We are recruiting! Two year Postdoc available in plant conservation genomics

We have a two year full time postdoc position available to conduct bioinformatics, laboratory and field research in the area of conservation genomics as part of ARC Linkage Project LP180100721, and assist in the supervision of honours and postgraduate research students as required. This is a collaborative project between the University of New South Wales, Royal Botanic Gardens Sydney and the Australian National University to develop approaches for the conservation of plant species that are threatened by a fungal pathogen (Austropuccinia psidii, the cause of myrtle rust). Techniques involved include but are not limited to field collection of plant material, DNA extraction, plant growth experiments, execution of software for bioinformatic and statistical analyses.

More details can be found on the UNSW jobs site here: https://external-careers.jobs.unsw.edu.au/cw/en/job/499957/postdoctoral-research-associate. Informal enquiries are welcome if you want to know more about the project.

Research snapshot - January 2020

One of the most important, interesting and challenging questions in biology is how new traits evolve at the molecular level. My lab employs sequence analysis techniques to interrogate DNA and protein sequences for the signals left behind by evolution. We are a bioinformatics lab but like to incorporate bench/field data through collaboration wherever possible.

Main Research

Building on a solid foundation of bioinformatics and evolutionary theory, we apply genomics, transcriptomics, proteomics and interactomics and systems analysis to understand complex biological systems. Core research activities can be broadly divided into two main themes:

1. Evolutionary Genomics, with a focus on applying de novo genome assembly and population genomics to problems in ecology and biotechnology.

2. Protein-protein interactions, with a focus on the prediction of short linear interaction motifs and their role in human health and disease, including host-pathogen interactions.

These are explored in more detail, below.

1. Evolutionary Genomics.

The main research focus of the lab is the exploitation of genomic and post-genomic data to understand biological function and adaptation to novel environments. We work closely with the Ramaciotti Centre for Genomics and are involved in numerous de novo whole genome sequencing and assembly projects, using short read (Illumina), long read (PacBio & Nanopore) and linked read (10x Chromium) sequencing. One of the biggest of these is leading the bioinformatics and assembly effort in a consortium to sequence the cane toad genome, and leading the BABS Genome project to sequence two iconic Australian snakes. We are a member of the Oz Mammals Genomics initiative, assisting with the sequencing and assembly of Australia’s unique marsupial fauna. In 2018, we were selected as part of a team to sequence the Waratah genome as part of the pilot phase for the new Genomics of Australian Plants initiative.

We enjoy bringing our bioinformatics to bear on a variety of collaborative research projects. Most notably, we have an ARC Linkage Grant with Microbiogen Pty Ltd to understand how a strain of Saccharomyces cerevisiae has evolved to efficiently use xylose as a sole carbon source: something vital for second generation biofuel production that wild yeast cannot do. We are combining comparative genomics, evolutionary genetics, RNA-Seq transcriptomics, and competition assays to understand how the novel metabolism evolved. Through deep Illumina resequencing of evolving populations, and assembling reliable complete genomes of the founding ancestors, the ultimate goal is to trace how mutations have interacted with existing genetic variation during adaptive evolution. More recently, we have received an ARC Linkage Grant with the Royal Botanic Gardens and Domain Trust, to apply genomics approaches to the challenges of rainforest tree conservation in the face of climate change and invasive pathogens. We are also collaborating with industrial and academic partners to de novo sequence, assemble, annotate and interrogate the genomes of a selection of microbes with interesting metabolic abilities.

2. Short Linear Motifs (SLiMs).

Many protein-protein interactions are mediated by Short Linear Motifs (SLiMs): short stretches of proteins (5-15 amino acids long), of which only a few positions are critical to function. These motifs are vital for biological processes of fundamental importance, acting as ligands for molecular signalling, post-translational modifications and subcellular targeting. SLiMs have extremely compact protein interaction interfaces, generally encoded by less than 4 major affinity-/specificity-determining residues. Their small size enables high functional density and evolutionary plasticity, making them frequent products of convergent “ex nihilo” evolution. It also makes them challenging to identify, both experimentally and computationally.

