Despite doubts about methods used and the association between vector density and dengue transmission, routine sampling of mosquito vector populations is common in dengue-endemic countries worldwide. ...This study examined the evidence from published studies for the existence of any quantitative relationship between vector indices and dengue cases.
From a total of 1205 papers identified in database searches following Cochrane and PRISMA Group guidelines, 18 were included for review. Eligibility criteria included 3-month study duration and dengue case confirmation by WHO case definition and/or serology. A range of designs were seen, particularly in spatial sampling and analyses, and all but 3 were classed as weak study designs. Eleven of eighteen studies generated Stegomyia indices from combined larval and pupal data. Adult vector data were reported in only three studies. Of thirteen studies that investigated associations between vector indices and dengue cases, 4 reported positive correlations, 4 found no correlation and 5 reported ambiguous or inconclusive associations. Six out of 7 studies that measured Breteau Indices reported dengue transmission at levels below the currently accepted threshold of 5.
There was little evidence of quantifiable associations between vector indices and dengue transmission that could reliably be used for outbreak prediction. This review highlighted the need for standardized sampling protocols that adequately consider dengue spatial heterogeneity. Recommendations for more appropriately designed studies include: standardized study design to elucidate the relationship between vector abundance and dengue transmission; adult mosquito sampling should be routine; single values of Breteau or other indices are not reliable universal dengue transmission thresholds; better knowledge of vector ecology is required.
Dense SNP genotypes are often combined with complex trait phenotypes to map causal variants, study genetic architecture and provide genomic predictions for individuals with genotypes but no ...phenotype. A single method of analysis that jointly fits all genotypes in a Bayesian mixture model (BayesR) has been shown to competitively address all 3 purposes simultaneously. However, BayesR and other similar methods ignore prior biological knowledge and assume all genotypes are equally likely to affect the trait. While this assumption is reasonable for SNP array genotypes, it is less sensible if genotypes are whole-genome sequence variants which should include causal variants.
We introduce a new method (BayesRC) based on BayesR that incorporates prior biological information in the analysis by defining classes of variants likely to be enriched for causal mutations. The information can be derived from a range of sources, including variant annotation, candidate gene lists and known causal variants. This information is then incorporated objectively in the analysis based on evidence of enrichment in the data. We demonstrate the increased power of BayesRC compared to BayesR using real dairy cattle genotypes with simulated phenotypes. The genotypes were imputed whole-genome sequence variants in coding regions combined with dense SNP markers. BayesRC increased the power to detect causal variants and increased the accuracy of genomic prediction. The relative improvement for genomic prediction was most apparent in validation populations that were not closely related to the reference population. We also applied BayesRC to real milk production phenotypes in dairy cattle using independent biological priors from gene expression analyses. Although current biological knowledge of which genes and variants affect milk production is still very incomplete, our results suggest that the new BayesRC method was equal to or more powerful than BayesR for detecting candidate causal variants and for genomic prediction of milk traits.
BayesRC provides a novel and flexible approach to simultaneously improving the accuracy of QTL discovery and genomic prediction by taking advantage of prior biological knowledge. Approaches such as BayesRC will become increasing useful as biological knowledge accumulates regarding functional regions of the genome for a range of traits and species.
A new technology called genomic selection is revolutionizing dairy cattle breeding. Genomic selection refers to selection decisions based on genomic breeding values (GEBV). The GEBV are calculated as ...the sum of the effects of dense genetic markers, or haplotypes of these markers, across the entire genome, thereby potentially capturing all the quantitative trait loci (QTL) that contribute to variation in a trait. The QTL effects, inferred from either haplotypes or individual single nucleotide polymorphism markers, are first estimated in a large reference population with phenotypic information. In subsequent generations, only marker information is required to calculate GEBV. The reliability of GEBV predicted in this way has already been evaluated in experiments in the United States, New Zealand, Australia, and the Netherlands. These experiments used reference populations of between 650 and 4,500 progeny-tested Holstein-Friesian bulls, genotyped for approximately 50,000 genome-wide markers. Reliabilities of GEBV for young bulls without progeny test results in the reference population were between 20 and 67%. The reliability achieved depended on the heritability of the trait evaluated, the number of bulls in the reference population, the statistical method used to estimate the single nucleotide polymorphism effects in the reference population, and the method used to calculate the reliability. A common finding in 3 countries (United States, New Zealand, and Australia) was that a straightforward BLUP method for estimating the marker effects gave reliabilities of GEBV almost as high as more complex methods. The BLUP method is attractive because the only prior information required is the additive genetic variance of the trait. All countries included a polygenic effect (parent average breeding value) in their GEBV calculation. This inclusion is recommended to capture any genetic variance not associated with the markers, and to put some selection pressure on low-frequency QTL that may not be captured by the markers. The reliabilities of GEBV achieved were significantly greater than the reliability of parental average breeding values, the current criteria for selection of bull calves to enter progeny test teams. The increase in reliability is sufficiently high that at least 2 dairy breeding companies are already marketing bull teams for commercial use based on their GEBV only, at 2 yr of age. This strategy should at least double the rate of genetic gain in the dairy industry. Many challenges with genomic selection and its implementation remain, including increasing the accuracy of GEBV, integrating genomic information into national and international genetic evaluations, and managing long-term genetic gain.
