Genomic tools and selective breeding in molluscs

This review of genetic resources and selective breeding in molluscs was carried out as part of the European Marine Biological Research Infrastructure Cluster (EMBRIC) project funded by the European Union's Horizon 2020 research and innovation program under grant agreement No 654008.The production of most farmed molluscs, including mussels, oysters, scallops, abalone, and clams, is heavily dependent on natural seed from the plankton. Closing the lifecycle of species in hatcheries can secure independence from wild stocks and enables long-term genetic improvement of broodstock through selective breeding. Genomic techniques have the potential to revolutionize hatchery-based selective breeding by improving our understanding of the characteristics of mollusc genetics that can pose a challenge for intensive aquaculture and by providing a new suite of tools for genetic improvement. Here we review characteristics of the life history and genetics of molluscs including high fecundity, self-fertilization, high genetic diversity, genetic load, high incidence of deleterious mutations and segregation distortion and critically assess their impact on the design and effectiveness of selective breeding strategies. A survey of the results of current breeding programs in the literature show that selective breeding with inbreeding control is likely the best strategy for genetic improvement of most molluscs, and on average growth rate can be improved by 10% per generation and disease resistance by 15% per generation across the major farmed species by implementing individual or family-based selection. Rapid advances in sequencing technology have resulted in a wealth of genomic resources for key species with the potential to greatly improve hatchery-based selective breeding of molluscs. In this review, we catalogue the range of genomic resources currently available for molluscs of aquaculture interest and discuss the bottlenecks, including lack of high-quality reference genomes and the relatively high cost of genotyping, as well as opportunities for applying genomics-based selection.Publisher PDFPeer reviewe

Genomic Tools and Selective Breeding in Molluscs

The production of most farmed molluscs, including mussels, oysters, scallops, abalone, and clams, is heavily dependent on natural seed from the plankton. Closing the lifecycle of species in hatcheries can secure independence from wild stocks and enables long-term genetic improvement of broodstock through selective breeding. Genomic techniques have the potential to revolutionize hatchery-based selective breeding by improving our understanding of the characteristics of mollusc genetics that can pose a challenge for intensive aquaculture and by providing a new suite of tools for genetic improvement. Here we review characteristics of the life history and genetics of molluscs including high fecundity, self-fertilization, high genetic diversity, genetic load, high incidence of deleterious mutations and segregation distortion, and critically assess their impact on the design and effectiveness of selective breeding strategies. A survey of the results of current breeding programs in the literature show that selective breeding with inbreeding control is likely the best strategy for genetic improvement of most molluscs, and on average growth rate can be improved by 10% per generation and disease resistance by 15% per generation across the major farmed species by implementing individual or family-based selection. Rapid advances in sequencing technology have resulted in a wealth of genomic resources for key species with the potential to greatly improve hatchery-based selective breeding of molluscs. In this review, we catalog the range of genomic resources currently available for molluscs of aquaculture interest and discuss the bottlenecks, including lack of high-quality reference genomes and the relatively high cost of genotyping, as well as opportunities for applying genomics-based selection

These aren’t the loci you’re looking for: Principles of effective SNP filtering for molecular ecologists

Sequencing reduced‐representation libraries of restriction site‐associated DNA (RADseq) to identify single nucleotide polymorphisms (SNPs) is quickly becoming a standard methodology for molecular ecologists. Because of the scale of RADseq data sets, putative loci cannot be assessed individually, making the process of filtering noise and correctly identifying biologically meaningful signal more difficult. Artefacts introduced during library preparation and/or bioinformatic processing of SNP data can create patterns that are incorrectly interpreted as indicative of population structure or natural selection. Therefore, it is crucial to carefully consider types of errors that may be introduced during laboratory work and data processing, and how to minimize, detect and remove these errors. Here, we discuss issues inherent to RADseq methodologies that can result in artefacts during library preparation and locus reconstruction resulting in erroneous SNP calls and, ultimately, genotyping error. Further, we describe steps that can be implemented to create a rigorously filtered data set consisting of markers accurately representing independent loci and compare the effect of different combinations of filters on four RAD data sets. At last, we stress the importance of publishing raw sequence data along with final filtered data sets in addition to detailed documentation of filtering steps and quality control measures

2014 dDocent: a RADseq, variantcalling pipeline designed for population genomics of non-model organisms

