Background: Date palm (Phoenix dactylifera L.) is a cultivated woody plant with agricultural and economic importance in many countries around the world. With the advantages of next generation sequencing technologies, genome sequences for many date palm cultivars have been released recently. Short sequence repeat (SSR) and single nucleotide polymorphism (SNP) can be identified from these genomic data, and have been proven to be very useful biomarkers in plant genome analysis and breeding.Results: Here, we first improved the date palm genome assembly using 130X of HiSeq data generated in our lab. Then 246,445 SSRs  were annotated in this genome assembly; among the SSRs, mononucleotide SSRs (58.92%) were the most abundant, followed by di- (29.92%), tri- (8.14%), tetra- (2.47%), penta- (0.36%), and hexa-nucleotide SSRs (0.19%). The high-quality PCR primer pairs were designed for most  SSRs. We also annotated 6,375,806 SNPs with raw read depth≥3 in 90% cultivars. To further reduce false positive SNPs, we only kept 5,572,650  SNPs with at least 20% cultivars support for downstream analyses. The high-quality PCR primer pairs were also obtained for 4,177,778 (65.53%) SNPs. We reconstructed the phylogenetic relationships among the 62 cultivars using these variants and found that they can be divided into three clusters, namely North Africa, Egypt – Sudan, and Middle East – South Asian, with Egypt – Sudan being the admixture of North Africa and Middle East – South Asian cultivars; we further confirmed these clusters using principal component analysis. Moreover, 34,346 SSRs and 4,177,778 SNPs with PCR primers were assigned to shared cultivars for cultivar classification and diversity analysis. All these SSRs, SNPs and their classification are available in our database, and can be used for cultivar identification, comparison, and molecular breeding.Conclusion:DRDB is a comprehensive genomic resource database of date palm. It can serve as a bioinformatics platform for date palm genomics, genetics, and molecular breeding. DRDB is freely available at http://drdb.big.ac.cn/home. Phoenix dactylifera L.) is a widely cultivated plant species with agricultural and economic importance in the world. It is a dioecious plant in palm family Arecaceae with long life cycle, long period of juvenility and various of cultivars . We included in DRDB in total of 6,375,806 SNPs and 246,445 SSRs from 62 cultivars. The main purpose of DRDB is to help the researchers/breeders to distinguish the plethora of date palm cultivars by using well-selected polymorphic markers (SNPs or SSRs). With DRDB, users can search for SNPs or SSRs of interests, and easily find SNP/SSR markers that are unique to user-selected cultivars. In addition, we also provided detailed annotations for the SNPs and SSRs. With DRDB, we not only expanded and enhanced the date palm cultivars data contents, but also incorporated useful tools to mine the data. To our knowledge, DRDB is the first comprehensive genetic variation database for date palm.To better understand the genetic basis of different date palm cultivars, it is necessary to have a high-quality genome assembly and get insight into genome variations (SSRs and SNPs). Here, based on 130X HiSeq data produced by our lab, we first updated the date palm genome assembly. Then, we annotated SSRs and other types of sequence variants among 62 cultivars. To facilitate the use of these data, we developed a web-based date palm genome database  cultivar in Al-Hssa Oasis  were collected, washed with double distilled water, and frozen immediately in a liquid nitrogen container. After transported to the laboratory, these samples were stored in -80°C freezers until use.Fresh green leaves from an adult date palm plant of Genomic DNA was isolated from 50 g fresh leaves according to a CTAB-based method as before . BrieflyWe obtained ∼130X HiSeq data using Illumina HiSeq 2000 platform. The raw data was filtered using an in-house Perl script firstly. Then, SOAPdenovo2 (v2.04) was used to build a new genome assembly based on the newly produced HiSeq data with the option “-k 63” and other default parameters . Next, tTable 1). The re-sequencing data of 62 date palm cultivars produced by The updated genome assembly was used for SSR identification by MISA (v1.0)   was used to permute the clusters generated from independent STRUCTURE runs  . The gapURE runs .DRDB contained both SNPs and SSRs data from 62 date palm cultivars. The website was built on LAMP stack . MySQL was used for data storage on the server side. The front-end interface was implemented with Bootstrap and Angular.The Table 2, comparing the new version (referred as to version 2 below) with the old version (referred as to version 1 below), the number of scaffolds and N bases were reduced to 60.87 and 56.57%, respectively. At contig level, the quality of version 2 was significantly improved; for example, N50 was increased threefold to 34.35 kb, and the number of contigs was decreased ∼50% to 69,963 (Table 2). Our results suggested that the new genome assembly could not be further improved by adding more shot-read data with limited insert size (≤8 kb).We re-assembled the palm genome by incorporating newly sequenced HiSeq data (∼130X) produced in our lab and obtained a new genome assembly of 602,484,697 bp in length. As summarized in Figure 1) and 26,148 (10.61%) were imperfect SSRs. The imperfect SSRs in date palm are significantly less than those in chickpea (17%) (Elaeis guineensis (10.87%), and more than those in Oryza sativa (9.60%), Aegilops tauschii (7.53%), Zea mays (5.72%), and Brachypodium distachyon (5.47%). Mononucleotide SSRs and dinucleotide SSRs are the most abundant types ; among the dinucleotide SSRs, AG/TC (50.50%) is the most abundant, followed by AT/TA (35.50%), AC/TG (13.25%), and CG/GC (0.75%). Trinucleotide SSRs account for 8.14% of the total SSRs, among which AAG/TTC (30.81%) is the most abundant, followed by AAT/TTA (23.20%) and AGG/TCC (17.97%). Using Primer 3, we were able to design high-quality primer pairs for 174,497 (70.81%) SSRs.Using the updated date palm genome sequence, we identified 246,445 SSRs. Among them, 31,544 (12.80%) were compound SSRs (ea (17%)  and lentea (17%) , similarFor the published SSRs that we examined, most of them were covered by our dataset. For example, the SSRs that we inferred here contained 9 of 16 ones proposed previously We identified 6,375,806 SNPs (raw read depth≥3 in 90% cultivars) among 62 date palm cultivars. To reduce false positives, we only kept those  found in more than 20% cultivars for downstream analysis. We designed high-quality PCR primers for 4,177,778 (65.53%) SNPs.These genetic variants and pre-designed PCR primers could be a valuable resource for researchers for genetic and breeding studies.k = 1–7 for SSRs and k = 1–6 for SNPs; we run STRUCTURE HARVESTER program to determine the best k-values for SSRs (k = 4) and SNPs (k = 3)  . We further confirmed the clustering using PCA using all SNPs .To elucidate the population genetic structure, we selected 34,346 SSRs with length polymorphism and 57,310 SNPs in the largest scaffold of data palm genome for further analysis with STRUCTURE. We run STRUCTURE with gure S1) . Our resDRDB with a user-friendly web interface, incorporated visualization tools for genomic features and provided powerful searching functionality. DRDB comes with several pages including Home, Browse, Marker selection, SNP annotation, Download, and Documentation. Below we introduce selected pages in details .We designed Figure 5), which lists all available SNPs and SSRs for user-selected cultivars. Users can search for SNPs and SSRs they are interested by changing different parameters  .In browse page, the phylogenetic tree that was derived from the SNP data is shown; the topology of this tree suggests that there are at least three sub-groups of date palm cultivars, each features distinct geographic locations: Middle East, Egypt Sudan, and North Africa. Users can click on any cultivar they interested in, and view a list of its available SNPs and SSRs in a new page , which contains also the allele frequency and detailed information of selected markers, including “position, ref, alt, dp, qual” in SNP marker or “SSR_type, size, type, cov” in SSR marker .In marker selection page, we divided SNP and SSR markers into three levels . Users can select any combination of maker types (SNP or SSR) and levels  they are interested, and view the results in a new page  comparing with the previous genome assembly. Large (≥20 kb) insert size sequencing data, genetic map and physical map are needed for improving genome assembly in the future.Date palm has unique genetic diversity due to long-lived life cycle, vegetative propagation, and complex origin. Study data palm genetic diversity and classification is an important research aspect. In this study, based on an improved genome assembly, we identified 246,445 SSRs and 6,375,806 SNPs in 62 cultivars and designed high-quality PCR primers for most of variations (70.81% in SSRs and 65.53% in SNPs). These genetic variants and pre-designed PCR primers will be a valuable resource for researchers to perform genetic and breeding studies.The origin of date palm is controversial because date palm cultivation spread out many countries starting in ancient times. Based on SSRs and SNPs, we elucidated the population genetic structure of date palm and the results showed that date palm can be divided into three genetically differentiated clusters, North Africa, Egypt – Sudan and Middle East – South Asian, with Egypt – Sudan being the admixture of North Africa and Middle East – South Asian cultivars.To facilitate the use of our data, we developed DRDB for distinguishing the different sub-types of date palms and mining the genetic variation of interest. DRDB provides visualization tools for genomic features and powerful searching functionality. Users can download all these data from download page.In summary, DRDB provided an updated date palm genome assembly and enabled genetic variation searching for 62 date palm cultivars rapidly and conveniently, which sets the stage for further genetic and breeding studies.ZH, CZ, and WL contributed equally to this work. SH, W-HC, and HA led the research. ZH and CZ constructed the database. WL, QL, and TW analyzed the data. ZH, W-HC, and WL wrote and revised the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


