Coffea arabica L. was sequenced to assemble independently the two component subgenomes (putatively deriving from C. canephora and C. eugenioides) and to perform a genome-wide analysis of the genetic diversity in cultivated coffee germplasm and in wild populations growing in the center of origin of the species. We assembled a total length of 1.536 Gbp, 444 Mb and 527 Mb of which were assigned to the canephora and eugenioides subgenomes, respectively, and predicted 46,562 gene models, 21,254 and 22,888 of which were assigned to the canephora and to the eugeniodes subgenome, respectively. Through a genome-wide SNP genotyping of 736 C. arabica accessions, we analyzed the genetic diversity in the species and its relationship with geographic distribution and historical records. We observed a weak population structure due to low-frequency derived alleles and highly negative values of Taijma’s D, suggesting a recent and severe bottleneck, most likely resulting from a single event of polyploidization, not only for the cultivated germplasm but also for the entire species. This conclusion is strongly supported by forward simulations of mutation accumulation. However, PCA revealed a cline of genetic diversity reflecting a west-to-east geographical distribution from the center of origin in East Africa to the Arabian Peninsula. The extremely low levels of variation observed in the species, as a consequence of the polyploidization event, make the exploitation of diversity within the species for breeding purposes less interesting than in most crop species and stress the need for introgression of new variability from the diploid progenitors.The genome of the allotetraploid species  Coffea arabica is an allopolyploid species (2n = 4x = 44) resulting from the hybridization between two species most closely related to C. eugenioides and C. canephora1. The allopolyploid speciation of C. arabica has a broad time interval estimate spanning 10,000 or 665,000 years BP3. Unlike many tropical tree crops, Arabica coffee is not clonally propagated. Cultivars and landraces are typically propagated by seed. The mating system is primarily based on self-fertilization, although pollinator-mediated outcrossing may occasionally occur. The predominant autogamy leads to high levels of inbreeding.C. arabica is indigenous to Ethiopia and South Sudan which represents its primary center of diversity4 . Yemen is a secondary dispersal center5. Several accounts of the early history of C. arabica germplasm usage and movements are available in the literature, but the most complete and best documented publication is the one of Haarer (1958). Sometimes during the 14th century, coffee seeds were brought out of the forests of South Western Ethiopia to Yemen, where coffee cultivation expanded to satisfy the demand of a growing number of coffee houses in Moccha and Cairo at the end of the 15th century. The center of diversity in South Western Ethiopia corresponded to the area that has been for centuries under the control of the Kingdom of Kafa. This area was described as an impenetrable “citadelle” until Menelik II conquered the Kingdom in 1897. Hence, early escapes of coffee seeds from South Western Ethiopia were likely occasional and the coffee cultivation in Yemen has started from a narrow genetic basis. C. arabica was then spread worldwide from Yemen rather than from its primary center of origin in Ethiopia. Significant out-of-Yemen movements were documented (i) in 1670, from Yemen to India with some seeds smuggled by Baba Budan and (ii) in 1715, from Yemen to Bourbon Island (today Ile de la Réunion) with very few seeds. The former gave rise to the Typica variety after the Dutch brought some seeds from India to today’s Indonesia in 1696 and 1699. From Indonesia through Europe, Typica reached the Americas in 1723. The latter gave rise to the Bourbon variety that reached the Americas and East Africa in the mid-19th century. In India, the early seeds introduced in 1670 were grown locally for centuries. In the early 20th century, East Africa  started coffee cultivation and introduced seeds from Yemen, Bourbon, Typica and Indian varieties and very few Ethiopian landraces, which leaked from Ethiopia in the pockets of travelers (Geisha and Rume Sudan for instance). Hence, East Africa could be considered as a melting pot of all different varieties descending from early coffee cultivation in Yemen6.C. arabica9. More recently, a molecular study of C. arabica germplasm was performed by Merot-L’anthoene et al.10 using an 8.5k SNP array, which represents the first genome-wide analysis of the genetic diversity in this species but it suffers from the ascertainment bias associated with the limited breadth of variation included in the SNP discovery panel. Unbiased approaches to investigate genetic diversity are supposed to rely on the availability of a C. arabica genome sequence. The genome of a modern accession of C. canephora, one of the progenitors of C. arabica, has been sequenced11, but the assembly of a diploid genome provides limited support for analyzing sequencing data from tetraploid coffee germplasm. Genome sequencing initiatives of tetraploid accessions have been launched by several research groups  but an open-access genome assembly, with a reliable sorting of homoeologous sequences, is not yet available. Decoding the allotetraploid genome of C. arabica is therefore mandatory to have accurate genotyping-by-sequencing (GBS) studies in this species.It is evident that molecular analyses of genetic diversity are needed to support this scenario that is based on geographical and historical data. In the past, microsatellites or RAPDs have been used for studying genetic diversity in C. arabica L. that enabled us to undertake the first GBS approach for polymorphism detection on C. arabica accessions and its parental species. This allowed us to (i) confirm the geographical structure of the genetic diversity of C. arabica which originated after a single event of polyplodization that gave rise to the species and was partly shaped by early movements of planting material, (ii) detect sources of diversity for coffee breeding and (iii) understand the relatedness between the canephora subgenome of C. arabica and the modern diploid C. canephora, some of which are used for the production of Robusta coffee beans.One of the challenges in short read sequencing of polyploid genomes is the difficulty in assembling a reference sequence for the haploid complement by disentangling its homoeologous components. Here we used short read sequencing of pooled BAC clones. Each DNA pool contained ~3% of the haploid genome and was sequenced and assembled separately. This strategy resulted into the first public draft genome of C. arabica varieties conserved in the CATIE International Coffee Collection in Costa Rica. This collection does not only contain elite cultivars, but also the most extensive sampling of C. arabica genetic diversity available outside of Ethiopia. We studied also 93 Yemeni genotypes collected from farmers’ fields in Yemen. Based on the GBS analysis of 736 C. arabica accessions we developed a description of the genetic diversity of the species in the context of their geographical distribution and historical records.For this analysis we selected C. arabica plant of the variety ‘Bourbon Vermelho’. BAC clones amounting to a ~2.8X genome coverage were arranged into 96 pools of 384 clones . After masking repetitive sequences from C. arabica scaffolds we compared 51-mers generated from each scaffold with 51-mers obtained from C. eugenioides and C. canephora WGS reads. A total of 25,315 scaffolds, amounting to a total length of 444 Mbp, shared more 51-mers with C. canephora than with C. eugenioides and were therefore assigned to the canephora subgenome. A total of 26,627 scaffolds, amounting to a total length of 527 Mbp, shared more 51-mers with C. eugenioides than with C. canephora and were therefore assigned to the eugenioides subgenome. The remaining 112,312 scaffolds, amounting to a total length of 565 Mbp, could not be assigned with high confidence to either subgenome due to either their short size or the presence of repetitive sequences or the high similarity between homoeologous sequences. We sequenced 560 million reads, corresponding to 70 Gb of RNA-seq from 8 different tissues of C. arabica, ‘Bourbon Vermelho’ variety . We detected a single large chromosomal rearrangement, corresponding to an event of homoeologous replacement of canephora DNA with eugeniodes DNA in the terminal 1.2-Mbp of chromosome 7, involving 179 predicted genes . Shared regions within each scaffold were identified using (B)LastZ and realigned using MUSCLE. Nucleotide diversity (π) between C. arabica subgenomes based on hemi-SNPs amounted to 3.1 × 10−2.The tetraploid genome in the sequenced accession of ‘Bourbon’ did not show major chromosomal deletions compared to a reference diploid genome of one of the progenitor species (C. arabica (Dataset S2), presumably representing a large fraction of the diversity available in the species. The nucleotide diversity estimate obtained is low , a value that is one order of magnitude lower than that estimated in the present-day germplasm of the two progenitor diploid species . We observed a very peculiar distribution of private mutations , with such mutations corresponding to 74.4% of the variant sites. In order to exclude an underestimation of π due to any alignment bias between the native and derived subgenomes used as a reference genome in our procedure of read mapping  or due to the fragmentation of our reference, we repeated this analysis by aligning dRAD reads against a chromosome-scale assembly of C. arabica ‘Caturra Vermelho’ that became recently available (GenBank assembly