What is quantitative genetics?

Quantitative genetics is the study of the genetics of quantitative traits, which show variation between individuals both within and across populations. Part of that variation can be attributed to genetic factors as demonstrated by resemblance between relatives. The genetic architecture is polygenic which is well-approximated, at least in the first instance, through the infinitesimal model theory first introduced by Ronald Fisher over 100 years ago. Quantitative genetics theory ties in with population genetics and evolutionary genetics theory which provide a framework for understanding standing variation. However, validity of quantitative genetic theory over the last century has depended heavily on selection theory which can be tested in populations undergoing artificial selection.

What is quantitative genetics?

Who attends the International Conference of Quantitative Genetics (ICQG)?

ICQG6 will bring together researchers from the full range of applications of quantitative genetics - from plants, crops and trees to livestock to humans including common disease, to wild populations and laboratory model species. This community comes together united by methods and theory. It provides a forum to be exposed to the solutions found in one species application, which may be novel but relevant to the problems faced in a new application. In the genomics era the integration of quantitative genetics theory across species applications is converging, and new quantitative trait phenotypes such as single cell gene expression are studied.

Who attends the International Conference of Quantitative Genetics (ICQG)?

How does a virtual meeting work across time zones?

We have scheduled the conference over a two week period, enough of a “block” to get a community buzz, but with a schedule of 3 sessions a day, of which at least two should be within the waking hours of any time zone. Each session is scheduled to have ~1.5 hours of content, but we will let sessions run up to 2 hours if there is discussion (we hope so!). All sessions will be recorded and will be uploaded immediately, so if the session is in your sleep time, you can watch as soon as you wake! We will use the program we had planned pre-COVID. We have 24 invited speakers each with a 35 minute time slot. We have many contributed talks of 15 minutes each. The conference will be run by zoom and these long format talks will be “live”. All speakers have been scheduled to speak in a slot friendly for their time zone. Concurrent with the talks we will have the “There’s no such thing as a dumb question” discussion channel. We invite comments to be posted throughout the talk. We will have a team manning the channel to help lead responses to questions, some of which of course will have to wait for the presenter. The conference starts on November 2nd or 3rd and finishes on November 12th or 13th depending on time zone.

How does a virtual meeting work across time zones?

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Invited Speakers

Hover on speaker’s image to see link to the recording.

Nicholas BartonQG Theory

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Nick Barton is a Professor of Evolutionary Genetics at the Institute of Science and Technology, Austria. Nick and his research group focus on the evolution of populations that are distributed through space, and that experience natural selection on many genes. Their research covers a wide range, including a long-term study of a flower colour hybrid zone in snapdragons (Antirrhinum), statistical analysis of the effects of selection on sequence variation, and theoretical work on speciation and quantitative genetics. Recent papers include analyses of “islands of divergence” in Antirrhinum, of a mouse selection experiment, and of the infinitesimal model for the inheritance of quantitative traits.

Nicholas BartonQG Theory

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Nick Barton is a Professor of Evolutionary Genetics at the Institute of Science and Technology, Austria. Nick and his research group focus on the evolution of populations that are distributed through space, and that experience natural selection on many genes. Their research covers a wide range, including a long-term study of a flower colour hybrid zone in snapdragons (Antirrhinum), statistical analysis of the effects of selection on sequence variation, and theoretical work on speciation and quantitative genetics. Recent papers include analyses of “islands of divergence” in Antirrhinum, of a mouse selection experiment, and of the infinitesimal model for the inheritance of quantitative traits.

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Ed BucklerQG in Maize and Other Crops

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Ed Buckler is a USDA-ARS crop geneticist based at Cornell University campus.
Ed’s research focusses on developing genomic, statistical, and bioinformatic methods with applications in maize and other crops. Key questions are:
· How does genetic variation give rise to phenotypic variation?
· How can we use genetics to make agriculture more efficient and share those efficiencies globally?
· How can we reduce the impact of agriculture on the environment?
Ed’s tools and approaches have been applied to over 3000 other species – everything from human genetics, nearly every crop, and many species of ecological interest. Ed’s latest papers have been on machine learning of RNA expression and the relationship between eQTL and fitness.

Ed BucklerQG in Maize and Other Crops

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Ed Buckler is a USDA-ARS crop geneticist based at Cornell University campus.
Ed’s research focusses on developing genomic, statistical, and bioinformatic methods with applications in maize and other crops. Key questions are:
· How does genetic variation give rise to phenotypic variation?
· How can we use genetics to make agriculture more efficient and share those efficiencies globally?
· How can we reduce the impact of agriculture on the environment?
Ed’s tools and approaches have been applied to over 3000 other species – everything from human genetics, nearly every crop, and many species of ecological interest. Ed’s latest papers have been on machine learning of RNA expression and the relationship between eQTL and fitness.

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Anne CharmantierQG in Wild Birds in the Anthropocene

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Anne Charmantier is an evolutionary ecologist interested in between-individual variation of life-history, morphological, and behavioural traits in natural populations. She holds a senior CNRS position (eq. Prof) in the Centre d’Ecologie Fonctionnelle et Evolutive (CNRS, UMR 5175, Montpellier, France). Her main research interests are focused on understanding the mechanisms involved in the evolution of adaptive traits, especially in a context of climate change and urbanisation. Since 2007 she has been managing a blue tit/great tit project dating back from 1976, which offers unique opportunity to study adaptation in heterogeneous and rapidly changing environments. In 2014, she published the OUP book ‘Quantitative Genetics in the Wild’ with Profs. Dany Garant and Loeske Kruuk.

Anne CharmantierQG in Wild Birds in the Anthropocene

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Anne Charmantier is an evolutionary ecologist interested in between-individual variation of life-history, morphological, and behavioural traits in natural populations. She holds a senior CNRS position (eq. Prof) in the Centre d’Ecologie Fonctionnelle et Evolutive (CNRS, UMR 5175, Montpellier, France). Her main research interests are focused on understanding the mechanisms involved in the evolution of adaptive traits, especially in a context of climate change and urbanisation. Since 2007 she has been managing a blue tit/great tit project dating back from 1976, which offers unique opportunity to study adaptation in heterogeneous and rapidly changing environments. In 2014, she published the OUP book ‘Quantitative Genetics in the Wild’ with Profs. Dany Garant and Loeske Kruuk.

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Susanne DreisigackerQG in Wheat

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Over the past ten years, Dr. Susanne Dreisigacker has been leading the Wheat Molecular Breeding Laboratory at the International Wheat and Maize Improvement Center (CIMMYT) in Mexico. Dr. Dreisigacker’s main interest is to bring promising genomics tools into use in the CIMMYT Global Wheat Program. Her lab conducts genetics studies on key biotic (foliar diseases), abiotic (yield and yield stability) and quality factors that limit the production and value of wheat especially in the developing world. She provides the Global Wheat Program access to state-of-the-art molecular technologies and together with the CIMMYTs wheat breeders she applies marker-assisted selection strategies such as MAS, MABC and genomic selection targeting to accelerate genetic gains in bread and durum wheat. Dr. Dreisigacker’s research team collaborates with scientists around the world, including teams in India, China, Middle East, UK, USA, Germany, and South Africa. She trains and supervises students coming from local universities or internationally through CIMMYT’s intensive wheat training program.

