Matching structural densities from different biophysical origins with gain and bias

The registration of volumetric structures in real space involves geometric and density transformations that align a target map and a probe map in the best way possible. Many computational docking strategies exist for finding the geometric transformations that superimpose maps, but the problem of finding an optimal density transformation, for the purposes of difference calculations or segmentation, has received little attention in the literature. We report results based on simulated and experimental electron microscopy maps, showing that a single scale factor (gain) may be insufficient when it comes to minimizing the density discrepancy between an aligned target and probe. We propose an affine transformation, with gain and bias, that is parameterized by known surface isovalues and by an interactive centering of the “cancellation peak” in the surface thresholded difference map histogram. The proposed approach minimizes discrepancies across a wide range of interior densities. Owing to having only two parameters, it avoids overfitting and requires only minimal knowledge of the probe and target maps. The linear transformation also preserves phases and relative amplitudes in Fourier space. The histogram matching strategy was implemented in the newly revised volhist tool of the Situs package, version 2.6.     

Use of the EM algorithm to detect QTL affecting multiple-traits in an across half-sib family analysis

QTL detection experiments in livestock species commonly use the half-sib design. Each male is mated to a number of females, each female producing a limited number of progeny. Analysis consists of attempting to detect associations between phenotype and genotype measured on the progeny. When family sizes are limiting experimenters may wish to incorporate as much information as possible into a single analysis. However, combining information across sires is problematic because of incomplete linkage disequilibrium between the markers and the QTL in the population. This study describes formulæ for obtaining MLEs via the expectation maximization (EM) algorithm for use in a multiple-trait, multiple-family analysis. A model specifying a QTL with only two alleles, and a common within sire error variance is assumed. Compared to single-family analyses, power can be improved up to fourfold with multi-family analyses. The accuracy and precision of QTL location estimates are also substantially improved. With small family sizes, the multi-family, multi-trait analyses reduce substantially, but not totally remove, biases in QTL effect estimates. In situations where multiple QTL alleles are segregating the multi-family analysis will average out the effects of the different QTL alleles.     

Acoustic mapping using a multibeam echosounder reveals cold-water coral reefs and surrounding habitats

Multibeam surveys were carried out in four areas to the west of Scotland where the coral Lophelia pertusa had previously been recorded. Distinctive seabed mounds were found in one area; video images from the mounds showed coral reef formation, and grab samples recovered L. pertusa reef framework and rubble. Skeleton samples were dated to 3,800 years BP. Grab samples contained 123 species of fauna. The reef structures, termed the Mingulay Reef Complex, were identified as topographic mound-like structures from the bathymetric data and were also visible on the backscatter images. The location of the reefs coincides with Atlantic bottom waters, close to a primary productivity centre and mixing zone, in an area where currents are likely to be accelerated by rocky seafloor ridges. This study shows that multibeam echosounders are powerful tools to locate and map deep-water coral reefs irrespective of water depth. Electronic Supplementary Material Supplementary material is available for this article at and is accessible for authorized users.     

Soil CN ratio as a scalar parameter to predict nitrous oxide emissions

Forested histosols have been found in some cases to be major, and in other cases minor, sources of the greenhouse gas nitrous oxide (N₂O). In order to estimate the total national or global emissions of N₂O from histosols, scaling or mapping parameters that can separate low‐ and high‐emitting sites are needed, and should be included in soil databases. Based on interannual measurements of N₂O emissions from drained forested histosols in Sweden, we found a strong negative relationship between N₂O emissions and soil CN ratios (r²_adj=0.96, mean annual N₂O emission=ae^{(?b CN ratio)}). The same equation could be used to estimate the N₂O emissions from Finnish and German sites based on CN ratios in published data. We envisage that the correlation between N₂O emissions and CN ratios could be used to scale N₂O emissions from histosols determined at sampled sites to national levels. However, at low CN ratios (i.e. below 15–20) other parameters such as climate, pH and groundwater tables increase in importance as regulating factors affecting N₂O emissions.     

Identification and Validation of Molecular Markers Associated with Pachymetra Root Rot and Brown Rust Resistance in Sugarcane Using Map- and Association-based Approaches

Marker-assisted selection for traits that are difficult to screen for, such as resistance to many sugarcane diseases, has the potential to facilitate the development of improved cultivars in sugarcane. Pachymetra root rot (PRR) and brown rust resistance ratings were obtained over two years for 192 I1 progeny (progeny produced by two heterozygous, non-inbred parental lines) of a sugarcane (Saccharum spp. hybrid) cross between two elite sugarcane clones, Q117 and 74C42. Approximately 1000 single-dose markers, including microsatellite (SSR), amplified fragment length polymorphism (AFLP) and restriction fragment length polymorphism (RFLP) markers, were scored across the population and maps containing approximately 400 markers were constructed for each parent. At p ≤ 0.01, two genomic regions, one from the female Q117 map and a different region from the 74C42 male map, plus an unlinked bi-parental simplex marker (single-dose marker present in both parents) were identified as associated with PRR over both years of data collection. These regions explained between 6 and 16% of the phenotypic variation. An additional region was identified in the female map as associated with PRR at p ≤ 0.01 in one year and p ≤ 0.05 in the second year. This region explained between 4 and 8% of the phenotypic variation. For brown rust, two genomic regions, one from the female map and one from the male map, plus an unlinked marker from both maps, were identified as associated with brown rust resistance at p ≤ 0.01 over two years of phenotypic data. Each region explained between 7 and 18% of the phenotypic variation. Several additional regions were identified in both maps as associated with brown rust at p ≤ 0.01 in one year and p ≤ 0.05 in the second year. These regions also explained between 5 and 11% of the phenotypic variation. To validate these markers and determine whether they would be useful in alternative germplasm, markers from each genomic region associated with PRR or brown rust were screened across a set of 154 elite sugarcane clones; PRR and brown rust ratings were available for 131 and 72 of the clones, respectively. For PRR, three of the 6 markers tested remained significantly associated (p ≤ 0.01) with resistance ratings in the elite clone set. For brown rust, only one of the seven markers tested remained significantly associated (p ≤ 0.01) with resistance in the elite clone set, with one other marker associated at p ≤ 0.05. These results suggest that these markers could be broadly effective in selecting for PRR and/or brown rust resistance in sugarcane breeding programs.     

