Full-genome evolutionary histories of selfing, splitting and selection in Caenorhabditis
Cristel G. Thomas, Wei Wang, Richard Jovelin, Rajarshi Ghosh, Tatiana Lomasko, Quang Trinh, Leonid Kruglyak, Lincoln D Stein, Asher D Cutter
The nematode Caenorhabditis briggsae is a model for comparative developmental evolution with C. elegans. Worldwide collections of C. briggsae have implicated an intriguing history of divergence among genetic groups separated by latitude, or by restricted geography, that is being exploited to dissect the genetic basis to adaptive evolution and reproductive incompatibility. And yet, the genomic scope and timing of population divergence is unclear. We performed high-coverage whole-genome sequencing of 37 wild isolates of the nematode C. briggsae and applied a pairwise sequentially Markovian coalescent (PSMC) model to 703 combinations of genomic haplotypes to draw inferences about population history, the genomic scope of natural selection, and to compare with 40 wild isolates of C. elegans. We estimate that a diaspora of at least 6 distinct C. briggsae lineages separated from one another approximately 200 thousand generations ago, including the ???Temperate??? and ???Tropical??? phylogeographic groups that dominate most samples from around the world. Moreover, an ancient population split in its history 2 million generations ago, coupled with only rare gene flow among lineage groups, validates this system as a model for incipient speciation. Low versus high recombination regions of the genome give distinct signatures of population size change through time, indicative of widespread effects of selection on highly linked portions of the genome owing to extreme inbreeding by self-fertilization. Analysis of functional mutations indicates that genomic context, owing to selection that acts on long linkage blocks, is a more important driver of population variation than are the functional attributes of the individually encoded genes.
Bayesian analyses of Yemeni mitochondrial genomes suggest multiple migration events with Africa and Western Eurasia
Deven Nikunj Vyas, Andrew Kitchen, Aida Teresa Miró-Herrans, Laurel Nichole Pearson, Ali Al-Meeri, Connie Jo Mulligan
Anatomically modern humans (AMHs) left Africa ~60,000 years ago, marking the first of multiple dispersal events by AMH between Africa and the Arabian Peninsula. The southern dispersal route (SDR) out of Africa (OOA) posits that early AMHs crossed the Bab el-Mandeb strait from the Horn of Africa into what is now Yemen and followed the coast of the Indian Ocean into eastern Eurasia. If AMHs followed the SDR and left modern descendants in situ, Yemeni populations should retain old autochthonous mitogenome lineages. Alternatively, if AMHs did not follow the SDR or did not leave modern descendants in the region, only young autochthonous lineages will remain as evidence of more recent dispersals. We sequenced 113 whole mitogenomes from multiple Yemeni regions with a focus on haplogroups M, N, and L3(xM,N) as they are considered markers of the initial OOA migrations. We performed Bayesian evolutionary analyses to generate time-measured phylogenies calibrated by Neanderthal and Denisovan mitogenome sequences in order to determine the age of Yemeni-specific clades in our dataset. Our results indicate that the M1, N1, and L3(xM,N) sequences in Yemen are the product of recent migration from Africa and western Eurasia. Although these data suggest that modern Yemeni mitogenomes are not markers of the original OOA migrants, we hypothesize that recent population dynamics may obscure any genetic signature of an ancient SDR migration.
A general condition for adaptive genetic polymorphism in temporally and spatially heterogeneous environments
Hannes Svardal, Claus Rueffler, Joachim Hermisson
Comments: Accepted for publication in Theoretical Population Biology
Subjects: Populations and Evolution (q-bio.PE)
Both evolution and ecology have long been concerned with the impact of variable environmental conditions on observed levels of genetic diversity within and between species. We model the evolution of a quantitative trait under selection that fluctuates in space and time, and derive an analytical condition for when these fluctuations promote genetic diversification. As ecological scenario we use a generalized island model with soft selection within patches in which we incorporate generation overlap. We allow for arbitrary fluctuations in the environment including spatio-temporal correlations and any functional form of selection on the trait. Using the concepts of invasion fitness and evolutionary branching, we derive a simple and transparent condition for the adaptive evolution and maintenance of genetic diversity. This condition relates the strength of selection within patches to expectations and variances in the environmental conditions across space and time. Our results unify, clarify, and extend a number of previous results on the evolution and maintenance of genetic variation under fluctuating selection. Individual-based simulations show that our results are independent of the details of the genetic architecture and on whether reproduction is clonal or sexual. The onset of increased genetic variance is predicted accurately also in small populations in which alleles can go extinct due to environmental stochasticity.