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Susanne DreisigackerQG in Wheat

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Over the past ten years, Dr. Susanne Dreisigacker has been leading the Wheat Molecular Breeding Laboratory at the International Wheat and Maize Improvement Center (CIMMYT) in Mexico. Dr. Dreisigacker’s main interest is to bring promising genomics tools into use in the CIMMYT Global Wheat Program. Her lab conducts genetics studies on key biotic (foliar diseases), abiotic (yield and yield stability) and quality factors that limit the production and value of wheat especially in the developing world. She provides the Global Wheat Program access to state-of-the-art molecular technologies and together with the CIMMYTs wheat breeders she applies marker-assisted selection strategies such as MAS, MABC and genomic selection targeting to accelerate genetic gains in bread and durum wheat. Dr. Dreisigacker’s research team collaborates with scientists around the world, including teams in India, China, Middle East, UK, USA, Germany, and South Africa. She trains and supervises students coming from local universities or internationally through CIMMYT’s intensive wheat training program.

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Yaniv ErlichQG in Crowd-Sourced Data

Watch RecordingDr. Yaniv Erlich is the Chief Science Officer of MyHeritage.com and an Associate Professor of Computer Science and Computational Biology at Columbia University (leave of absence). Prior to these positions, he was a Fellow at the Whitehead Institute, MIT. Dr. Erlich received his bachelor’s degree from Tel-Aviv University, Israel (2006) and a PhD from the Watson School of Biological Sciences at Cold Spring Harbor Laboratory (2010). Dr. Erlich’s research interests are computational human genetics. Dr. Erlich is a TEDMED speaker (2018), the recipient of DARPA’s Young Faculty Award (2017), the Burroughs Wellcome Career Award (2013), Harold M. Weintraub award (2010), the IEEE/ACM-CS HPC award (2008), and he was selected as one of 2010 Tomorrow’s PIs team of Genome Technology. He is currently working on statistical genetics at scale using direct to consumer genomics.

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Yaniv ErlichQG in Crowd-Sourced Data

Watch RecordingDr. Yaniv Erlich is the Chief Science Officer of MyHeritage.com and an Associate Professor of Computer Science and Computational Biology at Columbia University (leave of absence). Prior to these positions, he was a Fellow at the Whitehead Institute, MIT. Dr. Erlich received his bachelor’s degree from Tel-Aviv University, Israel (2006) and a PhD from the Watson School of Biological Sciences at Cold Spring Harbor Laboratory (2010). Dr. Erlich’s research interests are computational human genetics. Dr. Erlich is a TEDMED speaker (2018), the recipient of DARPA’s Young Faculty Award (2017), the Burroughs Wellcome Career Award (2013), Harold M. Weintraub award (2010), the IEEE/ACM-CS HPC award (2008), and he was selected as one of 2010 Tomorrow’s PIs team of Genome Technology. He is currently working on statistical genetics at scale using direct to consumer genomics.

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Daniel GaffneyQG in Human Induced Pluripotent Stem Cells

Daniel is a Group Leader at the Wellcome Sanger Institute. The long-term goal of Daniel’s group is to understand the molecular and cellular consequences of genetic changes in gene regulatory regions. His research combines statistical genetics with high-throughput experimental techniques in human cells to address these questions. Much of the group’s recent research has been focussed on using human induced pluripotent stem cells (hIPSCs) and cells derived from hIPSCs as model systems to map and characterise human noncoding genetic changes.

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Daniel GaffneyQG in Human Induced Pluripotent Stem Cells

Daniel is a Group Leader at the Wellcome Sanger Institute. The long-term goal of Daniel’s group is to understand the molecular and cellular consequences of genetic changes in gene regulatory regions. His research combines statistical genetics with high-throughput experimental techniques in human cells to address these questions. Much of the group’s recent research has been focussed on using human induced pluripotent stem cells (hIPSCs) and cells derived from hIPSCs as model systems to map and characterise human noncoding genetic changes.

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Lucia Galvão de AlbuquerqueQG in Tropical Cattle

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Lucia Galvão de Albuquerque is Professor of Animal Breeding and Genetics at the Department of Animal Science at São Paulo State University and a researcher of the National Council for Scientific and Technological Development (CNPq). She has experience in beef cattle breeding, working closely with the beef industry in Brazil. Lately, she has been leading research projects, based in complete DNA and RNA sequences, with the objective of developing technologies to increase biologic knowledge and to promote genetic improvement of quality, efficiency and sustainability of Nellore beef cattle production.

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Lucia Galvão de AlbuquerqueQG in Tropical Cattle

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Lucia Galvão de Albuquerque is Professor of Animal Breeding and Genetics at the Department of Animal Science at São Paulo State University and a researcher of the National Council for Scientific and Technological Development (CNPq). She has experience in beef cattle breeding, working closely with the beef industry in Brazil. Lately, she has been leading research projects, based in complete DNA and RNA sequences, with the objective of developing technologies to increase biologic knowledge and to promote genetic improvement of quality, efficiency and sustainability of Nellore beef cattle production.

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Jarrod HadfieldQG theory and applications in wild systems

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Jarrod is an evolutionary biologist based in the Institute for Evolutionary Biology at the University of Edinburgh. He is interested in understanding how natural and kin selection operate in wild systems, and how the genetic basis of traits determines how they evolve in response to selection. His lab combines theoretical work and statistical development with empirical work primarily on wild populations of bird. Current QG projects in the lab are 1) the importance of indirect genetic effects (parent-offspring, siblings) for the evolution of growth traits and the relationship between indirect genetic models and kin selection models 2) the role of phenotypic plasticity versus genetic differentiation in response to spatially and temporally fluctuating environments 3) the relative importance of mutation versus selection in determining levels of quantitative genetic variation and 4) theory and statistical methods for dealing with genetic and environmental skew. In addition to these biological questions he is interested in general statistical methods for hierarchical models, particularly MCMC methods for non-Gaussian data.

Jarrod HadfieldQG theory and applications in wild systems

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Jarrod is an evolutionary biologist based in the Institute for Evolutionary Biology at the University of Edinburgh. He is interested in understanding how natural and kin selection operate in wild systems, and how the genetic basis of traits determines how they evolve in response to selection. His lab combines theoretical work and statistical development with empirical work primarily on wild populations of bird. Current QG projects in the lab are 1) the importance of indirect genetic effects (parent-offspring, siblings) for the evolution of growth traits and the relationship between indirect genetic models and kin selection models 2) the role of phenotypic plasticity versus genetic differentiation in response to spatially and temporally fluctuating environments 3) the relative importance of mutation versus selection in determining levels of quantitative genetic variation and 4) theory and statistical methods for dealing with genetic and environmental skew. In addition to these biological questions he is interested in general statistical methods for hierarchical models, particularly MCMC methods for non-Gaussian data.

