Sex-specific evolution of a Drosophila sensory system via interacting cis- and trans-regulatory changes

The evolution of gene expression via cis-regulatory changes is well established as a major driver of phenotypic evolution. However, relatively little is known about the influence of enhancer architecture and intergenic interactions on regulatory evolution. We address this question by examining chemosensory system evolution in Drosophila. D. prolongata males show a massively increased number of chemosensory bristles compared to females and males of sibling species. This increase is driven by sex-specific transformation of ancestrally mechanosensory organs. Consistent with this phenotype, the Pox neuro transcription factor (Poxn), which specifies chemosensory bristle identity, shows expanded expression in D. prolongata males. Poxn expression is controlled by non-additive interactions among widely dispersed enhancers. Although some D. prolongata Poxn enhancers show increased activity, the additive component of this increase is slight, suggesting most changes in Poxn expression are due to epistatic interactions between Poxn enhancers and trans-regulatory factors. Indeed, the expansion of D. prolongata Poxn enhancer activity is only observed in cells that express doublesex (dsx), the gene that controls sexual differentiation in Drosophila and also shows increased expression in D. prolongata males due to cis-regulatory changes. Although expanded dsx expression may contribute to increased activity of D. prolongata Poxn enhancers, this interaction is not sufficient to explain the full expansion of Poxn expression, suggesting that cis-trans interactions between Poxn, dsx, and additional unknown genes are necessary to produce the derived D. prolongata phenotype. Overall, our results demonstrate the importance of epistatic gene interactions for evolution, particularly when pivotal genes have complex regulatory architecture.

Wavelet-based robust estimation and variable selection in nonparametric additive models

This article studies M-type estimators for fitting robust additive models in the presence of anomalous data. The components in the additive model are allowed to have different degrees of smoothness. We introduce a new class of wavelet-based robust M-type estimators for performing simultaneous additive component estimation and variable selection in such inhomogeneous additive models. Each additive component is approximated by a truncated series expansion of wavelet bases, making it feasible to apply the method to nonequispaced data and sample sizes that are not necessarily a power of 2. Sparsity of the additive components together with sparsity of the wavelet coefficients within each component (group), results into a bi-level group variable selection problem. In this framework, we discuss robust estimation and variable selection. A two-stage computational algorithm, consisting of a fast accelerated proximal gradient algorithm of coordinate descend type, and thresholding, is proposed. When using nonconvex redescending loss functions, and appropriate nonconvex penalty functions at the group level, we establish optimal convergence rates of the estimates. We prove variable selection consistency under a weak compatibility condition for sparse additive models. The theoretical results are complemented with some simulations and real data analysis, as well as a comparison to other existing methods.

COVID-19 Crisis as the New-State-of-the-Art in the Crimmigration Milieu

The concept of crimmigration connotes the currently prevailing approach between the different fields of penal, administrative and migration laws. It seems that, progressively, there is an amalgamation of penal law practices with those of civil and administrative law processes in a way creating confusion as to the boundaries of each law discipline and rational. In addition, the protection of public health from COVID-19 interrelates with the above three fields of law while at the same time the measures undertaken for the confrontation of the pandemic are further strengthening the social controls already imposed towards the migrant-refugee populations. Based on the Greek experience, we are particularly interested in mixed migration flows’ status of a ‘prolonged reception’. We have decided to examine the cases of the ‘asylum-seeker’ population and the ‘undocumented’ population who, to a large extent, constitute a large unseen category for the national vaccine program implemented to combat the COVID-19 hygiene crisis. The basic idea supported by our present study is that the health field is used as an additive component to crimmigration as it helps the establishment of a concrete screening intensifying the already imposed migration controls. In addition, the official social controls imposed to combat the COVD-19 health crisis contribute to crimmigration through the intensification of the dangerization of mixed migration flows. Currently, the health field, affected by COVID-19, contributes to the intensification of the crimmigration regime and at the same time to a dangerous cul-de-sac.

Generation Mean Analysis for Yield and Drought Tolerant Traits under Rainfed and Irrigated Conditions in Rice (Oryza sativa L.)