SNP rs798827 is within strong linkage disequilibrium (r2 = 1) to rs58163073, where rs58163073 [T] allele increases the binding affinity of SOX2 and allele [TA] decreases it. In our analysis, SOX2 silencing downregulates VDAC3 in two LSCC cell lines. Chromatin conformation capturing data indicates that this SNP is located within the same Topologically Associating Domain (TAD) of VDAC3, further suggesting SOX2's role in the regulation of VDAC3 through the binding of rs58163073. By first subgrouping patients based on SOX2 activity, we made more relevant eQTL discoveries and our analysis can be applied to other diseases.Lung squamous cell carcinoma (LSCC) is a genomically complex malignancy with no effective treatments. Recent studies have found a large number of DNA alterations such as SOX2 amplification in LSCC patients. As a stem cell transcription factor, SOX2 is important for the maintenance of pluripotent cells and may play a role in cancer. To study the downstream mechanisms of SOX2, we employed expression quantitative trait loci (eQTLs) technology to investigate how the presence of SOX2 affects the expression of target genes. We discovered unique eQTLs, such as rs798827-VDAC3 (FDR  Lung cancer is the leading cause of cancer death in the United States with approximately 158,000 deaths in 2016 , 4. The in vivo upon loss of Pten and Cdkn2ab  allele of SNP rs58163073 increased the position weight matrix score for SOX2 and the [TA] allele decreased it. This SNP directly alter the binding sequence of SOX2 and the [T] allele increased its binding affinity.Our cell line and ChIP-seq analysis further suggests that SOX2 regulates VDAC3. When SOX2 was silenced in two LSCC cell lines, the expression of VDAC3 was also downregulated. In addition, SOX2 ChIP-seq peaks show SOX2 binding in the promoter region of VDAC3. SNP rs58163073 and VDAC3 are also located within the same TAD in lung tissues, normal lung, and lung cancer cell lines. VDAC3 is the least investigated isoform of voltage-dependent anion channels. They are localized in the mitochondrial outer members and are pore-forming structures that control the exchange of metabolites between the mitochondria and cytoplasm . They alFurther analysis shows that Black or African American patients have a higher MAF than those of White or Asian patients and patients with MAF had tumors located more predominantly on the right lungs. Collectively, these analyses support the notion that the SNP variant rs58163073 affects the binding of SOX2, which in turn affects SOX2's modulation of target genes such as VDAC3 Figure . This diPatient gene expression, copy number variation, methylation, and SNP data were collected from The Cancer Genome Atlas (TCGA) database. Specifically, Illumina HiSeq RNAseqv2 was used for gene expression data, Genome Wide SNP 6.0 was used for both copy number variation and SNP genotype data, and Human Methylation 450 bioassay data set was used for methylation data. A total number of 366 LSCC patients had all three datatypes available.http://www.bios.unc.edu/research/genomic_software/Matrix_eQTL/. Output threshold p-values were set at 0.05. Local eQTLs (or cis eQTLs) were set at the default distance of 1 million base pairs of each other.Expression quantitative trait loci (eQTL) analysis was conducted with Matrix eQTL: Ultra-fast eQTL analysis via large matrix operations by Andrey Shabalin . SoftwarSOX2 silencing experimental data was obtained from NCBI GSE48871 . Two LSCr2 > 0.8 was used to query variants. The 16 eQTLs were within strong LD to 263 SNPs. HaploRegv4.1 also contained information on regulatory motif changes. Only the SNP variants that overlapped the binding motif of SOX2 and changed the position weight matrix (PWM) score were considered. Under these conditions, only seven unique LD SNPs are identified.LD SNPs were explored using HaploRegv4.1 hosted by Broad Institute . The datSOX2 ChIP-seq data was obtained from NCBI- GSE46837 . A LSCC et al. (2014) [et al. (2016) [Hi-C data was obtained and visualized on 3D Genome Browser . IMR90 H. (2014) , A549 ce. (2014) , 60, and


EcoR I- Mse I was chosen as the optimal combination for the chicken genome. We firstly proposed that two parameters, optimal read-count point (ORP) and saturated read-count point (SRP), could be utilized to determine the optimal sequencing volume. A total of 291,772 high-density SNPs from 824 animals were identified. By validation using the SNP chip, we found that the consistency between ddGBS data and the SNP chip is over 99%. The approach that we developed in chickens, which is high-quality, high-density, cost-effective , and time-saving (within 48 h), will have broad applications in animal breeding programs.High-density single nucleotide polymorphism (SNP) markers are crucial to improve the resolution and accuracy of genome-wide association study (GWAS) and genomic selection (GS). Numerous approaches, including whole genome sequencing, genome sampling sequencing, and SNP chips are able to discover or genotype markers at different densities and costs. Achieving an optimal balance between sequencing resolution and budgets, especially in large-scale population genetics research, constitutes a major challenge. Here, we performed improved double-enzyme digestion genotyping by sequencing (ddGBS) on chicken. We evaluated eight double-enzyme digestion combinations, and  Genetic markers, as material for genetic research, have evolved from early restriction fragment length polymorphisms (RFLPs), amplified fragment length polymorphisms (AFLPs), and simple sequence repeats (SSRs) to currently widely-used SNP markers. Tremendous advances in genome-wide genotyping approaches have revolutionized the fields of population genetics and molecular breeding analysis . Many diFor research on population genetics, genotyping via whole genome sequencing is currently prohibitively expensive and technically unnecessary . SNP chiAlu I, Hind III, Ava II, Pst I, respectively) was used for preparing sequencing libraries, under the guidance of the choosing of enzyme by either in silico digestion or extant literature [Regarding chickens, RRGS approaches are widely employed. Kerstens et al. investigated genome-wide structure variations (SVs) by constructing reduced representation libraries (RRLs) of the chicken genome . They idterature ,21,22. Hterature ,22. A meterature ,23. HoweThe required SNP marker density was determined by the extent of linkage disequilibrium (LD) in the experimental population. Previous studies have shown that the extent of LD varied significantly across different chicken breeds –26. GeneEcoR I- Mse I combination was most suitable for chicken-GBS analysis. We proposed to use two parameters, optimal read-count point (ORP) and saturated read-count point (SRP), to determine the optimal sequencing volume. With an average sequencing depth of 10×, approximately 300 K SNP markers could be discovered with the EcoR I- Mse I combination.In this paper, we systematically evaluated the effects of various restriction enzymes and their combinations on the chicken genome. A nine-generation advanced intercross population was used to examine the ddGBS output. Our results showed that the Many RRGS adopted low-depth sequencing and imputation strategies. The common problem of these methods is high error rates in distinguishing heterozygous and homozygous individuals ,30. In tAll methods were carried out in accordance with relevant guidelines and regulations. All experimental protocols were approved by the Animal Welfare Committee of Agro-biotechnology of China Agricultural University. All animals used in this study were cared for and experimented on according to the requirements of the Animal Welfare Committee of Agro-biotechnology of China Agricultural University with the approval SKLAB-2014-06-07.2 cross has been described in detail by Sheng et al. [2 generation, the population was bred by random mating. In total, a set of animal material, consisting of 31 F0 individuals, 191 F8 animals, and 602 F9 progeny, was selected. DNA was extracted from EDTA-anticoagulated blood using the Qiagen DNeasy Blood and Tissue Kit according to the manufacturer’s instructions .We aim to assess ddGBS performance in a population with a low level of LD. A nine-generation advanced intercross population was established from two divergent chicken lines, High Quality chicken Line A (HQLA), a broiler line bred by Guangdong Wiz Agricultural Science and Technology, Co. , and Huiyang Beard chicken (HB), a native Chinese meat-type breed. The F0—Fg et al. . After Fin silico simulation and empirical evidence were considered in choosing the proper enzyme for the digestion of chicken genome. We employed seven single-enzyme digestions  and eight double-enzyme digestions  in our experiment. In silico analysis were conducted with an in-house Perl script. The size distribution of enzyme digestion fragments was reported using R software. Enzyme digestion experiments for all enzyme digestion combinations were performed according to the enzyme manufacturer’s protocol , and the digesting time for each combination was either 2 h or 12 h.In this study, both 0 generation. All DNA samples were diluted to 50 ng/μL, and 200 ng DNA was used for each digestion of the eight double-enzyme combinations according to the enzyme manufacturer’s instructions. We designed 24 barcode adapters : 0.8× and 1.3× sample volume of Agencourt® AMPure® XP Reagent can remove most of the short fragments (< 300 bp) and long fragments (> 650 bp), respectively. Detailed library preparation procedures are provided in We employed double-digest genotyping by sequencing (ddGBS) on three samples from the Fbination . The bardepth), the number of SNPs, and the distribution uniformity of SNPs across the chromosomes. We also subsampled reads of each individual in different proportions , and evaluated the “optimal read-count point (ORP)” and the “saturated read-count point (SRP)” parameters for cost optimization. A detailed definition of the above technical terms was described in the “Terminology” section.We evaluated each double-enzyme digestion strategy based on the enzyme digestion fragment size, the fragment consistency index (FCI), the coefficient of variation of sequencing depth (per fragment) across three samples  in 20 μL volume containing 4 μL DNA (200 ng), 1× CutSmart® Buffer, 5U EcoR I, and 5U Mse I. The enzymes were then inactivated by heating at 65°C for 20 min, and the samples were cooled to 4°C. The barcode adaptor (EcoR-BA) binds to the EcoR I overhang, and the common adaptor (Mse-CA) matches the Mse I overhang. The 96 indexes at the 3’ end of the barcode adaptors were designed by the GBS Barcode Generator (http://www.deenabio.com/) and modified to allow for Illumina NextSeq500 sequencer  . Agencourt® AMPure® beads  were used for DNA fragment purification and size-selection. The PCR amplification reaction system contained 10 ng purified products, 50 μL Platinum® PCR SuperMix High Fidelity , and 25 pmol primers  was determined by Qubit2.0 Fluorometer  and Agilent 2100 Bioanalyzer , respectively.All DNA concentrations were normalized to 50 ng/μL. Samples were digested for 12 h at 37°C with  primers . The amphttp://www.bioinformatics.babraham.ac.uk/projects/fastqc/). We used TASSEL GBS analysis pipeline (version 4.0) [8-F9 family relationships. To annotate mutations from the GBS output, we used the SNPEff program [http://www.ensembl.org/info/data/ftp/index.html). The Circos software package (http://circos.ca/) [2) against the distance between the SNPs. To visualize the LD pattern, the r2 values were plotted against the pair-wise SNP distances.All sequencing experiments were performed on the Illumina Nextseq500 Sequencer at the State Key Laboratory for Agro-biotechnology, China Agricultural University. BCL files as primary sequencing output were converted into FASTQ files using bcl2fastq2 conversion software (version 2.16.0). During the conversion step, we also masked and trimmed the sequencing adapter . After tion 4.0) ,33, in wion 4.0) . All SNPion 4.0)  accordinion 4.0)  with the program , with thcos.ca/)  was utildepth is calculated as the mean of sequencing depth (per fragment) across three samples divided by the standard deviation (SD). The SNP density is defined as SNP number divided by chromosome length. The CVSNP density is calculated as the mean of SNP density (per chromosome) divided by the standard deviation (SD).A “good barcode read” is a sequence read with a perfect match to one of the barcodes provided in a barcode file. A “tag” refers to a unique sequence (excluding the barcode) from one or more “good barcode reads”. A “fragment” is defined as a set of tags that align to the exact same genomic position and strand. The number of tags and fragments is counted by the output file of the TASSEL software . The fraThe sequencing cost per fragment unit is calculated by total sequencing cost against fragment counts. The optimal read-count point (ORP) is defined as the minimum sequencing cost per fragment unit. We also defined the saturated read-count point (SRP) as the minimum good barcode reads when reaching the maximum fragment counts.in silico digestion, for every combination the majority of the predicted fragments were smaller than 500 bp (Pst I- ApeK I and HinP1 I- ApeK I combinations produced a high proportion of short fragments (< 100 bp). Although the size-selection step could theoretically filter out short fragments, it is difficult to remove them completely in practice. Specifically, too many short fragments will lower the quality of library construction and subsequent sequencing. In addition, by comparing the results of three methylation-sensitive enzymes , we noticed that HinP1 I (G/CGC) could not completely digest the chicken genomic DNA in 12 h, and the ApeK I (G/CWGC) digestion products exhibited a few discrete bands (EcoR I (G/AATTC) digestion product were appropriate (100 bp—1000 bp) and evenly distributed without discrete bands.We performed a series of assessments for enzyme selection. The