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Rachel HawkenQG in Broiler Chickens

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Rachel Hawken currently leads a team at Cobb-Vantress developing genetic tools to maintain a competitive product for the broiler breeding industry. To achieve this goal her team explores genomic and statistical genetic approaches, and engages innovative technologies and collaborative research. Rachel received her Ph.D. at The University of Melbourne, School of Veterinary Science. She moved to Minnesota to complete Postdoctoral Fellow and Research Fellow positions at the School of Veterinary Science at the University of Minnesota. Rachel then returned to Australia to join the Commonwealth Science and Industrial Research Organization (CSIRO) as a Senior Research scientist, before being recruited to Cobb in Arkansas. Rachel is now the Senior Director for Genetics (Genomics and Quantitative Genetics) at Cobb. The focus of Rachel’s early academic career was the development and testing of genomic tools to enable the selection of superior breeding stock for the swine, sheep, dairy and beef industries. Since joining Cobb, Rachel has implemented such genomic tools for the genetic improvement of the Cobb broiler. In addition, she has had the privilege of designing and implementing logistic and sampling systems needed to engage genomic technologies. Rachel is also responsible for the statistical analyses of large broiler performance data sets produced by Cobb to achieve genetic improvement.

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Rachel HawkenQG in Broiler Chickens

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Rachel Hawken currently leads a team at Cobb-Vantress developing genetic tools to maintain a competitive product for the broiler breeding industry. To achieve this goal her team explores genomic and statistical genetic approaches, and engages innovative technologies and collaborative research. Rachel received her Ph.D. at The University of Melbourne, School of Veterinary Science. She moved to Minnesota to complete Postdoctoral Fellow and Research Fellow positions at the School of Veterinary Science at the University of Minnesota. Rachel then returned to Australia to join the Commonwealth Science and Industrial Research Organization (CSIRO) as a Senior Research scientist, before being recruited to Cobb in Arkansas. Rachel is now the Senior Director for Genetics (Genomics and Quantitative Genetics) at Cobb. The focus of Rachel’s early academic career was the development and testing of genomic tools to enable the selection of superior breeding stock for the swine, sheep, dairy and beef industries. Since joining Cobb, Rachel has implemented such genomic tools for the genetic improvement of the Cobb broiler. In addition, she has had the privilege of designing and implementing logistic and sampling systems needed to engage genomic technologies. Rachel is also responsible for the statistical analyses of large broiler performance data sets produced by Cobb to achieve genetic improvement.

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David HouleQG of the Genotype-Phenotype Map

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David is an evolutionary geneticist based at Florida State University who studies the relationship between the genomic, genetic and functional underpinnings of life and the process of adaptation at the phenotypic level. His lab uses the appendages of Drosophila melanogaster as a model. His current research goal is to understand how the processes of mutation and the forces that maintain quantitative genetic variation within populations are connected to long-term evolutionary trends.

David HouleQG of the Genotype-Phenotype Map

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David is an evolutionary geneticist based at Florida State University who studies the relationship between the genomic, genetic and functional underpinnings of life and the process of adaptation at the phenotypic level. His lab uses the appendages of Drosophila melanogaster as a model. His current research goal is to understand how the processes of mutation and the forces that maintain quantitative genetic variation within populations are connected to long-term evolutionary trends.

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Satish KumarQG in Horticulture

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Satish Kumar is a scientist at Plant & Food Research, New Zealand. He earned his PhD degree in Genetics and Breeding from Massey University, and then worked as a scientist (Tree Improvement) at the New Zealand Forest Research Institute, Rotorua for 10 years before joining Plant & Food Research in 2009. His area of research includes breeding and genetic evaluation strategies, germplasm conservation and improvement, and genetic architecture of fruit traits. Dr Kumar led the first application of genomic selection and GWAS in apple breeding. His current research focuses on the integration of genetics and genomics technologies into breeding programmes of horticultural crops.​

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Satish KumarQG in Horticulture

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Satish Kumar is a scientist at Plant & Food Research, New Zealand. He earned his PhD degree in Genetics and Breeding from Massey University, and then worked as a scientist (Tree Improvement) at the New Zealand Forest Research Institute, Rotorua for 10 years before joining Plant & Food Research in 2009. His area of research includes breeding and genetic evaluation strategies, germplasm conservation and improvement, and genetic architecture of fruit traits. Dr Kumar led the first application of genomic selection and GWAS in apple breeding. His current research focuses on the integration of genetics and genomics technologies into breeding programmes of horticultural crops.​

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Michael LynchQG and Evolutionary Biology

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Michael Lynch is Director of the Biodesign Institute for Mechanisms of Evolution at Arizona State University. His research is focused on mechanisms of evolution at the gene, genomic, cellular, and phenotypic levels, with special attention being given to the roles of mutation, random genetic drift, and recombination. This work relies on the integration of theory development and computational analysis with empirical work on several model systems, including the microcrustacean Daphnia, the ciliate Paramecium, and numerous microbial species. He is well-known to us all from the text books Lynch & Walsh (1998) Genetic Analysis of Quantitative Traits and now Walsh & Lynch (2018) Evolution and Selection of Quantitative Traits, as well as from Lynch (2007) Origins of Genome Architecture. He is a member of the US National Academy of Sciences, and past president of the Genetics Society of America, Society for Molecular Biology and Evolution, and Society for the Study of Evolution.

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Michael LynchQG and Evolutionary Biology

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Michael Lynch is Director of the Biodesign Institute for Mechanisms of Evolution at Arizona State University. His research is focused on mechanisms of evolution at the gene, genomic, cellular, and phenotypic levels, with special attention being given to the roles of mutation, random genetic drift, and recombination. This work relies on the integration of theory development and computational analysis with empirical work on several model systems, including the microcrustacean Daphnia, the ciliate Paramecium, and numerous microbial species. He is well-known to us all from the text books Lynch & Walsh (1998) Genetic Analysis of Quantitative Traits and now Walsh & Lynch (2018) Evolution and Selection of Quantitative Traits, as well as from Lynch (2007) Origins of Genome Architecture. He is a member of the US National Academy of Sciences, and past president of the Genetics Society of America, Society for Molecular Biology and Evolution, and Society for the Study of Evolution.

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Peter VisscherQG isn’t dead yet

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Peter Visscher FRS is a quantitative geneticist with research interests focussed on a better understanding of genetic variation for complex traits in human populations, including quantitative traits and disease, and on systems genomics. The first half of his research career to date was predominantly in livestock genetics (animal breeding is applied quantitative genetics), whereas the last 15 years he has contributed to methods, software and applications to quantify and dissect genetic variation in human traits.

Peter VisscherQG isn’t dead yet

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Peter Visscher FRS is a quantitative geneticist with research interests focussed on a better understanding of genetic variation for complex traits in human populations, including quantitative traits and disease, and on systems genomics. The first half of his research career to date was predominantly in livestock genetics (animal breeding is applied quantitative genetics), whereas the last 15 years he has contributed to methods, software and applications to quantify and dissect genetic variation in human traits.

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Jian YangNovel statistical methods for QG

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Jian Yang is a Professor of Statistical Genomics at the Institute for Molecular Bioscience, The University of Queensland (UQ). He received his PhD in 2008 from Zhejiang University, China, before undertaking postdoctoral research at the QIMR Berghofer Medical Research Institute in Brisbane. He joined UQ in 2012. His primary research interests are in developing novel statistical methods to better understand the genetic architecture of complex traits and diseases, to identify putative target genes, and to improve the accuracy of genomic risk prediction using high-throughput genetic and genomic data. He has led the development of QG analysis tools such as GCTA, SMR and OSCA. His recent papers have been on causal inference using GWAS summary data, and an extremely resource-efficient GWAS tool for large-scale data.