accession: GCA_003713225.1). We confirmed the levels of π both in the progenitor diploid species  and C. arabica (π = 2.0 × 10−4) across a larger sample of 339,526 nucleotides.We used GBS data to estimate genetic diversity in a sample of 736 accessions of D in C. arabica was highly negative (−2.51), as expected for a population undergoing expansion after a recent severe bottleneck. A large fraction (87.6%) of variant sites in C. arabica showed a minor allele frequency lower than 0.05. Among the variant sites that were present in more than one individual of C. arabica, 28.7% did not violate Hardy-Weinberg equilibrium, 6% showed an excess of heterozygotes and the majority (65.3%) showed a deficiency of heterozygotes, as expected for an autogamous species.The value of Taijma’s Coffea genus, represented in this study by the most likely parental species, into the population of C. arabica suggest that the tetraploid species has originated from a single event of hybridization. This conclusion is supported also by the distribution of private alleles among the three species  that shows that the vast majority of SNPs identified in C. arabica  of a current population of effective size Ne = 10,000 or 50,000 initiated with a single hybrid individual 10,000 or 20,000 years ago, which attained the final size in 200 generations of exponential growth followed by a constant size or recovering to the final size from a bottleneck that occurred 1,000 years ago. The other parameters in the model were kept constant . These models predicted a nucleotide diversity π ranging between 1.2 × 10−4 and 2.5 × 10−4 for the highest mutation rate and between 2.4 × 10−6 and 5 × 10−6 for the lowest mutation rate and a proportion of private SNPs ranging from 23%  to 35% . Considering a generation time of 5 years, the highest mutation rate per generation of 3.25 × 10−8, that provides diversity estimates that are very similar to those observed, corresponds, on a per year basis, to that estimated in Arabidopsis17. Since coffee varieties and landraces are propagated by seed for establishing new plantations, we also simulated a recent expansion since the beginning of massive coffee cultivation (approx. 0.4 kya) to a current size of Ne = 500,000. This model did not predict substantial changes in the expected values of π but it generated higher expected values of private SNPs (42%) that are closer to the observed values.We performed C. arabica accessions from a single individual that underwent polyploidization, that seems to be fully supported by both the available data and the in silico simulations, expectations can be derived on the patterns and distribution of genetic diversity within the C. arabica population itself and in comparison to diversity within the ancestral species.Under the assumption of a recent origin of all C. arabica in relation to diversity in 35 C. canephora accessions using only the variants identified in the canephora subgenome by performing a Principal Component Analysis (PCA) where the first two PC’s explained 16.9 and 8.2% of the variance  of the Yemeni population from Ethiopian accessions . Indian old varieties and East African old varieties, as well as Bourbon/Typica varieties, overlapped with the area of the PCA plane populated by Yemeni germplasm  and allowed us to assign 94.8% of the predicted genes to their parental genome. We predicted 46,562 protein‐coding genes in C. arabica, which is nearly double the number  of one of its ancestor C. canephora11. This high number is fully compatible with the hypothesis of a recent genome doubling and limited gene loss or pseudogenization since the event of polyploidisation to the present time.Whole genome sequencing is revolutionizing our understanding of biology and the field is developing rapidly due to advances in DNA sequencing technologies. The accuracy of genome sequencing and assembly of complex genomes is affected by different factors ranging from plant material availability to genome size, GC content, repeat content, ploidy level, sequencing technology, and bioinformatic softwareC. arabica, the main issue we had to face was the ploidy level28. To tackle this, we could have opted to isolate chromosomes through flow cytometry29 but we could not consider this technology due to lack of appropriate genetic stocks that would allow for easy chromosome isolation. We thus opted for a hierarchical sequencing approach of BAC pooling where the likelihood of two homoeologous fragments occurring in the same pool was extremely low31, leading to dramatic reduction of the genome complexity in the assemblies of each pool. In this paper, we show a successful application of this genome assembly for studying Arabica diversity.Given the extremely low level of heterozygosity of 32. Yemen would have become the first coffee market. In Ethiopia, drinking coffee was formally prohibited for Christians until the early 20th century and the Ethiopian Coffee ceremony is considered a recent invention33. The prevailing assumption is that coffee seeds were introduced from Ethiopia to Yemen. From southwestern Ethiopia, wild coffee genotypes should have been acclimated to the other side of the gulf. However, domestication of C. arabica over a long period of time (end of 17th century) has also been reported in Ethiopia by scientific observers or travelers in the Harar region, Zeghie peninsula, Sidamo, and Welega province34. During the 15th and 16th centuries, coffee cultivation was developed within Yemen to meet local needs. In Yemen, people transformed the mountainsides into terraced hillsides, built irrigation networks, and invented farming techniques including growing coffee without shade. In our study we compared some ‘Typica’ and ‘Bourbon’–derived cultivars with the Yemeni and Ethiopian accessions. In Latin America, breeders exploited these two narrow genetic bases, which resulted in ‘Typica’ and ‘Bourbon’–derived cultivars, all showing similar agronomic traits and high susceptibility to the major coffee diseases and pests35. Today, over 80% of Arabica coffee is produced in Latin America and Arabica coffee production is still based to a large extent on cultivars developed long ago by line selection within the ‘Typica’ and ‘Bourbon’ varieties or among seedlings originating from crosses between these varieties36.Coffee is a recent beverage relative to the time scale of mankind. Ethiopian nomadic mountain people were probably the first to recognize coffee’s stimulating effect. However, it is estimated that the use of coffee brewing as we know it today would have begun in the Middle Ages in Yemen. The first archaeological evidence of beverage coffee consumption was found in Zabid (Yemen) a city at the south end of the Arabian PeninsulaC. arabica species and in comparison to the ancestral donor species using an unbiased resequencing-based method such as GBS rather than using a SNP chip such as the one recently developed for coffee10. Even though we have analyzed a total number of SNPs that is lower than that present on the above mentioned chip, the unbiased view of sequence diversity provided by the GBS approach has allowed us, on one hand, to obtain robust estimates of nucleotide diversity, allele frequency spectra and other population parameters that could be used to infer past population demographic history and, on the other hand, to avoid the ascertainment bias in estimating population divergence that is intrinsic to SNP chip-based approaches caused by the limited number of individuals from specific populations present within the initial SNP discovery panels38.We have chosen to analyze genetic diversity and population divergence within the C. arabica the lowest level of genetic diversity reported so far in crop species  and predicts that all variation observed in the new species is due to new mutations arisen after the polyploidization event. During the early stages following polyploid formation, the occurrence of a ‘genomic shock’ leading to gene loss and/or homeologous recombination has been observed in some species39. In C. arabica we observed a single instance of homeologous replacement at the tip of chromosome 7 and thus we do not have evidence of a significant contribution of major structural rearrangements occurring after polyploidization.We found in es Table , only coC. arabica out of Yemen through the Bourbon/Typica lineages and point to the existence of wild Ethiopian germplasm that could represent a yet untapped, even though very limited, reservoir of novel genetic variation for improvement of C. arabica cultivated varieties .Despite the hypothesized very recent origin of all accessions from a single allopolyploid and the consequent very recent origin of all polymorphisms surveyed, our results revealed genetic differentiation between Ethiopian accessions, still present in rainforest areas at the Southwesternmost range of distribution of the species, and the germplasm used for intensive plantation in Eastern Ethiopia and in Yemen that is also genetically similar to all cultivated varieties worldwide, from East Africa and India as well as belonging to the Bourbon/Typica lineages. These results are in agreement with historical information on a worldwide spreading of et al.40, the authors used RAPD markers to genotype 20 accessions, observed two groups, consisting of either cultivated coffee or wild Ethiopian accessions. A similar study7 with 119 accessions and 16 markers showed similar results. Finally, a study by Silvestrini et al.41 based on 73 accessions and 15 SSR markers found only two groups, the cultivated group from Yemen and a second group representing accessions from Ethiopia.In the study of Lashermes C. arabica germplasm conservation in Ethiopia have been reviewed by Labouisse et al.42 and regional