Author post: Segregation distorters are not a primary source of Dobzhansky-Muller incompatibilities in house mouse hybrids

This guest post is by Russ Corbett-Detig, Emily Jacobs-Palmer, and Hopi Hoekstra (@hopihoekstra) on their paper Corbett-Detig et al Segregation distorters are not a primary source of Dobzhansky-Muller incompatibilities in house mouse hybrids bioRxived here.

What are segregation distorters and how can they contribute to reproductive isolation?

Within an individual, somatic cells are typically genetic clones of one another; in contrast, haploid gametes are related to their compatriots at only half of all loci on average, opening doors to intra-individual competition and conflict. Eggs and sperm may express selfish genetic elements called segregation distorters (SDs) that disable or destroy competitor gametes carrying unrelated alleles. The resulting transmission advantage attained by SDs allows them to invade populations without improving the fitness of individuals that harbor them. Indeed, SDs often negatively impact carriers’ fitness because such hosts transmit fewer fit (or viable) gametes. Hence natural selection favors the evolution of alleles that suppress distortion and thereby restore fertility.

Coevolution of SDs and their suppressors can in turn contribute to the evolution of reproductive isolation between diverging lineages. How? If two populations become temporarily isolated from one another, SDs and later their accompanying suppressors may arise and eventually fix in one isolated population, possibly multiple times over. Should the two populations then encounter each other again, the sperm of hybrid males, for example, will contain one or more distorters without the appropriate suppressors, and these males will suffer decreased fertility. Over time, gene flow may be substantially and perhaps permanently hindered leading to the formation of two reproductively isolated species.

In some Drosophila species pairs, and in many crop plants, it is clear that the coevolution of SDs and their suppressors are major, even primary, contributors to the evolution of reproductive isolation between diverging lineages. At present, however, the relative importance of SDs-suppressor systems to reproductive isolation in broader taxonomic swathes of sexually reproducing organisms (e.g. mammals) is largely unexplored.

Our solution to the practical challenges of studying SDs

Supplemental_Figure_S1

The primary impediment to addressing this important question in evolutionary biology is practical, not conceptual. Conventionally, researchers detect SD-suppressor systems by crossing two strains to produce a large second-generation hybrid population; they then genotype these hybrids at a set of markers across the genome to identify loci that show substantive deviations from 50:50 mendelian ratios—putative SDs. Ultimately, this traditional approach suffers from two major pitfalls. First, for many organisms it is not feasible to raise and genotype enough hybrids (hundreds to thousands) to have sufficient statistical power to detect SDs, especially those with weaker effects. Second, by genotyping these second generation hybrids, rather than the gametes of their parents, one conflates SD with hybrid inviability, and it can be very difficult to disentangle these two factors.

How to circumvent these challenges? In this work, we develop an alternative approach that avoids these practical challenges. We first obtain high quality, motile sperm from first generation hybrid males (generated from two strains with available genome sequences), and then sequence these sperm in bulk as well as a somatic ‘control’ tissue. We then contrast the relative representation of the parental chromosomes in windows across the genome in both samples, searching for regions where the sperm allele ratios show more DNA copies of one parental haplotype, but the somatic alleles do not. Importantly, this approach is very general, and it can easily be applied to any number of interspecific or intraspecific crosses where it is possible to obtain large quantities of viable gametes.

Little evidence for SDs in house mouse hybrids

We apply this method to a nascent pair of Mus musculus subspecies,M. m. castaneus and M. m. domesticus. We chose these subspecies because hybrid males formed in this cross are known to be partially reproductively dysfunctional. Nonetheless, using our novel method we find no evidence supporting the presence of SDs—no genomics regions showing a statistical deviation from 50:50 compared to control tissue—despite strong statistical power to detect them. We conclude that SDs do not contribute appreciably to the evolution of reproductive isolation in this nascent species pair. Instead, reproductive isolation in these mammalian subspecies likely stems from other incompatibilities in spermatogenesis or ejaculate production unrelated to SD-suppressor coevolution.

So what’s next? Because this approach—bulk sequencing of sperm from hybrid males—can be used on almost any pair of interfertile taxa, we can begin to better understand the prevalence of SD and its role in speciation in a wide diversity of species.

Author post: Generation of a Panel of Induced Pluripotent Stem Cells From Chimpanzees: a Resource for Comparative Functional Genomics

Thus guest post is by Irene Gallego Romero (@ee_reh_neh) on her paper Gallego Romero et al “Generation of a Panel of Induced Pluripotent Stem Cells From Chimpanzees: a Resource for Comparative Functional Genomics” bioRxived here.

Genetic divergence in protein coding regions between humans and chimpanzees cannot explain phenotypic differences between the two species, or, more broadly, between other closely related groups. Although we have known this since the early days of genetic sequencing, it has been very hard to formally test the hypothesis that follows logically – that it may be changes in gene expression and regulation that underlie the divergence in phenotypes. This is especially true in the great apes, where there are plenty of ethical and practical impediments to experimentation. For instance, our ability to carry out functional studies and really decode cellular mechanisms is restricted to tissues that can be sampled non-invasively. To date, this has mostly meant fibroblasts and immortalised lymphoblastoid cell lines. The rest of comparative work in primates tends to be done in tissue samples collected post-mortem, where experimental manipulation is not a possibility.

