Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Tim Sutton is active.

Publication


Featured researches published by Tim Sutton.


Science | 2007

Boron-Toxicity Tolerance in Barley Arising from Efflux Transporter Amplification

Tim Sutton; Ute Baumann; Julie Hayes; Nicholas C. Collins; Bu-Jun Shi; Thorsten Schnurbusch; Alison Hay; Gwenda M Mayo; Margaret Pallotta; Mark Tester; Peter Langridge

Both limiting and toxic soil concentrations of the essential micronutrient boron represent major limitations to crop production worldwide. We identified Bot1, a BOR1 ortholog, as the gene responsible for the superior boron-toxicity tolerance of the Algerian barley landrace Sahara 3771 (Sahara). Bot1 was located at the tolerance locus by high-resolution mapping. Compared to intolerant genotypes, Sahara contains about four times as many Bot1 gene copies, produces substantially more Bot1 transcript, and encodes a Bot1 protein with a higher capacity to provide tolerance in yeast. Bot1 transcript levels identified in barley tissues are consistent with a role in limiting the net entry of boron into the root and in the disposal of boron from leaves via hydathode guttation.


Plant Physiology | 2010

Boron Toxicity Tolerance in Barley through Reduced Expression of the Multifunctional Aquaporin HvNIP2;1

Thorsten Schnurbusch; Julie Hayes; Maria Hrmova; Ute Baumann; Sunita A. Ramesh; Stephen D. Tyerman; Peter Langridge; Tim Sutton

Boron (B) toxicity is a significant limitation to cereal crop production in a number of regions worldwide. Here we describe the cloning of a gene from barley (Hordeum vulgare), underlying the chromosome 6H B toxicity tolerance quantitative trait locus. It is the second B toxicity tolerance gene identified in barley. Previously, we identified the gene Bot1 that functions as an efflux transporter in B toxicity-tolerant barley to move B out of the plant. The gene identified in this work encodes HvNIP2;1, an aquaporin from the nodulin-26-like intrinsic protein (NIP) subfamily that was recently described as a silicon influx transporter in barley and rice (Oryza sativa). Here we show that a rice mutant for this gene also shows reduced B accumulation in leaf blades compared to wild type and that the mutant protein alters growth of yeast (Saccharomyces cerevisiae) under high B. HvNIP2;1 facilitates significant transport of B when expressed in Xenopus oocytes compared to controls and to another NIP (NOD26), and also in yeast plasma membranes that appear to have relatively high B permeability. We propose that tolerance to high soil B is mediated by reduced expression of HvNIP2;1 to limit B uptake, as well as by increased expression of Bot1 to remove B from roots and sensitive tissues. Together with Bot1, the multifunctional aquaporin HvNIP2;1 is an important determinant of B toxicity tolerance in barley.


BMC Genomics | 2006

Microarray expression analysis of meiosis and microsporogenesis in hexaploid bread wheat.

Wayne Crismani; Ute Baumann; Tim Sutton; Neil J. Shirley; Tracie Webster; German Spangenberg; Peter Langridge; Jason A. Able

BackgroundOur understanding of the mechanisms that govern the cellular process of meiosis is limited in higher plants with polyploid genomes. Bread wheat is an allohexaploid that behaves as a diploid during meiosis. Chromosome pairing is restricted to homologous chromosomes despite the presence of homoeologues in the nucleus. The importance of wheat as a crop and the extensive use of wild wheat relatives in breeding programs has prompted many years of cytogenetic and genetic research to develop an understanding of the control of chromosome pairing and recombination. The rapid advance of biochemical and molecular information on meiosis in model organisms such as yeast provides new opportunities to investigate the molecular basis of chromosome pairing control in wheat. However, building the link between the model and wheat requires points of data contact.ResultsWe report here a large-scale transcriptomics study using the Affymetrix wheat GeneChip® aimed at providing this link between wheat and model systems and at identifying early meiotic genes. Analysis of the microarray data identified 1,350 transcripts temporally-regulated during the early stages of meiosis. Expression profiles with annotated transcript functions including chromatin condensation, synaptonemal complex formation, recombination and fertility were identified. From the 1,350 transcripts, 30 displayed at least an eight-fold expression change between and including pre-meiosis and telophase II, with more than 50% of these having no similarities to known sequences in NCBI and TIGR databases.ConclusionThis resource is now available to support research into the molecular basis of pairing and recombination control in the complex polyploid, wheat.


Scientific Reports | 2015

Prioritization of candidate genes in “ QTL-hotspot ” region for drought tolerance in chickpea ( Cicer arietinum L.)

