|IMG Tutorials, Part 2: Microbial Genome Analysis|
|09.00-09.45||9. Introduction to Annotations, Terms and Definitions – Natalia Ivanova
Annotation of microbial genomes usually starts with finding the genes coding for stable RNAs (rRNA and tRNA) and protein-coding genes (CDSs). The principles underlying gene prediction in microbial genomes, as well as different implementations of these algorithms and most popular gene finding tools will be discussed.Genome analysis and gene function prediction depends on the comparison of sequences to the existing information stored in databases. They can either be simple repositories of nucleotide or protein sequence, or contain curated information related to the function of the genetic elements. Used in combination, bioinformatics databases constitute the most powerful method for gene function prediction. In this presentation, methods commonly used for functional annotation will be discussed.
|09.45-10.30||10. Introduction to Functional annotation and comparative genomics for gene discovery
[Live Demo] – Rekha Seshadri
Microbial genome data analysis in IMG is set in the comparative context of multiple microbial genomes. IMG allows navigating the microbial genome data space along three key dimensions: genomes (organisms), functions (terms and pathways), and genes. In this section, ways in which users can interact with protein families, function assignments, and pathways in IMG will be presented.
|10.45-11.30||Hands On Exercises I – Users|
|11.30-12.00||Exercise I solutions [Live Demo] – Rekha Seshadri|
|12.00–13.00||Lunch & Facility Tour|
|13.00–13.45||Hands On Exercises II – Users|
|13.45-14.15||Exercise II solutions [Live Demo] – Rekha Seshadri|
|14.15-15.00||11. Introduction to Biosynthetic Cluster Analysis in IMG (IMG-ABC) – Natalia Ivanova
Secondary metabolites are small naturally occurring bioactive molecules that are not necessary for the growth of an organism, but improve its survival chances. These molecules are usually produced by biosynthetic proteins that are encoded by genes found in clusters. The newly developed Atlas of Biosynthetic gene Clusters in IMG (IMG-ABC) contains information about predicted and experimentally verified biosynthetic gene clusters and, when available, the secondary metabolites that they produce. Additionally, IMG-ABC provides powerful search and analysis functions to help navigate this large dataset. During this presentation you will be introduced to the structure of the database, the different user interfaces and representative analysis workflows, thus providing you with the tools needed for an exploration of the secondary metabolism world and the search for novel chemical structures.
|15.15-16.15||IMG/ABC Exercises and solutions [Live Demo] –Natalia Ivanova|
|16.15-17.00||12. CASE STUDY: Hungate1000 – A catalog of genomes from the rumen microbiome – Rekha Seshadri
Productivity of ruminant livestock depends on the rumen microbiota, which ferment indigestible plant polysaccharides into nutrients used for growth. We present 410 cultured bacterial and archaeal genomes, and evaluate their role in polysaccharide degradation, short-chain fatty acid production and methanogenesis. Metagenome recrutiment and genome comparisons reveal new insights into rumen-specific adaptations. New tools in IMG to recapitulate some of these analyses will be presented.
|User Presentations, and JGI Technologies|
|09.00-11.30||Working Group Presentations – User Groups|
|11.30-12.00||19. JGI User Programs – Susannah Tringe
JGIʼs future depends on new sequencing technologies and applications developed based on these technologies. With multiple sequencing platforms available, JGIʼs &D team has been aimed to develop sequencing applications based on the strength provided by different platforms. Our areas of development lie in de novo whole genome shotgun sequencing, transcriptome sequencing, and metagenomic sample diversity study. Examples of JGIʼs available sequencing applications in genomic research will be discussed.
|13.30-13.45|| 20. Introduction to Single Cell Genomics – Tanja Woyke
The bulk of finished microbial genomes to date are derived from bacteria and archaea that can be readily grown in culture. However, the vast majority of microorganisms on this planet elude current culturing attempts, severely limiting access to their genomes. While various enrichment methods as well as metagenomic approaches have been successfully applied to aid the genome analysis of such uncultured environmental microbes, these methodologies are not suitable for countless community members of interest. Single-cell genomics is an approach that aims to access the genome from an individual microbial cell. The methodology as well as a range of JGI single cell projects will be discussed.
|13.45-14.30||21. Accelerating functional genomics using mass spectrometry – Trent Northen
Microorganisms exhibit complex metabolism and metabolic interactions with their environment, large parts of which remain unknown. Deficiencies in functional annotations of microbial genomes as well as incomplete knowledge of small molecule repertoires (metabolomes) of microorganisms limit the understanding of their metabolism. This talk will introduce mass spectrometry based metabolomics and approaches to link these to microbial genomics. This will include recent work connecting genes to the utilization of specific metabolites in bacteria by profiling metabolite utilization in libraries of mutant strains. Here, untargeted mass spectrometry-based metabolomics was used to identify metabolites utilized by soil microbes. Targeted high-throughput metabolite profiling of spent media of 8042 individual mutant strains was performed to link utilization to specific genes. Using this approach we identified genes of known function as well as those required for the metabolism of ‘novel’ metabolites.
|14.45-15.15||22.DNA Synthesis program – Yasuo Yoshikuni|
|15.15-16.00||23.Fungal Program, Science and Tools – Steven Ahrendt|