Contrasting coordination of non-structural carbohydrates with leaf and root economic strategies of alpine coniferous forests.

Non-structural carbohydrates (NSCs), as the labile fraction and dominant carbon currency, are essential mediators of plant adaptation to environments. However, whether and how NSC coordinates with plant economic strategy frameworks, particularly the well-recognized leaf economics spectrums (LES) and root economics space (RES), remains unclear. We examined the relationships between NSC and key plant economics traits in leaves and fine roots across 90 alpine coniferous populations on the Tibetan Plateau, China. We observed contrasting coordination of NSC with economics traits in leaves and roots. Leaf total NSC and soluble sugar aligned with the leaf economic spectrum, conveying a trade-off between growth and storage in leaves. However, NSC in roots was independent of the root economic spectrum, but highly coordinated with root foraging, with more starch and less sugar in forage-efficient, thinner roots. Further, NSC-trait coordination in leaves and roots was, respectively, driven by local temperature and precipitation. These findings highlight distinct roles of NSC in shaping the above- and belowground multidimensional economics trait space, and NSC-based carbon economics provides a mechanistic understanding of how plants adapt to heterogeneous habitats and respond to environmental changes.

Variation in leaf carbon economics, energy balance, and heat tolerance traits highlights differing timescales of adaptation and acclimation.

Multivariate leaf trait correlations are hypothesized to originate from natural selection on carbon economics traits that control lifetime leaf carbon gain, and energy balance traits governing leaf temperatures, physiological rates, and heat injury. However, it is unclear whether macroevolution of leaf traits primarily reflects selection for lifetime carbon gain or energy balance, and whether photosynthetic heat tolerance is coordinated along these axes. To evaluate these hypotheses, we measured carbon economics, energy balance, and photosynthetic heat tolerance traits for 177 species (157 families) in a common garden that minimizes co-variation of taxa and climate. We observed wide variation in carbon economics, energy balance, and heat tolerance traits. Carbon economics and energy balance (but not heat tolerance) traits were phylogenetically structured, suggesting macroevolution of leaf mass per area and leaf dry matter content reflects selection on carbon gain rather than energy balance. Carbon economics and energy balance traits varied along a common axis orthogonal to heat tolerance traits. Our results highlight a fundamental mismatch in the timescales over which morphological and heat tolerance traits respond to environmental variation. Whereas carbon economics and energy balance traits are constrained by species' evolutionary histories, photosynthetic heat tolerance traits are not and can acclimate readily to leaf microclimates.

Genetic architecture of gene regulation in Indonesian populations identifies QTLs associated with global and local ancestries.

Lack of diversity in human genomics limits our understanding of the genetic underpinnings of complex traits, hinders precision medicine, and contributes to health disparities. To map genetic effects on gene regulation in the underrepresented Indonesian population, we have integrated genotype, gene expression, and CpG methylation data from 115 participants across three island populations that capture the major sources of genomic diversity in the region. In a comparison with European datasets, we identify eQTLs shared between Indonesia and Europe as well as population-specific eQTLs that exhibit differences in allele frequencies and/or overall expression levels between populations. By combining local ancestry and archaic introgression inference with eQTLs and methylQTLs, we identify regulatory loci driven by modern Papuan ancestry as well as introgressed Denisovan and Neanderthal variation. GWAS colocalization connects QTLs detected here to hematological traits, and further comparison with European datasets reflects the poor overall transferability of GWAS statistics across diverse populations. Our findings illustrate how population-specific genetic architecture, local ancestry, and archaic introgression drive variation in gene regulation across genetically distinct and in admixed populations and highlight the need for performing association studies on non-European populations.

Assessment of leaf morphological, physiological, chemical and stoichiometry functional traits for understanding the functioning of Himalayan temperate forest ecosystem.

