Biology subjects

Nugent, C. M.

Publications and source records attributed to Nugent, C. M..

6 recordsLinked to original sources

bioRxiv2023

Post-glacial recolonization and multiple scales of secondary contact contribute to contemporary Atlantic salmon (Salmo salar) genomic variation in North America.

AimIn northern environments, periods of isolation during Pleistocene glaciations and subsequent recolonization and secondary contact have had a significant influence on contemporary diversity of many species. The recent advent of high-resolution genomic analyses allows unprecedented power to resolve genomic signatures of such events in northern species. Here, we provide the highest resolution genomic characterization of Atlantic salmon in North America to infer glacial refugia and the geographic scales of postglacial secondary contact. LocationNorth America. TaxonAtlantic salmon, Salmo salar. MethodsSamples were collected for 5455 individuals from 148 populations encompassing the majority of Atlantic salmons native range in North America, from Labrador to Maine. Individuals were genotyped using a 220K SNP array aligned to the Atlantic salmon (Salmo salar) genome. Spatial genetic structure (PCA, k-means clustering, admixture) was evaluated in conjunction with genomic comparisons of identified lineages to infer the refugia during the last glacial maximum and regions of secondary contact following recolonization. ResultsSpatial genomic analyses identified three phylogeographic groups, consistent with the northward recolonization from two southern glacial refugia in North America (a western Maritime lineage and an eastern Newfoundland and Labrador lineage), with subsequent differentiation of the eastern lineage into two separate groups. Secondary contact among these North American groups was present within the northern Gulf of St. Lawrence and evidence of trans-Atlantic secondary contact was detected within the eastern Newfoundland and Labrador lineage. Comparison of groups from insular Newfoundland with those from mainland Labrador suggests genomic regions displaying high differentiation were characterized by elevated European admixture, suggesting a possible role of European secondary contact in population divergence. Main ConclusionsThese findings present the first evidence suggesting that genomic diversity in extant North American Atlantic salmon populations has resulted from allopatric isolation in two glacial refugia followed by both regional and trans-Atlantic recolonization and secondary contact and demonstrate the power of genomic tools to resolve historical drivers of diversity in wild populations.

evolutionary biology↗

bioRxiv2022

Whole genome sequencing reveals fine-scale climate associated adaptive divergence near the range limits of a temperate reef fish.

Adaptation to ocean climate is increasingly recognized as an important driver of diversity in marine species despite the lack of physical barriers to dispersal and the presence of pelagic stages in many taxa. A robust understanding of the genomic and ecological processes involved in structuring populations is lacking for most marine species, often hindering management and conservation action. Cunner (Tautogolabrus adspersus), is a temperate reef fish that displays both pelagic early life history stages and strong site-associated homing as adults; the species is also presently of interest for use as a cleaner fish in salmonid aquaculture in Atlantic Canada. Here we produce a chromosome-level genome assembly for cunner and characterize spatial population structure throughout Atlantic Canada using whole genome resequencing. The genome assembly spanned 0.72 Gbp and resolved 24 chromosomes; whole genome resequencing of 803 individuals from 20 locations spanning from Newfoundland to New Jersey identified approximately 11 million genetic variants. Principal component analysis revealed four distinct regional groups in Atlantic Canada, including three near the range edge in Newfoundland. Pairwise FST and selection scans revealed consistent signals of differentiation and selection at discrete genomic regions including adjacent peaks on chromosome 10 recurring across multiple pairwise comparisons (i.e., FST 0.5-0.75). Redundancy analysis suggested significant association of environmental variables related to benthic temperature and oxygen range with genomic structure, again highlighting the previously identified region on chromosome 10. Our results suggest that climate associated adaptation in this temperate reef fish drives regional diversity despite high early life history dispersal potential.

genomics↗

bioRxiv2022

Genomic and machine learning-based screening of aquaculture associated introgression into at-risk wild North American Atlantic salmon (Salmo salar) populations.

The negative genetic impacts of gene flow from domestic to wild populations can be dependent on the degree of domestication and exacerbated by the magnitude of pre-existing genetic differences between wild populations and the domestication source. Recent evidence of European ancestry within North American aquaculture Atlantic salmon (Salmo salar) has elevated the potential impact of escaped farmed salmon on often at-risk wild North American salmon populations. Here we compare the ability of single nucleotide polymorphism (SNP) and microsatellite (SSR) marker panels of different sizes (7-SSR, 100-SSR, and 220K-SNP) to detect introgression of European genetic information into North American wild and aquaculture populations. Linear regression comparing admixture predictions for a set of individuals common to the three data sets showed that the 100-SSR panel and 7-SSR panels replicated the full 220K-SNP-based admixture estimates with low accuracy (r2 of 0.64 and 0.49 respectively). Additional tests explored the effects of individual sample size and marker number, which revealed that ~300 randomly selected SNPs could replicate the 220K-SNP admixture predictions with greater than 95% fidelity. We designed a custom SNP panel (301-SNP) for European admixture detection in future monitoring work and then developed and tested a Python package, SalmonEuAdmix (https://github.com/CNuge/SalmonEuAdmix), that uses a deep neural network to make de novo estimates of individuals European admixture proportion without the need to conduct complete admixture analysis utilizing baseline samples. The results demonstrate the mobilization of targeted SNP panels and machine learning in support of at-risk species conservation and management.

