# Towards the Recapitulation of Ancient History in the Laboratory: Combining Synthetic Biology with Experimental Evolution

Towards the Recapitulation of Ancient History in the Laboratory: Combining Synthetic Biology with Experimental Evolution

Betul Kacar, Eric Gaucher
(Submitted on 23 Sep 2012)

One way to understand the role history plays on evolutionary trajectories is by giving ancient life a second opportunity to evolve. Our ability to empirically perform such an experiment, however, is limited by current experimental designs. Combining ancestral sequence reconstruction with synthetic biology allows us to resurrect the past within a modern context and has expanded our understanding of protein functionality within a historical context. Experimental evolution, on the other hand, provides us with the ability to study evolution in action, under controlled conditions in the laboratory. Here we describe a novel experimental setup that integrates two disparate fields – ancestral sequence reconstruction and experimental evolution. This allows us to rewind and replay the evolutionary history of ancient biomolecules in the laboratory. We anticipate that our combination will provide a deeper understanding of the underlying roles that contingency and determinism play in shaping evolutionary processes.

# Comparative Analysis of Tandem Repeats from Hundreds of Species Reveals Unique Insights into Centromere Evolution

Comparative Analysis of Tandem Repeats from Hundreds of Species Reveals Unique Insights into Centromere Evolution

Daniël P. Melters, Keith R. Bradnam, Hugh A. Young, Natalie Telis, Michael R. May, J. Graham Ruby, Robert Sebra, Paul Peluso, John Eid, David Rank, José Fernando Garcia, Joseph L. DeRisi, Timothy Smith, Christian Tobias, Jeffrey Ross-Ibarra, Ian F. Korf, Simon W.-L. Chan
(Submitted on 22 Sep 2012)

Centromeres are essential for chromosome segregation, yet their DNA sequences evolve rapidly. In most animals and plants that have been studied, centromeres contain megabase-scale arrays of tandem repeats. Despite their importance, very little is known about the degree to which centromere tandem repeats share common properties between different species across different phyla. We used bioinformatic methods to identify high-copy tandem repeats from 282 species using publicly available genomic sequence and our own data. The assumption that the most abundant tandem repeat is the centromere DNA was true for most species whose centromeres have been previously characterized, suggesting this is a general property of genomes. Our methods are compatible with all current sequencing technologies. Long Pacific Biosciences sequence reads allowed us to find tandem repeat monomers up to 1,419 bp. High-copy centromere tandem repeats were found in almost all animal and plant genomes, but repeat monomers were highly variable in sequence composition and in length. Furthermore, phylogenetic analysis of sequence homology showed little evidence of sequence conservation beyond ~50 million years of divergence. We find that despite an overall lack of sequence conservation, centromere tandem repeats from diverse species showed similar modes of evolution, including the appearance of higher order repeat structures in which several polymorphic monomers make up a larger repeating unit. While centromere position in most eukaryotes is epigenetically determined, our results indicate that tandem repeats are highly prevalent at centromeres of both animals and plants. This suggests a functional role for such repeats, perhaps in promoting concerted evolution of centromere DNA across chromosomes.

# Chimeric protein complexes in hybrid species generate novel evolutionary phenotypes

Chimeric protein complexes in hybrid species generate novel evolutionary phenotypes
Elzbieta M. Piatkowska, David Knight, Daniela Delneri
(Submitted on 19 Sep 2012)
Hybridization between species is an important mechanism for the origin of novel lineages and adaptation to new environments. Increased allelic variation and modification of the transcriptional network are the two recognized forces currently deemed to be responsible for the phenotypic properties seen in hybrids. However, since the majority of the biological functions in a cell are carried out by protein complexes, inter-specific protein assemblies therefore represent another important source of natural variation upon which evolutionary forces can act. Here we studied the composition of six protein complexes in two different Saccharomyces “sensu strictu” hybrids, to understand whether chimeric interactions can be freely formed in the cell in spite of species-specific co-evolutionary forces, and whether the different types of complexes cause a change in hybrid fitness. The protein assemblies were isolated from the hybrids via affinity chromatography and identified via mass spectrometry. We found evidence of spontaneous chimericity for four of the six protein assemblies tested and we showed that different types of complexes can cause a variety of phenotypes in selected environments. In the case of TRP2/TRP3 complex, the effect of such chimeric formation resulted in the fitness advantage of the hybrid in an environment lacking tryptophan, while only one type of parental combination of the MBF complex could confer viability to the hybrid under respiratory conditions. This study provides empirical evidence that chimeric protein complexes can freely assemble in cells and reveals a new mechanism to generate phenotypic novelty and plasticity in hybrids to complement the genomic innovation resulting from gene duplication. The ability to exchange orthologous members has also important implications for the adaptation and subsequent genome evolution of the hybrids in terms of pattern of gene loss.