Leaf functional traits support plant survival and growth in different stress and disturbed conditions and respond according to leaf habit. The present study examined 13 leaf traits (3 morphological, 3 chemical, 5 physiological, and 2 stoichiometry) of nine dominant forest tree species (3 coniferous, 3 deciduous broad-leaved, 3 evergreen broad-leafed) to understand the varied response of leaf habits. The hypothesis was to test if functional traits of the conifers, deciduous and evergreen differ significantly in the temperate forest and to determine the applicability of leaf economic theory i.e., conservative vs. acquisitive resource investment, in the temperate Himalayan region. The attributes of the functional traits i.e., leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC), leaf water content (LWC), stomatal conductance (Gs), and transpiration (E) followed the order deciduous > evergreen > coniferous. Leaf carbon and leaf C/N ratio showed the opposite pattern, coniferous > evergreen > deciduous. Chlorophyll (Chl) and photosynthetic rate (A) were highest for evergreen species, followed by deciduous and coniferous species. Also, structural equation modelling determined that morphological factors were negatively related to physiological and positively with chemical factors. Nevertheless, physiological and chemical factors were positively related to each other. The physiological traits were mainly regulated by stomatal conductance (Gs) however the morphological traits were determined by LDMC. Stoichiometry traits, such as leaf C/N, were found to be positively related to leaf carbon, and leaf N/P was found to be positively related to leaf nitrogen. The result of the leaf functional traits relationship would lead to precise prediction for the functionality of the temperate forest ecosystem at the regional scale.

AMMI and GGE biplot analysis for yield performance and stability assessment of selected Bambara groundnut (Vigna subterranea L. Verdc.) genotypes under the multi-environmental trails (METs).

The stability and high yielding of Vigna subterranea L. Verdc. genotype is an important factor for long-term development and food security. The effects of G × E interaction on yield stability in 30 Bambara groundnut genotypes in four different Malaysian environments were investigated in this research. The experiment used a randomized complete block design with three replications in each environment. Over multiple harvests, yield component traits such as the total number of pods per plant, fresh pods weight (g), hundred seeds weight (g), and yield per hectare were evaluated in the main and off-season in 2020 and 2021. Stability tests for multivariate stability parameters were performed based on analyses of variance. For all the traits, the pooled analysis of variance revealed highly significant (p < 0.01) variations between genotypes, locations, seasons, and genotypes by environment (G × E interaction). A two-dimensional GGE biplot was generated using the first two principal components (axis 1 and axis 2), which accounted for 94.97% and 3.11% difference in GEI for yield per hectare, respectively. Season and location were found to be the most significant causes of yield heterogeneity, accounting for 31.13% and 14.02% of overall G + E + G × E variation, respectively, according to the combined study of variance. The GGE biplot revealed that the three winning genotypes G1, G3, and G5 appear across environments whereas AMMI model exposed genotypes viz G18, G14, G7, G3, G1, and G5 as best performer. Based on ideal genotype ranking genotype G1 was the best performer, with a high mean yield and high stability in the tested environment. According to the AEC line, genotypes G1 and G3 were extremely stable, while genotypes G2 and G4 were low stable, with a high average yielding per hectare. A GGE and AMMI biplot graphically showed the interrelationships between the tested environment and genotypes, classified genotypes into three categories as well as simplifying visual evaluations, according to this investigation. According to our results, breeding could improve yield production, and the genotypes discovered could be recommended for commercial cultivation.

Long-term comparison between index selection and optimal independent culling in plant breeding programs with genomic prediction.

In the context of genomic selection, we evaluated and compared breeding programs using either index selection or independent culling for recurrent selection of parents. We simulated a clonally propagated crop breeding program for 20 cycles using either independent culling or an economic index with two unfavourably correlated traits under selection. Cycle time from crossing to selection of parents was kept the same for both strategies. Both methods led to increasingly unfavourable genetic correlations between traits and, compared to independent culling, index selection led to larger changes in the genetic correlation between the two traits. When linkage disequilibrium was not considered, the two methods had similar losses of genetic diversity. Two independent culling approaches were evaluated, one using optimal culling levels and one using the same selection intensity for both traits. Optimal culling levels outperformed the same selection intensity even when traits had the same economic importance. Therefore, accurately estimating optimal culling levels is essential for maximizing gains when independent culling is performed. Once optimal culling levels are achieved, independent culling and index selection lead to comparable genetic gains.

