Chromosomal rearrangements as barriers to genetic homogenization between archaic and modern humans

Chromosomal rearrangements as barriers to genetic homogenization between archaic and modern humans

Rebekah L. Rogers
(Submitted on 26 May 2015)

Chromosomal rearrangements, which shuffle DNA across the genome, are an important source of divergence across taxa that can modify gene expression and function. Using a paired-end read approach with Illumina sequence data for archaic humans, I identify changes in genome structure that occurred recently in human evolution. Hundreds of rearrangements indicate genomic trafficking between the sex chromosomes and autosomes, raising the possibility of sex-specific changes. Additionally, genes adjacent to genome structure changes in Neanderthals are associated with testis-specific expression, consistent with evolutionary theory that new genes commonly form with expression in the testes. I identify one case of new-gene creation through transposition from the Y chromosome to chromosome 10 that combines the 5′ end of the testis-specific gene Fank1 with previously untranscribed sequence. This new transcript experienced copy number expansion in archaic genomes, indicating rapid genomic change. Finally, loci containing genome structure changes show diminished rates of introgression from Neanderthals into modern humans, consistent with the hypothesis that rearrangements serve as barriers to gene flow during hybridization. Together, these results suggest that this previously unidentified source of genomic variation has important biological consequences in human evolution.

A Unified Architecture of Transcriptional Regulatory Elements

A Unified Architecture of Transcriptional Regulatory Elements

Robin Andersson, Albin Sandelin, Charles G Danko
doi: http://dx.doi.org/10.1101/019844

Gene expression is precisely controlled in time and space through the integration of signals that act at gene promoters and gene-distal enhancers. Classically, promoters and enhancers are considered separate classes of regulatory elements, often distinguished by histone modifications. However, recent studies have revealed broad similarities between enhancers and promoters, blurring the distinction: active enhancers often initiate transcription, and some gene promoters have the potential of enhancing transcriptional output of other promoters. Here, we propose a model in which promoters and enhancers are considered a single class of functional element, with a unified architecture for transcription initiation. The context of interacting regulatory elements, and surrounding sequences, determine local transcriptional output as well as the enhancer and promoter activities of individual elements.

Large-scale Machine Learning for Metagenomics Sequence Classification

Large-scale Machine Learning for Metagenomics Sequence Classification

Kévin Vervier (CBIO), Pierre Mahé, Maud Tournoud, Jean-Baptiste Veyrieras, Jean-Philippe Vert (CBIO)
(Submitted on 26 May 2015)

Metagenomics characterizes the taxonomic diversity of microbial communities by sequencing DNA directly from an environmental sample. One of the main challenges in metagenomics data analysis is the binning step, where each sequenced read is assigned to a taxonomic clade. Due to the large volume of metagenomics datasets, binning methods need fast and accurate algorithms that can operate with reasonable computing requirements. While standard alignment-based methods provide state-of-the-art performance, compositional approaches that assign a taxonomic class to a DNA read based on the k-mers it contains have the potential to provide faster solutions. In this work, we investigate the potential of modern, large-scale machine learning implementations for taxonomic affectation of next-generation sequencing reads based on their k-mers profile. We show that machine learning-based compositional approaches benefit from increasing the number of fragments sampled from reference genome to tune their parameters, up to a coverage of about 10, and from increasing the k-mer size to about 12. Tuning these models involves training a machine learning model on about 10 8 samples in 10 7 dimensions, which is out of reach of standard soft-wares but can be done efficiently with modern implementations for large-scale machine learning. The resulting models are competitive in terms of accuracy with well-established alignment tools for problems involving a small to moderate number of candidate species, and for reasonable amounts of sequencing errors. We show, however, that compositional approaches are still limited in their ability to deal with problems involving a greater number of species, and more sensitive to sequencing errors. We finally confirm that compositional approach achieve faster prediction times, with a gain of 3 to 15 times with respect to the BWA-MEM short read mapper, depending on the number of candidate species and the level of sequencing noise.

On the equivalence of Maximum Parsimony and Maximum Likelihood on phylogenetic networks

On the equivalence of Maximum Parsimony and Maximum Likelihood on phylogenetic networks

Mareike Fischer, Parisa Bazargani
(Submitted on 26 May 2015)

Phylogenetic inference aims at reconstructing the evolutionary relationships of different species given some data (e.g. DNA, RNA or proteins). Traditionally, the relationships between species were assumed to be treelike, so the most frequently used phylogenetic inference methods like e.g. Maximum Parsimony or Maximum Likelihood were originally introduced to reconstruct phylogenetic trees. However, it has been well-known that some evolutionary events like hybridization or horizontal gene transfer cannot be represented by a tree but rather require a phylogenetic network. Therefore, current research seeks to adapt tree inference methods to networks. In the present paper, we analyze Maximum Parsimony and Maximum Likelihood on networks for various network definitions which have recently been introduced, and we investigate the well-known Tuffley and Steel equivalence result concerning these methods under the setting of a phylogenetic network.

