HighlanderLab (@highlanderlab) 's Twitter Profile
HighlanderLab

@highlanderlab

Research on managing and improving populations at @RoslinInstitute & @TheDickVet. Led by the chief Highlander @GregorGorjanc. Also on fediscience dot org

ID: 1155635495218667522

linkhttps://www.ed.ac.uk/roslin/highlanderlab calendar_today29-07-2019 00:25:47

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Gregor Gorjanc (@gregorgorjanc) 's Twitter Profile Photo

The ARG: * Captured key biological signals * Encoded genomic data more efficiently than conventional formats * Resulted in the highest predictive ability when combining both subspecies (though not by much)

Gregor Gorjanc (@gregorgorjanc) 's Twitter Profile Photo

This builds upon the work of tskit community - there is an advanced manuscript in the pipeline on how to build relationship/relatedness matrix from tree sequence encoding of an ARG!

Gregor Gorjanc (@gregorgorjanc) 's Twitter Profile Photo

After building the ARG, we demonstrated it captures biological signals using genealogical nearest neighbors (GNN) - it clearly distinguished indica and japonica rice subspecies and effectively represented population structure.

After building the ARG, we demonstrated it captures biological signals using genealogical nearest neighbors (GNN) - it clearly distinguished indica and japonica rice subspecies and effectively represented population structure.
Gregor Gorjanc (@gregorgorjanc) 's Twitter Profile Photo

Local trees from two genomic regions showed distinct patterns: (A) revealed deep separation between indica and japonica, linked to the DST gene associated with panicle length in japonica. The (B) region segregated in both subspecies and was linked to panicle traits in both.

Local trees from two genomic regions showed distinct patterns: (A) revealed deep separation between indica and japonica, linked to the DST gene associated with panicle length in japonica. The (B) region segregated in both subspecies and was linked to panicle traits in both.
Gregor Gorjanc (@gregorgorjanc) 's Twitter Profile Photo

The ARG encoded genomic data more efficiently than the standard VCF: the tree sequence file for all chromosomes was 62 MB, compared to 228 MB for the VCF—nearly four times smaller!

The ARG encoded genomic data more efficiently than the standard VCF: the tree sequence file for all chromosomes was 62 MB, compared to 228 MB for the VCF—nearly four times smaller!
Gregor Gorjanc (@gregorgorjanc) 's Twitter Profile Photo

The age distributions for (A) nodes (ancestors), (B) mutations, and (C) SNP sites (i.e., first mutation at each site) were heavily right-skewed towards the present (as expected).

The age distributions for (A) nodes (ancestors), (B) mutations, and (C) SNP sites (i.e., first mutation at each site) were heavily right-skewed towards the present (as expected).
Gregor Gorjanc (@gregorgorjanc) 's Twitter Profile Photo

(A) The standard site-based relationship matrix (SRM, VanRaden’s) and (B) the ARG-based branch relationship matrix (BRM) revealed similar population structure, with highly correlated (C) diagonal and (D) off-diagonal elements, though on different scales.

(A) The standard site-based relationship matrix (SRM, VanRaden’s) and (B) the ARG-based branch relationship matrix (BRM) revealed similar population structure, with highly correlated (C) diagonal and (D) off-diagonal elements, though on different scales.
Gregor Gorjanc (@gregorgorjanc) 's Twitter Profile Photo

In cross-validation for yield prediction, the ARG-based branch relationship matrix (BRM) demonstrated higher predictive ability than the standard site-based relationship matrix (SRM) when combining both subspecies.

In cross-validation for yield prediction, the ARG-based branch relationship matrix (BRM) demonstrated higher predictive ability than the standard site-based relationship matrix (SRM) when combining both subspecies.
Gregor Gorjanc (@gregorgorjanc) 's Twitter Profile Photo

Irene De Carlos presented her work on Modelling the Impact of Non-Native Honey Bee Importation on Native Apis mellifera mellifera Populations (with Laura Strachan, Grace McCormack, Jana Obšteter)

Gregor Gorjanc (@gregorgorjanc) 's Twitter Profile Photo

Jana Obsteter presented the work of Laura Strachan on Optimizing pedigree reconstruction and patriline determination in honeybees (with Jernej Bubnič and Janez Presern)

Gregor Gorjanc (@gregorgorjanc) 's Twitter Profile Photo

I presented the work of Letícia Lara on Evaluation of selective breeding programme designs for black soldier fly larvae body weight (with María Martínez Castillero, Thiago Oliveira, Ivan Pocrnić, Jana Obšteter)

Gregor Gorjanc (@gregorgorjanc) 's Twitter Profile Photo

Lastly I gave a short course on Stochastic simulations of breeding programmes with AlphaSimR - a teaser for our free on-line course edx.org/learn/animal-b…

HighlanderLab (@highlanderlab) 's Twitter Profile Photo

It can be tricky to visualise large #pedigrees. We have develped 'randPedPCA' for running #PCA on large pedigrees (can be >1M individuals). Check out our preprint doi.org/10.1101/2025.0… and the R package github.com/HighlanderLab/… Gregor Gorjanc Hanbin Lee Hannes Becher

Gregor Gorjanc (@gregorgorjanc) 's Twitter Profile Photo

Please share: Registration is now open for EUCARPIA Biometrics in Plant Breeding 2025 highlanderlab.github.io/EUCARPIA2025Bi…

Please share: Registration is now open for EUCARPIA Biometrics in Plant Breeding 2025 highlanderlab.github.io/EUCARPIA2025Bi…
Gregor Gorjanc (@gregorgorjanc) 's Twitter Profile Photo

I feel blessed & hyped after another fantastic HighlanderLab meeting covering: * Selective breeding of artemia Bruna Santana * Selection index (Smith-Hazel, desired gains, economic weights, …) Daniel Tolhurst

Gregor Gorjanc (@gregorgorjanc) 's Twitter Profile Photo

* Imprinting / gametic models on simulated and real beef data David Lopez Carbonell * Selection for stability in plant breeding Dominic Waters * Tracking inheritance of alleles within a dog pedigree Rosalind Craddock * EUCARPIA Conference organisation highlanderlab.github.io/EUCARPIA2025Bi…