Jian YangNovel statistical methods for QG

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Jian Yang is a Professor of Statistical Genomics at the Institute for Molecular Bioscience, The University of Queensland (UQ). He received his PhD in 2008 from Zhejiang University, China, before undertaking postdoctoral research at the QIMR Berghofer Medical Research Institute in Brisbane. He joined UQ in 2012. His primary research interests are in developing novel statistical methods to better understand the genetic architecture of complex traits and diseases, to identify putative target genes, and to improve the accuracy of genomic risk prediction using high-throughput genetic and genomic data. He has led the development of QG analysis tools such as GCTA, SMR and OSCA. His recent papers have been on causal inference using GWAS summary data, and an extremely resource-efficient GWAS tool for large-scale data.

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Theo MeuwissenQG theory in livestock and crops

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Theo Meuwissen is a Professor at the Norwegian University of Life Sciences. His work focuses on uniting quantitative genetic theory with genomics technology, revolutionising the genetic improvement of livestock and crops.

Theo MeuwissenQG theory in livestock and crops

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Theo Meuwissen is a Professor at the Norwegian University of Life Sciences. His work focuses on uniting quantitative genetic theory with genomics technology, revolutionising the genetic improvement of livestock and crops.

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Han MulderQG of GxE Interaction

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Herman (Han) Mulder is Associate Professor at Wageningen University & Research Animal Breeding and Genomics, Netherlands. His main research interests are quantitative genetics of genotype by environment interaction and genetic control of environmental variation in livestock and aquaculture. Han’s research focuses on developing statistical methods to estimate genetic variance in environmental sensitivity, either due to known environmental factors, such as temperature, or unknown factors that could be animal specific and appear as differences in within-individual variance or within-family variance. Currently, Han’s research is focused at how genetic variance in environmental variance is a measure of genetic variance in resilience when using longitudinal profiles of animals such as daily milk yield in cattle and daily feed intake in various livestock species.

Han MulderQG of GxE Interaction

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Herman (Han) Mulder is Associate Professor at Wageningen University & Research Animal Breeding and Genomics, Netherlands. His main research interests are quantitative genetics of genotype by environment interaction and genetic control of environmental variation in livestock and aquaculture. Han’s research focuses on developing statistical methods to estimate genetic variance in environmental sensitivity, either due to known environmental factors, such as temperature, or unknown factors that could be animal specific and appear as differences in within-individual variance or within-family variance. Currently, Han’s research is focused at how genetic variance in environmental variance is a measure of genetic variance in resilience when using longitudinal profiles of animals such as daily milk yield in cattle and daily feed intake in various livestock species.

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Jessica RutkoskiQG in Rice

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Jessica received a Bachelor of Science degree in genetics from the University of Wisconsin-Madison in 2009. During her time at Wisconsin she worked for Professor Bill Tracy’s sweetcorn breeding program where she developed a love for plant breeding. Shortly after graduation, Jessica began her PhD work at Cornell University under the direction of wheat breeder and plant breeding professor Mark Sorrells. Jessica’s PhD research focused on genomic selection for quantitative disease resistance in wheat, and it included one of the first empirical genomic selection experiments in plants. After receiving her PhD in 2014, Jessica took a position as an assistant professor at Cornell and an adjunct associate scientist at CIMMYT working on integrating genomic selection and high-throughput phenotyping to predict breeding values for yield in wheat. Jessica is now leading the quantitative genetics cluster at the international rice research institute (IRRI) where her research currently focuses on improving rice breeding efficiency and monitoring breeding program effectiveness.

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Jessica RutkoskiQG in Rice

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Jessica received a Bachelor of Science degree in genetics from the University of Wisconsin-Madison in 2009. During her time at Wisconsin she worked for Professor Bill Tracy’s sweetcorn breeding program where she developed a love for plant breeding. Shortly after graduation, Jessica began her PhD work at Cornell University under the direction of wheat breeder and plant breeding professor Mark Sorrells. Jessica’s PhD research focused on genomic selection for quantitative disease resistance in wheat, and it included one of the first empirical genomic selection experiments in plants. After receiving her PhD in 2014, Jessica took a position as an assistant professor at Cornell and an adjunct associate scientist at CIMMYT working on integrating genomic selection and high-throughput phenotyping to predict breeding values for yield in wheat. Jessica is now leading the quantitative genetics cluster at the international rice research institute (IRRI) where her research currently focuses on improving rice breeding efficiency and monitoring breeding program effectiveness.

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Matthew StephensStatistics in QG

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Matthew Stephens is Professor of Statistics and Professor of Human Genetics at the University of Chicago, and a Gordon and Betty Moore Investigator in Data Driven Discovery. He received a BA in Mathematics (1992) and Diploma in Mathematical Statistics (1994) from the University of Cambridge UK, and a D.Phil in Statistics (1997) from the University of Oxford UK. Dr Stephens is a statistician and data scientist, who has made seminal contributions to the practice and applications of statistics in genetics. His research interests include analysis of
population structure, analysis of genetic association studies (including both complex traits, and molecular phenotypes, such as gene expression and chromatin accessibility), large scale regression and multiple testing. His lab distributes several widely-used sofware packages for statistical analysis, including PHASE and fastPHASE (for haplotype inference), GEMMA (for association testing) and BIMBAM (for genotype imputation and association testing).
Dr Stephens’s Honors include the Guy Medal in Bronze by the
Royal Statistical Society in 2006, was honored as a Medallion Lecturer by the Institute for Mathematical Statistics in 2014, and inclusion in the Thomson-Reuters list of Highly Cited Researchers 2014.

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Matthew StephensStatistics in QG

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Matthew Stephens is Professor of Statistics and Professor of Human Genetics at the University of Chicago, and a Gordon and Betty Moore Investigator in Data Driven Discovery. He received a BA in Mathematics (1992) and Diploma in Mathematical Statistics (1994) from the University of Cambridge UK, and a D.Phil in Statistics (1997) from the University of Oxford UK. Dr Stephens is a statistician and data scientist, who has made seminal contributions to the practice and applications of statistics in genetics. His research interests include analysis of
population structure, analysis of genetic association studies (including both complex traits, and molecular phenotypes, such as gene expression and chromatin accessibility), large scale regression and multiple testing. His lab distributes several widely-used sofware packages for statistical analysis, including PHASE and fastPHASE (for haplotype inference), GEMMA (for association testing) and BIMBAM (for genotype imputation and association testing).
Dr Stephens’s Honors include the Guy Medal in Bronze by the
Royal Statistical Society in 2006, was honored as a Medallion Lecturer by the Institute for Mathematical Statistics in 2014, and inclusion in the Thomson-Reuters list of Highly Cited Researchers 2014.

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Barbara StrangerQG of Gene Expression
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Barbara StrangerQG of Gene Expression
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Shamil SunyaevQG at the Interface with Biology

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Shamil Sunyaev is a Professor of Computational Genomics Medicine at Harvard Medical School. He obtained a PhD in molecular biophysics from the Moscow Institute of Physics and Technology and completed his postdoctoral training in bioinformatics at the European Molecular Biology Laboratory (EMBL). The primary focus of research in his lab is genetic variation, including the biology and evolution of mutation, the effect of variation on molecular function and structure, population genetics as a lens on evolution, and the maintenance and allelic architecture of complex traits.