Quantitative Trait Loci Mapping of Leaf Morphological Traits and Chlorophyll Content in Cultivated Tetraploid Cotton

Genetic mapping provides a powerful tool for quantitative trait loci （QTL） analysis at the molecular level. A simple sequence repeat （SSR） genetic map containing 590 markers and a BCI population from two cultivated tetraploid cotton （Gossypium hirsutum L.） cultivars, namely TM-1 and Hai 7124 （G. barbadense L.）, were used to map and analyze QTL using the composite interval mapping （CIM） method. Thirty one QTLs, 10 for lobe length, 13 for lobe width, six for lobe angle, and two for leaf chlorophyll content, were detected on 15 chromosomes or linkage groups at logarithm of odds （LOD）≥2.0, of which 15 were found for leaf morphology at LOD≥3.0. The genetic effects of the QTL were estimated. These results are fundamental for marker-assisted selection （MAS） of these traits in tetraploid cotton breeding.     

水稻籼粳亚种间杂种低温花粉不育的QTL分析

为探明籼粳杂种低温花粉不育的遗传基础,以籼稻品种3037和粳型广亲和品种02428的F2分离群体进行了低温花粉不育的遗传分析。推迟播种后,F2群体各单株孕穗期的日平均温度为21～23℃,调查了F2群体各单株的花粉育性。利用108对SSR引物构建了包含157个F2单株,覆盖12条染色体的分子标记连锁图谱。该连锁图的总长度为1857．8cM,标记间平均距离为16．26cM,标记较均匀地分布在12条染色体上。采用区间作图法对F2群体花粉不育进行QTL分析,共检测到2个低温花粉不育QTLS,即qLTSPS2和qLTSPS5,分别位于第2、5染色体,其加性效应分别为0．021、0．045,显性效应分别为-0．246、-0．251,显性度分别为11．7和4．8,具有超显性效应．超显性是QTL作用的主要方式,这2个位点杂合基因型在低温环境下具有降低花粉育性的作用,分别解释表型变异的15．6％、11．9％。另外,两因素的方差分析表明这两个QTL之间不存在互作。     

矮泰引-3中半矮秆基因的分子定位

矮泰引-3的矮生性状受两对独立遗传的半矮秆基因控制,利用SSR标记将这两个矮秆基因分别定位到第1和第4染色体上。等位性测交的结果表明,位于第1染色体上的矮秆基因与sd1是等位的,所以仍然称其为sd1;而位于第4染色体上的矮秆基因是一个新基因,暂命名为sdt2。利用SSR标记将sd1定位于RM297、RM302和RM212的同一侧,而与OSR3共分离,它们之间的位置关系可能是RM297-RM302-RM212-OSR3-sd1,遗传距离分别为4．7cM、0cM、0．8cM和0cM,这与sd1在第1染色体长臂上的确切位置是基本一致的。利用已有的SSR标记和拓展的SSR标记将sdt2定位于SSR332、RM1305和RM5633、RM307、RM401之间,它们的排列位置可能是SSR332-RM1305-sdt2-RM5633-RM307-RM401,它们之间的遗传距离分别为11．6cM、3．8cM、0．4cM、0cM和0．4cM。     

Characterization of moorland vegetation and the prediction of bird abundance using remote sensing

Aims To characterize and identify upland vegetation composition and height from a satellite image, and assess whether the resulting vegetation maps are accurate enough for predictions of bird abundance. Location South‐east Scotland, UK. Methods Fine‐taxa vegetation data collected using point samples were used for a supervised classification of a Landsat 7 image, while linear regression was used to model vegetation height over the same image. Generalized linear models describing bird abundance were developed using field‐collected bird and vegetation data. The satellite‐derived vegetation data were substituted into these models and efficacy was examined. Results The accuracy of the classification was tested over both the training and a set of test plots, and showed that more common vegetation types could be predicted accurately. Attempts to estimate the heights of both dwarf shrub and graminoid vegetation from satellite data produced significant, but weak, correlations between observed and predicted height. When these outputs were used in bird abundance–habitat models, bird abundance predicted using satellite‐derived vegetation data was very similar to that obtained when the field‐collected data were used for one bird species, but poor estimates of vegetation height produced from the satellite data resulted in a poor abundance prediction for another. Conclusions This pilot study suggests that it is possible to identify moorland vegetation to a fine‐taxa level using point samples, and that it may be possible to derive information on vegetation height, although more appropriate field‐collected data are needed to examine this further. While remote sensing may have limitations compared with relatively fine‐scale fieldwork, when used at relatively large scales and in conjunction with robust bird abundance–habitat association models, it may facilitate the mapping of moorland bird abundance across large areas.