FindZX: an automated pipeline for detecting and visualising sex chromosomes using whole-genome sequencing data

Sex chromosomes have evolved numerous times, as revealed by recent genomic studies. However, large gaps in our knowledge of sex chromosome diversity across the tree of life remain. Filling these gaps, through the study of novel species, is crucial for improved understanding of why and how sex chromosomes evolve. Characterization of sex chromosomes in already well-studied organisms is also important to avoid misinterpretations of population genomic patterns caused by undetected sex chromosome variation. Here we present findZX, an automated Snakemake-based computational pipeline for detecting and visualizing sex chromosomes through differences in genome coverage and heterozygosity between males and females. FindZX is user-friendly and scalable to suit different computational platforms and works with any number of male and female samples. An option to perform a genome coordinate lift-over to a reference genome of another species allows users to inspect sex- linked regions over larger contiguous chromosome regions, while also providing important between- species synteny information. To demonstrate its effectiveness, we applied findZX to publicly available genomic data from species belonging to widely different taxonomic groups (mammals, birds, reptiles, fish, and insects), with sex chromosome systems of different ages, sizes, and levels of differentiation. We also demonstrate that the lift-over method is robust over large phylogenetic distances (>80 million years of evolution).

Segmentation and genome annotation algorithms for identifying chromatin state and other genomic patterns

Segmentation and genome annotation (SAGA) algorithms are widely used to understand genome activity and gene regulation. These algorithms take as input epigenomic datasets, such as chromatin immunoprecipitation-sequencing (ChIP-seq) measurements of histone modifications or transcription factor binding. They partition the genome and assign a label to each segment such that positions with the same label exhibit similar patterns of input data. SAGA algorithms discover categories of activity such as promoters, enhancers, or parts of genes without prior knowledge of known genomic elements. In this sense, they generally act in an unsupervised fashion like clustering algorithms, but with the additional simultaneous function of segmenting the genome. Here, we review the common methodological framework that underlies these methods, review variants of and improvements upon this basic framework, and discuss the outlook for future work. This review is intended for those interested in applying SAGA methods and for computational researchers interested in improving upon them.

Interactions between natural selection and recombination shape the genomic landscape of introgression

Hybridization between lineages that have not reached complete reproductive isolation appears more and more like a common phenomenon. Indeed, speciation genomics studies have now extensively shown that many species’ genomes have hybrid ancestry. However, genomic patterns of introgression are often heterogeneous across the genome. In many organisms, a positive correlation between introgression levels and recombination rate has been observed. It is usually explained by the purging of deleterious introgressed material due to incompatibilities. However, the opposite relationship was observed in a North American population of Drosophila melanogaster with admixed European and African ancestry. In order to explore how directional and epistatic selection can impact the relationship between introgression and recombination, we performed forward simulations of whole D. melanogaster genomes reflecting the North American population’s history. Our results revealed that the simplest models of positive selection often yield negative correlations between introgression and recombination such as the one observed in D. melanogaster. We also confirmed that incompatibilities tend to produce positive introgression-recombination correlations. And yet, we identify parameter space under each model where the predicted correlation is reversed. These findings deepen our understanding of the evolutionary forces that may shape patterns of ancestry across genomes, and they strengthen the foundation for future studies aimed at estimating genome-wide parameters of selection in admixed populations.

Genomic context of NTRK1/2/3 fusion-positive tumours from a large real-world population

Neurotrophic tropomyosin receptor kinase (NTRK) gene fusions are rare oncogenic drivers in solid tumours. This study aimed to interrogate a large real-world database of comprehensive genomic profiling data to describe the genomic landscape and prevalence of NTRK gene fusions. NTRK fusion-positive tumours were identified from the FoundationCORE® database of >295,000 cancer patients. We investigated the prevalence and concomitant genomic landscape of NTRK fusions, predicted patient ancestry and compared the FoundationCORE cohort with entrectinib clinical trial cohorts (ALKA-372-001 [EudraCT 2012-000148-88]; STARTRK-1 [NCT02097810]; STARTRK-2 [NCT02568267]). Overall NTRK fusion-positive tumour prevalence was 0.30% among 45 cancers with 88 unique fusion partner pairs, of which 66% were previously unreported. Across all cases, prevalence was 0.28% and 1.34% in patients aged ≥18 and <18 years, respectively; prevalence was highest in patients <5 years (2.28%). The highest prevalence of NTRK fusions was observed in salivary gland tumours (2.62%). Presence of NTRK gene fusions did not correlate with other clinically actionable biomarkers; there was no co-occurrence with known oncogenic drivers in breast, or colorectal cancer (CRC). However, in CRC, NTRK fusion-positivity was associated with spontaneous microsatellite instability (MSI); in this MSI CRC subset, mutual exclusivity with BRAF mutations was observed. NTRK fusion-positive tumour types had similar frequencies in FoundationCORE and entrectinib clinical trials. NTRK gene fusion prevalence varied greatly by age, cancer type and histology. Interrogating large datasets drives better understanding of the characteristics of very rare molecular subgroups of cancer and allows identification of genomic patterns and previously unreported fusion partners not evident in smaller datasets.

