The processing flowsheet model utilised was the same for each feedstock. The sustainability study's economic, environmental, and energy perspectives were investigated. The economic and environmental indices were assessed using Superpro Designer and openLCA sustainability software, respectively. Exergy and lost work were subsequently estimated manually with Microsoft Excel. The economic analyses showed that the plants using cassava and sweet potato initially had the highest return on investment (ROI) of 64.41 and 41.96% respectively at a minimum of 80% plants’ capacity utilisation. The break-even point occurs at a bioethanol price of $3.27 per gallon, beyond which positive net present values were obtained for the four processes. The least profitable plant was based on sorghum recording an ROI value of 34.11%. The environmental assessment on the four selected feedstocks showed that the processes based on cassava, corn, sweet potato, and sorghum recorded encouraging global warming potential (GWP) of 0.2452, 0.2067, 2.5261, and 0.2099 kg CO2 equivalent respectively. Cassava and corn emerged as the two most economically viable feedstocks when economic parameters were adjusted to include pollutants emission/discharge costs but with a slight decrease in profitability indices. The lost work analyses showed that distillation columns were the least energy-efficient units in the four bioethanol production routes assessed, recording loss work of about 61, 68, 34, and 49 MW for cassava, sweet potato, corn, and sorghum processing plants respectively. However, the net energy balance (NEB) and energy renewability results of the four production routes showed that the processes utilising the four selected starchy biomass feedstocks are more sustainable compared to fossil fuels.A comparative sustainability study of bioethanol production from selected starchy feedstocks that are abundantly available was carried out in this work. This is to ensure the safe, reliable, and efficient production and consumption of fuel-grade bioethanol. The analysis utilised the established economic minimum bioethanol plant capacity of 158,000 m Crude oil accounts for about 53,369 TWh of global power consumption, while natural gas-based global power consumption stands at 39,063 TWh2. These figures are products of their constantly increasing consumption levels for the past few decades despite the attractive prospect possessed by other energy sources especially biofuels2.The global energy resources profile is rich in natural gas, solar, tar sand, coal, biomass, and crude oil but fossil fuel-based energy has remained the greatest energy and revenue source3. The constantly growing worldwide industrialization and overreliance on non-renewable energy sources have resulted in a huge quantity of greenhouse gases being emitted. This has led to a rise in global temperature and the attendant effect of environmental dilapidation4. The increment in worldwide mean atmospheric carbon dioxide (CO2) concentration from the pre-industrialization era of 1850 to date has been estimated at 285–419 ppm6 which is quite significant. In light of this, the United Kingdom meteorological office evaluates a worldwide mean surface temperature rise of about 0.97–1.21 °C between these periods, with a dominant estimate of 1.09 °C. It has also been predicted that this trend of global temperature increase will continue in subsequent years7. Furthermore, Rabaey and Ragauskas, 2014 also predicted a rise in global greenhouse gas emissions to be 50% by 2050, as a result of the utilisation of non-renewable energy-based CO2 emissions8. Therefore, in the absence of urgent and effective measures or technological modifications to curtail CO2 emissions, the global mean atmospheric concentration of CO2 and ocean temperatures will steadily increase10.Biofuels have been identified as low-carbon alternatives to fossil fuels because they tend to reduce greenhouse gas (GHG) emissions, and the other associated undesirable climate change impacts11.Fortunately, world leaders are well informed about this environmental deterioration posed by fossil fuel consumption and as such adopted an agendum of cleaner energy of the sustainable development goal in 2015. Some countries like USA and Brazil initiated a plan to realise this agendum by the use of biofuel (gasohol); 10% bioethanol and 90% gasoline (E10) in preference to the use of 100% conventional premium motor spirit (PMS) with much priority given to corn and sugarcane, as feedstocks for the bioethanol production12.The usage of renewable sources for fuels and electricity in transport is capable of profitably achieving great decarbonisation of the transport sector and expanding energy diversification within the sector while encouraging modernization and providing jobs in the Union economy and minimising overreliance on energy importations12. Meanwhile, second-generation biofuel production utilizes uneatable materials but the financial involvement in its large-scale production has hindered its growth. Recently, attention has been shifted to third and fourth-generation biofuels with greater emphasis on the use of algae and genetically modified microorganisms, respectively12. These probable interwoven consequences of food shortage from the utilization of food crops to ensure energy security have made the second, third, and fourth-generation feedstocks (lignocellulosic) more attractive12. Nevertheless, decisive measures can be put in place by governments and other stakeholders to replace the obsolete traditional farming practices with modern mechanized techniques to ensure improved acreage yields of these food crops for sustainable biofuel policies and food security.However, the reliance on first-generation (consumables) bioethanol feedstocks has prompted great concern and opinions on whether its fulfillment will not engender the risk of food scarcity15. Consideration of these sustainability indicators requires the stepwise analysis of bioethanol produced from different starchy feedstocks in different climes. Despite this bright global prospect for biofuel production, no work has been reported on the sustainability assessment of bioethanol production from this abundant tuber and grain starchy feedstocks. Thus, sustainability analysis of bioethanol production with these feedstocks is essential to assist policymakers and bioethanol producers in feedstock selection.The economic viability of bioethanol production using different feedstocks is dependent on factors such as local cost and composition of the feedstocks, energy cost, technology alternatives, plant capacity, etc. The sustainability of bioethanol production with respect to economic, environmental, and social indices has been carried out for some starchy feedstocks when utilised in different countries and/or under different conditionsIn this work, a sustainability study of bioethanol production from cassava, sweet potato, corn, and sorghum was carried out as well as a comparative assessment of the technological pathways utilising the feedstocks.16. Separate hydrolysis and fermentation (SHF) was selected in preference to simultaneous saccharification and fermentation (SSF) for maximum starch-to-glucose conversion17. Two enzymes in separate reactors  medium, the temperature of 100 °C, a pressure of 1.013 bar, and 0.082% dried base) and glucoamylase  was selected for saccharification18. The selected temperatures and pressures have been established as the optimum conditions for alpha-amylase and glucoamylase activities in their respective medium. More so, alpha-amylase and glucoamylase-based hydrolysis are associated with a high rate of glucose yield, exceptional resistance of the enzymes to denaturation, especially at high temperatures, and reduced viscosity of the starchy medium19. Saccharomyces cerevisiae was selected as the fermentation organism for its cost-effectiveness and efficient glucose conversion20. The ideal fermentation conditions (temperature of 32 °C and pressure of 1.013 bar for 48 h) were selected21.The dry grind milling method was chosen for the starchy feedstocks because it has been identified to be cheaper and produce a higher yield of bioethanol than the wet milling process22. while the first column performed at best condenser temperature (107.6 °C) and reboiler condition (111.3 °C pressure is 1.013 bar), the other performed at condenser temperature (84.1 °C) and reboiler condition (99.9 °C and pressure of 1.013 bar) for ethanol recovery. This approach concentrated the bottom of the first column and solids of the pretreatment section in a multi-effect evaporator. The dried solid was collected to be sold as animal feed. The bottom of the second column and the evaporator joined the distillation feed stream. The cost of the hydrophilic membrane, the complexity of installing pervaporation, and solvents recovery costs for azeotropic and extractive distillations23 favour the selection of molecular sieve adsorption process  for the four processes in dehydration.Double-effect distillation columns were the chosen distillation technology as they promote energy savings at a low cost24 was input in the Superpro Designer simulation startup window. The process flow models for the selected technologies were represented in the Superpro Designer simulation environment. Updated engineering plant and raw material costs were estimated using cost indices for November 201625 which were 100.3 and 99.7 respectively, and November 2013 (106.8) as the base cost using Eq.  as given in Table 24. The discounted cash flow parameters presented in Table 26 were input on the ‘Finances’ window. The indirect and fixed costs presented in Table The economic parameters extracted from Sinnott et al., 005 as gi27. The average cost of co-product (electricity) was set at $0.047/kWh. Utility steam and cooling water requirement costs within the programme were set at US$ 17.08 per 1000 kg and US$ 0.1 per 1000 kg respectively11. The exchange rate used was $ = ₦43726. The costs of major equipment were obtained from equipment suppliers and erectors28. Equipment of varying capacities from received quotations had their costs adjusted using the scaling expression given by Eq.  was set at $3.27 per gallonPrices of cassava, sweet potato, maize, and sorghum per kg are presented in Table i.Agricultural production of the feedstocksii.Feedstocks transportation to the processing siteiii.Feedstocks processing to fuel-grade bioethanol and coproducts (distillers dried grain with soluble and pomace).A life cycle approach of cradle-to-grave was chosen as the assessment approach using openLCA sustainability software. This method followed the product from its primal production stage of raw materials production through to its end use. The required information was the source of material and process parameters input  for life cycle impact assessment (LCIA) incorporated in SimaProv8.0 was imported into openLCA 1.5.5 and selected as the life cycle impact method. The CML baseline characterization model was then used to run the environmental assessment results where acidification, eutrophication, global warming, human toxicity, and photochemical oxidation potentials of the four bioethanol production processes were estimated.The environmental and economic performances of the four production routes were then established from environmental emissions/discharge and energy perspectives (net energy ratio and energy renewability). The costs of all the environmental emissions/discharge for the four selected starchy feedstocks were then estimated and added to the annual operating cost of each process. Economic