ABSTRACT 14 Restriction-site associated DNA sequencing (RADseq) has become a powerful and useful 15 approach for population genomics. Currently, no software exists that utilizes both paired-end 16 reads from RADseq data to efficiently produce population-informative variant calls, 17 especially for organisms with large effective population sizes and high levels of genetic 18 polymorphism but for which no genomic resources exist. dDocent is an analysis pipeline with 19 a user-friendly, command-line interface designed to process individually barcoded RADseq 20 data (with double cut sites) into informative SNPs/INDELs for population-level analyses. The 21 pipeline, written in BASH, uses data reduction techniques and other stand-alone software 22 packages to perform quality trimming and adapter removal, de novo assembly of RAD loci, 23 read mapping, SNP and INDEL calling, and baseline data filtering. Double-digest RAD data 24 from population pairings of three different marine fishes were used to compare dDocent with 25 Stacks, the first generally available, widely used pipeline for analysis of RADseq data. 26 dDocent consistently identified more SNPs shared across greater numbers of individuals and 27 with higher levels of coverage. This is most likely due to the fact that dDocent quality trims 28 instead of filtering and incorporates both forward and reverse reads in assembly, mapping, 29 and SNP calling, thus enabling use of reads with INDEL polymorphisms. The pipeline and a 30 comprehensive user guide can be found at (http://dDocent.wordpress.com). 31 32 PeerJ PrePrints | http://dx.doi.org/10.7287/peerj.preprints.314v1 | CC-BY 4.

Model for Screened, Charge-Regulated Electrostatics of an Eye Lens Protein: Bovine GammaB-Crystallin

We model screened, site-specific charge regulation of the eye lens protein bovine gammaB-crystallin (γB) and study the probability distributions of its proton occupancy patterns. Using a simplified dielectric model, we solve the linearized Poisson-Boltzmann equation to calculate a 54 × 54 work-of-charging matrix, each entry being the modeled voltage at a given titratable site, due to an elementary charge at another site. The matrix quantifies interactions within patches of sites, including γB charge pairs. We model intrinsic pK values that would occur hypothetically in the absence of other charges, with use of experimental data on the dependence of pK values on aqueous solution conditions, the dielectric model, and literature values. We use Monte Carlo simulations to calculate a model grand-canonical partition function that incorporates both the work-of-charging and the intrinsic pK values for isolated γB molecules and we calculate the probabilities of leading proton occupancy configurations, for 4 \u3c pH \u3c 8 and Debye screening lengths from 6 to 20 A. We select the interior dielectric ˚ value to model γB titration data. At pH 7.1 and Debye length 6.0 A, on a given ˚ γB molecule the predicted top occupancy pattern is present nearly 20% of the time, and 90% of the time one or another of the first 100 patterns will be present. Many of these occupancy patterns differ in net charge sign as well as in surface voltage profile. We illustrate how charge pattern probabilities deviate from the multinomial distribution that would result from use of effective pK values alone and estimate the extents to which γB charge pattern distributions broaden at lower pH and narrow as ionic strength is lowered. These results suggest that for accurate modeling of orientation-dependent γB-γB interactions, consideration of numerous pairs of proton occupancy patterns will be needed

Feeding Nucleotides with Corn Germ Meal or Dried Corn Distillers Grains Does Not Promote Growth Performance of Receiving and Growing Calves

Corn germ meal is often used in swine and poultry diets, but very little information exists on the effects on beef cattle and on newly arrived stressed cattle. When formulating receiving and growing diets, calf health and stress are important factors to consider. Including nucleotides, an immune-boosting feed additive may aid in gastrointestinal health of an animal and furthermore improve growth performance. The objective of these experiments was to determine: 1) the effects of corn germ meal in comparison to dried corn distillers grains on growth performance and 2) the effects of nucleotides on growth performance, by receiving and growing cattle

The crossroads of evidence-based medicine and health policy: implications for urology

As healthcare spending in the United States continues to rise at an unsustainable rate, recent policy decisions introduced at the national level will rely on precepts of evidence-based medicine to promote the determination, dissemination, and delivery of “best practices” or quality care while simultaneously reducing cost. We discuss the influence of evidence-based medicine on policy and, in turn, the impact of policy on the developing clinical evidence base with an eye to the potential effects of these relationships on the practice and provision of urologic care

Factors Associated with Revision Surgery after Internal Fixation of Hip Fractures

Background: Femoral neck fractures are associated with high rates of revision surgery after management with internal fixation. Using data from the Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trial evaluating methods of internal fixation in patients with femoral neck fractures, we investigated associations between baseline and surgical factors and the need for revision surgery to promote healing, relieve pain, treat infection or improve function over 24 months postsurgery. Additionally, we investigated factors associated with (1) hardware removal and (2) implant exchange from cancellous screws (CS) or sliding hip screw (SHS) to total hip arthroplasty, hemiarthroplasty, or another internal fixation device. Methods: We identified 15 potential factors a priori that may be associated with revision surgery, 7 with hardware removal, and 14 with implant exchange. We used multivariable Cox proportional hazards analyses in our investigation. Results: Factors associated with increased risk of revision surgery included: female sex, [hazard ratio (HR) 1.79, 95% confidence interval (CI) 1.25-2.50; P = 0.001], higher body mass index (fo