This research was conducted with an awesome team of co-authors: @annasanture.bsky.social my amazing PhD supervisor, @katarinastuart.bsky.social, @josephguhlin.bsky.social, @vbtram.bsky.social, Selina Patel, Laura Duntsch, John G. Ewen, and @pbrekke.bsky.social
👩🔬👨🔬
@wiley.com
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Hui Zhen Tan
We found moderate inbreeding levels in the Tiritiri Matangi population that is associated with lower reproductive success, indicating inbreeding depression (ID). ID in the hihi is likely polygenic in nature including two potential regions harbouring genes related to reproduction in other birds.
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Whole-genome data from yellow-eyed penguins (hoiho) identify three lineages with high geographical and genomic divergence, and candidate gene variants associated with differential susceptibility to neonatal respiratory distress syndrome, according to a paper in Nature Ecology & Evolution. 🌍🧬🧪
New study 🧬 Inbreeding depression is a concern in small populations, and evaluating its genomic proxies is important for #ConservationGenomics. In hihi, genome-wide homozygosity best predicts lifetime reproductive success, compared to genetic load and FROH.
Publication: doi.org/10.1111/eva....
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Now out in ME: dx.doi.org/10.1111/mec....
Empirical comparison of WGS and RADseq selection scans shows missed signals and false outliers in RADseq selection scans resulting from population specific allelic dropout @katarinastuart.bsky.social @lee-rollins.bsky.social @annasanture.bsky.social
🔑 Choosing your imputation tool:
- All tools worked well in highly related populations.
- Accuracy varied in populations with low relatedness, but GLIMPSE2 & QUILT2 generally outperformed the other tools.
- STITCH is useful when no reference panel exists but results in some missing data.
New Zealand’s invasive starlings on the cover of Molecular Ecology! 🐦🧬
This collaborative project unpacks the invasion history of starlings in Aotearoa New Zealand, combining population genomics with historical records of human-mediated translocations.
onlinelibrary.wiley.com/doi/10.1111/...
💥 Downstream impact:
- PopGen analyses (relatedness, population structure) were congruent with imputation accuracy and depend on genetic relatedness.
- Inbreeding coefficient estimates were more sensitive to imputation.
- Demographic analysis on imputed data showed similar results across the tools.
👩🏻💻 We tested 5️⃣ imputation methods (GLIMPSE2, GeneImp, QUILT2, STITCH, Beagle5.4), simulated realistic populations with different genetic structures, and applied the methods to data from 283 wild hihi (stitchbird) 🧬.
Whole-genome data from 249 yellow-eyed penguins (hoiho) identify three lineages with high geographical and genomic divergence, and candidate gene variants associated with differential susceptibility to neonatal respiratory distress syndrome.
💡 Bonus: Open Snakemake pipelines for both simulation and imputation are provided:
- github.com/vibaotram/si...
- github.com/vibaotram/im...
Feel free to test and optimize imputation strategies for your own datasets before committing to large-scale LCS projects.
Hui Zhen Tan
Nature Portfolio
Population declines result in increasingly small populations, which often experience an increase in inbreeding. Inbreeding may be negatively associated with fitness traits like survival and reproduct...
