Variety Of Traits Research Articles

No general support for functional diversity enhancing resilience across terrestrial plant communities

AbstractAimUnderstanding the mechanisms promoting resilience in plant communities is crucial in times of increasing disturbance and global environmental change. Here, we present the first meta‐analysis evaluating the relationship between functional diversity and resilience of plant communities. Specifically, we tested whether the resilience of plant communities is positively correlated with interspecific trait variation (following the niche complementarity hypothesis) and the dominance of acquisitive and small‐size species (following the mass ratio hypothesis), and for the context‐dependent effects of ecological and methodological differences across studies.LocationGlobal.Time Period2004–2021.Major Taxa StudiedVascular plants.MethodsWe compiled a dataset of 69 independent sites from 26 studies that have quantified resilience. For each site, we calculated functional diversity indices based on the floristic composition and functional traits of the plant community (obtained from the TRY database) which we correlated with resilience of biomass and floristic composition. After transforming correlation coefficients to Fisher's Z‐scores, we conducted a hierarchical meta‐analysis, using a multilevel random‐effects model that accounted for the non‐independence of multiple effect sizes and the effects of ecological and methodological moderators.ResultsIn general, we found no positive functional diversity–resilience relationships of grand mean effect sizes. In contrast to our expectations, we encountered a negative relationship between resilience and trait variety, especially in woody ecosystems, whereas there was a positive relationship between resilience and the dominance of acquisitive species in herbaceous ecosystems. Finally, the functional diversity–resilience relationships were strongly affected by both ecological (biome and disturbance properties) and methodological (temporal scale, study design and resilience metric) characteristics.Main ConclusionsWe rejected our hypothesis of a general positive functional diversity–resilience relationship. In addition to strong context dependency, we propose that idiosyncratic effects of single resident species present in the communities before the disturbances and biological legacies could play major roles in the resilience of terrestrial plant communities.

Sustainable consumption futures: according to whom?

This article aims to uncover diverse perspectives regarding what sustainable consumption is and should be in the future. We draw upon and combine critical futures studies with recognitional justice. Futures studies enables inclusive approaches and divergence from current narratives of the future that are perceived as dominant. Recognitional justice allows for reflection upon who is usually not in the room when consumption futures are discussed. The article analyzes sustainable consumption-futures workshops held with four groups in Sweden. The first was with partners in a research program focusing on sustainable consumption. The second workshop enlisted elderly rural retirees, the third newly-arrived women from Syria and Eritrea, and the fourth high-income earners. A variety of traits in the discussions were noticeably influenced by the local context and backgrounds of the participants. Several issues brought up in the discussions dealt with issues that are on the political agenda in Sweden, such as circulating materials and more information and knowledge. There were also matters not on the political agenda such as eating a vegetarian diet, reducing consumption, and spending less time working. In addition, the newly-arrived women and, to some extent, the retirees, framed peace and ending the use of weapons as a vital element in sustainable consumption. This diversity and divergence highlights that, if it is to become relevant and inclusive, both research and policy need to recognize a multitude of perspectives and incorporate the distribution of power and critical futures perspectives to navigate a pathway toward consumption that is just and sustainable.

GENETIC CHARACTERIZATION AND POPULATION STRUCTURE BY iPBS MARKERS OF BOTTLE GOURD (Lagenaria siceraria) GENOTYPES

Bottle gourd (Lagenaria siceraria (Molina) Standl.) is a significant cucurbit plant species whose ripe fruits are consumed as ornamental items and immature fruits are consumed as vegetables. In addition, these plants are used as rootstocks in vegetable grafts due to their strong root structure. This study aimed to determine the genetic diversity of bottle gourd genotypes whose fresh fruits are consumed. Using iPBS (Inter-Primer Binding Site) retrotransposon marker techniques, a total of 186 bands in 30 genotypes were obtained and the polymorphism rate was calculated as 93.3%. Similarity coefficient values were found in the range of 0.35-0.96. Three main clusters emerged from cluster analysis. As a result of the structure analysis, genotypes were divided into four subpopulations. There was also a high level of genetic diversity among bottle gourd genotypes. To improve a variety's traits, genetic diversity can be used. The iPBS technique is also a powerful tool for understanding the genetic characterization of bottle gourd. These data can be used in breeding strategies to improve bottle gourd varieties. Keywords: Bottle Gourd, iPBS, Laneraria siceraria, molecular characterization, vegetable

