Biology subjects

Rick, J. A.

Publications and source records attributed to Rick, J. A..

5 recordsLinked to original sources

bioRxiv2026

BLink-seq delivers population-scale haplotypes without long reads: a scalable framework for non-model genomics

Information about segregating haplotypes and structural variation (SV) can be extremely rich for a variety of applications in population genomics but remains largely inaccessible for many non-model species. Of the available methods, linked-read sequencing is especially promising for its low cost and scalability, but its adoption remains limited. One existing linked-read method is Haplotagging, which barcodes sequencing reads to reconstruct long molecules that encode haplotype information, with the potential to generate phased whole-genome data and detect structural variants. In this study, we present BLink-seq, a novel Haplotagging method that is compatible with standard short-read next-generation sequencing platforms, is locally reproducible with low-cost reagents, and is scalable for high-throughput sample processing. We optimized library preparation parameters, explored their relationship to linked-read library metrics, and validated phasing performance and structural variant detection in two evolutionary extremes: an experimental Drosophila melanogaster cross of inbred lines carrying known inversions, and four Atlantic silverside (Menidia menidia) parent-offspring trios sourced from highly outbred, wild-caught populations. We then applied our protocol to a cohort of 376 silversides to demonstrate its scalability and potential for SV detection and genotype imputation. Using BLink-seq, we generated chromosome-scale phased blocks and identified known inversions in both validation datasets. We discovered previously uncharacterized structural complexity within a known adaptive inversion on silverside chromosome 11, demonstrating that linked-read data can refine our understanding of SV architecture beyond what short reads alone can resolve. Finally, we provide a user guide for researchers interested in using BLink-seq.

genomics↗

bioRxiv2025

Admixture and environmental fluctuations shape the evolutionary history of a predator radiation in East Africa's Lake Tanganyika

Top predators have oversized influence on food webs and ecosystem dynamics, and introducing a novel predator to a naive environment can have dramatic consequences for endemic biodiversity. Using genomic data, we find that the colonization of Lake Tanganyika by Lates fishes--the top predators in this ancient lake--occurred more recently than other diverse clades within the lake. Diversification into four endemic Lates species occurred within the lake during a time of dramatic changes in lake levels driven by glacial-interglacial cycles, supporting the hypothesis that these fluctuations were a "species pump" for lacustrine taxa. These lake level fluctuations also likely contributed to multiple admixture events among Lates species during the Pleistocene ([~] 90-500 Kya). Together, our findings suggest a dynamic and environmentally-linked evolutionary history of this predator radiation, and that their colonization of the lake and subsequent diversification likely had dramatic ecosystem consequences for taxa already present in Lake Tanganyika.

evolutionary biology↗

bioRxiv2022

Reference genome choice and filtering thresholds jointly influence phylogenomic analyses

AO_SCPLOWBSTRACTC_SCPLOWMolecular phylogenies are a cornerstone of modern comparative biology and are commonly employed to investigate a range of biological phenomena, such as diversification rates, patterns in trait evolution, biogeography, and community assembly. Recent work has demonstrated that significant biases may be introduced into downstream phylogenetic analyses from processing genomic data; however, it remains unclear whether there are interactions among bioinformatic parameters or biases introduced through the choice of reference genome for sequence alignment and variant-calling. We address these knowledge gaps by employing a combination of simulated and empirical data sets to investigate to what extent the choice of reference genome in upstream bioinformatic processing of genomic data influences phylogenetic inference, as well as the way that reference genome choice interacts with bioinformatic filtering choices and phylogenetic inference method. We demonstrate that more stringent minor allele filters bias inferred trees away from the true species tree topology, and that these biased trees tend to be more imbalanced and have a higher center of gravity than the true trees. We find greatest topological accuracy when filtering sites for minor allele count >3-4 in our 51-taxa data sets, while tree center of gravity was closest to the true value when filtering for sites with minor allele count >1-2. In contrast, filtering for missing data increased accuracy in the inferred topologies; however, this effect was small in comparison to the effect of minor allele filters and may be undesirable due to a subsequent mutation spectrum distortion. The bias introduced by these filters differs based on the reference genome used in short read alignment, providing further support that choosing a reference genome for alignment is an important bioinformatic decision with implications for downstream analyses. These results demonstrate that attributes of the study system and dataset (and their interaction) add important nuance for how best to assemble and filter short read genomic data for phylogenetic inference.

bioinformatics↗

bioRxiv2021

The genetic population structure of Lake Tanganyika's Lates species flock, an endemic radiation of pelagic top predators

Understanding genetic connectivity plays a crucial role in species conservation decisions, and genetic connectivity is an important component of modern fisheries management. In this study, we investigated the population genetics of four endemic Lates species of Lake Tanganyika (Lates stappersii, L. microlepis, L. mariae and L. angustifrons) using reduced-representation genomic sequencing methods. We find the four species to be strongly differentiated from one another (mean interspecific FST = 0.665), with no evidence for contemporary admixture. We also find evidence for strong genetic structure within L. mariae, with the majority of individuals from the most southern sampling site forming a genetic group that is distinct from the individuals at other sampling sites. We find evidence for much weaker structure within the other three species (L. stappersii, L. microlepis, and L. angustifrons). Our ability to detect this weak structure despite small and unbalanced sample sizes and imprecise geographic sampling locations suggests the possibility for further structure undetected in our study. We call for further research into the origins of the genetic differentiation in these four species--particularly that of L. mariae--which may be important for conservation and management of this culturally and economically important clade of fish.

evolutionary biology↗

bioRxiv2019

Sex differentiation and a chromosomal inversion lead to cryptic diversity in Lake Tanganyika sardines

Identifying patterns in genetic structure and the genetic basis of ecological adaptation is a core goal of evolutionary biology and can inform the management and conservation of species that are vulnerable to population declines exacerbated by climate change. We used reduced representation genomic sequencing methods to gain a better understanding of genetic structure among and within populations of Lake Tanganyikas two sardine species, Limnothrissa miodon and Stolothrissa tanganicae. Samples of these ecologically and economically important species were collected across the length of Lake Tanganyika, as well as from nearby Lake Kivu, where L. miodon was introduced in 1959. Our results reveal unexpected differentiation within both S. tanganicae and L. miodon that is not explained by geography. Instead, this genetic differentiation is due to the presence of large sex-specific regions in the genomes of both species, but involving different polymorphic sites in each species. Our results therefore indicate rapidly evolving XY sex determination in the two species. Additionally, we found evidence of a large segregating inversion in L. miodon. We found all inversion karyotypes throughout Lake Tanganyika, but the frequencies vary along a north-south gradient, and differ substantially in the introduced Lake Kivu population. We do not find evidence for significant isolation-by-distance, even over the hundreds of kilometers covered by our sampling, but we do find shallow population structure.

evolutionary biology↗