parameters such as gross margin, return on investment, net present value (NPV), internal rate of return (IRR), and payback period were re-estimated to establish the financial implications of the pollutants.9 was used to estimate the total entropy of each unit. Evaluation of lost work and exergy components with Eqs. 9 was useith Eqs. 30 followsee Eqs.  and 7.4\Figure From Fig. Figure 3/annum bioethanol) from each of the feedstocks, which ultimately affects the utility cost, annual operating costs, and the overall profitability of the processes. Similarly, the internal rate of return for each of the four processes was higher than the interest rate (15.5%) from which the NPV was generated (see Table This economic viability of cassava and sweet potato was justified by their discounted payback periods (1.5 and 2 years) and net present value (NPV)  at an annual discounted rate of 15.5%  for the four bioethanol production routes and a project lifespan of ten (10) years  are 0.2453, 2.5261, 0.2067, and 0.2099 for cassava, sweet potato, corn, and sorghum respectively. The results show that the global warming potential was highest in sweet potatoes with carbon dioxide from fossils contributing the highest emission of 85.19%  as an alternative source holds promise. Organic farming has been expanding at an annual rate of 20% in the last decade31.The application of chemical fertilizers and herbicides generally improves crop production. However, concerns have been raised not only about the severe environmental problems posed by such practices but also about their long-term sustainability2 emissions from fossil fuel consumption in bioethanol production processes32. In this work, the results presented in Fig. 2 equivalent.Enzyme production had recently been reported to be the dominant contributor to the overall acidification burdens due to SOA large amount of nitrogenous fertilizer required to produce the needed sorghum for the set bioethanol throughput  that lead to shifts in species composition and increased biological productivityAmong the bioethanol production processes assessed, bioethanol produced from sweet potatoes was the dominant contributor to the eutrophication burden as seen in Fig. Although corn, sorghum, and cassava require larger amounts of liming material, the overall quantity of sweet potato needed to actualize the desired bioethanol throughput is larger because of its lower bioethanol yield Table .x and hydrocarbons or volatile organic compounds (VOCs)33. The four selected processes showed close photochemical oxidation burdens of 0.0089, 0.0067, 0.0076, and 0.0082 kg ethylene equivalent for cassava, sweet potato, corn, and sorghum respectively  of each emission of the emitted toxic substance into the air, water body, and soil is often measured relative to 1,4-dichlorobenzene  and is expressed as kg 1,4 DB equivalent. The principal HTP in the four processes was derived from the hydrolysis phase, which involves the use of acid. Sorghum was the dominant contributor to human toxicity burden  emissions among the four processes. This can be attributed to fossil fuel combustion derived from tractor activities . The impact of the high global warming burden of the sweet potato process was also demonstrated in Fig. The environmental performances  of bioethanol production processes from the selected feedstocks were critically assessed and the processes were ranked accordingly as shown in Table The high level of consistency displayed by corn and cassava through economic and environmental sustainability assessment indicators proves that they are the most viable of the selected four starchy feedstocks. Cassava and sweet potato stood first and second in the economic assessment with return on investment of 64.41% and 41.96%. However, the difference in the economic performances of corn and sweet potato is insignificant as evident from Fig. Table Table Table 2 out of the 30 317 tonnes/annum, while that of the sweet potato process produced 1374 tonnes/annum CO2 out of 312 776 tonnes/annum as shown in Table 2 from cassava and sweet potato processes emanated from fossil fuel combustion derived from bush clearing, ploughing, planting, mineral fertilizer application, harvesting, and subsequent transportation of the feedstocks to the processing site as summarized in Table 2 emission constituted a system bottleneck in the feedstock production phase.From Table Upon assigning emission/discharge costs to the environmental pollutants as presented in Table Figure Table 2 emission in corn production with about 62% of the overall CO2 released31 while a similar process in cassava production contributes about 30.15% of CO234. Hence, mineral fertilizer application was identified as a feedstock production phase bottleneck. According to the findings of Tongwane et al. (2016), and Nguyen et al. (2007), the use of compost manure derived from decayed plant residue left in the field is capable of reducing CO2 emission by 62% and 30.15% for corn and cassava productions respectively with the corresponding reduction in annual operating costs by $129 760, and $72 475 respectively as expressed in Table 29.Carbondioxide emissions in the feedstock production phase were derived from fossil fuel combustion from tractor operations  as estimated in Table 35. His study on the exergo recycled stream-economic assessment of bioethanol refining showed that energy savings of 61.8% could be achieved with the use of THIDC and molecular sieve hybrid configuration. The adoption of this hybrid configuration in this work is capable of reducing the cost of utility by $2827.81 and $1588.66 for the cassava and corn processing plants respectively as presented in Table The feedstock processing phase bottleneck was identified to be the distillation column with 61 MW and 32 MW of lost work in cassava and corn processing plants respectively. These figures amount to 59.81 and 53.44% of the total energy losses in their respective processes. As a way of reducing energy losses in fermentation broth purification, Suleiman et al. (2014) suggested the use of a hybrid configuration of a totally heat-integrated distillation column (THIDC) and molecular sieve adsorption column2 emissions and lost work in the feedstock production and processing phases respectively. The major limitations to this research work are the insufficiency of a reliable database on costs of feedstocks and materials with their variations, fluctuations in currency exchange rates, and the cost of acquiring licensed software that contains all the information of the selected feedstocks. Further comparative sustainability studies concerning these three indicators  should be conducted simultaneously on more attractive third and fourth-generation bioethanol feedstocks.A sustainability study of four selected starchy feedstocks  for bioethanol production was conducted to include economic, environmental, and energy indicators. The four-bioethanol production routes were found to be economically viable recording ROI values of 64.41, 41.96, 40.89, and 34.11% for cassava, sweet potato, corn, and sorghum processes respectively. While all the processes recorded positive NPVs for a discounted rate of 15.5% and a 10-year project span, the sensitivity analyses revealed an important constraint to the four processes, which limit the capacity utilization of the production routes to a minimum of 80% per annum below which the projects recorded losses. The four processes were also observed to be environmentally favorable from an energy perspective as they recorded net energy balance values of greater than 1. The four processes portrayed appreciable economic viability  despite adjusting the economic parameters to include pollutants emission/discharge costs. Because of the huge impact, carbon dioxide emission cost had on the sweet potato process, the final ROI value of the sweet potato process fell below that of the corn-based bioethanol process. As such cassava and corn-based bioethanol production processes represent the two most sustainable bioethanol production routes. The two production routes (cassava and corn-based processes) recorded a total lost work of 101 MW and 64 MW respectively. As a way of enhancing the energy and environmental performances of the best two processes, which would ultimately translate into better economic prosperity, compost manure utilisation and hybrid configuring of thermally integrated distillation column (THIDC) were suggested to minimize CO


LEPR, ACACA, FTO, LIPE or SCD on fatness, growth and fatty acid composition) and also disclosed interesting effects of new SNPs in less known genes such as LRIG3, DENND1B, SOWAHB, EPHX1 or NFE2L2 affecting body weight, average daily gain and adiposity at different ages, or KRT10, NLE1, KCNH2 or AHNAK affecting fatness and FA composition. The results provide a valuable basis for future implementation of marker-assisted selection strategies in swine and contribute to a better understanding of the genetic architecture of relevant traits.Iberian pigs and its crosses are produced to obtain high-quality meat products. The objective of this work was to evaluate a wide panel of DNA markers, selected by biological and functional criteria, for association with traits related to muscle growth, fatness, meat quality and metabolism. We used 18 crossbred Iberian pigs with divergent postnatal growth patterns for whole genome sequencing and SNP discovery, with over 13 million variants being detected. We selected 1023 missense SNPs located on annotated genes and showing different allele frequencies between pigs with makerdly different growth patterns. We complemented this panel with 192 candidate SNPs obtained from literature mining and from muscle RNAseq data. The selected markers were genotyped in 480 Iberian × Duroc pigs from a commercial population, in which phenotypes were obtained, and an association study was performed for the 1005 successfully genotyped SNPs showing segregation. The results confirmed the effects of several known SNPs in candidate genes (such as  Iberian × Duroc crossbred pigs are the main genotype employed to produce Iberian meat products in intensive production systems, although their sensorial meat quality is considered lower than that of pure Iberian pigs5. Furthermore, crossbred Iberian pigs are characterised by very heterogeneous developmental, productive and quality traits6, with great potential to identify the underlying genes. Knowledge of the molecular genetic basis of relevant traits would help in the design of marker-assisted selection programs.Iberian pig is an autochtonous fatty breed characterized by a high adipogenic potential, high appetite and outstanding meat quality. These features are consequence of their genetics and the traditional extensive production system, both contributing to the deposition of subcutaneous and intramuscular fat with a high content of oleic acid and antioxidantsLEPR8, ELOVL69 or ACSL411. Recently, Fernandez-Barroso et al.12 found significant associations of mutations in PRKAG3, CAPN1 and several other genes on meat quality traits in pure Iberian animals. Also, functional genetic studies have been performed in Iberian pigs which have provided information on functional candidate genes and pathways potentially involved in phenotypic variation15. On the other hand, the use of commercially available high-density SNP arrays for genome-wide association studies (GWAS) provides a systematic and powerful approach for deepening into the genetic basis of complex traits. This approach has led to the identification of many interesting genomic regions and