Generation mean analysis was carried out using two crosses, involving a high yielding drought susceptible variety NDR 359 and drought tolerant rainfed cultivars Nagina 22 and Vandana. Six generations namely P1, P2, F1, F2, BC1 and BC2 were grown under both rainfed and irrigated environment to study the gene action for various yield and drought tolerance traits. Scaling test revealed the presence of epistasis for most of the yield and drought tolerance traits in both the crosses. Hence, six parameter model was adopted for these traits and for few traits where epistasis was absent, three parameter model was used. The results revealed that dominance gene effect along with non-allelic interactions had profound effect on the genetic control of majority of the yield traits. Therefore, early generation selection will be misleading for these traits. However, the drought tolerance related traits like proline content and stomatal conductance were governed by additive component as well. Duplicate epistasis was observed for majority of the traits. Hence, present study indicates that, epistasis has a key role in the expression of almost all the traits in both the environment.

Detection of Epistasis and Genetic Parameters of Some Quantitative Traits Through Triple Test Cross Analysis in Chickpea (Cicer Arietinum L.)

Triple test cross analysis was carried out to detect the epistasis of thirteen yield and yield components in five chickpea (Cicer arietinum L.) crosses. Total epistatic effect was found to be non-significant for all the studied traits. Partitioning of total epistasis indicated the involvement of ‘i’ type (additive × additive) epistasis for DFF, PHFF, PWH, NPd/P, PdW/P, NS/P and SW/P in cross-1; NPBFF and NSBFF in cross-3 and for PHFF, DMF, PHMF and NSBMF in cross-5. The magnitude of additive component (D) was higher than that of the dominance component (H). Partial degree of dominance (√H/D) was observed for most of the traits. Both broad (h2b) and narrow (h2n) sense heritability were found to be moderately high. Positive and significant correlation between sums and differences indicated the direction of dominance towards decreasing parents and vice-versa. Bangladesh J. Bot. 50(2): 351-358, 2021 (June)

Breeding Resistance for Post Flowering Stalk rot (Macrophomina phaseolina) in Maize Identification of Resistance against Post Flowering Stalk Rot (Macrophomina phaseolina) in Maize

Maize is one of the most important staple food crops in the World. However, the yields of maize have been affected by various fungal infestations. Post flowering stalk rot is one of the devastating diseases and so, we planned our study to order to identify suitable resistance maize genotypes against post flowering stalk rot (PFSR) complex caused by Macrophomina phaseolina through in-vivo screening and toothpick method for creating artificial epiphytotics. A total of 20 maize inbreds were screened and crossed in Line × Tester mating design (15 × 5) during Kharif 2019, Six resistant inbred lines were identified and generated the 75 F1s (SCHs) at MRC, ARI, Rajendranagar, Hyderabad. All these 20 parents and 75 F1s along with three checks were evaluated by raising the crop in disease sick plot accompanied by toothpick inoculation during Rabi, 2019-20, in a Randomized Block Design with two replications. The field screening of maize genotypes by the standard toothpick method which needs about 40 days for expression of plant drying symptoms due to PFSR and data are possible to record only at the time of crop harvesting using 1-9 rating scale of PFSR for scoring disease severity in-vivo condition by splitting the stem of each plant. As a result, most of the genotypes were exhibited disease reaction varying from resistant (score 2) to moderately resistant (score 5) against M. phaseolina. While studying the genetics of PFSR, we found that interaction of lines and testers were proportionally contributed towards resistant, and degree of dominance is preferably non-additive gene action, it shows that the magnitude of dominance was higher than additive effect indicating that PFSR resistance is largely governed by dominance effect i.e., non additive component is not fixable for resistance. It is also found that the resistant genotypes also exhibited highest significant positive heterosis and combining ability effects (GCA and SCA). A considerable yield reduction in grain yield (10.5 to 28.3%) over checks was observed in susceptible lines. Most of the genotypes were found resistant as the reduction in yield is low. Hybrids developed using such lines exhibited high yields which are promoted for extensive testing to know their stability before release as commercial hybrids.

Automatic Fruit Morphology Phenome and Genetic Analysis: An Application in the Octoploid Strawberry

Automatizing phenotype measurement will decisively contribute to increase plant breeding efficiency. Among phenotypes, morphological traits are relevant in many fruit breeding programs, as appearance influences consumer preference. Often, these traits are manually or semiautomatically obtained. Yet, fruit morphology evaluation can be enhanced using fully automatized procedures and digital images provide a cost-effective opportunity for this purpose. Here, we present an automatized pipeline for comprehensive phenomic and genetic analysis of morphology traits extracted from internal and external strawberry (Fragaria x ananassa) images. The pipeline segments, classifies, and labels the images and extracts conformation features, including linear (area, perimeter, height, width, circularity, shape descriptor, ratio between height and width) and multivariate (Fourier elliptical components and Generalized Procrustes) statistics. Internal color patterns are obtained using an autoencoder to smooth out the image. In addition, we develop a variational autoencoder to automatically detect the most likely number of underlying shapes. Bayesian modeling is employed to estimate both additive and dominance effects for all traits. As expected, conformational traits are clearly heritable. Interestingly, dominance variance is higher than the additive component for most of the traits. Overall, we show that fruit shape and color can be quickly and automatically evaluated and are moderately heritable. Although we study strawberry images, the algorithm can be applied to other fruits, as shown in the GitHub repository.