# On The External Branches Of Coalescent Processes With Multiple Collisions With An Emphasis On The Bolthausen-Sznitman Coalescent

On The External Branches Of Coalescent Processes With Multiple Collisions With An Emphasis On The Bolthausen-Sznitman Coalescent
Jean-Stephane Dhersin (IG, LAGA), Martin Moehle
(Submitted on 15 Sep 2012)

A recursion for the joint moments of the external branch lengths for coalescents with multiple collisions ($\Lambda$-coalescents) is provided. This recursion is used to derive asymptotic expansions as the sample size $n$ tends to infinity for the moments of the total external branch length of the Bolthausen–Sznitman coalescent. The proof is based on an elementary difference method. An alternative differential equation method is developed which can be used to obtain exact solutions for the joint moments of the external branch lengths for the Bolthausen–Sznitman coalescent. The results for example show that the lengths of two randomly chosen external branches are positively correlated for the Bolthausen–Sznitman coalescent, whereas they are negatively correlated for the Kingman coalescent provided that $n\ge 4$.

# Maximum Likelihood Estimation of Frequencies of Known Haplotypes from Pooled Sequence Data

Maximum Likelihood Estimation of Frequencies of Known Haplotypes from Pooled Sequence Data

Darren Kessner, Tom Turner, John Novembre
(Submitted on 19 Sep 2012)

DNA samples are often pooled, either by experimental design, or because the sample itself is a mixture. For example, when population allele frequencies are of primary interest, individual samples may be pooled together to lower the cost of sequencing. Alternatively, the sample itself may be a mixture of multiple species or strains (e.g. bacterial species comprising a microbiome, or pathogen strains in a blood sample). We present an expectation-maximization (EM) algorithm for estimating haplotype frequencies in a pooled sample directly from mapped sequence reads, in the case where the possible haplotypes are known. This method is relevant to the analysis of pooled sequencing data from selection experiments, as well as the calculation of proportions of different strains within a metagenomics sample. Our method outperforms existing methods based on single- site allele frequencies, as well as simple approaches using sequence read data. We have implemented the method in a freely available open-source software tool.

# Our paper: Integrated analysis of variants and pathways in genome-wide association studies using polygenic models of disease

[This author post is by Peter Carbonetto on Integrated analysis of variants and pathways in genome-wide association studies using polygenic models of disease, available from the arXiv here.]

I expect that most readers of this blog appreciate the impact that genome-wide association studies have had on our understanding of many common diseases. Still, I think it is important to reiterate a major appeal of genome-wide association studies: the analysis is conceptually straightforward to understand, even for people who have never had to suffer through a course on statistics or epidemiology. To find links between genetic loci and disease, the analysis consists of systematically searching across the genome for variants that show statistically significant correlation with susceptibility to disease. These correlations signal the presence of nearby genes—or perhaps DNA elements that regulate other genes—that are risk factors for disease.

Many readers of this blog will also appreciate, due to the multifactorial nature of most common diseases, the difficulty of establishing compelling evidence for disease-variant correlations. Hence the search for more effective data-driven strategies for discovering genetic factors underlying common diseases.

One strategy is to assess evidence for the accumulation, or “enrichment,” of disease-conferring mutations within known biological pathways. The intuition is that identifying the accumulation of small genetic effects acting in a common pathway is easier than mapping the individual genes within the pathway that contribute to disease susceptibility.

We asked whether identifying these enriched pathways can also give us useful feedback about the individual gene variants associated with disease. To answer this question, we developed a statistical method that adjusts the support for disease-variant associations to reflect enrichment of associations in a pathway. Our approach was to introduce an enrichment parameter that quantifies the increase in the probability that each variant in the pathway is associated with disease risk.

Is this a valid approach? To investigate, we applied our approach to data from the Wellcome Trust Crohn’s disease study from 2007. First, we identified a broad class of cytokine signaling genes that were enriched for genetic associations with Crohn’s disease. Next, by prioritizing variants in this pathway, we discovered candidates for association—including the STAT3 gene, the IBD5 locus, and the MHC class II genes—that were not identified in conventional analyses of the same data. These results help validate our approach, as these genetic associations have been independently confirmed in other studies and meta-analyses with much larger combined samples.

Several other important lessons emerged from our case study:

1. Interrogate as many pathways as possible. Because we collected over 3000 candidate pathways from several sources (Reactome, KEGG, BioCarta, BioCyc, etc.), many of the pathways highlighted in previous analyses of the same data were eclipsed by much stronger enrichment signals in our analysis.

2. Assess evidence for combinations of enriched pathways. Some pathways become interesting only after assessing enrichment of the pathway in combination with another pathway.

3. Account for the heterogeneity of effect sizes in Crohn’s disease. One of the assumptions we made in our analysis, mainly out of convenience, was that the additive effects on disease risk are normally distributed. While this assumption simplified this analysis, we suspect that a normal distribution does not adequately capture the smaller effect sizes in pathways, leading to a loss of power to detect enriched pathways.

