Genome‐wide detection of CNVs associated with beak deformity in chickens using high‐density 600K SNP arrays

Beak deformity (crossed beaks) is found in several indigenous chicken breeds including Beijing‐You studied here. Birds with deformed beaks have reduced feed intake and poor production performance. Recently, copy number variation (CNV) has been examined in many species and is recognized as a source of genetic variation, especially for disease phenotypes. In this study, to unravel the genetic mechanisms underlying beak deformity, we performed genome‐wide CNV detection using Affymetrix chicken high‐density 600K data on 48 deformed‐beak and 48 normal birds using penncnv . As a result, two and eight CNV regions (CNVRs) covering 0.32 and 2.45 Mb respectively on autosomes were identified in deformed‐beak and normal birds respectively. Further RT‐qPCR studies validated nine of the 10 CNVRs. The ratios of six CNVRs were significantly different between deformed‐beak and normal birds (P < 0.01). Within these six regions, three and 21 known genes were identified in deformed‐beak and normal birds respectively. Bioinformatics analysis showed that these genes were enriched in six GO terms and one KEGG pathway. Five candidate genes in the CNVRs were further validated using RT‐qPCR. The expression of LRIG2 (leucine rich repeats and immunoglobulin like domains 2) was lower in birds with deformed beaks (P < 0.01). Therefore, the LRIG2 gene could be considered a key factor in view of its known functions and its potential roles in beak deformity. Overall, our results will be helpful for future investigations of the genomic structural variations underlying beak deformity in chickens.     

NINJA-OPS: Fast Accurate Marker Gene Alignment Using Concatenated Ribosomes

The explosion of bioinformatics technologies in the form of next generation sequencing (NGS) has facilitated a massive influx of genomics data in the form of short reads. Short read mapping is therefore a fundamental component of next generation sequencing pipelines which routinely match these short reads against reference genomes for contig assembly. However, such techniques have seldom been applied to microbial marker gene sequencing studies, which have mostly relied on novel heuristic approaches. We propose NINJA Is Not Just Another OTU-Picking Solution (NINJA-OPS, or NINJA for short), a fast and highly accurate novel method enabling reference-based marker gene matching (picking Operational Taxonomic Units, or OTUs). NINJA takes advantage of the Burrows-Wheeler (BW) alignment using an artificial reference chromosome composed of concatenated reference sequences, the “concatesome,” as the BW input. Other features include automatic support for paired-end reads with arbitrary insert sizes. NINJA is also free and open source and implements several pre-filtering methods that elicit substantial speedup when coupled with existing tools. We applied NINJA to several published microbiome studies, obtaining accuracy similar to or better than previous reference-based OTU-picking methods while achieving an order of magnitude or more speedup and using a fraction of the memory footprint. NINJA is a complete pipeline that takes a FASTA-formatted input file and outputs a QIIME-formatted taxonomy-annotated BIOM file for an entire MiSeq run of human gut microbiome 16S genes in under 10 minutes on a dual-core laptop.     

The Optimal Solution of a Non-Convex State-Dependent LQR Problem and Its Applications

This paper studies a Non-convex State-dependent Linear Quadratic Regulator (NSLQR) problem, in which the control penalty weighting matrix in the performance index is state-dependent. A necessary and sufficient condition for the optimal solution is established with a rigorous proof by Euler-Lagrange Equation. It is found that the optimal solution of the NSLQR problem can be obtained by solving a Pseudo-Differential-Riccati-Equation (PDRE) simultaneously with the closed-loop system equation. A Comparison Theorem for the PDRE is given to facilitate solution methods for the PDRE. A linear time-variant system is employed as an example in simulation to verify the proposed optimal solution. As a non-trivial application, a goal pursuit process in psychology is modeled as a NSLQR problem and two typical goal pursuit behaviors found in human and animals are reproduced using different control weighting . It is found that these two behaviors save control energy and cause less stress over Conventional Control Behavior typified by the LQR control with a constant control weighting , in situations where only the goal discrepancy at the terminal time is of concern, such as in Marathon races and target hitting missions.     

Characterization of Flavin-Containing Opine Dehydrogenase from Bacteria

Opines, in particular nopaline and octopine, are specific compounds found in crown gall tumor tissues induced by infections with Agrobacterium species, and are synthesized by well-studied NAD(P)H-dependent dehydrogenases (synthases), which catalyze the reductive condensation of α-ketoglutarate or pyruvate with L-arginine. The corresponding genes are transferred into plant cells via a tumor-inducing (Ti) plasmid. In addition to the reverse oxidative reaction(s), the genes noxB-noxA and ooxB-ooxA are considered to be involved in opine catabolism as (membrane-associated) oxidases; however, their properties have not yet been elucidated in detail due to the difficulties associated with purification (and preservation). We herein successfully expressed Nox/Oox-like genes from Pseudomonas putida in P. putida cells. The purified protein consisted of different α-, β-, and γ-subunits encoded by the OdhA, OdhB, and OdhC genes, which were arranged in tandem on the chromosome (OdhB-C-A), and exhibited dehydrogenase (but not oxidase) activity toward nopaline in the presence of artificial electron acceptors such as 2,6-dichloroindophenol. The enzyme contained FAD, FMN, and [2Fe-2S]-iron sulfur as prosthetic groups. On the other hand, the gene cluster from Bradyrhizobium japonicum consisted of OdhB ₁ -C-A-B ₂, from which two proteins, OdhAB₁C and OdhAB₂C, appeared through the assembly of each β-subunit together with common α- and γ-subunits. A poor phylogenetic relationship was detected between OdhB₁ and OdhB₂ in spite of them both functioning as octopine dehydrogenases, which provided clear evidence for the acquisition of novel functions by “subunit-exchange”. To the best of our knowledge, this is the first study to have examined flavin-containing opine dehydrogenase.