human overpopulation appears to be the main cause of accelerated destruction of the biodiversity in the montane forests of southwestern Ethiopia43. Knowledge of coffee genetic diversity at the molecular level is essential for effective strategic conservation in ex situ collections and for protection of in situ populations, as well as the use of these resources to meet both current and future breeding needs. The vast germplasm collection of CATIE is easily accessible but its use for crop improvement is still very limited. Molecular markers used in the present study helped to clarify the structure of the genetic diversity of the species. The wild germplasm collected from the forest areas in Ethiopia is already considered a valuable source of new diversity for breeding programs. For example, controlled crosses between wild Ethiopian progenitors and American cultivars (i.e. descendants from the Yemeni population) have produced high yielding F1 hybrids44, suggesting heterotic groups that can be further differentiated and optimized through targeted selection45. The genetic diversity of C. arabica available within the collections outside of Ethiopia is currently exploited for breeding programs to cope with the challenges of climate change around the world. While a global coffee genetic resource conservation consortium is certainly needed to ensure that existing coffee genetic resources are preserved in Ethiopia, the low level of genetic diversity in C. arabica compared to the much higher diversity in the present-day populations of its progenitors suggests that introgression events into the allotetraploid species from the diploid species such as those exploited to achieve coffee rust resistance in derivatives of the Timor hybrid47 are of paramount importance to broaden substantially the genetic diversity in the cultivated germplasm and increase environmental, economic and social sustainability of coffee cultivation.Genetic diversity is the foundation of the genetic improvement of crops and has become a strategic economic and cultural identity issue. The challenges of Coffea arabica, a tetraploid species, with the aim of reconstructing separately homoeologous sequences and provide a reference for studying allelic variation in Arabica. Our genome assembly is relatively fragmented, but it contains most of the conserved set of plant single-copy orthologs and allowed us to assign most of the predicted genes to their parental genome and to perform an in-depth unbiased analysis of Arabica population history and diversity. We found in C. arabica a very low level of genetic diversity and an extremely large fraction of private alleles, both when considering individual accessions as well as when comparing the polyploid species with the two progenitor species. All evidence collected are compatible with the origin of C. arabica from a single polyploidization event that occurred in very recent evolutionary times, as attested also by in silico forward simulations under different demographic scenarios.In our study we adopted a hierarchical sequencing approach to reduce the genome complexity and consequently to maximize the accuracy of sequence assembly of C. arabica cultivated varieties but, due to its limited divergence from the commercially grown materials, we suggest exploiting introgression events from the diploid parental species into the allotetraploid species, as in the case of the famous Timor hybrid. The extremely recent origin and low genetic diversity of Coffea arabica make many of the traditionally used approaches in plant breeding, trait mapping and gene isolation less efficient and the development of novel alternative approaches a definitive must.Our results still reveal genetic differentiation between a group of ‘wild’ Ethiopian accessions and another group including other ‘wild’ Ethiopian accessions and most of cultivated accessions studied, including commercial germplasm belonging to the ‘Typica’ and/or ‘Bourbon’ lineages. The Ethiopian reservoir may be exploited for improvement of C. arabica ‘Bourbon Vermelho’. Seedlings were obtained by somatoclonal embryogenesis from cherries imported from a production area called Ahuachapan in El Salvador. Nine tissues/organs  were sampled from the same variety. Sequencing for subgenome assignment was performed using an accession of C. eugenioides derived from an illycaffè greenhouse in Rivignano, Udine, Italy.Sequencing for genome assembly was performed using an individual of in vitro with Bacteriophage Phi29 polymerase  with an isothermic reaction at 20 °C for 16 hours. BAC DNA was then purified with ethanol and sodium-acetate precipitation and resuspended in distilled water. BAC pools were quantified on a fluorometer  and visualized on a 0.8% agarose gel in 1x TBE buffer. Illumina libraries were constructed with the NexteraTM DNA Sample Preparation kit (New England Biolabs), following the manufacturer’s protocol.A BAC library of 175,872 BAC clones was constructed from genomic DNA by Lucigen Corporation (Lucigen Corporation). 36,864 BACs were randomly selected, inoculated into 96 384-well plates and grown at 37 °C for 22 hours in 2x LB medium supplemented with chloramphenicol antibiotic. The 384 bacterial cultures of each plate were mixed in a single tube. Each pool was subjected to alkaline lysis of bacterial cells and BAC vector was amplified Libraries were then purified with magnetic beads AMPure XP (Agencourt), quantified on a Caliper GX (Perkin Elmer), and sequenced using an Illumina HiSeq2000 (Illumina), generating 100-bp paired ends. Libraries from 12 pools were also sequenced with an Illumina MiSeq sequencer, generating 250-bp paired ends.C. arabica and from one accession of C. eugenioides using the Illumina TruSeq DNA Sample prep kit, according to the manufacturer’s protocol. C. arabica WGS was performed using an Illumina HiSeq2000 and generated 100-bp paired ends. C. eugenioides WGS was performed using an Illumina HiSeq2000 and generated 125-bp paired ends.Whole-Genome Shotgun libraries were constructed from genomic DNA of the same individual of C. arabica a 2-3 kbp mate-pair library was constructed using a Mate Pair Library v2 Sample Preparation kit following the Illumina protocol without gel electrophoresis size selection. The libraries were validated using a Bioanalyzer 2100 (Agilent), quantified using Qubit (Invitrogen) and then sequenced on Illumina HiSeq2000.For the same individual of 48 using default parameters and minimum read length of 50 bp. Adapters were removed with cutadapt49 using default parameters but -O 5 -n 2 -m 35. Cloning vector, Escherichia coli and chloroplast reads were filtered with erne-filter v1.4.348. Mate pairs were trimmed and filtered using the same procedure as above and then sorted into genuine mate pairs or paired-ends with internally developed Perl scripts based on the presence/absence of the Biotine signature.Reads were quality trimmed with erne-filter v1.4.313 with default parameters but k = 71, aligner=map, b = 1000000, p = 0.95, s = 500, n = 10. WGS mate pairs were used for scaffolding contigs within each BAC pool with SSPACE v3.050 with a minimum of 10 mate pair links to join adjacent contigs. Repetitive DNA was masked with RepeatMasker with the following parameters: -qq -nolow -norna -no_is -gff with repeat library derived from the C. canephora genome11. k-mer analysis was carried out with Jellyfish51 with parameters -c 3 -s 10 G and -m either 16 or 51. Effective sequencing depth (N) was estimated with k-mer analysis based on modal k-mer frequency (M), read length (L), k-mer length (K) and on the formula N = M*L/(L-K + 1)52; genome size was derived from sequencing yield divided by N. For C. canephora k-mer analysis, reads were downloaded from NCBI Sequence Read Archive experiments ERX294808, ERX294809, ERX294819, ERX294831, ERX294847, ERX294857, ERX294862, ERX294873, ERX294881, and ERX294885. C. eugenioides and C. canephora 51-mers were generated from Illumina reads using Jellyfish51 with parameters -m 51 -c 3 -s 10 G. Scaffolds were classified with internally developed Perl scripts as belonging to either the canephora or eugenioides subgenome if they either shared more 51-mers with C. canephora or shared more 51-mers with C. eugenioides, respectively. Scaffolds with less than 1000 available 51-mers, i.e. either very short or containing mostly repetitive DNA, or with similar numbers of shared 51-mers for both parental species (difference < 10%) remained unclassified.Each BAC pool was assembled independently with ABySS v1.3.7www.sigmaaldrich.com/). 