Genomics of Gene Gain and Gene Loss in Eukaryotes

Evolution has often been perceived as a process driving species toward greater complexity at both biological (organismal) and genomic level. However, this view has repeatedly been challenged through writings of authors like Stephen J. Gould and Eugene V. Koonin, rendering the current evidence inadequate for any strong, trend-like (progressive in particular) claims. The current state of this problem is an agreement that despite the diversity of individual case-study evidence, it is still difficult to make any unequivocal conclusion regarding patterns and trends associated to complexity changes without a sufficiently accurate evolutionary reconstruction of ancestral genomes across numerous evolutionary lineages. Such reconstruction in return would provide valuable source of information regarding the change in the number of genes as a function of time and serve as an adequate proxy for monitoring genomic and consequently organismal complexity patterns. Here I propose a novel method for ancestral genome reconstruction in terms of gene families, revealing a consistent, across all investigated lineages, bell-shaped pattern of change in genomic complexity, with complexity periodically increasing throughout Proterozoic eon, followed by a more systematic decrease prevailing the Phanerozoic. Moreover, a global inverse relationship between gain and loss of gene families appears to be a general rule. Furthermore, some evolutionary periods exhibit specific profiles with exceptionally high gene family gain (or loss) rates coinciding with known key evolutionary transition events

SFQ: Constructing and Querying a Succinct Representation of FASTQ Files

A large and ever increasing quantity of high throughput sequencing (HTS) data is stored in FASTQ files. Various methods for data compression are used to mitigate the storage and transmission costs, from the still prevalent general purpose Gzip to state-of-the-art specialized methods. However, all of the existing methods for FASTQ file compression require the decompression stage before the HTS data can be used. This is particularly costly with the random access to specific records in FASTQ files. We propose the sFASTQ format, a succinct representation of FASTQ files that can be used without decompression (i.e., the records can be retrieved and listed online), and that supports random access to individual records. The sFASTQ format can be searched on the disk, which eliminates the need for any additional memory resources. The searchable sFASTQ archive is of comparable size to the corresponding Gzip file. sFASTQ format outputs (interleaved) FASTQ records to the STDOUT stream. We provide SFQ, a software for the construction and usage of the sFASTQ format that supports variable length reads, pairing of records, and both lossless and lossy compression of quality scores

Comparable genomic copy number aberrations differ across astrocytoma malignancy grades

A collection of intracranial astrocytomas of different malignancy grades was analyzed for copy number aberrations (CNA) in order to identify regions that are driving cancer pathogenesis. Astrocytomas were analyzed by Array Comparative Genomic Hybridization (aCGH) and bioinformatics utilizing a Bioconductor package, Genomic Identification of Significant Targets in Cancer (GISTIC) 2.0.23 and DAVID software. Altogether, 1438 CNA were found of which losses prevailed. On our total sample, significant deletions affected 14 chromosomal regions, out of which deletions at 17p13.2, 9p21.3, 13q12.11, 22q12.3 remained significant even at 0.05 q-value. When divided into malignancy groups, the regions identified as significantly deleted in high grades were: 9p21.3; 17p13.2; 10q24.2; 14q21.3; 1p36.11 and 13q12.11, while amplified were: 3q28; 12q13.3 and 21q22.3. Low grades comprised significant deletions at 3p14.3; 11p15.4; 15q15.1; 16q22.1; 20q11.22 and 22q12.3 indicating their involvement in early stages of tumorigenesis. Significantly enriched pathways were: PI3K-Akt, Cytokine-cytokine receptor, the nucleotide-binding oligomerization domain (NOD)–like receptor, Jak-STAT, retinoic acid-inducible gene (RIG)-I-like receptor and Toll-like receptor pathways. HPV and herpex simplex infection and inflammation pathways were also represented. The present study brings new data to astrocytoma research amplifying the wide spectrum of changes that could help us identify the regions critical for tumorigenesis

No Evidence for Phylostratigraphic Bias Impacting Inferences on Patterns of Gene Emergence and Evolution

