News

Acknowledgement: The authors thanked the University of Queensland Genome Innovation Hub for continuing support.

Dear Colleagues,
Welcome to the second edition of the GIH newsletter for 2021.
In this issue we highlight some of our new developments, project updates and news. We also shine a spotlight on some of our collaborators and one of our partner facilities.
The next edition of this newsletter will be distributed in August 2021.
Professor Grant Montgomery, Director

Acknowledgment: The Authors noted that the work was supported by funding from the Genome Innovation Hub external project grants.

Thanks to AGRF's new "Live & On Demand" webinar series, you can find out more about the AGRF-UQ PacBio Sequel II service by watching a webinar featuring talks by our GIH collaborator, Dr CX Chan, the UQ IMB sequencing Facility Manager, Angelika Christ, as well as representatives from UQ Research Infrastructure, AGRF and PacBio.

Advances in DNA sequencing have reduced the difficulty of sequencing and assembling plant genomes. A range of methods for long read sequencing and assembly have been recently compared and we now extend the earlier study and report a comparison with more recent methods.

The cavin proteins are essential for caveola biogenesis and function. Here, we identify a role for the muscle-specific component, Cavin4, in skeletal muscle T-tubule development by analyzing two vertebrate systems: mouse and zebrafish.

In a worlds first, the Genome Innovation Hub and colleagues completed the de novo assembly of the genome of the Australiian wild Macadamia, Macadamia jansenii. By benchmarking different methods for long read sequencing, this publication is a useful, up-to-date comparison of costs and software options for assembly and polishing.

Acknowledgement: The authors thanked the University of Queensland Genome Innovation Hub for continuing support.

***NOTE THAT APPLICATIONS HAVE CLOSED FOR 2021 EXTERNAL PROJECTS***

Spatially resolved transcriptome profiles of mammalian kidneys illustrate the molecular complexity of functional nephron segments, cell-to-cell interactions and genetic variants

In this work, we developed a powerful experimental and analytical pipeline that allows for the genome-wide discovery and targeted validation of cellular communication. By profiling thousands of genes, spatial transcriptomic and single-cell RNA sequencing data show genes that are possibly involved in interactions.

This project established the availability of CAGE through development of an optimized, cost -efficient in-house protocol, benchmarked against a commercially available ‘gold standard’ kit.

stLearn: integrating spatial location, tissue morphology and gene expression to find cell types, cell-cell interactions and spatial trajectories within undissociated tissues

This webinar will present a comparison of three long read sequencing technologies applied to the de novo assembly of a plant genome, Macadamia jansenii.
GIH Collaborative Project.
Hosted by Australian BioCommons.

Thursday, July 2, 2020, 12:00 PM 1:00 PM

In this webinar, Professor Lachlan Coin will talk about his recent study with the Genome Innovation Hub at The University of Queensland for de novo assembly of the genome of Australia’s vulnerable plant species, Macadamia jansenii. In this study several long read sequencing technologies, including MGI’s unique single-tube Long Fragment Read (stLFR), are compared for the same sample.
GIH Collaborative Project.
Hosted by MGI

A new tool for visualising TraDIS (Transposon Directed Insertion Site Sequencing ) data. Search for your gene of interest via our new web browser developed with Professor Ian Henderson at the Institute of Biomolecular Sciences (IMB), Dr Dom Gorse at the Queensland Facility for Advanced Bioinformatics (QFAB Bioinformatics) in collaboration with the Genome Innovation Hub (GIH) at the University of Queensland.

Acknowledgement: The authors have acknowledged that the research for this publication was supported by GIH funding.

Here we introduce a simple, accurate, and efficient tool, mainly for droplet-based scRNA-seq, called "scSplit", which uses a hidden state model approach to demultiplex individual samples from mixed scRNA-seq data with high accuracy. Our approach does not require genotype information from the individual samples to demultiplex them, which also makes it suitable for applications where genotypes are unavailable or difficult to obtain. scSplit uses existing bioinformatics tools to identify putative variant sites from scRNA-seq data, then models the allelic counts to assign cells to clusters using an expectation-maximisation framework.

stLearn is designed to comprehensively analyse Spatial Transcriptomics (ST) data to investigate complex biological processes within an undissociated tissue.

A new method for demultiplexing pooled scRNA-seq data, which does not require a sample genotype, but uses genetic differences learnt from the data. Developed at The University of Queensland's Genome Innovation Hub (GIH) by Jon Xu with Professor Lachlan Coin (The University of Melbourne, Doherty Institute) and colleagues.