1.5 µg of good quality RNA (R.I.N. > 7) was used as starting material for library preparation with the Illumina mRNA-Seq Sample Prep kit v2.0 following the manufacturer’s instructions (www.illumina.com/). The poly-A mRNA was fragmented for 1.5 minutes at 94 °C and all purification steps were performed using 1X Agencourt AMPure XP beads. Library quality and quantity were assessed using the Agilent Bioanalyzer 2100 High Sensitivity and Qubit DNA High Sensitivity (Invitrogen) as described more in detail in53. Libraries were pooled together, and the obtained pool checked on an Agilent Bioanalyzer 2100 in order to determine the molarity. Paired-end sequencing was performed on the Illumina HiSeq2500 (www.illumina.com/systems/sequencing-platforms/hiseq-2500.html) generating 125-base reads.RNAs were extracted using Spectrum Plant Total RNA Kit (SIGMA) following the manufacturer’s protocol . The transcripts were further assembled using PASA57, a eukaryotic genome annotation tool that exploits spliced alignments of expressed transcript sequences to automatically model gene structures.Trimmomaticde novo gene training and prediction. Five different programs were used for ab initio gene prediction: Augustus59, Snap60, Glimmer61 and GeneMark62. Intron coordinates derived from RNA-Seq read alignments were provided to GeneMark. Gene models generated by PASA were used to train Snap, Glimmer and Augustus. Briefly, the PASA alignment assemblies were used to automatically extract protein coding regions in order to generate a high-quality data set for training ab initio gene predictors. To discard the lowest quality gene models generated by PASA, from the training dataset, only complete genes and validated through a similarity search with blast against a dataset of C. canephora were considered. From the blast search, only proteins with a match with an e-value lower that 1e-30 and an alignment coverage higher than 90% were used to train the ab initio predictors.Gene prediction resulted integrating several sources of evidence: (i) RNA-seq data; (ii) nucleotide and protein alignments; (iii) C. canephora species were downloaded from NCBI and aligned to the reference genome using exonerate (https://www.ebi.ac.uk/about/vertebrate-genomics/software/exonerate). Only high-quality alignments were retained applying the following stringent criteria: 30% identity and 70% alignment coverage at the protein level, 50% identity and 70% alignment coverage at the nucleotide level.Nucleotide and protein sequences ranging from close to distantly related organisms belonging to eudycotyledon taxonomic rank, Gentianales order, Coffea genus and 57 in order to obtain a single gene model. EVidenceModeler (EVM) combines ab initio gene predictions and protein and transcript alignments into weighted consensus gene structures. To reduce false positive prediction and improve the overall gene prediction quality, several filters were applied:ab initio programs were considered only if they were confirmed by at least two different ab initio programs, if they were complete (with a start and a stop codon) and longer than 300 base pairs.Genes predicted only by e.g. proteins/RNA-seq) were considered if confirmed by at least two different types of evidence or by one external evidence and one ab initio gene predictor.Gene supported by external evidence (ab initio support (as per step 1) were further processed. Those supported by only one ab initio program were retained only if found in a database of Coffea protein sequences. While proteins with a sequence coverage match higher than 50% for both query and subject and an e-value lower than 1e-6 were recovered.Predicted genes with a low Previously collected evidence was combined for gene prediction using EVidenceModelerGene models passing these filters were further processed using PASA to add UTR regions and predict alternative splicing.63 with option -g set to 1 and for each gene locus we selected the longest transcripts isoform. CD-HIT was initially run setting the clustering percentage identity to 0.9. A Perl script was developed to parse the output in order to empirically identify a threshold that clustered as many genes as possible while keeping subgenome k-mer classified genes in proper clusters. The optimal clustering percentage identity was obtained at 0.9961  of C. arabica predicted genes were performed against the non-redundant protein database (NCBI). InterProscan564 was used to obtain the conserved protein domains and functional annotation. The databases used included PROSITE patterns, PRINTS, PFAM, PRODOM, SMART, TIGRFAM, and PANTHER. Gene Ontology and KEGG classifications were predicted running BLAST2GO 2.6.065 on the BLASTp and InterProscan outputs.BLASTp similarity searches , C. canephora (35) and C. eugenioides (10) were collected for genotypic analysis for this study. Because 45 of the Coffea arabica accessions failed to produce sufficient reads following GBS analysis they were removed from the study leaving a total of 736 Arabica accessions. The final Coffea arabica genotypes included in this study were represented as follows: 648 C. arabica accessions provided by CATIE and 88 C. arabica accessions collected in Yemen provided by Sana’a University. The C. canephora and C. eugenioides accessions were collected by IRD 66 and provided by CATIE or CIRAD. The list of all 781 accessions is provided in Dataset S2.An extensive number of accessions from In relation to this history, the Arabica accessions are coded using the following categories:Survey Ethiopia: 441 accessions from the FAO survey in Ethiopia (FAO 1964), 84 from the ORSTOM survey (1966) in Ethiopia (Guillaumet 1967) and 16 accessions from the ‘Lejeune survey’ or other surveys collected in Ethiopia before 1957. In Dataset S2 geographic coordinates and altitude for 359 accessions provided by botanists during the FAO and ORSTOM surveys is provided.Landrace cultivated: 49 accessions of Ethiopian cultivated populations that have been collected in Ethiopian farms in addition to the FAO and ORSTOM surveys. These surveys are less documented than the FAO and ORSTOM surveys.Survey Yemen: 93 accessions representing subspontaneous-derived accessions cultivated in Yemen and collected by Sana’a University (88 accessions) or by FAO (5 accessions planted in the CATIE collection). Those accessions can be considered as domesticated. For 28 accessions provided by Sana’a University, the altitude and the geographical coordinates are reported in Dataset S2.East Africa and Indian Old varieties: 45 accessions of varieties selected in the 30’s in India and East Africa.Typica/Bourbon cultivars: Seven accessions from the CATIE field GeneBank that conformed to the botanical varieties described by Krug and Carvalho (1951). In this study they represent the two widely cultivated varieties in Asia and Latin America for more than two centuries.http://www.adnid.fr/index-2-4A.html) at ADNid .Leaves were collected and lyophilized, and genomic DNA was extracted using the ADNid method (http://www.igd.cornell.edu/index.cfm/page/GBS.htm). Illumina template libraries were produced using the restriction enzyme PstI followed by single-end sequencing on a HiSeq2000 (Illumina) as previously described67.Genotyping by sequencing (GBS) was conducted at the Cornell University Institute for Genomic Diversity  at Cornell University. In total ~172 GB of DNA sequence data was obtained. Reads were initially processed to remove the individual barcodes corresponding to each accession and separated into individual fastq files for each accession using a custom python script. To avoid false positive SNP detection due to the allopolyploid nature of the C. arabica genome (i.e. polymorphism between the two subgenomes), two in silico reference sequences were generated, one for each of the two subgenomes. The canephora in silico reference was composed by (i) the assembled canephora subgenome, (ii) a full homoeologous complement of the assembled eugenioides subgenome, and (iii) the unassigned scaffolds. Similarly, the eugenioides in silico reference was composed by (i) the assembled eugenioides subgenome, (ii) a full homoeologous complement of the assembled canephora subgenome, and (iii) the unassigned scaffolds. In order to produce the full homoeologous complement of the assembled canephora subgenome, WGS reads of C. arabica ‘Bourbon Vermelho’ were aligned using BWA68 against the assembled canephora subgenome and the unassigned scaffolds. Then, homoeologous SNPs were called using GATK69 with default parameters and the alternative homoeologous reference was generated using GATK FastaAlternateReferenceMaker for sites with minimum depth 50 and allele frequency between 0.25 and 0.75. The same procedure was applied to obtain the full homoeologous complement of the assembled eugenioides subgenome.787 68 against the canephora and eugenioides in silico references in order to call allelic SNPs in the two subgenomes, respectively. For both artificial references, SNP calling was performed using Stacks v2.170. Only variant sites covered by at least 10 reads were retained. Heterozygous SNPs with an allele frequency lower than 0.25 or higher than 0.75 were discarded. Polymorphisms detected using the two artificial references were merged and only variant sites called in native scaffolds of each subgenome were retained for subsequent analyses. To obtain a dataset of SNPs for STRUCTURE and PC analyses, Stacks was run with the option –r  set to 0.75 and the option–max-clipped  set to the default value of 0.20, corresponding to a minimum stack length of 73 bp. Variants sites with seven or eight missing genotype calls out of the eight Bourbon/Typica accessions were interpreted as misalignments and filtered out.GBS reads were aligned using BWA-MEM v0.7.1071. A hierarchical study of the diversity has been conducted using a model-based clustering procedure with admixture as implemented in STRUCTURE v2.3.472. Runs were performed at values of k ranging from 1 to 13 with 10 replicates per K and a burn-in period of 75,000 and 75,000 MCMC repetitions. Plotting k vs ΔK indicated that the highest value was for 2 groups followed by 3 groups  with ape73, using provesti distance matrix calculated using poppr package74. The PCoA was plotted with ggplot2  set to 0.50 and the option–max-clipped  set to the value of 0.68, corresponding to a minimum stack length of 30 bp. For these analyses, sites in which all C. eugenioides accessions were homozygous reference and all C. canephora accessions were homozygous alternative, or vice versa, were interpreted as residual homoeologous SNPs and filtered out, as well as sites within missing data in C. eugenioides and C. canephora and >95% heterozygous calls in C. arabica. Nucleotide diversity and Tajima’s D were calculated for each group using the diversity.stats method included in the R package PopGenome75.Given the low level of diversity of the species and the high frequency of the Supplementary information.