Additive Models of Single-tree Biomass Sensitive to Temperature and Precipitation in Eurasia – A Comparative Study for Larix spp. and Quercus spp.

In the context of current climate change, it is important to know the patterns characterising the response of forest trees to the dynamics of air temperature and precipitation. In this study, the first attempt to model changes of additive component composition of genera Larix spp. and Quercus spp. aboveground biomass according to Eurasian gradients of January’s mean temperature and annual mean precipitation is made, taking into account regional particularities of tree age and morphology structure. In the process of modelling, the database of single-tree biomass for forest-forming species in Eurasia is used. According to our results, the factors limiting the biomass of trees differ not only between the two tree genera but also between different components of biomass within the genus. In larches, the reaction of the biomass of all components to an increase in precipitation in cold zones is directly opposite in comparison with oaks, i.e. it decreases as precipitation increases. But in warm areas, the reactions of the two genera to increased precipitation coincide, i.e. precipitation does not affect the biomass of all components, both in larches and oaks. In wet areas, larch biomass components react to temperature increases in the opposite way, i.e. the aboveground and stem biomass increases, but the biomass of foliage and branches decreases. In dry areas, the reaction to the temperature of all larch and oak biomass components is unambiguous and opposite, i.e. there is a decrease in the larch biomass of all components as temperatures rise, and in oak biomass vice versa. This situation is discussed in terms of limiting factors.

Plasma Parameters and Etching Characteristics of SiOxNy Films in CF4 + O2 + X (X = C4F8 or CF2Br2) Gas Mixtures

In this work, we carried out the study of CF4 + O2 + X (X = C4F8 or CF2Br2) gas chemistries in respect to the SiOxNy reactive-ion etching process in a low power regime. The interest in the liquid CF2Br2 as an additive component is motivated by its generally unknown plasma etching performance. The combination of various diagnostic tools (double Langmuir probe, quadrupole mass-spectrometry, X-ray photoelectron spectroscopy) allowed us to compare the effects of CF4/X mixing ratio, input power and gas pressure on gas-phase plasma characteristics as well as to analyze the SiOxNy etching kinetics in terms of process-condition-dependent effective reaction probability. It was found that the given gas systems are characterized by: (1) similar changes in plasma parameters (electron temperature, ion current density) and fluxes of active species with variations in processing conditions; (2) identical behaviors of SiOxNy etching rates, as determined by the neutral-flux-limited process regime; and (3) non-constant SiOxNy + F reaction probabilities due to changes in the polymer deposition/removal balance. The features of CF4 + CF2Br2 + O2 plasma are lower polymerization ability (due to the lower flux of CFx radicals) and a bit more vertical etching profile (due to the lower neutral/charged ratio).

Automatic fruit morphology phenome and genetic analysis: An application in the octoploid strawberry

ABSTRACTAutomatizing phenotype measurement is needed to increase plant breeding efficiency. Morphological traits are relevant in many fruit breeding programs, as appearance influences consumer preference. Often, these traits are manually or semi-automatically obtained. Yet, fruit morphology evaluation can be boosted by resorting to fully automatized procedures and digital images provide a cost-effective opportunity for this purpose. Here, we present an automatized pipeline for comprehensive phenomic and genetic analysis of morphology traits extracted from internal and external strawberry images. The pipeline segments, classifies and labels the images, extracts conformation features, including linear (area, perimeter, height, width, circularity, shape descriptor, ratio between height and width) and multivariate (Fourier Elliptical components and Generalized Procrustes) statistics. Internal color patterns are obtained using an autoencoder to smooth out the image. In addition, we develop a variational autoencoder to automatically detect the most likely number of underlying shapes. Bayesian modeling is employed to estimate both additive and dominant effects for all traits. As expected, conformational traits are clearly heritable. Interestingly, dominance variance is higher than the additive component for most of the traits. Overall, we show that fruit shape and color can be quickly and automatically evaluated and is moderately heritable. Although we study the strawberry species, the algorithm can be applied to other fruits, as shown in the GitHub repository https://github.com/lauzingaretti/DeepAFS.