a This method can be used to detect cytosine methylation by designing primers of different lengths corresponding to different cytosine markers that vary among body fluids/tissues of human (e.g. blood, saliva, and semen) or between monozygotic twins or with the ageing of human beings.
Although sample size, methods of evaluation and expression platforms vary and could account for differences in gene expression profiles, additional independent studies are required for cross-comparison to identify reliable gene markers that vary in expression.
In C. remanei, sperm competition assays were carried out essentially the same as above, except that C. remanei females were used as the "arena" for male-male competition, and males from the three strains were allowed to compete directly (i.e., no standardized male competitors), with offspring paternity determined by examining a microsatellite marker that varied among strains.
Simulations that vary marker spacing show that although high marker density does not improve the power to detect loci, it has a significant effect on the precision of QTL localization (Darvasi et al. 1993; Stange et al. 2013).
For each trait, the number of SNPs ranged from 3 to 9, with marker effects that varied from 2.2 to 13.5% (Supplementary Table S9).
Of these, three significant SNP markers were associated with α-cellulose content (SNP18, SNP49, and SNP75); one SNP marker each was associated with holocellulose, fiber length, and fiber width, and H traits were observed in the linkage population, with marker effects that varied from 1.5 to 3.6% (Q < 0.10) (Table 5).
In this paper we use four molecular markers (two nuclear and two mitochondrial) that vary in overall rates of evolution to diagnose relationships among species of dolphin in the genus Lagenorhynchus and among genera within the subfamily Lissodelphininae [ 13].
The quantitative trait loci (QTL) mapping in Drosophila requires two inbred strains that vary genetically for life span and a polymorphic molecular marker linkage map.
To gain further insight into the differences between colon cancer cells that vary in their apoptotic response to camptothecin, and to identify additional markers that could help recognise tumours that vary in their response to this agent, we assessed the level of expression of 9216 sequences in resistant LoVo cells, and in sensitive L2 and L3 derivatives, using cDNA microarray analysis.
Explanations for that vary.
Both the 4gamete and HapBlock methods produce blocks that vary greatly in size, depending on regional properties of the data (i.e., linkage disequilibrium and marker density).