Interactive, which offers significant improvements in power consumption, without reducing the performance of the application. These improvements depend on the load that the system has to support, so the results are evaluated against three different loads, from higher to lower, showing improvements ranging from 62% to 26%.Today, a wide range of developments and paradigms require the use of embedded systems characterized by restrictions on their computing capacity, consumption, cost, and network connection. The evolution of the Internet of Things (IoT) towards Industrial IoT (IIoT) or the Internet of Multimedia Things (IoMT), its impact within the 4.0 industry, the evolution of cloud computing towards edge or fog computing, also called near-sensor computing, or the increase in the use of embedded vision, are current examples of this trend. One of the most common methods of reducing energy consumption is the use of processor frequency scaling, based on a particular policy. The algorithms to define this policy are intended to obtain good responses to the workloads that occur in smarthphones. There has been no study that allows a correct definition of these algorithms for workloads such as those expected in the above scenarios. This paper presents a method to determine the operating parameters of the dynamic governor algorithm called  Reduce the vulnerability of data;Offer the possibility of customisation through specialisation of the hardware to reduce latency and energy consumption;Gain a huge reduction in bandwidth, avoiding the transmission of irrelevant information.The development of the IIoT  and ICPS  paradigms  introducIn this work, where trends to develop edge intelligence are analyzed, an Odroid XU4 with Linux and 2 GB of RAM is used. In  the authSoCs have evolved significantly in recent years, greatly influenced by the exponential increase in the smartphone market, to a point where today we have central processing units (CPUs) capable of running complete operating systems with their own graphical environment. These architectures have evolved from the original homogeneous architectures, to the current heterogeneous architectures, where several cores with different capacities and different energy requirements are mounted on the same chip. This property makes it the perfect choice to integrate IoMT systems into the Industry 4.0 paradigm, as it allows for enormous flexibility. The use of multicore systems also allows for improved energy efficiency based on a reduction in frequency achievable by spreading the work over several cores ,13. In tbig.LITTLE ARM architecture, where processes with less computational requirements are executed in the LITTLE cores. However, when increased computational capacity is needed, the process is executed in the big cores. Initially only the processor could internally decide on which core a process was running. In kernel switch scheduling (IKS), each pair of big.LITTLE cores was seen as a single virtual processor associated with a process, switching internally from one to the other according to these needs. More recently, global task scheduling (GTS) has become available [big or LITTLE, can execute tasks simultaneously. In [Ondemand is used but not interactive, and it is not specified which parameters have been used. In [The predominant architecture in this type of ARM processor-based system is the vailable , where eusly. In  the diffusly. In  the workusly. In , energy usly. In  where mausly. In  where a usly. In , based ously. In , based ously. In , Ondemanused. In , there iIn Ref.  there isThis paper does not propose a new governor that would be suitable for a multi-load and multi-application environment and that would require neural network training stages to assign statically the best working frequency for a given symmetric load. Instead, it aims to demonstrate how energy efficiency can be increased in devices by running IoMT applications, which have an asymmetric load by the very nature of the data they handle, using standard dynamic controllers, but setting the parameters of these controllers to achieve this efficiency. The paper presents a methodology to choose these parameters according to the load of the task, and its periodicity. Furthermore, instead of comparing only the energy improvements achieved, the results are explained through an analysis of the frequency histogram obtained with each method.minF), a maximum frequency (Fmax), and a range of frequencies available between these two, so that, depending on the policy applied by the governor, and the computer load required by the process, one particular frequency will be chosen as the working frequency (wf), a value that can change continuously during the execution of the task. These governors can apply a static or dynamic frequency assignment policy. As a static, there is the Powersave governor, where wf = minF, and the Performance governor, where wf = maxF. The dynamic governors will make the fw value go up and down through the available frequencies between minF and maxF with the objective of executing the tasks in a satisfactory time alongside a reduction in the energy consumption. Common examples of dynamic policies are the Ondemand, Conservative, and Interactive governors. These are naive algorithms [Ondemand, if the load on the core exceeds a certain threshold, wf = maxF will be set, and a gradual reduction of wf will be performed until wf = minF is reached, as the load on the core decreases. Conservative has a more gradual way of raising the wf value, and a progressive decrease when the load drops from the lower threshold. The Interactive governor was designed for interactive workloads that require a fast reaction in response to user actions. In addition, the procedure for adjusting the wf value is in the kernel with the highest priority, in order to avoid delays in response. This governor, has a series of parameters that allow the operation to be regulated according to the relationship between performance and energy to be achieved. In a big.LITTLE ARM architecture see  each typgorithms , which mwf so that it meets the requirements of applications while reducing consumption. Each load-sampling interval (TR) is checked to see if this load is above the GHL threshold. If it is, the frequency is raised to the value of Fhs. Once this frequency has been established, the system waits for a time determined by AHD, to re-evaluate the use, and if it continues to exceed the threshold, it increases the fw value again, which is already already above Fhs. value, and may reach Fmax. If the threshold is not exceeded, the system waits for MST, and if the load remains below the threshold, the value of fw will be reduced. Usually this governor is configured so that Fhs = maxF, as also indicated in [Algorithm 1 Interactive governor algorithmwf) between minF and maxF1: Set core working frequency (TRdo2: for every 3:  U ← current_CPU_Utilizationif (U > GHL) then4:  w = Fhsf5:   AHD6:   wait 7:   U ← current_CPU_Utilizationif (U > GHL) then8:   wf     increase end if9:   else10:  MST)11:   wait (if (U < GHL) then12:   wf     decrease end if13:   end if14:  end for15: In Algorithm 1 there is a description of the operation of the algorithm which aims to determine the value of cated in , which iw fw=FiiF is chosen which allows that even in the worst case, the execution time is less than the period T of the tasks. However, to satisfy the worst case, in a static governor, a high value, close to maxF, may have to be taken and thus the idle time is considerable, which will mean a significant waste of energy. In the case of using a dynamic governor, the parameters hsF and AHD will be modified in order to satisfy hsF in this paper is:That is, the frequency iF is chosen, which guarantees that the average time is less than the period. Although a value close to the average is used, this is for a determined value of wf. Choosing this value for hsF, if the computational load for processing an image is higher, the value of wf will change from hsF to higher values, meaning that the execution time will be reduced in comparison with the time that would be obtained with a static governor using wf = hsF′. In whichever case, with this selection, the deadline will not be met on occasions. Another possible relationship to reduce the possibility of the deadline not being met is: That is to say, the frequency hsF higher than with Equation (2) will be chosen, reducing the chances of missing the deadline at the cost of higher energy consumption. The other important parameter is the value for the time that this frequency will remain in use, before checking that the use is still high and therefore raising the frequency again.In this case a value of hsF, before increasing the value of wf towards maxF.In this way, we can be sure that we are working for a greater period of time with the value of An Odroid XU4 was used for the experiments, the main features of which can be seen in i and Ii+1 is exceeded . This same sequence was then used, but processed in three different ways, and henceforth in this work will be described as three different videos. In the first (vid1) an artificially high change threshold has been used, so it does not manage to detect vehicles and is, therefore, equivalent to a video sequence with very low activity. In the second (vid2), the threshold is set to an appropriate value, so all the images where there are changes are processed and movement of cars is detected, and the ROI of the vehicles found is also sent by WiFi. In this sequence, moments of higher activity are alternated with moments of less activity. The third (vid3) is a part of the same sequence with high activity, which is repeated several times and is thus considered to be a scene with high activity.maxF for the sequence Vid3. As can be seen, the value of T = 125 ms has been used in the sequence, so the value of AHD chosen is 120 ms.Performance and Ondemand governors can be seen in In the sequence denominated Vid2, the values obtained by the Interactive governor, with its default parameters (hsF = 2.0 GHz), and the values obtained for lower values of hsF while maintaining the rest of the default parameters. As can be seen in the table, the energy cost is higher than that obtained with the OnDemand governor, very close to that of the Performance governor, with similar temporal results. In the case of choosing a value of hsF in this configuration which would provide a power consumption similar to that of OnDemand, as with hsF = 800 MHz, the values of hsF′ = 1.6 GHz or F″hs = 1.0 GHz, where AHD = 120 ms. and the rest of parameters as conf2), and the values obtained for other hsF values. As can be seen, using the proposed parameters compared to the default ones, the power consumption using hsF′ is reduced by 41% compared to Performance and 8% compared to Ondemand, while the temporal values also show better performance compared to the Ondemand governor. Using hsF″ it consumption is reduced by 50% compared to Performance and 15% compared to Ondemand, maintaining a temporal behavior similar to Ondemand. The