A major focus of the lab is the computational prediction of SLiMs from protein sequences. This research originated with Rich’s postdoctoral research, during which he developed a sequence analysis methods for the rational design of biologically active short peptides. He subsequently developed SLiMDisc, one of the first algorithms for successfully predicting novel SLiMs from sequence data - and coined the term “SLiM” into the bargain. This subsequently lead to the development of SLiMFinder, the first SLiM prediction algorithm able to estimate the statistical significance of motif predictions. SLiMFinder greatly increased the reliability of predictions. SLiMFinder has since spawned a number of motif discovery tools and webservers and is still arguably the most successful SLiM prediction tool on benchmarking data. Methods are made available through the SLiMSuite bioinformatics package and webservers.

Current research is looking to develop these SLiM prediction tools further and apply them to important biological questions. Of particular interest is the molecular mimicry employed by viruses to interact with host proteins and the role of SLiMs in other diseases, such as cancer. Other work is concerned with the evolutionary dynamics of SLiMs within protein interaction networks.

OTHER RESEARCH PROJECTS

In addition to the main research in the lab, the lab has a number of interdisciplinary collaborative projects applying bioinformatics tools and molecular evolution theory to experimental biology, often using large genomic, transcriptomic and/or proteomic datasets. These projects often involve the development of bespoke bioinformatics pipelines and a number of open source bioinformatics tools have been generated as a result. Please see the Publications and Lab software pages for more detail, or get in touch if something catches your eye and you want to find out more. We frequently have small collaborations and/or undergraduate student research projects. Many of these are “on hold” waiting for the right person, or sometimes data, to come along. If you think that you have what it needs, get in touch!

Research snapshot - July 2019

One of the most important, interesting and challenging questions in biology is how new traits evolve at the molecular level. My lab employs sequence analysis techniques to interrogate protein and DNA sequences for the signals left behind by evolution. We are a bioinformatics lab but like to incorporate bench data through collaboration wherever possible.

Main Research

The core research in the lab is broadly divided into two main themes:

1. Evolutionary Genomics.

Since moving to UNSW, a major focus of the lab has been the exploitation of genomic and post-genomic data to understand biological function and adaptation to novel environments. We work closely with the Ramaciotti Centre for Genomics and are involved in numerous de novo whole genome sequencing and assembly projects, using short read (Illumina), long read (PacBio & Nanopore) and linked read (10x Chromium) sequencing. The biggest of these is leading the bioinformatics and assembly effort in a consortium to sequence the cane toad genome, and leading the BABS Genome project to sequence two iconic Australian snakes. We are a member of the Oz Mammals Genomics initiative, assisting with the sequencing and assembly of Australia’s unique marsupial fauna. In 2018, we were selected as part of a team to sequence the Waratah genome as part of the pilot phase for the new Genomics of Australian Plants initiative.

We enjoy bringing our bioinformatics to bear on a variety of collaborative research projects. Most notably, we have an ARC Linkage Grant with Microbiogen Pty Ltd to understand how a strain of Saccharomyces cerevisiae has evolved to efficiently use xylose as a sole carbon source: something vital for second-generation biofuel production that wild yeast cannot do. We are combining comparative genomics, evolutionary genetics, RNA-Seq transcriptomics, and competition assays to understand how the novel metabolism evolved. Through deep Illumina resequencing of evolving populations, and assembling reliable complete genomes of the founding ancestors, the ultimate goal is to trace how mutations have interacted with existing genetic variation during adaptive evolution. More recently, we have received an ARC Linkage Grant with the Royal Botanic Gardens and Domain Trust, to apply genomics approaches to the challenges of rainforest tree conservation in the face of climate change and invasive pathogens. We are also collaborating with industrial and academic partners to de novo sequence, assemble, annotate and interrogate the genomes of a selection of microbes with interesting metabolic abilities.

2. Short Linear Motifs (SLiMs).

Many protein-protein interactions are mediated by Short Linear Motifs (SLiMs): short stretches of proteins (5-15 amino acids long), of which only a few positions are critical to function. These motifs are vital for biological processes of fundamental importance, acting as ligands for molecular signalling, post-translational modifications and subcellular targeting. SLiMs have extremely compact protein interaction interfaces, generally encoded by less than 4 major affinity-/specificity-determining residues. Their small size enables high functional density and evolutionary plasticity, making them frequent products of convergent “ex nihilo” evolution. It also makes them challenging to identify, both experimentally and computationally.