Sandip M. Kale; Deepa Jaganathan; Pradeep Ruperao; Charles Chen; Ramu Punna; Himabindu Kudapa; Mahendar Thudi; Manish Roorkiwal; Mohan A. V. S. K. Katta; Dadakhalandar Doddamani; Vanika Garg; P. B. Kavi Kishor; Pooran M. Gaur; Henry T. Nguyen; Jacqueline Batley; David Edwards; Tim Sutton; Rajeev K. Varshney

A combination of two approaches, namely QTL analysis and gene enrichment analysis were used to identify candidate genes in the “QTL-hotspot” region for drought tolerance present on the Ca4 pseudomolecule in chickpea. In the first approach, a high-density bin map was developed using 53,223 single nucleotide polymorphisms (SNPs) identified in the recombinant inbred line (RIL) population of ICC 4958 (drought tolerant) and ICC 1882 (drought sensitive) cross. QTL analysis using recombination bins as markers along with the phenotyping data for 17 drought tolerance related traits obtained over 1–5 seasons and 1–5 locations split the “QTL-hotspot” region into two subregions namely “QTL-hotspot_a” (15 genes) and “QTL-hotspot_b” (11 genes). In the second approach, gene enrichment analysis using significant marker trait associations based on SNPs from the Ca4 pseudomolecule with the above mentioned phenotyping data, and the candidate genes from the refined “QTL-hotspot” region showed enrichment for 23 genes. Twelve genes were found common in both approaches. Functional validation using quantitative real-time PCR (qRT-PCR) indicated four promising candidate genes having functional implications on the effect of “QTL-hotspot” for drought tolerance in chickpea.


Nature | 2014

Molecular basis of adaptation to high soil boron in wheat landraces and elite cultivars

Margaret Pallotta; Thorsten Schnurbusch; Julie Hayes; Alison Hay; Ute Baumann; J. G. Paull; Peter Langridge; Tim Sutton

Environmental constraints severely restrict crop yields in most production environments, and expanding the use of variation will underpin future progress in breeding. In semi-arid environments boron toxicity constrains productivity, and genetic improvement is the only effective strategy for addressing the problem. Wheat breeders have sought and used available genetic diversity from landraces to maintain yield in these environments; however, the identity of the genes at the major tolerance loci was unknown. Here we describe the identification of near-identical, root-specific boron transporter genes underlying the two major-effect quantitative trait loci for boron tolerance in wheat, Bo1 and Bo4 (ref. 2). We show that tolerance to a high concentration of boron is associated with multiple genomic changes including tetraploid introgression, dispersed gene duplication, and variation in gene structure and transcript level. An allelic series was identified from a panel of bread and durum wheat cultivars and landraces originating from diverse agronomic zones. Our results demonstrate that, during selection, breeders have matched functionally different boron tolerance alleles to specific environments. The characterization of boron tolerance in wheat illustrates the power of the new wheat genomic resources to define key adaptive processes that have underpinned crop improvement.


Plant Biotechnology Journal | 2016

QTL-seq for rapid identification of candidate genes for 100-seed weight and root/total plant dry weight ratio under rainfed conditions in chickpea

Vikas K. Singh; Aamir W. Khan; Deepa Jaganathan; Mahendar Thudi; Manish Roorkiwal; Hiroki Takagi; Vanika Garg; Vinay Kumar; Annapurna Chitikineni; Pooran M. Gaur; Tim Sutton; Ryohei Terauchi; Rajeev K. Varshney

Summary Terminal drought is a major constraint to chickpea productivity. Two component traits responsible for reduction in yield under drought stress include reduction in seeds size and root length/root density. QTL‐seq approach, therefore, was used to identify candidate genomic regions for 100‐seed weight (100SDW) and total dry root weight to total plant dry weight ratio (RTR) under rainfed conditions. Genomewide SNP profiling of extreme phenotypic bulks from the ICC 4958 × ICC 1882 population identified two significant genomic regions, one on CaLG01 (1.08 Mb) and another on CaLG04 (2.7 Mb) linkage groups for 100SDW. Similarly, one significant genomic region on CaLG04 (1.10 Mb) was identified for RTR. Comprehensive analysis revealed four and five putative candidate genes associated with 100SDW and RTR, respectively. Subsequently, two genes (Ca_04364 and Ca_04607) for 100SDW and one gene (Ca_04586) for RTR were validated using CAPS/dCAPS markers. Identified candidate genomic regions and genes may be useful for molecular breeding for chickpea improvement.


Theoretical and Applied Genetics | 2015

High-resolution skim genotyping by sequencing reveals the distribution of crossovers and gene conversions in Cicer arietinum and Brassica napus

Philipp E. Bayer; Pradeep Ruperao; Annaliese S. Mason; Jiri Stiller; Chon-Kit Kenneth Chan; Satomi Hayashi; Yan Long; Jinling Meng; Tim Sutton; Paul Visendi; Rajeev K. Varshney; Jacqueline Batley; David Edwards

Key messageWe characterise the distribution of crossover and non-crossover recombination inBrassica napusandCicer arietinumusing a low-coverage genotyping by sequencing pipeline SkimGBS.AbstractThe growth of next-generation DNA sequencing technologies has led to a rapid increase in sequence-based genotyping for applications including diversity assessment, genome structure validation and gene–trait association. We have established a skim-based genotyping by sequencing method for crop plants and applied this approach to genotype-segregating populations of Brassica napus and Cicer arietinum. Comparison of progeny genotypes with those of the parental individuals allowed the identification of crossover and non-crossover (gene conversion) events. Our results identify the positions of recombination events with high resolution, permitting the mapping and frequency assessment of recombination in segregating populations.