Shamil SunyaevQG at the Interface with Biology

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Shamil Sunyaev is a Professor of Computational Genomics Medicine at Harvard Medical School. He obtained a PhD in molecular biophysics from the Moscow Institute of Physics and Technology and completed his postdoctoral training in bioinformatics at the European Molecular Biology Laboratory (EMBL). The primary focus of research in his lab is genetic variation, including the biology and evolution of mutation, the effect of variation on molecular function and structure, population genetics as a lens on evolution, and the maintenance and allelic architecture of complex traits.

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Albert TenesaQC in Human Big Data

Albert Tenesa studied agricultural engineering at the Polytechnic University of Valencia before undertaking an MSc in Quantitative Genetics and Genome Analysis at the University of Edinburgh, where he also completed his PhD in quantitative genetics, under the supervision of Peter Visscher and Sara Knott. After a postdoc with Professor Malcolm Dunlop working on colorectal cancer genetics, he became a group leader at the Roslin Institute and the Medical Research Council Human Genetics Unit at the University of Edinburgh. Albert’s research aims to understand how genetic variation contributes to phenotypic variation of complex traits in humans and to develop the tools that will help in transitioning from study cohorts to whole populations. You can follow his research team on twitter: @GroupTenesa.

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Albert TenesaQC in Human Big Data

Albert Tenesa studied agricultural engineering at the Polytechnic University of Valencia before undertaking an MSc in Quantitative Genetics and Genome Analysis at the University of Edinburgh, where he also completed his PhD in quantitative genetics, under the supervision of Peter Visscher and Sara Knott. After a postdoc with Professor Malcolm Dunlop working on colorectal cancer genetics, he became a group leader at the Roslin Institute and the Medical Research Council Human Genetics Unit at the University of Edinburgh. Albert’s research aims to understand how genetic variation contributes to phenotypic variation of complex traits in humans and to develop the tools that will help in transitioning from study cohorts to whole populations. You can follow his research team on twitter: @GroupTenesa.

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Bruce WalshQG and Evolutionary Biology

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Bruce Walsh is Professor, Ecology and Evolutionary Biology at the University of Arizona. His interests are broadly in using mathematical models to explore the interface of genetics and evolution, with particular focus on the evolution and analysis of complex genetic characters. He is well known to us all from the textbooks Lynch & Walsh (1998) Genetic Analysis of Quantitative Traits and now Walsh & Lynch (2018) Evolution and Selection of Quantitative Traits. He is a prolific teacher, having taught over 80 short courses during the last decade in 24 countries. He founded the Tucson Plant Breeding Institute and was a founding instructor in the African Plant Breeding Academy. He is also an avid lepidopterist, having described over two dozen new species of Arizona moths, and has three species named after him.

Bruce WalshQG and Evolutionary Biology

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Bruce Walsh is Professor, Ecology and Evolutionary Biology at the University of Arizona. His interests are broadly in using mathematical models to explore the interface of genetics and evolution, with particular focus on the evolution and analysis of complex genetic characters. He is well known to us all from the textbooks Lynch & Walsh (1998) Genetic Analysis of Quantitative Traits and now Walsh & Lynch (2018) Evolution and Selection of Quantitative Traits. He is a prolific teacher, having taught over 80 short courses during the last decade in 24 countries. He founded the Tucson Plant Breeding Institute and was a founding instructor in the African Plant Breeding Academy. He is also an avid lepidopterist, having described over two dozen new species of Arizona moths, and has three species named after him.

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Bruce WeirBetween Population and Forensic QG

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Bruce Weir is a Professor of Biostatistics at the University of Washington in Seattle. His research focuses on statistical methodology for genetic data, with an emphasis on allelic dependencies, population structure, disease associations and relationships, including applications in forensic genetics.

Bruce WeirBetween Population and Forensic QG

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Bruce Weir is a Professor of Biostatistics at the University of Washington in Seattle. His research focuses on statistical methodology for genetic data, with an emphasis on allelic dependencies, population structure, disease associations and relationships, including applications in forensic genetics.

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Eimear KennyTrans-ancestry human genetics

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Dr. Eimear Kenny, PhD, is Founding Director of the Institute for Genomic Health, and Associate Professor of Medicine and Genetics at Mount Sinai. She leads research at the interface of genomics, medicine, and computer science. Her research spans a number of different fields, including population and statistical genetics; computational and machine-learning approaches for genomics; biobank- and cohort-based research on monogenic disorders and common diseases; polygenic risk for human diseases and precision medicine.

Eimear KennyTrans-ancestry human genetics

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Dr. Eimear Kenny, PhD, is Founding Director of the Institute for Genomic Health, and Associate Professor of Medicine and Genetics at Mount Sinai. She leads research at the interface of genomics, medicine, and computer science. Her research spans a number of different fields, including population and statistical genetics; computational and machine-learning approaches for genomics; biobank- and cohort-based research on monogenic disorders and common diseases; polygenic risk for human diseases and precision medicine.

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Steve McCarrollQG in Single Neurones and Organoids

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Steve McCarroll is Professor of Biomedical Science and Genetics at Harvard Medical School. His research program reflects the diversity of his training. He was a Ph.D. student in Cori Bargmann’s lab (genetics and neuroscience in C. elegans) at U.C. San Francisco, then a postdoc in David Altshuler’s lab (human genetics and genomics) at MGH and the Broad Institute. The focus of Steve’s research is how human genomes vary and how this variation shapes human biology. His lab has led the development of single cell droplet gene expression sequencing and is using this technology to investigate allele specific gene expression in individual cell types.

Steve McCarrollQG in Single Neurones and Organoids

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Steve McCarroll is Professor of Biomedical Science and Genetics at Harvard Medical School. His research program reflects the diversity of his training. He was a Ph.D. student in Cori Bargmann’s lab (genetics and neuroscience in C. elegans) at U.C. San Francisco, then a postdoc in David Altshuler’s lab (human genetics and genomics) at MGH and the Broad Institute. The focus of Steve’s research is how human genomes vary and how this variation shapes human biology. His lab has led the development of single cell droplet gene expression sequencing and is using this technology to investigate allele specific gene expression in individual cell types.

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Trudy MackayQG using Drosophila as a model

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Trudy Mackay, FRS, is the Director of the Center for Human Genetics at Clemson University. Her research focuses on how multiple interacting molecular polymorphisms and environmental factors cause phenotypic variation in quantitative (complex) traits within and between populations and species. Using fruit flies (Drosophila) as a model system, she has used transposon tagging, high-resolution recombination mapping, genetic complementation tests, and whole genome transcript profiling to identify novel genes affecting morphology, lifespan, behaviors, stress resistance and human disease. She leads the Drosophila Genetic Reference Panel project that provides resources and computational approaches to integrate genotype-phenotype relationships across multiple levels of biological organization to uncover entire genetic pathways that affect variation of quantitative traits.

Trudy MackayQG using Drosophila as a model

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Trudy Mackay, FRS, is the Director of the Center for Human Genetics at Clemson University. Her research focuses on how multiple interacting molecular polymorphisms and environmental factors cause phenotypic variation in quantitative (complex) traits within and between populations and species. Using fruit flies (Drosophila) as a model system, she has used transposon tagging, high-resolution recombination mapping, genetic complementation tests, and whole genome transcript profiling to identify novel genes affecting morphology, lifespan, behaviors, stress resistance and human disease. She leads the Drosophila Genetic Reference Panel project that provides resources and computational approaches to integrate genotype-phenotype relationships across multiple levels of biological organization to uncover entire genetic pathways that affect variation of quantitative traits.

