Relaxation of Selective Constraint on the Ultra-Large Mitochondrial Genomes of Arcidae (Mollusca: Bivalvia)

The mitochondrial genomes(mitogenomes)are purportedly under selection for smaller size to improve their replica-tion and translation efficiency.However,the mitogenomes of Arcidae species are larger than those of other bivalves,and are among the largest metazoan mitogenomes reported to date.In order to explore the differences of base composition and selective constraints between the large and small mitogenomes,we compared the mitogenomes of 9 large arcid mitogenomes and 77 small bivalves mitogenomes.Base composition analyses indicated that Arcidae mitogenomes have significantly greater GC skews in both their whole genomes and coding sequences.This result suggests that the replication of the large mitogenomes in Arcidae may be slower than those in other bivalves,exposing the parental strand to deamination for a longer time.Selection pressure analyses showed that the mitochondrial protein-coding genes of Arcidae species have significantly higher Ka/Ks ratios than other bivalves,suggesting that they have accumulated more nonsynonymous nucleotide substitutions.Seven protein-coding genes(atp6,cox1-3,nad1,nad4 and nad5)show significant difference for Ka/Ks ratios between the Arcidae and non-Arcidae groups.However,these divergences are not observed in the nuclear gene within histone H3.From these observations,we concluded that the large mitoge-nomes of Arcidae species experienced more relaxed selective constraints.As some Arcidae species are more tolerant to hypoxia that can lead to low metabolic rate,the relaxed selective constraints of mitogenomes may be energy-related.This study provides new insights into the evolution of Arcidae mitogenomes.

Comparative Analysis of Codon Usage Patterns Among Mitochondrion, Chloroplast and Nuclear Genes

In many organisms, the difference in codon usage patterns among genes reflects variation in local base compositional biases and the intensity of natural selection. In this study, a comparative analysis was performed to investigate the characteristics of codon bias and factors in shaping the codon usage patterns among mitochondrion, chloroplast and nuclear genes in common wheat （Triticum aestivum L.）. GC contents in nuclear genes were higher than that in mitochondrion and chloroplast genes. The neutrality and correspondence analyses indicated that the codon usage in nuclear genes would be a result of relative strong mutational bias, while the codon usage patterns of mitochondrion and chloroplast genes were more conserved in GC content and influenced by translation level. The Parity Rule 2 （PR2） plot analysis showed that pyrimidines were used more frequently than purines at the third codon position in the three genomes. In addition, using a new alterative strategy, 11, 12, and 24 triplets were defined as preferred codons in the mitochondrion, chloroplast and nuclear genes, respectively. These findings suggested that the mitochondrion, chloroplast and nuclear genes shared particularly different features of codon usage and evolutionary constraints.

Instance-Specific Algorithm Selection via Multi-Output Learning

Instance-specific algorithm selection technologies have been successfully used in many research fields,such as constraint satisfaction and planning. Researchers have been increasingly trying to model the potential relations between different candidate algorithms for the algorithm selection. In this study, we propose an instancespecific algorithm selection method based on multi-output learning, which can manage these relations more directly.Three kinds of multi-output learning methods are used to predict the performances of the candidate algorithms：（1）multi-output regressor stacking;（2） multi-output extremely randomized trees; and（3） hybrid single-output and multioutput trees. The experimental results obtained using 11 SAT datasets and 5 Max SAT datasets indicate that our proposed methods can obtain a better performance over the state-of-the-art algorithm selection methods.