At conferences, and around the lab, I’ve heard many complaints about pathway analysis (or gene set enrichment analysis) for genome-wide association studies. One complaint is that the results are difficult to interpret. Another common complaint is that the findings are sensitive to arbitrary significance thresholds. While we didn’t devote much space in the paper to a discussion of these issues, we believe that our approach offers a coherent solution to many of these problems.

Ultimately, we would like other researchers to use our methods to analyze data from their own genome-wide association studies. We tried to make our paper as accessible as possible, especially to biologists that are not well-acquainted with Bayesian approaches, by carefully explaining how to interpret the Bayes factors and posterior statistics used in the analysis. We are working on releasing the full source code (in R and MATLAB) for all our methods, and accompanying documentation.

Peter Carbonetto

# Our paper: The genetic prehistory of southern Africa

[This author post is by Joe Pickrell (@joe_pickrell), Nick Patterson, Mark Stoneking, David Reich, and Brigitte Pakendorf on The genetic prehistory of southern Africa, available from arXiv here]

The indigenous populations of southern Africa are phenotypically, linguistically, culturally, and genetically diverse. Although many groups speak Bantu languages (having arrived in the region during an expansion of Iron-Age agriculturalists), there are a number of populations who speak diverse non-Bantu languages with heavy use of click consonants. We refer to these populations as “Khoisan“. Most of the Khoisan populations are hunter-gatherers, but some are pastoralists; the extensive linguistic and cultural diversity of the Khoisan (who live in a relatively small region around the Kalahari semi-desert) is historically puzzling.

Two hunter-gatherer (or formerly hunter-gatherer) populations in East Africa, the Hadza and Sandawe, also speak languages that also make use of click consonants. Linguists see little in common between the languages in southern Africa and Hadza, although Sandawe might be genealogically related to some of the Khoisan languages. Nevertheless, the shared use of click consonants and a foraging lifestyle led many to hypothesize that the southern African Khoisan populations are genetically related to the Hadza and Sandawe, which would imply that their ancestors were once considerably more widespread. This hypothesis has been controversial for decades.

Tree relating the Khoisan-like proportion of ancestry (shown in blue in the barplot) in Khoisan, Hadza, and Sandawe after accounting for non-Khoisan admixture.

In our study, we use genetic data to address the history of the diverse groups within southern Africa and their relationship to the Hadza and Sandawe. Specifically, we genotyped individuals from 16 Khoisan populations, 5 neighboring populations that speak Bantu languages, and the Hadza (the latter thanks to Brenna Henn, Joanna Mountain, and Carlos Bustamante) on a SNP array designed for studies of human history, in that the SNP ascertainement scheme is known and includes SNPs ascertained in the Khoisan. We then merged in Hadza and Sandawe samples from a recent paper by Joseph Lachance, Sarah Tishkoff and colleagues. The main conclusions are as follows:

1. Within the southern African Khoisan, there are two genetic groups, which correspond roughly to populations in the northwest and southeast Kalahari semi-desert. Populations from these two groups have been labeled in the tree in this post (see also Figure 1B in the preprint). We estimate that these two groups diverged within the last 30,000 years. However, this date should be taken as an upper bound due to point #2 below.
2. All southern African Khoisan groups are admixed with non-Khoisan populations. Even the most isolated Khoisan groups (i.e. the “San” from the HGDP, who are included in the “Ju|’hoan_North” group in our paper) show some evidence of admixture with agricultualist and/or pastoralist groups. A subtle technical point is that this had not been previously noticed because methods that rely on correlations in allele frequencies are sometimes unable to detect admixture if all populations are admixed (this is related to Mr. Razib Khan’s post on why ADMIXTURE is not a test for admixure). To get around this, we developed new methods based on the decay of linkage disequilibrum.
3. The Hadza and Sandawe trace part of their ancestry to admixture with a population related to the Khoisan. After accounting for admixture, we built a tree of “Khoisan-like” ancestry in the southern and eastern African populations (see the Figure above). The striking thing is that the Hadza and Sandawe fall with high confidence on the same branch as the Khoisan. This suggests that, prior to subsequent migrations of food-producing peoples over most of sub-Saharan Africa, populations related to the Khoisan were indeed spread continuously over a huge geographic range including Tanzania and southern Africa.

We’re excited about these results for a number of reasons. First of all, we’re now on our way towards understanding the history of the diverse Khoisan populations–for years these populations have been treated as genetically equivalent, but it’s clear that each population has its own complex history. Secondly, with the new statistical methods we’ve developed we were able to show not only the varying amounts of admixture that has occurred at different times in southern African populations, but were also able to peel away these layers of admixture to learn about the relationships among Khoisan populations that existed thousands of years ago. Finally, we think that these results have important implications for work using genetics to understand the geographic origin of modern humans within Africa. Though both southern and eastern Africa have been proposed as potential origins, from the tree in this post, we see no genetic evidence in favor of either; from our point of view this question remains open.

Joe Pickrell, Nick Patterson, Mark Stoneking, David Reich, and Brigitte Pakendorf