Comparative genomics of Glandirana rugosa using unsupervised AI reveals a high CG frequency

Sex chromosome cycle as a mechanism of stable sex determination

Recent advances in DNA sequencing technology have enabled the precise decoding of genomes in non-model organisms, providing a basis for unraveling the patterns and mechanisms of sex chromosome evolution. Studies of different species have yielded conflicting results regarding the traditional theory that sex chromosomes evolve from autosomes via the accumulation of deleterious mutations and degeneration of the Y (or W) chromosome. The concept of the 'sex chromosome cycle,' emerging from this context, posits that at any stage of the cycle (i.e., differentiation, degeneration, or loss), sex chromosome turnover can occur while maintaining stable sex determination. Thus, understanding the mechanisms that drive both the persistence and turnover of sex chromosomes at each stage of the cycle is crucial. In this review, we integrate recent findings on the mechanisms underlying maintenance and turnover, with a special focus on several organisms having unique sex chromosomes. Our review suggests that the diversity of sex chromosomes in the maintenance of stable sex determination is underappreciated and emphasizes the need for more research on the sex chromosome cycle.

Unsupervised AI reveals insect species-specific genome signatures

Insects are a highly diverse phylogeny and possess a wide variety of traits, including the presence or absence of wings and metamorphosis. These diverse traits are of great interest for studying genome evolution, and numerous comparative genomic studies have examined a wide phylogenetic range of insects. Here, we analyzed 22 insects belonging to a wide phylogenetic range (Endopterygota, Paraneoptera, Polyneoptera, Palaeoptera, and other insects) by using a batch-learning self-organizing map (BLSOM) for oligonucleotide compositions in their genomic fragments (100-kb or 1-Mb sequences), which is an unsupervised machine learning algorithm that can extract species-specific characteristics of the oligonucleotide compositions (genome signatures). The genome signature is of particular interest in terms of the mechanisms and biological significance that have caused the species-specific difference, and can be used as a powerful search needle to explore the various roles of genome sequences other than protein coding, and can be used to unveil mysteries hidden in the genome sequence. Since BLSOM is an unsupervised clustering method, the clustering of sequences was performed based on the oligonucleotide composition alone, without providing information about the species from which each fragment sequence was derived. Therefore, not only the interspecies separation, but also the intraspecies separation can be achieved. Here, we have revealed the specific genomic regions with oligonucleotide compositions distinct from the usual sequences of each insect genome, e.g., Mb-level structures found for a grasshopper Schistocerca americana. One aim of this study was to compare the genome characteristics of insects with those of vertebrates, especially humans, which are phylogenetically distant from insects. Recently, humans seem to be the "model organism" for which a large amount of information has been accumulated using a variety of cutting-edge and high-throughput technologies. Therefore, it is reasonable to use the abundant information from humans to study insect lineages. The specific regions of Mb length with distinct oligonucleotide compositions have also been previously observed in the human genome. These regions were enriched by transcription factor binding motifs (TFBSs) and hypothesized to be involved in the three-dimensional arrangement of chromosomal DNA in interphase nuclei. The present study characterized the species-specific oligonucleotide compositions (i.e., genome signatures) in insect genomes and identified specific genomic regions with distinct oligonucleotide compositions.

Highly rapid and diverse sex chromosome evolution in the Odorrana frog species complex

Sex chromosomes in poikilothermal vertebrates are characterized by rapid and diverse evolution at the species or population level. Our previous study revealed that the Taiwanese frog Odorrana swinhoana (2n = 26) has a unique system of multiple sex chromosomes created by three sequential translocations among chromosomes 1, 3, and 7. To reveal the evolutionary history of sex chromosomes in the Odorrana species complex, we first identified the original, homomorphic sex chromosomes, prior to the occurrence of translocations, in the ancestral-type population of O. swinhoana. Then, we extended the investigation to a closely related Japanese species, Odorrana utsunomiyaorum, which is distributed on two small islands. We used a high-throughput nuclear genomic approach to analyze single-nucleotide polymorphisms and identify the sex-linked markers. Those isolated from the O. swinhoana ancestral-type population were found to be aligned to chromosome 1 and showed male heterogamety. In contrast, almost all the sex-linked markers isolated from O. utsunomiyaorum were heterozygous in females and homozygous in males and were aligned to chromosome 9. Morphologically, we confirmed chromosome 9 to be heteromorphic in females, showing a ZZ-ZW sex determination system, in which the W chromosomes were heterochromatinized in a stripe pattern along the chromosome axis. These results indicated that after divergence of the two species, the ancestral homomorphic sex chromosome 1 underwent highly rapid and diverse evolution, i.e., sequential translocations with two autosomes in O. swinhoana, and turnover to chromosome 9 in O. utsunomiyaorum, with a transition from XY to ZW heterogamety and change to heteromorphy.

