Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.

The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Background
Multiple genome alignment remains a challenging problem. Effects of recombination including rearrangement, segmental duplication, gain, and loss can create a mosaic pattern of homology even among closely related organisms.

https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0011147&type=printable

progressiveMauve: Multiple Genome Alignment with Gene Gain, Loss and Rearrangement

We present version 6 of the DNA Sequence Polymorphism (DnaSP) software, a new version of the popular tool for performing exhaustive population genetic analyses on multiple sequence alignments. This major upgrade incorporates novel functionalities to analyze large data sets, such as those generated by high-throughput sequencing technologies. Among other features, DnaSP 6 implements: 1) modules for reading and analyzing data from genomic partitioning methods, such as RADseq or hybrid enrichment approaches, 2) faster methods scalable for high-throughput sequencing data, and 3) summary statistics for the analysis of multi-locus population genetics data. Furthermore, DnaSP 6 includes novel modules to perform single- and multi-locus coalescent simulations under a wide range of demographic scenarios. The DnaSP 6 program, with extensive documentation, is freely available at http://www.ub.edu/dnasp.

/pdf/dnasp-6-dna-sequence-polymorphism-analysis-of-large-data-33lszalous.pdf

DnaSP 6: DNA Sequence Polymorphism Analysis of Large Data Sets.

Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement neighbor-joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest-neighbor interchanges to reduce the length of the tree. For an alignment with N sequences, L sites, and a different characters, a distance matrix requires O(N^2) space and O(N^2 L) time, but FastTree requires just O( NLa + N sqrt(N) ) memory and O( N sqrt(N) log(N) L a ) time. To estimate the tree's reliability, FastTree uses local bootstrapping, which gives another 100-fold speedup over a distance matrix. For example, FastTree computed a tree and support values for 158,022 distinct 16S ribosomal RNAs in 17 hours and 2.4 gigabytes of memory. Just computing pairwise Jukes-Cantor distances and storing them, without inferring a tree or bootstrapping, would require 17 hours and 50 gigabytes of memory. In simulations, FastTree was slightly more accurate than neighbor joining, BIONJ, or FastME; on genuine alignments, FastTree's topologies had higher likelihoods. FastTree is available at http://microbesonline.org/fasttree.

/pdf/fast-tree-computing-large-minimum-evolution-trees-with-4grq0gwfpy.pdf

Fast Tree: Computing Large Minimum-Evolution Trees with Profiles instead of a Distance Matrix

Evolutionary relationships between species are traditionally represented in the form of a tree, called the species tree. The reconstruction of the species tree from molecular data is hindered by frequent conflicts between gene genealogies. A standard way of dealing with this issue is to pos-tulate the existence of a unique species tree where disagreements between gene trees are explained by incomplete lineage sorting (ILS) due to random coalescences of gene lineages inside the edges of the species tree. This paradigm, known as the multi-species coalescent (MSC), is constantly violated by the ubiquitous presence of gene flow revealed by empirical studies, leading to topological incon-gruences of gene trees that cannot be explained by ILS alone. Here we argue that this paradigm should be revised in favor of a vision acknowledging the importance of gene flow and where gene histories shape the species tree rather than the opposite. We propose a new, plastic framework for modeling the joint evolution of gene and species lineages relaxing the hierarchy between the species tree and gene trees. As an illustration, we implement this framework in a mathematical model called the genomic diversification (GD) model based on coalescent theory, with four parameters tuning repli-cation, genetic differentiation, gene flow and reproductive isolation. We use it to evaluate the amount of gene flow in two empirical data-sets. We find that in these data-sets, gene tree distributions are better explained by the best fitting GD model than by the best fitting MSC model. This work should pave the way for approaches of diversification using the richer signal contained in genomic evolution-ary histories rather than in the mere species tree.

/pdf/the-genomic-view-of-diversification-3qs2xijw9h.pdf

The genomic view of diversification

Contiguous assemblies are fundamental to decipher the exact composition of extant genomes. In molluscs, this task is considerably challenging owing to their large size, heterozygosity, and widespread content of repetitive content. Consequently, the usage of long-read sequencing technologies is fundamental to achieve high contiguity and quality. The first genome assembly of Margaritifera margaritifera (Linnaeus, 1758) (Mollusca: Bivalvia: Unionida), a culturally relevant, widespread, and highly threatened species of freshwater mussels, has been produced recently. However, the current genome is highly fragmented since the assembly relied solely on short-read approaches. To overcome this caveat, here, a new improved reference genome assembly is produced using a combination of PacBio CLR long reads and Illumina paired-end short reads. This novel genome assembly is 2.4 Gb long, organized into 1,700 scaffolds with a contig N50 length of 3.4Mbp. The ab initio gene prediction resulted in a total of 48,314 protein-coding genes. This new assembly represents a substantial improvement and is an essential resource for studying this species’ unique biological and evolutionary features that ultimately will help to promote its conservation.

/pdf/the-crown-pearl-v2-an-improved-genome-assembly-of-the-3ayremy8.pdf

The Crown Pearl V2: an improved genome assembly of the European freshwater pearl mussel Margaritifera margaritifera (Linnaeus, 1758)

This paper gives a new flavor of what Peter Jagers and his co-authors call `the path to extinction'. In a neutral population with constant size $N$, we assume that each individual at time $0$ carries a distinct type, or allele. We consider the joint dynamics of these $N$ alleles, for example the dynamics of their respective frequencies and more plainly the nonincreasing process counting the number of alleles remaining by time $t$. We call this process the extinction process. We show that in the Moran model, the extinction process is distributed as the process counting (in backward time) the number of common ancestors to the whole population, also known as the block counting process of the $N$-Kingman coalescent. Stimulated by this result, we investigate: (1) whether it extends to an identity between the frequencies of blocks in the Kingman coalescent and the frequencies of alleles in the extinction process, both evaluated at jump times; (2) whether it extends to the general case of $\Lambda$-Fleming-Viot processes.

/pdf/the-sequential-loss-of-allelic-diversity-ut0zuuagek.pdf

The sequential loss of allelic diversity

Genotypic fitness landscapes are constructed by assessing the fitness of all possible combinations of a given number of mutations. In the last years, several experimental fitness landscapes have been completely resolved. As fitness landscapes are high-dimensional, their characterization relies on simple measures of their structure, which can be used as statistics in empirical applications. Here we propose two new sets of measures that explicitly capture two relevant features of fitness landscapes: epistasis and constraints. The first set contains new measures for epistasis based on the correlation of fitness effects of mutations. They have a natural interpretation, capture well the interaction between mutations, can be obtained analytically for most landscape models and can therefore be used to discriminate between different models. The second set contains measures of evolutionary constraints based on "chains" of forced mutations along fitness-increasing paths. Some of these measures are non-monotonic in the amount of epistatic interactions, but have instead a maximum for intermediate values. We further characterize the relationships of these measures to the ones that were previous proposed (e.g. number of peaks, roughness/slope, fraction of non-additive components, etc). Finally, we show how these measures can help uncovering the amount and the nature of epistatic interactions in two experimental landscapes.

/pdf/epistasis-and-constraints-in-fitness-landscapes-3lyails7lt.pdf

Epistasis and constraints in fitness landscapes

/pdf/the-sequential-loss-of-allelic-diversity-4uxo2p2h3z.pdf

Guillaume Achaz

Papers

The genomic view of diversification

The Crown Pearl V2: an improved genome assembly of the European freshwater pearl mussel Margaritifera margaritifera (Linnaeus, 1758)

The sequential loss of allelic diversity

Epistasis and constraints in fitness landscapes

The sequential loss of allelic diversity