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Dive into the research topics where Josquin Tibbits is active.

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Featured researches published by Josquin Tibbits.


Nature | 2014

The genome of Eucalyptus grandis

Alexander Andrew Myburg; Dario Grattapaglia; Gerald A. Tuskan; Uffe Hellsten; Richard D. Hayes; Jane Grimwood; Jerry Jenkins; Erika Lindquist; Hope Tice; Diane Bauer; David Goodstein; Inna Dubchak; Alexandre Poliakov; Eshchar Mizrachi; Anand Raj Kumar Kullan; Steven G. Hussey; Desre Pinard; Karen Van der Merwe; Pooja Singh; Ida Van Jaarsveld; Orzenil Bonfim Silva-Junior; Roberto C. Togawa; Marilia R. Pappas; Danielle A. Faria; Carolina Sansaloni; Cesar D. Petroli; Xiaohan Yang; Priya Ranjan; Timothy J. Tschaplinski; Chu-Yu Ye

Eucalypts are the world’s most widely planted hardwood trees. Their outstanding diversity, adaptability and growth have made them a global renewable resource of fibre and energy. We sequenced and assembled >94% of the 640-megabase genome of Eucalyptus grandis. Of 36,376 predicted protein-coding genes, 34% occur in tandem duplications, the largest proportion thus far in plant genomes. Eucalyptus also shows the highest diversity of genes for specialized metabolites such as terpenes that act as chemical defence and provide unique pharmaceutical oils. Genome sequencing of the E. grandis sister species E. globulus and a set of inbred E. grandis tree genomes reveals dynamic genome evolution and hotspots of inbreeding depression. The E. grandis genome is the first reference for the eudicot order Myrtales and is placed here sister to the eurosids. This resource expands our understanding of the unique biology of large woody perennials and provides a powerful tool to accelerate comparative biology, breeding and biotechnology.


Genome Biology | 2015

Transcriptomic analysis of wheat near-isogenic lines identifies PM19-A1 and A2 as candidates for a major dormancy QTL

Jose M. Barrero; Colin Cavanagh; Klara L. Verbyla; Josquin Tibbits; Arunas P. Verbyla; B. Emma Huang; Garry M. Rosewarne; Stuart Stephen; Penghao Wang; Alex Whan; Philippe Rigault; Matthew J. Hayden; Frank Gubler

BackgroundNext-generation sequencing technologies provide new opportunities to identify the genetic components responsible for trait variation. However, in species with large polyploid genomes, such as bread wheat, the ability to rapidly identify genes underlying quantitative trait loci (QTL) remains non-trivial. To overcome this, we introduce a novel pipeline that analyses, by RNA-sequencing, multiple near-isogenic lines segregating for a targeted QTL.ResultsWe use this approach to characterize a major and widely utilized seed dormancy QTL located on chromosome 4AL. It exploits the power and mapping resolution afforded by large multi-parent mapping populations, whilst reducing complexity by using multi-allelic contrasts at the targeted QTL region. Our approach identifies two adjacent candidate genes within the QTL region belonging to the ABA-induced Wheat Plasma Membrane 19 family. One of them, PM19-A1, is highly expressed during grain maturation in dormant genotypes. The second, PM19-A2, shows changes in sequence causing several amino acid alterations between dormant and non-dormant genotypes. We confirm that PM19 genes are positive regulators of seed dormancy.ConclusionsThe efficient identification of these strong candidates demonstrates the utility of our transcriptomic pipeline for rapid QTL to gene mapping. By using this approach we are able to provide a comprehensive genetic analysis of the major source of grain dormancy in wheat. Further analysis across a diverse panel of bread and durum wheats indicates that this important dormancy QTL predates hexaploid wheat. The use of these genes by wheat breeders could assist in the elimination of pre-harvest sprouting in wheat.


Theoretical and Applied Genetics | 2017

Detection and validation of genomic regions associated with resistance to rust diseases in a worldwide hexaploid wheat landrace collection using BayesR and mixed linear model approaches

Raj K. Pasam; Urmil Bansal; Hans D. Daetwyler; Kerrie L. Forrest; Debbie Wong; Joanna Petkowski; Nicholas Willey; Mandeep Randhawa; Mumta Chhetri; H. Miah; Josquin Tibbits; Harbans Bariana; Matthew J. Hayden