Inferring the demographic history of tetraploid species from genomic data

Genomic patterns of diversity and divergence are impacted by certain life history traits, reproductive systems and demographic history. The latter is characterised by fluctuations in population sizes over time, as well as by temporal patterns of introgression. For a given organism, identifying a demographic history that deviates from the standard neutral model allows a better understanding of its evolution, but also helps to reduce the risk of false positives when screening for molecular targets of natural selection. Tetraploid organisms and beyond have demographic histories that are complicated by the mode of polyploidisation, the mode of inheritance and different scenarios of gene flow between subgenomes and diploid parental species. Here we provide guidelines for experimenters wishing to address these issues through a flexible statistical framework: approximate Bayesian computation (ABC). The emphasis is on the general philosophy of the approach to encourage future users to exploit the enormous flexibility of ABC beyond the limitations imposed by generalist data analysis pipelines.

Demographic Inferences and Loci Under Selection in a Recently Expanded Coral Population

Coral poleward range expansions in response to warming oceans have been historically observed, however contemporary expansion rates of some coral species have become more rapid as global temperatures rise at unprecedented rates. Range expansion can lead to reduced genetic diversity and surfing of deleterious mutations in expanding populations, potentially limiting the ability for adaption and persistence in novel environments. Successful expansions that overcome these founder effects and colonize new habitat have been attributed to multiple introductions from different sources, hybridization with native populations, or rapid adaptive evolution. Here, we investigate population genomic patterns of the reef-building coral Acropora hyacinthus along a latitudinal cline that includes a well-established range expansion front in Japan using 2b-RAD sequencing. A total of 184 coral samples were collected across seven sites spanning from ~24N to near its northern range front at ~33N. We uncover the presence of three cryptic lineages of A. hyacinthus, which occupy discrete areas within this region. Only one lineage is present at the expansion front and we find evidence of its historical occupation of marginal habitats. Within this lineage we also find evidence of bottleneck pressures associated with expansion events including higher clonality, increased linkage disequilibrium, and lower genetic diversity in range edge populations compared to core populations. Asymmetric migration between populations was also detected with lower migration from edge sites. Lastly, we describe genomic signatures of local adaptation potentially attributed to lower winter temperatures experienced at the more recently expanded northern populations. Together these data illuminate the genomic consequences of range expansion in a coral and highlight how adaptation to colder temperatures along the expansion front may facilitate further range expansion in this coral lineage.

Adaptive Divergence under Gene Flow along an Environmental Gradient in Two Coexisting Stickleback Species

There is a general and solid theoretical framework to explain how the interplay between natural selection and gene flow affects local adaptation. Yet, to what extent coexisting closely related species evolve collectively or show distinctive evolutionary responses remains a fundamental question. To address this, we studied the population genetic structure and morphological differentiation of sympatric three-spined and nine-spined stickleback. We conducted genotyping-by-sequencing and morphological trait characterisation using 24 individuals of each species from four lowland brackish water (LBW), four lowland freshwater (LFW) and three upland freshwater (UFW) sites in Belgium and the Netherlands. This combination of sites allowed us to contrast populations from isolated but environmentally similar locations (LFW vs. UFW), isolated but environmentally heterogeneous locations (LBW vs. UFW), and well-connected but environmentally heterogenous locations (LBW vs. LFW). Overall, both species showed comparable levels of genetic diversity and neutral genetic differentiation. However, for all three spatial scales, signatures of morphological and genomic adaptive divergence were substantially stronger among populations of the three-spined stickleback than among populations of the nine-spined stickleback. Furthermore, most outlier SNPs in the two species were associated with local freshwater sites. The few outlier SNPs that were associated with the split between brackish water and freshwater populations were located on one linkage group in three-spined stickleback and two linkage groups in nine-spined stickleback. We conclude that while both species show congruent evolutionary and genomic patterns of divergent selection, both species differ in the magnitude of their response to selection regardless of the geographical and environmental context.