Assessment of genetic diversity and structure of Bambara groundnut [Vigna subterranea (L.) verdc.] landraces in South Africa.

With its drought tolerant and protein-rich properties, Bambara groundnut [Vigna subterranea (L.) Verdc.], an indigenous African legume crop can contribute immensely to food security. This miracle crop is used as food and for the enhancement of soil fertility in South Africa. Knowledge on the genetic diversity and structure among the Bambara groundnut landraces can pave the way for the effective use and cultivation of this crop in southern Africa, especially South Africa. The aim of this study was to assess the genetic diversity and structure among Bambara groundnut landraces collected across South Africa and compared to a limited number of accessions from southern Africa using SSR markers. Seventy-eight Bambara groundnut accessions were genotyped using 19 Bambara specific SSR markers. SSR loci explored in this study, were all polymorphic. A total of 127 alleles were detected with a mean of 6.7 alleles per locus. Allele diversity and frequency among genotypes varied from 0.21 to 0.85 with an average of 0.62 per locus. Genetic variation as described by the analysis of molecular variance indicated higher genetic diversity (92%) within landraces than between (8%) different landraces. Population structure analysis showed that three subpopulations existed, and most of the South African accessions were restricted to one subpopulation, indicating that Bambara landraces has the ability to form unique haplotypes in different environments. Information harnessed in this study is helpful for further use in breeding programs for crop improvement.

Genomic sequencing analysis reveals copy number variations and their associations with economically important traits in beef cattle.

Copy number variation (CNV) represents a major source of genetic variation, which may have potentially large effects, including alternating gene regulation and dosage, as well as contributing to gene expression and risk for normal phenotypic variability. We carried out a comprehensive analysis of CNV based on whole genome sequencing in Chinese Simmental beef cattle. Totally, we found 9313 deletion and 234 duplication events, covering 147.5 Mb autosomal regions. Within them, 257 deletion events of high frequency overlapped with 193 known RefGenes. Among these genes, we observed several genes were related to economically important traits, like residual feed intake, immune responding, pregnancy rate and muscle differentiation. Using a locus-based analysis, we identified 11 deletions and 1 duplication, which were significantly associated with three traits including carcass weight, tenderloin and longissimus muscle area. Our sequencing-based study provided important insights into investigating the association of CNVs with important traits in beef cattle.

Assessment of genetic diversity of cultivated and wild Iranian grape germplasm using retrotransposon-microsatellite amplified polymorphism (REMAP) markers and pomological traits.

Understanding the genetic diversity and relationships between genotypes is an effective step in designing effective breeding programs. Insertional polymorphisms of retrotransposons were studied in 75 cultivated and wild grape genotypes using retrotransposon-microsatellite amplified polymorphism (REMAP) technique. In the morphological part of work, seven pomological traits with a high breeding interest were also analyzed in the cultivated genotypes. A total of 328 markers were produced by 42 primer pairs, out of which 313 markers (95.43%) were polymorphic. Number of markers ranged from 4 in loci Tvv1Fa-873, Vine1-811, Gret1Ra-855 and Tvv1Fa-890 to 12 in locus Vine1Ra-841 with an average value of 7.45. Similarity values based on Dice's coefficient among all 75 grapevine genotypes varied from 0.41 to 0.77. Classification of genotypes using unweighted pair-group method using complete-linkage clustering led to six distinct groups. Some wild and cultivated varieties placed in the same groups. It seems there are close relationship between wild and cultivated genotypes and maybe wild genotypes are ancestor of native grapevines. Grouping of grapevine genotypes based on molecular marker data was not in agreement with clustering by agro-morphological data indicating that the most of multiplied sequences are confined to the non-coding regions of transposon elements. Results showed a substantial level of genetic diversity at molecular and pomological level and the potential of this diversity for future grape breeding programs.