Detection of trait-associated structural variations using short-read sequencing

Genomic structural variation (SV) affects genetic and phenotypic characteristics in diverse organisms, but the lack of reliable methods to detect SV has hindered genetic analysis. We developed a computational algorithm (MOPline) that includes missing call recovery combined with high-confidence SV call selection and genotyping using short-read whole-genome sequencing (WGS) data. Using 3,672 high-coverage WGS datasets, MOPline stably detected ∼16,000 SVs per individual, which is over ∼1.7-3.3-fold higher than previous large-scale projects while exhibiting a comparable level of statistical quality metrics. We imputed SVs from 181,622 Japanese individuals for 42 diseases and 60 quantitative traits. A genome-wide association study with the imputed SVs revealed 41 top-ranked or nearly top-ranked genome-wide significant SVs, including 8 exonic SVs with 5 novel associations and enriched mobile element insertions. This study demonstrates that short-read WGS data can be used to identify rare and common SVs associated with a variety of traits.

Signatures of Convergent Evolution and Natural Selection at the Alcohol Dehydrogenase Gene Region are Correlated with Agriculture in Ethnically Diverse Africans.

The alcohol dehydrogenase (ADH) family of genes encodes enzymes that catalyze the metabolism of ethanol into acetaldehyde. Nucleotide variation in ADH genes can affect the catalytic properties of these enzymes and is associated with a variety of traits, including alcoholism and cancer. Some ADH variants, including the ADH1B*48His (rs1229984) mutation in the ADH1B gene, reduce the risk of alcoholism and are under positive selection in multiple human populations. The advent of Neolithic agriculture and associated increase in fermented foods and beverages is hypothesized to have been a selective force acting on such variants. However, this hypothesis has not been tested in populations outside of Asia. Here, we use genome-wide selection scans to show that the ADH gene region is enriched for variants showing strong signals of positive selection in multiple Afroasiatic-speaking, agriculturalist populations from Ethiopia, and that this signal is unique among sub-Saharan Africans. We also observe strong selection signals at putatively functional variants in nearby lipid metabolism genes, which may influence evolutionary dynamics at the ADH region. Finally, we show that haplotypes carrying these selected variants were introduced into Northeast Africa from a West-Eurasian source within the last ∼2,000 years and experienced positive selection following admixture. These selection signals are not evident in nearby, genetically similar populations that practice hunting/gathering or pastoralist subsistence lifestyles, supporting the hypothesis that the emergence of agriculture shapes patterns of selection at ADH genes. Together, these results enhance our understanding of how adaptations to diverse environments and diets have influenced the African genomic landscape.

Body size in Batesian mimicry

A variety of traits is available for predators to distinguish unpalatable prey from palatable Batesian mimics. Among them, body size has received little attention as a possible mimetic trait. Size should influence predator behaviour if it shows variation between models and mimics, is detectable by the predator in question, and is not overshadowed by other traits more salient to the predator. Simple predictions within mimetic populations are that perfect mimics receive the lowest predation rate. However, prey body size is typically tightly linked to the nutritional yield and handling time for a successful predator, as well as likely being correlated with a model’s levels of defence. In certain circumstances, these confounding factors might mean that (a) selection pressures on a mimic’s size either side of the model’s phenotype are not symmetrical, (b) the optimal body size for a mimic is not necessarily equal to that of the model, and/or (c) for predators, attacking better mimics of a model’s body size more readily is adaptive. I discuss promising avenues for improving our understanding of body size as a mimetic trait, including the importance of treatments that range in both directions from the model’s size. Further work is required to understand how body size ranks in saliency against other mimetic traits such as pattern. Comparative studies could investigate whether mimics are limited to resembling only models that are already similar in size.

Behind the Screens: A Systematic Literature Review of Quantitative Research on Mobile Dating.