A major focus of the lab is the computational prediction of SLiMs from protein sequences. This research originated with Rich’s postdoctoral research, during which he developed a sequence analysis methods for the rational design of biologically active short peptides. He subsequently developed SLiMDisc, one of the first algorithms for successfully predicting novel SLiMs from sequence data - and coined the term “SLiM” into the bargain. This subsequently lead to the development of SLiMFinder, the first SLiM prediction algorithm able to estimate the statistical significance of motif predictions. SLiMFinder greatly increased the reliability of predictions. SLiMFinder has since spawned a number of motif discovery tools and webservers and is still arguably the most successful SLiM prediction tool on benchmarking data. Methods are made available through the SLiMSuite bioinformatics package and webservers.

Current research is looking to develop these SLiM prediction tools further and apply them to important biological questions. Of particular interest is the molecular mimicry employed by viruses to interact with host proteins and the role of SLiMs in other diseases, such as cancer. Other work is concerned with the evolutionary dynamics of SLiMs within protein interaction networks.

OTHER RESEARCH PROJECTS

In addition to the main research in the lab, the lab has a number of interdisciplinary collaborative projects applying bioinformatics tools and molecular evolution theory to experimental biology, often using large genomic, transcriptomic and/or proteomic datasets. These projects often involve the development of bespoke bioinformatics pipelines and a number of open source bioinformatics tools have been generated as a result. Please see the Publications and Lab software pages for more detail, or get in touch if something catches your eye and you want to find out more. We frequently have small collaborations and/or undergraduate student research projects. Many of these are “on hold” waiting for the right person, or sometimes data, to come along. If you think that you have what it needs, get in touch!

Term 2 Honours projects available

For any students completing their undegrad studies in UNSW Term 1, or external students finishing before June 2019, the UNSW Term 2 honours student application is now open. Deadline for Term 2 applications is 5pm Friday 12th April 2019. For how to apply please check the Faculty link: http://www.science.unsw.edu.au/honours-apply.

As usual, the EdwardsLab is looking to recruit enthusiastic students in genomics, in two main areas:

1. Comparative genomics and molecular evolution in yeast, using long-read PacBio sequencing. We are particularly keen to get a student to work on aspects of our ARC Linkage grant, investigating the evolution of a novel biochemical pathway in yeast.

2. De novo whole genome sequencing of vertebrates, including two snakes and the cane toad. In addition to general assembly and annotation activities, the lab has a few analytical tools that would benefit from

More details of honours can be found on the BABS website, or please get in touch if you have questions about specific projects. We welcome students interested in any of our Research areas, not just the projects listed. Applications from non-UNSW students are also encouraged.

Term 3 applications

Please also note that T3 honours application open date and deadline below, should you apply for T3 intake:

• Applications open from Friday 17th May 2019

• Deadline for Term 3 applications is 5pm Friday 26th July 2019

What are we sequencing next? The waratah!

Thanks to seed funding from the UNSW, we were able to sequence two rainforest tree species earlier this year in collaboration with the Royal Botanic Gardens and Domain Trust (RBGDT), Sydney. I am pleased to announce that, together with RBGDT and the Blue Mountains Botanic Garden, Mt Tomah, we won a bid to sequence one of the first genomes as part of the new Genomics for Australian Plants Framework Initiative by Bioplatforms Australia: the NSW state flower, the Waratah (Telopea speciosissima).

As announced recently, this is one of three species selected for the initial pilot study. Details will be sorted out in the new year, but we will be looking to use a combination of 10x Genomics linked reads and long-read sequencing (PacBio and/or Nanopore).