first parameter tested was fragment size. According to the predicted results from the n 500 bp . In extrte bands . By contdepth), the number of SNPs, and the distribution uniformity of SNPs across chromosomes. We prepared and sequenced 24 libraries of the eight double-enzyme digestions .For a more accurate estimation, we carried out direct sequencing after digestion. We presented another four parameters, including the fragment consistency index (FCI), the coefficient of variation of sequencing depth (per fragment) across three samples ) followed shortly after by Bgl II—ApeK I (0.44±0.43 (SD)). The highest mean CVdepth across three individuals occurred in HinP1 I—ApeK I (0.82±0.51 (SD)) followed by HinP1 I—Mse I (0.77±0.51 (SD)).The consistency of sequencing depth (per fragment) across samples is also important because it is related to genotyping accuracy. We defined the CVPst I—Mse I) would increase sequencing cost, while too few (such as EcoR I—Msp I) would lower the resolution (SNP density) across different chromosomes is shown in EcoR I-Mse I and Bgl II-ApeK I was more evenly distributed across chromosomes with a CVSNP density of 0.19 than other combinations. In contrast, the highest CVSNP density was found in Pst I-Mse I (0.60) followed by HinP1 I-ApeK I (0.59). Overall, the parameters among selected combinations were summarized in EcoR I- Mse I digestion was the optimal combination for the chicken ddGBS.The number of SNPs was also critical, since too many . On average, 3.44 million good barcode reads were obtained for each sample, and the average sequence depth was approximately 10×. The coefficient of variation (CV) of read counts among individuals was 0.13 . In addition, the markers were evenly distributed without interference from GC islands and repeat regions  in AIL were used to construct the ddGBS libraries. 96-plex samples were sequenced in one lane according to the ORP of was 0.13 , indicatwas 0.13 . It is wwas 0.13  are nove regions . The maj regions , compris0 individuals were compared. The correspondence between the two methods was evaluated at different depths ranging from 2× to 12×. When the sequencing depth reached 5×, the genotyping consistency for homozygous loci, heterozygous loci and total SNPs was 100%, 97.2%, and 99.1%, respectively  by adding 0.8× sample volume of Agencourt® AMPure® XP Reagent  or polymorphism disrupted a restriction site in varying extents among different samples [The number of SNPs declined with the increase of minimum depth used for identifying SNPs , which w samples . MoreoveThe accuracy of genotyping constitutes another key aspect of GBS technology. Currently, a typical GBS combines low-depth sequencing  and missing data imputation –45. HoweEcoR I- Mse I. The SNP density was approximately 290 K, and some minichromosomes were not included. AIL population was commonly used for QTL fine-mapping in animal genetics [2 in the F9 generation, which was r20.1 = 3.1 Kb, was substantially lower than the F0 generation (r20.1 > 50 Kb)  . This suEcoR I- Mse I) and approximate scope of the sequencing depth . Consequently, we achieved a balance between the density of SNPs and cost. This pre-assessment method is recommended for any novel species.The preliminary experiment was introduced to determine the optimal enzyme combination (http://www.illumina.com/systems/hiseq-x-sequencing-system/system.html). The RRGS process will be quickly standardized with the declining cost of sequencing and it will, together with SNP chips, continue to be a crucial method for genomics study. In addition, the combination of RRGS and other genome-wide sampling sequencing, such as RNA-seq or Targeted Re-sequencing, could effectively promote genetics and evolutionary studies. In conclusion, we present an accurate, high-density, and cost-effective genotyping method for chickens. Our method could facilitate functional gene mapping and molecular breeding of agricultural animals, and could easily be applied to any other species.Reducing cost constitutes a primary aim of all reduced-representation genome sequencing methods. Thus, our method has been optimized for cost at almost every step. However, Illumina HiSeq X Ten pair-end 150 sequencing is now much more cost-effective than single-end sequencing using NextSeq500. Moreover, adopting pair-end sequencing would provide a better chance in SNP identification than single-end sequencing in this study. Currently, ddGBS costs $30 per sample , and more than 65% of the expense comes from the sequencing step in our protocol. Therefore, decreases in the cost of GBS are expected with the rapid development of sequencing technology. For example, HiSeq X Ten systems can output 800–900 Gb data/2.6–3 billion reads in a single flow cell with a cost of $1,000 for 30× of the human genome, which would be more appropriate for large-scale population sequencing Click here for additional data file.S2 FigIn total, 292 K SNPs were identified among all individuals. The genome characteristics and genome-wide distribution of restricted digest fragments are represented circularly. The exterior circle displays the lengths of the chromosomes. The four interior circles show the distribution of fragments (green), GC islands (orange), repeat regions (black), and SNPs (red) from outside to inside.(PDF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S4 Table(PDF)Click here for additional data file.S1 Protocol(PDF)Click here for additional data file.


This study also lays the foundation for genetic analysis of important agronomic traits using this rapeseed population.Single Nucleotide Polymorphisms (SNPs) are the most abundant and richest form of genomic polymorphism, and hence make highly favorable markers for genetic map construction and genome-wide association studies. In this study, a total of 300 rapeseed accessions  were collected and sequenced using Specific-Locus Amplified Fragment Sequencing (SLAF-seq) technology, obtaining 660.25M reads with an average sequencing depth of 6.27 × and a mean Q30 of 85.96%. Based on the 238,711 polymorphic SLAF tags a total of 1,197,282 SNPs were discovered, and a subset of 201,817 SNPs with minor allele frequency >0.05 and integrity >0.8 were selected. Of these, 30,877 were designated SNP “hotspots,” and 41 SNP-rich genomic regions could be delineated, with 100 genes associated with plant resistance, vernalization response, and signal transduction detected in these regions. Subsequent analysis of genetic diversity, linkage disequilibrium (LD), and population structure in the 300 accessions was carried out based on the 201,817 SNPs. Nine subpopulations were observed based on the population structure analysis. Hierarchical clustering and principal component analysis divided the 300 varieties roughly in accordance with their ecotype origins. However, spring-type varieties were intermingled with semi-winter type varieties, indicating frequent hybridization between spring and semi-winter ecotypes in China. In addition, LD decay across the whole genome averaged 299 kb when  Brassica napus  is an amphidiploid species originating from hybridization between B. rapa  and B. oleracea  within the past 10,000 years . Rapeseed oil is primarily an edible oil, but is also used as biofuel, as an industrial lubricant and as a base for polymer synthesis  are DNA sequence variations that occur when a single nucleotide in the genome sequence is changed. SNPs are the most abundant form of genomic polymorphism, and SNP markers hence have higher density than any other marker type. Nowadays, it is possible to identify a large number of SNPs in a species quickly and efficiently via high-throughput DNA sequencing technologies. These have now been widely applied to develop massive genotyping arrays, which allow many more individuals in a species to be genotyped at an extremely high marker density in a fast, efficient, and highly reproducible way  is a fast, accurate, highly efficient, and cost-effective method for developing large-scale SNP and InDel markers  analysis are prerequisites for genome-wide studies of complex agronomic traits in a natural population . Each sample was sequenced using SLAF-seq, and genetic variation was analyzed by alignment to the B. napus reference genome  assess the genetic diversity of our association mapping panel to deepen our understanding of the B. napus germplasm pool; and (3) investigate the population structure and the patterns of LD among the accessions, allowing us to deduce traces of breeding and distinct evolution in the A and C subgenomes. Our study also provides a valuable resource for further genome-wide association studies in B. napus, and paves the way for optimizing cross combinations, identifying loci closely related to agronomic traits, and exploiting rich allelic variation for marker-assisted breeding.In this study, we carried out a genome-wide analysis of a set of 300 accessions representing eco-geographical diversity in China (278 lines) plus international varieties of A set of 300 inbred rapeseed lines were included in the present study Table , includi−1 for SLAF sequencing.All accessions were collected from plants growing in the experimental fields at Jiangxi Agricultural University, Nanchang, China. Young healthy leaves were obtained from a single plant of each accession for DNA extraction using a modified cetyltrimethylammonium bromide (CTAB) method based on Murray and Thompson . DNA conin silico using the 1.2 Gb B. napus reference genome of European winter homozygous oilseed cultivar “Darmor-bzh” . In order to acquire more than 250, 000 SLAF tags (defined as an enzyme fragment sequence of 314–414 bp) per genome, restriction enzyme combinations were tested and selected using in silico digestion prediction using the following criteria: (1) low percentage of restriction fragments comprising repeat sequences; (2) even distribution of restriction fragments across chromosomes; (3) simulated fragments align uniquely to the reference genome; and (4) high number of SLAF tags. Based on these four criteria, the restriction enzyme combination of RsaI and HaeIII  was selected.SLAF-seq success was predicted RsaI and HaeIII to obtain the SLAF tags, followed by fragment end reparation, dual-index paired-end adapter ligation, PCR amplification, and target fragment selection for SLAF library construction. Finally, the SLAF sequencing was carried out using an Illumina HiseqTM 2500  at the Biomarker Technologies Corporation in Beijing.Genomic DNA from each accession was digested with *B. napus using the Burrows-Wheeler alignment tool (BWA) software  was predicted from 1 to 10, and the number of ancestors was determined according to the position of the minimum value, with error rate obtained from 5-fold cross-validation. Maximum likelihood estimates for the ancestry proportion from each K subgroup of each accession were calculated.Based on the same set of SNPs, the number of subgroups  were found in the sequenced genome  involved in the biological process of plant vernalization response. Another candidate gene BnaA05g33430D  participated in floral development. The SNP-rich region on A09 chromosome contained candidate gene BnaA09g44900D, which is closely related to plant systemic acquired resistance and defense response. Known QTLs for resistance to Sclerotinia sclerotiorum  had genetic relationship coefficients <0.05 Figure . Hence, B. napus reference genome  fell into two groups, with only a few clustering into semi-winter groups. In addition, 16 spring accessions were almost all dispersed between the semi-winter groups, suggesting genetic permeation between spring and semi-winter varieties Figure . FurtherPopulation structure as assessed by Admixture  up to more than 2,000 Kb  of the AC genome was 298.95 Kb, while the LD decay was 42.99 Kb and 1,455.28 Kb in the A and C subgenomes respectively  of the Illumina Infinium r2 > 0.8) that tends to travel through the generations as a block . This study also drew the same conclusion as found in our data, that the number of haplotype blocks in the A subgenome is lower than in the C subgenome. In addition, we found 30,877 SNP hotspots and 41 SNP-rich regions in the B. napus genome. There could be several explanations for these. Firstly, there