Key messageBayesR and MLM association mapping approaches in common wheat landraces were used to identify genomic regions conferring resistance to Yr, Lr, and Sr diseases.AbstractDeployment of rust resistant cultivars is the most economically effective and environmentally friendly strategy to control rust diseases in wheat. However, the highly evolving nature of wheat rust pathogens demands continued identification, characterization, and transfer of new resistance alleles into new varieties to achieve durable rust control. In this study, we undertook genome-wide association studies (GWAS) using a mixed linear model (MLM) and the Bayesian multilocus method (BayesR) to identify QTL contributing to leaf rust (Lr), stem rust (Sr), and stripe rust (Yr) resistance. Our study included 676 pre-Green Revolution common wheat landrace accessions collected in the 1920–1930s by A.E. Watkins. We show that both methods produce similar results, although BayesR had reduced background signals, enabling clearer definition of QTL positions. For the three rust diseases, we found 5 (Lr), 14 (Yr), and 11 (Sr) SNPs significant in both methods above stringent false-discovery rate thresholds. Validation of marker–trait associations with known rust QTL from the literature and additional genotypic and phenotypic characterisation of biparental populations showed that the landraces harbour both previously mapped and potentially new genes for resistance to rust diseases. Our results demonstrate that pre-Green Revolution landraces provide a rich source of genes to increase genetic diversity for rust resistance to facilitate the development of wheat varieties with more durable rust resistance.


Frontiers in Plant Science | 2017

Haplotype Analysis of the Pre-harvest Sprouting Resistance Locus Phs-A1 Reveals a Causal Role of TaMKK3-A in Global Germplasm

Oluwaseyi Shorinola; Barbara Balcárková; Jessica Hyles; Josquin Tibbits; Matthew J. Hayden; Katarina Holušova; Miroslav Valárik; Assaf Distelfeld; Atsushi Torada; Jose M. Barrero; Cristobal Uauy

Pre-harvest sprouting (PHS) is an important cause of quality loss in many cereal crops and is particularly prevalent and damaging in wheat. Resistance to PHS is therefore a valuable target trait in many breeding programs. The Phs-A1 locus on wheat chromosome arm 4AL has been consistently shown to account for a significant proportion of natural variation to PHS in diverse mapping populations. However, the deployment of sprouting resistance is confounded by the fact that different candidate genes, including the tandem duplicated Plasma Membrane 19 (PM19) genes and the mitogen-activated protein kinase kinase 3 (TaMKK3-A) gene, have been proposed to underlie Phs-A1. To further define the Phs-A1 locus, we constructed a physical map across this interval in hexaploid and tetraploid wheat. We established close proximity of the proposed candidate genes which are located within a 1.2 Mb interval. Genetic characterization of diverse germplasm used in previous genetic mapping studies suggests that TaMKK3-A, and not PM19, is the major gene underlying the Phs-A1 effect in European, North American, Australian and Asian germplasm. We identified the non-dormant TaMKK3-A allele at low frequencies within the A-genome diploid progenitor Triticum urartu genepool, and show an increase in the allele frequency in modern varieties. In United Kingdom varieties, the frequency of the dormant TaMKK3-A allele was significantly higher in bread-making quality varieties compared to feed and biscuit-making cultivars. Analysis of exome capture data from 58 diverse hexaploid wheat accessions identified fourteen haplotypes across the extended Phs-A1 locus and four haplotypes for TaMKK3-A. Analysis of these haplotypes in a collection of United Kingdom and Australian cultivars revealed distinct major dormant and non-dormant Phs-A1 haplotypes in each country, which were either rare or absent in the opposing germplasm set. The diagnostic markers and haplotype information reported in the study will help inform the choice of germplasm and breeding strategies for the deployment of Phs-A1 resistance into breeding germplasm.


Theoretical and Applied Genetics | 2017

Accelerating wheat breeding for end-use quality with multi-trait genomic predictions incorporating near infrared and nuclear magnetic resonance-derived phenotypes

Ben J. Hayes; J. Panozzo; C. K. Walker; A. L. Choy; Surya Kant; Debbie Wong; Josquin Tibbits; Hans D. Daetwyler; Simone Rochfort; M. J. Hayden; German Spangenberg

Key messageUsing NIR and NMR predictions of quality traits overcomes a major barrier for the application of genomic selection to accelerate improvement in grain end-use quality traits of wheat.AbstractGrain end-use quality traits are among the most important in wheat breeding. These traits are difficult to breed for, as their assays require flour quantities only obtainable late in the breeding cycle, and are expensive. These traits are therefore an ideal target for genomic selection. However, large reference populations are required for accurate genomic predictions, which are challenging to assemble for these traits for the same reasons they are challenging to breed for. Here, we use predictions of end-use quality derived from near infrared (NIR) or nuclear magnetic resonance (NMR), that require very small amounts of flour, as well as end-use quality measured by industry standard assay in a subset of accessions, in a multi-trait approach for genomic prediction. The NIR and NMR predictions were derived for 19 end-use quality traits in 398 accessions, and were then assayed in 2420 diverse wheat accessions. The accessions were grown out in multiple locations and multiple years, and were genotyped for 51208 SNP. Incorporating NIR and NMR phenotypes in the multi-trait approach increased the accuracy of genomic prediction for most quality traits. The accuracy ranged from 0 to 0.47 before the addition of the NIR/NMR data, while after these data were added, it ranged from 0 to 0.69. Genomic predictions were reasonably robust across locations and years for most traits. Using NIR and NMR predictions of quality traits overcomes a major barrier for the application of genomic selection for grain end-use quality traits in wheat breeding.


