The hypoxic groups were exposed in 4 cycles to 96 h of HH followed by 96 h of normobaric normoxia for 32 days. Total antioxidant capacity (FRAP) and lipid peroxidation  in plasma and reduced (GSH)/oxidized glutathione (GSSG) ratio, tissue lipid peroxidation (TBARS) and antioxidant enzymes activity were assessed at the end of the study in testis. Also, SIRTUIN 1 and HIF-1 protein expression in testis were determined.Intermittent hypobaric hypoxia (IHH) induces changes in the redox status and structure in rat testis. These effects may be present in people at high altitudes, such as athletes and miners. Polyunsaturated fatty acids (PUFA) can be effective in counteracting these oxidative modifications due to their antioxidants properties. The aim of the work was to test whether PUFA supplementation attenuates oxidative damage in testis by reinforcing the antioxidant defense system. The animals were divided into four groups (7 rats per group): normobaric normoxia ; Nx + PUFA, supplemented with PUFA (DHA: EPA = 3:1; 0.3 g kgIHH increased lipid peroxidation in plasma and HIF-1 protein levels in testis. In addition, IHH reduced FRAP levels in plasma, antioxidant enzymes activities and SIRTUIN 1 protein levels in testis. PUFA supplementation attenuated these effects, inducing the increases in FRAP, in the antioxidant enzymes activity and HIF-1 levels.These results suggest that the IHH model induces a prooxidant status in plasma and testis. The molecular protective effect of PUFA may involve the induction of an antioxidant mechanism. Humans at high altitudes are exposed to hypobaric hypoxia, a condition where reduced barometric pressure decreases oxygen availability  resultinAt high altitudes, oxidative stress is higher than at sea level under normobaric conditions, due to a combination of factors such as temperature fluctuation, increased UV light intensity and metabolic rate, low blood oxygenation and localized anoxia/reoxygenation . Due to 2+levels, the suppression of vascular proliferation, and the improvement of cell membrane integrity [Studies and clinical intervention trials have demonstrated a probable protective role of dietary fish oils and n-3 polyunsaturated fatty acids (PUFA) in cardiovascular diseases -14. The ntegrity ,20. Indentegrity . In testntegrity . HoweverTherefore, in an established rat model of IHH we hypothesized that PUFA supplementation attenuates oxidative damage in testis by reinforcing the antioxidant defense system.−1d−1) via gavage; hypoxic hypoxia  and, Hx + PUFA (n = 7). The hypoxic groups were exposed in 4 cycles to 96 h of hypobaric hypoxia followed by 96 h of normobaric normoxia for 32 days. The desired pressure inside the hypobaric chamber was achieved by pressure changes simulating altitude increases of 150 m per minute. The animals in the Nx groups were lodged in the same room as the Hx (22°C). The 4 groups received the same amount of daily food and drinking water . Body weight was determined at the beginning of the study and then every other day, and at the end of each period. The PUFA supplementation was maintained for the 32 days of the study. At the end of the study and after blood samples and tissue extraction, the rats were euthanized by cervical dislocation in a room separated from the remaining animals.All animal care and procedures complied with the principles of animal care outlined by the National Society Laboratory and the Medical Research, and the Guide for the Care and Use of Laboratory Animals , and were approved by the Faculty of Medicine’s Bioethics Committee. (Study number: CBA# 0627 FMUCH). All experiments were performed in adult male Wistar rats (n = 28). The animals were randomly divided into four equal groups: normobaric normoxia ; Nx + PUFA (n = 7), supplemented with PUFA  at 489 × +3) to ferrous iron (Fe+2) . The Fe+2-III/TPTZ-complex was detected at light absorbance 594 mm (spectrophotometer method), with a detection limit of 10 μmol/l [Plasma antioxidant capacity was assessed by measuring the ability of plasma compounds to reduce ferric  with a Potter homogenizer  at .050301 The Cu-Zn SOD assay is based on the SOD-mediated increase in the rate of autooxidation of catechols in an aqueous alkaline solution in order to yield a chromophore with a maximum absorbance of 525 nm . One GSHThe redox status in testicular tissue was assessed by a fluorometric method in order to measure oxidized (GSSG) and reduced glutathione (GSH). The o-phthalaldehyde (OPT) was used as a fluorescent reagent. This method assesses the reaction of GSH with OPT at pH 8 and of GSSG with OPT at pH 12; GSH can be complexed to N-ethylmaleimide to prevent interference of GSH with the measurement of GSSG . The GSHhttp://imagej.nih.gov/ij/) and the integrated density values of the glutathione reductase bands were normalized by dividing