Achieving accurate genomic estimated breeding values for dairy cattle requires a very large reference population of genotyped and phenotyped individuals. Assembling such reference populations has ...been achieved for breeds such as Holstein, but is challenging for breeds with fewer individuals. An alternative is to use a multi-breed reference population, such that smaller breeds gain some advantage in accuracy of genomic estimated breeding values (GEBV) from information from larger breeds. However, this requires that marker-quantitative trait loci associations persist across breeds. Here, we assessed the gain in accuracy of GEBV in Jersey cattle as a result of using a combined Holstein and Jersey reference population, with either 39,745 or 624,213 single nucleotide polymorphism (SNP) markers. The surrogate used for accuracy was the correlation of GEBV with daughter trait deviations in a validation population. Two methods were used to predict breeding values, either a genomic BLUP (GBLUP_mod), or a new method, BayesR, which used a mixture of normal distributions as the prior for SNP effects, including one distribution that set SNP effects to zero. The GBLUP_mod method scaled both the genomic relationship matrix and the additive relationship matrix to a base at the time the breeds diverged, and regressed the genomic relationship matrix to account for sampling errors in estimating relationship coefficients due to a finite number of markers, before combining the 2 matrices. Although these modifications did result in less biased breeding values for Jerseys compared with an unmodified genomic relationship matrix, BayesR gave the highest accuracies of GEBV for the 3 traits investigated (milk yield, fat yield, and protein yield), with an average increase in accuracy compared with GBLUP_mod across the 3 traits of 0.05 for both Jerseys and Holsteins. The advantage was limited for either Jerseys or Holsteins in using 624,213 SNP rather than 39,745 SNP (0.01 for Holsteins and 0.03 for Jerseys, averaged across traits). Even this limited and nonsignificant advantage was only observed when BayesR was used. An alternative panel, which extracted the SNP in the transcribed part of the bovine genome from the 624,213 SNP panel (to give 58,532 SNP), performed better, with an increase in accuracy of 0.03 for Jerseys across traits. This panel captures much of the increased genomic content of the 624,213 SNP panel, with the advantage of a greatly reduced number of SNP effects to estimate. Taken together, using this panel, a combined breed reference and using BayesR rather than GBLUP_mod increased the accuracy of GEBV in Jerseys from 0.43 to 0.52, averaged across the 3 traits.
AIMS: The relationship of Atlantic salmon gastrointestinal (GI) tract bacteria to environmental factors, in particular water temperature within a commercial mariculture system, was investigated. ...METHODS AND RESULTS: Salmon GI tract bacterial communities commercially farmed in south‐eastern Tasmania were analysed, over a 13‐month period across a standard commercial production farm cycle, using 454 16S rRNA‐based pyrosequencing. Faecal bacterial communities were highly dynamic but largely similar between randomly selected fish. In postsmolt, the faecal bacteria population was dominated by Gram‐positive fermentative bacteria; however, by midsummer, members of the family Vibrionaceae predominated. As fish progressed towards harvest, a range of different bacterial genera became more prominent corresponding to a decline in Vibrionaceae. The sampled fish were fed two different commercial diet series with slightly different protein, lipid and digestible energy level; however, the effect of these differences was minimal. CONCLUSIONS: The overall data demonstrated dynamic hind gut communities in salmon that were related to season and fish growth phases but were less influenced by differences in commercial diets used routinely within the farm system studied. SIGNIFICANCE AND IMPACT OF THE STUDY: This study provides understanding of farmed salmon GI bacterial communities and describes the relative impact of diet, environmental and farm factors.
A group of strains with potent extracellular enzymic activity were isolated from the surfaces of the chain-forming sea-ice diatom Melosira and from an unidentified macrophyte collected from the ...Eastern Antarctic coastal zone. 16S rDNA sequence analysis indicated that the strains belonged to the genus Cellulophaga and showed greatest similarity to the species Cellulophaga baltica (sequence similarity 97%). Phenotypic characteristics, DNA base composition and DNA-DNA hybridization values clearly separate the Antarctic strains from Cellulophaga baltica and other Cellulophaga species. Thus, the strains form a distinct and novel species and have the proposed name Cellulophaga algicola sp. nov. (type strain IC166T = ACAM 630T). In addition, it was recognized that the species Cytophaga uliginosa (ZoBell and Upham 1944) Reichenbach 1989, a species phylogenetically remote from the type species of the genus Cytophaga, possessed 16S rDNA sequences and phenotypic and chemotaxonomic traits similar to those of other Cellulophaga species. Thus, it was proposed that the species Cytophaga uliginosa be renamed as Cellulophaga uliginosa comb. nov.