Theoretical and Applied Genetics | 2017

Exome sequence genotype imputation in globally diverse hexaploid wheat accessions

Fan Shi; Josquin Tibbits; Raj K. Pasam; Pippa Kay; Debbie Wong; Joanna Petkowski; Kerrie L. Forrest; Ben J. Hayes; Alina Akhunova; John P. Davies; Steven R. Webb; German Spangenberg; Eduard Akhunov; Matthew J. Hayden; Hans D. Daetwyler

Key messageImputing genotypes from the 90K SNP chip to exome sequence in wheat was moderately accurate. We investigated the factors that affect imputation and propose several strategies to improve accuracy.AbstractImputing genetic marker genotypes from low to high density has been proposed as a cost-effective strategy to increase the power of downstream analyses (e.g. genome-wide association studies and genomic prediction) for a given budget. However, imputation is often imperfect and its accuracy depends on several factors. Here, we investigate the effects of reference population selection algorithms, marker density and imputation algorithms (Beagle4 and FImpute) on the accuracy of imputation from low SNP density (9K array) to the Infinium 90K single-nucleotide polymorphism (SNP) array for a collection of 837 hexaploid wheat Watkins landrace accessions. Based on these results, we then used the best performing reference selection and imputation algorithms to investigate imputation from 90K to exome sequence for a collection of 246 globally diverse wheat accessions. Accession-to-nearest-entry and genomic relationship-based methods were the best performing selection algorithms, and FImpute resulted in higher accuracy and was more efficient than Beagle4. The accuracy of imputing exome capture SNPs was comparable to imputing from 9 to 90K at approximately 0.71. This relatively low imputation accuracy is in part due to inconsistency between 90K and exome sequence formats. We also found the accuracy of imputation could be substantially improved to 0.82 when choosing an equivalent number of exome SNP, instead of 90K SNPs on the existing array, as the lower density set. We present a number of recommendations to increase the accuracy of exome imputation.


BMC Genomics | 2017

Medium term water deficit elicits distinct transcriptome responses in Eucalyptus species of contrasting environmental origin

Antanas V. Spokevicius; Josquin Tibbits; Philippe Rigault; Marc-Alexandre Nolin; Caroline Müller; Andrew Merchant

BackgroundClimatic and edaphic conditions over geological timescales have generated enormous diversity of adaptive traits and high speciation within the genus Eucalyptus (L. Hér.). Eucalypt species occur from high rainfall to semi-arid zones and from the tropics to latitudes as high as 43°S. Despite several morphological and metabolomic characterizations, little is known regarding gene expression differences that underpin differences in tolerance to environmental change. Using species of contrasting taxonomy, morphology and physiology (E. globulus and E. cladocalyx), this study combines physiological characterizations with ‘second-generation’ sequencing to identify key genes involved in eucalypt responses to medium-term water limitation.ResultsOne hundred twenty Million high-quality HiSeq reads were created from 14 tissue samples in plants that had been successfully subjected to a water deficit treatment or a well-watered control. Alignment to the E. grandis genome saw 23,623 genes of which 468 exhibited differential expression (FDR < 0.01) in one or both ecotypes in response to the treatment. Further analysis identified 80 genes that demonstrated a significant species-specific response of which 74 were linked to the ‘dry’ species E. cladocalyx where 23 of these genes were uncharacterised. The majority (approximately 80%) of these differentially expressed genes, were expressed in stem tissue. Key genes that differentiated species responses were linked to photoprotection/redox balance, phytohormone/signalling, primary photosynthesis/cellular metabolism and secondary metabolism based on plant metabolic pathway network analysis.ConclusionThese results highlight a more definitive response to water deficit by a ‘dry’ climate eucalypt, particularly in stem tissue, identifying key pathways and associated genes that are responsible for the differences between ‘wet’ and ‘dry’ climate eucalypts. This knowledge provides the opportunity to further investigate and understand the mechanisms and genetic variation linked to this important environmental response that will assist with genomic efforts in managing native populations as well as in tree improvement programs under future climate scenarios.