Signatures of selection reveal candidate genes involved in economic traits and cold acclimation in five Swedish cattle breeds.

BACKGROUND: Thousands of years of natural and artificial selection have resulted in indigenous cattle breeds that are well-adapted to the environmental challenges of their local habitat and thereby are considered as valuable genetic resources. Understanding the genetic background of such adaptation processes can help us design effective breeding objectives to preserve local breeds and improve commercial cattle. To identify regions under putative selection, GGP HD 150 K single nucleotide polymorphism (SNP) arrays were used to genotype 106 individuals representing five Swedish breeds i.e. native to different regions and covering areas with a subarctic cold climate in the north and mountainous west, to those with a continental climate in the more densely populated south regions. RESULTS: Five statistics were incorporated within a framework, known as de-correlated composite of multiple signals (DCMS) to detect signatures of selection. The obtained p-values were adjusted for multiple testing (FDR < 5%), and significant genomic regions were identified. Annotation of genes in these regions revealed various verified and novel candidate genes that are associated with a diverse range of traits, including e.g. high altitude adaptation and response to hypoxia (DCAF8, PPP1R12A, SLC16A3, UCP2, UCP3, TIGAR), cold acclimation (AQP3, AQP7, HSPB8), body size and stature (PLAG1, KCNA6, NDUFA9, AKAP3, C5H12orf4, RAD51AP1, FGF6, TIGAR, CCND2, CSMD3), resistance to disease and bacterial infection (CHI3L2, GBP6, PPFIBP1, REP15, CYP4F2, TIGD2, PYURF, SLC10A2, FCHSD2, ARHGEF17, RELT, PRDM2, KDM5B), reproduction (PPP1R12A, ZFP36L2, CSPP1), milk yield and components (NPC1L1, NUDCD3, ACSS1, FCHSD2), growth and feed efficiency (TMEM68, TGS1, LYN, XKR4, FOXA2, GBP2, GBP5, FGD6), and polled phenotype (URB1, EVA1C). CONCLUSIONS: We identified genomic regions that may provide background knowledge to understand the mechanisms that are involved in economic traits and adaptation to cold climate in cattle. Incorporating p-values of different statistics in a single DCMS framework may help select and prioritize candidate genes for further analyses.

Comparison of two models to estimate genetic parameters for number of born alive in pigs.

The performance of the two-trait animal model that regards the first parity and later parities as two different traits in estimating genetic parameters for number of born alive (NBA) was examined using real and simulated data. Genetic parameters for NBA were estimated in purebred Landrace and Large White pigs using a single-trait repeatability model (Model 1) that regards all parities as the same trait and a two-trait animal model (Model 2) that regards the first and the later parities as different traits. For Model 2, the permanent environmental effect was fitted to only the records of the later parities. Heritability for NBA estimated using Model 1 was 0.12 for Landrace and 0.11 for Large White. Estimated heritability for NBA of the first parity and the later parities was 0.21 and 0.16, respectively, for Landrace; 0.18 and 0.16, respectively, for Large White obtained using Model 2, and higher than those in both breeds obtained using Model 1. Further results based on data simulated using the Monte Carlo method suggest that estimated additive genetic variance could be more biased using Model 2 than Model 1.

Fast and accurate quantification of insertion-site specific transgene levels from raw seed samples using solid-state nanopore technology.

