4,092 research outputs found
Counting, Generating, Analyzing and Sampling Tree Alignments
Pairwise ordered tree alignment are combinatorial objects that appear unimportant applications, such as RNA secondary structure comparison. However, the usual representation of tree alignments as supertrees is ambiguous, i.e. two distinct supertrees may induce identical sets of matches between identical pairs of trees. This ambiguity is uninformative, and detrimental to any probabilistic analysis. In this work, we consider tree alignments up to equivalence. Our first result is a precise asymptotic enumeration of tree alignments, obtained from a context-free grammar by mean of basic analytic combinatorics. Our second result focuses on alignments between two given ordered trees SS and TT. By refining our grammar to align specific trees, we obtain a decomposition scheme for the space of alignments, and use it to design an efficient dynamic programming algorithm for sampling alignments under the Gibbs-Boltzmann probability distribution. This generalizes existing tree alignment algorithms, and opens the door for a probabilistic analysis of the space of suboptimal alignments
Topological network alignment uncovers biological function and phylogeny
Sequence comparison and alignment has had an enormous impact on our
understanding of evolution, biology, and disease. Comparison and alignment of
biological networks will likely have a similar impact. Existing network
alignments use information external to the networks, such as sequence, because
no good algorithm for purely topological alignment has yet been devised. In
this paper, we present a novel algorithm based solely on network topology, that
can be used to align any two networks. We apply it to biological networks to
produce by far the most complete topological alignments of biological networks
to date. We demonstrate that both species phylogeny and detailed biological
function of individual proteins can be extracted from our alignments.
Topology-based alignments have the potential to provide a completely new,
independent source of phylogenetic information. Our alignment of the
protein-protein interaction networks of two very different species--yeast and
human--indicate that even distant species share a surprising amount of network
topology with each other, suggesting broad similarities in internal cellular
wiring across all life on Earth.Comment: Algorithm explained in more details. Additional analysis adde
Chromosomal-level assembly of the Asian Seabass genome using long sequence reads and multi-layered scaffolding
We report here the ~670 Mb genome assembly of the Asian seabass (Lates calcarifer), a tropical marine teleost. We used long-read sequencing augmented by transcriptomics, optical and genetic mapping along with shared synteny from closely related fish species to derive a chromosome-level assembly with a contig N50 size over 1 Mb and scaffold N50 size over 25 Mb that span ~90% of the genome. The population structure of L. calcarifer species complex was analyzed by re-sequencing 61 individuals representing various regions across the species' native range. SNP analyses identified high levels of genetic diversity and confirmed earlier indications of a population stratification comprising three clades with signs of admixture apparent in the South-East Asian population. The quality of the Asian seabass genome assembly far exceeds that of any other fish species, and will serve as a new standard for fish genomics
Aligning Multiple Sequences with Genetic Algorithm
The alignment of biological sequences is a crucial
tool in molecular biology and genome analysis. It helps to build
a phylogenetic tree of related DNA sequences and also to predict
the function and structure of unknown protein sequences by
aligning with other sequences whose function and structure is
already known. However, finding an optimal multiple sequence
alignment takes time and space exponential with the length or
number of sequences increases. Genetic Algorithms (GAs) are
strategies of random searching that optimize an objective
function which is a measure of alignment quality (distance) and
has the ability for exploratory search through the solution space
and exploitation of current results
A single polyploidization event at the origin of the tetraploid genome of Coffea arabica is responsible for the extremely low genetic variation in wild and cultivated germplasm
The genome of the allotetraploid species Coffea arabica L. was sequenced to assemble independently the two component subgenomes (putatively deriving from C. canephora and C. eugenioides) and to perform a genome-wide analysis of the genetic diversity in cultivated coffee germplasm and in wild populations growing in the center of origin of the species. We assembled a total length of 1.536 Gbp, 444 Mb and 527 Mb of which were assigned to the canephora and eugenioides subgenomes, respectively, and predicted 46,562 gene models, 21,254 and 22,888 of which were assigned to the canephora and to the eugeniodes subgenome, respectively. Through a genome-wide SNP genotyping of 736 C. arabica accessions, we analyzed the genetic diversity in the species and its relationship with geographic distribution and historical records. We observed a weak population structure due to low-frequency derived alleles and highly negative values of Taijma's D, suggesting a recent and severe bottleneck, most likely resulting from a single event of polyploidization, not only for the cultivated germplasm but also for the entire species. This conclusion is strongly supported by forward simulations of mutation accumulation. However, PCA revealed a cline of genetic diversity reflecting a west-to-east geographical distribution from the center of origin in East Africa to the Arabian Peninsula. The extremely low levels of variation observed in the species, as a consequence of the polyploidization event, make the exploitation of diversity within the species for breeding purposes less interesting than in most crop species and stress the need for introgression of new variability from the diploid progenitors
