Adaptive convergence at the genomic level-prevalent, uncommon or very rare?

Shallow-water mussels (Mytilus galloprovincialis) adapt to deep-sea environment through transcriptomic and metagenomic insights

Recent studies have unveiled the deep sea as a rich biosphere, populated by species descended from shallow-water ancestors post-mass extinctions. Research on genomic evolution and microbial symbiosis has shed light on how these species thrive in extreme deep-sea conditions. However, early adaptation stages, particularly the roles of conserved genes and symbiotic microbes, remain inadequately understood. This study examined transcriptomic and microbiome changes in shallow-water mussels Mytilus galloprovincialis exposed to deep-sea conditions at the Site-F cold seep in the South China Sea. Results reveal complex gene expression adjustments in stress response, immune defense, homeostasis, and energy metabolism pathways during adaptation. After 10 days of deep-sea exposure, shallow-water mussels and their microbial communities closely resembled those of native deep-sea mussels, demonstrating host and microbiome convergence in response to adaptive shifts. Notably, methanotrophic bacteria, key symbionts in native deep-sea mussels, emerged as a dominant group in the exposed mussels. Host genes involved in immune recognition and endocytosis correlated significantly with the abundance of these bacteria. Overall, our analyses provide insights into adaptive transcriptional regulation and microbiome dynamics of mussels in deep-sea environments, highlighting the roles of conserved genes and microbial community shifts in adapting to extreme environments.

The theory of massively repeated evolution and full identifications of cancer-driving nucleotides (CDNs)

Tumorigenesis, like most complex genetic traits, is driven by the joint actions of many mutations. At the nucleotide level, such mutations are cancer-driving nucleotides (CDNs). The full sets of CDNs are necessary, and perhaps even sufficient, for the understanding and treatment of each cancer patient. Currently, only a small fraction of CDNs is known as most mutations accrued in tumors are not drivers. We now develop the theory of CDNs on the basis that cancer evolution is massively repeated in millions of individuals. Hence, any advantageous mutation should recur frequently and, conversely, any mutation that does not is either a passenger or deleterious mutation. In the TCGA cancer database (sample size n=300-1000), point mutations may recur in i out of n patients. This study explores a wide range of mutation characteristics to determine the limit of recurrences (i*) driven solely by neutral evolution. Since no neutral mutation can reach i*=3, all mutations recurring at i≥3 are CDNs. The theory shows the feasibility of identifying almost all CDNs if n increases to 100,000 for each cancer type. At present, only <10% of CDNs have been identified. When the full sets of CDNs are identified, the evolutionary mechanism of tumorigenesis in each case can be known and, importantly, gene targeted therapy will be far more effective in treatment and robust against drug resistance.

Learning from the unknown: exploring the range of bacterial functionality

Determining the repertoire of a microbe's molecular functions is a central question in microbial biology. Modern techniques achieve this goal by comparing microbial genetic material against reference databases of functionally annotated genes/proteins or known taxonomic markers such as 16S rRNA. Here, we describe a novel approach to exploring bacterial functional repertoires without reference databases. Our Fusion scheme establishes functional relationships between bacteria and assigns organisms to Fusion-taxa that differ from otherwise defined taxonomic clades. Three key findings of our work stand out. First, bacterial functional comparisons outperform marker genes in assigning taxonomic clades. Fusion profiles are also better for this task than other functional annotation schemes. Second, Fusion-taxa are robust to addition of novel organisms and are, arguably, able to capture the environment-driven bacterial diversity. Finally, our alignment-free nucleic acid-based Siamese Neural Network model, created using Fusion functions, enables finding shared functionality of very distant, possibly structurally different, microbial homologs. Our work can thus help annotate functional repertoires of bacterial organisms and further guide our understanding of microbial communities.

What Has Genomics Taught An Evolutionary Biologist?

Genomics, an interdisciplinary field of biology on the structure, function, and evolution of genomes, has revolutionized many subdisciplines of life sciences, including my field of evolutionary biology, by supplying huge data, bringing high-throughput technologies, and offering a new approach to biology. In this review, I describe what I have learned from genomics and highlight the fundamental knowledge and mechanistic insights gained. I focus on three broad topics that are central to evolutionary biology and beyond-variation, interaction, and selection-and use primarily my own research and study subjects as examples. In the next decade or two, I expect that the most important contributions of genomics to evolutionary biology will be to provide genome sequences of nearly all known species on Earth, facilitate high-throughput phenotyping of natural variants and systematically constructed mutants for mapping genotype-phenotype-fitness landscapes, and assist the determination of causality in evolutionary processes using experimental evolution.