RAD sequencing enables unprecedented phylogenetic resolution and objective species delimitation in recalcitrant divergent taxa

RAD sequencing enables unprecedented phylogenetic resolution and objective species delimitation in recalcitrant divergent taxa

Santiago Herrera, Timothy M. Shank
doi: http://dx.doi.org/10.1101/019745

Species delimitation is problematic in many taxa due to the difficulty of evaluating predictions from species delimitation hypotheses, which chiefly relay on subjective interpretations of morphological observations and/or DNA sequence data. This problem is exacerbated in recalcitrant taxa for which genetic resources are scarce and inadequate to resolve questions regarding evolutionary relationships and uniqueness. In this case study we demonstrate the empirical utility of restriction site associated DNA sequencing (RAD-seq) by unambiguously resolving phylogenetic relationships among recalcitrant octocoral taxa with divergences greater than 80 million years. We objectively infer robust species boundaries in the genus Paragorgia, which contains some of the most important ecosystem engineers in the deep-sea, by testing alternative taxonomy-guided or unguided species delimitation hypotheses using the Bayes factors delimitation method (BFD*) with genome-wide single nucleotide polymorphism data. We present conclusive evidence rejecting the current morphological species delimitation model for the genus Paragorgia and indicating the presence of cryptic species boundaries associated with environmental variables. We argue that the suitability limits of RAD-seq for phylogenetic inferences in divergent taxa cannot be assessed in terms of absolute time, but depend on taxon-specific factors such as mutation rate, generation time and effective population size. We show that classic morphological taxonomy can greatly benefit from integrative approaches that provide objective tests to species delimitation hypothesis. Our results pave the way for addressing further questions in biogeography, species ranges, community ecology, population dynamics, conservation, and evolution in octocorals and other marine taxa.

Distance from Sub-Saharan Africa Predicts Mutational Load in Diverse Human Genomes

Distance from Sub-Saharan Africa Predicts Mutational Load in Diverse Human Genomes

Brenna M. Henn, Laura R Botigue, Stephan Peischl, Isabelle Dupanloup, Mikhail Lipatov, Brian K Maples, Alicia R Martin, Shaila Musharoff, Howard Cann, Michael Snyder, Laurent Excoffier, Jeffrey Kidd, Carlos D Bustamante
doi: http://dx.doi.org/10.1101/019711

The Out-of-Africa (OOA) dispersal ~50,000 years ago is characterized by a series of founder events as modern humans expanded into multiple continents. Population genetics theory predicts an increase of mutational load in populations undergoing serial founder effects during range expansions. To test this hypothesis, we have sequenced full genomes and high-coverage exomes from 7 geographically divergent human populations from Namibia, Congo, Algeria, Pakistan, Cambodia, Siberia and Mexico. We find that individual genomes vary modestly in the overall number of predicted deleterious alleles. We show via spatially explicit simulations that the observed distribution of deleterious allele frequencies is consistent with the OOA dispersal, particularly under a model where deleterious mutations are recessive. We conclude that there is a strong signal of purifying selection at conserved genomic positions within Africa, but that many predicted deleterious mutations have evolved as if they were neutral during the expansion out of Africa. Under a model where selection is inversely related to dominance, we show that OOA populations are likely to have a higher mutation load due to increased allele frequencies of nearly neutral variants that are recessive or partially recessive.

Determining Exon Connectivity in Complex mRNAs by Nanopore Sequencing

Determining Exon Connectivity in Complex mRNAs by Nanopore Sequencing

Mohan Bolisetty, Gopinath Rajadinakaran, Brenton Graveley
doi: http://dx.doi.org/10.1101/019752

Though powerful, short-read high throughput RNA sequencing is limited in its ability to directly measure exon connectivity in mRNAs containing multiple alternative exons located farther apart than the maximum read lengths. Here, we use the Oxford Nanopore MinION™ sequencer to identify 7,899 ‘full-length’ isoforms expressed from four Drosophila genes, Dscam1, MRP, Mhc, and Rdl. These results demonstrate that nanopore sequencing can be used to deconvolute individual isoforms and that it has the potential to be an important method for comprehensive transcriptome characterization.