Characterization of the complete mitochondrial genome of Cerogria popularis Borchmann, 1936 (Coleoptera: Tenebrionidae).

In this study, we sequenced the complete mitochondrial genome (mitogenome) of Cerogria popularis Borchmann, 1936 based on the Illumina platform. The circular DNA molecule is 16,175 bp in size, including the 37 typical animal mitochondrial genes and a non-coding control region. All 37 genes are arranged in the same order as the previously reported most mitogenomes of Tenebrionidae. All PCGs initiate with standard start codon ATN (ATA/T/G/C) except cox1 with the special start codon AAT. Most PCGs terminate with TAA/G, whereas cox1, atp6, nad5, and nad4 end with its incomplete form T-. All the 22 tRNAs have the typical clover-leaf structure except for trnS1. The rrnL and rrnS genes are 1,250 and 737 bp in length, with an AT content of 82.6 and 84.5%, respectively. The phylogenetic tree supports the monophyly of the included tenebrionid subfamilies represented by more than one species. Furthermore, the sister relationship between Lagriinae and other tenebrionid subfamilies is recovered.

The first complete mitochondrial genome of Matsucoccidae (Hemiptera, Coccoidea) and implications for its phylogenetic position.

The mitochondrial genome (mitogenome) has been extensively used to better understand the phylogenetic relationships within the hemipteran suborder Sternorrhyncha, but sequenced mitogenomes remain unavailable for the entire family Matsucoccidae to date. To address this, here we sequenced the complete mitogenome of Matsucoccusmatsumurae; the first for this family. The mitogenome is 15,360 bp in size and comprises the typical set of 37 mitochondrial genes and a large non-coding region (AT-rich region). Gene order, nucleotide composition and codon usage of protein-coding genes (PCGs) of M.matsumurae differ considerably from those of the other two sequenced Coccidae species. All PCGs were initiated by the ATN start codons and ended with the TAA/G or single T-- stop codons. Nine transfer RNA genes could be folded into typical clover-leaf secondary structures. The length and AT content of the ribosomal RNA genes are highly conserved in the Coccoidea mitogenomes. In contrast, the AT-rich control region is highly variable in size and in the number of tandem repeats. The sliding window analysis showed that the cox1 gene is the most conserved amongst the 13 PCGs, while the ratios of non-synonymous to synonymous substitution rates indicated that the evolution of this mitogenome has been dominated by positive selection. Phylogenetic analyses, based on nucleotide sequence data of 37 mitochondrial genes and amino acid sequence data of 13 PCGs using Bayesian Inference and Maximum Likelihood methods, showed that Matsucoccidae diverged before the Coccidae.

Using triallelic SNPs for determining parentage in North American yak ( Bos grunniens) and estimating cattle ( B. taurus) introgression.

Background: Genetic testing for pedigree accuracy is critical for managing genetic diversity in North American (NA) yak ( Bos grunniens), a population expanded mostly from imported zoological park specimens.  DNA testing also enhances species conservation by identifying recent B. taurus F1 hybrid ancestors (within three generations).  Biallelic single nucleotide polymorphisms (SNPs) can accomplish either task, but increases the marker count and costs necessary to achieve both.  Our aim was to identify novel, multifunctional, triallelic yak SNPs (tySNPs), with each having two alleles for yak parentage testing, and a third allele for identifying recent cattle introgression.  Methods:  Genome sequences were aligned to the cattle UMD3.1 assembly and SNPs were screened for 1) heterozygosity in a NA and a Chinese yak, 2) a third allele at high frequency in cattle, and 3) flanking sequences conserved in both species.  Subsequently, tySNPs were filtered for unique alignment to the haplotype-resolved F1 yak assembly.  Allele frequencies were estimated in a subset of 87 tySNPs by genotyping 170 NA yak. Results:  We identified 610 autosomal tySNPs, distributed in 441 clusters with 5 Mb average genome spacing.  The average NA yak minor allele frequency was high (0.296), while average introgressed cattle alleles were low (0.004).  In simulations with tySNPs, 28 were sufficient for globally-unique animal identification (P I=5.81x10 -12), 87 were able to exclude 19 random bulls from parentage at the 99% level without using the dam's genotype (P E=5.3x10 -4), and 87 were able to detect F1 hybridization events after three generations of yak backcrosses (1/16th B. taurus germplasm). Conclusions:  Identifying animals, determining parentage and detecting recent hybridization events was efficient with as few as 87 tySNPs.  A similar triallelic approach could be used with other bottlenecked Bos species that hybridize with cattle, such as NA plains bison ( B. bison).