Collaborators on the project: M Rossetto¹, M van der Merwe¹, H Sauquet¹, P Lu-Irving¹, J Bragg¹, G Bourke², RJ Edwards³

1. Royal Botanic Gardens and Domain Trust, Sydney
2. Blue Mountains Botanic Garden, Mt Tomah
3. The University of New South Wales, Sydney

Image: Telopea speciosissima, Suellen’s Garden, Falls Ck NSW: Photo, Suellen Harris

Research snapshot - October 2018

One of the most important, interesting and challenging questions in biology is how new traits evolve at the molecular level. My lab employs sequence analysis techniques to interrogate protein and DNA sequences for the signals left behind by evolution. We are a bioinformatics lab but like to incorporate bench data through collaboration wherever possible.

Main Research

The core research in the lab is broadly divided into three main themes:

1. Short Linear Motifs (SLiMs)

Many protein-protein interactions are mediated by Short Linear Motifs (SLiMs): short stretches of proteins (5-15 amino acids long), of which only a few positions are critical to function. These motifs are vital for biological processes of fundamental importance, acting as ligands for molecular signalling, post-translational modifications and subcellular targeting. SLiMs have extremely compact protein interaction interfaces, generally encoded by less than 4 major affinity-/specificity-determining residues. Their small size enables high functional density and evolutionary plasticity, making them frequent products of convergent "ex nihilo" evolution. It also makes them challenging to identify, both experimentally and computationally.

A major focus of the lab is the computational prediction of SLiMs from protein sequences. This research originated with Rich’s postdoctoral research, during which he developed a sequence analysis methods for the rational design of biologically active short peptides. He subsequently developed SLiMDisc, one of the first algorithms for successfully predicting novel SLiMs from sequence data - and coined the term “SLiM” into the bargain. This subsequently lead to the development of SLiMFinder, the first SLiM prediction algorithm able to estimate the statistical significance of motif predictions. SLiMFinder greatly increased the reliability of predictions. SLiMFinder has since spawned a number of motif discovery tools and webservers and is still arguably the most successful SLiM prediction tool on benchmarking data.

Current research is looking to develop these SLiM prediction tools further and apply them to important biological questions. Of particular interest is the molecular mimicry employed by viruses to interact with host proteins and the role of SLiMs in other diseases, such as cancer. Other work is concerned with the evolutionary dynamics of SLiMs within protein interaction networks.

2. The evolution of novel functions.

Previous work in the lab has focused on the evolution of functional specificity following gene duplication. Since moving to UNSW, activities have shifted more towards the use of PacBio long read sequencing and other cutting-edge sequencing technologies, working closely with the Ramaciotti Centre for Genomics. We are collaborating with industrial and academic partners to de novo sequence, assemble, annotate and interrogate the genomes of a selection of microbes with interesting metabolic abilities. Most notably, we have an ARC Linkage Grant with Microbiogen Pty Ltd. to understand how a strain of Saccharomyces cerevisiae has evolved to efficiently use xylose as a sole carbon source: something vital for second generation biofuel production that wild yeast cannot do. We are combining comparative genomics, evolutionary genetics, RNA-Seq transcriptomics, and competition assays to understand how the novel metabolism evolved. Through deep Illumina resequencing of evolving populations, and assembling reliable complete genomes of the founding ancestors, the ultimate goal is to trace how mutations have interacted with existing genetic variation during adaptive evolution.

3. Whole genome sequencing and assembly.

Following our experiences with de novo whole genome assembly in yeast, the lab is getting involved in an increasing number of genome sequencing projects. The biggest of these is leading the bioinformatics and assembly effort in a consortium to sequence the cane toad genome. The lab is also leading the BABS Genome project two iconic Australian snakes for use in teaching and public engagement. We are a member of the Oz Mammals Genomics initiative, assisting with the sequencing and assembly of Australia's unique marsupial fauna. We also have an number of bacterial long-read whole genome sequencing collaborations.

Other Research Projects

In addition to the main research in the lab, the lab has a number of interdisciplinary collaborative projects applying bioinformatics tools and molecular evolution theory to experimental biology, often using large genomic, transcriptomic and/or proteomic datasets. These projects often involve the development of bespoke bioinformatics pipelines and a number of open source bioinformatics tools have been generated as a result. We frequently have small collaborations and/or undergraduate student research projects. Many of these are “on hold” waiting for the right person, or sometimes data, to come along. If you think that you have what it needs, get in touch!