Comparative genomic analysis of the human genome and six bat genomes using unsupervised machine learning: Mb-level CpG and TFBS islands

Background

Emerging infectious disease-causing RNA viruses, such as the SARS-CoV-2 and Ebola viruses, are thought to rely on bats as natural reservoir hosts. Since these zoonotic viruses pose a great threat to humans, it is important to characterize the bat genome from multiple perspectives. Unsupervised machine learning methods for extracting novel information from big sequence data without prior knowledge or particular models are highly desirable for obtaining unexpected insights. We previously established a batch-learning self-organizing map (BLSOM) of the oligonucleotide composition that reveals novel genome characteristics from big sequence data.

Results

In this study, using the oligonucleotide BLSOM, we conducted a comparative genomic study of humans and six bat species. BLSOM is an explainable-type machine learning algorithm that reveals the diagnostic oligonucleotides contributing to sequence clustering (self-organization). When unsupervised machine learning reveals unexpected and/or characteristic features, these features can be studied in more detail via the much simpler and more direct standard distribution map method. Based on this combined strategy, we identified the Mb-level enrichment of CG dinucleotide (Mb-level CpG islands) around the termini of bat long-scaffold sequences. In addition, a class of CG-containing oligonucleotides were enriched in the centromeric and pericentromeric regions of human chromosomes. Oligonucleotides longer than tetranucleotides often represent binding motifs for a wide variety of proteins (e.g., transcription factor binding sequences (TFBSs)). By analyzing the penta- and hexanucleotide composition, we observed the evident enrichment of a wide range of hexanucleotide TFBSs in centromeric and pericentromeric heterochromatin regions on all human chromosomes.

Conclusion

Function of transcription factors (TFs) beyond their known regulation of gene expression (e.g., TF-mediated looping interactions between two different genomic regions) has received wide attention. The Mb-level TFBS and CpG islands are thought to be involved in the large-scale nuclear organization, such as centromere and telomere clustering. TFBSs, which are enriched in centromeric and pericentromeric heterochromatin regions, are thought to play an important role in the formation of nuclear 3D structures. Our machine learning-based analysis will help us to understand the differential features of nuclear 3D structures in the human and bat genomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08664-9.

Identification of ancestral sex chromosomes in the frog Glandirana rugosa bearing XX-XY and ZZ-ZW sex-determining systems

Sex chromosomes constantly exist in a dynamic state of evolution: rapid turnover and change of heterogametic sex during homomorphic state, and often stepping out to a heteromorphic state followed by chromosomal decaying. However, the forces driving these different trajectories of sex chromosome evolution are still unclear. The Japanese frog Glandirana rugosa is one taxon well suited to the study on these driving forces. The species has two different heteromorphic sex chromosome systems, XX-XY and ZZ-ZW, which are separated in different geographic populations. Both XX-XY and ZZ-ZW sex chromosomes are represented by chromosome 7 (2n = 26). Phylogenetically, these two systems arose via hybridization between two ancestral lineages of West Japan and East Japan populations, of which sex chromosomes are homomorphic in both sexes and to date have not yet been identified. Identification of the sex chromosomes will give us important insight into the mechanisms of sex chromosome evolution in this species. Here, we used a high-throughput genomic approach to identify the homomorphic XX-XY sex chromosomes in both ancestral populations. Sex-linked DNA markers of West Japan were aligned to chromosome 1, whereas those of East Japan were aligned to chromosome 3. These results reveal that at least two turnovers across three different sex chromosomes 1, 3 and 7 occurred during evolution of this species. This finding raises the possibility that cohabitation of the two different sex chromosomes from ancestral lineages induced turnover to another new one in their hybrids, involving transition of heterogametic sex and evolution from homomorphy to heteromorphy.

