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Notably, the underlying locus underwent tandem duplication after grape-vine lineage split, leading to presence of a tandem array in all Brassicales including orange, but an evident singleton gene in Solanaceae and V. vinifera.
Thus, at the studied L1M loci, we found a mixed picture of higher methylation at the Xi or Xa with no clear correlation to the inactivation status of the underlying locus.
With the development of genome-wide SNP arrays for all livestock species, it has become possible to rapidly map the underlying locus by means of autozygosity mapping to intervals that typically span 2 to 5 megabases thereby proving the inherited nature and mode of inheritance of the corresponding condition (f.i. [ 1]).
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The extracted principal components are then analyzed in conjunction with marker data to map the underlying loci.
First, the results support the analytical solutions relating number of underlying loci to the rate of change of genetic variance, but the rates of change are lower, relative to linear genotypes, with the directional epistasis that network structures introduce.
Empirical results show that the presence of epistasis can increase power to detect the underlying loci compared to the non-epistatic additive case, in two-marker full model tests as well as in single-marker main effect tests.
We know that the rate of change of genetic variance is inversely proportional to the number of underlying loci [9], [10], and therefore the species with twice as many loci will lose gene variation at approximately half the speed of the other species.
The nature of the underlying loci remains unclear.
These scenarios could be tested, once underlying loci are identified, by examining genetic variation at these loci in D. gunungcola.
This enables us to quantitatively link the weights of codes to functional or biochemical properties of the underlying loci.
In theory, linkage disequilibrium lasting longer than a few generations may be due to close physical linkage of underlying loci or strong selection on unlinked loci.
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