An investigation into inter- and intragenomic variations of graphic genomic signatures

We provide, on an extensive dataset and using several different distances, confirmation of the hypothesis that CGR patterns are preserved along a genomic DNA sequence, and are different for DNA sequences originating from genomes of different species. This finding lends support to the theory that CGRs of genomic sequences can act as graphic genomic signatures. In particular, we compare the CGR patterns of over five hundred different 150,000 bp genomic sequences originating from the genomes of six organisms, each belonging to one of the kingdoms of life: H. sapiens, S. cerevisiae, A. thaliana, P. falciparum, E. coli, and P. furiosus. We also provide preliminary evidence of this method's applicability to closely related species by comparing H. sapiens (chromosome 21) sequences and over one hundred and fifty genomic sequences, also 150,000 bp long, from P. troglodytes (Animalia; chromosome Y), for a total length of more than 101 million basepairs analyzed. We compute pairwise distances between CGRs of these genomic sequences using six different distances, and construct Molecular Distance Maps that visualize all sequences as points in a two-dimensional or three-dimensional space, to simultaneously display their interrelationships. Our analysis confirms that CGR patterns of DNA sequences from the same genome are in general quantitatively similar, while being different for DNA sequences from genomes of different species. Our analysis of the performance of the assessed distances uses three different quality measures and suggests that several distances outperform the Euclidean distance, which has so far been almost exclusively used for such studies. In particular we show that, for this dataset, DSSIM (Structural Dissimilarity Index) and the descriptor distance (introduced here) are best able to classify genomic sequences.Comment: 14 pages, 6 figures, 5 table

Molecular Distance Maps: An alignment-free computational tool for analyzing and visualizing DNA sequences\u27 interrelationships

In an attempt to identify and classify species based on genetic evidence, we propose a novel combination of methods to quantify and visualize the interrelationships between thousand of species. This is possible by using Chaos Game Representation (CGR) of DNA sequences to compute genomic signatures which we then compare by computing pairwise distances. In the last step, the original DNA sequences are embedded in a high dimensional space using Multi-Dimensional Scaling (MDS) before everything is projected on a Euclidean 3D space. To start with, we apply this method to a mitochondrial DNA dataset from NCBI containing over 3,000 species. The analysis shows that the oligomer composition of full mtDNA sequences can be a source of taxonomic information, suggesting that this method could be used for unclassified species and taxonomic controversies. Next, we test the hypothesis that CGR-based genomic signature is preserved along a species\u27 genome by comparing inter- and intra-genomic signatures of nuclear DNA sequences from six different organisms, one from each kingdom of life. We also compare six different distances and we assess their performance using statistical measures. Our results support the existence of a genomic signature for a species\u27 genome at the kingdom level. In addition, we test whether CGR-based genomic signatures originating only from nuclear DNA can be used to distinguish between closely-related species and we answer in the negative. To overcome this limitation, we propose the concept of ``composite signatures\u27\u27 which combine information from different types of DNA and we show that they can effectively distinguish all closely-related species under consideration. We also propose the concept of ``assembled signatures\u27\u27 which, among other advantages, do not require a long contiguous DNA sequence but can be built from smaller ones consisting of ~100-300 base pairs. Finally, we design an interactive webtool MoDMaps3D for building three-dimensional Molecular Distance Maps. The user can explore an already existing map or build his/her own using NCBI\u27s accession numbers as input. MoDMaps3D is platform independent, written in Javascript and can run in all major modern browsers

Winter moth adaptation to climate change:Genetic changes in thermal plasticity of embryonic development rate

Timing of winter moth egg hatching shows rapid genetic adaptation to climate change. The reaction norm of egg development rate versus temperature has shifted up compared to 10 years ago. This later hatching for a given temperature has led to a better match with timing of their food source, young oak leaves. To identify the genes underlying the genetic adaptation of winter moth egg hatching, we used an evo-eco-devo approach: eggs collected from the field were used in a split-brood experiment. At different times during development, we measured embryonic development in, and obtained transcriptomes of, eggs before and after transfer to a colder or warmer temperature compared to a baseline. Stages of embryonic development in the winter moth were determined by imagining eggs using epifluorescence microscopy. These images were then used to map the thermal sensitivity of winter moth embryonic development over time, enabling us to focus on the transcriptomes taken during thermally sensitive stages of development. Ultimately, we aim to compare the genes identified this way with genes that show changes in allele frequency over the past 20 years, using our DNA record of four natural populations that adapted to climate change. As winter moths are one of the few species showing genetic adaptation under climate change, this study of winter moth embryonic development can advance our understanding of the genetic basis of adaptive evolutionary change in a natural population

Winter moth adaptation to climate change:Genetic changes in thermal plasticity of embryonic development rate

Timing of winter moth egg hatching shows rapid genetic adaptation to climate change. The reaction norm of egg development rate versus temperature has shifted up compared to 10 years ago. This later hatching for a given temperature has led to a better match with timing of their food source, young oak leaves. To identify the genes underlying the genetic adaptation of winter moth egg hatching, we used an evo-eco-devo approach: eggs collected from the field were used in a split-brood experiment. At different times during development, we measured embryonic development in, and obtained transcriptomes of, eggs before and after transfer to a colder or warmer temperature compared to a baseline. Stages of embryonic development in the winter moth were determined by imagining eggs using epifluorescence microscopy. These images were then used to map the thermal sensitivity of winter moth embryonic development over time, enabling us to focus on the transcriptomes taken during thermally sensitive stages of development. Ultimately, we aim to compare the genes identified this way with genes that show changes in allele frequency over the past 20 years, using our DNA record of four natural populations that adapted to climate change. As winter moths are one of the few species showing genetic adaptation under climate change, this study of winter moth embryonic development can advance our understanding of the genetic basis of adaptive evolutionary change in a natural population