De novo assembly and analysis of the transcriptome of the Siberian wood frog Rana amurensis

The Siberian wood frog Rana amurensis Boulenger, 1886 is the most hypoxia-tolerant amphibian. It can survive for several months in an almost complete absence of oxygen. Little is known about the mechanisms of this remarkable resilience, in part because studies of amphibian genomes are impeded by their large size. To make the Siberian wood frog more amenable for genetic analysis, we performed transcriptome sequencing and de novo assembly for the R. amurensis brain under hypoxia and normoxia, as well as for the normoxic heart. In order to build a de novo transcriptome assembly of R. amurensis, we utilized 125-bp paired-end reads obtained from the brain under normoxia and hypoxia conditions, and from the heart under normoxia. In the transcriptome assembled from about 100,000,000 reads, 81.5 % of transcripts were annotated as complete, 5.3 % as fragmented, and 13.2 % as missing. We detected 59,078 known transcripts that clustered into 22,251 genes; 11,482 of them were assigned to specific GO categories. Among them, we found 6696 genes involved in protein binding, 3531 genes involved in catalytic activity, and 576 genes associated with transporter activity. A search for genes encoding receptors of the most important neurotransmitters, which may participate in the response to hypoxia, resulted in a set of expressed receptors of dopamine, serotonin, GABA, glutamate, acetylcholine, and norepinephrine. Unexpectedly, no transcripts for histamine receptors were found. The data obtained in this study create a valuable resource for studying the mechanisms of hypoxia tolerance in the Siberian wood frog, as well as for amphibian studies in general.

Pattern of Repetitive Element Transcription Segregate Cell Lineages during the Embryogenesis of Sea Urchin Strongylocentrotus purpuratus

Repetitive elements (REs) occupy a significant part of eukaryotic genomes and are shown to play diverse roles in genome regulation. During embryogenesis of the sea urchin, a large number of REs are expressed, but the role of these elements in the regulation of biological processes remains unknown. The aim of this study was to identify the RE expression at different stages of embryogenesis. REs occupied 44% of genomic DNA of Strongylocentrotus purpuratus. The most prevalent among these elements were the unknown elements-in total, they contributed 78.5% of REs (35% in total genome occupancy). It was revealed that the transcription pattern of genes and REs changes significantly during gastrulation. Using the de novo transcriptome assembly, we showed that the expression of RE is independent of its copy number in the genome. We also identified copies that are expressed. Only active RE copies were used for mapping and quantification of RE expression in the single-cell RNA sequencing data. REs expression was observed in all cell lineages and they were detected as population markers. Moreover, the primary mesenchyme cell (PMC) line had the greatest diversity of REs among the markers. Our data suggest a role for RE in the organization of developmental domains during the sea urchin embryogenesis at the single-cell resolution level.

AI for the collective analysis of a massive number of genome sequences: various examples from the small genome of pandemic SARS-CoV-2 to the human genome

In genetics and related fields, huge amounts of data, such as genome sequences, are accumulating, and the use of artificial intelligence (AI) suitable for big data analysis has become increasingly important. Unsupervised AI that can reveal novel knowledge from big data without prior knowledge or particular models is highly desirable for analyses of genome sequences, particularly for obtaining unexpected insights. We have developed a batch-learning self-organizing map (BLSOM) for oligonucleotide compositions that can reveal various novel genome characteristics. Here, we explain the data mining by the BLSOM: an unsupervised AI. As a specific target, we first selected SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) because a large number of viral genome sequences have been accumulated via worldwide efforts. We analyzed more than 0.6 million sequences collected primarily in the first year of the pandemic. BLSOMs for short oligonucleotides (e.g., 4-6-mers) allowed separation into known clades, but longer oligonucleotides further increased the separation ability and revealed subgrouping within known clades. In the case of 15-mers, there is mostly one copy in the genome; thus, 15-mers that appeared after the epidemic started could be connected to mutations, and the BLSOM for 15-mers revealed the mutations that contributed to separation into known clades and their subgroups. After introducing the detailed methodological strategies, we explain BLSOMs for various topics, such as the tetranucleotide BLSOM for over 5 million 5-kb fragment sequences derived from almost all microorganisms currently available and its use in metagenome studies. We also explain BLSOMs for various eukaryotes, including fishes, frogs and Drosophila species, and found a high separation ability among closely related species. When analyzing the human genome, we found enrichments in transcription factor-binding sequences in centromeric and pericentromeric heterochromatin regions. The tDNAs (tRNA genes) could be separated according to their corresponding amino acid.