candidate genes in different populations and breeds, including the Iberian22. Nevertheless, the applicability of commercial SNP arrays is limited because they only identify a fraction of genetic variation. This is due to the fact that they have been designed from SNPs detected in a few cosmopolitan breeds resulting in limited informativity and power, specially for the analysis of local breeds23. In contrast, whole-genome sequencing (WGS) can potentially detect all genetic variants, including causal ones24 and may allow the design of customized, highly-informative SNP panels, useful to uncover the genetic basis of relevant traits in local breeds. Such advances make genetic improvement achievable for relevant productive and quality traits in non-cosmopolitan pig breeds.Different candidate gene studies have been performed in Iberian pig populations, mostly in purebred animals or experimental crosses and with low-scale structural approaches, in order to deepen in the genetic architecture of productive traits. Relevant genes and mutations have been identified so far with this approach, mainly those detected in the IBMAP experimental populations such as The objective of this work was to discover and evaluate a wide panel of DNA markers for association with traits related to muscle growth, fat deposition and composition, metabolism and meat quality in Iberian crossbred pigs. For this purpose, a medium density custom genotyping protocol was used, designed with SNPs obtained and selected from a combination of whole genome sequencing data, transcriptome sequencing data and a candidate gene approach.https://arriveguidelines.org/arrive-guidelines).The study was performed according to the Spanish Policy for Animal Protection RD53/2013, which meets the European Union Directive 2010/63/UE about the protection of animals used in research. The experiment was specifically assessed and approved (report CEEA 2012/036) by the INIA Committee of Ethics in Animal Research, which is the named Institutional Animal Care and Use Committee (IACUC) for the INIA. The study was carried out in compliance with the ARRIVE guidelines  and local anesthesia  applied with a 25G needle inserted directly into the spermatic cord through the skin. Piglets were weaned at an average age of 24 days-old, and housed in groups of 12 piglets/pen distributed by sex and body weight (BW) during the transition phase. In the growing-fattening phase (from 70 days-old until slaughter), animals were housed by sex and BW in groups of 40 pigs/pen. Females received immunocastration using VACSINCEL  with two vaccinations at 120 and 148 days-old, respectively. From day 240 until day 340 of age, pigs were marketed whenever they reached the minimum market weight, which for Iberian crossbred pigs is set at 115 kg of carcass weight. At day 340 of age, all remaining pigs were sent to market, independently of their weight. The phenotype evaluation followed the methods already described in a previous paper using part of the animals involved in this study6.We used an Iberian × Duroc crossbred population. The animals were housed at a commercial farm, Ibéricos de Arauzo 2004 S.L. . A total of 477 crossbred piglets  born from 47 third and fourth-parity Iberian sows were involved in this study. The Iberian sows were inseminated with cooled semen from Duroc PIC boars . The sows were individually identified with an electronic ear tag and housed in groups until day 101 of pregnancy, when they were moved to individual pens until the end of the suckling phase. Sows and offspring were fed standard diets for the Iberian breed, adjusted to fulfil individual daily requirements, based on recommendations from De Blas et alDifferent measurements were carried out at the following time points: birth, weaning (24 days-old), days 70, 110, 150, 180, 215 and 240 of averaged age and at slaughter. Body weight was determined individually at all these time points. Morphological measures  were recorded at birth and at weaning for all piglets, with a measure tape. Backfat thickness and loin diameter were determined at weaning and at 110 and 215 days-old. Weight and length of carcasses and backfat thickness were recorded at the slaughterhouse.The average daily weight gain (ADWG) was calculated during the suckling phase (1–24), the transition phase (25–70), and during the five selected time periods of the growing-fattening phase until the day 240 of age . The feed conversion ratio (FCR) was calculated by pen during the five selected periods of the growing-fattening phase. Average daily weight gain and FCR were also calculated for the whole periods from birth to slaughter and from weaning to slaughter, respectively.longissimus dorsi (LD) muscle, right liver lobe and subcutaneous fat were taken at slaughter and biobanked at − 20 °C until fatty acid (FA) composition was analysed. Muscle drip-loss analysis was also carried out26.Samples of blood were obtained in vivo (110 and 215 days-old) and at slaughter, and employed for DNA extraction and metabolic status evaluation. Samples of Metabolic status was assessed at the time points of 110 and 215 days-old and at slaughter. Blood samples were assayed for determination of parameters related to metabolism of glucose (glucose and fructosamine) and lipid profiles , by means of a clinical chemistry analyzer .27 and expressed as a percentage of dry matter. These lipids were fractionated into the two main fractions of the fat tissue: neutral lipids (NL) and polar lipids (PL)27. Subcutaneous fat was extracted and separated in outer and inner layers to be analysed individually. From individual FA values, proportions of saturated, monounsaturated, and polyunsaturated FA , the unsaturation index (UI), and the sum of total n-3 FA (n-3) and n-6 FA (n-6) and its ratio (n-6/n-3) were calculated28. Moreover, the activity of stearoyl-CoA desaturase enzyme 1 (SCD1) was estimated using two desaturation indexes, the ratios of C18:1/C18:0 and MUFA/SFA29.Liver fat (LF) and intramuscular fat (IMF) were extracted as described by Segura and Lopez-BoteOut of the crossbred Iberian pig population, 18 male pigs with divergent postnatal growth patterns were selected for whole genome sequencing. Birth weight and BW at 240d were considered in order to select animals corresponding to three different growth categories: low birth weight and low final weight , low birth weight but normal final weight  and normal values for both birth and final weights  . A NanoDrop 2000 spectrophotometer  was used to measure the concentration and quality of the DNA. Whole-genome resequencing of the selected 18 animals was performed on an Illumina HiSeq 2000 platform by CNAG-CRG . About 1 μg genomic DNA was randomly fragmented. The genomic library was prepared according to the manufacturer’s protocol  using the TruSeq DNA sample preparation kit. The paired-end library was sequenced on an Illumina HiSeq 2000 using the v4 chemistry and 2 × 125 reads.Genomic DNA was obtained from the blood samples of all animals using the NucleoSpinhttp://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Trimmomatic package version 0.3830 was used for paired-end read trimming. Reads were trimmed to remove adapters, eliminate low quality or N-bases at the start or end of the read and scan the reads from the 3′-end with a 4 bases sliding window, cutting when the average Phred quality drops below 20. After trimming, reads were removed if they were shorter than 40 bp. Filtered paired reads were aligned to the porcine reference genome build 1131 by the Burrows-Wheeler Aligner (BWA version 0.7.10)32, employing the “bwa-mem” algorithm. SAMtools version 1.633 was used to filter unmapped or unproperly mapped reads, sorting, indexing and adding read groups. Picard tools version 2.18.9 (http://broadinstitute.github.io/picard/) was employed to mark duplicates. From this step on till the Variant Call Format (VCF) file, the reads were processed using the Genome Analysis Toolkit (GATK version 4.0.6.0)35. Base quality was recalibrated using BaseRecalibrator and variant calling was carried out for each sample using HaplotypeCaller, resulting in Genomic Variant Call Format files (GVCFs), which were combined to a VCF file using CombineGVCFs using default parameter values. Finally, variants were called using GenotypeGVCFs using default parameters. A total of 14,871,405 and 3,613,138 raw SNPs and INDELS were detected, respectively. The SNPs were quality filtered using the GATK VariantFiltration tool, excluding those with parameters “QUAL < 40 || QD < 5.0 || FS > 60.0 || MQ < 40.0 || DP < 30” and resulting in 13,324,328 filtered SNPs. VCFtools36 was employed to filter those SNPs with Minor allele frequency (MAF) lower than 0.05, leading to a final set of 11,756,179 filtered SNPs.FastQC software was employed to perform the quality control of the raw data (37 was used to annotate the variants from our WGS dataset with information in the VEP database (the merged cache file Sscrofa11.1 ver. 99). The default parameter of --distance 5 kb of VEP was applied to define the upstream and downstream variants. We also applied --sift b option to the prediction of the SIFT score38 of missense variants.Ensembl variant effect predictor (VEP ver. 99)39 removing a total of 20,049 SNPs with r2 > 0.6 in 1000 kb windows. Finally, a total of 8419 SNPs mapped on autosomes were used for downstream analyses. Allele frequencies within growth groups were calculated with PLINK 1.9. We kept those SNPs having an allelic frequency difference between groups higher than 0.25 in at least one comparision . As a result, a total of 2259 SNPs remained.We focused on missense SNPs located on annotated genes and showing differences in allele frequencies between groups differing in growth patterns. A total of 32,688 markers were classified as missense out of the 11.7 million, according to VEP. LD-pruning was implemented with PLINK 1.9Genotyping by Sequencing (GBS) in the Iberian × Duroc population, from which phenotypes were also available. The list of markers genotyped by GBS is included as Supplementary Table Among these preselected SNPs, 1023 were technically adequate for Agriseq genotyping. These were included in the design and genotyped by 40 (Suplementary Table ® OpenArray™ (OA) Genotyping platform . Genotyping was carried out in a QuantStudio™ 12 K Flex Real-Time PCR System  at the Veterinary Molecular Genetics Service . DNA samples were loaded and amplified on the arrays following manufacturer instructions. Detection of allele-specific signal intensities was performed using OpenArray NT Imager, and the genotypes were called using OpenArray SNP Genotyping analysis software. In addition, SNPs images were visually inspected to detect any clustering issues.Besides, we complemented this panel with 192 candidate SNPs obtained from the literature mining and from pure and Duroc-crossbred Iberian muscle RNAseq dataleave-one-chromosome-out option from the software GCTA41. This option implements a mixed linear model-based association analysis using the following general model:y is the phenotypic value corresponding to each trait, a is the mean term, b includes the additive effects (fixed term) of the analysed SNP, X includes the genotype indicator variable that is coded as 0, 1 or 2, f includes the remaining fixed effects and covariates that were different depending on the group of traits analysed  except those mapped on the same chromosome than the SNP analysed and e is the residual. The genetic variance var(g-) is estimated based in the null model y = a + g- + e and then fixed while the association between each SNP and the trait is tested. This variance is re-estimated each time that a chromosome is excluded when the GRM is calculated. False discovery rate (FDR) was controlled for using the library q-value42 in Rstudio43. SNPs with a p-value and q-value lower than 0.05 and 0.10, respectively, were considered as significantly associated with the trait tested.The total SNP dataset (1215 markers) was filtered for association analyses using PLINK 1.9 by MAF value (0.1) and excluding markers with genotyping errors, with 1005 SNPs remaining after the filtering. These analyses were carried out on 477 individuals with genotyping and phenotyping data. SNP effects were analysed with the An average of 83 million paired-reads were generated per sample by Illumina sequencing, ranging from 67 to 100 million, with a mean coverage of 8.4 ×. After quality control, 98% of the reads were mapped, on average, to the reference genome (Sscrofa11.1), and over 14 million variants were detected. After the application of several quality filters and functional and technical selection criteria, 1023 missense polymorphisms were finally genotyped by GBS.GBS quality metrics confirmed the reliability of the genotyping procedure. Both average sample and marker call were 93.9%, and 90.2% of the markers had a call rate above 90%. Average coverage was 183 ×, well above the Agriseq recommended coverage of 100 × for genotyping purposes. Uniformity (percentage of target bases that have at least 0.2 times the mean depth) averaged 92.9%.Out of the 1023 SNPs included in the GBS marker panel, 120 polymorphisms were discarded due to lack of segregation (MAF < 0.10) or genotyping errors, resulting in 903 GBS markers with useful data for the association study.In parallel, 192 markers in candidate genes were genotyped by openarray. Out of them, 60 were monomorphic and a total of 30 discarded due to low variability (0 > MAF < 0.10) or genotyping errors, thus 102 OA markers remained informative.Joint results of GBS and OA genotyping resulted in 1005 markers being included in the association study . Minimum allele frequencies (MAF) distribution for the genotyped markers in the Iberian crossbred population is shown in Fig. p-values, for those genes showing at least one significant association (q < 0.10).The association study was performed for the 1005 successfully genotyped SNPs showing segregation within our population and all growth, fatness, FA composition and metabolic traits available  for which previous biological or functional hypothesis were available.ACACA, EPHX1 and FREM2 genes  for slaughter weight, 10 kg for carcass weight (1.25 SD) and 0.125 kg/d (1.9 SD) for global ADG  included LEPR, NFE2L2, FTO and LIPE candidate genes .Backfat was affected by ts Table  and withLongissimus dorsi muscle and liver tissues . A total of 100 significant associations were found for these traits  only in the backfat outer layer; while other genes such as AHNAK, LIPE, EPHX1 or TNF had effects on different locations affecting similar traits (Table Fatty acid composition was determined in backfat (inner and outer layers) and in 0 Tables  and 5, ws Tables  and 6, bts Table .Table 4SSCD gene were associated with palmitoleic acid and the desaturation ratio oleic/stearic only in the neutral lipid fraction of liver   and palmitoleic acid (C16:1n-7), respectively, in both the backfat outer layer and the neutral lipids from muscle (Table Three different SNPs located in ) Tables , 4. Howe) Tables . Also, tIRX3, ADIPOQ, MSTN or MYOD1, had significant effects on just one trait  after the multiple test correction.In this study, a medium-throughput genotyping approach was performed after an initial SNP discovery step, in order to uncover DNA polymorphisms related to relevant productive traits. SNPs analysed were mostly obtained from WGS data, and complemented with a panel of biological and functional candidate genes/SNPs, obtained from literature and RNAseq data.Genotyping results showed a good level of informativity of the markers derived from WGS, with a high proportion of markers showing intermediate frequencies (56% showed 0.3 < MAF < 0.7) and scarce proportion being discarded due to low segregation (10.6%). These results support the validity of the SNP discovery approach perfomed from WGS data. On the contrary, markers obtained from bibliography and RNAseq data were less informative (33% showed 0.3 < MAF < 0.7) and a high proportion was detected as monomorphic or scarcely informative (50%). This finding was not unexpected as WGS markers were obtained from sequencing data from animals of the same Iberian crossbred population employed for the association study, while candidate genes/SNPs were previously identified in different pig breeds and populations.In spite of a lower number of previously known candidate SNPs, and their lower informativity, in comparison to WGS-derived markers (102 vs 903) a much higher number of significant associations were observed for the SNPs with previous evidences of association or differential expression. This is not surprising as those fulfill more functional criteria than the ones discovered in the present work from WGS data. In fact, out of 174 significant associations, 152 involved previously identified SNPs in candidate genes and only 22 involved WGS-derived markers. Besides, out of the 152 associations related to previously characterized SNPs, 62 corresponded to well-known markers with previous evidences of association, and 90 corresponded to markers discovered from RNAseq data, within genes showing differential expression between Iberian pig genotypes or with a potential regulatory role. This finding supports the usefulness of deep sequencing transcriptome data mining to uncover structural variants with interesting effects on phenotype.ACACA and SCD, were found to affect, respectively, birth measures and livelong performance traits. These genes are involved in fat synthesis and metabolism and, indeed, significant effects were also found for both genes on FA composition. However, their potential role on growth traits is not clear so far. Acetyl-CoA carboxylase (ACACA) is a multifunctional enzyme system that catalyzes the carboxylation of acetyl-CoA to malonyl-CoA, the rate-limiting step in FA synthesis. In agreement, our results show a significant effect of this gene on palmitoleic acid abundance in backfat and muscle and suggestive effects on many main FA and FA ratios. Besides this main role, the ACACA gene influences mitochondrial membrane potential, thus it might condition cell proliferation and tissue growth44. In fact, a deficiency in ACACA activity was associated to defects in early growth and muscle development in humans45. Stearoyl-CoA desaturase (SCD) catalyzes the ∆9-cis desaturation of palmitoyl- and stearoyl-CoA, which are converted into palmitoleoyl- and oleoyl-CoA, respectively. In addition to being components of tissue lipids, MUFAs also serve as mediators of signal transduction, cellular differentiation, food intake, apoptosis, and mutagenesis, and therefore, variation in SCD function in mammals would be expected to have an effect on a variety of key physiological events, including growth46. Thus, it has been proposed that BW gain may be associated with SCD increased activity. In fact, a different polymorphism in SCD gene was associated with ADG and FCR in lean pigs47. Nevertheless, the three SNPs analysed in this study , located in the promoter region and in full linkage disequilibrium, had not been previously associated with performance traits50. This novel finding is also striking because of the size of the effect, especially on BW traits, with an estimated additive effect close to 30 kg. This finding should be cautiously interpreted, as the frequency of the homozygous genotype was low and the effect could be overestimated. Interestingly, Estany et al.48 found that C-T-A haplotype was additively associated with enhanced C18∶1/C18∶0 desaturation index both in muscle and subcutaneous fat, but not in liver, in a purebred Duroc line. According to our results, the main effect of SCD gene regarding FA composition is detected in liver neutral lipid fraction, with C-T-A haplotype enhancing the desaturation index as well as C16:1n-9 content. Also, a potential effect on IMF was reported for this mutation49 which has not been validated in the present work.Regarding growth and development traits, two main genes, FREM2, EPHX1, SOWAHB or TFRC15. Thus, those genes fulfill a functional criteria to be considered involved in the phenotypic differences observed between Iberian and Duroc genotypes. The FREM2 gene (FRAS1 related extracellular matrix protein 2) encodes an extracellular matrix protein with a role in morphogenetic processes51. In agreement with our findings, the FRAS/FREM complex is particularly important during early development. In humans, mutations in this gene cause the Fraser syndrome, a multisystem disorder involved in the structural adhesion of the skin ephitelium to its underlying mesenchyma52 and in pigs this gene has been proposed as candidate for developmental morphological traits such as presence of wattles53, The genes SOWAHB and EPHX1 showed somewhat similar association results, both affecting livelong growth traits and some fat deposition traits. The gene SOWAHB (sosondowah ankyrin repeat domain family member B) is part of the Ankyrin family, involved in membrane skeleton organisation, ionic transport, protein recognition as well as cell–cell adhesion regulation54. Moreover, SOWAHB is activated in response to insulin and possibly involved in insulin resistance55. Besides its effect on growth traits, significant nominal p-values were observed in the test of association with fatness traits at different ages  gene showed significant association results for growth as well as FA composition traits, specifically for C20:1(n-9) and for C20:3(n-6) contents. The enzyme encoded by this gene is able to either detoxify or bioactivate a wide range of substrates56 including epoxides derived from endogenous polyunsaturated FA, thus mediating several biological processes such as inflammation or angiogenesis, and regulating crucial signaling pathways for cellular homeostasis, adipocyte differentiation and insulin response59. This gene was shown to be upregulated in biceps femoris, longissimus dorsi and backfat of pure Iberians in comparison to Duroc genotypes15. The upregulation of SOWAHB and EPHX1 genes in pure Iberians in different tissues may be related to their potential role in insulin response and adiposity, which is in agreement with the suggestive association of their structural variants with fatness traits and significant association with weight at growing stages, when Iberian pigs are known to develop a compensatory growth and a more intense development than Duroc genotypes5. The TFRC gene (Transferrin Receptor) encodes a cell surface receptor necessary for cellular iron uptake and has been studied as a positional candidate gene for disease susceptibility60. In addition, it acts as a lipid sensor that regulates mitochondrial function by regulating activation of the JNK pathway61. Interestingly, TFRC was upregulated in loin muscle of Duroc × Iberian crossbred pigs at birth14, but it was upregulated in biceps femoris and backfat of Iberian purebred growing pigs15. According to our results, the SNP in this gene affects BW and ADG. Thus, the opposite regulation observed at birth and growing stages would be related to the different paucity of muscle developmental processes observed in Iberian vs Duroc genotypes, with the latter showing higher prenatal development and birth weight and the Iberian purebreds showing increased muscle development at growing stages.Other interesting genes and SNPs that have not yet been established as candidates for growth traits were also identified. Some of them were obtained from RNAseq data and were differentially expressed between Iberian and Iberian × Duroc crossbred or Duroc purebred pigs, such as LRIG3, DENND1B or TMCC1. Although none of these genes has been studied for association with any productive trait, all have roles or evidences which suggest involvement in early developmental processes. LRIG3 (leucine-rich repeats and immunoglobulin-like domains 3) plays a role in embryo development, including cranio-facial morphogenesis and neural crest formation62. Also a direct relationship for LRIG3 and early growth was observed since KO mice were smaller than wild-type ones63. In agreement, our results show significant effects on birth weight and thoracic circumference and suggestive effects on all remaining traits recorded in neonates, including those related to head development. DENN Domain Containing 1B (DENND1B) gene has an important role on cytokine production and regulation of T cell receptor signaling and mutations or loss of this factor were associated with immune diseases in neonates64. Interestingly, methylation of DENND1B gene in venous umbilical cord blood at delivery has been associated to birth weight in humans65. According to our results, this gene influences birth weight, abdominal circumference and biparietal diameter and is suggestively associated to most early traits recorded at birth and at weaning. TMCC1 (Transmembrane And Coiled-Coil Domain Family 1) is an integral endoplasmic reticulum (ER) membrane protein that has been associated with central adiposity and waist circumference66 and is supposed to be involved in regulation of myogenesis67. Our results indicate effects on biparietal and thoracic diameter as well as thoracic circumference, and also at a suggestive level, on several other birth traits and later fatness traits such as backfat.Newborn developmental traits were also affected by several SNPs detected through WGS, located in relatively unknown genes such as LEPR, LIPE or FTO, with the clearest results detected for LEPR. Leptin receptor is known to have a determinant role on energy homeostasis and has been widely studied as functional and positional candidate gene for fat deposition traits. Iberian pigs are known to carry a fixed mutation in this gene which is considered a causal mutation contributing to their characteristic trend for adiposity and high appetite as well as their leptin resistant phenotype8. This mutation has been evaluated in different genetic backgrounds, mainly in experimental pig populations, but also in other breeds and commercial populations70. According to the present results, the effects of this SNP on fatness are further validated in our Iberian × Duroc commercial population, with significant effects on different backfat thickness measures and global ADG, and suggestive associations with BW, FA composition and cholesterol, HDL and LDL levels. As expected, the Iberian T allele increases fattening, with an additive effect close to 0.5 cm for backfat, which means an estimated difference of almost 1 cm between homozygous animals for alternative alleles .Fattening traits were mainly affected by SNPs located in known candidate genes such as NFE2L2 gene (nuclear factor erythroid 2-related factor 2) was associated with fatness. This gene codes a transcription factor whose main role involves the regulation of the expression of antioxidant proteins that protect against oxidative damage. Moreover, this transcription factor is determinant in the maintenance of homeostasis, participating in the regulation of metabolism, inflammation, autophagy, proteostasis, mitochondrial physiology, and immunity71. This gene was selected from RNAseq data for SNP discovery, despite not being differentially expressed, due to its potential role as predicted regulator for the differential expression observed between Iberian pig genotypes14. Our results show a significant effect on backfat thickness and suggestive effects on intramuscular fat content and FA composition, especially in loin, in agreement with its known role in muscle mitochondrial biogenesis and the predicted role as regulator of muscle metabolism.Besides the known candidate genes, the KRT10 and NLE1, both affecting the proportions of SFA and MUFA in backfat and loin. KRT10 (keratin 10) was studied because it was overexpressed in muscle from pure Iberian in comparison to crossbred pigs13, although it does not have a known role in relation to fat metabolism. However, it has been recently shown that KRT10 expression is suppressed by serum lipids72 and, interestingly, different keratin genes had been associated to FA composition traits in a chromosome 12 survey in Iberian × Landrace backcrossed pigs73. In fact, the KRT10 gene maps on SSC12, where several QTL for FA composition traits have been discovered. Moreover, KRT10 was found as the most significant differentially expressed gene according to ACACA genotype regarding polymorphism ALGA0066302A, not analysed here, which in turn is associated with FA composition. On the other hand, the NLE1 gene (Notchless homolog 1) plays a role in regulating the Wnt pathway, which is known to play a central role in adipocyte differentiation and lipid metabolism74. In fact, Wnt pathway plays a dual function in adipocytes, including a well-known repressive effect on adipogenesis and the stimulation of leptin production in mature adipocytes75. In agreement with the antiadipogenic effect, a higher expression of this gene was observed in loin of crossbred Iberian pigs, which are leaner than purebreds14. Our association results do not relate this gene with adiposity traits, but clearly demonstrates its involvement in relevant traits related to FA metabolism and profile, which influence meat quality, in the two main productive tissues, fat and muscle, and especially on this last one. The allele that increases oleic acid content and monounsaturated to saturated fat proportions, with effects ranging from 0.5 to 1 SD in magnitude, also shows suggestive positive effects on BW and ADG at late growing stages, meaning it could be an interesting marker to improve meat quality without negative pleiotropic effects on other relevant traits.The main genes affecting FA composition were KCNH2 gene (Potassium Voltage-Gated Channel Subfamily H Member 2) was associated with the main PUFA contents in backfat, although, suggestive effects were observed on the muscle FA profile and on some growth and carcass traits. This gene was previously found overexpressed in loin and biceps of pure Iberians in comparison to crossbreds and Duroc animals14. Our results agree with previous findings in humans showing that mutations in KCNH2 gene are associated with alteration of insulin homeostasis and glucose and lipid metabolism76 and its methylation is related to obesity77. AHNAK gene (Neuroblast differentiation-associated protein) codes a nucleoprotein involved in adipogenesis and lipid metabolism. AHNAK KO mice have reduced fat accumulation and decreased serum triglyceride levels as well as increased expression of genes involved in lipolysis and FA oxidation78. In agreement, its expression was higher in pure Iberian animals14, which are characterised by a higher adipogenic potential than crossbreds. In addition, our results show effects of this SNP on different FA in backfat and liver and a suggestive effect on backfat thickness at weaning.Several other SNPs showed significant effects limited to a few FA. FASN, LIPE and TNF had similar effects, mainly on C14:0 in backfat and muscle. As mentioned previously, LIPE gene (hormone sensitive lipase) was one of the genes significantly affecting backfat depth at slaughter. The LIPE allele with a positive effect on backfat also positively affected C14:0 and C16:0 in backfat and loin and had suggestive negative effects on several MUFA parameters and glucose metabolism indicators. LIPE is a key enzyme in the mobilization of FA from acylglycerols79, which has been related to different fat deposition and FA profile traits in different species. On the other hand, FASN gene (fatty acid synthase) codes a multifunctional enzyme that catalyzes the synthesis of FA and has been repeatedly associated with FA composition traits, especially affecting short chain saturated FA80, as in our results. This gene, together with ACACA, regulates de novo synthesis of FA. Thus, FASN, ACACA and LIPE are involved in the regulation of fat deposition by balancing lipogenesis and lipolysis, and significant association results are obtained for all three of them. On the other hand, tumor necrosis factor (TNF) is an adipokine that promotes insulin resistance and is associated with obesity-induced type 2 diabetes81. In agreement, our results indicate a significant effect on C14:0 in backfat and loin, but also many other suggestive associations are found for other saturated and monounsaturated FA, as well as carcass and meat quality traits  and BW records along growth.On the other hand, the genes TBC1D16 gene, which has a role in membrane trafficking and molecule transport and is known to be dysregulated in obesity82. Besides the significant effect on HDL, this SNP showed suggestive effects on many different FA traits related to MUFA contents and MUFA/SFA ratios in loin and liver, which are known to be correlated with physical markers of obesity such as body mass and adiposity indexes83, in agreement with the role of this gene, although no effect was observed on fatness.Scarce significant associations were found for metabolic traits. Only HDL concentration was significantly associated with two different SNPs, both derived from WGS data, at two different ages. The association found at 110 days old is interesting as it involves LEPR, SCD, ACACA, FASN or LIPE). Moreover, our approach allowed for the discovery of interesting new effects of SNPs in less known genes  affecting BW and ADG at different ages, as well as fatness and FA composition . Most significant associations came from SNPs identified through structural mining of transcriptome deep-sequencing data. In spite of a relatively small number of significant associations detected for WGS-derived markers, the approach employed here is proposed as a useful genome-wide strategy for the discovery of untapped genetic basis of productive traits. Our results contribute to a better understanding of the molecular genetic basis of relevant traits in pigs, including both growth and yield-related traits as well as traits involved in sensory and technological quality of meat which are essential for Iberian pig cured products. Besides, our results provide interesting SNPs and new candidate genes for association studies in different pig breeds and populations and for future implementation of marker-assisted selection strategies. Different markers can be highlighted as most promising, such as KRT10, NLE1, TFRC, NFE2L2, SCD or LEPR, and some of them may allow the improvement of meat quality without negatively affecting growth efficiency, or viceversa.A combined approach of candidate SNP recovery from literature and SNP discovery from WGS and RNAseq data has been successful in validating the effects of different SNPs in candidate genes previously associated with fatness, growth and FA composition traits (such as Supplementary Legends.Supplementary Table S1.Supplementary Table S2.Supplementary Table S3.Supplementary Table S4.Supplementary Table S5.Supplementary Table S6.


Trichoderma gamsii strain T6085 is a potential biocontrol agent to limit the infection of F. graminearum and F. culmorum in wheat. However, the possible impacts of T. gamsii T6085 on the broader microbiome associated with the wheat plant are not currently understood. Therefore, we identified bacteria and fungi associated with different wheat tissues, including assessment of their relative abundances and dynamics in response to the application of T6085 and over time, using amplicon sequencing. Residues of the prior year’s wheat crop and the current year’s wheat spikes were collected at multiple time points, and kernel samples were collected at harvest. DNA was extracted from the collected wheat tissues, and amplicon sequencing was performed to profile microbiomes using 16S v4 rRNA amplicons for bacteria and ITS2 amplicons for fungi. Quantitative PCR was performed to evaluate the absolute abundances of F. graminearum and T. gamsii in different wheat tissues. Disease progression was tracked visually during the growing season, revealing that FHB severity and incidence were significantly reduced when T6085 was applied to wheat spikes at anthesis. However, treatment with T6085 did not lessen the F. graminearum abundance in wheat spikes or kernels. There were substantial changes in F. graminearum abundance over time; in crop residue, pathogen abundance was highest at the initial time point and declined over time, while in wheat spikes, pathogen abundance increased significantly over time. The predominant bacterial taxa in wheat spikes and kernels were Pseudomonas, Enterobacter, and Pantoea, while Alternaria and Fusarium were the dominant fungal groups. Although the microbiome structure changed substantially over time, there were no community-scale rearrangements due to the T6085 treatment. The work suggests several other taxa that could be explored as potential biocontrol agents to integrate with T6085 treatment. However, the timing and the type of T6085 application need to be improved to give more advantages for T6085 to colonize and reduce the F. graminearum inoculum in the field.Fusarium head blight (FHB) is a major fungal disease that causes severe yield and quality loss in wheat. Biological control can be integrated with other management strategies to control FHB. For this purpose,   Fusarium is the genus of pathogens that cause FHB, with primary causal agents being F. graminearum and F. culmorum  is a prominent disease of wheat worldwide. The spread of the FHB pathogens reduces wheat production and causes toxins to contaminate harvested wheat grains, decreasing both the quality and quantity of wheat products . Fusariuculmorum . Fusariue fungus .Fusarium graminearum overwinters within crop residue. In this phase of its lifecycle, the pathogen acquires nutrients from decaying plant materials and lives saprotrophically during the fall, winter and spring seasons , warm and humid environmental conditions favor spore production and successful infection  and nivalenol (NIV) are the major Type B trichothecenes. These mycotoxins affect the baking quality of wheat-based food products. They cannot be easily eliminated during food processing due to the stability of the toxins under typical food processing conditions. Consumption of mycotoxin-contaminated foods can lead to health problems in humans  seems particularly important  was prepared on the day of application from cultures on potato dextrose agar (PDA) plates . For inoculation of crop residues from the prior cropping season, inoculum was prepared on whole millet grain. Briefly, 15 mL of aqueous spore suspension  was used to inoculate 1 kg of millet seeds in sterile plastic bags (previously wet with 300 mL of distilled water and sterilized by autoclaving for 20 min at 121°C). The millet seeds were incubated at 24°C under 12 h light/12 h darkness for 10 days, then dried in a laminar flow hood and stored at 4°C until use.Inoculum of strain T6085 was prepared for application in the field trial using two different methods. For inoculation of wheat spikes, an aqueous suspension of spores (10Triticum durum cv Tirex) was sown on 11 December 2018 in a no-tillage system, using a no-till seeder and applying about 400 seeds m–2 in rows 15 cm apart from each other. P and K mineral fertilizers were applied before sowing ; mineral nitrogen was applied splitting the total amount (170 kg ha–1) equally between the stages of beginning stem elongation and tillering. Weeds were controlled using a post-emergence herbicide application . The crop was harvested on the 24 July 2019.An experiment was performed during the 2018–2019 cropping season to evaluate the effect of the application of T6085 on bacterial and fungal communities naturally associated with wheat residue, spikes and kernels. The experiment was established at the Center of Agro-environmental Research “Enrico Avanzi,” San Piero a Grado, Pisa . Durum wheat (Random.org) with five blocks and a plot size of 6 m wide × 9 m long (40 rows for plot). Four treatments were implemented: (1) Non-inoculated control; (2) wheat spikes at anthesis inoculated with T6085 ; (3) crop residues from the previous cropping season  inoculated with T6085 ; (4) both spikes at anthesis and crop residues inoculated with T6085 . Natural Fusarium inoculum was relied upon for the development of FHB.Plots were assigned using a randomized block design (randomization via –2) while walking linearly into the field and spreading the inoculum all over the plot. For treatments with no inoculation of crop residues , sterile millet seeds were distributed in the same manner and at the same rate. Samples of residue from the prior cropping season were collected 1 day before the introduction of T6085 , after 1 month (Tcr1), and just before the harvest (Tcr2). At each sample collection, a quadrat was marked by placing a 50 cm × 50 cm frame within the central region (2 × 3 m) of each plot and 50 pieces of wheat straw residue were collected by hand from within the quadrat (quadrat method). Residue pieces were cut longitudinally, washed three times for 1 min in sterile water to remove soil particles, dried in a sterile laminar flow hood, ground with a Cyclotech 1093 Sample mill and stored at –20°C until use for microbiome profiling.At the beginning of stem extension (Feekes stage 6), T6085 was introduced to the soil surface of appropriate plots  by distributing colonized millet seeds by hand (4 g m–1) for treatments 2 and 4, while treatments 1 and 3 were given an equal volume of sterile water as a mock inoculum. Spikes were sampled using the quadrat method described above, taking a subsample of 10 spikes per sample. Spike sample collection took place 1 day before the introduction of T6085 to spikes , 14 days post-inoculation (dpi) (Tsp1), 28 dpi (Tsp2), and at harvest . From each spike, 6 spikelets were subsampled  were collected and stored at –20°C until use for microbiome profiling.At anthesis, T6085 inoculum was applied on spikes  was defined as the % of spikes showing premature bleaching of some or all spikelets. Disease Severity (DS) was defined as the % of spikelets within a spike that were symptomatic. At the end of the cropping season, wheat was harvested, and several agronomical parameters were evaluated on sub-samples, such as spike number (count m–2), straw and spike fresh weight (g m–2) and total kernel weight (g m–2).At time points Tpost hoc contrasts by using SygmaPlot 12.0 to evaluate the effect of T6085 application on disease development and crop productivity. The threshold for statistically significant effects was set at p ≤ 0.05.The DI and DS values, after angular transformation, and agronomical data were submitted to analysis of variance (ANOVA) and Tukey’s –1, based on spectrophotometric concentration measurement . The ITS2 region of the fungi (employing ITS3_KYO2 forward primer and ITS4_KYO3 reverse primer) and the v4 region of 16S rRNA gene of bacteria (employing F515 forward primer and R806 reverse primer) were amplified  were included at 0.25 μM in the 16S rRNA amplification only (Ground tissue samples were stored in DNA/RNA Shield (ZymoResearch) and shipped by express courier to Winnipeg, Canada. The DNA was extracted from a 0.1 g subsample using the GeneJet plant genomic DNA extraction kit (Thermo Fisher Scientific). The concentration of extracted DNA was diluted to a consistent 2 ng μLmplified . Primersion only .16s rRNA libraries, and the v3 reagent kit (2 × 300 bp) was used for ITS2 libraries. Negative controls (PCR reactions without template DNA) and mock communities were included in each sequencing run. For the bacterial libraries, the mock community was product MSA-3002 from the American Type Culture Collection, and for the fungal libraries, a mock community from PRJNA790613 at the NCBI SRA.Amplified PCR products were purified using KAPA HyperPure beads (Roche). Dual indices and adapters were attached via the Nextera XT Index Kit (Illumina), according to the manufacturer’s protocol. Indexed samples were pooled in equimolar quantities. Because some smaller than expected fragments (likely primer dimers) were present in the library, the pooled library was size-selected using a Flashgel recovery cassette (Lonza) and purified again with KAPA HyperPure beads. The amplicon size distribution of the pooled library was visualized using the TapeStation system (Agilent), and the concentration of MiSeq-compatible amplicons was determined using the KAPA Library Quantification Kit for Illumina Platforms (Roche). PhiX was spiked into each library at a rate of 7.5%. The samples were split across four sequencing runs. The MiSeq v2 reagent kit (2 × 250 bp) was used for v4 The sequence data were processed, and taxonomic identifications were assigned using CLC Genomics Workbench version 20.0.4 (Qiagen). The low-quality sequences (limit 0.05) and sequence ends containing ambiguous nucleotides (maximum 2) were trimmed off. Adapter sequences were trimmed and reads below a length of 15 were discarded. Reference-based operational taxonomic unit (OTU) clustering was performed at a 99% similarity percentage. To identify the likely taxonomic origin of fungal amplicons, the UNITE database v7.2  was used , while tT. gamsii and F. graminearum within samples, using assays Fus.GRA and Tgam from Fusa.GRA assay and 92.95% for the Tgam assay. The abundances of T. gamsii and F. graminearum were calculated using the standard curve method. Changes in F. graminearum densities over time and due to the presence of T. gamsii T6085 were analyzed by ANOVA, modeling log-transformed abundance values on treatment, time point, the interaction between treatment and time point, and the blocking factor in the experimental design. The Tukey HSD method was used to identify significant contrasts where the main effects were significant.Quantitative PCR (qPCR) was performed to calculate the densities of p ≤ 0.05).At 14 dpi of T6085, there was no naturally occurring disease in any spikes collected. However, by 28 dpi of T6085, the typical symptoms of FHB blight, such as bleaching of some or all the spikelets within each spike, appeared. A reduction of DI was recorded in all the treatments in which T6085 was applied as spike and/or soil inoculum, with Treatment 2 (T6085 applied to flowering spikes) showing a significantly reduced percentage of affected spikes (p ≤ 0.05).The pattern of effects for DS was the same as was observed for DI; the percentage of affected spikelets within each spike was generally reduced in all the plots where T6085 was applied, but the decrease was only statistically significant in the contrast of Treatment 2 vs. the non-inoculated control , thus demonstrating that the beneficial effect of the antagonist did not last over a long time.p > 0.05).At the end of the cropping season (on 24 July 2019), wheat was harvested from all plots, and agronomic factors were measured to evaluate the possible effects of the application of T6085 on wheat yield and yield components. There were no significant differences among treatments in spike density or the biomass of straw, spikes, or grain at harvest , and it decreased over time . The abundance of F. graminearum in wheat spikes showed an opposite trend, as values were significantly higher at the last time point (Tsp3) compared to all earlier time points (p ≤ 0.05).The abundance of F. graminearum abundance due to the application of T6085 (p > 0.05).Across experimental treatments, there were no significant changes in p ≤ 0.05). In crop residue, bacterial richness increased significantly from Tcr1 to Tcr2, and fungal richness increased significantly over time. In wheat spikes, bacterial richness was significantly lower at Tcr0 than at other time points, while the fungal richness significantly decreased from Tsp1 to Tsp2  and Shannon diversity index were calculated to further understand the dynamics in the microbial community in different wheat tissues due to the T6085 treatment and over time. Crop residue had bacterial and fungal richness within the range between 1,343 and 2,889 OTUs and 74–178 OTUs, respectively. In both wheat spikes and kernels, fungal richness was less than 100 OTUs, while bacterial OTU richness was comparatively higher. The richness values did not change significantly in response to the application of T6085 . However to Tsp2 .cr2 compared to Tcr0 . Further, bacterial diversity was significantly higher at all later time points compared to Tsp0 in wheat spikes, while there was a significant increase in diversity in the fungal community associated with wheat spikes from Tsp1 to Tsp2 .Similarly, the Shannon index of bacterial and fungal OTU diversity was not significantly changed by the application of T6085 . Howeverp > 0.05)  .p ≤ 0.05)  . These dn = 1 observations, and so these comparisons must be taken with a grain of salt.We explored network analyses  as an alternative approach to reveal whether broad community rearrangements could be observed. Interestingly, for microbiomes associated with wheat spikes, we observed only half as many significant associations among sequence variants for samples that had been treated with T6085, compared to samples that had not been treated with T6085 . For exacr0 and Tcr1, 1 040 between Tcr0 and Tcr2, and 589 between Tcr1 and Tcr2. In wheat spike samples, differentially abundant OTUs numbered 76 between Tsp0 and Tsp1, 120 between Tsp0 and Tsp2, 111 between Tsp0 and Tsp3, 44 between Tsp1 and Tsp2, 68 between Tsp1 and Tsp3 and 69 between Tsp2 and Tsp3  a significant reduction in DS was not observed  for the pathogen over the biocontrol agent, the biocontrol agent may not achieve the density required to inhibit the pathogen. In the present experiment, rainfall was 140 and 100 mm during April and May 2019, respectively, much higher than the respective 30 year average, i.e., 75 mm in April and 62 mm in May . During observed . TherefoT. gamsii T6085 as a biocontrol agent was evaluated to understand off target effects of the T6085 treatment on the wheatfield. The number of observed taxa (OTU richness) and the Shannon diversity index are commonly used estimates to measure the biodiversity of microbial communities and it is crucial to calculate the diversity indices to see the alteration made by the T6085 . In observations from our biological samples, we observed OTUs that similarly could not be placed below Hypocreaceae; therefore, it is likely that T. gamsii was represented among these observations. Therefore, the method we used for fungal community profiling does not provide good discrimination among genera or species within this family. In addition, even though the ITS is considered a superior marker in species identification across the Kingdom fungi, the discriminatory power of ITS in Ascomycota is lower  can be found below: SS, AB, GV, and MM designed and implemented the field experiment. AA performed the microbiome profiling and wrote the first draft of the manuscript. AB and AA worked in the portions of this work. All authors edited the manuscript and approved the final draft.


Metformin is a hypoglycemic drug widely used in the treatment of type 2 diabetes. It has been proven to have analgesic and neuroprotective effects. Metformin can reverse pain in rodents, such as diabetic neuropathic pain, neuropathic pain caused by chemotherapy drugs, inflammatory pain and pain caused by surgical incision. In clinical use, however, metformin is associated with reduced plasma vitamin B12 levels, which can further neuropathy. In rodent diabetes models, metformin plays a neuroprotective and analgesic role by activating adenosine monophosphate‐activated protein kinase, clearing methylgloxal, reducing insulin resistance, and neuroinflammation. This paper also summarized the neurological adverse reactions of metformin in diabetic patients. In addition, whether metformin has sexual dimorphism needs further study. HighlightsMetformin has been shown to alleviate diabetic peripheral neuropathy.The neuroprotective and analgesic effects of metformin are related to the activation of AMPK, the clearance of MGO, and the reduction of insulin resistance and neuroinflamation.AMPK activation is critical for the analgesic effect of metformin.AMPK activation can attenuate inflammatory response and oxidative stress, regulate autophagy and regulate ion channels. DPN is mainly characterized by sensory neuropathy but can also be accompanied by autonomic neuropathy and impaired motor function.Here, we reviewed the basic and clinical studies and summarized research status and mechanism of metformin in treating DPN. Data strongly suggested that metformin may be a promising agent in alleviating DPN. However, more clinical studies are needed to evaluate its efficacy and safety.2Metformin acts through multiple pathways, including inhibiting mitochondrial respiration and gluconeogenesis, activating AMPK, increasing insulin sensitivity, antagonizing the effects of glucagon, and increasing fatty acid oxidation.2.1AMPK is a ubiquitous energy‐sensitive kinase consisting of two regulatory subunits (β and γ) and one catalytic subunit (α).2.1.1Metformin activates AMPK to inhibit cytokines and reduce systemic inflammation. Peripheral nerve inflammation is one of the mechanisms of DPN.Inhibition of oxidative stress through activating AMPK may be a beneficial effect of metformin. Oxidative stress is an important part in the development of diabetes complications.2.1.2Beclin‐1 and LC3B, the key proteins of the autophagic response, significantly increased in the sciatic nerve of mice with diabetes and were also affected by CYP4A/20‐HETE/AMPK.2.1.3Voltage‐gated sodium channel Nav1.7 is selectively expressed in sensory and autonomic neurons and associated with excitability of nociceptive neurons.In addition to expression level, the gated properties of NaV1.7 also affect the excitability of nociceptive neurons. Mitogen‐activated protein kinase (MAPK) family is a pivotal signaling system with at least four pathways. Among them, the MAPK/ERK (extracellular‐regulated kinase) pathway has been implicated in many cellular functions  and pathologies including pain.The transient receptor potential ankyrin 1 (TRPA1) channel is a pain sensor mainly expressed in primary sensory neurons,Metformin can also treat other types pain by activating AMPK. In mouse models of postoperative pain, activated AMPK negatively regulated mammalian target of rapamycin (mTOR) signaling pathway, preventing acute pain from transitioning to chronic pain.2.2MGO is a reactive carbonyl compound produced by a nonenzymatic pathway of glucose metabolism and it has been reported to be associated with PDPN.T2DM patients with metformin had lower plasma methylglyoxal levels, despite similar blood sugar levels.Metformin can clear MGO in vivo and in vitro. When MGO was co‐incubated with metformin, free MGO levels were reduced by more than 90%. When the incubation solution was injected into the hind paw of mice, no mechanical pain was observed. Systemic injection of metformin can effectively inhibit the pain induced by claw injection of MGO and significantly block STZ‐induced mechanical pain.2.3In recent years, the conclusion that hyperglycemia is the main cause of diabetic neuropathy has been challenged by the research results. Evidence suggested that peripheral neuropathy is also present in normoglycemic patients with metabolic syndrome and in a progenitor state prior to the establishment of T2DM.Evidence for IR affecting nociception is as follows: (1) Insulinemia itself or its consequences play a role in mechanistic nociceptive injury. Chronic fructose treatment increased plasma insulin level and caused hyperalgesia and abnormal tactile pain without a significant increase of blood glucose levels.Metformin, an insulin sensitizer, reversed tactile pain and downregulated insulin receptor β in fructose‐induced IR rats with neuropathic pain. Metformin reversed the upregulation of GFAP (astrocyte activation markers), ASIC3 (acid‐sensing ion channel 3), and anoctamin‐1(an ionic channel involved in the nociceptive processing) in DRG of fructose induced IR rats.3According to the current clinical experience and data of metformin, there are few serious safety concerns. Rare and mild side effects such as hypoglycemia, gastrointestinal side effects , impaired liver and kidney function, and heart failure can be effectively avoided by adjusting dosage and form.Since 1971, when malabsorption of vitamin B12 in diabetic patients with metformin was first reported,Many clinical studies have investigated the relationship between metformin‐induced vitamin B12 deficiency and PDN, but they have reached inconsistent conclusions. In some cross‐sectional studies, T2DM patients were divided into metformin and metformin‐free groups based on metformin medication history. Results showed a higher incidence of vitamin B12 deficiencyIn addition to these two grouping methods, researchers discussed the influence of metformin on DPN from other perspectives. We summarized these studies in Table Anemia is also a potential consequence of vitamin B12 deficiency, which occurs much later than neuropathy.4A large body of studies have clearly suggested that men and women respond to pain differently, as well as to pharmacological pain interventions.In some mouse models of pain, the pain relief effect of metformin is also sexually dimorphic.According to a study of data from a UK biobank, T2DM patients are more likely to report musculoskeletal pain in shoulder, neck, knee, or hip, particularly among women.5Metformin is a first‐line treatment for T2DM patients, and it is also used to treat polycystic ovary syndrome, hyperlipidemia, coronary artery disease, obesity, and a variety of kidney diseases such as acute kidney diseases, diabetic kidney disease, urolithiasis, renal cell carcinoma, end‐stage renal disease, and renal fibrosis.However, there are discrepancies between clinical data and preclinical data. Only one study showed a lower frequency of neuropathy in patients using metformin,Even though the association between diabetic neuropathy and metformin‐induced vitamin B12 deficiency is unclear, as a matter of best safety, we recommend regular screening for serum vitamin B12 levels and peripheral neuropathy in T2DM patients on long‐term metformin use. However, because of financial and medical constraints, regular testing of vitamin levels is a burden for many patients, and researchers have suggested that the Metformin Usage Index (MUI) be used as a risk assessment tool to assess vitamin B12 deficiency in T2DM patients. MUI is the product of the dose (mg) of metformin used and its duration (years) divided by 1000, and patients have a high risk of vitamin B12 deficiency when the MUI>5.There are still some limitations in our study. Contrary to the results of basic studies, metformin does not provide significant neuroprotection in patients with T2DM in clinical practice, which may be because of vitamin B12 deficiency. The clinical and basic researches have different concerns. Basic researches focused on metformin's neuroprotective effects and mechanisms, whereas clinical studies focused on vitamin B12 deficiency. The shorter duration of metformin intervention in the primary study may be responsible for the lack of reports of vitamin B12 deficiency and associated adverse events. Metformin combined with vitamin B12 may be beneficial for diabetic neuropathy. Vitamin B12 in combination with metformin in T2DM patients reduced the incidence of peripheral neuropathy compared with metformin alone,In conclusion, the therapeutic effect of metformin on DPN has been confirmed in many basic studies, and more and more studies have been conducted on its mechanism. However, clinical studies have focused on whether metformin‐induced vitamin B12 deficiency exacerbates neuropathy. This contradiction is worthy of attention and research. More clinical studies are needed in the future to observe the efficacy and safety of metformin in the treatment of diabetic neuropathy.J.W. conducted the study and wrote the text. S.J. gave research and writing guidance and approved the final version. Yanling Wei revised grammer and technical terms to make the artical more accurate. Meiyan Huang and Peng Wang were the main producer of figures and tables.No external funding.The authors declare that they have no competing interest.