Previous Research

The lab has been involved in a number of interdisciplinary collaborative projects applying bioinformatics tools and molecular evolution theory to experimental biology, often using large genomic, transcriptomic and/or proteomic datasets. These projects often involved the development of bespoke bioinformatics pipelines and a number of open source bioinformatics tools have been generated as a result. Please see the Publications and Lab software pages for more detail, or get in touch if something catches your eye and you want to find out more.

Research Snapshot - June 2017

Research interests in the Edwards lab stem from a fascination with the molecular basis of evolutionary change and how we can harness the genetic sequence patterns left behind to make useful predictions about contemporary biological systems. We are a bioinformatics lab but like to incorporate bench data through collaboration wherever possible.

Main Research

The core research in the lab is broadly divided into three main themes:

1. Short Linear Motifs (SLiMs)

SLiMs are short regions of proteins that mediate interactions with other proteins. A major focus of the lab is the computational prediction of SLiMs from protein sequences. This research originated with Rich’s postdoctoral research, during which he developed a sequence analysis methods for the rational design of biologically active short peptides. He subsequently developed SLiMDisc, one of the first algorithms for successfully predicting novel SLiMs from sequence data - and coined the term “SLiM” into the bargain. This subsequently lead to the development of SLiMFinder, the first SLiM prediction algorithm able to estimate the statistical significance of motif predictions. SLiMFinder greatly increased the reliability of predictions. SLiMFinder has since spawned a number of motif discovery tools and webservers and is still arguably the most successful SLiM prediction tool on benchmarking data.

Current research is looking to develop these SLiM prediction tools further and apply them to important biological questions. Of particular interest is the molecular mimicry employed by viruses to interact with host proteins and the role of SLiMs in other diseases, such as cancer. Other work is concerned with the evolutionary dynamics of SLiMs within protein interaction networks.

2. The evolution of novel functions.

Previous work in the lab has focused on the evolution of functional specificity following gene duplication. Since moving to UNSW, activities have shifted more towards the use of PacBio long read sequencing and other cutting-edge sequencing technologies, working closely with the Ramaciotti Centre for Genomics. We are collaborating with industrial and academic partners to de novo sequence, assemble, annotate and interrogate the genomes of a selection of microbes with interesting metabolic abilities. Most notably, we have an ARC Linkage Grant with Microbiogen Pty Ltd. to understand how a strain of Saccharomyces cerevisiae has evolved to efficiently use xylose as a sole carbon source: something vital for second generation biofuel production that wild yeast cannot do. This project combines detailed molecular characterisation of highly adapted yeast strains with “molecular palaeontology” to trace the evolutionary process and identify functionally significant loci under selection.

3. Whole genome sequencing and assembly.

Following our experiences with de novo whole genome assembly in yeast, the lab is getting involved in an increasing number of genome sequencing projects. The biggest of these is leading the bioinformatics and assembly effort in a consortium to sequence the cane toad genome. The lab is also leading the BABS Genome project to sequence iconic Australian species for use in teaching and public engagement.

Previous Research

The lab has been involved in a number of interdisciplinary collaborative projects applying bioinformatics tools and molecular evolution theory to experimental biology, often using large genomic, transcriptomic and/or proteomic datasets. These projects often involved the development of bespoke bioinformatics pipelines and a number of open source bioinformatics tools have been generated as a result. Please see the Publications and Lab software pages for more detail, or get in touch if something catches your eye and you want to find out more.

The cane toad genome project

What are we doing? The Edwards Lab is part of an Australian, Portuguese and Brazilian consortium led by Peter White to sequence and assemble the genome of the cane toad (Rhinella marina). We are leading the bioinformatics component of the assembly effort.

How are we doing it? We are using a combination of Illumina (HiSeq X and NovaSeq) short read sequencing, PacBio (RS II) long read and sequence and 10x Genomics Chromium linked reads.

Details to follow. Please get in touch if you are interested in the project.

Opportunities

Honours and postgraduate* projects are available to work on the assembly and annotation. (*PhD students should have their own scholarship.)