genomics↗

bioRxiv2021

debar, a sequence-by-sequence denoiser for COI-5P DNA barcode data

DNA barcoding and metabarcoding are now widely used to advance species discovery and biodiversity assessments. High-throughput sequencing (HTS) has expanded the volume and scope of these analyses, but elevated error rates introduce noise into sequence records that can inflate estimates of biodiversity. Denoising --the separation of biological signal from instrument (technical) noise--of barcode and metabarcode data currently employs abundance-based methods which do not capitalize on the highly conserved structure of the cytochrome c oxidase subunit I (COI) region employed as the animal barcode. This manuscript introduces debar, an R package that utilizes a profile hidden Markov model to denoise indel errors in COI sequences introduced by instrument error. In silico studies demonstrated that debar recognized 95% of artificially introduced indels in COI sequences. When applied to real-world data, debar reduced indel errors in circular consensus sequences obtained with the Sequel platform by 75%, and those generated on the Ion Torrent S5 by 94%. The false correction rate was less than 0.1%, indicating that debar is receptive to the majority of true COI variation in the animal kingdom. In conclusion, the debar package improves DNA barcode and metabarcode workflows by aiding the generation of more accurate sequences aiding the characterization of species diversity.

bioinformatics↗

bioRxiv2020

Alignment-free identification of COI DNA barcode data with the Python package Alfie

Characterization of biodiversity from environmental DNA samples and bulk metabarcoding data is hampered by off-target sequences that can confound conclusions about a taxonomic group of interest. Existing methods for isolation of target sequences rely on alignment to existing reference barcodes, but this can bias results against novel genetic variants. Effectively parsing targeted DNA barcode data from off-target noise improves the quality of biodiversity estimates and biological conclusions by limiting subsequent analyses to a relevant subset of available data. Here, we present Alfie, a Python package for the alignment-free classification of cytochrome c oxidase subunit I (COI) DNA barcode sequences to taxonomic kingdoms. The package determines k-mer frequencies of DNA sequences, and the frequencies serve as input for a neural network classifier that was trained and tested using ~58,000 publicly available COI sequences. The classifier was designed and optimized through a series of tests that allowed for the optimal set of DNA k-mer features and optimal machine learning algorithm to be selected. The neural network classifier rapidly assigns COI sequences to kingdoms with greater than 99% accuracy and is shown to generalize effectively and make accurate predictions about data from previously unseen taxonomic classes. The package contains an application programming interface that allows the Alfie packages functionality to be extended to different DNA sequence classification tasks to suit a users need, including classification of different genes and barcodes, and classification to different taxonomic levels. Alfie is free and publicly available through GitHub (https://github.com/CNuge/alfie) and the Python package index (https://pypi.org/project/alfie/).

bioinformatics↗

bioRxiv2019

coil: an R package for cytochrome C oxidase I (COI) DNA barcode data cleaning, translation, and error evaluation.

Biological conclusions based on DNA barcoding and metabarcoding analyses can be strongly influenced by the methods utilized for data generation and curation, leading to varying levels of success in the separation of biological variation from experimental error. The five-prime region of cytochrome c oxidase subunit I (COI-5P) is the most common barcode gene for animals, with conserved structure and function that allows for biologically informed error identification. Here, we present coil (https://CRAN.R-project.org/package=coil), an R package for the pre-processing and error assessment of COI-5P animal barcode and metabarcode sequence data. The package contains functions for placement of barcodes into a common reading frame, accurate translation of sequences to amino acids, and highlighting insertion and deletion errors. The analysis of 10,000 barcode sequences of varying quality demonstrated how coil can place barcode sequences in reading frame and distinguish sequences containing indel errors from error-free sequences with greater than 97.5% accuracy. Package limitations were tested through the analysis of COI-5P sequences from the plant and fungal kingdoms as well as the analysis of potential contaminants: nuclear mitochondrial pseudogenes and Wolbachia COI-5P sequences. Results demonstrated that coil is a strong technical error identification method but is not reliable for detecting all biological contaminants.

bioinformatics↗