Many modern crop varieties contain patented biotechnology traits, and an increasing number of these crops have multiple (stacked) traits. Fast and accurate determination of transgene levels is advantageous for a variety of use cases across the food, feed and fuel value chain. With the growing number of new transgenic crops, any technology used to quantify them should have robust assays that are simple to design and optimize, thereby facilitating the addition of new traits to an assay. Here we describe a PCR-based method that is simple to design, starts from whole seeds, and can be run to end-point in less than 5 minutes. Subsequent relative quantification (trait vs. non-trait) using capillary electrophoresis performed in 5% increments across the 0-100% range showed a mean absolute error of 1.9% (s.d. = 1.1%). We also show that the PCR assay can be coupled to non-optical solid-state nanopore sensors to give seed-to-trait quantification results with a mean absolute error of 2.3% (s.d. = 1.6%). In concert, the fast PCR and nanopore sensing stages demonstrated here can be fully integrated to produce seed-to-trait quantification results in less than 10 minutes, with high accuracy across the full dynamic range.

Does seed size mediate sex-specific reproduction costs in the Callosobruchus maculatus bean beetle?

There is a trade-off between reproductive effort and adult longevity, and when resource allocation is taken into account, it is especially pronounced in species that have aphagous adult forms. This trade-off may be further complicated by environmental factors such as nutrient availability during larval development and by the other sex, which influences the costs of reproduction due to the presentation of nuptial gifts. Here, we examined the influence of larval nutrient quantity on the sex-specific longevity costs of reproduction in the gift-giving seed beetle Callosobruchus maculatus. We found no indication that differences in the nutrient quality of larger and smaller host seeds influence survival in virgin and reproducing individuals or nuptial gift size in reproducing individuals. However, in the case of reproducing individuals, the effect of seed size on survival was statistically marginal. Therefore, we advise taking this into account when investigating reproductive efforts in this species. We have also observed interesting interactions between male and female reproductive costs. While females had generally higher mortality than males, nuptial gifts resulted in lowered female mortality and increased male mortality. Additionally, we found a possibly non-linear relationship between nuptial gift size and the offspring production rate of female recipients.

Personality traits and risky behavior among motorcyclists: An exploratory study.

BACKGROUND: Personality traits have been associated with a series of dysfunctional behaviors, ranging from violence to drug abuse and other risky behaviors. However, few studies have investigated motorcycle riders' personality traits, and no research using the psychobiological model of personality was found. Thus, we investigated the association between temperament and character traits and the occurrence of Motorcycle Accidents (MAs). METHODS: This cross-sectional study was conducted with a randomly selected of 153 Brazilian motorcycle riders (116 male and 37 female) with a mean age of 31.8randomly selected from the driver's license register, between 2015 and 2018. A sociodemographic questionnaire and the Temperament and Character Inventory (TCI) were used. RESULTS: Of the 153 participants, 146 (95.4%) reported having been involved in previous accidents, with the main causes as follows: "other drivers' careless behavior" (34.9%); "personal disrespect of traffic rules" (18.5%) and "personal careless behavior" (20.6%). Motorcyclists exhibited higher scores for the temperament factors of novelty seeking and persistence and lower scores for harm avoidance and reward dependence in comparison to the Brazilian population). Considering the reason for motorcycle use, the group of riders that used their motorcycles for work exhibited more temperament factors associated with risk behaviors than those who did not. It was observed that 68.9% of them had low Harm Avoidance (HA) factor scores, whereas 72.1% had high Novelty Seeking (NS) factor scores. DISCUSSION: The present study highlighted the influences of different personality traits on behaviors, decision-making and risk attitudes that can be potentially harmful to an individual and others. The results provided evidence that a lack of knowledge and experience in riding a motorcycle or any other vehicle, combined with personality traits, contribute to the adoption of risky behaviors that may act as triggers for most causes of Motorcycle Accidents.

Phenotypic and molecular assessment of genetic structure and diversity in a panel of winged yam (Dioscorea alata) clones and cultivars.