Consortium members

Miguel Carneiro (CIBIO-InBIO), Richard Edwards (UNSW), Nuno Ferrand (CIBIO-InBIO), Eddie Holmes (U Sydney), Craig Moritz (ANU), Lee Ann Rollins (Deakin), Fernando Sequeira (CIBIO-InBIO), Rick Shine (U Sydney), Marcelo Vallinoto de Souza (Federal University of Pará & CIBIO-InBIO), Peter White (UNSW), Marc Wilkins (UNSW).

Research snapshot: June 2016

Research interests in the Edwards lab stem from a fascination with the molecular basis of evolutionary change and how we can harness the genetic sequence patterns left behind to make useful predictions about contemporary biological systems.

The core research in the lab is the study of Short Linear Motifs (SLiMs), which are short regions of proteins that mediate interactions with other proteins. This research originated with Rich’s postdoctoral research, during which he developed a bioinformatics (sequence analysis) method for rational design of biologically active short peptides. He subsequently developed SLiMDisc, one of the first algorithms for successfully predicting novel SLiMs from sequence data - and coined the term “SLiM” into the bargain - before developing the first SLiM prediction algorithm able to estimate the statistical significance of motif predictions (SLiMFinder), which greatly increased the reliability of predictions. SLiMFinder has since spawned a number of motif discovery tools and webservers and is still arguably the most successful SLiM prediction tool on benchmarking data.

Current research is looking to develop these SLiM prediction tools further and apply them to important biological questions. Of particular interest is the molecular mimicry employed by viruses to interact with host proteins and the role of SLiMs in other diseases, such as cancer. Other work is concerned with the evolutionary dynamics of SLiMs within protein interaction networks.

A new and exciting area of research in the lab is functional genomics with PacBio long-read sequencing. We are collaborating with industrial and academic partners to de novo sequence, assemble, annotate and interrogate the genomes of a selection of microbes with interesting metabolic abilities.

Finally, the lab has a number of interdisciplinary collaborative projects applying bioinformatics tools and molecular evolution theory to experimental biology, often using large genomic, transcriptomic and/or proteomic datasets. These projects often involve the development of bespoke bioinformatics pipelines and a number of open source bioinformatics tools have been generated as a result.

Research snapshot: June 2015

Research interests in the Edwards lab stem from a fascination with molecular basis of evolutionary change and how we can harness the genetic sequence patterns left behind to make useful predictions about contemporary biological systems.

The core research in the lab is the study of Short Linear Motifs (SLiMs), which are short regions of proteins that mediate interactions with other proteins. This research originated with Rich’s postdoctoral research, during which he developed a bioinformatics (sequence analysis) method for rational design of biologically active short peptides. He subsequently developed SLiMDisc, one of the first algorithms for successfully predicting novel SLiMs from sequence data - and coined the term “SLiM” into the bargain - before developing the first SLiM prediction algorithm able to estimate the statistical significance of motif predictions (SLiMFinder), which greatly increased the reliability of predictions. SLiMFinder has since spawned a number of motif discovery tools and webservers and is still arguably the most successful SLiM prediction tool on benchmarking data.

Current research is looking to develop these SLiM prediction tools further and apply them to important biological questions. Of particular interest is the molecular mimicry employed by viruses to interact with host proteins and the role of SLiMs in other diseases, such as cancer. Other work is concerned with the evolutionary dynamics of SLiMs within protein interaction networks.

Another area of research concerns the post-transcriptional regulation of protein expression. In collaboration with Dr Mark Coldwell (University of Southampton), we are asking the question: how does the ribosome choose where to start translating a protein? By combining bioinformatics screens with laboratory reporter assays, we are identifying proteins that are translated from non-canonical and/or multiple initiation codons. Possible roles of N-terminal variability in protein interactions and subcellular localisation are now under investigation.

Finally, the lab has a number of interdisciplinary collaborative projects applying bioinformatics tools and molecular evolution theory to experimental biology, often using large genomic, transcriptomic and/or proteomic datasets. These projects often involve the development of bespoke bioinformatics pipelines and a number of open source bioinformatics tools have been generated as a result.