same values of hsF′ give better energy consumption and behaviour of conf2 compared to conf1.hsF = 2 GHz, (b) with hsF′ = 1.6 GHz and hsF″ = 800 MHz. The same frequencies are included with configuration 1 for comparison purposes. As can be seen, when using hsF = maxF in configuration 1  the frequency remains at its maximum value most of the time, being at its minF value, a very small part of the time. Using configuration 2 and the values hsF′ and hsF″, it is clear that most of the time the core will work with that frequency, although sometimes it is necessary to increase the frequency value, but without reaching maxF at any time. Using the same values of hsF′ and hsF″ but with configuration 1 (default), the results show how the core, even when remaining for some time in that hsF frequency, the lower value of AHD means that it passes more easily to higher frequencies, including maxF, so the consumption is higher but without providing a significant time difference. The reduction of the MST value can also be seen in lower use between hsF and minF increasing the time in minF, which also favours the energy reduction achieved with configuration 2.hsF and compared to OnDemand and Performance. As can be seen, only conf2 provides better energy performance compared to Ondemand, and this is achieved by using an hsF < maxF.Performance and Ondemand controllers are shown in In the Vid1 sequence, when there is no activity in the whole video sequence, the values obtained by the hsF = 2.0 GHz), and the values obtained for lower values of hsF, while maintain the rest of the default parameters. As can be seen in the table, the same results are obtained as in the previous case. The energy cost is higher than that obtained with the OnDemand governor, and very close to that of the Performance governor, with quite similar temporal results. In the case of using an hsF that provides similar energy consumption, as is the case of 1.6 GHz, better temporal behavior can be appreciated.interactive governor, with the parameters proposed in the previous section , and the values obtained for other hsF values. As can be seen, using the proposed parameters compared to the default parameters, the energy consumption using hsF′ is reduced by 62% compared to the Performance and 18% compared to the Ondemand. Although the average time is 33% worse than Ondemand, it is in no danger of failing to meet the deadline. Using hsF″ energy consumption is reduced by 43% compared to Performance and 5% compared to Ondemand, maintaining a temporal behavior somewhat better than Ondemand. In any case, the same values of hsF give better consumption and behavior of conf2 compared to conf1.hsF, while with conf1, this value is exceeded as there is also a high use in a shorter evaluation time, as is the case with conf1.hsF and compared to OnDemand and Performance. As can be seen, with no activity in the sequence, both conf1 and conf2 provide better energy performance compared to Ondemand, although in both cases it is also necessary that hsF < maxF.Performance and Ondemand controllers can be seen in In what is considered sequence 3, when there is a lot of activity throughout the video sequence, the values obtained by the Interactive governor, with its default parameters (hsF = 2.0 GHz), and the values obtained for lower values of hsF maintaining the rest of the default parameters. As can be seen in the table, the same results are obtained as in the previous case. The energy cost is higher than that obtained with the OnDemand governor, very close to that of the Performance governor, with quite similar temporal results.Interactive governor, with the parameters proposed in the previous section , and the values obtained for other hsF values. As can be seen, using the proposed parameters compared to the default parameters, the energy consumption using hsF′ is reduced by 26% compared to the Performance and 22% compared to the Ondemand. The average time is 21% worse, and furthermore, as expected, not all deadlines are met, although these are not fully met using either Ondemand or Performance. Using hsF″ energy consumption is reduced by 22% compared to Performance and by 12% compared to Ondemand, maintaining a slightly better time performance than Ondemand and meeting all deadlines. In this case, the same values of hsF give a better consumption with configuration 2, while the temporal behavior is very similar.maxF is reached, although the percentage of use is higher in conf1 compared to conf2, where hsF is still the most used frequency, although now this frequency is at times exceeded. hsF and compared to OnDemand and Performance. The figure shows that as there is a high activity in the sequence, the consumption using Ondemand is close to that of Performance. With this workload, both conf1 and conf2 can provide better energy performance compared to Ondemand, although in both cases it is also necessary that hsF < maxF. big.LITTLE or not, allow the field of use of these devices to be extended. Thus, with respect to a cloud computing solution using Performance, savings of 178% are achieved for vid1, 101% for vid2, and 21% for vid3. Thus, compared to a cloud computing solution, a high energy saving is achieved, a key aspect in this field, although it depends on the system load. As for the solution based on edge computing, the default configurations are designed for smartphones. The use of the Interactive governor allows different computing loads to be dealt with efficiently. If the parameters of this governor are also set taking into account the load with which they have to work at a given time in an application in the 4.0 industry, it is possible to significantly improve energy savings while maintaining or even improving the temporal response of the system. This is demonstrated by the differences between configuration 2 used with the interactive governor, and configuration 1 with this same governor, or using Performance or Ondemand. Comparing the proposed Interactive configuration with respect to Performance, which is the one used by default by Exynos_cpufreq (see Interactive configuration (conf2) with the default Interactive configuration (conf1), savings are achieved from 58% for low-activity sequences, to 31% for very high-activity sequences. The use of smart sensors in the field of industry, in particular in near sensor computing or fog computing, has great potential for use in the future. The requirements determined by industry 4.0 require the flexibility of the sensors so that they can be used for different types of tasks. Multicore architectures, whether freq see , savingsInteractive governor, so that the temporal requirements of the applications are maintained, improving significantly the energy consumption. This improvement makes an edge computing solution even more efficient than cloud computing. The use of these SoCs in industry 4.0 allows a high degree of flexibility; they could be used, depending on the moment, using only a LITTLE core in applications with very low computing requirements, to other applications, such as that shown in This paper presents a method to determine the parameters of the The parameter selection method shown is based on the experimental information obtained with a video sequence. As a future work, and with the aim of achieving a flexible and more autonomous and reconfigurable system, the authors aim to develop a workload analysis system so that it is possible to select not only the parameters of the governor, but also to choose which type of cores and how many cores to use to achieve the desired performance, thus increasing energy savings.


The objective of this study was to evaluate the genetic behavior of a population of Holstein cattle in response to the variation of environmental temperature by analyzing the effects of genotype by environment interaction (GEI) through reaction norms for the somatic cell score (SCS).Data was collected for 67,206 primiparous cows from the database of the Paraná Holstein Breeders Association in Brazil, with the aim of evaluating the temperature effect, considered as an environmental variable, distinguished under six gradients, with the variation range found being 17°C to 19.5°C, over the region. A reaction norm model was adopted utilizing the fourth order under the Legendre polynomials, using the mixed models of analysis by the restricted maximum likelihood method by the WOMBAT software. Additionally, the genetic behavior of the 15 most representative bulls was assessed, in response to the changes in the temperature gradient.A mean score of 2.66 and a heritability variation from 0.17 to 0.23 was found in the regional temperature increase. The correlation between the environmental gradients proved to be higher than 0.80. Distinctive genetic behaviors were observed according to the increase in regional temperature, with an observed increase of up to 0.258 in the breeding values of some animals, as well as a reduction in the breeding of up to 0.793, with occasional reclassifications being observed as the temperature increased.Non-relevant GEI for SCS were observed in Holstein cattle herds of southern Brazil. Thus, the inclusion of the temperature effect in the model of genetic evaluation of SCS for the southern Brazilian Holstein breed is not required. Mastitis is one of the main diseases affecting dairy herds, causing major losses in the milk production chain . It is rDespite the search for genetically superior animals regarding this trait being a reality, the advances are still small and obtained mainly by correlation with the somatic cell score (SCS) . AlthougAlthough environmental influences have been observed in the manifestation of the mentioned trait, they are not taken into account in the genetic analysis models applied in the southern Brazil (one of the main milk basis in the country), which can lead to biases in the genetic information and reduce the response to selection . Such a Reaction norms are a powerful and flexible tool for mod eling the effects of the GEI . From thThe objectives of this study were therefore: i) verify the existence of a GEI through reaction norm models using random regression for the SCS trait in animals of the Holstein breed according to the regional temperature; ii) estimate the genetic variance and the heritabilities of the SCS according to changes in the temperature gradient; and iii) analyze the genetic performance of the main bulls used in the region regarding the SCS in accordance with changes in the regional temperature gradient.2 +3.Using the database of official milk recording from the Paraná Holstein Breeders Association, Brazil (APCBRH), data on somatic cell count from 67,206 primiparous females born between 1990 and 2015, daughters of 936 distinct bulls, were recorded. The relationship matrix was composed of 92,637 animals belonging to 398 herds from 88 cities in southern Brazil. The somatic cell count were transformed to SCS to achieve normality and homogeneity of variance, following the formula: SCS = logFrom an a priori survey based on the methodology of Alvares et al , the aveThe