Quantifying evolutionary constraints on B cell affinity maturation
The antibody repertoire of each individual is continuously updated by the
evolutionary process of B cell receptor mutation and selection. It has recently
become possible to gain detailed information concerning this process through
high-throughput sequencing. Here, we develop modern statistical molecular
evolution methods for the analysis of B cell sequence data, and then apply them
to a very deep short-read data set of B cell receptors. We find that the
substitution process is conserved across individuals but varies significantly
across gene segments. We investigate selection on B cell receptors using a
novel method that side-steps the difficulties encountered by previous work in
differentiating between selection and motif-driven mutation; this is done
through stochastic mapping and empirical Bayes estimators that compare the
evolution of in-frame and out-of-frame rearrangements. We use this new method
to derive a per-residue map of selection, which provides a more nuanced view of
the constraints on framework and variable regions.Comment: Previously entitled "Substitution and site-specific selection driving
B cell affinity maturation is consistent across individuals
The EM Algorithm and the Rise of Computational Biology
In the past decade computational biology has grown from a cottage industry
with a handful of researchers to an attractive interdisciplinary field,
catching the attention and imagination of many quantitatively-minded
scientists. Of interest to us is the key role played by the EM algorithm during
this transformation. We survey the use of the EM algorithm in a few important
computational biology problems surrounding the "central dogma"; of molecular
biology: from DNA to RNA and then to proteins. Topics of this article include
sequence motif discovery, protein sequence alignment, population genetics,
evolutionary models and mRNA expression microarray data analysis.Comment: Published in at http://dx.doi.org/10.1214/09-STS312 the Statistical
Science (http://www.imstat.org/sts/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Analysis of Sequence Conservation at Nucleotide Resolution
One of the major goals of comparative genomics is to understand the evolutionary history of each nucleotide in the human genome sequence, and the degree to which it is under selective pressure. Ascertainment of selective constraint at nucleotide resolution is particularly important for predicting the functional significance of human genetic variation and for analyzing the sequence substructure of cis-regulatory sequences and other functional elements. Current methods for analysis of sequence conservation are focused on delineation of conserved regions comprising tens or even hundreds of consecutive nucleotides. We therefore developed a novel computational approach designed specifically for scoring evolutionary conservation at individual base-pair resolution. Our approach estimates the rate at which each nucleotide position is evolving, computes the probability of neutrality given this rate estimate, and summarizes the result in a Sequence CONservation Evaluation (SCONE) score. We computed SCONE scores in a continuous fashion across 1% of the human genome for which high-quality sequence information from up to 23 genomes are available. We show that SCONE scores are clearly correlated with the allele frequency of human polymorphisms in both coding and noncoding regions. We find that the majority of noncoding conserved nucleotides lie outside of longer conserved elements predicted by other conservation analyses, and are experiencing ongoing selection in modern humans as evident from the allele frequency spectrum of human polymorphism. We also applied SCONE to analyze the distribution of conserved nucleotides within functional regions. These regions are markedly enriched in individually conserved positions and short (<15 bp) conserved “chunks.” Our results collectively suggest that the majority of functionally important noncoding conserved positions are highly fragmented and reside outside of canonically defined long conserved noncoding sequences. A small subset of these fragmented positions may be identified with high confidence
Chromosomal-level assembly of the Asian seabass genome using long sequence reads and multi-layered scaffolding
We report here the ~670 Mb genome assembly of the Asian seabass (Lates calcarifer), a
tropical marine teleost. We used long-read sequencing augmented by transcriptomics, optical
and genetic mapping along with shared synteny from closely related fish species to
derive a chromosome-level assembly with a contig N50 size over 1 Mb and scaffold N50
size over 25 Mb that span ~90% of the genome. The population structure of L. calcarifer species complex was analyzed by re-sequencing 61 individuals representing various
regions across the species’ native range. SNP analyses identified high levels of genetic
diversity and confirmed earlier indications of a population stratification comprising three
clades with signs of admixture apparent in the South-East Asian population. The quality of
the Asian seabass genome assembly far exceeds that of any other fish species, and will
serve as a new standard for fish genomics.Web of Scienc
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