A little bit about PhyloSift: phylogenetic analysis of genomes and metagenomes

New paper from people in the Eisen lab: PhyloSift: phylogenetic analysis of genomes and metagenomes [PeerJ].

Basically, the concept behind Phylosift is to provide for high quality, automated, high throughput phylogeny-driven analysis of metagenomic sequence data.  The software was developed openly on github and has been available in some form for more than a year.  Aaron, Holly, Erick and I have discussed it extensively in various talks around the world and thus we assume some are already familiar with it.

This project was coordinated by Aaron Darling, who was a Project Scientist in my lab and is now a Professor at the University of Technology Sydney.  Also involved were Holly Bik (post doc in the lab), Guillaume Jospin (Bioinformatics Engineer in the lab), Eric Lowe (was a UC Davis undergrad working in the lab) and Erick Matsen (from the FHCRC).

Abstract:

Like all organisms on the planet, environmental microbes are subject to the forces of molecular evolution. Metagenomic sequencing provides a means to access the DNA sequence of uncultured microbes. By combining DNA sequencing of microbial communities with evolutionary modeling and phylogenetic analysis we might obtain new insights into microbiology and also provide a basis for practical tools such as forensic pathogen detection.

In this work we present an approach to leverage phylogenetic analysis of metagenomic sequence data to conduct several types of analysis. First, we present a method to conduct phylogeny-driven Bayesian hypothesis tests for the presence of an organism in a sample. Second, we present a means to compare community structure across a collection of many samples and develop direct associations between the abundance of certain organisms and sample metadata. Third, we apply new tools to analyze the phylogenetic diversity of microbial communities and again demonstrate how this can be associated to sample metadata.

Nice timing: Our paper on the Darwin's Finch genome is out today on Darwin's birthday

Birthday party for Darwin in 2009

Well, I assume this was on purpose from the folks at Biomed Central but not sure.  Our paper on the genome of one of Darwin's Finches is out today in BMC Genomics: BMC Genomics | Abstract | Insights into the evolution of Darwin's finches from comparative analysis of the Geospiza magnirostris genome sequence.

Abstract of the paper:

Background
A classical example of repeated speciation coupled with ecological diversification is the evolution of 14 closely related species of Darwin’s (Galápagos) finches (Thraupidae, Passeriformes). Their adaptive radiation in the Galápagos archipelago took place in the last 2–3 million years and some of the molecular mechanisms that led to their diversification are now being elucidated. Here we report evolutionary analyses of genome of the large ground finch, Geospiza magnirostris.
Results
13,291 protein-coding genes were predicted from a 991.0 Mb G. magnirostris genome assembly. We then defined gene orthology relationships and constructed whole genome alignments between the G. magnirostris and other vertebrate genomes. We estimate that 15% of genomic sequence is functionally constrained between G. magnirostris and zebra finch. Genic evolutionary rate comparisons indicate that similar selective pressures acted along the G. magnirostris and zebra finch lineages suggesting that historical effective population size values have been similar in both lineages. 21 otherwise highly conserved genes were identified that each show evidence for positive selection on amino acid changes in the Darwin's finch lineage. Two of these genes (Igf2r and Pou1f1) have been implicated in beak morphology changes in Darwin’s finches. Five of 47 genes showing evidence of positive selection in early passerine evolution have cilia related functions, and may be examples of adaptively evolving reproductive proteins.
Conclusions
These results provide insights into past evolutionary processes that have shaped G. magnirostris genes and its genome, and provide the necessary foundation upon which to build population genomics resources that will shed light on more contemporaneous adaptive and non-adaptive processes that have contributed to the evolution of the Darwin’s finches.

Figure 1

There is a long long long story behind this paper.  Too long for me to write up right now.  I wrote up some of the story for a Figshare posting of the genome data last year.

“Darwin’s Finches” are a model system for the study of various aspects of evolution and development.  In 2008 we commenced on a project to sequence the genomes of some of these species – inspired by the (then) upcoming celebration of the 200th anniversary of the birth of Charles Darwin (which was in February 2009).  The project started with a brief discussion at the AGBT meeting in 2008 and then via an email conversation between Jonathan Eisen and Jason Affourtit about the possibility of a collaboration involving the 454 company (which was looking for projects to highlight the power of it’s then relatively new 454 sequencing machines).  After further discussions between Jonathan Eisen, his brother Michael Eisen (who separately had become interested in Darwin’s finches) and people from 454 it was decided that this was a potentially good project for a scientific and marketing collaboration.  

In these conversations it was determined that the most likely limiting factor would be access to DNA from the finches.  This was largely an issue due to the fact that the Galapagos Islands (where the finches reside) are a National Park in Ecuador and also a World Heritage site.  Collection of samples there for any type of research is highly regulated.  Thus, Jonathan Eisen made contact with Peter and Rosemary Grant – the most prominent researchers working on the finches – and who Eisen had discussed sequencing the finch genomes in the early 2000s.  In that previous conversation it was determined that the sequencing would be too expensive to carry out without a major fundraising effort.  However, with the advent of “next generation” sequencing methods such as 454 the total costs of such a project would be much lower.   