Frontiers in Plant Science | 2016

Genome-Enabled Prediction Models for Yield Related Traits in Chickpea

Manish Roorkiwal; Abhishek Rathore; Roma Rani Das; Muneendra K. Singh; Ankit Jain; Samineni Srinivasan; Pooran M. Gaur; Bharadwaj Chellapilla; Shailesh Tripathi; Yongle Li; John Hickey; Aaron J. Lorenz; Tim Sutton; José Crossa; Jean-Luc Jannink; Rajeev K. Varshney

Genomic selection (GS) unlike marker-assisted backcrossing (MABC) predicts breeding values of lines using genome-wide marker profiling and allows selection of lines prior to field-phenotyping, thereby shortening the breeding cycle. A collection of 320 elite breeding lines was selected and phenotyped extensively for yield and yield related traits at two different locations (Delhi and Patancheru, India) during the crop seasons 2011–12 and 2012–13 under rainfed and irrigated conditions. In parallel, these lines were also genotyped using DArTseq platform to generate genotyping data for 3000 polymorphic markers. Phenotyping and genotyping data were used with six statistical GS models to estimate the prediction accuracies. GS models were tested for four yield related traits viz. seed yield, 100 seed weight, days to 50% flowering and days to maturity. Prediction accuracy for the models tested varied from 0.138 (seed yield) to 0.912 (100 seed weight), whereas performance of models did not show any significant difference for estimating prediction accuracy within traits. Kinship matrix calculated using genotyping data reaffirmed existence of two different groups within selected lines. There was not much effect of population structure on prediction accuracy. In brief, present study establishes the necessary resources for deployment of GS in chickpea breeding.


Journal of Experimental Botany | 2016

Phenotypic plasticity and its genetic regulation for yield, nitrogen fixation and δ13C in chickpea crops under varying water regimes

Victor O. Sadras; Lachlan Lake; Yongle Li; Elizabeth A. Farquharson; Tim Sutton

We measured yield components, nitrogen fixation, soil nitrogen uptake and carbon isotope composition (δ(13)C) in a collection of chickpea genotypes grown in environments where water availability was the main source of yield variation. We aimed to quantify the phenotypic plasticity of these traits using variance ratios, and to explore their genetic basis using FST genome scan. Fifty-five genes in three genomic regions were found to be under selection for plasticity of yield; 54 genes in four genomic regions for the plasticity of seeds per m(2); 48 genes in four genomic regions for the plasticity of δ(13)C; 54 genes in two genomic regions for plasticity of flowering time; 48 genes in five genomic regions for plasticity of nitrogen fixation and 49 genes in three genomic regions for plasticity of nitrogen uptake from soil. Plasticity of yield was related to plasticity of nitrogen uptake from soil, and unrelated to plasticity of nitrogen fixation, highlighting the need for closer attention to nitrogen uptake in legumes. Whereas the theoretical link between δ(13)C and transpiration efficiency is strong, the actual link with yield is erratic due to trade-offs and scaling issues. Genes associated with plasticity of δ(13)C were identified that may help to untangle the δ(13)C-yield relationship. Combining a plasticity perspective to deal with complex G×E interactions with FST genome scan may help understand and improve both crop adaptation to stress and yield potential.


Functional Plant Biology | 2013

Germanium as a tool to dissect boron toxicity effects in barley and wheat

Julie Hayes; Margaret Pallotta; Ute Baumann; Bettina Berger; Peter Langridge; Tim Sutton

Tolerance to boron (B) toxicity in barley (Hordeum vulgare L.) is partially attributable to HvNIP2;1, an aquaporin with permeability to B, as well as to silicon, arsenic and germanium (Ge). In this study, we mapped leaf symptoms of Ge toxicity in a doubled-haploid barley population (Clipper×Sahara 3771). Two quantitative trait loci (QTL) associated with Ge toxicity symptoms were identified, located on Chromosomes 6H and 2H. These QTL co-located with two of four B toxicity tolerance loci previously mapped in the same population. The B toxicity tolerance gene underlying the 6H locus encodes HvNIP2;1, whereas the gene(s) and mechanisms underlying the 2H locus are as yet unknown. We provide examples of the application of Ge in studying specific aspects of B toxicity tolerance in plants, including screening of wheat (Triticum aestivum L.) and barley populations for altered function of HvNIP2;1 and related proteins. In particular, Ge may facilitate elucidation of the mechanism and gene(s) underlying the barley Chromosome 2H B tolerance locus.

Collaboration


Dive into the Tim Sutton's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar

Julie Hayes

Australian Centre for Plant Functional Genomics

View shared research outputs
Top Co-Authors

Avatar

Ute Baumann

Australian Centre for Plant Functional Genomics

View shared research outputs
Top Co-Authors

Avatar

Rajeev K. Varshney

International Crops Research Institute for the Semi-Arid Tropics

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Margaret Pallotta

Australian Centre for Plant Functional Genomics

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Yongle Li

University of Adelaide

View shared research outputs
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge