Ne), has shaped the contents of uORFs in eukaryotes. Besides, gene expression level is important in influencing uORF occurrences across genes in a species. Our analyses suggest that most uORFs might play regulatory roles rather than encode functional peptides. We also show that the Kozak sequence context of uORFs has evolved across eukaryotic clades, and that noncanonical uORFs tend to have weaker suppressive effects than canonical uORFs in translation regulation. This study provides insights into the driving forces underlying uORF evolution in eukaryotes.Upstream open reading frames (uORFs) play widespread regulatory functions in modulating mRNA translation in eukaryotes, but the principles underlying the genomic distribution and evolution of uORFs remain poorly understood. Here, we analyze ~17 million putative canonical uORFs in 478 eukaryotic species that span most of the extant taxa of eukaryotes. We demonstrate how positive and purifying selection, coupled with differences in effective population size ( Upstream open reading frames (uORFs) have widespread regulatory functions in eukaryotes, their genomic distribution and evolution is understudied. Here, the authors characterise ~17 million putative uORFs across 478 eukaryotic species, showing how evolution has shaped uORF contents and distribution. For an AUG triplet in the 5′ UTR (defined as “uAUG” hereafter), it can function as the start codon of a uORF that has a stop codon either preceding the start codon of the downstream CDS  or residing in the body of the downstream CDS 18. Less frequently, an uAUG can function as the start codon of an ORF whose stop codon overlaps with the stop codon of the downstream CDS 21. The advent of ribosome profiling26, a method that determines the ribosome occupancy on mRNAs at the codon level, has enabled the genome-wide characterization of uORFs and NTEs that showed evidence of translation in various species with high sensitivity and accuracy36. Besides the canonical uORFs (beginning with an AUG start codon and ending with a UAA/UAG/UGA stop codon), the modified ribosome profiling methods37, which detect initiating ribosomes in cells treated with harringtonine34 or lactimidomycin40, have provided further evidence showing that many noncanonical uORFs (beginning with a non-AUG codon and ending with a UAA/UAG/UGA stop codon) might be prevalent and functionally important. Collectively, recent studies have demonstrated that uORFs are prevalently translated in eukaryotic cells and that uORF-mediated regulation plays important roles in tuning the translational program during development45 or stress responses55.Upstream open reading frames (uORFs) are short open reading frames (ORFs) that have start codons located in the 5′ untranslated regions (UTRs) of eukaryotic mRNAs. uORFs can attenuate the translational initiation of downstream coding sequences (CDSs) by sequestering or competing for ribosomes60, and mutations that generate polymorphic uORFs are also usually deleterious and selected against in humans66 and flies32. Nevertheless, our recent study indicated that many uAUGs recently fixed in Drosophila melanogaster were driven by positive Darwinian selection32, which suggests that some uORFs and NTEs might be adaptive. Despite these exciting progress, the principles underlying the genomic distribution and evolution of uORFs and NTEs are poorly understood. For example, the following questions remained unanswered: (1) What is the role of natural selection in shaping the genome-wide contents of uORFs and NTEs in eukaryotes at the micro- and macroevolutionary scales? (2) Can we detect signatures of positive selection on uORFs and NTEs in clades other than Drosophila? (3) Are the sequence characteristics that influence the efficacy of uORF-mediated translational repression conserved between different eukaryotic species? Answers to these questions will not only help elucidate the role of translational regulation in adaptation, but also advance our understanding of the mechanisms underlying protein homeostasis in health and disease.It is well accepted that canonical uORFs are generally deleterious and are depleted in the 5′ UTRs of eukaryotic genomesNe). We also compare the conservation patterns of start codons versus coding regions of the canonical uORFs in different clades, disentangled the relationship between the Kozak sequence context and the translational efficiency of uORFs, and explore the evolution of Kozak contextual characteristics across eukaryotes. Our analyses present a broad overview of the interspecies variability of uAUGs in eukaryotes and provide insights into the general principles underlying the distribution and sequence evolution of uORFs and NTEs in eukaryotes.Here, we systematically characterize 16,907,129 uAUGs in 478 eukaryotic species and explore various factors and forces that determine the genome-wide distributions of uORFs and NTEs across genes and species. Our results suggest that differences in uORF occurrences across genes are mainly influenced by gene expression levels, while the interspecific variability of uORFs is shaped by the effective population size (67).We developed a bioinformatic pipeline and characterized uAUGs in the genomes of 478 eukaryotic species, including 242 fungi, 20 protists, and 216 multicellular eukaryotes that comprise plants and animals. As most species surveyed in this study currently have no ribosome profiling data, and it is very challenging to predict the noncanonical uORFs in silico reliably, we only focused on the putative canonical uORFs that start with the AUG start codon. In what follows, the uORFs analyzed in this study are restricted to the putative canonical uORFs unless explicitly stated otherwise  to 32,847 (Fibularhizoctonia sp.). A total of 3,469,095 uAUGs were identified in these fungal genomes, with the number ranging from 1233  to 94,695 (Verticillium longisporum)  to 38,544 (Emiliania huxleyi), and the number of uAUGs ranging from 1903  to 99,859 (Cystoisospora suis), which resulted in a total of 391,565 uAUGs in these protist genomes  41 plants, including mosses, eudicotyledons, and monocotyledons; (2) 38 invertebrates, including sponges, ctenophores, flatworms, cephalopods, mites, centipedes, crustaceans, springtails, insects, and tunicates; and (3) 137 vertebrates, including hagfishes, fishes, coelacanths, toads, lizards, turtles, crocodiles, birds, and mammals , marsupials (n = 3), an armadillo (n = 1), laurasiatherians (n = 17), a rabbit (n = 1), rodents (n = 21), and primates (n = 24), constituted the largest clade (n = 68 species). Nematodes were excluded from the analyses because trans-splicing alters the 5′ UTR sequences of many mRNAs in their transcriptomes76.The 216 multicellular plants and animals, whose last common ancestor was dated to 1.5 billion years agoBombus terrestris) to 107,545 (Triticum aestivum), and 3388 (Schistosoma mansoni) to 68,741 (T. aestivum) of these genes exhibited annotated 5′ UTRs for at least one transcript  to 798,433 (Theobroma cacao). Altogether, we identified a total of 13,046,469 uAUGs in the 216 multicellular plants and animals, although the number varied greatly across species.The number of annotated protein-coding genes in the 216 multicellular plants and animals ranged from 10,581 (The vast majority (>97%) of the uAUGs identified in the 478 eukaryotic species were start codons of putative canonical uORFs. Specifically, in a species, the percentage (mean ± s.e.) of nORFs, oORFs, and NTEs was 83.45 ± 0.41%, 14.24 ± 0.34%, and 2.31 ± 0.15%, respectively. The detailed information for the uORFs (nORFs and oORFs) and NTEs is presented in Supplementary Data 77. To control for the compounding factors, in each species, we compared the observed number of uAUGs (O) versus the expected number (E) that was obtained with the assumption of randomness by randomly shuffling the 5′ UTR sequences. We maintained the same dinucleotide frequencies in each sequence during shuffling for two reasons. First, the stacking energy of a new base pair is influenced by the neighboring base pairs in an RNA molecule79. Second, the biased mutations in certain dinucleotide contexts, such as from CpG to TpG mutations in mammals, might also affect the occurrences of uAUGs. The O/E ratio enabled the efficient measurement of selective pressure on uAUG depletion in a given species. As expected59, the O/E ratio of uAUGs was significantly lower than 1 in nearly all the examined species  than in the remaining 5′ UTR regions  recessivects Fig. . In birdmes Fig. . Thus, tOverall, these results suggest that uAUGs were selected against in 5′ UTRs, and the NTEs, which only accounted for a small fraction (~2.31% on average) of the uAUGs, were also shaped by strong purifying selection during evolution. Since uORFs (nORFs and oORFs) and NTEs might have different mechanisms in regulating gene expression and function, in what follows, we only focused on the putative canonical uORFs.84. Similarly, our analysis of previously published mRNA and protein abundance data of fly, human, mouse, mustard plant, and yeast revealed uORFs were infrequently detected in housekeeping genes, and there were significant anticorrelations between the gene expression level and the number of uORFs  for 14 animals for which the Ne value was estimated in previous studies  of CDSs between closely related species as an indirect measure of the average Ne for a clade based on the following rationale: if a clade includes species with a large Ne, deleterious nonsynonymous mutations in CDSs will be more efficiently removed by natural selection, resulting in a smaller ω value for that clade. Therefore, if the purifying selection is the major force acting on uORF prevalence, a positive correlation between the O/E of uORFs and the ω of CDSs would be expected across different species. We aligned orthologous CDS sequences at the genomic scale for 37 pairs of closely related species, and calculated the genome-wide ω value for each pair of species  and between the 5′ UTR length and the ω (P = 0.021). Together, our analyses suggest that purifying selection is the dominant force governing the contents of uORFs in eukaryotes and that the degree of uORF depletion in a species is mainly determined by the Ne of that species.Because the Drosophila, our previous results indicated that a considerable fraction of the uORFs recently fixed in D. melanogaster were driven by positive Darwinian selection32. Our results are consistent with the notion that the very large Ne of D. melanogaster increases the efficacy of both positive selection and purifying selection89. Nevertheless, whether positive selection drives the fixation of uORFs in a eukaryote with a small Ne, such as humans, remains unclear. To address this research gap, we analyzed the new uORFs that were newly fixed in the lineages leading to extant humans after divergence from Pongo abelii, Gorilla gorilla, or Pan troglodytes using the asymptotic McDonald-Kreitman test (asymptoticMK)93. We detected weak signals of positive selection on the newly fixed uORFs in all three branches, and the value of αasym, which represents the fraction of newly formed uORFs driven to fixation by positive selection, was 0.24 , 0.20 , and 0.19  in the three branches, respectively  from ACG to ATG, and (2) from CGTG to CATG , 0.45 , and 0.44  in the three branches, respectively), while the αasym for the remaining uORFs was close to 0  in vertebrates, insects, and yeasts. Among the 78,003 uoAUGs identified in the human reference genome, 98.7% have conserved uoAUGs in other vertebrates  more conserved than the other random triplets .Compared with the other triplets, uoAUGs showed significantly higher BLS values . 48.8% of these human uORFs putatively presented conserved peptide sequences only in primates; 36.6% of them putatively exhibited conserved peptide sequences in mammals other than primates, and 1.82% of them putatively exhibited conserved peptide sequences in fishes. Of note, the BLS values of the uORF coding sequences were significantly lower than those of the uoAUGs . Together, these results suggest that the coding regions of uORFs tend to be less conserved than start codons of uORFs.How many uORFs can encode functional peptides remains unclearies Fig. . A similies Fig. . Of noteω for coding regions of uORFs between humans and macaques. To reduce the noise in estimating ω values, we ranked the uORFs based on the Kozak scores of their start codons and equally grouped the uORFs into 1000 bins. For each bin, we concatenated the alignments of the uORF coding sequences and calculated the ω value. In contrast to CDSs, which present ω values markedly lower than 1, the ω value of the uORF coding region was roughly equal to 1 between humans and macaques  and flies (Drosophila Genetic Reference Panel99) based on the derived allele frequencies (DAF) and calculated the ratio of nonsynonymous SNPs to synonymous SNPs (pN/pS) in each bin. In parallel, we performed the same analyses on SNPs in CDSs. In CDSs of both humans and flies, the pN/pS ratios were substantially lower than the values expected under randomness, and the pN/pS ratio was significantly negatively correlated with the DAF bins in both species . As a negative control, we also calculated the PhyloCSF scores for 20,000 randomly selected ORFs in 3′ UTRs , as these dORFs have little chance of translation. Among the 36,655 uORFs that are ≥10 codons and evidenced of translation in humans, only 361 (0.985%) had positive PhyloCSF scores  translated uORFs and 0.39% (78 out of 20000 dORFs) had positive PhyloCSF scores , 57 (0.24%) had peptides detected in at least one sample  data from 38 samples of different developmental stages or tissues of 107. As the nucleotide compositions differ between eukaryotes110, the preferential Kozak sequence context around cAUGs also differs across species112. Nevertheless, whether Kozak contextual characteristics around uoAUGs evolve remains unclear. To address this research gap, in each of the 478 species, we reconstructed a position weight matrix of the Kozak sequence context (PWMK) for all the CDSs (Supplementary Data 32.The Kozak sequence context (−6 to +4 nucleotides) around the uoAUG plays a prominent role in influencing the translational initiation of that uORF40. We detected the translation of 26,344, 16,245, and 15,195 canonical uORFs that were supported by TIS data in at least one sample for human, mouse, and fly, respectively , we analyzed translation initiation site (TIS) profiling data from three species 59. Also, the Kozak scores of the uORFs were significantly lower than those of the CDSs in each species  as neutral controls. The Kozak scores of uoAUGs were significantly higher than those of dAUGs in most  vertebrates,  plants, and  fungi; however, an opposite trend was observed in invertebrates, and no obvious trend was observed in protists  between two species (“Methods”). Interestingly, for both uORFs and CDSs, the distance between two species from a clade tend to be significantly shorter than that between one species in that clade and another species outside of that clade Fig. . A simil34, and many of them might have diverse functions20. Moreover, hundreds of noncanonical uORFs are conserved between different yeast species, suggesting they might be functionally important114. In the above analyses, we mainly focused on the canonical uORFs because (1) the majority of the species analyzed in this study had no ribosome profiling data available, and (2) it is still challenging to identify noncanonical uORFs without experimental data.Recent studies have demonstrated that noncanonical uORFs are very abundant115, and examined whether variations in uORF start codons influence the translation efficiency of the main CDSs among different samples . We performed linear regressions to assess the regulatory impact of uORF alteration on the translation of down-stream CDSs, with a positive slope value in the regression meaning that the presence of a uORF in certain individuals is associated with a decrease in the translation efficiency of the downstream CDS in those individuals, and vice versa (“Methods”). A general trend was the slope values were overall positive for the canonical uORFs, while the slope values for the noncanonical uORFs fluctuated around 0 . Altogether, these results reinforced the thesis that the noncanonical uORFs overall have weaker repressive effects on CDS translation than the canonical uORFs.To experimentally verify the influence of both types of uORFs on CDS translation, we sampled 80 human uORFs and performed luciferase reporter assays in HEK293FT cells  of uORFs might produce peptides.We found that start codons of canonical uORFs, particularly the translated ones, tend to be maintained by functional constraints during evolution. These results might also be pertinent to the translational buffering mechanism, which indicates that protein expression levels are more conserved between species than mRNAs17 identified in humans are overall slightly (~1.2 times) more conserved than the other random triplets across vertebrates. Moreover, our re-analyses of the previously published gene expression data revealed that the noncanonical uORFs tend to have weaker repressive effects on CDS translation than the canonical uORFs, and this pattern was further confirmed by our luciferase reporter assays. Of note, these results do not necessarily suggest that noncanonical uORFs are functionally unimportant, as it has been well established that many noncanonical uORFs might have diverse functions in various biological processes20, such as stress responses126 or tumor initiation127. Overall, our current understanding of the prevalence and function of the noncanonical uORFs are still very limited. Further studies are required to reliably identify the noncanonical uORFs and elucidate their regulatory functions and evolutionary principles.We found the start codons of the noncanonical uORFs McGillivray et al.128, and many protists use alternative nuclear genetic codes involving stop-codon reassignments69 and obligatory frameshifting at internal stop codons74. In protists with no dedicated stop codons71, such as Condylostoma magnum71, Parduczia sp.71, Blastocrithidia72, and Amoebophrya sp. ex Karlodinium veneficum73, translation from any possible uAUG is supposed to terminate near the end of a transcript and overlaps with the main CDS, which results in a different protein. Thus, the occurrence of uORFs in protists with alternative genetic decoding schemes might differ considerably from that of most other eukaryotes. In this study, we only focused on 20 protists that use the standard genetic code. Although the O/E ratio of uAUGs was significantly <1 in all the fungi, multicellular plants and animals we examined, such a pattern was observed in only 15 of the 20 protists. The O/E ratio of uAUGs was close to or higher than 1 in the remaining five protists, including Cystoisospora suis , Toxoplasma gondii , Nannochloropsis gaditana , and two malaria vectors Plasmodium yoelii , and Plasmodium vivax . However, these five protists tended to have significantly longer 5′ UTRs than the other 15 protists , Ensembl Plants (release 43), Ensembl Protists (release 46), and Ensembl Fungi (release 46). Transcript ends of yeast mRNAs were obtained from a previous study133. Putative uORFs and NTEs that start with AUG codons and end with stop codons (UAA/UAG/UGA) were identified from the annotated 5′ UTRs of protein-coding genes. uORFs and NTEs with start codons located in CDSs of other transcripts were excluded from the analysis. Only the species for which 5′ UTR annotation information was available for more than 25% of the protein-coding genes were considered in the analyses. Among all the 479 species meet this criteria, Ichthyophthirius multifiliis was excluded since UAA and UAG are reassigned to encode glutamine in this species134, which would interfere with the uORF and NTE prediction.We downloaded the gene models and cDNA sequences of all eukaryotes that are annotated in the Ensembl Genome Browser (release 96)nobs. We subsequently shuffled the 5′ UTRs with 1000 replicates while maintaining the same dinucleotide frequency using uShuffle135. We calculated the median and 2.5% and 97.5% quantiles of the number of AUGs in the shuffled 5′ UTRs and denoted these numbers as nexp, n0.025, and n0.975, respectively. We then calculated the O/E ratios for the species as nobs/nexp with a 95% confidence interval of . The O/E ratio of other triplets in 5′ UTRs or 3′ UTRs was calculated using the same procedure.A permutation analysis was performed to determine the ratio of the observed to the expected number of uAUGs (O/E ratio) for each species. For genes that exhibited more than one transcript, only the longest transcript was used in the analysis. Unusually long 5′ UTRs in each species (longer than the mean + 3s.d. of the lengths of the 5′ UTRs in that species) were excluded because these are likely annotation artifacts. We denoted the number of AUG triplets in the 5′ UTRs of a species as ω of protein-coding genes between two closely-related species in a clade, we performed a reciprocal best BLAST136 of protein sequences between the two species (E < 10−10). We identified orthologs of protein-coding genes at the genomic scale for 37 pairs of closely related species, which spanned 56 species. For each pair of orthologs between two species, we aligned their protein sequences with MUSCLE (3.8.31)137 using the default parameters and generated codon alignments with tranalign from the EMBOSS package138. We then calculated ω using yn00 from PAML139 with the codon alignments as input. The median ω of all pairs of orthologs between two species was used as the genome-wide ω of protein-coding genes. For species that were compared with multiple other species, the median ω values obtained from different comparisons were averaged.To estimate the genome-wide average ω values were estimated, we obtained the phylogenetic tree from the Open Tree of Life140. We used BUSCO141 to identify single-copy protein orthologs that were conserved in all 56 species, concatenated the protein sequences of the single-copy orthologs in each species, and performed multiple alignments using MUSCLE with the default parameters. Poorly aligned regions in the resulting alignment were removed using trimAl142 with the “-automated1” method. The branch length of the tree was calculated using codeml from PAML with the JTT substitution model . Phylogenetic independent contrasts were performed using the “pic” function in the ape package143. The O/E ratio, ω, and median 5′ UTR length of each species were log-transformed before the contrasts.For the 56 metazoan species for which Pan troglodytes, Gorilla gorilla, Pongo abelii, and Macaca mulatta) from the UCSC Genome Browser144. AUG triplets that were newly fixed in the human or hominid lineages were inferred using the parsimonious method with M. mulatta as the outgroup. We obtained all human SNPs and their ancestral allele information from the phase 3 data of the 1000 Genomes Project98. Both fixed and polymorphic AUG differences located in repetitive regions were excluded from the downstream analysis. Newly fixed or polymorphic AUGs in 5′ UTRs that form NTEs were removed. AsymptoticMK93 tests were performed to detect the signal of positive selection. The data for asymptoticMK tests in flies was obtained from our previous study32. To determine the effect of gene expression on positive selection, fixed and segregating mutations were divided into two halves based on the median expression level of genes with fixed new AUGs in 5′ UTR. The average protein abundances across different tissues145 were used from humans, and the average Reads per Kilobase per Million mapped reads (RPKM) values in Ribo-Seq of 12 different developmental stages or tissues were utilized for flies32.To identify fixed differences in AUG triplets in 5′ UTRs and introns, we downloaded whole-genome pairwise alignments between humans (hg19 freeze) and other primates  of each uORF or CDS start codon and then normalized the initiating RPF count with the mean coverage of the RNA-Seq data in the same region. We only used start codons with at least 2 initiating RPFs and at least 4 mRNA reads for the downstream analysis of human and mouse cell lines, and those with at least 5 initiating RPF reads and at least 10 mRNA reads were used for the analysis of S2 cells.The genome-wide coverage of initiating ribosome profiling and matched mRNA-Seq data from human and mouse cell lines were downloaded from the GWIPs-viz database. The RNA-Seq data from S2 cells and corresponding Ribo-Seq data after harringtonine treatment were obtained from our previous studyA. thaliana, and yeast were downloaded from the Gene Ontology Resource (2019-06-09 release). Because not all genes under a GO term were provided in the GO annotation files, we parsed the gene annotation files to obtain the complete list of genes under each term using topGO150. For each species, all the GO terms belonging to Molecular Function, Biological Process, and Cellular Component were combined in the enrichment analysis. The GO terms enriched in uORF-containing genes or uORF-free genes were determined using Fisher’s exact tests. Multiple testing correction was performed with the Benjamini–Hochberg method151, and significant terms were determined at a false discovery rate of 0.1 for each species. Nonredundant representative terms that were significantly enriched in at least five species were chosen for visualization.Gene ontology (GO) annotations for human, mouse, rat, zebrafish, fly, D. melanogaster (dm6), the 7-way alignments of yeast species based on S. cerevisiae (sacCer3), and the corresponding phylogenetic trees from UCSC Genome Browser and used the Galaxy platform152 to parse the multiple sequence alignments of 5′ UTRs in vertebrates or insects. For the start codon of each human uORF (uoAUG), we calculated the sum of the branch lengths of the subtree composed of the species in which the uAUG was present in the orthologous sites (B0) and then calculated the BLS value by dividing B0 by the total branch lengths for the phylogenetic tree of the 100 species. Similarly, the BLS was calculated for the start codon of each uORF in D. melanogaster across 27 insect species.We downloaded the 100-way vertebrate genome alignments based on human (hg19), 27-way insect alignments based on 153. uoAUGs located in repeat regions (downloaded from UCSC Genome Browser) were excluded. For oORFs, only the portion that was not overlapping with CDSs were considered in the analysis. To avoid spurious matching, we only considered human uORF peptides containing at least m amino acids . We identified uORFs with conserved peptides in other species using the following criteria: (1) the first codon of the matched sequence was AUG; (2) no stop codons or frameshifts were present in the first 80% of the matched sequence; and (3) between humans and the studied species, the identity of the uORF peptide should be greater than the 2.5% quantile of the genome-wide identity of the main protein sequences. For each uORF, we also calculated the BLSs for peptide sequences based on the presence of conserved peptides in other vertebrates as described above. A similar analysis was performed for the fly and yeast uORFs.For each predicted uORF peptide in humans, we searched its peptide against the orthologous sequences of other species in the 5′ UTR alignments using Exonerate (V2.2)D. melanogaster and D. simulans. Due to the short length of uORFs, we ranked the uORFs based on their Kozak score and divided them into 1000 bins with equal numbers of uORFs. For the uORFs in each bin, we concatenated their alignments and calculated ω values using yn00 as described above.Based on these alignments of uORF peptides, we generated alignments of uORF coding regions between humans and macaques and between 154. The same analysis was performed for uORFs of D. melanogaster using the freeze 2 data of the Drosophila Genetic Reference Panel99.To study the population variation within uORFs, we merged the genomic intervals of human uORFs and excluded the regions overlapping with CDSs and repeats. We then extracted the SNPs overlapping with uORF regions from the phase 3 data of the 1000 Genomes Project. SNPs in the CDS-overlapping portion of oORFs were excluded. We annotated the effect of SNPs on human uORFs (nonsynonymous or synonymous) using custom scripts and excluded ambiguous SNPs that were annotated as both nonsynonymous and synonymous in different uORFs. For comparison, we also extracted the SNPs in CDS regions and determined their effect on CDSs using SnpEff100 using the parameter set “100vertebrates”. As a negative control, we annotated all the possible ORFs in 3′ UTRs (dORFs) with at least ten codons using getorf from EMBOSS suit138. dORFs overlapping with any CDS or uORF were excluded. We randomly selected 20,000 unique dORFs from the remaining dORFs and calculated PhyloCSF scores with the same procedure as for uORFs. The same analysis was performed for uORFs and dORFs in flies, except that the parameter set “23flies” was used when calculating PhyloCSF scores.The alignments of human uORFs with at least 10 codons were extracted from the 100-way vertebrate genome alignment based on humans as described above. PhyloCSF for each uORF was calculated with PhyloCSF softwareD. melanogaster were obtained from ProteomeCentral155. Information on these datasets is listed in Supplementary Data D. melanogaster and all the peptides encoded by regions between two consecutive in-frame stop codons in cDNA sequences with at least 7 amino acids. To recover as many uORF-encoded peptides as possible, each sample was searched with three different search engines  at a 1% false discovery rate. Enzyme specificity was set to trypsin, and at most two missing cleavages were allowed. Cysteine carbamidomethylation was included as the fixed modification and methine oxidation as the variable modification. Both the precursor and fragment tolerance were set to 20 ppm for higher-energy collisional dissociation datasets. Fragment tolerance was set to 0.5 Da for collision-induced dissociation (CID) datasets. Peptides with <7 amino acids were excluded during searching. Peptides that match the built-in contaminants in MaxQuant, yeast proteins and the annotated fly proteome were removed with PeptideMatchCMD v1.0159 allowing mismatches of leucine and isoleucine. The remaining peptides were mapped to peptides encoded by all the putative canonical uORFs. uORFs with uniquely mapped peptides were kept as MS-supported uORFs.MS datasets for multiple tissues, developmental stages, and cell lines of 32. The Euclidian distance between two PWMs of uORF or CDS Kozak sequences was calculated using TFBSTools160.For each species, we retrieved the six nucleotides upstream of the CDS start codons and one nucleotide downstream of these codons and built a position probability matrix (PWM) as the Kozak sequence context. We then determined the Kozak score for the start codon of a uORF or CDS, as well as for each AUG in 3′ UTRs by calculating the log-odds ratio of their flanking sequences using the above-derived PWM115. High-quality genotyping data from 60 LCLs were obtained from the 1000 Genomes project98. After pre-processing, the RNA-Seq reads and RPFs were mapped to the human reference genome with STAR161. Reads mapped to the CDS region of each protein-coding gene were tabulated with htseq-count162. CDS read counts were normalized across different cell lines with DESeq2163 separately for RNA-Seq and RPFs. The translation efficiency of a gene in a sample was calculated as the ratio of the normalized RPF read count over the normalized RNA-Seq read count. To control for false positives, only SNPs that disrupt the canonical and noncanonical uORFs annotated by McGillivray et al.17 were analyzed. SNPs with a minor allele frequency of <5% among the 60 LCLs were excluded. A SNP is classified as a canonical uORF variant if the wild-type start codon or mutant start codon is AUG and is classified as noncanonical otherwise. For each uORF variant, a linear regression was performed between the CDS translational efficiency and the number of non-uORF alleles  across different LCLs.The RNA-Seq and ribosome profiling data from lymphoblastoid cell lines (LCLs) were obtained in a previous studyThe effects of uORF variants were assayed with dual-luciferase reporter assays . HEK293FT cells were purchased from the Cell Bank of the Chinese Academy of Sciences. RNA was extracted using the TRIzol reagent , and cDNAs were synthesized using the PrimeScript First-strand cDNA Synthesis Kit . For each uORF variant, the wild-type (WT) 5′ UTR or mutated 5′ UTR were cloned from cDNAs by PCR. All the primers used for cloning 5′ UTR fragments were listed in Supplementary Data Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Reporting Summary


Anemia defined as a low blood hemoglobin concentration is public health importance. The adolescence age group is the most neglected in public health and nutrition research as priorities are usually given to pregnant women, lactating mothers, and their children less than 2 years. Current Ethiopian Food and Nutrition policy included adolescent girls in the most at-risk group for nutritional demands; however, only a few published studies have assessed a deficiency of anemia and associated factors to tackle the intergenerational cycle of malnutrition.  To assess the prevalence of anemia and associated factors among high school adolescent girls in Jimma town. p value ≤0.25 was considered as a candidate for multivariable logistic regression. Multivariable logistic regression was done to control for confounders and to identify factors independently associated with anemia. Level of statistical significance was declared at p < 0.05.  Data were collected from 528 secondary school adolescent girls by a school-based cross-sectional study design in Jimma town from 1/1/2019 to 1/2/2019, southwest Ethiopia. A multistage sampling technique was used to select the study participants. A portable battery-operated HemoCue Hb 301+ analyzer was used to measure the hemoglobin level, and then reading was classified as normal Hb ≥ 12 g\dl and anemic if the hemoglobin value <12 g/dl based on the WHO 2011 recommended cutoff points after adjustments to altitude was made. Bivariate analysis at  A total of 528 adolescent girls were included in the study yielding a response rate of 95.8%. The prevalence of anemia was found to be 26.7%, 95% CI . In multivariate logistic regression analysis, those living separately from their family ), low dietary diversity score ), menstrual bleeding more than 5 days ), and low economic status ) were positively associated factors with anemia and only having at least a secondary school in mother's educational status AOR = 0.43, 95% CI  was negatively associated with anemia in the study area.  Prevalence of anemia among school adolescent girls was moderate public health importance according to the World Health Organization prevalence estimation of anemia. The living condition of the adolescent girls, dietary diversity score, duration of menses, and low economic status were positive predictor variables, whereas mothers who are being secondary school and above was a protective factor for anemia. Therefore, iron-rich and diversified food consumption should be given attention. Adolescents are young people between the ages of 10 and 19 years . AdolescAnemia, defined as a low blood hemoglobin concentration, is a public health problem that affects LMICs and has significant adverse health consequences including morbidity and mortality as well as adverse impacts on social and economic development . Iron deWHO defines anemia as a condition in which hemoglobin (Hb) content of blood is lower than normal as a result of deficiency of one or more essential nutrients. Based on WHO 2011, if the hemoglobin level is ≥12 g/dl, it does not indicate anemia for males and females of age between 12 and 14 years and for nonpregnant women >15 years. Anemia is established if the level of hemoglobin is <12 g/dl for nonpregnant women >15 years and children 12–14 years old and 11–11.9 g/dl, 8–10.9 g/dl, and 8 mg/dl were consider as having mild, moderate, and severe anemia respectively . Based oThe WHO estimates the prevalence of anemia among adolescent girls in southwest Asian countries like Indonesia, Nepal, and Bhutan was 30%, 46%, and 58.6%, respectively . SimilarGlobally, the prevalence of anemia had shown dramatic increment among women of nonpregnant reproductive age groups from 464 million in 2000 to 578 million in 2016. A condition persists in LMICs which reported the overall prevalence of anemia was over 35%. So, there is still a long road ahead to achieve the SDG 2030 targets anemia in adolescent girls. In Ethiopia, eighteen percent (17.7%) nonpregnant women aged 15 to 49 are anemic, of which Somali regional state has the highest prevalence of anemia (34.8%) followed by the Gambella region where 26.7% and 19% of reproductive age nonpregnant women were anemic in Oromia regional state , 13.The associated factors of anemia among adolescent girls differ from study to study, like low dietary diversity score, living status of adolescents with either of the two parents, duration of menstruation, history of parasitic infestation, low socioeconomic status, household family size, inadequacy of dietary iron intake, drinking tea immediately after a meal, high consumption of whole wheat bread, and low consumption of vitamin C rich foods and molasses, parent's level of education, parasite infections, low BMI, being stunted, and underweight , 14, 15.The risk of anemia increases during adolescent years with the onset of menstruation and pregnancy. Iron loss from menstruation must be countered by further high iron intake for young women; the other is ever-increasing evidence that control anemia in pregnant women may be more easily achieved if satisfactory iron status can be ensured during adolescence , 16. MosA school-based cross-sectional study was conducted from 1/1/2019 to 1/2/2019 among adolescent girls aged 14 to 19 years. Jimma, the study area, is located 347 km away from Addis Ababa which is the capital city of Ethiopia. The town has 14 secondary schools both private and government. A total of 5694 adolescent girls were attending secondary school in the town. One teaching specialized hospital, one primary hospital, 5 health centers, and numerous private clinics are giving health care services of the population of the town.p) of anemia among adolescent girls in Babile district eastern, Ethiopia, 95% confidence interval (CI), margin of error (d) 5%, and design effect of 1.5. Secondly, factors associated with anemia among adolescent girls were considered to calculate the sample size from the previous literature, and finally, the largest sample size was used for this study which is 551.Adolescent girls who attended their education in Jimma town secondary schools, who were healthy, and lived in the study area for greater than six month, and nonpregnant adolescent girls during the study period were included in the study. The sample size was determined using single population proportion formula based on the following assumptions: estimated 32% prevalence  were randomly selected from 14 secondary schools found in Jimma town. Then, the total number of students was obtained from each school director office. The sample size was distributed among the selected schools proportionally based on the students' size in each school. Finally, the allocated sample size was selected from each school by using simple random sampling technique (computer generated random number) .A structured questionnaire, an anthropometric measurement for thinness and stunting, a standard Dietary Diversity Score (DDS) questionnaire from FAO 2010, knowledge related to anemia, and laboratory investigation for hemoglobin were used to collect the data. Sociodemographic and socioeconomic factors , ethnicity, religion, and wealth index), knowledge regarding anemia, health-related questionnaires , anthropometric measurement (to determine stunting and thinness), dietary pattern , and time and frequency of consumption of tea/coffee in the schools were addressed for adolescents.Data were collected face-to-face by trained four diploma nurses using a pretested and structured “Afaan Oromo and Amharic” language version questionnaires which were adapted from EDHS and FAO and reviewed from the existed literature, two lab technicians to determine the Hb level, four clinical nurses data collectors, and two BSC nurse supervisors. The questionnaire was prepared in English and then translated into the languages of both Afaan Oromo and Amharic version then retranslated back to English by experts to ensure consistency of the instrument. Two days of training were provided by the principal investigator which is focusing on the objective of the study to create a common understanding of the questionnaire administrations, anthropometric measurements, interviewing approach, and ethical issues. A pretest was conducted among 28 adolescents in Agaro town secondary school, which is 42 kilometers (km) from Jimma town. After pretesting, the necessary corrections were made based on the results of the pretest and the reliability test was performed through Cronbach's alpha (0.758) for selected tools.r = 0.985) and coefficient of variation (CV = 0.44).Standardization was done for anthropometric measurements, the weight scale was calibrated before data collection with a known standardized object weighing 2 kg, and it checked the functionality routine in between and before measuring the respondentʼs weight. The HemoCue Hb301 analyzer was validated before starting the actual data collection in Jimma University Medical Center, which is found in southwest Ethiopia by comparing with the Sysmex Pyramid XT-1800i model which was taken as a golden standard at a facility level to determine different hematological tests including hemoglobin. Hemoglobin measurement took place at a time with the same sample for 20 individualsʼ blood samples in both machines and the relationship of them were compared through the Pearson correlation coefficient , vegetables, fruits, fish, tubers, meat (including organ meat), milk, egg, and legumes. Each food group had been counted only once resulting in a possible score of 0 to 9. In this study, food groups are categorized into low dietary diversity (≤3 food groups), medium dietary diversity score who consumed four and five food groups, and high dietary diversity (≥6) , 18.Weight was measured by an electronic digital weight scale (Secca Germany) with minimum/lightly/clothing and no shoes/jewelry and recorded to the nearest 0.1 kg. Calibration was done every morning, and before every weight measurement, the data collectors assured the scales reading exactly at zero. The weight scale was validated against known object weighing 2 kg measured regularly. The same measurer was employed for a given anthropometric measurement to avoid variability after intensive training was given. All measurements had been taken twice, and the average was computed. Similarly, height measurements were carried out using a wooden height measuring board with a sliding head bar. The subjects were asked to stand straight on the leveled surface with heels together and their heads positioned and eyes looking straight ahead (frankfert plane) without shoes. Heals, buttocks, and shoulder blades should touch the vertical surface of the stadiometer. The moving headpiece of the stadiometer was applied to lower to rest flat on the top of the head, and reading was near to 0.1 cm .Anemia-related knowledge was assessed by using a pretested questionnaire. Adolescents in this study have been interviewed on anemia-related knowledge questionnaire that had been adapted from assessing KAP FAO guidelines. It had consisted of eight questions: how can recognize someone who had anemia, consequence of anemia for infants and children, causes of iron deficiency anemia, consequence of anemia in pregnant mother, prevention methods of anemia, sources of iron rich foods, foods increase iron absorption, and foods decrease iron absorption. Then, if the respondents answered the correct answer coded as “1” and “0” if they give the wrong answer regarding anemia. The maximum attainable score was 8 and the minimum possible score is zero. The answers to each question changed to a percentage. An individual who scored 50% and above was considered to have good knowledge and adolescent girls who scored below 50% have been considered to have poor knowledge .26 items used to assess household fixed assets. The tool was adapted from the Ethiopian demographic and health survey (EDHS), and it was ranked as tertile .∗  + 0.22 ∗  2 for an average altitude of the Jimma town (1780 m) above sea level to subtract (which was 0.56 gm/dl) the adjustment from the individual measured Hb concentration values [A portable battery-operated HemoCue Hb 301+ analyzer was used to measure the hemoglobin. It is used mainly in primary care and blood donation setting; it is a simple and convenient solution in poor resource settings. A sample of capillary blood was collected from the ring finger using lancet under strict aseptic precaution, using the thumb, lightly pressing the finger from the top of the knuckle towards the tip. This stimulates the blood flow towards the sampling point. The first drop of blood was wiped away, and the second drop was used for Hb determination. One microcuvette is used only once per individual. After that, the microcuvette was put in the haemoglobinometer, and the reading was observed within 1 minute. Then, reading was classified as normal hg ≥ 12 g\dl and anemic if the hemoglobin value <12 g/dl based on the WHO 2011 recommended cutoff points after adjustments to altitude was made. Adjusted Hb (hemoglobin) concentration was made calculated as Hb = −0.32 ma town 180 m abovThe collected data were checked for completeness and consistency by manually before entry into a computer. Then, the questionnaires were coded, and data was entered into Epidata version 3.1. Then, the data were exported to SPSS for windows version 20 for further analysis.Z-score of indices HAZ and BAZ using the standard of WHO 2007 growth reference. According to this reference, if adolescent girls had BAZ < −2SD, it is considered as thinness, normal if BAZ between −2SD and +1, and overweight was considered as if the 1SD < BAZ ≥ +2SD, whereas if the respondents HAZ ≤ −2SD, it indicates stunting [Height and weight are transferred into WHO Anthro plus considering the age to convert nutritional data into stunting .Descriptive statistics like table and pie charts were used to present data. Frequencies and Percentages were used to organize the categorical independent variables, mean/standard deviation was used to describe a continuous variable, and cross tabs were done to identify adolescents with and without anemia and the prevalence of anemia by its severity.p value ≤ 0.25. Adjusted odds ratio (AOR) with 95% CI was used to determine the predictors of the outcome variable independently and to show the strength of an association; p value less than 0.05 was considered as statistically significant.Both bivariate and multivariable logistic regression analyses were employed to identify the candidate variables and contributing factors of anemia in adolescent girls, respectively. Binary logistic regression analysis was used to identify the candidate variables for multivariable logistic regression at p < 0.05. After the entire checkup from the total 26 variables, 18 variables with six components were left. Finally, the household wealth status was computed and ranked into three categories after checking chi-squared assumptions.The household wealth status was computed using the PCA method by considering locally available household assets, which were dummy coded. Before running the PCA, assumptions were checked: sampling adequacy with KaiserMeyerOlkin and the results of each analysis was >0.5; presence of substantial correlation was checked by correlation matrix, which showed more than two items has a correlation coefficient >0.3. In addition, Bartlettʼs test of sphericity was checked, and it was significant at Ethical clearance was obtained from the Ethical Review Board of Jimma University, Institute of Health, College of public health and medical science, and we also got permission from Jimma Zone Education Department, Jimma zone health office, Jimma town health office, Jimma town administrative education office, school directors, and Keble units. Capillary blood collection was performed after obtaining a signed written informed consent from parents for adolescent girls less than 18 years of age and oral assent from the girls. Girls who are 18 years and above signed a written informed consent form. The aim of the study was explained to all students. Each study participants was informed about the right to withdraw the consent and stop participation at any time without any form of prejudice. Privacy and confidentiality were maintained at each step of the study process. Aseptic techniques were assured by wearing gloves during blood collection and using new lancet for finger pricking. Penetrating injuries were avoided by using fresh self-retractable lancets for all participants to draw a minimal drop of blood for the anemia testing.The sample blood was never used for further investigation other than hemoglobin analysis and subjects were informed accordingly. Adolescent girls who have anemia were given nutritional education and were asked to visit the nearest health facility.Five-hundred twenty-eight adolescent girls were interviewed in this study and yielded a 95.6% response rate. The mean ages with a standard deviation of the respondents were 16.48 ± 1.17 years. The majority (89.2%) of respondents was from government schools, and 224 (40.3%) students were from grade 9. More than half (52.8%) of the respondents belong to the Oromo ethnic group. Two-hundred nineteen (41.5%) of the respondents were orthodox by religion followed by Muslims (179 (33.9%)). The majority of (498 (94.3%)) of the adolescent girlsʼ marital status was single. Three-fourth (394 (74.6%)) of the adolescent girls are living with their parents. The majority (80.1%) of the respondentʼs parents were alive. Regarding the parental level of education, more than one-fourth (151 (28.6%)) adolescent girlsʼ fathers had finished grade 12 and above followed by secondary school (grade 9–12) (22.5%). Similarly, one-fourth (25%) of girlʼs mothers were above grade 12 by education and 12.5% of adolescent girlʼs mothers were not able to read and write. Similarly, as of the parental occupational status, 232 (43.9%) of mothers were housewives, whereas 26.9% of mothers were government employees. Forty-three percent of fathers of adolescent girls were government employees, and 29.2% of them were merchants. More than one-third (35%) of adolescent parents were under low economic class .The prevalence of anemia among adolescent girls was 141 ) , of whicSeventy-three (52%) of adolescent girls who had anemia were in the age group of 17–19 years, whereas 68 (48%) of them were in the age group 14–16 years old. Similarly, from the total anemic adolescent girls, 48.9% of them live with their family followed by 29.8% of girls who live away from their family and the rest 21.3% of them living with relatives. The proportion of anemia among adolescent girls was 61% and 23.9% among girls who were thin and stunt, respectively.Three-hundred seventy-one (70.3%) girls heard about iron deficiency anemia. From the total anemic adolescent girls, about 53.2% of girls heard or have information about anemia. The majority of 302 (82.7%) of them responded to have less energy/weakness to recognize somebody has anemia. One-hundred sixty (43.0%) of adolescent girls responded that lack of iron in the diet or eating too little was the cause of iron deficiency anemia followed by heavy bleeding during menstruation 117 (22.2%). Out of 371 respondents who heard about anemia, 296 (79.6%) study participants had poor knowledge related to anemia .Regarding DDS, the mean dietary diversity score of the adolescent girls was 5.15 (±1.99). Two-hundred thirty (43.6%) girls had a high dietary diversity score of six and above food groups followed by 195 (36.9%) adolescent girls who had medium dietary diversity scores who consumed four and five different food groups, and the rest respondents had low DDS of three and below food groups. The minimum dietary diversity score of adolescent girls was 1 (consumed only one food group), and the maximum dietary diversity score was 9 out of nine food group items .Almost all 519 (98.2%) adolescent girls had attained menarche with a reported age of menarche ranging from 9 years to 16 years with a mean age of 14 years of menarche. Out of five-hundred nineteen girls, 57 (10.7%) were on menstruation during data collection time. Four-hundred twenty-three (81.5%) girls changed their pads three and below three times per day. A small number of adolescent girls had a history of malaria infection within one month. Ninety-two (17.4%) girls had a history of worm infestation within one month during data collection time, and 83 (15.7%) of adolescent girls had taken deworm medicine within one month .Z score was −0.259 (±1.0775), and the mean height for age Z score was −0.7690 (±0.895), respectively. Thinness was recorded in 41 (7.8%) of which 10 (1.9) were severed thinness. Sixty-one (11.6%) of girls were overweight, of which only a few individuals 4 (0.8%) were obese. Stunting which is the chronic form of malnutrition is seen in 46 (8.7%) adolescent girls in the study area.The mean height and weight of the adolescent girls were 157.3 (±6.056) cm and 50.66 (±7.35) kg, respectively. The mean body mass index for age p value <0.05.The motherʼs educational status, living condition of the adolescent girls, dietary diversity score, and duration of menses, meal frequency, and wealth index were found to be a significant association with anemia by multivariate logistic regression at p < 0.001)). Similarly, the odds of having anemia were 3.6 times higher among adolescent girls who had low DDS compared with girls who had high DDS ). Additionally, the odds of having anemia were 2.2 times higher among adolescent girls having a duration of menses greater than five days compared with girls who had a duration of menses less than or equal to five days . Adolescent girls who were from low-income families were 2 times more likely to be anemic compared with girls who had high-income families AOR = 2.16 . However, maternal educational status of having at least attended a secondary school was negatively associated with anemia among adolescent girls compared with mothers who cannot read and write AOR = 0.43  , p=0.016) .The study was attempted to assess the magnitude of anemia and associated factors among adolescent girls in Jimma town high schools. The result of this study indicated that the overall prevalence of anemia among adolescent girls was 26.7% . According to WHO criterion, if the prevalence of anemia was within 20% to 39.9%, it is considered as a moderate public health concern, so anemia in adolescent girls in Jimma town is a moderate public health concern. Among adolescent girls who had anemia, the magnitude of mild and moderate anemia was 61%, and 39%, and no one was reported to have severe anemia. The factors associated with having anemia among adolescent girls include mother education, duration of menses, low dietary diversity score, living condition of adolescent girls, and lower economic class of the family.This finding is in line with that reported in Kenya (26.5%) , the locHowever, the finding of this result is found to be lower than that of studies conducted in Nigeria which showed the overall prevalence of anemia of 47.5% . The posThe finding of this study was higher than that reported in central Kerala, India, where the overall prevalence of anemia was 21%; the possible reason might be more than half (56.25%) of the respondents were taken deworm medication like that of the current study (15.7%) . SimilarThe result of this study is also higher than that conducted in the local studies, Bahirdar, northern Ethiopia, where the overall prevalence of anemia was 11.1% . The difIn addition to the abovementioned factors, to make difference regarding the magnitude of anemia among adolescent girls could be due to differences in sociocultural and behavioral practice including dietary habit differences between one another in the world. The result of our study also varied with the result of local studies; it might be because the differences of the study period could lead to seasonal variation.Adolescent girls whose mothers attended at least secondary school were 59.6% less likely to develop anemia than adolescent girls whose mothers cannot read and write. Similar studies were reported in four populous villages of India and the urban slum of Kanpur, Uttar Pradesh, India, adolescent girls whose mothers were either illiterate or had only primary education developed anemia than their counterparts , 33. ThiThe odds of having anemia were 4.4 times higher among adolescents living separately from their family than those lived with the family. Similarly, the odds of having anemia were 2.5 times higher among adolescents who lived with their relatives compared with those who lived with their families. A similar finding was reported from a study conducted in Dembia, northwest Ethiopia, where school going adolescent girls who lived with their guardians are more affected by anemia compared with their counterparts . The posThe present study also tells the odds of having anemia were 3.5 times higher among adolescents whose DDS is low compared with those who have high DDS. A similar study was reported from India, Nepal, Nigeria, and Kenya as consumption of low diversified foods was associated with anemia among adolescent girls , 27, 34.This finding was also consistent with the report of the study result conducted in Tigray, north Ethiopia  and DembIn this study, the history of worm infestation for the last one month before data collection was not significantly associated with anemia among adolescent girls; this is not in agreement with a similar study in Bahirdar where adolescent girls with a history of parasitic infection were 2.8 times more likely to be anemic than those without intestinal parasite . This stThe history of malaria infection for the last one month before data collection period also was not significantly associated with anemia in this study which is in contrast with the study result reported in Kenya where the presence of malaria parasitemia was 3.8 times more likely to be anemic than who did not have malaria parasitemia . The reaThe odds of anemia were 2 times higher among adolescents who had menstrual bleeding more than 5 days as compared with adolescents girls with menstrual bleeding less than or equal to 5 days. This finding was consistent with the study result reported in the Tang ail region of Bangladesh, central Kerala, India, Nepal, and locally Bahirdar, northwest Ethiopia , 34, 36.This study revealed that low economic status has been one factor for anemia in adolescent girls ). The odds of anemia were 2.6 times higher among adolescents whose families are under low wealth status than those who had high wealth status families. This finding is also comparable with the study report result conducted in the Berhale afar region ; in thisIn this study, the prevalence of anemia was a moderate public health problem. Factors associated with anemia were low wealth status, adolescent girls living separately from their parents, low dietary diversity score, and duration of menses greater than five days. However, adolescentsʼ mother who had attended at least secondary school was a protective factor for anemia in adolescent girls in this study.