In the conversations with the Grants, the Grants offered to ask around to see if anyone had sufficient amounts of DNA (or access to samples), which would be needed for genome library construction.  Subsequently they identified Arkhat Abzhanov from Harvard as someone who likely had samples as well as permission to do DNA-based work on them, from many of the finch species. Abzhanov offered to provide samples from three key species (large ground finch Geospiza magnirostris, large cactus finch G. conirostris and sharp-billed finch G. difficilis) and DNA was sent to Roche-454 for sequencing in July of 2008.  In August, the first “test” sequence data was provided from Geospiza magnirostris.  A plan was then made to generate additional data and Roche offered to do the sequencing at their center at a steep discount.  Funds were raised by Jonathan Eisen, Greg Wray, Monica Riley, and others to pay for the sequencing and over the next year or so, three sequencing bursts were conducted at Roche-454. "

That is a decent summary of the background.  The details on the science are in the paper.  What the background does not say is that the project languished for years as we did not have funds to support the actual analysis of the genomes and it was kind of out of my normal area of expertise.  Along the way, I did a poor job of communicating with some of the initial parties in the project (e.g., I did a really bad job of communicating with Greg Wray - who had provide some of the funds - and I will forever be trying to make things up to him).  Anyway, thankfully Arhat eventually pulled together a group of people led by Chris Ponting to help analyze the genome and Chris led the way to the paper that is out today.  Only four years after our original goal.

I have been a birder and an evolutionary biologist for many many many years. Thus this is kind of a cool project for me.  When I was in the Galapagos in 2002 I dreamed of doing a project like this - and even started doodling Darwin's finches all over the place - including on some of the styrofoam cups we sent down to the bottom of the ocean on the outside of the Alvin sub as part of a deep sea research cruise I went on.  See below:

Add caption

Some related posts:

From 2002

From 2002

Me, in the Galapagos in 2002

Me in the Galapagos in 2002

Me, today, w/ Darwin's finch art

• Top five metaphors Darwin considered and rejected for "The Tree of Life
• Art-Science Fusion and Darwin's Face at Davis
• 10 simple ways to honor Charlie D (aka Darwin)
• My favorite evolution stuff 2. Charles Darwin Tobacco Card
• Darwin Celebration in Davis
• Open Access Darwin?
• Evolution pumpkins - from Darwin to Woese
• Nice Darwin Art at #UCDavis Evolution/Ecology Dept.
• My favorite evolution stuff 1. 1900 Darwin Post Card

New #openaccess paper in G3 from my lab w/ many others on 'Programmed DNA elimination in Tetrahymena' #CiliatesRule

A new paper in which the lab was involved has been published recently (just found it though it is not in Pubmed yet): Genome-Scale Analysis of Programmed DNA Elimination Sites in Tetrahymena thermophila.  It was a collaboration between Kathy Collins, multiple Tetrahymena researchers, the Eisen lab, and the UC Davis Genome Center Bioinformatics core (Joseph Fass and Dawei Lin).  The paper is in G3, an open access journal from the Genetics Society. 

New publication from members of my lab (e.g., @ryneches) & lab of Marc Facciotti on ChIP-seq based mapping of archaeal transcription factors

New publication from members of my lab and the lab of Marc Facciotti on a workflow for ChIP-seq based mapping of archaeal transcription factors. The paper includes a description of new software from Russell Neches in my lab called pique for peak calling.

See: A workflow for genome-wide mapping of archaeal transcription factors with ChIP-seq

Russell's pique software is available on github here: https://github.com/ryneches/pique.

Figure 3.

The Pique software package processes ChIP-seq coverage data to predict protein-binding sites. Strand-specific coverage data are output as tracks for the Gaggle Genome Browser, and putative-binding sites (peaks) are output as ‘bookmark files’. (A) Screenshot of data browsing in the Gaggle Genome Browser. Green box outlines the navigation window for clicking through bookmarks of predicted binding sites. Details of each site can be displayed (inset). The Gaggle toolbar (shown with black arrow) can be used to broadcast selected data to other ‘geese’ in the gaggle package, programs such as R, cytoscape, BLAST or KEGG. (B) Schematic overview of bioinformatics workflow.

Wilbanks, E., Larsen, D., Neches, R., Yao, A., Wu, C., Kjolby, R., & Facciotti, M. (2012). A workflow for genome-wide mapping of archaeal transcription factors with ChIP-seq Nucleic Acids Research DOI: 10.1093/nar/gks063

Assemblathon 1 paper out, includes many #UCDavis folks, though @vsbuffalo name backwards

Quick one here. A new paper is out from many folks, including Aaron Darling from my lab as well as a few other UC Davis folks. It is a cool paper: Assemblathon 1: A competitive assessment of de novo short read assembly methods

One minor issue - seems they got Vince Buffalo's name backwards - he is listed as Buffalo Vince on the Genome Research page, though in the PDF they have his name correct. Will have to see what he has to say about that.