Epigenetic and transcriptional responses underlying mangrove adaptation to UV-B

Tropical plants have adapted to strong solar ultraviolet (UV) radiation. Here we compare molecular responses of two tropical mangroves Avecennia marina and Rhizophora apiculata to high-dose UV-B. Whole-genome bisulfate sequencing indicates that high UV-B induced comparable hyper- or hypo-methylation in three sequence contexts (CG, CHG, and CHH, where H refers to A, T, or C) in A. marina but mainly CHG hypomethylation in R. apiculata. RNA and small RNA sequencing reveals UV-B induced relaxation of transposable element (TE) silencing together with up-regulation of TE-adjacent genes in R. apiculata but not in A. marina. Despite conserved upregulation of flavonoid biosynthesis and downregulation of photosynthesis genes caused by high UV-B, A. marina specifically upregulated ABC transporter and ubiquinone biosynthesis genes that are known to be protective against UV-B-induced damage. Our results point to divergent responses underlying plant UV-B adaptation at both the epigenetic and transcriptional level.

Reinventing the wheel? Reassessing the roles of gene flow, sorting and convergence in repeated evolution

Biologists have long been intrigued by apparently predictable and repetitive evolutionary trajectories inferred across a variety of lineages and systems. In recent years, high-throughput sequencing analyses have started to transform our understanding of such repetitive shifts. While researchers have traditionally categorized such shifts as either "convergent" or "parallel," based on relatedness of the lineages involved, emerging genomic insights provide an opportunity to better describe the actual evolutionary mechanisms at play. A synthesis of recent genomic analyses confirms that convergence is the predominant driver of repetitive evolution among species, whereas repeated sorting of standing variation is the major driver of repeated shifts within species. However, emerging data reveal numerous notable exceptions to these expectations, with recent examples of de novo mutations underpinning convergent shifts among even very closely related lineages, while repetitive sorting processes have occurred among even deeply divergent taxa, sometimes via introgression. A number of very recent analyses have found evidence for both processes occurring on different scales within taxa. We suggest that the relative importance of convergent versus sorting processes depends on the interplay between gene flow among populations, and phylogenetic relatedness of the lineages involved.

Genomic Convergence in the Adaptation to Extreme Environments

Convergent evolution is especially common in plants that have independently adapted to the same extreme environments (i.e., extremophile plants). The recent burst of omics data has alleviated many limitations that have hampered molecular convergence studies of non-model extremophile plants. In this review, we summarize cases of genomic convergence in these taxa to examine the extent and type of genomic convergence during the process of adaptation to extreme environments. Despite being well studied by candidate gene approaches, convergent evolution at individual sites is rare and often has a high false-positive rate when assessed in whole genomes. By contrast, genomic convergence at higher genetic levels has been detected during adaptation to the same extreme environments. Examples include the convergence of biological pathways and changes in gene expression, gene copy number, amino acid usage, and GC content. Higher convergence levels play important roles in the adaptive evolution of extremophiles and may be more frequent and involve more genes. In several cases, multiple types of convergence events have been found to co-occur. However, empirical and theoretical studies of this higher level convergent evolution are still limited. In conclusion, both the development of powerful approaches and the detection of convergence at various genetic levels are needed to further reveal the genetic mechanisms of plant adaptation to extreme environments.

Convergent adaptation of the genomes of woody plants at the land-sea interface

Sequencing multiple species that share the same ecological niche may be a new frontier for genomic studies. While such studies should shed light on molecular convergence, genomic-level analyses have been unsuccessful, due mainly to the absence of empirical controls. Woody plant species that colonized the global tropical coasts, collectively referred to as mangroves, are ideal for convergence studies. Here, we sequenced the genomes/transcriptomes of 16 species belonging in three major mangrove clades. To detect convergence in a large phylogeny, a CCS+ model is implemented, extending the more limited CCS method (convergence at conservative sites). Using the empirical control for reference, the CCS+ model reduces the noises drastically, thus permitting the identification of 73 convergent genes with P true (probability of true convergence) > 0.9. Products of the convergent genes tend to be on the plasma membrane associated with salinity tolerance. Importantly, convergence is more often manifested at a higher level than at amino-acid (AA) sites. Relative to >50 plant species, mangroves strongly prefer 4 AAs and avoid 5 others across the genome. AA substitutions between mangrove species strongly reflect these tendencies. In conclusion, the selection of taxa, the number of species and, in particular, the empirical control are all crucial for detecting genome-wide convergence. We believe this large study of mangroves is the first successful attempt at detecting genome-wide site convergence.