Using the Murchison Widefield Array (MWA), the low-frequency Square Kilometre Array precursor located in Western Australia, we have completed the GaLactic and Extragalactic All-sky MWA (GLEAM) ...survey, and present the resulting extragalactic catalogue, utilizing the first year of observations. The catalogue covers 24 831 square degrees, over declinations south of +30... and Galactic latitudes outside 10... of the Galactic plane, excluding some areas such as the Magellanic Clouds. It contains 307 455 radio sources with 20 separate flux density measurements across 72-231 MHz, selected from a time- and frequency-integrated image centred at 200 MHz, with a resolution of ...2 arcmin. Over the catalogued region, we estimate that the catalogue is 90 per cent complete at 170 mJy, and 50 per cent complete at 55 mJy, and large areas are complete at even lower flux density levels. Its reliability is 99.97 per cent above the detection threshold of 5..., which itself is typically 50 mJy. These observations constitute the widest fractional bandwidth and largest sky area survey at radio frequencies to date, and calibrate the low-frequency flux density scale of the southern sky to better than 10 per cent. This paper presents details of the flagging, imaging, mosaicking and source extraction/characterization, as well as estimates of the completeness and reliability. All source measurements and images are available online. This is the first in a series of publications describing the GLEAM survey results. (ProQuest: ... denotes formulae/symbols omitted.)
Feed makes up a large proportion of variable costs in dairying. For this reason, selection for traits associated with feed conversion efficiency should lead to greater profitability of dairying. ...Residual feed intake (RFI) is the difference between actual and predicted feed intakes and is a useful selection criterion for greater feed efficiency. However, measuring individual feed intakes on a large scale is prohibitively expensive. A panel of DNA markers explaining genetic variation in this trait would enable cost-effective genomic selection for this trait. With the aim of enabling genomic selection for RFI, we used data from almost 2,000 heifers measured for growth rate and feed intake in Australia (AU) and New Zealand (NZ) genotyped for 625,000 single nucleotide polymorphism (SNP) markers. Substantial variation in RFI and 250-d body weight (BW250) was demonstrated. Heritabilities of RFI and BW250 estimated using genomic relationships among the heifers were 0.22 and 0.28 in AU heifers and 0.38 and 0.44 in NZ heifers, respectively. Genomic breeding values for RFI and BW250 were derived using genomic BLUP and 2 Bayesian methods (BayesA, BayesMulti). The accuracies of genomic breeding values for RFI were evaluated using cross-validation. When 624,930 SNP were used to derive the prediction equation, the accuracies averaged 0.37 and 0.31 for RFI in AU and NZ validation data sets, respectively, and 0.40 and 0.25 for BW250 in AU and NZ, respectively. The greatest advantage of using the full 624,930 SNP over a reduced panel of 36,673 SNP (the widely used BovineSNP50 array) was when the reference population included only animals from either the AU or the NZ experiment. Finally, the Bayesian methods were also used for quantitative trait loci detection. On chromosome 14 at around 25 Mb, several SNP closest to PLAG1 (a gene believed to affect stature in humans and cattle) had an effect on BW250 in both AU and NZ populations. In addition, 8 SNP with large effects on RFI were located on chromosome 14 at around 35.7 Mb. These SNP may be associated with the gene NCOA2, which has a role in controlling energy metabolism.
ABSTRACT
We present the first asteroseismic results for δ Scuti and γ Doradus stars observed in Sectors 1 and 2 of the TESS mission. We utilize the 2-min cadence TESS data for a sample of 117 stars ...to classify their behaviour regarding variability and place them in the Hertzsprung–Russell diagram using Gaia DR2 data. Included within our sample are the eponymous members of two pulsator classes, γ Doradus and SX Phoenicis. Our sample of pulsating intermediate-mass stars observed by TESS also allows us to confront theoretical models of pulsation driving in the classical instability strip for the first time and show that mixing processes in the outer envelope play an important role. We derive an empirical estimate of 74 per cent for the relative amplitude suppression factor as a result of the redder TESS passband compared to the Kepler mission using a pulsating eclipsing binary system. Furthermore, our sample contains many high-frequency pulsators, allowing us to probe the frequency variability of hot young δ Scuti stars, which were lacking in the Kepler mission data set, and identify promising targets for future asteroseismic modelling. The TESS data also allow us to refine the stellar parameters of SX Phoenicis, which is believed to be a blue straggler.
Genome-wide association studies (GWAS) were used to discover genomic regions explaining variation in dairy production and fertility traits. Associations were detected with either single nucleotide ...polymorphism (SNP) markers or haplotypes of SNP alleles. An across-breed validation strategy was used to narrow the genomic interval containing causative mutations. There were 39,048 SNP tested in a discovery population of 780 Holstein sires and validated in 386 Holsteins and 364 Jersey sires. Previously identified mutations affecting milk production traits were confirmed. In addition, several novel regions were identified, including a putative quantitative trait loci for fertility on chromosome 18 that was detected only using haplotypes greater than 3 SNP long. It was found that the precision of quantitative trait loci mapping increased with haplotype length as did the number of validated haplotypes discovered, especially across breed. Promising candidate genes have been identified in several of the validated regions.
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