Luc L Janss
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Explore the profile of Luc L Janss including associated specialties, affiliations and a list of published articles.
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12
Citations
402
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Recent Articles
1.
Jayakodi M, Golicz A, Kreplak J, Fechete L, Angra D, Bednar P, et al.
Nature
. 2023 Mar;
615(7953):652-659.
PMID: 36890232
Increasing the proportion of locally produced plant protein in currently meat-rich diets could substantially reduce greenhouse gas emissions and loss of biodiversity. However, plant protein production is hampered by the...
2.
Wang L, Janss L, Madsen P, Henshall J, Huang C, Marois D, et al.
Genet Sel Evol
. 2020 Jun;
52(1):31.
PMID: 32527317
Background: The traditional way to estimate variance components (VC) is based on the animal model using a pedigree-based relationship matrix (A) (A-AM). After genomic selection was introduced into breeding programs,...
3.
Tsai H, Janss L, Andersen J, Orabi J, Jensen J, Jahoor A, et al.
Sci Rep
. 2020 May;
10(1):8205.
PMID: 32398811
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
4.
Tsai H, Janss L, Andersen J, Orabi J, Jensen J, Jahoor A, et al.
Sci Rep
. 2020 Feb;
10(1):3347.
PMID: 32099054
Genome-wide association study (GWAS) and genomic prediction (GP) are extensively employed to accelerate genetic gain and identify QTL in plant breeding. In this study, 1,317 spring barley and 1,325 winter...
5.
Kristensen P, Jahoor A, Andersen J, Cericola F, Orabi J, Janss L, et al.
Front Plant Sci
. 2018 Feb;
9:69.
PMID: 29456546
The aim of the this study was to identify SNP markers associated with five important wheat quality traits (grain protein content, Zeleny sedimentation, test weight, thousand-kernel weight, and falling number),...
6.
Cericola F, Jahoor A, Orabi J, Andersen J, Janss L, Jensen J
PLoS One
. 2017 Jan;
12(1):e0169606.
PMID: 28081208
Wheat breeding programs generate a large amount of variation which cannot be completely explored because of limited phenotyping throughput. Genomic prediction (GP) has been proposed as a new tool which...
7.
Ashraf B, Byrne S, Fe D, Czaban A, Asp T, Pedersen M, et al.
Theor Appl Genet
. 2015 Sep;
129(1):45-52.
PMID: 26407618
By using the genotyping-by-sequencing method, it is feasible to characterize genomic relationships directly at the level of family pools and to estimate genomic heritabilities from phenotypes scored on family-pools in...
8.
Galesloot T, Janss L, Burgess S, Kiemeney L, den Heijer M, de Graaf J, et al.
BMC Genet
. 2015 Jul;
16:79.
PMID: 26159428
Background: Previous reports suggested a role for iron and hepcidin in atherosclerosis. Here, we evaluated the causality of these associations from a genetic perspective via (i) a Mendelian randomization (MR)...
9.
Galesloot T, Van Steen K, Kiemeney L, Janss L, Vermeulen S
PLoS One
. 2014 Apr;
9(4):e95923.
PMID: 24763738
Joint association analysis of multiple traits in a genome-wide association study (GWAS), i.e. a multivariate GWAS, offers several advantages over analyzing each trait in a separate GWAS. In this study...
10.
Ashraf B, Jensen J, Asp T, Janss L
Theor Appl Genet
. 2014 Mar;
127(6):1331-41.
PMID: 24668443
We propose a method in which GBS data can be conveniently analyzed without calling genotypes. F2 families are frequently used in breeding of outcrossing species, for instance to obtain trait...