are many regions in the genome that are rich in repetitive sequences, where DNA polymerase errors resulting in strand slippage and inequitable exchange can easily occur . Similar conclusions were drawn by Harper et al.  on the A and C subgenomes was also calculated using 24,994 SNP markers in a panel of 203 Chinese semi-winter rapeseed accessions, revealing that mean LD decay was about 10 times faster in the A subgenome (0.25–0.30 Mb) than in the C subgenome , of which we found 30,877 SNP “hotspots” and 41 SNP-rich genomic regions, and detected potentially differentiated genomic regions between semi-winter, spring and winter ecotype rapeseed. Subsequent genetic analysis for these 300 accessions validated the breeding history of semi-winter rapeseed, showing introgressions from spring types as well as progenitor species B. rapa. Our study provides an important breeding resource, laying the foundation for future analysis of important agronomic traits in B. napus.In this study, we developed 201,817 high-confidence SNP markers in a panel of 300 accessions of B. napus. SF and CW made helpful suggestions on the manuscript and paticipated in the development of the population SNP markers. AM critically revised the manuscript. YH and DF provided plant materials, designed, led, and coordinated the overall study. All authors read and approved the final manuscript.QZ carried out the genetic analysis and wrote the manuscript and with CZ carried out the genotyping experiments. WZ processed the planting and management for the 300 accessions of The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The advent of –omics technologies has enabled the resolution of fine molecular differences among individuals within a species. DNA sequence variations, such as single nucleotide polymorphisms or small deletions, can be tabulated for many kinds of genotype comparisons. However, experimental designs and analytical approaches are replete with ways to overestimate the level of variation present within a given sample. Analytical pipelines that do not apply proper thresholds nor assess reproducibility among samples are susceptible to calling false-positive variants. Furthermore, issues with sample genotype identity or failing to account for heterogeneity in reference genotypes may lead to misinterpretations of standing variants as polymorphisms derived de novo.A recent publication that featured the analysis of RNA-sequencing data in three transgenic soybean event series appeared to overestimate the number of sequence variants identified in plants that were exposed to a tissue culture based transformation process. We reanalyzed these data with a stringent set of criteria and demonstrate three different factors that lead to variant overestimation, including issues related to the genetic identity of the background genotype, unaccounted genetic heterogeneity in the reference genome, and insufficient bioinformatics filtering.This study serves as a cautionary tale to users of genomic and transcriptomic data that wish to assess the molecular variation attributable to tissue culture and transformation processes. Moreover, accounting for the factors that lead to sequence variant overestimation is equally applicable to samples derived from other germplasm sources, including chemical or irradiation mutagenesis and genome engineering  processes.The online version of this article (10.1186/s12896-018-0447-9) contains supplementary material, which is available to authorized users. The process of genetic transformation typically involves inserting DNA sequences originating from one species into the genome of another species. This tool has been used to add traits into crop species, such as herbicide tolerance in soybean and root worm tolerance in corn –4. The cWith the recent revolution in high-throughput sequencing technology, there is now increased interest in understanding the molecular nature of transgenic events, and identifying possible safety implications of unintended molecular changes that may result. This information may be useful in assessing the likelihood that a particular event will express the intended trait(s) without detrimental unintended effects.Molecular studies have previously characterized the effects of transgenesis in several different plant species, focusing on the sequence changes at transgene integration sites , 10 and/Agrobacterium-mediated transformation of cotyledonary nodes) [A curious discrepancy in genome-wide sequence polymorphisms has been observed in recent resequencing studies of transgenic soybean. One study, published by our group , resequey nodes)  and reseGiven the importance and real-world relevance of this topic, it is imperative to resolve the discrepancy between the Anderson et al.  and LambLambirth et al. , 22 perfTwo findings in the Lambirth et al.  mutationUsing the GATK Best Practices workflow , 26, we The analysis and filtering pipeline described above was designed to prevent false-positive SNP calls. Nevertheless, the pipeline was able to detect nearly 10,000 SNPs among the transgenic samples . It is The relatively lower polymorphism rates found in the reanalysis of S77 and S111 compared to that of 764  clusters of polymorphisms. We investigated whether the 143 SNPs identified in our reanalysis of group ST77 could be explained by this type of standing heterogeneity between the ‘Williams 82’ controls used in the study and the ‘Williams 82’ individual that was used for the original ST77 transformation event , 22. IndTherefore, after filtering for genotype identity and background heterogeneity, we found three SNPs each in S77 and S111 that could not be explained by these factors. Follow-up analysis of S77 revealed one SNP within an intron, one synonymous SNP within an exon, and one non-synonymous SNP within an exon (M to V amino acid change in the sixth exon of Glyma.10G150500). Analysis of S111 revealed two SNPs within introns, and one non-synonymous SNP within an exon (T to G amino acid change in the fourth exon of Glyma.04G134800).The previous two sections addressed our reanalysis of RNA-seq data , 22, fochttp://de.iplantcollaborative.org/dl/d/533570A3-1EFB-4864-B9A9-9D82F17E09A8/snpeffgenes.zip). Initial analyses of genotype calls revealed that there was a higher number of heterozygous variants than homozygous variants for the alternate allele compared to the reference genome. ST77 and ST111 were respectively advanced to the T8 and T4 generation before sequencing. We can estimate the expected proportion of heterozygous variants in these generations if we assume the following: all of the mutations induced by transgenesis were heterozygous in the T0 generation, the variants are not subject to segregation distortion, and the variants have negligible effects on organismal fitness. Under these assumptions, we would expect approximately 0.39% of the ST77 variants to be heterozygous at the T8 generation, and 6.25% of the ST111 variants to be heterozygous at the T4 generation. However, the retrieved data showed that 50.21 and 48.62% of the variants were called as heterozygous for ST77 and ST111, respectively. The proportion of heterozygous variants were far higher than what was expected, and were most likely false positives resulting from the analysis method.We retrieved the variant calls for each of the 36 samples used in their analysis , in which a relatively small proportion  of the variants were in common to all three siblings  and those handling the computational analysis. Errors in genotype identity can be diagnosed using strictly molecular approaches, but situations where the identity of the material has been compromised or misinterpreted can be problematic . ThWhile the present reanalysis focused specifically on comparisons between transgenic lines, all the factors addressed in this paper need also be considered when conducting any type of expression and/or genomic comparisons. This includes studies that focus on the effects of mutagenesis, on-target and off-target effects of genome engineering technologies, assessments of standing/natural variation, or other comparisons of germplasm sources. This is particularly true for experiments on materials within the realm of biotechnology, as the findings may be used to inform regulatory agencies about the intended and unintended consequences of using these technologies. Evaluation for the presence of unintended changes at the DNA level continues to be a part of the safety evaluation for transgenic plants, and whole-genome sequencing has been proposed as a tool for this purpose . Howeverwww.soybase.org using the STAR aligner [RNA-seq from  was down aligner . Read-gr aligner . SNPs anwww.Soybase.org. SNP calls for each of the 20,087 accessions in the 50 k dataset were compared to the SNP calls for the 764 series to identify the accession with the highest level of SNP identity.Genotype calls from the filtered SNP list were extracted using a custom python script then loaded into R statistical software. The dataset was filtered for homozygous SNPs that are uniquely polymorphic to the reference compared to the other transgenic lines and ‘Williams 82’ controls. SNPs were removed from the analysis if there was more than 33% missing data for a given line and if there was no consensus genotype call between plants and replicates  called in the Lambirth et al. [Figure S3. Number of overlapping polymorphisms in the Lambirth et al. [h et al.  study. Fh et al.  study wiAdditional file 2:Table S1. SNP calls resulting from the data filtering pipeline shown in Additional file Table S2. Indel calls resulting from the data filtering pipeline shown in Additional file Additional file 3:Resulting raw variant SNP calls from GATK HaplotypeCaller. (VCF 49825 kb)Additional file 4:Resulting raw variant indel calls from GATK HaplotypeCaller. (VCF 29397 kb)


Coffea arabica accessions, including wild genotypes from the historical FAO collection from Ethiopia. A genome-wide association study was performed to identify genomic regions associated with lipid, cafestol and kahweol contents and cafestol/kahweol ratio. Using the diploid Coffea canephora genome as a reference, we identified 6,696 SNPs. Population structure analyses suggested the presence of two to three groups (K = 2 and K = 3) corresponding to the east and west sides of the Great Rift Valley and an additional group formed by wild accessions collected in western forests. We identified 5 SNPs associated with lipid content, 4 with cafestol, 3 with kahweol and 9 with cafestol/kahweol ratio. Most of these SNPs are located inside or near candidate genes related to metabolic pathways of these chemical compounds in coffee beans. In addition, three trait-associated SNPs showed evidence of directional selection among cultivated and wild coffee accessions. Our results also confirm a great allelic richness in wild accessions from Ethiopia, especially in accessions originating from forests in the west side of the Great Rift Valley.Lipids, including the diterpenes cafestol and kahweol, are key compounds that contribute to the quality of coffee beverages. We determined total lipid content and cafestol and kahweol concentrations in green beans and genotyped 107  The concentrations of those components, such as sucrose, caffeine, chlorogenic acids and lipids, are genetically controlled and can be selected to improve beverage quality2. Lipids are key compounds involved in flavor and aroma3. The coffee lipid fraction is mainly composed of triacylglycerols, sterols, tocopherols and diterpenes. Cafestol (CAF), kahweol (KAH), and 16-O-methyl cafestol are the main diterpenes found in coffee oil4. These diterpenes, which are specific to the Coffea genus, have both desirable and adverse effects on human health6. Previous studies of CAF and KAH diterpenes in Coffea arabica L. suggested a strong genetic control of their biosynthesis7. Despite their importance, as far as we know, there is no study trying to correlate the variability of these biochemical compounds among accessions with nucleotide diversity that would be of key interest to optimize coffee breeding strategies.Coffee beverage popularity is related to its unique aroma and flavor as well as its stimulant properties. The precursors of aroma and flavor, which characterize the beverage, correspond to the chemical compounds of green coffee beansC. arabica, and several landraces of this species are known from this region8. To increase the diversity of C. arabica breeding programs, research teams have been collecting accessions from various parts of Ethiopia since 19289, transferring germplasm to other tropical countries. One important survey was organized by FAO in 1964–1965, and harvested seeds were sent to India, Tanzania, Ethiopia, Costa Rica, Portugal, and Peru10. The Instituto Agronômico do Paraná  received 132 of those accessions in 1976, which were planted and maintained to this day. The accessions available in this collection show great phenotypic variation in plant architecture, and size of branches, leaves, fruits, and seeds. In relation to biotic and abiotic factors, these coffee accessions exhibit various levels of tolerance and resistance12. In addition to these morphological and agronomical characteristics, these accessions present a large variability in terms of biochemical contents in green beans, which often translates into a large range of beverage qualities13.The southwest Ethiopian highlands are the place of origin of C. arabica is an allotetraploid (2n = 4 ×  = 44), which is derived from a spontaneous hybridization between two closely related diploid species, Coffea eugenioides14 and Coffea canephora Pierre ex A. Froehner15. Whereas C. canephora (2n = 2 ×  = 22) is an allogamous diploid species harboring a high diversity16, the propagation history of C. arabica combined with its autogamy has led to a narrow genetic diversity among cultivars17. C. arabica breeding programs suffered from this lack of diversity, which also hampered the development of molecular tools whose efficiency is recognized as maximizing the genetic gains per unit of time. Genetic maps have only recently been reported for C. arabica18. However, there is no publicly available C. arabica reference genome, even though a few research efforts have been started. Nevertheless, a diploid genomic reference of C. canephora has been released and has allowed significant progress for C. arabica genomic analyses20.21. GWAS usually provides a higher mapping-resolution than classical biparental QTL mapping experiments, and is considered as a cost-effective way to detect associations between molecular markers and traits of interest22. However, assessing the population structure of the association panel is necessary to minimize the occurrence of spurious associations21. GWAS requires the use of an adequate number of markers. Recently, next-generation sequencing platforms have dramatically reduced the cost and time to obtain large numbers of markers. Because of its relative simplicity and robustness, the genotyping-by-sequencing (GBS) strategies have been extensively used22.Genome-wide association studies (GWAS) are an efficient approach to dissect the genetic architecture of complex traitsC. arabica genotypes based on GBS analyses; (ii) analyze the population structure of the IAPAR collection of C. arabica genotypes encompassing wild accessions; (iii) perform a GWAS to decipher the genetic basis of lipid and diterpene contents within the broad-based Ethiopian collection; and (iv) draw consequences for coffee collections and C. arabica breeding programs.In this study, our objectives were to (i) identify SNPs within The complete list of 107 accessions analyzed in the present study is shown in Supplementary Table C. arabica reference genome, we used the publicly available genome assembly of its ancestor C. canephora. This reference genome was used to map the GBS tags and perform the SNP calling. GBS libraries yielded approximately 48 million single-end reads. Those reads produced 6,210,920 tags, of which 20% were aligned to unique positions. A total of 6,696 SNPs was identified, with an average depth of 39×. The SNPs were filtered based on minor allele frequency (MAF > 0.05) and call rate (>0.80). Thereafter, the resulting SNPs were filtered based on their heterozygosity (Ho): SNPs with Ho >0.9 were discarded. Filtering based on Ho was performed in order to eliminate SNPs deriving from C. arabica homeologous genomic regions in which different alleles are fixed in the two subgenomes (CaCe vs CaCc)23. A final set of 2,587 SNPs were obtained and used for further population structure and genome wide association analysis for the lipids and diterpenes contents.Due to the lack of a 24.Population structure analysis was performed using a Bayesian model-based approach implemented in STRUCTURE software Fig. . The STRThe structure result using K = 2 Fig.  grouped In a principal coordinate analysis (PCoA), the first two coordinates explained 25% of the total genetic variation Fig. . SimilarThe M group presented the highest intragroup diversity, showing an allele number average (Na), Shannon’s information index (I) and expected heterozygosity (He) mean of 1.97, 0.55, and 0.37, respectively  decay below 0.2 at 185 Kbp , we observe a linkage disequilibrium decay below r2 = 0.2 at 298 Kbp. With the r2vs measure, lower values overall were obtained, as well as an expected exponential decline of linkage disequilibrium with distance, which demonstrated the efficiency of this measure in correcting bias. We also observed a difference between the estimated r2 and r2vs. The positive bias was removed across the whole chromosomal segment. However, for some close loci, the r2vs estimate was larger than r2, leading to the removal of negative bias, as well. It is important to note that LD was calculated using the C. canephora ancestral genome as a reference, since there is no Arabica genome available.The parameters rC. arabica beans, we performed GWAS using four different methods  with 107 accessions. We identified a total of 21 SNPs associated with lipid (5), CAF (4), and KAH (3) contents and CAF/KAH ratio (9), which were distributed among all chromosomes , CAF , and KAHFor candidate gene mining, we considered only SNPs associated with traits that were detected by at least two methods. Remarkably, we found SNPs positioned within or near genomic regions coding for proteins involved in lipids and diterpenes metabolic pathways Table .Table 3C25 were used to explore the gene expression patterns of some of the candidate genes identified , all the genes showed stronger expression profile in flowers and or fruit organs.RNA-seq data obtained from coffee leaves, flowers and fruit tissues from 30 to 150 days after flowering (DAF) from a previous studyAmong 2,587 SNPs analysed, 139 present signature of diversifying selection among genetic groups , according with BAYESCAN results Fig. .Figure 4Three of these SNPs were also identified as being associated with some of the traits analyzed in the GWAS. The frequency of the alternative alleles of these loci in the Q3 group, formed by wild accessions and collected in the western forests of Ethiopia, was very low compared to the Q1 group, which was composed of domesticated accessions with intermediate levels of breeding Table  and the C. arabica accessions from primary diversity centers for bean physical, organoleptic and biochemical qualities displaying high variability13. According to these studies, the influence of geographical origin on these traits was evident. Interestingly, in the present study a large influence of the geographic origin on CAF, KAH and lipid contents in the beans was also observed. Wild accessions collected in the forests of the west side of Great Rift Valley presented higher lipid contents than cultivars.The 107 genotypes analyzed presented high phenotypic variability for the lipid, CAF and KAH contents and for the CAF/KAH ratio. Other studies also report high genetic diversity in 12, have been already described, this is the first large-scale study using an Arabica population that includes several wild accessions from Ethiopia. Accessions with different lipid and diterpene contents may serve as a source of alleles for the development of plants with desirable lipid and diterpene contents in the beans. Therefore, the results of the present study can contribute to coffee breeding to deliver high-quality coffee varieties according to the consumer market demands.Although biochemical compounds related to beverage quality traits in coffee, including lipid and diterpene contentsC. canephora19 as a reference to find SNP markers in the C. arabica genome. The high degree of conservation between both genomes is well known26 and allowed us to map tags from genotyping-by-sequencing (GBS) data for SNP identification. We identified a total of 6,696 SNPs. Those SNPs were further filtered for MAF, call rate and heterozygosity, generating 2,587 high quality SNPs for population structure and genome-wide association analyses. One of the main difficulties of working with polyploids is distinguishing true SNPs segregating in the subgenomes from homologous SNPs representing fixed differences between both ancestral diploids subgenomes23. Therefore, SNPs corresponding to the differences between both subgenomes (heterozygosity = 1) were discarded and the SNPs selected represent true variability in C. arabica. The number of detected SNPs was relatively low. This can be explained by the low genetic diversity of the species, which has a recent origin15. In addition, we used just one subgenome as a reference, and the number of TAGs mapped was low (22%). However, in a recent similar study using GBS in C. canephora, only 32% of TAGs were mapped using the same C. canephora genome reference27.We used the diploid genome of C. arabica var. Typica, C. arabica var. Bourbon, their mutants and hybrids28. The narrow genetic base of those cultivars9 has resulted in a crop with homogenous agronomic behaviors15, including high susceptibility to biotic and climatic stress29 representing a breeding challenge due environmental changes or market demands. The genetic diversity analysis using SNP markers revealed that the collection of C. arabica used in this study has a higher genetic diversity than traditional cultivars, consistent with the great phenotypic variability observed for the biochemical characterization previously reported12. In this context, our Ethiopian germplasm collection has been shown to be a valuable source of novel favorable biochemical characteristic-related alleles, which can be explored by breeding programs.Despite the wide geographical range of Arabica coffee cultivation, the number of cultivars used is very small: mainly 11.In the STRUCTURE analysis using K = 3, all cultivars and genotypes from the east side of the Great Rift Valley were sorted into the same group (Q2). Previous genotypic characterization of this collection using microsatellite markers showed a subdivision of these genotypes only into two groups, from the west and east sides of the Rift Valley30.Interestingly, the Q3 group, formed by wild accessions, presented a high lipid content in comparison to the other groups. This result indicates that the Q3 group contains alleles conferring differentiated lipid content in beans. In Ethiopia, this wild gene pool has been potentially threatened by forest fragmentation and degradation and by introgressive hybridization with locally improved coffee varietiesC. arabica from the origin center (Ethiopia). Both forest fragmentation and forest degradation can have a negative impact on the genetic diversity of forest plant species through increased genetic drift, reduced gene flow, and alteration of mating patterns resulting in increased inbreeding32. In addition, the widespread planting since the 1970s of a restricted set of locally improved coffee varieties, mainly genotypes resistant to coffee berry disease, in the forest and its surroundings may result in the replacement of a part of the wild gene pool with a small number of domesticated alleles34. This can result in loss of genetic variation from the original gene pool and may even have negative fitness consequences for the original populations35. Overall, our results can help us to define which accessions are more important to preserve in order to have a good genetic representation of the FAO collection. The genetic diversity of plants from the western region demonstrated the