A better understanding of the structure and extent of genetic variability in a breeding population of a crop is essential for translating genetic diversity to genetic gain. We assessed the nature and pattern of genetic variability and differentiation in a panel of 100 winged-yam (Dioscorea alata) accessions using 24 phenotypic traits and 6,918 single nucleotide polymorphism (SNP) markers. Multivariate analysis for phenotypic variability indicated that all phenotypic traits assessed were useful in discriminating the yam clones and cultivars. Cluster analysis based on phenotypic data distinguished two significant groups, while a corresponding analysis with SNP markers indicated three genetic groups. However, joint analysis for the phenotypic and genotypic data provided three clusters that could be useful for the identification of heterotic groups in the D. alata breeding program. Our analysis for phenotypic and molecular level diversity provided valuable information about overall diversity and variation in economically important traits useful for establishing crossing panels with contrasting traits of interest. The selection and hybridization of parental lines from the different heterotic groups identified would facilitate maximizing diversity and exploiting population heterosis in the D. alata breeding program.

Variability Assessment for Root and Drought Tolerance Traits and Genetic Diversity Analysis of Rice Germplasm using SSR Markers.

The studies on genetic variation, diversity and population structure of rice germplasm of North East India could be an important step for improvements of abiotic and biotic stress tolerance in rice. Genetic diversity and genetic relatedness among 114 rice genotypes of North East India were assessed using genotypic data of 65 SSR markers and phenotypic data. The phenotypic diversity analysis showed the considerable variation across genotypes for root, shoot and drought tolerance traits. The principal component analysis (PCA) revealed the fresh shoot weight, root volume, dry shoot weight, fresh root weight and drought score as a major contributor to diversity. Genotyping of 114 rice genotypes using 65 SSR markers detected 147 alleles with the average polymorphic information content (PIC) value of 0.51. Population structure analysis using the Bayesian clustering model approach, distance-based neighbor-joining cluster and principal coordinate analysis using genotypic data grouped the accession into three sub-populations. Population structure analysis revealed that rice accession was moderately structured based on FST value estimates. Analysis of molecular variance (AMOVA) and pairwise FST values showed significant differentiation among all the pairs of sub-population ranging from 0.152 to 0.222 suggesting that all the three subpopulations were significantly different from each other. AMOVA revealed that most of the variation in rice accession mainly occurred among individuals. The present study suggests that diverse germplasm of NE India could be used for the improvement of root and drought tolerance in rice breeding programmes.

Impact of merging commercial breeding lines on the genetic diversity of Landrace pigs.

BACKGROUND: The pig breeding industry has undergone a large number of mergers in the past decades. Various commercial lines were merged or discontinued, which is expected to reduce the genetic diversity of the pig species. The objective of the current study was to investigate the genetic diversity of different former Dutch Landrace breeding lines and quantify their relationship with the current Dutch Landrace breed that originated from these lines. RESULTS: Principal component analysis clearly divided the former Landrace lines into two main clusters, which are represented by Norwegian/Finnish Landrace lines and Dutch Landrace lines. Structure analysis revealed that each of the lines that are present in the Dutch Gene bank has a unique genetic identity. The current Dutch Landrace breed shows a high level of admixture and is closely related to the six former lines. The Dumeco N-line, which is conserved in the Dutch Gene bank, is poorly represented in the current Dutch Landrace. All seven lines (the six former and the current line) contribute almost equally to the genetic diversity of the Dutch Landrace breed. As expected, the current Dutch Landrace breed comprises only a small proportion of unique genetic diversity that was not present in the other lines. The genetic diversity level, as measured by Eding's core set method, was equal to 0.89 for the current Dutch Landrace breed, whereas total genetic diversity across the seven lines, measured by the same method, was equal to 0.99. CONCLUSIONS: The current Dutch Landrace breed shows a high level of admixture and is closely related to the six former Dutch Landrace lines. Merging of commercial Landrace lines has reduced the genetic diversity of the Landrace population in the Netherlands, although a large proportion of the original variation is maintained. Thus, our recommendation is to conserve breeding lines in a gene bank before they are merged.