Mobile dating applications (MDAs) have become commonly used tools to seek out dating and sexual partners online. The current review aimed to systematically synthesize empirical findings in 72 quantitative studies on mobile dating, published in ISI-ranked journals between 2014 and 2020. This review focused on summarizing different approaches toward mobile dating, identity features of quantitative research on mobile dating, and hypothesized antecedents and outcomes of mobile dating. Our findings showed, first, that the literature diverges in how mobile dating is operationalized. Second, quantitative research on mobile dating predominantly consists of cross-sectional studies that draw on theoretical insights from multiple disciplines. Third, a variety of traits and sociodemographics were associated with MDA use. In particular, using MDAs for (1) relational goals related to being male, non-heterosexual, higher levels of sociosexuality, sensation seeking, extraversion, and holding more positive peer norms about using MDAs for relational goals; (2) intrapersonal goals related to being female and having more socially impairing traits; and (3) entertainment goals related to having higher levels of sociosexuality, sensation seeking, and antisocial traits. Outcomes significantly associated with general use of MDAs were scoring higher on sexual permissiveness and on engaging in casual (unprotected) sexual intercourse, as well as having higher risk at nonconsensual sex. MDA use was also connected with increased psychological distress and body dissatisfaction. Shortcomings of the existing research approaches and measures are discussed and six methodological and theoretical recommendations for future research are provided.

Pre-extension demonstration and evaluation of food barley technology (Hordeum vulgare L.) in West and Kellem Wollega zones

Pre extension demonstration of food barley varieties was carried out during 2010/11 and 2011/12 E.C cropping season with the objective of evaluating the best performed and preferred food barley varieties under farmer’s management condition. The trial was carried out selecting one kebele from each Anfilo, Hawa Gelan and Boji Dirmaji districts and selecting two kebeles from Seyo district. Three improved varieties of food barley (dinsho, abdane and biftu) with a local check were evaluated with full participation of FRG members under their management condition. The best fit variety was selected with the participants. The total of five (5) FRGs which incorporated a total of 59 male and 23 female was established. Each experimental plot had gross area of 100 m2 and rows spacing of 25 cm were used. All recommended agronomic practices were equally applied to all plots. Yield of varieties were collected and analyzed using descriptive statistics. Accordingly the yield performances of varieties were 28.66 qt/ha, 26.02 qt/ha, 23.96 qt/ha and 21.15 qt/ha for Dinsho, Abdane, Biftu and local respectively. Accordingly, the yield advantage of dinsho over local is 35.5% while the yield advantage of abdane over local is 23.02% and yield advantage of biftu over local is 13.28%. Farmers were enhanced to evaluate the technology using their own criteria. Accordingly they selected dinsho variety as their first choice by its grain yield, disease resistance, finger size and abdane variety secondly by its merits of early maturity, lodging tolerance and biftu and local thirdly and fourthly respectively. Generally based on farmer’s preference and objectively measured trait variety dinsho should be scaled up/out in Sayo, Hawa Galan, Anfilo and Bodji Dirmaji districts and similar agro ecology of West and Kellam wollega zones.
 Res. Agric., Livest. Fish.9(1): 29-36, April 2022

Predicting individual traits from unperformed tasks

Relating individual differences in cognitive traits to brain functional organization is a long-lasting challenge for the neuroscience community. Individual intelligence scores were previously predicted from whole-brain connectivity patterns, extracted from functional magnetic resonance imaging (fMRI) data acquired at rest. Recently, it was shown that task-induced brain activation maps outperform these resting-state connectivity patterns in predicting individual intelligence, suggesting that a cognitively demanding environment improves prediction of cognitive abilities. Here, we use data from the Human Connectome Project to predict task-induced brain activation maps from resting-state fMRI, and proceed to use these predicted activity maps to further predict individual differences in a variety of traits. While models based on original task activation maps remain the most accurate, models based on predicted maps significantly outperformed those based on the resting-state connectome. Thus, we provide a promising approach for the evaluation of measures of human behavior from brain activation maps, that could be used without having participants actually perform the tasks.

Morph Composition Matters in the Gouldian Finch (Chloebia gouldiae): Involvement of Red-Headed Birds Increases Vigilance

Animals invest in costly vigilance to detect threats. Joining groups reduces these costs, which can be further reduced in mixed-species assemblages. In colour-polymorphic species, morphs often experience different predation pressure and vary in a variety of traits. However, little is known about differences in vigilance or how group composition affects vigilance. The aim was to investigate whether higher conspicuousness increased vigilance and whether vigilance was reduced in mixed-morph groups like in mixed-species assemblages. I tested vigilance in the colour-polymorphic Gouldian Finch (Chloebia gouldiae). Same sex pairs of different age and of either pure (red-red or black-black) or mixed head colour were exposed to three contexts (familiar, changed and novel environment) and head movements were recorded. All birds reduced the frequency of head movements with increasing novelty, indicating different vigilance strategies (switching from a searching to a tracking strategy) depending on the situation. While vigilance did not differ between morphs, morph composition mattered. Black-headed pairs made fewer head movements than mixed-head colour pairs. Results indicated that conspicuousness did not affect vigilance, possibly due to existing adaptations to reduce predation risk. However, whenever red-headed birds were involved, vigilance increased either because of higher group conspicuousness or prevalence of aggression.

