Statistical methods of DNA sequence analysis: detection of intragenic recombination or gene conversion

Simple but exact statistical tests for detecting a cluster of associated nucleotide changes in DNA are presented. The tests are based on the linear distribution of a set of s sites among a total of n sites, where the s sites may be the variable sites, sites of insertion/deletion, or categorized in some other way. These tests are especially useful for detecting gene conversion and intragenic recombination in a sample of DNA sequences. In this case, the sites of interest are those that correspond to particular ways of splitting the sequences into two groups (e.g., sequences A and D vs. sequences B, C, and E-J). Each such split is termed a phylogenetic partition. Application of these methods to a well-documented case of gene conversion in human gamma-globin genes shows that sites corresponding to two of the three observed partitions are significantly clustered, whereas application to hominoid mitochondrial DNA sequences--among which no recombination is expected to occur--shows no evidence of such clustering. This indicates that clustering of partition-specific sites is largely due to intragenic recombination or gene conversion. Alternative hypotheses explaining the observed clustering of sites, such as biased selection or mutation, are discussed.      

Rapid screening for phenotype-genotype associations by linear transformations of genomic evaluations

Background

Currently, association studies are analysed using statistical mixed models, with marker effects estimated by a linear transformation of genomic breeding values. The variances of marker effects are needed when performing the tests of association. However, approaches used to estimate the parameters rely on a prior variance or on a constant estimate of the additive variance. Alternatively, we propose a standardized test of association using the variance of each marker effect, which generally differ among each other. Random breeding values from a mixed model including fixed effects and a genomic covariance matrix are linearly transformed to estimate the marker effects.

Results

The standardized test was neither conservative nor liberal with respect to type I error rate (false-positives), compared to a similar test using Predictor Error Variance, a method that was too conservative. Furthermore, genomic predictions are solved efficiently by the procedure, and the p-values are virtually identical to those calculated from tests for one marker effect at a time. Moreover, the standardized test reduces computing time and memory requirements.The following steps are used to locate genome segments displaying strong association. The marker with the highest − log(p-value) in each chromosome is selected, and the segment is expanded one Mb upstream and one Mb downstream of the marker. A genomic matrix is calculated using the information from those markers only, which is used as the variance-covariance of the segment effects in a model that also includes fixed effects and random genomic breeding values. The likelihood ratio is then calculated to test for the effect in every chromosome against a reduced model with fixed effects and genomic breeding values. In a case study with pigs, a significant segment from chromosome 6 explained 11% of total genetic variance.

Conclusions

The standardized test of marker effects using their own variance helps in detecting specific genomic regions involved in the additive variance, and in reducing false positives. Moreover, genome scanning of candidate segments can be used in meta-analyses of genome-wide association studies, as it enables the detection of specific genome regions that affect an economically relevant trait when using multiple populations.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-246) contains supplementary material, which is available to authorized users.     

Reproductive ecology of the female pink cusk-eel (Genypterus blacodes): evaluating differences between fishery management zones in the Chilean austral zone

The pink cusk-eel (Genypterus blacodes), a benthic-demersal fish confined to the southern hemisphere, supports an important commercial fishery in Chile where it is exploited over an extensive geographic area. Although the fishery was originally divided into a northern (41º28′–47º00′S) and southern (47º00′–57º00′S) zone for the purposes of fisheries management, recent studies have reported significant differences in life history parameters between these zones. Individuals from the southern zone reached larger asymptotic sizes and possessed higher survival rates compared to the northern zone. We estimate and compare the gonadosomatic index (GSI), shape of the maturity ogive, and length at 50 % maturity (L _50%) of female G. blacodes between management zones and across time using biological data collected from the industrial fleet between 1985 and 2009. Females in the northern zone had higher monthly mean GSI than females in the southern zone. Our analyses also revealed L _50% to be significantly higher in the southern zone than in the northern zone from 1985 to 2009. The significant differences in life-history traits between fishery management zones agree with the trade-offs predicted by Charnov’s life history theory. Together these results provide additional support for the hypothesis that two separate stocks exist and suggest that females from the northern zone have developed a life-history strategy, which favours early maturation and a proportionally greater investment in reproduction than females from the southern zone.     

Use of spatiotemporal analysis of laboratory submission data to identify potential outbreaks of new or emerging diseases in cattle in Great Britain

Background  

New and emerging diseases of livestock may impact animal welfare, trade and public health. Early detection of outbreaks can reduce the impact of these diseases by triggering control measures that limit the number of cases that occur. The aim of this study was to investigate whether prospective spatiotemporal methods could be used to identify outbreaks of new and emerging diseases in scanning surveillance data. SaTScan was used to identify clusters of unusually high levels of submissions where a diagnosis could not be reached (DNR) using different probability models and baselines. The clusters detected were subjected to a further selection process to reduce the number of false positives and a more detailed epidemiological analysis to ascertain whether they were likely to represent real outbreaks.     

Heavy metal concentrations in,and human health risk assessment of,three commercially valuable fish species in the lower Niger River,Nigeria

The concentrations of Fe, Mn, Ni, Pb and V in water, sediment and the gill, liver and muscle tissues of Synodontis resupinatus, Heterotis niloticus and Clarias gariepinus, all commercially important fish species of the lower Niger River, were investigated in 2015. Water, sediment and fish samples were collected for six months and heavy metals were determined using an Atomic Absorption Spectrometer. Fe ranked highest in water and sediment, with concentrations of 2.74 mg l^?1 and 61.60 mg kg^?1, respectively. Metals followed the magnitude of Fe > Mn > Ni > V > Pb in the water and Fe > Mn > V > Ni > Pb in the sediments. Metal concentrations were higher in the tissues of S. resupinatus compared with H. niloticus and C. gariepinus. Fe was also highest in the gills, liver and muscle of the three fish species. Its highest concentration of 132.97 mg kg^?1 dry weight was recorded in the gills of S. resupinatus. Bioconcentration factors of metals ranged from 8.79 for Mn in H. niloticus muscle to 67.99 for Ni in S. resupinatus gills. The fish species studied pose no health risk for all metals studied, because the target hazard quotient was less than 1 and the estimated daily intakes of the metals were below the reference doses.