In this study, an innovative methodology to optimize amorphization during the hot melt impregnation (HMI) process was proposed. The novelty of this report revolves around the use of thermal analysis in combination with design of experiments (DoEs) to reduce residual crystallinity during the HMI process. As a model formulation, a mixture of ibuprofen (IBU) and Neusilin was used. The main aim of the study was to identify the critical process parameters of HMI and determine their optimal values to assure a robust impregnation process and possibly the highest possible amorphization rate of IBU. In order to realize this, a DoE approach was proposed based on a face-centered composite design involving three factors. The IBU/Neusilin ratio, the feeding rate, and the screw speed were considered as variables, while the residual crystallinity level of IBU, determined using differential scanning calorimetry (DSC), was measured as the response. Additionally, the stability of IBU under HMI was analyzed using high-performance liquid chromatography to estimate the extent of potential degradation. In order to verify the correctness of the DoE model, tested extrudates were manufactured by HMI and the obtained extrudates were thoroughly examined using scanning electron micrography, X-ray powder diffraction, and DSC. Hot melt extrusion (HME) is a continuous process originating from the plastic and food industries. At the end of the last century, HME was successfully implemented into pharmaceutical technologies and applied as a production process of various drug delivery systems, such as granules, pellets, and sustained release tablets ,2. The main idea of HME is to disperse or dissolve an active pharmaceutical ingredient (API) within a polymeric matrix to form a solid dispersion in either a crystalline or amorphous phase, or ideally to create a one-phase solid solution system. This approach is especially useful to overcome problems with bioavailability commonly seen in poorly water-soluble drugs found in oral formulations, since the use of an amorphous form of an active substance is well known to improve oral bioavailability . AmorphoIn addition to standard polymeric substances, applications using inorganic excipients as drug carriers to increase dissolution rates of poorly water-soluble drugs were recently reported and defined as hot melt impregnation (HMI) . HMI is Currently, several technological design of experiment (DoE) processes are used for optimization . Such apIn this study, an innovative approach to optimize amorphization during the HMI process was proposed. The novelty of this report revolves around the use of thermal analysis in combination with DoE to reduce residual crystallinity during the HMI process. A model formulation mixture of ibuprofen (IBU) and magnesium aluminometasilicate (Neusilin) was used. Ibuprofen’s low melting temperature and Neusilin’s enormous specific surface area created a mixture with favorable physicochemical properties to investigate the process.The main aim of the study was to identify the critical process parameters of HMI and determine their optimal values, thereby assuring a robust impregnation process and possibly the highest possible amorphization rate of IBU. In order to realize this, a DoE approach was proposed based on a central composite design composed of a fractional factorial and star points placed on the faces of the sides. The IBU/Neusilin ratio, the feeding rate, and the screw speed were considered as the variables, while the residual crystallinity level of IBU, as determined using differential scanning calorimetry (DSC), was measured as the response. To the best of our knowledge, this is the first successful attempt to optimize hot melt impregnation in terms of amorphization efficiency using DSC to determine process efficiency. Additionally, the stability of IBU under HMI was analyzed using high-performance liquid chromatography (HPLC). The correctness of the obtained DoE model was verified, the tested extrudates were manufactured by HMI, and the obtained extrudates were thoroughly examined using scanning electron micrography (SEM), X-ray powder diffraction (XRPD), and differential scanning calorimetry (DSC).® copolymer, due to high friction during the process. Authors proved the possibility of preparation of a stable amorphous solid dispersion by HME  from the proposed HMI process as a function of the IBU content (expressed as mass percentage in the sample) and screw speed . It should be emphasized that the RThe presented equation is a mathematical representation of the model, where the predicted crystallinity can be calculated by inputting values of the impregnated IBU for any combination of input factors within the tested range. Graphically, results were presented as a three-dimensional response surface plot , showingTo verify the correctness of the obtained model, a test batch containing 50% IBU and 50% Neusilin was manufactured by HMI, and the obtained extrudates were thoroughly examined using SEM, XRPD, and DSC. The SEM images of the test composition before and after HMI are shown in The XRPD diffractogram showed the typical signal for IBU crystallinity in a physical mixture, which was contrary to the HMI extrudate sample. A DSC analysis confirmed these results, as endothermic effects visible at around 75 °C indicated the presence of crystalline IBU. In the analyzed impregnate, no endothermic effects were observed, thereby confirming the amorphous nature of the tested samples. Taking into account the assumptions of the proposed model, a fully amorphous material after HMI was obtained at the given conditions .The final step of our investigation was the verification that the obtained extrudate with an amorphous IBU can be used for the tableting process. Moreover, the comparison of the dissolution profile as well as assessment of the thermodynamic stability of the obtained tablets with amorphous IBU and Neusilin were performed. Prepared tablets (IBU04T-200) were manufactured from previously impregnated material and they are presented in The XRPD diffractogram indicated that an amorphous IBU impregnated into Neusilin structures is stable during the tableting process. The achieved results suggest that during tableting, we do not observe destruction of the amorphous IBU–Neusilin structure, which could cause recrystallization of IBU. Furthermore, the preliminary physical stability tests demonstrated that the target formulation causes no recrystallization within two months of accelerated stability study, further time points are ongoing. Currently, investigating the stability is further continued.IBU was purchased from Strides Shasun Ltd.  and magnesium aluminometasilicate was bought from Fuji Chemical Industries Co., Ltd.  under the branded name Neusilin, grade US2. Florite PS-200 were purchased from Tomita Pharmaceuticals Ltd.  and Syloid XDP 3150 were kindly donated by W.R. Grace . Croscarmellose sodium was donated by JRS Pharma . Magnesium stearate was purchased from FACI s.p.a. . Acetonitrile-grade liquid chromatography was obtained from Merck . Aluminum liding foil were purchased from Amcor Flexibles Kreuzlingen AG . PVC of 250 um foil was purchased from MKF-Ergis . The hydrochloric acid analytical grade was obtained from POCH . Commercially available drugs with IBU (200 mg) in both tablets and soft gel capsules were bought from the local drugstore. After weighing, the materials were sieved through a 1.0 mm sieve. The IBU–Neusilin mixtures were then blended in a 2 L stainless steel bin container and rotated at 12 RPM for 10 min in a rotary bin blender from Pharmatech, Multiblend MB015 . Three different compositions were examined: IBU–Neusilin 40%:60%, IBU–Neusilin 50%:50%, and IBU–Neusilin 60%:40%.The hot melt impregnation process was conducted with a twin screw (co-rotating) extruder ThreeTec ZE 18  with an L/D ratio of 20:1, including four heating zones. The optimal temperature profile of the process was chosen experimentally and described by our previous work . The finThe thermal properties of IBU, Neusilin, and the examined physical mixtures and extrudates after HMI were investigated using the Mettler-Toledo Star 1  apparatus. Samples ranging from 0.1 to 2 mg in mass were placed in a standard aluminum pan with a pierced lid and heated at 10 °C/min from 30 to 200 °C. Before the start of work each day, the DSC instrument was calibrated with respect to Zn and In. All experiments were carried out under a nitrogen flow of 30 mL/min. The observed thermal effects were quantified and recalculated to the residual IBU content.X-ray analyses of samples of physical mixtures and extruded materials were conducted using a powder diffractometer from Rigaku Miniflex . The XRPD apparatus was used to count the detected intensity as a function of the angle between the incident and the diffracted beam. A Cu anode at 30 kV and 15 mA with a Kβ foil filter, a variable divergence slit, a fixed scattering slit at 4.2 mm, a fixed receiving slit at 0.3 mm, a Soller slit at 2.5°, and a NaI scintillator as a detector were used during this study. After the sample was placed on a silicon holder, the scanning program was applied with the parameters of 2–38° 2θ, with a sampling width of 0.02°, and a scan speed of 1.00°/min.The surface morphologies of the physical mixtures and extruded materials were visualized using the Carl Zeiss EVO/LS25 Scanning Electron Microscope  equipment with a backscattered electron (BSE) detector. Before analysis, the samples were mounted on an aluminum stage using an adhesive carbon tape. The experiments were carried out in a variable pressure mode in a nitrogen gas environment. The gas pressure in the chamber ranged from 60 to 100 Pa at an accelerating voltage of 20 kV. This method allows for the analysis of non-conductive samples, since it reduces the sample surface charging effect .For DoE purposes and statistical analyses, the MODDE Pro 12  software was used and a face-centered composite design was chosen. The experimental plan, with three input factors at three levels and three repetitions at central points, was established using algorithms implemented into the MODDE Pro 12 software. The total number of runs was 17. Optimization of the hot melt impregnation process to develop an amorphous IBU solid dispersion was the aim of the design. The tested factors were feeding rate, screw speed, and IBU content, with the temperature profile and screw design kept at constant. As a response of the design, the content of crystalline IBU was measured. The run sequence was randomized according to the scheme presented in 18-HPLC column . Before injection, sample solutions were filtered through a 0.45 μm GHP syringe filter . A binary mobile phase consisting of 25% aqueous solution (0.1%) and 75% acetonitrile was used. The isocratic flow was set at 1 mL/min and the injection volume was 10 μL. The column oven and autosampler temperature were constant at 25 °C. The detection of IBU was performed at 273 nm.The HPLC analysis was carried out using the Waters Alliance 2695 Separations HPLC System  equipped with an ACE CAn in vitro dissolution study was conducted on IBU products 200 mg in strength. The drug release was carried out in 900 mL of 0.1 N HCl, paddle apparatus (paddle speed 50 RPM). Dissolution bath and vessels were equilibrated to 37 ± 0.5 °C. During the test no sink conditions were fulfilled. At predetermined time points, samples were collected . The test was performed on the DISTEK Evolution 6100 . Collected samples were analyzed using UV–Vis spectroscopy . Samples were collected automatically from dissolution vessels by the peristaltic pump Agilent 8VS  and analyzed at 221 nm wavelength. Analyses were performed for six formulations of each type and the standard deviation of obtained results was below 5%.Tablet compression has been conducted on a laboratory rotary tablet press Killian IMA Pressima . Formulation IBU04  was compressed into Ø12 mm biconvex round tablets, each tablet contained 200 mg of ibuprofen in an inorganic carrier. The tableting blend was fed through the feeder with paddles. The rotation speed of the turret was set at 25 RPM. A pre-compression force equaled 0.5 kN, and the main compression force was set at 5 kN.Prepared tablets were packed in PVC/Al blisters. The O.M.A.R. Fantasy Plus Blistering machine  was utilized. The sealing temperature was set at 135 °C, the sealing time was equal to 1.5 s. For blistering, previously formed PVC 250 um thickness blisters were used. Blister forming was conducted at 125 °C.The accelerated stability study was conducted in a validated climatic chamber KK750 . A climatic chamber was validated to conditions of 40 °C and 75% RH. Tablets packed in PVC/Al blisters were placed in a chamber and the influence of storage time were tested.The discussed method provides a fresh new look regarding the optimization of HMI in terms of amorphization efficiency. The developed model allowed the prediction of processing parameters, which should be applied in order to manufacture completely amorphous solid-phase dispersions. Among the target process parameters, the IBU content and screw speed significantly influenced the crystallinity level of IBU, whereas the feeding rate did not have an impact on IBU amorphization. The accuracy of the proposed model confirmed verification of the test batch, which was subjected to SEM, XRPD, and DSC analysis. Taking into account the similarities between amorphous API and the matrix substance complex formations, which are based on physical mechanisms such as pore size, we believe that the proposed approach could be simply transferred to optimize the HMI process for other mixtures. This assumption supports reports of other chemically diverse substances such as ketoprofen, indomethacin, naproxen, or progesterone ,18, whic