Identification of Promising Genotypes Through Systematic Evaluation for Arsenic Tolerance and Exclusion in Rice (Oryza sativa L.).

Rice remains a major staple food source for the rapidly growing world population. However, regular occurrences of carcinogenic arsenic (As) minerals in waterlogged paddy topsoil pose a great threat to rice production and consumers across the globe. Although As contamination in rice has been well recognized over the past two decades, no suitable rice germplasm had been identified to exploit in adaptive breeding programs. Therefore, this current study identified suitable rice germplasm for As tolerance and exclusion based on a variety of traits and investigated the interlinkages of favorable traits during different growth stages. Fifty-three different genotypes were systematically evaluated for As tolerance and accumulation. A germination screening assay was carried out to identify the ability of individual germplasm to germinate under varying As stress. Seedling-stage screening was conducted in hydroponics under varying As stress to identify tolerant and excluder genotypes, and a field experiment was carried out to identify genotypes accumulating less As in grain. Irrespective of the rice genotypes, plant health declined significantly with increasing As in the treatment. However, genotype-dependent variation in germination, tolerance, and As accumulation was observed among the genotypes. Some genotypes (WTR1-BRRI dhan69, NPT-IR68552-55-3-2, OM997, and GSR IR1-5-Y4-S1-Y1) showed high tolerance by excluding As in the shoot system. Arsenic content in grain ranged from 0.12 mg kg−1 in Huang-Hua-Zhan (indica) from China to 0.48 mg kg−1 in IRAT 109 (japonica) from Brazil. This current study provides novel insights into the performance of rice genotypes under varying As stress during different growth stages for further use in ongoing breeding programs for the development of As-excluding rice varieties for As-polluted environments.

Addiction-Associated Genetic Variants Implicate Brain Cell Type- and Region-Specific Cis-Regulatory Elements in Addiction Neurobiology.

Recent large genome-wide association studies have identified multiple confident risk loci linked to addiction-associated behavioral traits. Most genetic variants linked to addiction-associated traits lie in noncoding regions of the genome, likely disrupting cis-regulatory element (CRE) function. CREs tend to be highly cell type-specific and may contribute to the functional development of the neural circuits underlying addiction. Yet, a systematic approach for predicting the impact of risk variants on the CREs of specific cell populations is lacking. To dissect the cell types and brain regions underlying addiction-associated traits, we applied stratified linkage disequilibrium score regression to compare genome-wide association studies to genomic regions collected from human and mouse assays for open chromatin, which is associated with CRE activity. We found enrichment of addiction-associated variants in putative CREs marked by open chromatin in neuronal (NeuN+) nuclei collected from multiple prefrontal cortical areas and striatal regions known to play major roles in reward and addiction. To further dissect the cell type-specific basis of addiction-associated traits, we also identified enrichments in human orthologs of open chromatin regions of female and male mouse neuronal subtypes: cortical excitatory, D1, D2, and PV. Last, we developed machine learning models to predict mouse cell type-specific open chromatin, enabling us to further categorize human NeuN+ open chromatin regions into cortical excitatory or striatal D1 and D2 neurons and predict the functional impact of addiction-associated genetic variants. Our results suggest that different neuronal subtypes within the reward system play distinct roles in the variety of traits that contribute to addiction.SIGNIFICANCE STATEMENT We combine statistical genetic and machine learning techniques to find that the predisposition to for nicotine, alcohol, and cannabis use behaviors can be partially explained by genetic variants in conserved regulatory elements within specific brain regions and neuronal subtypes of the reward system. Our computational framework can flexibly integrate open chromatin data across species to screen for putative causal variants in a cell type- and tissue-specific manner for numerous complex traits.