More on 'phylogenomics' - as in functional prediction w/ phylogeny

There is a new paper out: Phylogenetic-based propagation of functional annotations within the Gene Ontology consortium in Briefings in Bioinformatics.

The paper is interesting and presents a new general approach to using phylogeny for functional prediction of uncharacterized genes. I am interested in this for many reasons including that I was one of, if not the first to lay this out as a concept.  In a series of papers from 1995-1998 I outlined how phylogenetic analysis could be used to aid in functional prediction for all the genes that were starting to be sequenced in genome projects without any associated functional studies (at the time, I referred to all these ESTs and other sequences as an "onslaught" - little did I know what was to come).

My first paper on this topic was in 1995: Evolution of the SNF2 family of proteins: subfamilies with distinct sequences and functions.  The abstract is below:

The SNF2 family of proteins includes representatives from a variety of species with roles in cellular processes such as transcriptional regulation (e.g. MOT1, SNF2 and BRM), maintenance of chromosome stability during mitosis (e.g. lodestar) and various aspects of processing of DNA damage, including nucleotide excision repair (e.g. RAD16 and ERCC6), recombinational pathways (e.g. RAD54) and post-replication daughter strand gap repair (e.g. RAD5). This family also includes many proteins with no known function. To better characterize this family of proteins we have used molecular phylogenetic techniques to infer evolutionary relationships among the family members. We have divided the SNF2 family into multiple subfamilies, each of which represents what we propose to be a functionally and evolutionarily distinct group. We have then used the subfamily structure to predict the functions of some of the uncharacterized proteins in the SNF2 family. We discuss possible implications of this evolutionary analysis on the general properties and evolution of the SNF2 family.

My first PLoS One paper .... yay: automated phylogenetic tree based rRNA analysis

Well, I have truly entered the modern world. My first PLoS One paper has just come out. It is entitled "An Automated Phylogenetic Tree-Based Small Subunit rRNA Taxonomy and Alignment Pipeline (STAP)" and well, it describes automated software for analyzing rRNA sequences that are generated as part of microbial diversity studies. The main goal behind this was to keep up with the massive amounts of rRNA sequences we and others could generate in the lab and to develop a tool that would remove the need for "manual" work in analyzing rRNAs.

The work was done primarily by Dongying Wu, a Project Scientist in my lab with assistance from a Amber Hartman, who is a PhD student in my lab. Naomi Ward, who was on the faculty at TIGR and is now at Wyoming, and I helped guide the development and testing of the software.

We first developed this pipeline/software in conjunction with analyzing the rRNA sequences that were part of the Sargasso Sea metagenome and results from the word was in the Venter et al. Sargasso paper. We then used the pipeline and continued to refine it as part of a variety of studies including a paper by Kevin Penn et al on coral associated microbes. Kevin was working as a technician for me and Naomi and is now a PhD student at Scripps Institute of Oceanography. We also had some input from various scientists we were working with on rRNA analyses, especially Jen Hughes Martiny

We made a series of further refinements and worked with people like Saul Kravitz from the Venter Institute and the CAMERA metagenomics database to make sure that the software could be run outside of my lab. And then we finally got around to writing up a paper .... and now it is out.

You can download the software here. The basics of the software are summarized below: (see flow chart too).

• Stage 1: Domain Analysis


• Take a rRNA sequence
• blast it against a database of representative rRNAs from all lines of life
• use the blast results to help choose sequences to use to make a multiple sequence alignment
• infer a phylogenetic tree from the alignment
• assign the sequence to a domain of life (bacteria, archaea, eukaryotes)


• Stage 2: First pass alignment and tree within domain
• take the same rRNA sequence
• blast against a database of rRNAs from within the domain of interest
• use the blast results to help choose sequences for a multiple alignment
• infer a phylogenetic tree from the alignment
• assign the sequence to a taxonomic group


• Stage 3: Second pass alignment and tree within domain
• extract sequences from members of the putative taxonomic group (as well as some others to balance the diversity)
• make a multiple sequence alignment
• infer a phylogenetic tree

From the above path, we end up with an alignment, which is useful for things such as counting number of species in a sample as well as a tree which is useful for determining what types of organisms are in the sample.

I note - the key is that it is completely automated and can be run on a single machine or a cluster and produces comparable results to manual methods. In the long run we plan to connect this to other software and other labs develop to build a metagenomics and microbial diversity workflow that will help in the processing of massive amounts of sequence data for microbial diversity studies.

I should note this work was supported primarily by a National Science Foundation grant to me and Naomi Ward as part of their “Assembling the Tree of Life” Program (Grant No. 0228651). Some final work on the project was funded by the Gordon and Betty Moore Foundation through grant #1660 to Jonathan Eisen and the CAMERA grant to UCSD.

Wu, D., Hartman, A., Ward, N., & Eisen, J. (2008). An Automated Phylogenetic Tree-Based Small Subunit rRNA Taxonomy and Alignment Pipeline (STAP) PLoS ONE, 3 (7) DOI: 10.1371/journal.pone.0002566