In Tampere the public sauna is open this night so that people can go to sauna while waiting for the Lunar eclipse. And while we have here temperatures above 30 degrees, this is highly appreciated (at least the swimming, though, 30 does not feel too bad, if you leave from 115…)
We finally managed to plant some sweet cherry trees. Lets see, although it is said they will survive climate zones 4 here in Finland, I am not sure if they will…
Our publication “Validated quantitative trait loci for eggshell quality in experimental and commercial laying hens” has been published as short communication in Animal Genetics.
Summary
Compromised eggshell quality causes considerable economic losses for the egg industry. Breeding for improved eggshell quality has been very challenging. Eggshell quality is a trait that would greatly benefit from marker‐assisted selection, which would allow the selection of sires for their direct contribution to the trait and would also allow implementation of measurements integrating a number of shell parameters that are difficult to measure. In this study, we selected the most promising autosomal quantitative trait loci (QTL) affecting eggshell quality on chromosomes 2, 3, 6 and 14 from earlier experiments and we extended the F2 population to include 1599 F2 females. The study was repeated on two commercial populations: Lohmann Tierzucht Rhode Island Red line (n = 692 females) and a Hy‐Line White Plymouth Rock line (n = 290 progeny tested males). We analyzed the selected autosomal QTL regions on the three populations with SNP markers at 4–13 SNPs/Mb density. QTL for eggshell quality were replicated on all studied regions in the F2 population. New QTL were detected for eggshell color on chromosomes 3 and 6. Marker associations with eggshell quality traits were validated in the tested commercial lines on chromosomes 2, 3 and 6, thus paving the way for marker‐assisted selection for improved eggshell quality.
Just discovered, but highly recommended (Sarah Lesch):
Since 2014 the standard for genome studies in bovine was the UMD 3.1 genome, e.g. for download here:
However, a few days ago a new assembly was release, called ARS_UCD1.2.This assembly can be downloaded here:
ftp://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/002/263/795/GCA_002263795.2_ARS-UCD1.2/
Just to get a quick impression, I compared both assemblies and checked for their similarities using LAST http://last.cbrc.jp/ .
First, I created a LAST database like this
lastdb -P0 -uNEAR -R01 $FOLDER/UMD31/UMD31-NEAR $FOLDER/UMD31/UMD3.1_chromosomes.fa
Then, I determined the substitution and gap frequencies
last-train -P0 --revsym --matsym --gapsym -E0.05 -C2 $FOLDER/UMD31/UMD31-NEAR $FOLDER/ARS/ARS_UCD12.fna > $FOLDER/UMD-ARS.mat
After the training, the blasting was performed (here is the parallel part of the slurm script)
FOLDER="/wrk/daniel/References/";
chr=($(ls $FOLDER/ARS/chr*));
lastal -m50 -E0.05 -C2 -p $FOLDER/UMD-ARS.mat $FOLDER/UMD31/UMD31-NEAR ${chr[$SLURM_ARRAY_TASK_ID]} | last-split -m1 > UMD-ARS-$SLURM_ARRAY_TASK_ID.maf
As I ran the blasting parallel for each chromosome, the header of the files needed to be removed
cat *.maf > all.maf sed '/^#/ d' < all.maf > temp.maf head -n 22 all.maf > headerLines cat headerLines temp.maf > alignments.maf
Finally, the merged simple-sequence alignments were discarded, the alignments were converted to tabular format, and alignments with error probability > 10^-5 were discarded:
last-postmask alignments.maf | maf-convert -n tab | awk -F'=' '$2 <= 1e-5' > alignments.tab
And for that tab file was then the dotplot created
last-dotplot -x 4000 -y 4000 alignment.tab alignment.png
This is how the dotplot looks like, it seems pretty much the same genome, but has in some areas clearly changed it! (Open it and zoom to the diagonal to see the differences)
For the steps, I followed the tutorial here: https://github.com/mcfrith/last-genome-alignments