Using diverse U.S. beef cattle genomes to identify missense mutations in EPAS1, a gene associated with pulmonary hypertension.

The availability of whole genome sequence (WGS) data has made it possible to discover protein variants in silico. However, existing bovine WGS databases do not show data in a form conducive to protein variant analysis, and tend to under represent the breadth of genetic diversity in global beef cattle. Thus, our first aim was to use 96 beef sires, sharing minimal pedigree relationships, to create a searchable and publicly viewable set of mapped genomes relevant for 19 popular breeds of U.S. cattle. Our second aim was to identify protein variants encoded by the bovine endothelial PAS domain-containing protein 1 gene ( EPAS1), a gene associated with pulmonary hypertension in Angus cattle. The identity and quality of genomic sequences were verified by comparing WGS genotypes to those derived from other methods. The average read depth, genotype scoring rate, and genotype accuracy exceeded 14, 99%, and 99%, respectively. The 96 genomes were used to discover four amino acid variants encoded by EPAS1 (E270Q, P362L, A671G, and L701F) and confirm two variants previously associated with disease (A606T and G610S). The six EPAS1 missense mutations were verified with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry assays, and their frequencies were estimated in a separate collection of 1154 U.S. cattle representing 46 breeds. A rooted phylogenetic tree of eight polypeptide sequences provided a framework for evaluating the likely order of mutations and potential impact of EPAS1 alleles on the adaptive response to chronic hypoxia in U.S. cattle. This public, whole genome resource facilitates in silico identification of protein variants in diverse types of U.S. beef cattle, and provides a means of translating WGS data into a practical biological and evolutionary context for generating and testing hypotheses.

Optimal Design of Low-Density SNP Arrays for Genomic Prediction: Algorithm and Applications.

Low-density (LD) single nucleotide polymorphism (SNP) arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for the optimal design of LD SNP chips. A multiple-objective, local optimization (MOLO) algorithm was developed for design of optimal LD SNP chips that can be imputed accurately to medium-density (MD) or high-density (HD) SNP genotypes for genomic prediction. The objective function facilitates maximization of non-gap map length and system information for the SNP chip, and the latter is computed either as locus-averaged (LASE) or haplotype-averaged Shannon entropy (HASE) and adjusted for uniformity of the SNP distribution. HASE performed better than LASE with ≤1,000 SNPs, but required considerably more computing time. Nevertheless, the differences diminished when >5,000 SNPs were selected. Optimization was accomplished conditionally on the presence of SNPs that were obligated to each chromosome. The frame location of SNPs on a chip can be either uniform (evenly spaced) or non-uniform. For the latter design, a tunable empirical Beta distribution was used to guide location distribution of frame SNPs such that both ends of each chromosome were enriched with SNPs. The SNP distribution on each chromosome was finalized through the objective function that was locally and empirically maximized. This MOLO algorithm was capable of selecting a set of approximately evenly-spaced and highly-informative SNPs, which in turn led to increased imputation accuracy compared with selection solely of evenly-spaced SNPs. Imputation accuracy increased with LD chip size, and imputation error rate was extremely low for chips with ≥3,000 SNPs. Assuming that genotyping or imputation error occurs at random, imputation error rate can be viewed as the upper limit for genomic prediction error. Our results show that about 25% of imputation error rate was propagated to genomic prediction in an Angus population. The utility of this MOLO algorithm was also demonstrated in a real application, in which a 6K SNP panel was optimized conditional on 5,260 obligatory SNP selected based on SNP-trait association in U.S. Holstein animals. With this MOLO algorithm, both imputation error rate and genomic prediction error rate were minimal.

Stable aqueous dispersion of ZnO quantum dots with strong blue emission via simple solution route.

The aqueous dispersion of ZnO quantum dots (QDs) with strong blue emission (quantum yield of 76%) was synthesized through a simple solution route. The water stability of such QDs is provided by the hydroxyl groups on their surface, and the strong blue emission is suggested to arise from the formation of surface ZnO/oleic acid complexes. Under irradiation, these complexes are thought to absorb the excitation light with 3.54 eV and then generate the blue emission with 2.82 eV.