Pyricularia oryzae, represents the most damaging fungal disease of rice worldwide. Utilization of rice resistant cultivars represents a practical way to control the disease. Most of the rice varieties cultivated in Europe and several other temperate regions are severely depleted of blast resistance genes, making the identification of resistant sources in genetic background adapted to temperate environments a priority. Given these assumptions, a Genome Wide Association Study (GWAS) for rice blast resistance was undertaken using a panel of 311 temperate/tropical japonica and indica accessions adapted to temperate conditions and genotyped with 37,423 SNP markers. The panel was evaluated for blast resistance in field, under the pressure of the natural blast population, and in growth chamber, using a mixture of three different fungal strains.Rice blast, caused by the fungus japonica and indica with respect to temperate japonica varieties. The GWAS identified 14 Marker-Traits Associations (MTAs), 8 of which discovered under field conditions and 6 under growth chamber screening. Three MTAs were identified in both conditions; five MTAs were specifically detected under field conditions while three for the growth chamber inoculation. Comparative analysis of physical/genetic positions of the MTAs showed that most of them were positionally-related with cloned or mapped blast resistance genes or with candidate genes whose functions were compatible for conferring pathogen resistance. However, for three MTAs, indicated as BRF10, BRF11–2 and BRGC11–3, no obvious candidate genes or positional relationships with blast resistance QTLs were identified, raising the possibility that they represent new sources of blast resistance.The parallel screening identified 11 accessions showing high levels of resistance in the two conditions, representing potential donors of resistance sources harbored in rice genotypes adapted to temperate conditions. A general higher resistance level was observed in tropical We identified 14 MTAs for blast resistance using both field and growth chamber screenings. A total of 11 accessions showing high levels of resistance in both conditions were discovered. Combinations of loci conferring blast resistance were identified in rice accessions adapted to temperate conditions, thus allowing the genetic dissection of affordable resistances present in the panel. The obtained information will provide useful bases for both resistance breeding and further characterization of the highlighted resistance loci. Pyricularia (syn. Magnaporthe) oryzae, ranked first as the most important rice disease in the world  genes in the same line, is a priority for rice breeding  genes, have been identified in both indica and japonica rice cvs  proteins  and 102 rice Linkage Disequilibrium (LD)-mapping based on Genome-Wide Association Studies (GWAS), exploiting marker polymorphisms across all chromosomes, has become increasingly popular and powerful over the last years and widely adopted for QTL mapping in plants  was also evaluated in growth chamber conditions using a mixture of three highly virulent Italian P. oryzae isolates , were respectively evaluated under field and growth chamber conditions for resistance to rice blast.A total of 290 and 277 rices, belonging to a panel of 311 p-value < 2.2e-16), indicating a robust relationship among the data from 2 years. Blast evaluation was based on a 1–9 scoring system on leaves ; all the accessions with a score below or equal to 3, showing higher number of small lesions with some becoming elliptical, indicating capabilities in limiting the spread of infection, were considered as resistant, while the remainder as susceptible. Using this threshold, only 5.5% (16/290) of accessions were classified as resistant, while 57.2% (166/290) were highly susceptible  are reported in Fig. R genes , showing a broad pattern of virulence towards several blast , IT10, sPair-wise comparisons of disease resistance between the field and growth chamber data indicate a robust relationship between the recorded phenotypes  was defined, and the percentage of varieties classified as admixed was 12.5%  were 8.75 and 4.00 for the field and growth chamber evaluations, respectively; while the K2 cluster, containing mainly tropical japonica, but also indica, aus and aromatic accessions, showed median scores of 5.63 and 2.17 for field and growth chamber evaluations respectively; admixed varieties scored in-between the two main groups . The differences between temperate japonica and the tropical japonica plus outgroups were statistically significant, as resulted from Kruskal-Wallis and Dunn’s tests  and minor allele frequency (> 5%) the final set included 37,423 SNPs, with an average value of 3119 markers/chromosome. Assuming an estimated genome size of 373 Mbp  of the peak SNP markers ranging between 3.87 and 14.59 and passing a False Discovery Rate threshold of 0.05  were identified, with -log05 Table . Of thesjaponica cluster and outgroups) or the admixed group  were observed for BRF04, BRF11–1 and BRF06–1 , suggesting that gene(s) underlying these MTAs contributed most effectively to blast resistance under these conditions. The same was observed for BRGC11–2, BRGC11–1 and BRGC06 in growth chamber conditions . For these loci, the highest incidence of favourable alleles at the peak markers was observed in either the K2  and BRGC06  largely overlapped, even considering that the two peak markers were separated by about 205 Kbp from each other  and located within the regions defined by −/+ 100 kbp sequences from the MTA peak marker. Moreover, the positions of the significant MTAs were compared with those of known blast R genes or QTLs present in literature. Results are summarized in Fig. To search for candidate genes underlying the MTAs identified in this study, we considered all annotated genes available from the R gene Piz and its allelic variants Piz-t, Pi2, Pi9 and Pi40  and Pigm(t), were also present in this region  was treated as a single peak. The search on RAP-DB detected a total of 26 genes located in the chromosome 6 interval from 10,084,497 to 10,490,006 bp. Of these, 20 were functionally annotated and included Os06g0286700 , corresponding to the cloned blast Pib gene , as well as its allelic forms , Pish (Os01g0782100) and Pi37 (Os01g0781700). Local LD decays slowly in this region, as evidenced by a 246 Kbp block, spanning from 32,855,693 to 33,101,889 bp, and covering the entire region between BRF01  and Pi64  , no genes having a function related to pathogen resistance were detected using RAP-DB, with the exception of a MATH domain containing protein  and Pi63 blast resistance loci  contained both BRGC01 and the Pit gene , Os11g0647600 (Plant disease resistance response-related protein) and Os11g0648600 and Os11g0649100 (both NB-ARC domains containing genes). Moreover, the locus is positionally related to AtGPAT6, involved in Arabidopsis resistance to fungal pathogens  and the susceptible accession Maratelli  under growth chamber conditions. Infection and disease scores were evaluated following the procedures adopted for the GWAS of the 277 accessions. The analysis of variance of phenotypic data revealed a highly significant effect of the genotype (P < 0.0001) on the disease incidence, with no significant differences observed between replications (P = 0.38). No transgressive lines (with extreme resistance/susceptibility phenotypes) were observed, suggesting that resistance factors were contributed only by Salvo. The estimated broad sense heritability for resistance within the Salvo x Maratelli population was 92.5%, indicating that most of the phenotypic variance was due to genetic effects.BRGC11–1 was an MTA providing a high allelic effect  under growth chamber conditions. To further dissect and validate the role of this region in blast resistance, a biparental FA total of 3724 SNP markers together with 46 SSRs were used to assemble the genetic linkage map. After elimination of the unlinked loci, the genotypic data relating to 1581 informative marker loci were assembled into 15 linkage groups corresponding to the 12 rice chromosomes  on chromosome 11, with a LOD score of 29.81 and explaining 74% of the phenotypic variation. The QTL peak was represented by the RM224 SSR marker and, based on Darvasi and Soller , the conjaponica rice cvs cultivated in temperate regions are susceptible to blast, a situation that underlines the relevance of identifying suitable sources of resistance adapted to these environments and loci governing the traits to be used in marker-assisted breeding for durable blast resistance. This study identified sources of resistance adapted to temperate conditions and with limited barriers for crossing with temperate japonica. The adoption of the two screening procedures allowed to discriminate accessions  showing resistance under the simplified pressure of a mixture of three blast isolates but being susceptible under a different or more complex pathogen field population. Moreover, the application of two different disease pressures allowed the identification of a high number of genomic regions involved in blast resistance, thus boosting the power of the investigation. Indeed, of the 14 MTAs identified, five  were detected only under field conditions while three  only after inoculation in growth chamber conditions. Similarly, previous GWAS studies for blast resistance conducted using the rice diversity panel 1 , while admixed represented the 12.5%. When the disease scores were analyzed in relation to each group, the average disease scores were higher for the temperate japonica accessions compared to the remaining accessions  and 2.25 in the field . This observation is in agreement with evidence that several donors for qualitative Pi R genes conferring high levels of vertical resistance belong to the indica group  and 53 tropical 2) observed In the GWAS panel decayed to 0.2  or a mixture of a restricted number of strains (BRGC). Furthermore, since the positions of BRF11–1/BRGC11–2 and BRF06–1/BRGC06 are overlapping, these loci should be considered effective in governing both single and multiple strain resistance and can be suggested as the most interesting and