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Program

The program listed here is in Brisbane Time.
Go to PROGRAM tab to get the Program in your timezone.
Click on the title to see link to the recording.

  • Week 1
  • Week 2
  • Session 1 Nov 3rd
  • Session 2 Nov 3rd
  • Session 3 Nov 3rd
  • Session 4 Nov 4th
  • Session 5 Nov 4th
  • Session 6 Nov 4th
  • Session 7 Nov 5th
  • Session 8 Nov 5th
  • Session 9 Nov 5th
  • Session 10 Nov 6th
  • Session 11 Nov 6th
  • Session 12 Nov 6th
07:00 AM - 07:05 AMIntroduction to Session By Naomi Wray, Ben Hayes & Mark BlowsUniversity of Queensland, Australia
07:05 AM - 07:40 AMQuantitative genetics, past, present & future: views from the authors of Lynch & Walsh and Walsh & Lynch By Bruce WalshArizona, USA
07:40 AM - 08:20 AMQuantitative Genetics Isn’t Dead Yet By Peter VisscherUniversity of Queensland, Australia
08:20 AM - 08:40 AMPanel discussion By Bruce Walsh, Michael Lynch, Naomi Wray, Ben Hayes, Mark Blows & Peter Visscher
The Genetic Architecture of Drosophila Lifespan
12:00 PM - 12:35 PMThe Genetic Architecture of Drosophila Lifespan By Trudy MackayClemson University, South Carolina, USA
12:35 PM - 01:10 PMEstimation of realized rates of genetic gain for breeding program assessment: Insights from rice research at IRRI By Jessica RutkoskiUniversity of Illinois at Urbana-Champaign, USA
01:10 PM - 01:25 PMThe role of cross-sex genetic covariances in the evolution of sexual dimorphism among species By Jacqueline SztepanaczUniversity of Toronto, Canada
07:00 PM - 07:35 PMCrowdsourcing genetic data. A look from the outside and inside. By Yaniv ErlichMyHeritage, Israel

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07:35 PM - 08:10 PMAdaptation and quantitative trait evolution in an urban context By Anne CharmantierCNRS, Montpelier, France
08:10 PM - 08:25 PMPolyOrigin: Haplotype Reconstruction in Tetraploid Multiparent Populations By Chaozhi ZhengWageningen, The Netherlands
07:00 AM - 07:35 AMImpact of omics on the genetic improvement of Zebu cattle in the tropics By Lucia AlburqueueSão Paulo State University, Brazil
07:35 AM - 08:10 AMTransferability of polygenic risk scores across diverse populations By Eimear KennyIcahn Mt Sinai, USA
08:10 AM - 08:25 AMPredicting the Accuracy of Genomic Predictions By Jack DekkersIowa State University, USA
12:00 PM - 12:15 PMPolygenic Risk Scores in Humans – What are they Good For? By Greg GibsonGeorgia Tech, USA
12:15 PM - 12:30 PMGenome-wide association study identifies tissue-specific regulation of human protein N-glycosylation By Sodbo SharapovNovosibirsk State University, Russia
12:30 PM - 12:45 PMGenomic mate selection for clonal crops: improving the chance of breeding top ranking clones by predicted variance in total merit By Marnin WolfeCornell University, USA
12:45 PM - 01:00 PMA mate allocation program for mass spawning species By Cecile MassaultJames Cook University, Australia
5×5 poster
01:00 PM - 01:25 PM5×5 poster By ----
07:00 PM - 07:15 PMImproved heritability models improve our ability to analyze complex traits. By Doug SpeedAarhus University, Denmark
07:15 PM - 07:30 PMGenomic prediction using a multi-breed reference data of purebred and admixed populations By Emre KaramanAarhus University, Denmark
07:30 PM - 07:45 PMGenomic and temporal analysis of genetic covariation between traits By Gregor GorjancUniversity of Edinburgh, UK
07:45 PM - 08:00 PMFstSeg: an efficient multiple changepoint procedure/algorithm for the detection of local signatures of selection By Tristan Mary-HuardINRA, Paris, France
08:00 PM - 08:15 PMMulti-trait analysis with Bayesian models instructed by functional priors identify informative markers that predict traits across populations and countries By Ruidong XiangAgriculture Victoria, Australia
08:15 PM - 08:25 PMMeet the Editor: Genetics & G3 – Genes|Genomes|Genetics By DJ De KoningEditor for G3 and GENETICS
07:00 AM - 07:35 AMQuantitative genetics of the genotype-phenotype Map By David HouleFlorida State University USA
07:35 AM - 08:10 AMTurbocharging Fruit Tree Breeding By Satish KumarPlant and Food Research, NZ