Phylostratigraphy is a computational framework for dating the emergence of DNA and protein sequences in a phylogeny. It has been extensively applied to make inferences on patterns of genome evolution, including patterns of disease gene evolution, ontogeny and de novo gene origination. Phylostratigraphy typically relies on BLAST searches along a species tree, but new simulation studies have raised concerns about the ability of BLAST to detect remote homologues and its impact on phylostratigraphic inferences. Here, we re-assessed these simulations. We found that, even with a possible overall BLAST false negative rate between 11–15%, the large majority of sequences assigned to a recent evolutionary origin by phylostratigraphy is unaffected by technical concerns about BLAST. Where the results of the simulations did cast doubt on previously reported findings, we repeated the original analyses but now excluded all questionable sequences. The originally described patterns remained essentially unchanged. These new analyses strongly support phylostratigraphic inferences, including: genes that emerged after the origin of eukaryotes are more likely to be expressed in the ectoderm than in the endoderm or mesoderm in Drosophila, and the de novo emergence of protein-coding genes from non-genic sequences occurs through proto-gene intermediates in yeast. We conclude that BLAST is an appropriate and sufficiently sensitive tool in phylostratigraphic analysis that does not appear to introduce significant biases into evolutionary pattern inferences.We thank the following funding organizations for support of our work: TD-L: City of Zagreb and Adris Foundation grants; A-RC: National Institute of Health (NIH) grant K99 GM108865; MA: grant BFU2015-65235-P from MINECO/FEDER, EU; DT: ERC grant NewGenes, 322564

No Evidence for Phylostratigraphic Bias Impacting Inferences on Patterns of Gene Emergence and Evolution

Phylostratigraphy is a computational framework for dating the emergence of DNA and protein sequences in a phylogeny. It has been extensively applied to make inferences on patterns of genome evolution, including patterns of disease gene evolution, ontogeny and de novo gene origination. Phylostratigraphy typically relies on BLAST searches along a species tree, but new simulation studies have raised concerns about the ability of BLAST to detect remote homologues and its impact on phylostratigraphic inferences. Here, we re-assessed these simulations. We found that, even with a possible overall BLAST false negative rate between 11–15%, the large majority of sequences assigned to a recent evolutionary origin by phylostratigraphy is unaffected by technical concerns about BLAST. Where the results of the simulations did cast doubt on previously reported findings, we repeated the original analyses but now excluded all questionable sequences. The originally described patterns remained essentially unchanged. These new analyses strongly support phylostratigraphic inferences, including: genes that emerged after the origin of eukaryotes are more likely to be expressed in the ectoderm than in the endoderm or mesoderm in Drosophila, and the de novo emergence of protein-coding genes from non-genic sequences occurs through proto-gene intermediates in yeast. We conclude that BLAST is an appropriate and sufficiently sensitive tool in phylostratigraphic analysis that does not appear to introduce significant biases into evolutionary pattern inferences.We thank the following funding organizations for support of our work: TD-L: City of Zagreb and Adris Foundation grants; A-RC: National Institute of Health (NIH) grant K99 GM108865; MA: grant BFU2015-65235-P from MINECO/FEDER, EU; DT: ERC grant NewGenes, 322564

Defining connectivity of exploited octopus and shrimp populations across the Mediterranean

Fourth International Marine Connectivity (iMarCo) Conference, 8-9 October 2018, Crete, Greece.-- 1 pageIn this era of fast global change, defining connectivity and adaptive potential of exploited marine stocks is a key requirement towards sustainability of fisheries. Though the use of genetics tools is not very pervasive in fisheries management, evolutionary concepts that derive from its use provide the much needed information regarding stock structure and its adaptation capacity. In our study, we examine the integration of evolutionary-based knowledge in fisheries sustainable management and conservation of two target species: common octopus, Octopus vulgaris and red shrimp Aristeus antennatus. To that end, we sampled 19 octopus and 12 red shrimp populations across the Mediterranean. Populations were genotyped using genotyping by sequencing (GBS) approach and a number of polymorphic genetic markers (SNPs) was validated for each species and population. In order to assess stock structure, genetic differentiation among populations was estimated with F-statistics and patterns of genomic variation across spatial scales were obtained, providing evidence of connectivity. To investigate occurrences of local adaptation, the data set was tested for evolution under selection. Here we provide high resolution perspective on stock structure, connectivity and local adaptation of octopus and red shrimp in the Mediterranean and indicate fishery areas that are critical to preserve, contributing directly to the sustainable management of Mediterranean fishery populationsPeer Reviewe

The Gonium pectorale genome demonstrates co-option of cell cycle regulation during the evolution of multicellularity

The transition to multicellularity has occurred numerous times in all domains of life, yet its initial steps are poorly understood. The volvocine green algae are a tractable system for understanding the genetic basis of multicellularity including the initial formation of cooperative cell groups. Here we report the genome sequence of the undifferentiated colonial alga, Gonium pectorale, where group formation evolved by co-option of the retinoblastoma cell cycle regulatory pathway. Significantly, expression of the Gonium retinoblastoma cell cycle regulator in unicellular Chlamydomonas causes it to become colonial. The presence of these changes in undifferentiated Gonium indicates extensive group-level adaptation during the initial step in the evolution of multicellularity. These results emphasize an early and formative step in the evolution of multicellularity, the evolution of cell cycle regulation, one that may shed light on the evolutionary history of other multicellular innovations and evolutionary transitions