useful targets for blast resistance breeding. For example, resistant alleles at both loci are present in accessions like Arsenal, Cadet, Jefferson, and UPLA_91, and these lines could therefore be used as resistance donors in breeding programs, using the polymorphisms at the peak markers of the identified blast resistance associated regions for molecular marker assisted selection.indica accessions  under both field and growth chamber conditions was associated with a conserved combination of MTA resistant alleles , whereas for temperate and tropical japonica, high levels of resistance were achieved through substantially different combinations of MTA alleles. For example, Virgo  carries resistant alleles at BRF01, BRF06–1, BRF07 and BRGC07; Jefferson  has resistant alleles at most of the MTAs; Gigante Vercelli carries resistant alleles at BRF04 and BRF10. The BRF04 resistant allele is the most frequently identified (and the most effective) in field conditions and its position  is adjacent to a QTL for durable blast resistance qBDR4  identified in a cross between the durable resistant Gigante Vercelli and the susceptible Vialone Nano , BRF07, BRF10, BRGC07 and BRGC11–3, while for the tropical japonica Lacassine, resistant allele were highlighted for BRF06–2, BRF11–1, BRF11–2 and BRGC11–1/2/3. Finally, the temperate japonica Venere brings resistant alleles for BRF07 and BRGC07. The use of these accessions as blast resistance donors in breeding can be assisted with the identified polymorphisms at the MTAs by selecting the resistant alleles for all the involved loci or just selecting those providing larger values of explained phenotypic variance and larger gap in average blast scores among the major and minor allele of the peak marker.Analysis of haplotypes around peak markers in the 11 accessions showing resistance in both phenotyping conditions  is also localized on chromosome 6, inside the BRF06–1 and BRG06 MTAs  there are no obvious resistance gene candidates, likely indicating that these loci might harbor previously unidentified blast R genes. A survey of the Nipponbare annotated genome was performed, by screening a region (peak marker of each MTA −/+ 100 Kbp) approximately corresponding to a LD decay to its half-maximum as a trade-off between accuracy and power of the analysis; this allowed to restrict the analyzed interval and to focus on stronger marker-gene associations. Several genes were thus identified in the peak regions of these MTAs, whose function is related to mechanisms of resistance to biotic stress, suggesting that they may contribute to the resistant phenotypes. These genes include a MATH domain containing protein, a RING protein with ligase E3 function, adenosine-sulphate kinases, a B3 domain transcriptional repressor, a glycerol–3–phosphate acyltransferase, a Leucine-rich repeat N-terminal domain containing protein, a plant disease resistance response-related protein, and two proteins containing NB-ARC domains. Interestingly, a pair of co-located loci, the BRF11–2 and BRGC-11-3, were identified using the two different phenotypic screening procedures, and the BRF11–2 resistant allele is the second (after BRF04) most frequent allele detected in resistant accessions under field conditions, while the BRGC11–3 resistant allele is the most frequent allele detected in resistant accessions in the growth chamber  and LOC_Os11g45930 , were located inside the LD blocks of BRGC11–1  and BRF11–1/BRGC11–2 , respectively. Overlapping was also observed between the physical positions of the resistance QTLs identified in the present work and the ones discovered by Li et al. , represents a non-strain specific partial R gene  in a region that is replete with known blast resistance genes. SxMBRQTL-1 was sparsely covered by SNPs in the diversity panel, yet it showed a correspondence with the BRGC11–1 interval and, most importantly, the peak marker of BRGC11–1 was located within SxMBRQTL-1. Approximately 50% of the resistant cvs analyzed in growth chamber experiments were found to carry the resistant allele at this locus. These results suggest that chromosome 11 harbors a large reservoir of genetic variation that contributes to blast resistance in temperate-adapted rice varieties.japonica and outgroup varieties, though highly resistant temperate japonica genotypes were also identified.The parallel screening (field and growth chamber) for blast resistance of this study allowed the identification of blast resistant rice accessions adapted to temperate conditions. The adoption of the two screening procedures uncovered accessions showing differential resistance under the two conditions and allowed us to identify a larger number of genomic regions conferring blast resistance than relying on a single approach. The GWAS approach identified 14 MTAs associated to blast resistance. Five of them were detected only under field conditions, while three were discovered only for the growth chamber experiment. The screening procedures identified the largest number of resistant accessions in the cluster of tropical indica accessions with high levels of resistance shared a conserved combination of MTA resistant alleles, while the temperate and tropical japonica cvs achieved high levels of resistance based on a variety of different combinations of resistant alleles at MTA peak markers.Some of the 14 MTAs explained a larger proportion of phenotypic variation than others, and MTAs providing resistance to multiple pathogen strains in the field often overlapped with MTAs providing resistance to a restricted number of strains under growth chamber conditions. Loci conferring high level of resistance in both conditions provide useful targets for blast resistance breeding. When resistant alleles at the MTAs were analyzed with respect to sub-populations, it was observed that the R genes and recently described QTLs were found to be co-located with a large proportion of MTAs, providing numerous “candidates” underlying the associations reported in this study. However, for BRF-10, BRF11–2, BRGC11–3 no obvious relationships with cloned/mapped Pi genes was found, raising the possibility that these loci may represent previously unidentified genetic sources conferring quantitative resistance to the rice blast disease.Previously cloned or characterized blast Oryza sativa accessions from the Rice Germplasm Collection maintained at CREA-Research Centre for Cereal and Industrial Crops . This panel is composed of 76 tropical japonica, 224 temperate japonica, 8 indica, 2 aromatic and 1 aus accessions. Most of these accessions (162) were selected in Italy, 35 in United States, 27 in Portugal, 17 in Spain, 10 in Bulgaria, 10 in Argentina, 8 in France, and the remaining were developed elsewhere but considered as well adapted to Italian agro-climatic conditions. Detailed information regarding the accessions is reported in Additional file The panel used in this study, largely overlapping with the one described in Volante et al. , is comp2/F3lines was obtained from a cross between the blast resistant accession Salvo and the blast susceptible accession Maratelli, both present in the rice panel described above. Young leaf tissue from each F2 plants and the two parents were utilized for the extraction of genomic DNAs through the DNeasy Plant Mini Kit (QIAGEN) following manufacturer’s instructions.A segregant population of 130 FFor field infection, the panel was evaluated for blast disease resistance in two field seasons in 2013 and 2014. The experiments were conducted in a breeding station in North west of Italy  at an altitude of 96 m asl. Blast infection occurred naturally, and spreader rows of the highly susceptible variety Maratelli, sown on the plot borders, were used to ensure high, homogeneous disease pressure. Moreover, to increase blast incidence, a delayed sowing (middle of July) was performed in both experiments. A total of 290 accessions were evaluated in each field season; for each accession, two lines of 2.4 m were sown for a total of 120 plants per accession. Two replicates were performed in the 2013 trials, while no replications were conducted in 2014. Disease scoring was evaluated at full tillering stage using a 1–9 scoring system  modified from the Standard Evaluation System (SES) for Rice  3 lines derived from the cross between Salvo x Maratelli. Plants were grown from seeds in growth chamber and the reaction to blast was tested with three different Italian M. oryzae isolates  of disease traits was performed to test the significance of differences between accessions and replications using the aov function in R. The effects of replications and genotypes were accounted for in the model. The values of variance obtained from the ANOVA were used to calculate broad-sense heritability according to Nyquist . CorrelaThe accessions included in the rice panel were Genotyped-by-Sequencing (GBS) following a pipeline described by Biscarini et al. , except 2/F3 population was digested using the restriction enzyme ApeKI and bar-coded following the protocol as described by Elshire et al.  was obtained. Moreover, all the SNPs having a call rate lower than 90% and/or the ones with MAF lower than 3% were removed from the dataset. A total of 3724 high-quality SNPs were obtained.Genomic DNAs of the Fe et al. . Sets ofe et al. , as deschttp://www.gramene.org/marker) were also tested for polymorphisms between Salvo and Maratelli. The polymorphic SSRs were analyzed in the segregant population using the M13-tailed primer method  was performed on the marker subset used for the analysis of population structure, following the same pipeline described in Volante et al.  method according to Benjamini and Hochberg (p) values below the FDR threshold, in the Manhattan plot. Clusters of SNPs in full LD showing the same p-value in the association analysis were considered as a peak region.A total of 37,423 SNPs were used for the GWAS analysis. A Mixed Linear Model (MLM) was applied, with the kinship matrix (K) as a random effect to consider the population stratification. Association analyses were performed for the two blast evaluations (field and growth chamber), using the average between SES scores recorded in 2013 (average of two replicates) and 2014 for field data, while the average score of the three replicates was used for the growth chamber data. The Tassel v5.2.0 software was used with the following parameters: optimal compression, genetic and residual variance estimated for each marker (P3D OFF). A Hochberg . ManhattThe chromosome-wise local LD was calculated by the Haploview v4.2 software  and reported in Additional file https://shigen.nig.ac.jp/rice/oryzabase/) and neighbor-joining tree.Additional file 2 Table S1. List of accessions used in the study with their geographical origin, taxonomical group, commercial class, group assigned by the STRUCTURE analysis and blast score values.Additional file 3 Table S2. Statistical analyses of the phenotypic traits: ANOVA and h2 for Field and Growth chamber evaluations.Additional file 4 Figure S2. Analysis of the genome-wide LD decay in the rice panel used for GWAS.Additional file 5 Figure S3. Plots of SNPs significantly associated (FDR > 0.05) to blast resistance loci against their chromosome positions and –log10(p) values. BRF and BRGC refer to Blast resistance in Field and Blast Resistance in Growth Chamber, respectively.Additional file 6 Table S3. Gene models contained in the regions defined by the GWAS analysis, from the Os-Nipponbare-Reference-IRGSP-1.0.Additional file 7 Table S4. Colocalization between MTA and known Pi genes. Bold names indicate cloned genes.Additional file 8 Table S5. A. Salvo x Maratelli linkage map. Linkage Groups (LG), chromosomes, marker names and their position  are reported. B. Distribution of molecular markers in the chromosomes of the Salvo x Maratelli map. C. QTL detected in Salvo x Maratelli segregating population. LOD score, percentage of phenotypic variance explained (R2), additive effect and the confidence interval (CI; Darvasi and Soller,