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08:10 AM - 08:25 AMTracking the tempo and target of natural/artificial selection in a thousand mice and butterflies by haplotype tagging and sequencing By Frank ChanMax Planck Society, Germany
12:00 PM - 12:15 PMGenetic correlation between two populations can be predicted from the FST between the populations and the non-additive genetic variance By Michael GoddardAgriculture Victoria, Australia
12:15 PM - 12:30 PMCross-population fine-mapping of complex traits and diseases in ~675,000 individuals across three global biobanks By Masahiro KanaiBroad Institute of MIT and Harvard, USA
12:30 PM - 12:45 PMPartitioning risk for complex diseases by race and genetic ancestry By Ky'Era ActkinsMeharry Medical College, Tennessee, USA
12:45 PM - 01:00 PMFamily-Based GWAS of Educational Attainment By Alexander YoungUniversity of Southern California, USA
01:00 PM - 01:40 PM8×5 poster
07:00 PM - 07:15 PMHow fast are wild animals currently adapting? By Timothée BonnetAustralian National University, Canberra, Australia
07:15 PM - 07:30 PMEstimating maternal and paternal genetic effects on offspring phenotypes in large scale cohorts when parental genotypes are unavailable By David EvansUniversity of Queensland, Australia
09:30 PM - 09:45 PMGenomic architecture of 184 plasma proteins in 18,884 individuals: the SCALLOP Consortium By Erin Macdonald-DunlopUniversity of Edinburgh, UK
07:45 PM - 08:00 PMGenotype-by-environment interactions among Scots pine vitality and growth traits, in harsh and mild environments in Northern Scandinavia By Ainhoa Calleja-RodriguezSkogforsk (the Forestry Research Institute Of Sweden), Sweden
08:00 PM - 08:15 PMPhenotypic covariance across the entire spectrum of relatedness for 88 billiion pairs of individuals By Kathryn E KemperUniversity of Queensland, Australia
08:15 PM - 08:30 PMSex difference in genetic correlations and its implication on causality By Xia ShenUniversity of Edinburgh, UK
07:00 AM - 07:15 AMPredicting Phenotype: Modeling Approaches Within The GxE Space By Jacob WashburnUSDA Missouri, USA
07:15 AM - 07:30 AMPopulation genetics of transposable elements in the maize Wisconsin diversity panel By Christine O’ConnorUniversity of Minnesota, USA
07:30 AM - 07:45 AMModelling GxE in High Throughput Phenotyping data from crop variety trials By Joanne De FaveriCSIRO Data61, QLD, Australia
07:45 AM - 08:00 AMQTL mapping in autotetraploid multi-parent populations By Rodrigo AmadeuUniversity of Florida, USA
08:00 AM - 08:15 AMImproving genomic prediction of target hybrids in unobserved environments using geospatial assessment of predictive analytics derived from machine learning techniques By Diego JarquinUniversity of Nebraska-Lincoln, USA
08:15 AM - 08:30 AMA statistical framework to incorporate high-throughput proxy phenotypes in genomic predictions for wheat breeding By Lee HickeyUniversity of Queensland, Australia
12:00 PM - 12:15 PMFast Parallelized Sampling of Bayesian Linear Mixed Models for Whole-genome Prediction By Hao ChengUniversity of California Davis, USA
12:15 PM - 12:30 PMPopulation scale single cell eQTL mapping identifies cell type specific control of disease By Joseph PowellSydney, Australia
12:30 PM - 12:45 PMA novel linear mixed model approach for multi-omics data By S. Hong LeeUniversity of South Australia, Australia
12:45 PM - 01:00 PMMetagenomics for selection of environmentally friendly ruminants By Melanie HessAgResearch Otago, NZ
01:00 PM - 01:25 PM6×5 poster
07:00 PM - 07:15 PMCan dominance genetic variance be ignored in evolutionary quantitative genetic analyses of wild populations? By Barbara ClassUniversity of the Sunshine Coast, Australia
07:15 PM - 07:30 PMGenetic constraints persist through metamorphosis: RNA seq reveals major pleiotropy within and between life stages By Julie ColletCEFE, CNRS, Montpelier, France
07:30 PM - 07:45 PMThe interaction of quantitative genetics and changing environment on a wild bird population By Loeske KruukAustralian National University, Canberra, Australia
07:45 PM - 08:00 PMGenome-wide chromatin accessibility and transcriptome profiling during onset of maturation in Atlantic salmon By Amin MohamedGEOMAR Helmholtz Centre for Ocean Research, Germany
08:00 PM - 08:15 PMDoes mutation explain standing genetic variation in complex phenotypes? By Robert DugandUniversity of Queensland, Australia
08:15 PM - 08:30 PMTriangulation of analysis strategies establishes relevant tissues and cell types for complex traits By Zhijian YangSun Yat-sen University, Guangzhou, China
  • Session 13 Nov 9th
  • Session 14 Nov 9th
  • Session 15 Nov 9th
  • Session 16 Nov 10th
  • Session 17 Nov 10th
  • Session 18 Nov 10th
  • Session 19 Nov 11th
  • Session 20 Nov 11th
  • Session 21 Nov 11th
  • Session 22 Nov 12th
  • Session 23 Nov 12th
  • Session 24 Nov 12th
  • Session 25 Nov 13th
07:00 AM - 07:35 AMDoes epistasis matter? By Nick Barton Institute of Science and Technology, Austria
07:35 AM - 07:50 AMPhantom Epistasis in Genomic Selection: On the predictive ability of epistatic models By Matias F. SchraufUniversity of Buenos Aires, Argentina
07:50 AM - 08:05 AMThe impact of physiological non-additivity on variance components for complex traits By Kai Voss-FelsUniversity of Queensland, Australia
08:05 AM - 08:20 AMDifferential complex trait architecture across humans: epistasis identified in non-European populations at multiple genomic scales By Michael TurchinBrown University,USA
08:20 AM - 08:30 AMPanel Discussion By Nick Barton, Matias F. Schrauf, Kai Voss-Fels, Michael Turchin, Andy Clark, Mark Cooper & Trudy Mackay
12:00 PM - 12:35 PMDependencies within and among forensic match probabilities By Bruce WeirUniversity of Washington, USA
12:35 PM - 01:15 PM6×5 Poster submission
01:15 PM - 01:35 PMMeet the Editor By Catherine PotenskiEditor, Nature Genetics
07:00 PM - 07:35 PMQuantitative genetics of environmental variance, uniformity and resilience in livestock animals By Han MulderWageningen University, The Netherlands
07:35 PM - 07:50 PMIncreased developmental density decreases the magnitude of indirect genetic effects exprssed during agonistic interactions By Chang HanKyunghee University, Seoul, Sth Korea
07:50 PM - 08:05 PMDynamics of secondary traits offer new possibilities for modelling genotype by environment interactions in focal traits By Fred van EeuwijkWageningen University, The Netherlands
08:05 PM - 08:20 PMExploiting methylation to measure genome-by-smoking interactions By Carmen AmadorUniversity of Edinburgh, UK
07:00 AM - 07:35 AMFrom pedigree to genomics based management of genetic diversity: how to measure and control genomic inbreeding in genomic selection schemes By Theo MeuwissenNorwegian University of Life Sciences, As, Norway

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07:35 AM - 08:10 AMFrom Statistical Models to Biological Mechanisms of Human Mutation By Shamil SunyaevBrigham and Womens Hospital/ Harvard Medical School, Boston, USA
08:05 AM - 08:25 AMLeveraging mathematical optimization to drive short-term gains while maintaining long-term genetic variability in a plant breeding program By Nicholas SantantonioCornell University, NY, USA
12:00 PM - 12:35 PMUnderstanding the polygenic architecture and regulatory mechanisms of human complex traits By Jian YangWestlake University, Hangzhou, China
12:35 PM - 01:10 PMImplementation of Genomic Selection in the CIMMYT Global wheat program, learnings from the past 10 years By Susanne DreisigackerCIMMYT, Mexico
01:10 PM - 01:25 PMIndirect genetic effects on a broad range of biomedical phenotypes measured in laboratory mice and rats By Amelie BaudEuropean Bioinformatics Institute, Ca, USA
07:00 PM - 07:15 PMExtracellular vesicles with specific surface proteins are associated with waist circumference and visceral fat By Ranran ZhaiSun Yat-sen University, Guangzhou, China
07:15 PM - 07:30 PMDissecting genetic variation in gene expression at the single-cell resolution in Arabidopsis thaliana root tips By Adam ReddiexAustralian National University, Canberra, Australia
07:30 PM - 07:45 PMA genomic meta-analysis of 184 neuroproteins and their implied causality on psychiatric disorders By Linda RepettoUniversity of Edinburgh, UK
07:45 PM - 08:00 PMChromatin and epigenomic variation reveals the gene regulatory landscape of adaptive divergence in sticklebacks By Felicity JonesMax Planck Society, Tuebingen, Germany
08:00 PM - 08:15 PMWhole exome sequences reveal rare and common variants associated with 1102 plasma proteins By Lucija KlaricUniversity of Edinburgh, UK
08:15 PM - 08:30 PMGenomic prediction of complex phenotypes in livestock – potential applications and lessons to be learned from crops and model species By Henner SimianerUniversity of Goettingen, Germany
07:00 AM - 07:15 AMMatching Genetics to Environment Using Genomics: Synthesis of results from USDA-NIFA Food Security Grant on Local Adaptation in Beef Cattle By Jared DeckerUniversity of Missouri, USA
07:15 AM - 07:30 AMLifting the lid of the rumen: genomic solutions for sustainable livestock production By Suzanne RoweAgresearch, Dunedin, NZ
07:30 AM - 07:45 AMScanning the Angus genome for homozygosity deficient haplotypes By Duc LuAngus Genetics Inc., Missouri, USA
07:45 AM - 08:00 AMNon-additive effects in dairy cattle By Edwardo ReynoldsMassey University, NZ
08:00 AM - 08:15 AMEvaluating the accuracy of imputed whole-genome sequence data in admixed dairy cattle By Yu WangMassey University, New Zealand
08:15 AM - 08:30 AMTrait correlation and accuracy weighted selection index emphasis By Luna ZhangAbacusBio Ltd, Dunedin, NZ
12:00 PM - 12:15 PMComplex-Trait Prediction using Sparse Selection Indices By Gustavo de los CamposMichigan State University, USA
12:15 PM - 12:30 PMUsing information across tissues and genes to predict gene expression in Transcriptome-wide Association Studies By Fabio MorganteClemson University, South Carolina, USA
12:30 PM - 12:45 PMA statistical model for genomic predictions of high-dimensional traits By Daniel RuncieUniversity of California Davis, USA
12:45 PM - 01:15 PM6×5 poster
07:00 PM - 07:15 PMPooled genotyping strategies for the rapid construction of genomic reference populations By Dr Pamela AlexandreCSIRO Agriculture and Food, Australia
07:15 PM - 07:30 PMIncreasing the accuracy of genomic prediction for crossbred livestock: examples from dairy cattle By Dr Iona MacleodAgriculture Victoria, Australia
07:30 PM - 07:45 PMGenomic analysis reveals new genes and causal mutations for the environmental variance of litter size in rabbits By Cristina Casto RebolloInstitute for Animal Science and Technology, Valencia, Spain
07:45 PM - 08:00 PMGenetic parameter for variability of milk production in cattle as indicator of environmental sensitivity By Enrico MancinUniversity of Padova, Italy
08:00 PM - 08:15 PMEnvironmental influences on the effects of new mutations By Katrina McGuiganUniversity of Queensland, Australia
08:15 PM - 08:30 PMEstimating mutation rate and characterising de novo mutations in pigs By Christina RochusWageningen University, The Netherlands
07:00 AM - 07:35 AMInherited genetic variation, acquired mutations and clonal selection By Steve McCarrollHarvard University, USA
07:35 AM - 08:10 AMMulti-trait evolution in the presence of social interactions By Jarrod HadfieldUniveristy of Edinburgh, UK
08:10 AM - 08:25 AMSimultaneous quantification of mRNA and protein in single cells reveals trans-acting genetic variation in gene expression By Frank AlbertUniversity of Minnesota, USA
12:00 PM - 12:35 PMFuture application of genomics in the poultry industry By Rachel HawkenCobb - Vantress, Arkansas, USA