Revisions to USDA biotechnology regulations: The SECURE rule

In keeping with the directive in Executive Order 13874 (Modernizing the Regulatory Framework for Agricultural Biotechnology Products) to adopt regulatory approaches that are proportionate to risk and avoid arbitrary distinctions across like products, the US Department of Agriculture (USDA) revised its biotechnology regulations by promulgating the Sustainable, Ecological, Consistent, Uniform, Responsible, and Efficient (SECURE) rule. Specifically, the SECURE rule 1) establishes exemptions for plants modified by genetic engineering where the modification could otherwise have been made through conventional breeding, 2) uses risk posed by the introduced trait to determine whether an organism is regulated, rather than relying on whether the organism was developed using a plant pest, and 3) provides a mechanism for a rapid initial review to efficiently distinguish plants developed using genetic engineering that do not pose plausible pathways to increased plant pest risk from those that do. As a result of the focused oversight on potentially riskier crops developed using genetic engineering, USDA is expected to improve the efficiency and effectiveness of its oversight program. The reduced regulatory burden is expected to promote innovation by expanding the number and diversity of developers to include smaller businesses and academics and to increase the number and variety of traits being developed through biotechnology.

Genetic correlations between COVID-19 and a variety of traits and diseases

Genetic correlations between COVID-19 and a variety of traits and diseases

Ethnic Identity and Genome Wide Runs of Homozygosity

It is long known that inbreeding increases the detrimental effects of recessive sequence variants in “Runs of Homozygosity” (ROHs). However, although the phenotypic association of ROH has been investigated for a variety of traits, the statistical power of the results often remains limited as a sufficiently high number of cases are available for only a restricted number of traits. In the present study, we aim to analyze the association of runs of homozygosity with the trait “in-group ethnic favoritism”. This analysis assumes that if ethnic identity is important for an individual, that individual may tend to marry more frequently within their own group and therefore ROH are expected to increase. We hypothesize that an attitude preferring one’s own ethnic group may be associated with a stronger tendency of inbreeding and, as a result, with more and longer ROHs. Accordingly, we investigated the association between the attitude to someone’s own ethnicity and ROH, using the Wisconsin Longitudinal data (WLS, total N ~ 9000) as discovery data set and the Brisbane Twin data as replication data set (N ~ 8000). We find that both the number as well as the total length of homozygous segments are significantly positively associated with “in-group ethnic favoritism”, independent of the method used for ROH calculation.

Predicting the Evolution of Sexual Dimorphism in Gene Expression.

Sexual dimorphism in gene expression is likely to be the underlying source of dimorphism in a variety of traits. Many analyses implicitly make the assumption that dimorphism only evolves when selection favors different phenotypes in the two sexes, although theory makes clear that it can also evolve as an indirect response to other kinds of selection. Furthermore, previous analyses consider the evolution of a single transcript or trait at a time, ignoring the genetic covariance with other transcripts and traits. We first show which aspects of the genetic-variance–covariance matrix, G, affect dimorphism when these assumptions about selection are relaxed. We then reanalyze gene expression data from Drosophila melanogaster with these predictions in mind. Dimorphism of gene expression for individual transcripts shows the signature of both direct selection for dimorphism and indirect responses to selection. To account for the effect of measurement error on evolutionary predictions, we estimated a G matrix for eight linear combinations of expression traits. Sex-specific genetic variances in female- and male-biased transcription, as well as one relatively unbiased combination, were quite unequal, ensuring that most forms of selection on these traits will have large effects on dimorphism. Predictions of response to selection based on the whole G matrix showed that sexually concordant and antagonistic selection are equally capable of changing sexual dimorphism. In addition, the indirect responses of dimorphism due to cross-trait covariances were quite substantial. The assumption that sexual dimorphism in transcription is an adaptation could be incorrect in many specific cases.

Distinctiveness of genes contributing to growth of Pseudomonas syringae in diverse host plant species.

A variety of traits are necessary for bacterial colonization of the interior of plant hosts, including well-studied virulence effectors as well as other phenotypes contributing to bacterial growth and survival within the apoplast. High-throughput methods such as transposon sequencing (TnSeq) are powerful tools to identify such genes in bacterial pathogens. However, there is little information as to the distinctiveness of traits required for bacterial colonization of different hosts. Here, we utilize randomly barcoded TnSeq (RB-TnSeq) to identify the genes that contribute to the ability of Pseudomonas syringae strain B728a to grow within common bean (Phaseolus vulgaris), lima bean (Phaseolus lunatus), and pepper (Capsicum annuum); species representing two different plant families. The magnitude of contribution of most genes to apoplastic fitness in each of the plant hosts was similar. However, 50 genes significantly differed in their fitness contributions to growth within these species. These genes encoded proteins in various functional categories including polysaccharide synthesis and transport, amino acid metabolism and transport, cofactor metabolism, and phytotoxin synthesis and transport. Six genes that encoded unannotated, hypothetical proteins also contributed differentially to growth in these hosts. The genetic repertoire of a relatively promiscuous pathogen such as P. syringae may thus be shaped, at least in part, by the conditional contribution of some fitness determinants.