Bilirubin is a potent endogenous antioxidant and immunomodulating substance, which is also implicated in both cell signalling and various metabolic pathways. Mild elevation of systemic bilirubin concentrations provides substantial protection against many diseases of civilization. Rare published reports have suggested that serum bilirubin might also be relevant to sports performance. The purpose of the current study was to evaluate serum bilirubin concentrations and the prevalence of Gilbert syndrome (GS) in elite athletes.UGT1A1 gene promoter responsible for GS manifestation in Caucasians (rs81753472) were evaluated in study subjects.The study was carried out in 536 consecutive healthy elite athletes and in 2594 individuals of the Czech post-MONICA study representing the general Czech population. Serum bilirubin concentrations, the prevalence of benign hyperbilirubinemia > 17 µmol/L , and a variant of the p < 0.001), both in men  and women . Furthermore, the prevalence of GS was also significantly higher in elite athletes  together with the tendency to higher frequencies of the genotypes (TA)7/7 and (TA)6/7UGT1A1.Compared to the general Czech population, significantly higher serum bilirubin concentrations were found in elite athletes (9.6 vs. 11.6 µmol/L, Elite athletes have significantly higher concentrations of serum bilirubin, the most potent endogenous antioxidant substance known. Simultaneously, the prevalence of GS syndrome is also much higher in elite athletes, suggesting that a mild elevation of serum bilirubin might predispose to better sports performance.The online version contains supplementary material available at 10.1186/s40798-022-00463-6. Elite athletes have significantly higher serum concentrations of serum bilirubin.The prevalence of GS syndrome is much higher in elite athletes.Serum bilirubin concentrations correlate with concentrations of uric acid and albumin, the other endogenous antioxidants.The beneficial effects of regular physical exercise on overall health status are well known and appreciated. However, vigorous and exhaustive training sessions, particularly on a long-term basis, are accompanied by increased oxygen consumption, leading to an overproduction of reactive oxygen and nitrogen species (RONS). In a feedback mechanism, this process is counteracted by improving the antioxidant defence system of the human body to mitigate the potentially harmful effects of overproduced RONS UGT1A1 gene encoding for bilirubin UDP-glucuronosyl transferase, responsible for its hepatic elimination out of the body UGT1A1 gene promoter region. Homozygosity for this variant , defines genotypic GS. However, due to its low penetrance, phenotypic manifestation occurs only in about 50% of carriers In the general population, serum bilirubin concentrations between 5 and 17 µmol/L are generally considered the physiological range. Epidemiologically, they have a bimodal, non-normal distribution, which is due to the fact that from about 2 to 12% of healthy people have Gilbert syndrome (GS), also known as benign hyperbilirubinemia Due to convincing experimental and clinical data that demonstrate the beneficial biological activities of bilirubin reported in the last few decades, and also due to lack of valid epidemiological data on markers of bilirubin metabolism, we hypothesized whether bilirubin might be a competitive advantage in elite sport. Therefore, the aim of our study was to determine serum bilirubin concentrations in elite athletes, to also determine the prevalence of GS, as well as the frequency of the UGT1A1*28 allele among them, compared to the general Czech population. Furthermore, our objective was also to determine the total antioxidant status in a subset of elite athletes and to correlate it with their serum bilirubin concentrations.A total of 536 consecutive elite athletes Table , and allA total of 2594 people from the general population of the Czech Republic were used to compare the bilirubin concentration data obtained from the elite athlete study population. This general population subset was derived from the cross-sectional Czech post-MONICA study, conducted between 2015 and 2018, which consisted of 2594 randomly selected from the Czech general population . The protocol of the Czech post-MONICA study was approved by the Ethics Committee of the Institute for Clinical and Experimental Medicine and Thomayer Hospital, Prague, Czech Republic (No. G 14-08-04). All participants provided their informed consent.Before recruitment, all athletes received detailed information about the study objectives, which were also included in the informed consent form. Research questions were developed due to frequent requests by athletes and their supporting teams to look for new markers predisposing persons for high sports performance. The participation of individuals in the general population was governed by the detailed protocols of the Czech post-MONICA study. [28]In elite athletes, a venous blood sample was collected in the morning, while the athletes were fasting and analysed in the laboratory within 1 h of collection for standard biochemical  and hematological (complete blood count) parameters. An aliquot of serum was immediately stored at − 80 °C for later antioxidant analyses .The determinations of serum biochemical and hematological parameters were performed on automatic analysers .γ-glutamyl transferase (GGT) > 0.84 μkat/L.For the determination of the prevalence of phenotypic GS, based on the upper limits of normal in our laboratories, the following values of liver function enzymes were considered abnormal: alanine aminotransferase (ALT) > 0.78 μkat/L and n = 183) using TAS and GLUT RED spectrophotometric kits, respectively, both according to the manufacturer’s instructions . These subjects were those consecutively examined at the Sports Research Institute of the Czech Armed Forces between 2019 and 2020.Total antioxidant status (TAS) and glutathione reductase activity (GR) were determined in a subset of the athlete group . Again, these subjects were those consecutively examined at the Sports Research Institute of the Czech Armed Forces between 2019 and 2020. Similarly, a subgroup randomly selected from the general population  was used for comparison 3 blood samples using a slightly modified method by Miller et al. [29]DNA analysis of (TA)UGT1A1 gene promoter variants were analysed by multicoloured capillary electrophoresis as previously described, with some slight modification  was determined by fragment analysis performed by SEQme .The T test or the Mann–Whitney rank sum test was used to compare laboratory parameters. The frequency of the alleles was evaluated using the Chi-square test. ANOVA on ranks with Dunn's post hoc analysis was used for all pairwise comparisons in groups of different genotypes of the UGT1A1 gene promoter. Linear regression analyses were used to compare the possible relationship between serum bilirubin concentrations and age, while logistic regression analyses were used to assess the predictive role of serum bilirubin concentrations in elite athletes. All analyses were performed with the alpha set to 0.05. Statistics were calculated using SigmaPlot v. 14.5 .Data are expressed as the mean ± SD, or as the median and IQ range when the data were non-normally distributed. The p < 0.001), with this difference observed in both men  and women  (Table ) and female athletes  , as well as for men and women, in whom serum bilirubin concentrations were not at all affected by age.No differences in serum bilirubin concentrations were found in athletes belonging to sports disciplines involving endurance/strength endurance or strength/speed endurance (data not shown).7/7 and (TA)6/7 in both male and female athletes did not differ from the general population on Table . Serum bon Table . As expeon Table .Table 4Ap = 0.058). A strong positive association of serum bilirubin concentrations was observed for uric acid and albumin concentrations . The median serum TAS was 1.33 ± 0.15 mmol/L, while the median serum GR activity was 60 ± 7.7 U/L. A significant positive correlation was observed between serum bilirubin and serum TAS  ; however, the correlation between serum bilirubin and GR activity was not present.Serum TAS and GR activity were analysed in a subset of the athlete group n = 83. The mIn our study, elite athletes were found to have significantly higher serum concentrations of serum bilirubin, the most potent endogenous antioxidant substance known It seems that regular physical exercise is associated with an increase in serum bilirubin concentrations, most likely as a feedback mechanism to regulate the increased oxidative stress that accompanies training processes. Our data are consistent with most published studies. In fact, serum bilirubin concentrations also increased significantly in response to regular soccer training On the other hand, not all published reports agree with any positive association of serum bilirubin and training. For example, no such effect was detected in a small study on soccer players and sedentary controls. [37]. Another factor that possibly contributes to higher systemic bilirubin concentrations in elite athletes is their much lower adiposity due to regular training, as also evidenced by much lower BMI values in athletes studied Table . In factSmoking is an important factor that decreases serum bilirubin concentrations due to increased oxidative stress [27]Another important factor that could affect serum bilirubin concentrations is age, which differed significantly between athletes and the general population Table . In factIn correspondence with significantly elevated serum bilirubin concentrations, the prevalence of phenotypic GS among our elite athletes reached 22%, which is even more than has been described in the few reports published to date. In fact, a prevalence of GS of 9% was observed in a recent Australian study nUGT1A1 gene promoter variants, responsible for the manifestation of GS in the Caucasian population. The frequencies of the (TA)7/7 and (TA)6/7 alleles did not differ between athletes and the general population nUGT1A1 predisposition) seems to be even more important.For the first time, our study on elite athletes demonstrates the frequencies of (TA)on Table . Howeveron Table . There aIt is well known that strenuous exercise dramatically increases oxygen consumption in working muscles, leading to a marked increase in RONS formation [52]Significantly higher serum bilirubin concentrations in elite athletes are directly related to serum TAS. Furthermore, positive correlations of serum bilirubin concentrations with serum concentrations of uric acid and albumin, two other potent antioxidants, were also found. These data suggest that upregulation of the antioxidant defence system in elite athletes is complex, and that bilirubin, indeed, may play both protective and beneficiary roles during and after exercise.It is important to emphasize that each micromolar change in serum bilirubin concentration is associated with a marked beneficiary modification of metabolic risk factors Our study has several limitations. First, our control population differed substantially in many variables, including: age; anthropometric parameters; presence of concomitant diseases, either latent or apparent, which must have been present in our control subjects and which certainly may affect serum bilirubin concentrations; different lifestyle . Nevertheless, as discussed above, we have tried to eliminate possible confounding effects of these variables by additional sub-analyses. Other limitations include the fact that some analyses  could be performed only in a subset of the elite athlete group. Furthermore, it would be very interesting to correlate the parameters of bilirubin metabolism with the success rate of individual athletes, which, however, was beyond the scope of the current study.Our point in view on mild increases of serum bilirubin concentrations has changed dramatically over the last few decades. Although in the past and sometimes even to this day, individuals with GS were considered predisposed to chronic fatigue and various gastrointestinal problems. They were also advised against physical exercise or any appropriate improvements involving a training routine Additional file1:Table S1. Primers used in genotyping analyses.