importance of carefully preserving and exploring the accessions from this region in order to increase genetic variability, especially for coffee beverage quality12. It is important to observe that our work was performed only with a subset of the full FAO collection. Studies using the whole collection and or focusing in the genotypes from the Western side of Great Rift Valley would be of great value for increase our knowledge on the phenotypic and genotypic diversity of C. arabica.Our results reinforce the importance of preserving the germplasm of C. canephora35 and other Coffea species36, but none has been reported for C. arabica. We performed GWAS for lipids and CAF and KAH diterpenes in coffee beans using 104 accessions from the FAO Ethiopian collection and three cultivars. We used 2,587 high-quality SNPs and identified 21 SNP/trait associations.Several studies relating quantitative trait loci (QTLs) to cup quality compounds have been performed on 37. Another problem with the method is the issue of multiple test corrections for the threshold value of significance testing. The typical Bonferroni correction is often too conservative, so many important loci may not pass the stringent criterion of significance testing37. The mrMLM method was efficient to identify genomic regions associated with lipid and diterpenes concentrations in coffee green beans, combining an efficient control of false positives with high power, as described by the authors of this method37.A common feature of the MLM-based GWAS methods is the one-dimensional genome scan, performed by testing one marker at a time. However, such a model does not facilitate good estimates of marker effects because the model is never correct if a trait is indeed controlled by multiple loci, which is the case for most complex traits4. Insights into the details of lipid biosynthesis and information on the genes and enzymes involved in this process may lead to innovative strategies to modify the fatty acid composition and increase seed oil content. In the present study, we identified one lipid-associated SNP (S8_25559761) co-localized with the Cc08_g10680 gene, which encodes a fatty acid desaturase (FAD2). Desaturase enzymes regulate the unsaturation of fatty acids through the introduction of double bonds between defined carbons of the fatty acyl chain. Very interestingly, the difference of diterpenes CAF and KAH is just one unsaturated carbon38, therefore the potential role of FAD2 in KAH formation should be further investigated. In Arabidopsis thaliana, FAD2 has been shown to be important in the seed oil biosynthesis pathway39. This gene was identified as associated with lipid content in corn grains40 and brassica41.Coffee bean lipids are composed mainly of triacylglycerols, sterols and tocopherols, the typical components found in all common edible vegetable oils38. Sequential condensation of these units by transferases yields a handful of central prenyl diphosphate intermediates in terpenoid biosynthesis. Diterpenoids originate predominantly from the MEP pathway.All plant diterpenoids are derived from only two five-carbon (C5) isoprenoids, isopentenyl diphosphate (IPP), and dimethylallyl diphosphate (DMAPP), produced via the cytosolic mevalonate (MVA) and the plastidial 2-C-methyl-D-erythritol-4-phosphate (MEP) pathwaysCoffea genus7. They have a very similar chemical structure with one double bond difference in the aromatic hydrocarbon composed by twenty carbons38. In contrast to other biochemical compounds, the total amount of diterpenes does not significantly change among cropping years and environments2, suggesting that the production of these compounds is under strong genetic control. Terpene diversification is driven by the machinery consisting TPSs and cytochrome P450-dependent monooxygenases (CYP) genes. The latter is important for modifying and diversifying the terpenoid scaffolds by redox modification42. We identified one SNP associated with CAF (S11_29778697) that was co-localized with the gene Cc11_g12750, which encodes a cytochrome P450 704 (CYP704). Several P450 genes are involved in secondary metabolite biosynthesis, including terpenoids44. CYP704 in rice was also shown to provide lipid monomers for the synthesis of anther cutin45. Another SNP associated with CAF is positioned close to a monooxygenase. Monooxygenase was described as being directly involved in plant terpene biosynthesis46.KAH and CAF are exclusive diterpenes of the LACS). LACS proteins occupy a critical position in the biosynthetic pathways of nearly all fatty acid-derived molecules47. LACS proteins esterify free fatty acids to acyl-CoAs, a key activation step that is necessary for the utilization of fatty acids by most lipid metabolic enzymes. LACS proteins initiate the process of fatty acid β-oxidation. In oilseeds, carbon reserves are stored as triacylglycerol (TAG). With the onset of germination, lipases release free fatty acids from the TAG molecules. LACS proteins activate the free fatty acids to acyl-CoAs that enter the β-oxidation pathway in the glyoxysomes of the germinating seedling. The enzymes of the β-oxidation cycle completely degrade fatty acids by the sequential removal of two-carbon units, which are released in the form of acetyl-CoA. The resulting acetyl-CoA pool is essential for the production of cellular energy (through the tricarboxylic acid cycle) and for synthesis of sugars and other carbon skeletons. LACS were also identified as being associated with lipid content in maize40 and brassica48.The SNP S2_45775221 associated with KAH is co-localized with Cc02_g33380, which encodes a long chain acyl-CoA synthetase . LpdA encoding the E3 subunits of both the pyruvate dehydrogenase and 2-oxoglutarate dehydrogenase complexes51.Among SNPs associated with the CAF/KAH ratio, one is co-localized with the gene Cc06_g14660, which encodes a diterpene synthase (momilactone A synthase). Momilactone A is a diterpenoid secondary metabolite that is involved in the defense mechanism of the plant38. One SNP associated with CAF/KAH ratio (S7_5138106) is co-localized with the gene Cc07_g06960, which encodes an acyl-CoA N-acyltransferases (NAT). N-Acyltransferase catalyzes the transfer of an acyl group to a substrate. Members of the N-acyltransferase superfamily have a similar catalytic mechanism but vary in the types of acyl groups they transfer, including those of the three main nutrient substances, saccharides, lipids and proteins. These substances participate in a common metabolic pathway mediated by acetyl-CoA in the tricarboxylic acid cycle and oxidative phosphorylation reactions. Acyl lipids have various functions in plants, and the structures and properties of the acyl lipids vary greatly even though they are all derived from the same fatty acid and glycerolipid biosynthesis pathway. Some acyl lipids, including jasmonic acid, participate in signaling pathways. Acyl-CoA and acyl-CoA N-acyltransferase are involved in these metabolic pathways, including pyruvate dehydrogenase and pyruvate, and they are involved in the metabolism of sugars in the citric acid cycle and fatty acids and fat metabolism required for the synthesis of flavonoids and related polyketides for the elongation of fatty acids involved in sesquiterpenes, brassinosteroids, and membrane sterols47.As already demonstrated in the phenotypic analysis, the CAF/KAH ratio is significantly correlated with lipid content, and this could explain why some SNPs associated with lipid content are also co-localized with genes related to lipid metabolism. In addition, the initial steps of CAF and KAH biosynthesis use acetyl-CoA as a substratepdTPI). After germination, seedling establishment requires a transition from heterotrophic to autotrophic growth to sustain plant growth once storage reserves are used. This likely involves multiple plastid biosynthetic pathways. In plants, triose phosphate isomerase  is involved in several metabolic pathways operating during this transition, including glycolysis, gluconeogenesis, and the Calvin cycle52. In Arabidopsis, a plastid isoform of triose phosphate isomerase (pdTPIP) plays a crucial role in the transition from heterotrophic to autotrophic growth54. A T-DNA insertion in Arabidopsis thaliana pdTPIP resulted in a fivefold reduction in transcription, reduced TPIP activity, and a severely stunted and chlorotic seedling that accumulated dihydroxyacetone phosphate (DHAP), glycerol, and glycerol-3-phosphate53.We identified a SNP associated with CAF/KAH ratio (S2_15335417) that co-localized with the Cc02_g16540 gene, which encodes a plastidial triosephosphate isomerase (BTAF1), the transcriptional data strongly corroborates to diterpene biochemical profile reported for the same organs25. Diterpenes are present mainly in roots, flowers and accumulated in fruits during its development reaching a peak around 120 DAF7. In flowers the presence of CAF is predominant and it will be very interesting to study the role of the MAS in CAF formation. Meanwhile FADS2, CYP704 and TPIP1, showed a transcription pattern similar to KAH accumulation during coffee fruit development. The role of FCM, strongly expressed in the final stages of fruit maturation, also can be very interestingly with a potential role in the final composition of lipids in coffee grains.We observed the transcription pattern of the genes co-localized with associated SNPs. With one exception . The Q3 group (wild accessions) presented very low frequencies of the reference alleles at these loci when compared to the Q1 group and especially compared to the Q2 group, which is composed of cultivated accessions. These observations indicate that domestication and the breeding process of C. arabica germplasm collection originated from FAO surveys in the 1960’s. We identified a great allelic richness in the accessions of Ethiopia, especially in the West side of the Great Rift Valley. Trait-associated-SNPs identified by GWAS may be helpful to develop Markers Assisted Selection strategies aiming to improve the biochemical quality of the coffee beans.In summary, these findings identify candidate genes representing potential targets for improving beverage quality in relation to lipids and diterpenes composition. The information reported here can be a starting point to obtain plants with desirable content of lipids, CAF, and KAH by incorporating molecular breeding techniques to the traditional programs. Our analyses also allowed assessing the population structure and genetic relationships among genotypes of a C. arabica collection as well as cultivars from the Instituto Agronômico do Paraná (IAPAR) breeding program were cultivated at its experimental station in Londrina, Brazil (23°23′00″S and 51°11′30″W). The soil is a red dystrophic latosol, and the average rainfall and temperature are 1,500 mm/year and 21 °C, respectively. The FAO collection at IAPAR comes from open-pollinated seeds from the original collection at CATIE (Costa Rica) introduced in Brazil in 1976, and kindly transferred from the Instituto Agronômico de Campinas (IAC) to IAPAR. Fruits were harvested from 107 genotypes between May to July 2011 at full maturity. Cherries were manually selected in order to avoid immature and damaged seeds, which were washed and sun-dried until they contained 12% moisture. Coffee beans were processed  and standardized in grade 16-sized sieves (6.5 mm); all defective beans were discarded.The complete list of 107 accessions analyzed in the present study is shown in Supplementary Table 2. The extracts were identified and quantified by HPLC at 220 and 290 nm for CAF and KAH, respectively. A reversed-phase Spherisorb ODS 1 column (250 mm × 4.6 mm id 5 mm)  and an acetonitrile: water (55:45) mobile phase were used to separate the compounds. Quantification was carried out by external standardization, generating calibration curves with CAF and KAH content between 50 and 1,000 mg.100 g−1 (six different concentrations in triplicate). To determine the lipid content of ground coffee beans, the methods described in the Association of Official Analytical Chemists (AOAC)55 using petroleum ether as a solvent was employed.Coffee beans were frozen using liquid nitrogen to prevent compound oxidation in the matrix and ground (0.5 mm particles) in a disk mill . The milled samples were stored in plastic bags and kept in a freezer (−18 °C) until analysis. The moisture content (oven set at 105 °C to constant weight) was also determined to express the results in terms of dry weight. Cafestol (CAF) and kahweol (KAH) were analyzed by direct extraction using saponification and cleanup in terc-butyl-methyl-ether and water56. GBS was performed by the Genomic Diversity Facility LIMS at Cornell University. The PstI restriction enzyme was used for library preparation57. Single-end sequencing of multiplexed GBS libraries were performed on Illumina HiSeq 2000 equipment, with 159 samples in two 96-well multiplex plates. Single nucleotide polymorphisms were identified using the TASSEL-GBS pipeline58 in TASSEL software version 3.0.166. Briefly, raw FASTQ sequences were trimmed to remove barcodes and reads from each of the four FASTQ files were collapsed into one master TagCounts file containing unique tags along with their associated read count information. Tags aligned to unique positions on the C. canephora reference genome19 were used for SNP calling. SNP discovery was performed for each set of tags that aligned to the exact same starting genomic position and strand. SNP genotyping was determined by the default binomial likelihood ratio method of quantitative SNP calling in TASSEL 3.0.16658. GBS SNP calling was performed using the C. canephora genome as reference. Quality control of the SNPs was performed using the parameters of call rate (CR > 80%), minor allele frequency (MAF > 5%), and heterozygosity (Ho < 0.9).DNA extractions were performed from leaves using a modified CTAB protocol59.According to the whole set of SNP, we estimated mean number of alleles (Na), percentage of polymorphic loci (P), expected heterozygosity (He), Shannon’s information index (I) and number of private alleles in each genetic group using GenAlEx 6 softwareWe performed principal coordinate analyses (PCoAs) via covariance matrices with data standardization using GenAlEx 6 software to assess and visualize genetic relationships among genetic groups and individuals.60. Allele frequencies of each K cluster (from 2 to 10) were estimated. We assumed a single domestication event and restricted our analysis to the correlated frequency model. We used a 105 burn-in period and 105 iterations, as these parameters resulted in relative stability of the results with 10 runs per K value. The genome composition (genome plot) of the accessions was represented for each K. Only accessions displaying a membership larger than 0.6 were assigned to a genetic group, resulting in assignments for 80% of the accessions. Accessions with memberships lower than 0.6 were assigned to a mixed cluster (M). We used the ΔK criterion24 in Structure Harvester software61 to estimate the upper-most level of structure.Genetic structure was estimated using the model-based Bayesian method implemented in STRUCTURE software version 2.3.42vs obtained by considering the population structure and cryptic relatedness using the R package ‘LDcorSV’ version 1.3.162. An identity-by-state (IBS) centered kinship matrix was calculated using TASSEL software version 5.2.2063. A population structure matrix (Q matrix) was obtained using STRUCTURE software version 2.3.461 (K = 2).Pairwise linkage disequilibrium (LD) between SNP markers was calculated to evaluate the extent of LD decay. Only pairs of markers with distances at most 20 Mbp from each other were considered. LD was estimated using the parameter rTo identify SNPs and candidate genes associated with natural variation in lipid and diterpene contents in Arabica beans, we performed GWAS using four methods: multi-locus random-SNP-effect mixed linear model (mrMLM), FAST multi-locus random-SNP-effect EMMA (FASTmrEMMA), integrative sure independence screening EM-Bayesian LASSO (ISIS EM-BLASSO), and polygenic-background-control-based least angle regression plus empirical Bayes (pLARmEB).37. For the mrMLM method, the parameters used were critical p-value in rMLM = 0.01, search radius of candidate gene (Kb) = 20, critical LOD score in mrMLM = 3.The mrMLM method used a random-SNP-effect MLM (RMLM) and a multi-locus RMLM (mrMLM) for GWAS. The mrMLM treats the SNP-effect as random, but it allows a modified Bonferroni correction to calculate the threshold p-value for significance tests. The mrMLM is a multi-locus model including markers selected from the RMLM method with a less stringent selection criterion. Due to the multi-locus nature, no multiple test correction is needed. The results from real data analyses and simulation studies show that the mrMLM has the highest power for quantitative trait nucleotide QTN detection, the best fit for genetic models, the minimal bias in the estimation of the QTN effect, and the strongest robustness, compared with the RMLM and the EMMA65. All the putative QTNs with the ≤0.005 p-values in the first step of the new method are included in one multi-locus model for true QTN detection. Owing to the multi-locus feature, the Bonferroni correction is replaced by a less stringent selection criterion. The results from analyses of both simulated and real data showed that FASTmrEMMA is more powerful in QTN detection, model fit and robustness, has less bias in QTN effect estimation, and requires less running time than the current single- and multi-locus methodologies for GWAS, such as E-BAYES, SUPER, EMMA, CMLM and ECMLM64. For FASTmrEMMA, we used the critical p-value in the first step of FASTmrEMMA = 0.005 and critical LOD score in the last step of FASTmrEMMA = 364.In the FASTmrEMMA method, a new matrix transformation is constructed to obtain a new genetic model that includes only QTN variation and normal residual error; allowing the number of nonzero eigenvalues to be one and fixing the polygenic-to-residual variance ratio is used to increase computing speed65. Expectation-maximization (EM)-Bayesian least absolute shrinkage and selection operator (BLASSO) is used to estimate all the selected SNP effects for true quantitative trait nucleotide (QTN) detection. Monte Carlo simulation studies validated this method, which has the highest empirical power in QTN detection and the highest accuracy in QTN effect estimation, and it is the fastest, compared to the efficient mixed-model association (EMMA), smoothly clipped absolute deviation (SCAD), fixed and random model circulating probability unification (FarmCPU), and multi-locus random-SNP-effect mixed linear model (mrMLM)65. For the ISIS EM-BLASSO method, we considered a critical p-value = 0.01.ISIS EM-BLASSO uses an iterative modified-sure independence screening (ISIS) approach in reducing the number of SNPs to a moderate size66 using an algorithm of model transformation that whitened the covariance matrix of the polygenic matrix K and environmental noise. Markers on one chromosome are included simultaneously in a multi-locus model and least angle regression is used to select the most potentially associated single nucleotide polymorphisms (SNPs), whereas the markers on the other chromosomes are used to calculate a kinship matrix as a polygenic background control. The selected SNPs in the multi-locus model are further detected for their association with the trait by empirical Bayes and likelihood ratio test. The results from the simulation studies showed that pLARmEB was more powerful in QTN detection and more accurate in QTN effect estimation, had lower false positive rates and required less computing time than Bayesian hierarchical generalized linear model, efficient mixed model association (EMMA) and least angle regression plus empirical Bayes. For the pLARmEB method, the parameters used were critical LOD score = 2 and the number of potentially associated variables selected by LARS = 50.The pLARmEB method integrates a least angle regression with empirical Bayes to perform multi-locus GWAS under polygenic background control37 in the R program. To control the effect of population structure, we used a Q matrix generated by STRUCTURE software considering K = 2. To control the bias generated by the kinship effects between individuals, an identity by state (IBS) kinship matrix was used. The Coffee Genome Hub database20 was used to identify C. canephora genes located in the interval of 100 Kbp encompassing significant SNPs.All these analyses were performed using the mrMLM package25. Graphic were developed using Genesis Software version 1.8.167.The digital gene expression pattern was obtained using RPKM values from coffee leaves, flowers and fruit tissues from 30 to 150 days after flowering published in a previous study68. BAYESCAN was run with burn-in = 50,000, thinning interval = 30, sample size = 5,000, number of pilot runs = 50, length of pilot runs = 5,000, and the false discovery rate (FDR) threshold 0.1.To detect loci under directional selection among genetic groups identified using STRUCTURE analysis, we used the Bayesian approach of BAYESCAN 2.01Supplementary Information


Mmp13, Nos2, and Ptgs2/Cox2 in chondrocytes in vitro. Here, we investigated the contribution of ELF3 to cartilage degradation in vivo, using a mouse model of OA. To this end, we generated mouse strains with cartilage-specific Elf3 knockout (Col2Cre:Elf3f/f) and Comp-driven Tet-off-inducible Elf3 overexpression (TRE-Elf3:Comp-tTA). To evaluate the contribution of ELF3 to OA, we induced OA in 12-week-old Col2Cre:Elf3f/f and 6-month-old TRE-Elf3:Comp-tTA male mice using the destabilization of the medial meniscus (DMM) model. The chondrocyte-specific deletion of Elf3 led to decreased levels of IL-1β- and DMM-induced Mmp13 and Nos2 mRNA in vitro and in vivo, respectively. Histological grading showed attenuation of cartilage loss in Elf3 knockout mice compared to wild type (WT) littermates at 8 and 12 weeks following DMM surgery that correlated with reduced collagenase activity. Accordingly, Elf3 overexpression led to increased cartilage degradation post-surgery compared to WT counterparts. Our results provide evidence that ELF3 is a central contributing factor for cartilage degradation in post-traumatic OA in vivo.The E-74 like factor 3 (ELF3) is a transcription factor induced by inflammatory factors in various cell types, including chondrocytes. ELF3 levels are elevated in human cartilage from patients with osteoarthritis (OA), and ELF3 contributes to the IL-1β-induced expression of genes encoding  Although OA has long been regarded as “wear and tear” arthritis, the involvement of inflammation in disease progression has been well recognized in recent years3. Inflammatory and mechanical stress in OA leads to abnormal activation of common signaling pathways in the cells resident in joint tissues5. Chondrocytes, constituting the unique cell type of articular cartilage, become activated in OA in response to the abnormal environment, leading to a plethora of transcriptional and non-transcriptional events that result in aberrant expression of genes contributing to the degradation of the extracellular matrix6.Osteoarthritis (OA) is a whole joint disorder characterized by pathologic changes of multiple components of the joint7, are implicated in a diverse range of biological functions9. The E-74 like factor 3 (ELF3) is a member of the ELF subfamily with roles in epithelial cell differentiation and function11. ELF3 is abundantly expressed in epithelial tissues10. In non-epithelial cells, in which it is not expressed normally13, the induction of ELF3 by inflammatory stimuli drives the expression of genes such as cyclooxygenase 2 (COX2), nitric oxide synthase 2 (NOS2), angiopoietin-1, and matrix metalloproteinase 13 (MMP13)17.The ETS transcription factors, defined by a highly conserved DNA binding domain18. We showed that ELF3 represses the expression of the type II collagen gene (COL2A1) by directly binding to the COL2A1 promoter18 and disrupting the activator functions of Sox9 and CBP/p30019. In addition, we showed that ELF3 binds to and transactivates the MMP13 promoter in chondrocytes, thereby mediating IL-1β- and TNFα-driven MMP13 gene expression17. Altogether, these results suggest that ELF3 plays a critical role in cartilage remodeling in OA disease.ELF3 is expressed in the cartilage and synovium of