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling.

Microbial community profiles have been associated with a variety of traits, including methane emissions in livestock. These profiles can be difficult and expensive to obtain for thousands of samples (e.g. for accurate association of microbial profiles with traits), therefore the objective of this work was to develop a low-cost, high-throughput approach to capture the diversity of the rumen microbiome. Restriction enzyme reduced representation sequencing (RE-RRS) using ApeKI or PstI, and two bioinformatic pipelines (reference-based and reference-free) were compared to bacterial 16S rRNA gene sequencing using repeated samples collected two weeks apart from 118 sheep that were phenotypically extreme (60 high and 58 low) for methane emitted per kg dry matter intake (n = 236). DNA was extracted from freeze-dried rumen samples using a phenol chloroform and bead-beating protocol prior to RE-RRS. The resulting sequences were used to investigate the repeatability of the rumen microbial community profiles, the effect of laboratory and analytical method, and the relationship with methane production. The results suggested that the best method was PstI RE-RRS analyzed with the reference-free approach, which accounted for 53.3±5.9% of reads, and had repeatabilities of 0.49±0.07 and 0.50±0.07 for the first two principal components (PC1 and PC2), phenotypic correlations with methane yield of 0.43±0.06 and 0.46±0.06 for PC1 and PC2, and explained 41±8% of the variation in methane yield. These results were significantly better than for bacterial 16S rRNA gene sequencing of the same samples (p<0.05) except for the correlation between PC2 and methane yield. A Sensitivity study suggested approximately 2000 samples could be sequenced in a single lane on an Illumina HiSeq 2500, meaning the current work using 118 samples/lane and future proposed 384 samples/lane are well within that threshold. With minor adaptations, our approach could be used to obtain microbial profiles from other metagenomic samples.

Genetic variability, stability and heritability for quality and yield characteristics in provitamin A cassava varieties

Cassava is widely consumed in many areas of Africa, including Ghana, and is a major part of most household diets. These areas are characterized by rampant malnutrition, because the tuberous roots are low in nutritional value. Provitamin A biofortified cassava varieties have been developed by the International Institute for Tropical Agriculture, but adoption of these varieties in Ghana will largely depend on their agronomic performance, including fresh root yield, dry matter content, resistance to major pests and diseases, mealiness, starch content and the stability of these traits. Eight provitamin A varieties with two white checks were planted in three environments for two seasons to determine stability and variability among the varieties for important traits. There were significant variations in performance between varieties and between environments for cassava mosaic disease, root number, fresh root yield and starch content. High broad-sense heritability and genetic advance were observed in all traits, except for storage root number, and could be exploited through improvement programs. This study identified the best performing enhanced provitamin A varieties for traits that are key drivers of variety adoption in Ghana. In view of this, some varieties can be recommended for varietal release after on-farm testing. The study also showed the possibility of tapping heterosis after careful selection of parents.

Choosing the proper autoencoder for feature fusion based on data complexity and classifiers: Analysis, tips and guidelines

Classifying data patterns is one of the most recurrent applications in machine learning. The number of input features influences the predictive performance of many classification models. Most classifiers work with high-dimensional spaces. Therefore, there is a great interest in facing the task of reducing the input space. Manifold learning has been shown to perform better than classical dimensionality reduction approaches, such as Principal Component Analysis and Linear Discriminant Analysis. In this sense, Autoencoders (AEs) provide an automated way of performing feature fusion, finding the best manifold to reconstruct the data. There are several models and architectures of AEs. For this reason, in this study an exhaustive analysis of the predictive performance of different AEs models with a large number of datasets is proposed, aiming to provide a set of useful guidelines. These will allow users to choose the appropriate AE model for each case, depending on data traits and the classifier to be used. A thorough empirical analysis is conducted including four AE models, four classification paradigms and a group of datasets with a variety of traits. A convenient set of rules to follow is obtained as a result.