Proceedings of the First International Conference on Phylogenomics. March 15-19, 2006. Quebec, Canada

Phylogenomic analyses of nuclear genes reveal the evolutionary relationships within the BEP clade and the evidence of positive selection in Poaceae

BEP clade of the grass family (Poaceae) is composed of three subfamilies, i.e. Bambusoideae, Ehrhartoideae, and Pooideae. Controversies on the phylogenetic relationships among three subfamilies still persist in spite of great efforts. However, previous evidence was mainly provided from plastid genes with only a few nuclear genes utilized. Given different evolutionary histories recorded by plastid and nuclear genes, it is indispensable to uncover their relationships based on nuclear genes. Here, eleven species with whole-sequenced genome and six species with transcriptomic data were included in this study. A total of 121 one-to-one orthologous groups (OGs) were identified and phylogenetic trees were reconstructed by different tree-building methods. Genes which might have undergone positive selection and played important roles in adaptive evolution were also investigated from 314 and 173 one-to-one OGs in two bamboo species and 14 grass species, respectively. Our results support the ((B, P) E) topology with high supporting values. Besides, our findings also indicate that 24 and nine orthologs with statistically significant evidence of positive selection are mainly involved in abiotic and biotic stress response, reproduction and development, plant metabolism and enzyme etc. from two bamboo species and 14 grass species, respectively. In summary, this study demonstrates the power of phylogenomic approach to shed lights on the evolutionary relationships within the BEP clade, and offers valuable insights into adaptive evolution of the grass family.

Determination of Genetic Diversity among Korean Hanwoo Cattle Based on Physical Characteristics

This study was conducted to establish genetic criteria for phenotypic characteristics of Hanwoo cattle based on allele frequencies and genetic variance analysis using microsatellite markers. Analysis of the genetic diversity among 399 Hanwoo cattle classified according to nose pigmentation and coat color was carried out using 22 microsatellite markers. The results revealed that the INRA035 locus was associated with the highest Fis (0.536). Given that the Fis value for the Hanwoo INRA035 population ranged from 0.533 (white) to 1.000 (white spotted), this finding was consistent with the loci being fixed in Hanwoo cattle. Expected heterozygosities of the Hanwoo groups classified by coat colors and degree of nose pigmentation ranged from 0.689±0.023 (Holstein) to 0.743±0.021 (nose pigmentation level of d). Normal Hanwoo and animals with a mixed white coat showed the closest relationship because the lowest DA value was observed between these groups. However, a pair-wise differentiation test of Fst showed no significant difference among the Hanwoo groups classified by coat color and degree of nose pigmentation (p<0.01). Moreover, results of the neighbor-joining tree based on a DA genetic distance matrix within 399 Hanwoo individuals and principal component analyses confirmed that different groups of cattle with mixed coat color and nose pigmentation formed other specific groups representing Hanwoo genetic and phenotypic characteristics. The results of this study support a relaxation of policies regulating bull selection or animal registration in an effort to minimize financial loss, and could provide basic information that can be used for establishing criteria to classify Hanwoo phenotypes.

Computation and Analysis of Genomic Multi-Sequence Alignments

Multi-sequence alignments of large genomic regions are at the core of many computational genome-annotation approaches aimed at identifying coding regions, RNA genes, regulatory regions, and other functional features. Such alignments also underlie many genome-evolution studies. Here we review recent computational advances in the area of multi-sequence alignment, focusing on methods suitable for aligning whole vertebrate genomes. We introduce the key algorithmic ideas in use today, and identify publicly available resources for computing, accessing, and visualizing genomic alignments. Finally, we describe the latest alignment-based approaches to identify and characterize various types of functional sequences. Key areas of research are identified and directions for future improvements are suggested.