIMA, The University of Western Australia 37. Days to flowering of field pea varieties throughout WA Mark Seymour1, Ian Pritchard1, Rodger Beermier1, Pam Burgess1 and Dr Eric Armstrong2 Department of Agriculture, 2NSW Department of Primary Industries, Wagga Wagga 38. Semi-leafless field peas yield more, with less ryegrass seed set, in narrow rows, Glen Riethmuller, Department of Agriculture 39. Swathing, stripping and other innovative ways to harvest field peas, Mark Seymour, Ian Pritchard, Rodger Beermier and Pam Burgess, Department of Agriculture 40. Pulse demonstrations, Ian Pritchard, Wayne Parker, Greg Shea, Department of Agriculture 41. Field pea extension – focus on field peas 2005, Ian Pritchard, Department of Agriculture 42. Field pea blackspot disease in 2005: Prediction versus reality, Moin Salam, Jean Galloway, Pip Payne, Bill MacLeod and Art Diggle, Department of Agriculture 43. Pea seed-borne mosaic virus in pulses: Screening for seed quality defects and virus resistance, Rohan Prince, Brenda Coutts and Roger Jones, Department of Agriculture, and CLIMA, The University of Western Australia 44. Yield losses from sowing field peas infected with pea seed-borne mosaic virus, Rohan Prince, Brenda Coutts and Roger Jones, Department of Agriculture, and CLIMA, The University of Western Australia 45. Desi chickpea, Wayne Parker, Department of Agriculture 46. Breeding highlights, Tanveer Khan 1,2, Pooran Gaur3, Kadambot Siddique2, Heather Clarke2, Stuart Morgan1and Alan Harris1, 1Department of Agriculture2CLIMA, The University of Western Australia, 3International Crop Research Institute for Semi Arid Tropics (ICRISAT), India 47. National chickpea improvement program, Kerry Regan1, Ted Knights2 and Kristy Hobson3,1Department of Agriculture, 2Agriculture New South Wales 3Department of Primary Industries, Victoria 48. Chickpea breeding lines in CVT exhibit excellent ascochyta blight resistance, Tanveer Khan1,2, Alan Harris1, Stuart Morgan1 and Kerry Regan1,2, 1Department of Agriculture, 2CLIMA, The University of Western Australia 49. Variety evaluation, Kerry Regan1,2, Tanveer Khan1,2, Jenny Garlinge2 and Rod Hunter2, 1CLIMA, The University of Western Australia 2Department of Agriculture 50. Desi chickpeas for the wheatbelt, Wayne Parker and Ian Pritchard, Department of Agriculture 51. Large scale demonstration of new chickpea varieties, Wayne Parker, MurrayBlyth, Steve Cosh, Dirranie Kirby and Chris Matthews, Department of Agriculture 52. Ascochyta management with new chickpeas, Martin Harries, Bill MacLeod, Murray Blyth and Jo Walker, Department of Agriculture 53. Management of ascochyta blight in improved chickpea varieties, Bill MacLeod1, Colin Hanbury2, Pip Payne1, Martin Harries1, Murray Blyth1, Tanveer Khan1,2, Kadambot Siddique2, 1Department of Agriculture, 2CLIMA, The University of Western Australia 54. Botrytis grey mould of chickpea, Bill MacLeod, Department of Agriculture 55. Kabuli chickpea, Kerry Regan, Department of Agriculture, and CLIMA, The University of Western Australia 56. New ascochyta blight resistant, high quality kabuli chickpea varieties, Kerry Regan1,2, Kadambot Siddique2, Tim Pope2 and Mike Baker1, 1Department of Agriculture, 2CLIMA, The University of Western Australia 57. Crop production and disease management of Almaz and Nafice, Kerry Regan and Bill MacLeod, Department of Agriculture, and CLIMA, The University of Western Australia 58. Faba bean,Mark Seymour, Department of Agriculture 59. Germplasm evaluation – faba bean, Mark Seymour1, Tim Pope2, Peter White1, Martin Harries1, Murray Blyth1, Rodger Beermier1, Pam Burgess1 and Leanne Young1,1Department of Agriculture, 2CLIMA, The University of Western Australia 60. Factors affecting seed coat colour of faba bean during storage, Syed Muhammad Nasar-Abbas1, Julie Plummer1, Kadambot Siddique2, Peter White 3, D. Harris4 and Ken Dods4.1The University of Western Australia, 2CLIMA, The University of Western Australia, 3Department of Agriculture, 4Chemistry Centre 61. Lentil,Kerry Regan, Department of Agriculture, and CLIMA, The University of Western Australia 62. Variety and germplasm evaluation, Kerry Regan1,2, Tim Pope2, Leanne Young1, Phill Chambers1, Alan Harris1, Wayne Parker1 and Michael Materne3, 1Department of Agriculture 2CLIMA, The University of Western Australia, 3Department of Primary Industries, Victoria Pulse species 63. Land suitability for production of different crop species in Western Australia, Peter White, Dennis van Gool, and Mike Baker, Department of Agriculture 64. Genomic synteny in legumes: Application to crop breeding, Huyen Phan1, Simon Ellwood1, J. Hane1, Angela Williams1, R. Ford2, S. Thomas3 and Richard Oliver1,1Australian Centre of Necrotrophic Plant Pathogens, Murdoch University 2BioMarka, School of Agriculture and Food Systems, ILFR, University of Melbourne 3NSW Department of Primary Industries 65. ALOSCA – Development of a dry flow legume seed inoculant, Rory Coffey and Chris Poole, ALOSCA Technologies Pty Ltd 66. Genetic dissection of resistance to fungal necrotrophs in Medicago truncatula, Simon Ellwood1, Theo Pfaff1, Judith Lichtenzveig12, Lars Kamphuis1, Nola D\u27Souza1, Angela Williams1, Emma Groves1, Karam Singh2 and Richard Oliver1 1Australian Centre of Necrotrophic Plant Pathogens, Murdoch University, 2CSIRO Plant Industry APPENDIX I: LIST OF COMMON ACRONYM

Genetic diversity fuels gene discovery for tobacco and alcohol use

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury(1-4). These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries(5). Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.Peer reviewe

Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, repeated measurements, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype