Bayesian analysis of linkage between genetic markers and quantitative trait loci. I. Prior knowledge

Summary Prior information on gene effects at individual quantitative trait loci (QTL) and on recombination rates between marker loci and QTL is derived. The prior distribution of QTL gene effects is assumed to be exponential with major effects less likely than minor ones. The prior probability of linkage between a marker and another single locus is a function of the number and length of chromosomes, and of the map function relating recombination rate to genetic distance among loci. The prior probability of linkage between a marker locus and a quantitative trait depends additionally on the number of detectable QTL, which may be determined from total additive genetic variance and minimum detectable QTL effect. The use of this prior information should improve linkage tests and estimates of QTL effects.     

Quantitative trait loci influencing protein and starch concentration in the Illinois Long Term Selection maize strains

A study was initiated to determine the number, chromosomal location, and magnitude of effect of QTL (quantitative trait loci or locus depending on context) controlling protein and starch concentration in the maize (Zea mays L.) kernel. Restriction fragment length polymorphism (RFLP) analysis was performed on 100 F₃ families derived from a cross of two strains, Illinois High Protein (IHP), X Illinois Low Protein (ILP), which had been divergently selected for protein concentration for 76 generations as part of the Illinois Long Term Selection Experiment. These families were analyzed for kernel protein and starch in replicated field trials during 1990 and 1991. A series of 90 genomic and cDNA clones distributed throughout the maize genome were chosen for their ability to detect RFLP between IHP and ILP. These clones were hybridized with DNA extracted from the 100 F₃ families, revealing 100 polymorphic loci. Single factor analysis of variance revealed significant QTL associations of many loci with both protein and starch concentration (P < 0.05 level). Twenty-two loci distributed on 10 chromosome arms were significantly associated with protein concentration, 19 loci on 9 chromosome arms were significantly associated with starch concentration. Sixteen of these loci were significant for both protein and starch concentration. Clusters of 3 or more significant loci were detected on chromosome arms 3L, 5S, and 7L for protein concentration, suggesting the presence of QTL with large effects at these locations. A QTL with large additive effects on protein and starch concentration was detected on chromosome arm 3L. RFLP alleles at this QTL were found to be linked with RFLP alleles at the Shrunken-2 (Sh2) locus, a structural gene encoding the major subunit of the starch synthetic enzyme ADP-glucose pyrophosphorylase. A multiple linear regression model consisting of 6 significant RFLP loci on different chromosomes explained over 64 % of the total variation for kernel protein concentration. Similar results were detected for starch concentration. Thus, several chromosomal regions with large effects may be responsible for a significant portion of the changes in kernel protein and starch concentration in the Illinois Long Term Selection Experiment.     

DNA fingerprint bands applied to linkage analysis with quantitative trait loci in chickens

Summary
An efficient approach to detect association between quantitative traits and bands of DNA fingerprint patterns uses intra-family tail analysis, which compares fingerprints of DNA mixes from individuals at the two tails of a phenotypic distribution. In analysis of 67 paternal half-sibs of a meat-type chicken family, of 57 sire bands generated by two probes, one sire-specific band (S6–6) was associated with abdominal fat deposition. The band effect was estimated by a linear model analysis to be 0–88 standard deviations, or about 30% of the family mean. The association between band S6–6 and abdominal fat was further examined by testing progeny of paternal half-sibs of the chickens which were used in the tail analysis, establishing genetic linkage between the DNA marker and a genetic locus affecting abdominal fat deposition.     

Human-modified landscapes driving the global primate extinction crisis

The world's primates have been severely impacted in diverse and profound ways by anthropogenic pressures. Here, we evaluate the impact of various infrastructures and human-modified landscapes on spatial patterns of primate species richness, at both global and regional scales. We overlaid the International Union for the Conservation of Nature (IUCN) range maps of 520 primate species and applied a global 100 km² grid. We used structural equation modeling and simultaneous autoregressive models to evaluate direct and indirect effects of six human-altered landscapes variables (i.e., human footprint [HFP], croplands [CROP], road density [ROAD], pasture lands [PAST], protected areas [PAs], and Indigenous Peoples' lands [IPLs]) on global primate species richness, threatened and non-threatened species, as well as on species with decreasing and non-decreasing populations. Two-thirds of all primate species are classified as threatened (i.e., Critically Endangered, Endangered, and Vulnerable), with ~86% experiencing population declines, and ~84% impacted by domestic or international trade. We found that the expansion of PAST, HFP, CROP, and road infrastructure had the most direct negative effects on primate richness. In contrast, forested habitat within IPLs and PAs was positively associated in safeguarding primate species diversity globally, with an even stronger effect at the regional level. Our results show that IPLs and PAs play a critical role in primate species conservation, helping to prevent their extinction; in contrast, HFP growth and expansion has a dramatically negative effect on primate species worldwide. Our findings support predictions that the continued negative impact of anthropogenic pressures on natural habitats may lead to a significant decline in global primate species richness, and likely, species extirpations. We advocate for stronger national and international policy frameworks promoting alternative/sustainable livelihoods and reducing persistent anthropogenic pressures to help mitigate the extinction risk of the world's primate species.     

Causal inference and large-scale expert validation shed light on the drivers of SDM accuracy and variance

Aim

To develop a causal understanding of the drivers of Species distribution model (SDM) performance.

Location

United Kingdom (UK).

Methods

We measured the accuracy and variance of SDMs fitted for 518 species of invertebrate and plant in the UK. Our measure of variance reflects variation among replicate model fits, and taxon experts assessed model accuracy. Using directed acyclic graphs, we developed a causal model depicting plausible effects of explanatory variables (e.g. species' prevalence, sample size) on SDM accuracy and variance and quantified those effects using a multilevel piecewise path model.

Results

According to our model, sample size and niche completeness (proportion of a species' niche covered by sampling) directly affect SDM accuracy and variance. Prevalence and range completeness have indirect effects mediated by sample size. Challenging conventional wisdom, we found that the effect of prevalence on SDM accuracy is positive. This reflects the facts that sample size has a positive effect on accuracy and larger sample sizes are possible for widespread species. It is possible, however, that the omission of an unobserved confounder biased this effect. Previous studies, which reported negative correlations between prevalence and SDM accuracy, conditioned on sample size.

Main conclusions

Our model explicates the causal basis of previously reported correlations between SDM performance and species/data characteristics. It also suggests that niche completeness has similarly large effects on SDM accuracy and variance as sample size. Analysts should consider niche completeness, or proxies thereof, in addition to sample size when deciding whether modelling is worthwhile.     

Three-dimensional species distribution modelling reveals the realized spatial niche for coral recruitment on contemporary Caribbean reefs

The three-dimensional structure of habitats is a critical component of species' niches driving coexistence in species-rich ecosystems. However, its influence on structuring and partitioning recruitment niches has not been widely addressed. We developed a new method to combine species distribution modelling and structure from motion, and characterized three-dimensional recruitment niches of two ecosystem engineers on Caribbean coral reefs, scleractinian corals and gorgonians. Fine-scale roughness was the most important predictor of suitable habitat for both taxa, and their niches largely overlapped, primarily due to scleractinians' broader niche breadth. Crevices and holes at mm scales on calcareous rock with low coral cover were more suitable for octocorals than for scleractinian recruits, suggesting that the decline in scleractinian corals is facilitating the recruitment of octocorals on contemporary Caribbean reefs. However, the relative abundances of the taxa were independent of the amount of suitable habitat on the reef, emphasizing that niche processes alone do not predict recruitment rates.     

一株C3形态多重耐药大肠杆菌噬菌体生物学特性和基因组分析

【目的】多重耐药菌的出现对公共卫生安全构成严重威胁,本研究分离多重耐药大肠杆菌噬菌体,研究其生物学特性和基因组特征,为耐药菌的噬菌体疗法提供理论依据。【方法】使用双层平板法从污水样本中分离纯化大肠杆菌噬菌体;磷钨酸染色后通过透射电镜观察形态;测定其宿主范围,测定温度和pH稳定性、一步生长曲线和体外抑菌效果等生物学特性;体内抑菌试验评估噬菌体对多重耐药大肠杆菌N1203-1Af感染的大蜡螟幼虫的保护作用;基于全基因组测序对其基因组特点进行分析。【结果】本研究分离共得到5株大肠杆菌噬菌体,分别命名为pEC-S163-2.1、pEC-S163-2.2、pEC-M1167-5Ar.1、pEC-m1291-2Dr.1和pEC-N1203-2Af.1;电镜结果显示噬菌体pEC-N1203-2Af.1属于短尾噬菌体中罕见的C3形态型,头部较长,长是宽的2–3倍;pEC-N1203-2Af.1可裂解受试15株大肠杆菌中的3株;感染10 min后进入指数增长期,–20-50℃、pH值为4.0–10.0的环境下均能够保持稳定活性;大蜡螟幼虫感染大肠杆菌N1203-2Af后噬菌体pEC-N1203-2Af....     

Comparison of conformational characteristics in structurally similar protein pairs.

Although it is known that three-dimensional structure is well conserved during the evolutionary development of proteins, there have been few studies that consider other parameters apart from divergence of the main-chain coordinates. In this study, we align the structures of 90 pairs of homologous proteins having sequence identities ranging from 5 to 100%. Their structures are compared as a function of sequence identity, including not only consideration of C alpha coordinates but also accessibility, Ooi numbers, secondary structure, and side-chain angles. We discuss how these properties change as the sequences become less similar. This will be of practical use in homology modeling, especially for modeling very distantly related or analogous proteins. We also consider how the average size and number of insertions and deletions vary as sequences diverge. This study presents further quantitative evidence that structure is remarkably well conserved in detail, as well as at the topological level, even when the sequences do not show similarity that is significant statistically.