Together, these limitations provided the impetus for us to develop a panel of high-quality induced pluripotent stem cell (iPSC) lines from chimpanzees. The promise of this panel lies, of course, not just in insights into the pluripotent state in chimpanzees (although that is certainly a worthy subject) but in how it opens the door to a tantalizing number of previously inaccessible questions, when we combine it with any of the many protocols available for differentiating iPSCs into particular somatic cell types that have remained out of reach until now.

The amount of work that went into developing an effective reprogramming protocol is not readily apparent in our preprint, but it was exhaustive – and exhausting! We began by using retroviral vectors to deliver the four factors that are commonly used to reprogram somatic cells to pluripotency, but soon encountered two fairly sizable problems with that approach. First, these viral vectors are integrated into the host genome during the course of reprogramming, and one never knows what they’re going to disrupt. This is an issue that everyone using retro- or lentiviral vectors has to contend with, and indeed, when we began working on the project three and a half years ago they were the most reliable and established reprogramming method around, so we were prepared to take our chances and scan the resulting lines to determine insertion sites. Regardless, the thought of random insertions of pluripotency genes set us somewhat on edge!

However, for reasons that we never fully understood, those chimpanzee lines had a lot of trouble silencing the retroviral vectors and maintaining pluripotency solely through endogenous mechanisms, as we show in one of our supplemental figures. At the time, we were making human iPSC lines in tandem using exactly the same vector stocks. While the human lines would lose most exogenous vector expression after 12 to 15 passages, in chimpanzee iPSCs of the same age we would generally find that expression of at least one, if not more, exongenous genes was as high as it had been on day one. This did not bode well for the lines, or for our ability to do interesting things with them! So we scrapped the integrating approach, and began optimizing protocols all over again. Fortunately for us, Shinya Yamanaka’s group had just published a very thorough protocol on reprogramming cells using non-integrating episomal vectors, which ended up laying the foundations of the one we present in our preprint.

The lines we have generated with it are of fantastic quality, and they have passed every test we have thrown at them with flying colours. Pluripotency is being endogenously maintained, they’re karyotypically normal, and they differentiate into all three germ layers both spontaneously as embryoid bodies and teratomas when injected into mice, and when we use directed protocols to push them towards a particular fate.

We were very interested in quantifying how human and chimpanzee iPSC lines differ from each other. To this end, we collected RNA-sequencing and methylation data from the chimpanzee iPSCs and the fibroblast lines they were generated from, as well as from seven human iPSC lines from various ethnic and cellular origins and their precursors, and compared them to one another. We find large numbers of inter-species differences both before and after reprogramming, but crucially, most of them are not the same differences. Of all the genes with strong evidence for differential expression between species at the iPSC stage, only 38% are also differentially expressed before reprogramming, and the situation is quite similar with regards to methylation.

Another thing we have found very striking in the data is the very clear increase in homogeneity within (and possibly between, although our design makes that harder to effectively quantify) species at the iPSC level relative to the precursor cells, both in gene expression levels and in DNA methylation. This finding will be very interesting to keep in mind as we go forward and differentiate the iPSCs into a suite of somatic cell types and see how these measures fluctuate through differentiation.

Ultimately, however, where the biggest significance of this work lies for us is in the fact that the lines are not just for our own use. They’re available to other researchers, and this is something we have had in mind from the earliest stages of the work. There is no possible way for our lab to even begin to tackle all the questions that these lines can be used to answer. So if you want to work with our chimpanzee iPSC lines, get in touch.

Increasing evolvability of local adaptation during range expansion.

Increasing evolvability of local adaptation during range expansion.
Marleen M. P. Cobben, Alexander Kubisch
doi: http://dx.doi.org/10.1101/008979

Increasing dispersal under range expansion increases invasion speed, which implies that a species needs to adapt more rapidly to newly experienced local conditions. However, due to iterated founder effects, local genetic diversity under range expansion is low. Evolvability (the evolution of mutation rates) has been reported to possibly be an adaptive trait itself. Thus, we expect that increased dispersal during range expansion may raise the evolvability of local adaptation, and thus increase the survival of expanding populations. We have studied this phenomenon with a spatially explicit individual-based metapopulation model of a sexually reproducing species with discrete generations, expanding into an elevational gradient. Our results show that evolvability is likely to evolve as a result of spatial variation experienced under range expansion. In addition, we show that different spatial phenomena associated with range expansion, in this case spatial sorting / kin selection and priority effects, can enforce each other.