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12:35 PM - 01:10 PMHow can biology and breeding contribute to improving food systems and climate change? By Ed BucklerUSDA, NY, USA
01:10 PM - 01:25 PMThe Open Chromatin Regulation of Complex Traits By Nathaniel W. Ellis University of Florida, USA
07:00 PM - 07:35 PMDetecting the functional consequences of human genetic variation using high-throughput differentiation of human induced pluripotent stem cells By Dan GaffneyWellcome Sanger Institute, Cambridge, UK
07:35 PM - 08:10 PMEvidence of horizontal indirect genetic effects in humans By Albert TenesaUniversity of Edinburgh, UK
08:10 PM - 08:25 PMBreeding Crops Resilient to Future Climate Change using Environment Covariant Enriched Genomic Prediction By Hans D. DaetwylerAgriculture Victoria, Australia

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07:00 AM - 07:35 AMThe impact of sex on gene expression and its genetic regulation across human tissues By Barbara StrangerNorthwestern University, Chicago, USA
07:35 AM - 07:50 AMA new interpretation for a 99 year-old equation: the Castle-Wright estimator is also a powerful test of natural selection By Hunter FraserStanford, USA
07:50 AM - 08:25 AMCome join the multiple testing party! By Matthew Stephens University of Chicago, USA

FAQ’s

  • Why have we gone virtual?

    Current global events led the ICQG6 committee to postpone the June 2020 Conference until June 2021, however the evolving COVID-19 situation means that Australian international borders are unlikely to be open before July 2021. In addition, an exciting ICQG6 program of invited and contributed abstracts has already been confirmed, so we feel that the best option is to transition ICQG6 to a virtual Conference that will be delivered from 3 – 13 November 2020 (Australian time zone) which is 2 November to 12 November 2020 in some time-zones.

  • How do poster sessions work for a virtual meeting?

    We will allow two formats for posters, either a single-screen document standard poster, or a 5 minute, up to 5 slides video. From those videos submitted by the October 20 deadline, we will select ~30 to be viewed during the conference sessions. All posters can be viewed from the poster gallery. Questions to poster presenters can be posted in the discussion channel.

  • Will ICQG7 take place in Brisbane, Australia?

    We know many people were excited to come to Australia for ICQG6, and we would love to host you here. Given the COVID situation, it is too early to make any firm commitment. Until there is a vaccine we live in a changed world.

  • When will the ICQG6 virtual Conference be held?

    ICQG6 virtual will be held from 3 – 13 November 2020 (Australian time zone) which is 2 -12 November 2020 in some time-zones.

  • What happens to my current registration for the ICQG6 Conference?

    All attendees with a current ICQG6 registration, will be contacted via email and provided options relating to virtual registration and refunds. Registered delegates will be provided a selection of 3 options available for transitioning their registration to a virtual registration. All components of current registrations that will no longer be delivered including pre-Conference workshop registration, Conference dinner ticket, go event travel cards, Lone Pine tour and accommodation will be refunded in full. Registered delegates who originally paid via credit card, will need to provide the last 4 digits on the card they used to pay, in order for a refund to be processed. Registered delegates who originally paid via bank transfer will be required to provide their banking information for refund. Please note refunds of registration, accommodation and other additional purchases will take up to 8 weeks to process.

  • What happens if I register for the virtual conference and then find I cannot attend ICQG6 virtual in November 2020?

    To limit administration costs, in the event that you are unable to attend virtually in November 2020, your virtual registration can be transferred to another registrant free of charge. Unless there are extenuating circumstances, there will be no refunds of new virtual registrations. The Organising Committee reserves final decision on a case by case basis.

  • What happens to my accepted presentation at the ICQG6 Conference?

    All accepted ICQG6 presentations have been allocated into the new ICQG6 virtual program. Please click here to view the program. Individual presenters will receive an email from the secretariat outlining their new presentation day/date and time. Each presenter will also be provided the necessary information and guidelines for presenting their oral or poster presentation virtually. If you are no longer able to or do not wish to present your accepted presentation virtually, please contact the secretariat immediately at program@icqg6.org to advise.

  • What happens to the accommodation booking I made for ICQG6 2020?

    All accommodation bookings made for ICQG6 2020 will be cancelled on your behalf. All monies paid towards your accommodation booking will be refunded, along with your other refund amounts.

  • I was successful in receiving an Early Career Researcher Scholarship for the face to face conference, does this still stand?

    Yes. Those who successfully received an Early Career Researcher Scholarship for ICQG6 can be assured that this scholarship still stands and will be rolled over to the virtual conference. You will be contacted by the secretariat to make the necessary arrangements regarding your virtual registration and any refunds required. If you were accepted for an ECR Scholarship and are unable to attend virtually in November 2020, please advise the secretariat via email.

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