Qiongzhou University

About: Qiongzhou University is a education organization based out in Sanya, China. It is known for research contribution in the topics: Gene & Electron capture. The organization has 611 authors who have published 603 publications receiving 3262 citations.

Comprehensive phylogeny of ray-finned fishes (Actinopterygii) based on transcriptomic and genomic data.

Abstract: Our understanding of phylogenetic relationships among bony fishes has been transformed by analysis of a small number of genes, but uncertainty remains around critical nodes. Genome-scale inferences so far have sampled a limited number of taxa and genes. Here we leveraged 144 genomes and 159 transcriptomes to investigate fish evolution with an unparalleled scale of data: >0.5 Mb from 1,105 orthologous exon sequences from 303 species, representing 66 out of 72 ray-finned fish orders. We apply phylogenetic tests designed to trace the effect of whole-genome duplication events on gene trees and find paralogy-free loci using a bioinformatics approach. Genome-wide data support the structure of the fish phylogeny, and hypothesis-testing procedures appropriate for phylogenomic datasets using explicit gene genealogy interrogation settle some long-standing uncertainties, such as the branching order at the base of the teleosts and among early euteleosts, and the sister lineage to the acanthomorph and percomorph radiations. Comprehensive fossil calibrations date the origin of all major fish lineages before the end of the Cretaceous.

MOMMOP: Multiobjective Optimization for Locating Multiple Optimal Solutions of Multimodal Optimization Problems

Abstract: In the field of evolutionary computation, there has been a growing interest in applying evolutionary algorithms to solve multimodal optimization problems (MMOPs). Due to the fact that an MMOP involves multiple optimal solutions, many niching methods have been suggested and incorporated into evolutionary algorithms for locating such optimal solutions in a single run. In this paper, we propose a novel transformation technique based on multiobjective optimization for MMOPs, called MOMMOP. MOMMOP transforms an MMOP into a multiobjective optimization problem with two conflicting objectives. After the above transformation, all the optimal solutions of an MMOP become the Pareto optimal solutions of the transformed problem. Thus, multiobjective evolutionary algorithms can be readily applied to find a set of representative Pareto optimal solutions of the transformed problem, and as a result, multiple optimal solutions of the original MMOP could also be simultaneously located in a single run. In principle, MOMMOP is an implicit niching method. In this paper, we also discuss two issues in MOMMOP and introduce two new comparison criteria. MOMMOP has been used to solve 20 multimodal benchmark test functions, after combining with nondominated sorting and differential evolution. Systematic experiments have indicated that MOMMOP outperforms a number of methods for multimodal optimization, including four recent methods at the 2013 IEEE Congress on Evolutionary Computation, four state-of-the-art single-objective optimization based methods, and two well-known multiobjective optimization based approaches.

An integrated genetic linkage map of cultivated peanut (Arachis hypogaea L.) constructed from two RIL populations.

Abstract: Construction and improvement of a genetic map for peanut (Arachis hypogaea L.) continues to be an important task in order to facilitate quantitative trait locus (QTL) analysis and the development of tools for marker-assisted breeding. The objective of this study was to develop a comparative integrated map from two cultivated × cultivated recombinant inbred line (RIL) mapping populations and to apply in mapping Tomato spotted wilt virus (TSWV) resistance trait in peanut. A total of 4,576 simple sequence repeat (SSR) markers from three sources: published SSR markers, newly developed SSR markers from expressed sequence tags (EST) and from bacterial artificial chromosome end-sequences were used for screening polymorphisms. Two cleaved amplified polymorphic sequence markers were also included to differentiate ahFAD2A alleles and ahFAD2B alleles. A total of 324 markers were anchored on this integrated map covering 1,352.1 cM with 21 linkage groups (LGs). Combining information from duplicated loci between LGs and comparing with published diploid maps, seven homoeologous groups were defined and 17 LGs (A1–A10, B1–B4, B7, B8, and B9) were aligned to corresponding A-subgenome or B-subgenome of diploid progenitors. One reciprocal translocation was confirmed in the tetraploid-cultivated peanut genome. Several chromosomal rearrangements were observed by comparing with published cultivated peanut maps. High consistence with cultivated peanut maps derived from different populations may support this integrated map as a reliable reference map for peanut whole genome sequencing assembling. Further two major QTLs for TSWV resistance were identified for each RILs, which illustrated the application of this map.