Behavioral individuality reveals genetic control of phenotypic variability

Behavioral individuality reveals genetic control of phenotypic variability

Julien F Ayroles, Sean M Buchanan, Chelsea Jenney, Kyobi Skutt-Kakaria, Jennifer Grenier, Andrew G Clark, Daniel L Hartl, Benjamin L de Bivort
doi: http://dx.doi.org/10.1101/009027

Variability is ubiquitous in nature and a fundamental feature of complex systems. Few studies, however, have investigated variance itself as a trait under genetic control. By focusing primarily on trait means and ignoring the effect of alternative alleles on trait variability, we may be missing an important axis of genetic variation contributing to phenotypic differences among individuals. To study genetic effects on individual-to-individual phenotypic variability (or intragenotypic variability), we used a panel of Drosophila inbred lines and focused on locomotor handedness, in an assay optimized to measure variability. We discovered that some lines had consistently high levels of intragenotypic variability among individuals while others had low levels. We demonstrate that the degree of variability is itself heritable. Using a genome-wide association study (GWAS) for the degree of intragenotypic variability as the phenotype across lines, we identified several genes expressed in the brain that affect variability in handedness without affecting the mean. One of these genes, Ten-a implicated a neuropil in the central complex of the fly brain as influencing the magnitude of behavioral variability, a brain region involved in sensory integration and locomotor coordination6. We have validated these results using genetic deficiencies, null alleles, and inducible RNAi transgenes. This study reveals the constellation of phenotypes that can arise from a single genotype and it shows that different genetic backgrounds differ dramatically in their propensity for phenotypic variabililty. Because traditional mean-focused GWASs ignore the contribution of variability to overall phenotypic variation, current methods may miss important links between genotype and phenotype.

The Sea Lamprey Meiotic Map Resolves Ancient Vertebrate Genome Duplications

The Sea Lamprey Meiotic Map Resolves Ancient Vertebrate Genome Duplications
Jeramiah Smith
doi: http://dx.doi.org/10.1101/008953

Gene and genome duplications serve as an important reservoir of material for the evolution of new biological functions. It is generally accepted that many genes present in vertebrate genomes owe their origin to two whole genome duplications that occurred deep in the ancestry of the vertebrate lineage. However, details regarding the timing and outcome of these duplications are not well resolved. We present high-density meiotic and comparative genomic maps for the sea lamprey, a representative of an ancient lineage that diverged from all other vertebrates approximately 550 million years ago. Linkage analyses yielded a total of 95 linkage groups, similar to the estimated number of germline chromosomes (1N ~ 99), spanning a total of 5,570.25 cM. Comparative mapping data yield strong support for one ancient whole genome duplication but do not strongly support a hypothetical second event. Rather, these comparative maps reveal several evolutionary independent segmental duplications occurring over the last 600+ million years of chordate evolution. This refined history of vertebrate genome duplication should permit more precise investigations into the evolution of vertebrate gene functions.

Scalable Genomics with R and Bioconductor

Scalable Genomics with R and Bioconductor
Michael Lawrence, Martin Morgan
Journal-ref: Statistical Science 2014, Vol. 29, No. 2, 214-226
Subjects: Genomics (q-bio.GN); Distributed, Parallel, and Cluster Computing (cs.DC)

This paper reviews strategies for solving problems encountered when analyzing large genomic data sets and describes the implementation of those strategies in R by packages from the Bioconductor project. We treat the scalable processing, summarization and visualization of big genomic data. The general ideas are well established and include restrictive queries, compression, iteration and parallel computing. We demonstrate the strategies by applying Bioconductor packages to the detection and analysis of genetic variants from a whole genome sequencing experiment.

Functional analysis and co-evolutionary model of chromatin and DNA methylation networks in embryonic stem cells

Functional analysis and co-evolutionary model of chromatin and DNA methylation networks in embryonic stem cells
Enrique Carrillo de Santa Pau, Juliane Perner, David Juan, Simone Marsili, David Ochoa, Ho-Ryun Chung, Daniel Rico, Martin Vingron, Alfonso Valencia
doi: http://dx.doi.org/10.1101/008821
We have analyzed publicly available epigenomic data of mouse embryonic stem cells (ESCs) combining diverse next-generation sequencing (NGS) studies (139 experiments from 30 datasets with a total of 77 epigenomic features) into a homogeneous dataset comprising various cytosine modifications (5mC, 5hmC and 5fC), histone marks and Chromatin related Proteins (CrPs). We applied a set of newly developed statistical analysis methods with the goal of understanding the associations between chromatin states, detecting co-occurrence of DNA-protein binding and epigenetic modification events, as well as detecting coevolution of core CrPs. The resulting networks reveal the complex relations between cytosine modifications and protein complexes and their dependence on defined ESC chromatin contexts. A detailed analysis allows us to detect proteins associated to particular chromatin states whose functions are related to the different cytosine modifications, i.e. RYBP with 5fC and 5hmC, NIPBL with 5hmC and OGT with 5hmC. Moreover, in a co-evolutionary analysis suggesting a central role of the Cohesin complex in the evolution of the epigenomic network, as well as strong co-evolutionary links between proteins that co-locate in the ESC epigenome with DNA methylation (MBD2 and CBX3) and hydroxymethylation (TET1 and KDM2A). In summary, the new application of computational methodologies reveals the complex network of relations between cytosine modifications and epigenomic players that is essential in shaping the molecular state of ESCs.