Accuracies of genomic prediction for twenty economically important traits in Chinese Simmental beef cattle.

Genomic prediction has been widely utilized to estimate genomic breeding values (GEBVs) in farm animals. In this study, we conducted genomic prediction for 20 economically important traits including growth, carcass and meat quality traits in Chinese Simmental beef cattle. Five approaches (GBLUP, BayesA, BayesB, BayesCπ and BayesR) were used to estimate the genomic breeding values. The predictive accuracies ranged from 0.159 (lean meat percentage estimated by BayesCπ) to 0.518 (striploin weight estimated by BayesR). Moreover, we found that the average predictive accuracies across 20 traits were 0.361, 0.361, 0.367, 0.367 and 0.378, and the averaged regression coefficients were 0.89, 0.86, 0.89, 0.94 and 0.95 for GBLUP, BayesA, BayesB, BayesCπ and BayesR respectively. The genomic prediction accuracies were mostly moderate and high for growth and carcass traits, whereas meat quality traits showed relatively low accuracies. We concluded that Bayesian regression approaches, especially for BayesR and BayesCπ, were slightly superior to GBLUP for most traits. Increasing with the sizes of reference population, these two approaches are feasible for future application of genomic selection in Chinese beef cattle.

Challenges to capture the big five personality traits in non-WEIRD populations.

Can personality traits be measured and interpreted reliably across the world? While the use of Big Five personality measures is increasingly common across social sciences, their validity outside of western, educated, industrialized, rich, and democratic (WEIRD) populations is unclear. Adopting a comprehensive psychometric approach to analyze 29 face-to-face surveys from 94,751 respondents in 23 low- and middle-income countries, we show that commonly used personality questions generally fail to measure the intended personality traits and show low validity. These findings contrast with the much higher validity of these measures attained in internet surveys of 198,356 self-selected respondents from the same countries. We discuss how systematic response patterns, enumerator interactions, and low education levels can collectively distort personality measures when assessed in large-scale surveys. Our results highlight the risk of misinterpreting Big Five survey data and provide a warning against naïve interpretations of personality traits without evidence of their validity.

Genomic selection for productive traits in biparental cassava breeding populations.

Cassava improvement using traditional breeding strategies is slow due to the species' long breeding cycle. However, the use of genomic selection can lead to a shorter breeding cycle. This study aimed to estimate genetic parameters for productive traits based on pedigree (pedigree and phenotypic information) and genomic (markers and phenotypic information) analyses using biparental crosses at different stages of selection. A total of 290 clones were genotyped and phenotyped for fresh root yield (FRY), dry matter content (DMC), dry yield (DY), fresh shoot yield (FSY) and harvest index (HI). The clones were evaluated in clonal evaluation trials (CET), preliminary yield trials (PYT), advanced yield trials (AYT) and uniform yield trials (UYT), from 2013 to 2018 in ten locations. The breeding stages were analyzed as follows: one stage (CET), two stages (CET and PYT), three stages (CET, PYT and AYT) and four stages (CET, PYT, AYT and UYT). The genomic predictions were analyzed via k-fold cross-validation based on the genomic best linear unbiased prediction (GBLUP) considering a model with genetic additive effects and genotype × location interactions. Genomic and pedigree accuracies were moderate to high (0.56-0.72 and 0.62-0.78, respectively) for important starch-related traits such as DY and FRY; when considering one breeding stage (CET) with the aim of early selection, the genomic accuracies ranged from 0.60 (DMC) to 0.71 (HI). Moreover, the correlations between the genomic estimation breeding values of one-stage genomic analysis and the estimated breeding values of the four-stage (full data set) pedigree analysis were high for all traits as well as for a selection index including all traits. The results indicate great possibilities for genomic selection in cassava, especially for selection early in the breeding cycle (saving time and effort).