The developmental transcriptome of contrasting Arctic charr (Salvelinus alpinus) morphs
Jóhannes Gudbrandsson, Ehsan P Ahi, Kalina H Kapralova, Sigrídur R Franzdottir, Bjarni K Kristjánsson, Sophie S Steinhaeuser, Ísak M Jóhannesson, Valerie H Maier, Sigurdur S Snorrason, Zophonías O Jónsson, Arnar Pálsson
Species showing repeated evolution of similar traits can help illuminate the molecular and developmental basis of diverging traits and specific adaptations. Following the last glacial period, dwarfism and specialized bottom feeding morphology evolved rapidly in several landlocked Arctic charr (Salvelinus alpinus) populations in Iceland. In order to study the genetic divergence between small benthic morphs and larger morphs with limnetic morphotype, we conducted an RNA-seq transcriptome analysis of developing charr. We sequenced mRNA from whole embryos at four stages in early development of two stocks with very different morphologies, the small benthic (SB) charr from Lake Thingvallavatn and Holar aquaculture (AC) charr. The data reveal significant differences in expression of several biological pathways during charr development. There is also a difference between SB- and AC-charr in mitochondrial genes involved in energy metabolism and blood coagulation genes. We confirmed expression difference of five genes in whole embryos with qPCR, including lysozyme and natterin which was previously identified as a fish-toxin of a lectin family that may be a putative immunopeptide. We verified differential expression of 7 genes in developing heads, and the expression associated consistently with benthic v.s. limnetic charr (studied in 4 morphs total). Comparison of Single nucleotide polymorphism (SNP) frequencies reveals extensive genetic differentiation between the SB- and AC-charr (60 fixed SNPs and around 1300 differing more than 50% in frequency). In SB-charr the high frequency derived SNPs are in genes related to translation and oxidative processes. Curiously, several derived SNPs reside in the 12s and 16s mitochondrial ribosomal RNA genes, including a base highly conserved among fishes. The data implicate multiple genes and molecular pathways in divergence of small benthic charr and/or the response of aquaculture charr to domestication. Functional, genetic and population genetic studies on more freshwater and anadromous populations are needed to confirm the specific loci and mutations relating to specific ecological or domestication traits in Arctic charr.
A Composite Genome Approach to Identify Phylogenetically Informative Data from Next-Generation Sequencing
Rachel S. Schwartz, Kelly Harkins, Anne C. Stone, Reed A. Cartwright
(Submitted on 16 May 2013 (v1), last revised 12 Nov 2014 (this version, v3))
We have developed a novel method to rapidly obtain homologous genomic data for phylogenetics directly from next-generation sequencing reads without the use of a reference genome. This software, called SISRS, avoids the time consuming steps of de novo whole genome assembly, genome-genome alignment, and annotation. For simulations SISRS is able to identify large numbers of loci containing variable sites with phylogenetic signal. For genomic data from apes, SISRS identified thousands of variable sites, from which we produced an accurate phylogeny. Finally, we used SISRS to identify phylogenetic markers that we used to estimate the phylogeny of placental mammals. We recovered phylogenies from multiple datasets that were consistent with previous conflicting estimates of the relationships among mammals. SISRS is open source and freely available at this https URL
Resolving microbial microdiversity with high accuracy full length 16S rRNA Illumina sequencing
Catherine Burke, Aaron E Darling
We describe a method for sequencing full-length 16S rRNA gene amplicons using the high throughput Illumina MiSeq platform. The resulting sequences have about 100-fold higher accuracy than standard Illumina reads and are chimera filtered using information from a single molecule dual tagging scheme that boosts the signal available for chimera detection. We demonstrate that the data provides fine scale phylogenetic resolution not available from Illumina amplicon methods targeting smaller variable regions of the 16S rRNA gene.
Epidemiological and evolutionary analysis of the 2014 Ebola virus outbreak
Marta Łuksza, Trevor Bedford, Michael Lässig
Subjects: Populations and Evolution (q-bio.PE)
The 2014 epidemic of the Ebola virus is governed by a genetically diverse viral population. In the early Sierra Leone outbreak, a recent study has identified new mutations that generate genetically distinct sequence clades. Here we find evidence that major Sierra Leone clades have systematic differences in growth rate and reproduction number. If this growth heterogeneity remains stable, it will generate major shifts in clade frequencies and influence the overall epidemic dynamics on time scales within the current outbreak. Our method is based on simple summary statistics of clade growth, which can be inferred from genealogical trees with an underlying clade-specific birth-death model of the infection dynamics. This method can be used to perform realtime tracking of an evolving epidemic and identify emerging clades of epidemiological or evolutionary significance.