patients with rheumatoid arthritis and OAin vivo in a model of post-traumatic OA. Using mice with Col2a1-driven Elf3 knockout (Elf3-cKO) or Comp-driven Tet-Off inducible overexpression of Elf3 (Elf3-Tg) subjected to destabilization of the medial meniscus (DMM), we show that Elf3 accounts, in large part, for the expression and activity of Mmp13 in articular chondrocytes in vivo.In this study, we aimed to investigate the contribution of ELF3 to cartilage degradation Elf3 deficiency in articular cartilage remodeling in vivo, we first generated mice with cartilage-specific Elf3 KO. The Col2a1-Cre:Elf3f/f (Elf3-cKO) mice were born at the expected Mendelian ratio, with no gross abnormality, and with comparable size and weight to the Elf3f/f Cre-negative littermates (WT) and sex- and age-matched wild-type C57/BL6 mice (not shown). To assess knockout efficiency, total RNA was isolated from cartilage explants from femoral heads of 5- to 6-day-old cKO and WT littermates. Since Elf3 mRNA is barely detectable in articular chondrocytes and other non-epithelial cells17, we incubated the cartilage explants with 10 ng/ml IL-1β for 6 days. RTqPCR analyses confirmed increased Elf3 mRNA in IL-1β-treated WT cartilage explants, whereas IL-1β treatment did not induce Elf3 mRNA in cKO cartilage explants, verifying efficient Elf3 ablation in articular cartilage , suggesting that Elf3 does not contribute to growth plate development. To confirm this, we assessed whether the postnatal growth plate architecture was altered in the cKO animals. As shown in Fig. Col2a1-driven Elf3 knockout does not lead to skeletal abnormalities, and that the adult Elf3 cKO mice are suitable for studying OA.To elucidate the role of age Fig. . Next, tElf3 deletion by RTqPCR analyses of total RNA extracted from WT and cKO primary chondrocytes after treatment with 1 ng/ml of IL-1β for 6 hours in vitro. As shown in Fig. Elf3 expression was ablated in cKO cells without impacting the levels of Ehf and Elf5 mRNA, other members of the ELF subfamily  mouse strain. Pregnant females and litters were administered doxycycline until weaning, as described21, and post-natal Elf3 overexpression was induced by doxycycline withdrawal in Comp-expressing tissues. No doxycycline-induced defect or gross abnormality due to the transgene was observed in any of the lines (not shown). The ComptTA;TRE-Elf3 (Elf3Tg) and TRE-Elf3 (WT) control littermates displayed comparable size and weight to ComptTA and wild-type C57/B6 sex and age-matched mice at 1 and 3 months of age (not shown). We isolated total RNA from the articular cartilage of WT and Elf3Tg mice at 2, 5, and 8 months after doxycycline removal . While we did not consistently detect changes in Elf3 mRNA in Elf3Tg mice at 2 months after doxycycline withdrawal (data not shown), increased Elf3 mRNA was observed in the articular cartilage of Elf3Tg mice compared to WT littermates at 6 and 9 months of age . Safranin O staining revealed comparable structural integrity in Elf3Tg and WT littermates at 6 (not shown) and 9 months of age . Cartilage integrity was assessed in unoperated and DMM-operated WT and Elf3Tg mouse knee joints at 8 weeks post-DMM. Consistent with our previous findings Fig. , the Elfrts Fig.  without in vitro data in human and mouse primary chondrocytes provided evidence for the pivotal role of ELF3 in regulating MMP13 gene transcription17 and in disrupting chondrocyte anabolism19, suggesting its contribution to abnormal cartilage remodeling in OA disease. Here, we show that ELF3 contributes to increased collagenase activity and cartilage degradation in vivo, in a mouse model of post-traumatic OA, and that ELF3 overexpression accelerates cartilage degradation concomitant to post-traumatic OA disease.OA disease involves the interplay of numerous regulators and signaling factors that in concert lead to deregulated remodeling of joint tissues. We showed previously that ELF3 mRNA and protein levels are increased in human OA cartilage, and our Elf3 deletion in OA, WT and Elf3-cKO littermates were subjected to the DMM model, which mimics post-traumatic OA in humans23. The DMM-operated WT mice showed enhanced cartilage damage at 8 and 12 weeks compared to the cKO mice, which had significantly lower OA scores. The lack of difference observed between the genotypes at 4 weeks post-DMM may be due to the time it requires to upregulate sufficient Elf3 gene expression and/or activity of its target gene products, including matrix-degrading proteinases, which also require activation of pro-enzyme precursors24. In addition to progressive erosion of articular cartilage, OA is characterized by thickening of the subchondral bone and osteophyte formation25. Both Elf3-cKO mice and their WT littermates developed DMM-induced osteophytes, with no difference in size or maturity of osteophytes observed between genotypes, indicating that Elf3 does not have a significant role in osteophyte formation. This result is consistent with previous reports showing that Mmp13 knockout mice are protected from articular cartilage erosion, but not from osteophyte development26. The increased expression of Elf3 mRNA in the articular cartilage of the WT DMM-operated limbs suggests that Elf3 may be induced by mechanical stress in the absence of overt inflammation. DMM-induced expression of Elf3 and Mmp13 correlated with increased collagenase activity, which was reduced in cKO mice. The latter further suggests that ELF3 mediates cartilage degradation by specifically modulating MMP-13, in agreement with our previous in vitro results showing that other proteases are not affected by the absence of ELF3, and is consistent with the view that MMP-13 plays a central role in erosion of the collagen network, which marks OA progression27. However, while our observations in vitro support the notion that Elf3 drives cartilage degradation via MMP-13 induction and not through other collagenase or aggrecanase-mediated events, the contribution of Elf3 in driving the expression in vivo of other relevant inflammatory and catabolic genes that impact OA disease is yet to be elucidated. Similarly, with our experimental conditions we did not detect significant changes in selected anabolic genes. However, since changes in anabolism constitute a somewhat early event in OA disease and are sometimes difficult to detect reliably in cartilage with established pathology and evident structural damage, the impact of Elf3 in the anabolic responses of OA chondrocytes in vivo requires further investigation.To assess the effects of the Elf3-cKO mice from cartilage degradation post-DMM surgery, imply that increased Elf3 levels and/or activity may have a role in initiating or accelerating the progression of OA. To assess the effects of enforced expression of Elf3 in adult mouse articular cartilage, we generated the Comp-tTA:TRE-Elf3 (Elf3Tg) mouse strain, with inducible Elf3 expression. We chose the Tet-Off system because of the reported advantages over other regulated gene expression systems29. While removal of doxycycline induced Elf3 mRNA expression efficiently and specifically in the Elf3Tg cartilage, we did not observe significantly increased spontaneous or age-related cartilage degradation in the Elf3Tg mice at 6 and 9 months of age, indicating that increased Elf3 gene expression is not sufficient to drive OA disease. Interestingly, DMM-operated Elf3Tg mice showed increased cartilage degradation at 8 weeks after surgery.Our data showing increased ELF3 expression in human OA cartilage and in the DMM-operated mouse cartilage, and protection of 17, or to induce the expression or activity of other co-activators of ELF3, including AP-1 and NF-κB32. We showed previously that ELF3 synergizes with c-Fos/c-Jun to transactivate MMP13, and that the ELF3-induced transactivation of the MMP13 promoter in response to IL-1β in primary chondrocytes is partially mediated by activation of MEK/ERK17. In addition, ELF3 has been linked to NF-κB signaling in different gene promoters and cellular contexts, being a downstream target33, a co-factor14, and a modulator of canonical NF-κB signaling13. Thus, it is conceivable that mechanical stress activates upstream signaling pathways such as MAPKs to enhance ELF3 activity, but also upregulates other transcription factors, which could then directly or indirectly interact with ELF3 to drive gene transcription in chondrocytes. Future studies should aim to further elucidate the mechanisms of action by which ELF3 accelerates OA disease progression in vivo, by investigating whether stress-induced MAPK activation directly phosphorylates ELF3 and increases its stability, activity, subcellular location, and DNA binding capacity in vivo. Furthermore, mechanical stress could increase the expression and/or activity of ELF3’s interacting partners to drive transcription in a disease-, cell-, and/or promoter-specific manner. Our findings in vivo suggest that ELF3 is a critical transcriptional regulator of genes required for collagen erosion during the progression of OA disease. Thus, defining the downstream targets and interacting factors of ELF3 will provide valuable insight into disease mechanisms and potentially lead to the development of novel targeted therapies for OA.Together, these observations suggest that biomechanical challenge may be required to enhance ELF3 activity via mechanotransduction events that induce activating kinases of ELF3See Supplementary Information for a detailed outline of the methods, procedures and specific materials used in this study.34.All experiments were performed according to the guidelines of the American Veterinary Association and were approved by the IACUC of the Hospital for Special Surgery, and all procedures are reported following the ARRIVE guidelines35 to generate a novel Elf3f/f mouse strain , in which exons 2–8 of the Elf3 gene are flanked by loxP sites. For deletion of the floxed alleles in chondrocytes, we crossed the Elf3f/f mice with Col2a1-Cre mice37. Additional details about the generation and genotyping of the Col2a1-Cre;Elf3f/f (Elf3-cKO) mice are provided in the Supplementary Methods. For gain-of-function studies, we generated the transgenic TRE-Elf3 mice 1Mote/J; stock# 030058), that express Elf3 under the control of the tetracycline-responsive element (TRE). For this, a tet-responsive element  and a minimal CMV promoter were placed upstream of the full-length mouse Elf3 cDNA in a transgenic vector introduced in C57/BL6 embryos. To direct expression of Elf3 specifically in adult knee joints, we crossed the TRE-Elf3 strain with Comp-tTA mice21. Additional details about the generation and genotyping of ComptTA;TRE-Elf3 (Elf3Tg) mice are provided in the Supplementary Methods.For loss-of-function studies, we used a targeting vector obtained from the European Conditional Mouse Mutagenesis Program 22, in 12-week-old male Elf3-cKO and WT littermates, or 6-month-old male Elf3Tg and WT littermates. The left knees were unoperated and served as contralateral controls. At 4, 8, and 12 weeks post-surgery, animals were euthanized and the knees collected and processed, as described20. Two blinded scorers assessed OA pathology38. The data are shown as sum and max scores. Sum scores were calculated by adding the scores of 10 sections per mouse. Osteophyte size and maturity were evaluated as described26.DMM surgeries were performed, as describedt-test was used to establish statistical significance between two groups. Analysis of the histological scores was performed using Mann-Whitney test. For data involving multiple groups, one-way analysis of variance (ANOVA) was performed followed by Tukey’s post-hoc test. P < 0.05 was considered significant.Statistical analyses were performed using GraphPad Prism 7 Software . Data are reported as means ± S.D. or as median and 95% C.I.  of at least three independent experiments. Data were assessed for approximation to the Gaussian distribution using the D’Agostino-Pearson omnibus test of normality. Distributions were considered to be Gaussian if the P-value for the null hypothesis was greater than 0.05. Unpaired Student The data that supports the findings of this study are available from the corresponding author on reasonable request.Supplementary Information