A chromosome-level reference genome and pangenome for barn swallow population genomics

Secomandi, Simona; Gallo, Guido Roberto; Sozzoni, Marcella; Iannucci, Alessio; Galati, Elena; Abueg, Linelle; Balacco, Jennifer; Caprioli, Manuela; Chow, William; Ciofi, Claudio; Collins, Joanna; Fédrigo, Olivier; Ferretti, Luca; Fungtammasan, Arkarachai; Haase, Bettina; Howe, Kerstin; Lombardo, Gianluca; Masterson, Patrick; Messina, Graziella; Møller, Anders Pape; Mountcastle, Jacquelyn; Mousseau, Timothy A.; Obiol, Joan Ferrer; Olivieri, Anna; Rhie, Arang; Rubolini, Diego; Saclier, Marielle; Stanyon, Roscoe; Stucki, David; Thibaud‐Nissen, Françoise; Torrance, James; Torroni, Antonio; Weber, Kristina; Ambrosini, Roberto; Bonisoli-Alquati, Andrea; Jarvis, Erich D.; Gianfranceschi, L.; Formenti, Giulio

doi:10.1016/j.celrep.2023.111992

Cited by 13 publications

(15 citation statements)

References 128 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To estimate the latter, we first calculated LD in 25 kb non-overlapping windows and, following ref. 91 , we averaged genome-wide LD values within 500 kb blocks using the chr_ld.pl custom script ( https://github.com/SwallowGenomics/BarnSwallow/blob/main/Analyses/LD-scripts/chr_ld.pl ) to visualize areas of the genome that are in high linkage (see Fig. 2 ).…”

Section: Methodsmentioning

confidence: 99%

A genomic basis of vocal rhythm in birds

Sebastianelli,

Lukhele,

Secomandi

et al. 2024

Nat Commun

Self Cite

View full text Add to dashboard Cite

Vocal rhythm plays a fundamental role in sexual selection and species recognition in birds, but little is known of its genetic basis due to the confounding effect of vocal learning in model systems. Uncovering its genetic basis could facilitate identifying genes potentially important in speciation. Here we investigate the genomic underpinnings of rhythm in vocal non-learning Pogoniulus tinkerbirds using 135 individual whole genomes distributed across a southern African hybrid zone. We find rhythm speed is associated with two genes that are also known to affect human speech, Neurexin-1 and Coenzyme Q8A. Models leveraging ancestry reveal these candidate loci also impact rhythmic stability, a trait linked with motor performance which is an indicator of quality. Character displacement in rhythmic stability suggests possible reinforcement against hybridization, supported by evidence of asymmetric assortative mating in the species producing faster, more stable rhythms. Because rhythm is omnipresent in animal communication, candidate genes identified here may shape vocal rhythm across birds and other vertebrates.

show abstract

Section: Methodsmentioning

confidence: 99%

A genomic basis of vocal rhythm in birds

Sebastianelli,

Lukhele,

Secomandi

et al. 2024

Nat Commun

Self Cite

View full text Add to dashboard Cite

show abstract

“…PacBio and 10X sequencing, optical mapping, and Hi-C generation were performed by the Rockefeller University Vertebrate Genome Laboratory using standard VGP protocols as previously described in Secomandi et al . 27 . The genome was assembled as previously described in Secomandi et al .…”

Section: Methodsmentioning

confidence: 99%

“…The genome was assembled as previously described in Secomandi et al . 27 , with minor modifications. Prior to the assembly, Genomescope2.0 28 was used on the raw 10X reads, yielding, through statistical analyses of k -mer profiles, an estimated genome size of 2.65 Gbp, heterozygosity of 0.22%, and repeat content of 0.75 Gbp.…”

Section: Methodsmentioning

confidence: 99%

Chromosome level genome assembly of the Etruscan shrew Suncus etruscus

Bukhman,

Meyer,

Chu

et al. 2024

Sci Data

Self Cite

View full text Add to dashboard Cite

Suncus etruscus is one of the world’s smallest mammals, with an average body mass of about 2 grams. The Etruscan shrew’s small body is accompanied by a very high energy demand and numerous metabolic adaptations. Here we report a chromosome-level genome assembly using PacBio long read sequencing, 10X Genomics linked short reads, optical mapping, and Hi-C linked reads. The assembly is partially phased, with the 2.472 Gbp primary pseudohaplotype and 1.515 Gbp alternate. We manually curated the primary assembly and identified 22 chromosomes, including X and Y sex chromosomes. The NCBI genome annotation pipeline identified 39,091 genes, 19,819 of them protein-coding. We also identified segmental duplications, inferred GO term annotations, and computed orthologs of human and mouse genes. This reference-quality genome will be an important resource for research on mammalian development, metabolism, and body size control.

show abstract

“…Despite the unknown impact, the human-based default model has seen a rapid expansion in comparative genomics. DV offers substantially fewer implementation barriers than GATK, enticing researchers across a wide range of species, including domesticated and endangered animals (Leonard et al 2023;Stenløkk et al 2022;Flack et al 2023), birds (Secomandi et al 2023;Guhlin et al 2023), plants (Osipowski et al 2020;Ruperao et al 2023), and pathogenic organisms (Gunderson et al 2020;Jesudoss Chelladurai et al 2023). As the 'default' genome, models intended for humans are often implicitly trusted to be the optimal method in other diploid species.…”

Section: Introductionmentioning

confidence: 99%

Overcoming Limitations to Deep Learning in Domesticated Animals with TrioTrain

Kalleberg,

Rissman,

Schnabel

2024

Preprint

View full text Add to dashboard Cite

Variant calling across diverse species remains challenging as most bioinformatics tools default to assumptions based on human genomes. DeepVariant (DV) excels without joint genotyping while offering fewer implementation barriers. However, the growing appeal of a "universal" algorithm has magnified the unknown impacts when used with non-human genomes. Here, we use bovine genomes to assess the limits of human-genome-trained models in other species. We introduce the first multi-species DV model that achieves a lower Mendelian Inheritance Error (MIE) rate during single-sample genotyping. Our novel approach, TrioTrain, automates extending DV for species without Genome In A Bottle (GIAB) resources and uses region shuffling to mitigate barriers for SLURM-based clusters. To offset imperfect truth labels for animal genomes, we remove Mendelian discordant variants before training, where models are tuned to genotype the offspring correctly. With TrioTrain, we use cattle, yak, and bison trios to build 30 model iterations across five phases. We observe remarkable performance across phases when testing the GIAB human trios with a mean SNP F1 score >0.990. In HG002, our phase 4 bovine model identifies more variants at a lower MIE rate than DeepTrio. In bovine F1-hybrid genomes, our model substantially reduces inheritance errors with a mean MIE rate of 0.03 percent. Although constrained by imperfect labels, we find that multi-species, trio-based training produces a robust variant calling model. Our research demonstrates that exclusively training with human genomes restricts the application of deep-learning approaches for comparative genomics.

show abstract

A chromosome-level reference genome and pangenome for barn swallow population genomics

Cited by 13 publications

References 128 publications

A genomic basis of vocal rhythm in birds

A genomic basis of vocal rhythm in birds

Chromosome level genome assembly of the Etruscan shrew Suncus etruscus

Overcoming Limitations to Deep Learning in Domesticated Animals with TrioTrain

Contact Info

Product

Resources

About