Human GAK ELISA Matched Antibody Pair

The current paper proposes a new genetic clustering technique using the concepts of line symmetry for assigning points to different clusters. The symmetrical line of a particular cluster is determined automatically using the search capability of genetic algorithms. This line is then used to compute the amount of symmetry of any point within a given cluster. The lines are encoded in the form of a chromosome. Mutation and crossover operations are modified in such a way so that those can help the GA to search for the symmetrical line efficiently. A way of measuring the amount of line symmetry of a given point with respect to a symmetrical line is also thoroughly described which is used further to assign points to different clusters. This in turn produces the partitioning corresponding to a particular chromosome. The compactness of this obtained partitioning is calculated using the line symmetry based measurement and is further used as the objective function of the chromosome. The proposed method is able to detect clusters having line symmetry property. The effectiveness of the proposed technique (LSGA) is shown for 12 artificial and two real-life data sets. Results are compared with those obtained by existing genetic algorithm with line symmetry based clustering technique (GALS), genetic algorithm based K-means clustering technique (GAK-means), average linkage clustering technique, spectral clustering technique, expectation maximization based clustering technique, fuzzy-GA and point-GA clustering techniques.

Meiotic recombination breaks down linkage disequilibrium (LD) and forms new haplotypes, meaning that it is an important driver of diversity in eukaryotic genomes. Understanding the causes of variation in recombination rate is important in interpreting and predicting evolutionary phenomena and in understanding the potential of a population to respond to selection. However, despite attention in model systems, there remains little data on how recombination rate varies at the individual level in natural populations. Here we used extensive pedigree and high-density SNP information in a wild population of Soay sheep (Ovis aries) to investigate the genetic architecture of individual autosomal recombination rates. Individual rates were high relative to other mammal systems and were higher in males than in females (autosomal map lengths of 3748 and 2860 cM, respectively). The heritability of autosomal recombination rate was low but significant in both sexes (h(2) = 0.16 and 0.12 in females and males, respectively). In females, 46.7% of the heritable variation was explained by a subtelomeric region on chromosome 6; a genome-wide association study showed the strongest associations at locus RNF212, with further associations observed at a nearby similar to 374-kb region of complete LD containing three additional candidate loci, CPLX1, GAK, and PCGF3. A second region on chromosome 7 containing REC8 and RNF212B explained 26.2% of the heritable variation in recombination rate in both sexes. Comparative analyses with 40 other sheep breeds showed that haplotypes associated with recombination rates are both old and globally distributed. Both regions have been implicated in rate variation in mice, cattle, and humans, suggesting a common genetic architecture of recombination rate variation in mammals.