statistical software SAS  was usedAmong the environmental gradients, herd connectivity was observed through the genetic presence of the bulls in at least three gradients. Since the animals were of unknown parentage, bulls that had been represented in less than three gradients or bulls that featured only once in the herd were removed from dataset. Finally, each environmental gradient contained included a minimum of 1,000 animals for analysis.A random regression model was adopted to analyze GEI through reaction norms while assuming the residual variance to be heterogeneous in as many as eight classes of variance. Lastly, the fourth class was used because it presented the best fit under the Legendre polynomials. These polynomials were recently selected to promote the improved convergence of data in orthogonal regressions, as seen in the work of Schaeffer .The reaction norms model, via random regression, is de scribed as follows:yij, phenotypic record for animal i, progeny of sire j; Tij, average temperature; φm(Tij), mth Legendre polynomial order; CGij, contemporary group effect; IPij, age at first calving as a covariate; βm average regression coefficient of order m ; αim random regression coefficient of order m for additive genetic effect of animal i; ɛij, error associated to variance class. The matrix representations are given as follows:where assuming that:y is the vector of observation; b is the vector of the fixed effects attributed to the contemporary group; u is the vector of random effects; e is the vector of the residual effects; X and Z are the incidence matrices for the fixed and random effects, respectively; Krn is the covariance matrix linked to the random effects for the model parameters of the reaction norms; A is the additive numerator relationship matrix; and R is the residual variance matrix.where The constituents of additive genetic variance and estimates of direct heritability apply to the different environmental gradients according to the following models:being,2t is the direct heritability for the trait linked to the temperature gradient t; 2et is the estimate of residual variance attributed to level t of the temperature gradient; σ2a is the genetic variance estimate of the intercept component; σ2b is the slope estimate of the variance components of the reaction norms; σa,b is the covariance estimate between the genetic effects of the intercept and slope; and t represents the temperature levels. Also, mixed models of analysis using the restricted maximum likelihood method were applied using WOMBAT software [where hsoftware . The breuij is the additive genetic value prediction of animal i in the environment j; αim is the random coefficient regression vector of additive genetic effects; øm is the i-esim Legendre polynomial associated to mth order; aij random effect associated to animal i in the environmental level j. A is the additive numerator relationship matrix. σ2gat is the additive genetic variance ascribed to level t of the temperature gradient.For the regression of bulls through the gradients, the ge netic value estimates at the t levels of the environmental gradient in the analysis of genetic behavior were given by the weighted average of the genetic value of the daughters of each bull at each temperature level. A subset of data with information from the bulls present in all environmental gradients was formed to present a more reliable representation of the genetic value in each temperature gradient. For these analyses, 15 sires with the highest number of daughters distributed by southern Brazil were considered. Finally, the GEI was considered statistically significant if the variance of the slope was significantly different from zero by using a one-tailed t-test with a significance level at 0.05, as demonstrated by Cardoso and Tempelman [The general descriptive mean and the mean by temperature gradient are presented in The breeding values of the 15 main bulls used in the south ern Brazil and their interaction with the advance of the environmental gradients are presented in Lower genetic differences were observed among the animals in the regions close to 19.5°C, demonstrating an approximation of the animal’s breeding values when temperature increases. Changes of specific positions occurred with some animals. Such as in the case of the animal E, which was in fifth position and went to the eighth position along with the bull J, who was in tenth position in the 17°C gradient. The greatest variations in the genetic value of the animals were found for the animals E, F, G, H, I, J, and K, the other bulls had greater stability of their genetic values when the environmental temperature increased.The means of SCS presented by the Holstein breed in southern Brazil were lower than those established by Brazilian  and inteAs can be seen, the producers more to the south of the evaluated region (lower temperatures) had the lowest SCS rates. This fact may be related to the existence of traditional dairy basins in these regions  with theThe heritabilities seem to be mostly in the low magni tudes, indicating greater environmental interferences in the manifestation of the trait. Such heritabilities are consistent with recent studies in Brazil  and otheWhen looking more closely at The correlations, shown in As can be seen in In these cases, the animals A, G, H, I, J, and O had the greatest variations in gene expression for the SCS. These variations in gene expression, and even the maintenance of performance according to the increase in temperature, are adaptive responses of the organism to the breeding environment  or even Despite the small reclassification in the sire ranking and the high genetic correlation observed, first indicating a non-relevant GEI for SCS, a slight change in the heritability estimates thru the gradients were verified. At this moment, the inclusion of the temperature effect in the model of genetic evaluation of SCS is not required, but a constant monitoring of a possible impact of GEI in this trait, for the southern Brazilian Holstein breed, can be recommended.


Plasmodium falciparum merozoite surface protein-3 (PfMSP-3) is a target of naturally acquired immunity against P. falciparum infection and is a promising vaccine candidate because of its critical role in the erythrocyte invasion of the parasite. Understanding the genetic diversity of pfmsp-3 is important for recognizing genetic nature and evolutionary aspect of the gene in the natural P. falciparum population and for designing an effective vaccine based on the antigen.P. falciparum-infected patients in Naung Cho and Pyin Oo Lwin, Myanmar, in 2015 were used in this study. The pfmsp-3 was amplified by polymerase chain reaction, cloned, and sequenced. Genetic polymorphism and natural selection of Myanmar pfmsp-3 were analysed using the programs DNASTAR, MEGA6, and DnaSP 5.10.00. Genetic diversity and natural selection of the global pfmsp-3 were also comparatively analysed.Blood samples collected from pfmsp-3 displayed 2 different alleles, 3D7 and K1. The 3D7 allelic type was predominant in the population, but genetic polymorphism was less diverse than for the K1 allelic type. Polymorphic characters in both allelic types were caused by amino acid substitutions, insertions, and deletions. Amino acid substitutions were mainly occurred at the alanine heptad repeat domains, whereas most insertions and deletions were found at the glutamate rich domain. Overall patterns of amino acid polymorphisms detected in Myanmar pfmsp-3 were similar in the global pfmsp-3 population, but novel amino acid changes were observed in Myanmar pfmsp-3 with low frequencies. Complicated patterns of natural selection and recombination events were predicted in the global pfmsp-3, which may act as major driving forces to maintain and generate genetic diversity of the global pfmsp-3 population.Myanmar pfmsp-3 revealed genetic polymorphisms, suggesting that the functional and structural consequences of the polymorphisms should be considered in designing a vaccine based on PfMSP-3. Further examination of genetic diversity of pfmsp-3 in the global P. falciparum population is necessary to gain in-depth insight for the population structure and evolutionary aspect of global pfmsp-3.Global  Plasmodium falciparum merozoite surface protein-3 (PfMSP-3) is a protein mainly expressed at the schizont stage of the parasite. This protein is initially synthesized as a 62 kDa precursor and then is subsequently processed into a mature protein with an approximate size of 44–48 kDa via removal of the N-terminal region in the parasitophorous vacuole [P. falciparum in vitro in the presence of blood monocytes [P. falciparum erythrocytic growth has been evaluated [ vacuole , 2. PfMS vacuole . Moreovevaluated , 8. GMZ2valuated –12. The P. falciparum are great hurdles to develop effective vaccines since they could generate a variant-specific immune response that is less effective against parasites with other genetic variants. Like other vaccine candidate antigens, the genetic diversity of pfmsp-3 was also reported in natural parasite populations [pfmsp-3 consists of 3 separated regions: the N-terminal region containing four alanine heptad repeats (AHR) having the AXXXAXXX motif, the glutamate rich domain, and the C-terminal region containing a leucine zipper motif [P. falciparum populations in several countries including Iran [pfmsp-3 in the natural P. falciparum population is important not only for evaluating the genetic nature of the vaccine candidate antigen, but also for advancing effective vaccine development.Genetic polymorphisms in vaccine candidate antigens of ulations –16. The er motif –20. The er motif . It has ing Iran , Thailaning Iran , 15, Campfmsp-3 in the natural P. falciparum population. In this study, the genetic diversity and natural selection of pfmsp-3 in Myanmar P. falciparum isolates were analysed. Comparative analysis of global pfmsp-3 was also performed to gain in-depth understanding of the genetic make-up of the gene in the global P. falciparum population.However, compared to other vaccine candidate antigens, fewer studies have been done to understand the genetic polymorphisms of P. falciparum infected symptomatic patients who live in villages located in Naung Cho and Pyin Oo Lwin, Myanmar in 2015  targeting 18S ribosomal RNA (rRNA) gene [Seventy-two blood samples were obtained from NA) gene . Finger-pfmsp-3 was amplified by a nested PCR method. The primers used in this study were designed as described previously [Ex Taq DNA polymerase  with proof- reading activity was used in all PCR amplification steps to minimize the nucleotide mis-incorporation. PCR products were resolved on a 1.2% agarose gel, and were visualized under ultraviolet (UV). Each PCR product was purified from the gel, and cloned into the T&A vector . Ligation mixture was transformed into Escherichia coli DH5α competent cells, and positive clones with appropriate insert were selected by colony PCR. The nucleotide sequence of cloned insert was analysed by automatic DNA sequencing with M13 forward and M13 reverse