Genome Biology | 2018

Optical and physical mapping with local finishing enables megabase-scale resolution of agronomically important regions in the wheat genome

Gabriel Keeble-Gagnère; Philippe Rigault; Josquin Tibbits; Raj K. Pasam; Matthew S. Hayden; Kerrie L. Forrest; Zeev Frenkel; Abraham B. Korol; B. Emma Huang; Colin Cavanagh; Jen Taylor; Michael Abrouk; Andrew G. Sharpe; David Konkin; Pierre Sourdille; Benoit Darrier; Frédéric Choulet; Aurélien Bernard; Simone Rochfort; Adam M. Dimech; Nathan S. Watson-Haigh; Ute Baumann; Paul Eckermann; Delphine Fleury; Angéla Juhász; Sébastien Boisvert; Marc-Alexandre Nolin; Jaroslav Doležel; Hana Šimková; Helena Toegelová

BackgroundNumerous scaffold-level sequences for wheat are now being released and, in this context, we report on a strategy for improving the overall assembly to a level comparable to that of the human genome.ResultsUsing chromosome 7A of wheat as a model, sequence-finished megabase-scale sections of this chromosome were established by combining a new independent assembly using a bacterial artificial chromosome (BAC)-based physical map, BAC pool paired-end sequencing, chromosome-arm-specific mate-pair sequencing and Bionano optical mapping with the International Wheat Genome Sequencing Consortium RefSeq v1.0 sequence and its underlying raw data. The combined assembly results in 18 super-scaffolds across the chromosome. The value of finished genome regions is demonstrated for two approximately 2.5 Mb regions associated with yield and the grain quality phenotype of fructan carbohydrate grain levels. In addition, the 50 Mb centromere region analysis incorporates cytological data highlighting the importance of non-sequence data in the assembly of this complex genome region.ConclusionsSufficient genome sequence information is shown to now be available for the wheat community to produce sequence-finished releases of each chromosome of the reference genome. The high-level completion identified that an array of seven fructosyl transferase genes underpins grain quality and that yield attributes are affected by five F-box-only-protein-ubiquitin ligase domain and four root-specific lipid transfer domain genes. The completed sequence also includes the centromere.


bioRxiv | 2017

Association mapping and haplotype analysis of the pre-harvest sprouting resistance locus Phs-A1 reveals a causal role of TaMKK3-A in global germplasm

Oluwaseyi Shorinola; Barbara Balcárková; Jessica Hyles; Josquin Tibbits; Matthew J. Hayden; Katarina Holušova; Miroslav Valárik; Assaf Distelfeld; Atsushi Torada; Jose M. Barrero; Cristobal Uauy

Pre-harvest sprouting (PHS) is an important cause of quality loss in many cereal crops and is particularly prevalent and damaging in wheat. Resistance to PHS is therefore a valuable target trait in many breeding programmes. The Phs-A1 locus on wheat chromosome arm 4AL has been consistently shown to account for a significant proportion of natural variation to PHS in diverse mapping populations. However the deployment of sprouting resistance is confounded by the fact that different candidate genes, including the tandem duplicated Plasma Membrane 19 (PM19) genes and the mitogen-activated protein kinase kinase 3 (TaMKK3-A) gene, have been proposed to underlie Phs-A1. To further define the Phs-A1 locus, we constructed a physical map across this interval in hexaploid and tetraploid wheat. We established close proximity of the proposed candidate genes which are located within a 1.2 Mb interval. An association analysis of diverse germplasm used in previous genetic mapping studies suggests that TaMKK3-A, and not PM19, is the major gene underlying the Phs-A1 effect in European, North American, Australian and Asian germplasm. We identified the non-dormant TaMKK3-A allele at low frequencies within the A-genome diploid progenitor Triticum urartu genepool, and show an increase in the allele frequency in modern varieties. In UK varieties, the frequency of the dormant TaMKK3-A allele was significantly higher in bread-making quality varieties compared to feed and biscuit-making cultivars. Analysis of exome capture data from 58 diverse hexaploid wheat accessions identified fourteen haplotypes across the extended Phs-A1 locus and four haplotypes for TaMKK3-A. Analysis of these haplotypes in a collection of UK and Australian cultivars revealed distinct major dormant and non-dormant Phs-A1 haplotypes in each country, which were either rare or absent in the opposing germplasm set. The diagnostic markers and haplotype information reported in the study will help inform the choice of germplasm and breeding strategies for the deployment of Phs-A1 resistance into breeding germplasm.


Molecular Phylogenetics and Evolution | 2013

Chloroplast genome analysis of Australian eucalypts – Eucalyptus, Corymbia, Angophora, Allosyncarpia and Stockwellia (Myrtaceae)

Michael J. Bayly; Philippe Rigault; Antanas V. Spokevicius; Pauline Y. Ladiges; Peter K. Ades; Charlotte Anderson; Gerd Bossinger; Andrew Merchant; Frank Udovicic; Ian E. Woodrow; Josquin Tibbits

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Jose M. Barrero

Commonwealth Scientific and Industrial Research Organisation

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