primers. Plasmids from at least two independent clones from each transformation mixture were sequenced in both directions to verify the sequence accuracy. The nucleotide sequences reported in this study have been deposited in the GenBank database under the accession numbers MN787600-MN787671.The full-length eviously . The thepfmsp-3 were analysed using EditSeq and SeqMan in the DNASTAR package . The pfmsp-3 sequences of 3D7 (XM_001347593) and K1 (U08851) were used as reference sequences. The value of singleton variable sites, parsimony informative sites, total number of mutations, segregating sites (S), average number pair-wise nucleotide difference (K), haplotype diversity (Hd), and nucleotide diversity (π) were calculated using DnaSP version 5.10.00 [P < 0.05) in order to test the null hypothesis of strict neutrality of pfmsp-3 in MEGA6 program [The nucleotide and deduced amino acid sequences of  5.10.00 . The π w program  using th program  with the program , and Fu  program  were per program . The Tajpfmsp-3 from different P. falciparum populations was analysed. The pfmsp-3 sequences included in this study were from Thailand (AM161544-AM161593), India (HM568669-HM568724), Kenya (KU527019-KU527058), and Nigeria (AM161594-AM161644). These sequences covered full-length or partial of pfmsp-3. Genetic polymorphism and tests of neutrality of each population were analysed or calculated using DNASTAR package, DnaSP version 5.10.00 [pfmsp-3 population to analyse the polymorphic patterns in the B cell epitopes using the WebLogo program (https://weblogo.berkeley.edu/logo.cgi).The genetic diversity of global  5.10.00  and MEGA 5.10.00  as descrpfmsp-3 were successfully amplified from Myanmar P. falciparum isolates. Sequence alignment analysis of the sequences suggested that they were classified into 2 allelic types, 3D7 type (n = 43) and K1 type (n = 29). For the 3D7 allelic types, 164 single nucleotide polymorphisms (SNPs) were identified at 87 polymorphic sites, in which 122 SNPs were non-synonymous mutations, resulting in amino acid substitutions at 49 positions. Four amino acid positions showed tri-morphic changes  and the others were di-morphic amino acid changes. The most predominant amino acid substitutions identified in Myanmar pfmsp-3 were L68S and D278E/M, which accounted for 90.7% and 58.1% in frequency, respectively. The other amino acid changes occurred at very low proportions. Amino acid changes at 25 positions  were novel ones that have not been reported previously. The glutamate rich domain of Myanmar pfmsp-3 was varied because of different repeat numbers of glutamate residues, ranging from 4 to 8 repeats. Deletions of E271 and/or E272 were identified in 12 distinct haplotypes and insertion of 2 additional glutamates was found in haplotype 26. Based on these polymorphic patterns, the 3D7 allelic types of Myanmar pfmsp-3 were further classified into 31 distinct haplotypes, in which haplotype 9 had the highest prevalence (23.3%)  were found in Thailand and Kenya pfmsp-3. The five amino acid substitutions  in the leucine zipper domain were detected only in Myanmar pfmsp-3. Polymorphic patterns of amino acid changes were more diverse and greater in global K1 allelic types  at position 79, 13 amino acids (ETEEEELEEKNEE) at position 280, and glutamate (E) at the position 298 were found in pfmsp-3 from Thailand, Kenya, and Nigeria. Deletion of glutamate (E) at position 297 was also identified in pfmsp-3 from Kenya and Nigeria. Meanwhile, the leucine zipper domain was well-conserved in global pfmsp-3. Only 5 minor amino acid changes  were uniquely identified in Myanmar pfmsp-3. Polymorphic patterns of the B-cell epitopes of 3D7 allelic types of global pfmsp-3 were analysed. The amino acid residues constructing the B-cell epitopes were tightly conserved in global pfmsp-3 allelic types  for 3D7 and K1 allelic types were 5.30 and 33.22, respectively. The 3D7 and K1 allelic types showed similar values of haplotype diversity , but nucleotide diversity (π) of K1 allelic types (0.0297 ± 0.0019) was greater than that for 3D7 allelic types (0.0050 ± 0.0006)  and K1 (− 0.016 ± 0.009), suggesting that both allelic types of Myanmar pfmsp-3 were affected by negative natural selection. The value of Tajima’s D for the 3D7 allelic types was negative , suggesting that 3D7 allelic types of Myanmar pfmsp-3 were under purifying selection. Meanwhile, the value was positive for the K1 allelic type , implying that the K1 type was under balancing selection  for the 3D7 allelic types of Myanmar  1 Table . Potenti 1 Table . The LD P. falciparum population are less understood that are other major vaccine candidate antigens, such as MSP-1, MSP-2, apical membrane antigen-1 (AMA-1), and circumsporozoite surface protein (CSP) of the parasite. In this study, genetic diversity and natural selection of Myanmar pfmsp-3 were analysed. Two allelic types of pfmsp-3, 3D7 and K1, were identified in Myanmar pfmsp-3 with the predominance of the 3D7 allelic type (59.7%). This is consistent with other reports that 3D7 allelic types are more prevalent in Peru [pfmsp-3 from Iran and Africa countries with a very low frequency [pfmsp-3. The lack of a recombinant allelic type may result from the large sequence difference between the two dimorphic alleles, which impedes recombination during meiosis. Otherwise, the sequence dimorphism among pfmsp-3 may be strictly maintained in the population by balancing selection [pfmsp-3 is likely to occur, considering the Rm value in each allelic type. Particularly, the K1 allelic type of Myanmar pfmsp-3 revealed many recombination events, indicating that active intragenic recombination is occurring in the population.PfMSP-3 is one of the leading vaccine candidates for malaria vaccine development, but its genetic makeup and evolutionary aspect in the global  in Peru , East Re in Peru , and the in Peru . Meanwhirequency , 16, waselection , 29. Howpfmsp-3 revealed polymorphic characteristics caused by amino acid substitutions, insertions, and deletions. Amino acid substitutions mainly occurred at the AHR domain in both allelic types of Myanmar pfmsp-3. Meanwhile, insertions and deletions were found at the glutamate rich domain. The major amino acid substitutions and insertions/deletions found in both allelic types of Myanmar pfmsp-3 were shared by global pfmsp-3, but their frequencies differed by geographical origin. Interestingly, novel amino acid changes that were not reported previously for either allelic type of Myanmar pfmsp-3, which renders genetic diversity of Myanmar pfmsp-3 more complex; 31 and 25 haplotypes for the 3D7 and K1 allelic types, respectively. Although incidence of malaria has been remarkably decreased in Myanmar in recent years [P. falciparum population. Regardless of the declining population in recent years, substantial levels of genetic heterogeneities in pfmsp-1, pfmsp-2, pfama-1, and pfcsp have been reported in the Myanmar P. falciparum population [Both 3D7 and K1 allelic types of Myanmar nt years , it seempulation . The reapfmsp-3 from each country, the overall patterns of amino acid polymorphisms were similar in the global pfmsp-3 population. Major amino acid changes and insertions/deletions found in both 3D7 and K1 allelic types were observed at the AHR and glutamate rich domains. The repeats of the AXXAXXX motif, which plays a role in maintaining and forming an α-helical secondary structure of PfMSP-3 [pfmsp-3 regardless of diversity within and flanking the ARH. The B-cell epitopes of 3D7 allelic types were also well conserved in the global pfmsp-3 population. The N-terminal region of pfmsp-3 including the B-cell epitopes is a target of naturally acquired immunity. In particular, the regions corresponding to amino acids 21 to 238 not only is an important immunogen to produce a protective immune response but also is involved in the interaction with PfMSP-1 [pfmsp-3 also suggests a critical role of the N-terminal region as a target of opsonizing antibodies. Therefore, the N-terminal region of pfmsp-3 may represent an attractive candidate for formulation of a PfMSP-3-based vaccine. Meanwhile, the leucine zipper domain was relatively well conserved in global pfmsp-3. The limited polymorphic pattern of the C-terminal region, especially in the leucine zipper domain, may result from its crucial function in the formation of protein oligomerization [pfmsp-3 plays an essential function in the invasion process of merozoite by mediating specific binding with erythrocytes [Despite different rates of amino acid changes and insertions/deletions in  PfMSP-3 , were hi PfMSP-1 . The prerization . Moreovehrocytes .pfmsp-3 were negative, implying that negative selection might act in the gene. Meanwhile, the values of Tajima’s D and Fu and Li’s D and F revealed complicated patterns that were different by country. These suggest that a complicated natural selection may act on 3D7 allelic types of the global pfmsp-3, in which either positive selection or purifying selection might have occurred in the population, depending on the geographical origin. As expected, overall nucleotide diversity in K1 allelic types was greater than that in 3D7 allelic types in the global isolates. The positive values of Tajima’s D indicated that K1 allelic types of global pfmsp-3 evolved under balancing selection. Amino acid substitutions, insertion or deletions may be the main pressure to generate genetic diversity of the allelic types. High recombination parameters also support the notion that recombination may be one of a force contributing to generate genetic diversity of K1 allelic types of global pfmsp-3.The dN–dS values for 3D7 allelic types of global pfmsp-3 showed genetic polymorphisms. Two different alleles, 3D7 and K1, were detected in Myanmar pfmsp-3, with a higher prevalence of 3D7 allelic types. Overall patterns of nucleotide diversity and distributions of amino acid changes and insertions/deletions found in Myanmar pfmsp-3 were similar to those from global pfmsp-3, even though minute regional differences were also identified between and among each population. Complicated patterns of natural selection and recombination events were predicted in the global pfmsp-3, which may act as major driving forces to maintain and generate genetic diversity of the global pfmsp-3 population. These results suggest that the functional consequences of the polymorphism should be considered for development of a vaccine based on PfMSP-3. This study provides in-depth insight into the genetic nature and population structure of global pfmsp-3. Considering that rather few global pfmsp-3 sequences were currently available, further examination of the genetic diversity and evolutionary aspect of pfmsp-3 with more global pfmsp-3 sequences would be necessary to better understand the genetic make-up of pfmsp-3 in the natural P. falciparum population.Myanmar Additional file 1: Fig. S1. Map of study site. The blood samples were collected from patients who infected P. falciparum. Community-based survey was conducted in 3 villages in Pyin Oo Lwin, and Naung Cho, Upper Myanmar in 2015.