by the value of the loading control band.Aliquots of testis tissue homogenate of testis containing an equal concentration of proteins, 50 μg, were electrophoresed 100 V) on a 12% SDS/PAGE gel as previously described by Farias et al. [0 V on a The Shapiro–Wilk test was used for checking normal distribution of data. The results were presented as mean ± standard deviation (SD). Data were analyzed using the one-way analysis of variance (ANOVA) test followed by Bonferroni analysis. The level of statistical significance was set at p < 0.05 for all tests.vs 276.7 ± 63.4 μmol Fe-II/L) (P < 0.05). PUFA supplementation induces an improvement of antioxidant capacity, showing higher levels of FRAP in Nx + PUFA (362.8 ± 32.1 μmol Fe-II/L) and Hx + PUFA (378.3 ± 44.8 μmol Fe-II/L) (P < 0.05)  (P < 0.05). PUFA supplementation attenuates these changes in the Nx group (0.29 ± 0.15 MDA/mg prot.) and maintains these values inclusive after IHH exposure (0.37 ± 0.10 MDA/mg prot.) (P < 0.05)  (P < 0.05). After PUFA supplementation, both the Nx and Hx groups showed higher SOD and GSH-Px activity than the non-supplemented rats   (P < 0.05)  (P < 0.05). Indeed, IHH induced higher levels of TBARS in testis than those values obtained from testis samples from Hx rats supplemented by PUFA (10.7 ± 1.7 vs. 6.63 ± 1.4 nmol TBARS/mg prot.) (P < 0.05)  and systemic oxidative stress [The determinations of the time course of oxidative stress markers are important for the study of clinical models associated with IHH, such as pulmonary hypertension and obstructive sleep apnea . Increase stress ,31. Indee stress ,33. Alsoe stress ,34. In oMale Wistar rats have responded to chronic hypoxia with blood and tissue changes, resembling the human response to high altitudes, including polyglobulia and right ventricular hypertrophy . IHH leaThe hypoxia-induced transcriptional responses are highly regulated in normal development and are deregulated in many diseases . HIF-1 iRecent reports have demonstrated that PUFA are beneficial against structural brain and cardiac IR injury ,41. Alth−1d−1) was lower than the dose at which exert antioxidant effects in other organs, such as heart, brain and intestinal rat tissues [In the current study, we endeavored to explore some molecular pathways related to the induction of antioxidant responses. SIRTUIN family proteins are involved in specific aspects of metabolism and ROS scavenging proteins, and SIRTUIN-1 and SIRTUIN-3 in particular, have been exhibited effects on antioxidant enzymes activity . Some wo tissues ,49. More tissues ,51. Howe tissues  (Figure In summary, we have concluded that IHH induces a pro-oxidant state in plasma and rat testes through increased lipid peroxidation and reduced in antioxidant mechanisms. PUFA supplementation attenuated these changes by inducing the enzymatic and non-enzymatic antioxidant defense systems. This decreases the possibility of structural and functional damage that need to be characterized. The molecular mechanisms induced by PUFA and IHH in rat testis, therefore should be determined in greater detail.


Anther culture has advantage to obtain a homozygous progeny by induced doubling of haploid chromosomes and to improve selection efficiency for invaluable agronomical traits. Therefore, anther culturing is widely utilized to breed new varieties and to induce genetic variations in several crops including rice. Genome sequencing technologies allow the detection of a massive number of DNA polymorphism such as SNPs and Indels between closely related cultivars. These DNA polymorphisms permit the rapid identification of genetic diversity among cultivars and genomic locations of heritable traits. To estimate sequence diversity derived from anther culturing, we performed whole-genome resequencing of five Korean rice accessions, including three anther culture lines , their progenitor cultivar (Hwayeong), and an additional japonica cultivar (Dongjin).6 raw reads were generated with over 58× coverage that detected 1,154,063 DNA polymorphisms between the Korean rice accessions and Nipponbare. We observed that in Hwayeong and its progenies, 0.64 SNP was found per one kb of Nipponbare genome, while Dongjin, bred by a conventional breeding method, had a lower number of SNPs (0.45 SNP/kb). Among 1,154,063 DNA polymorphisms, 29,269 non-synonymous SNPs located on 30,013 genes and these genes were functionally classified based on gene ontology (GO). We also analyzed line-specific SNPs which were estimated 1 ~ 3% of the total SNPs. The frequency of non-synonymous SNPs in each accession ranged from 26 SNPs in Hwayeong to 214 SNPs in HY-04.A total of 1,165 × 10The genetic difference we detected between the progenies derived from anther culture and their mother cultivar is due to somaclonal variation during tissue culture process, such as karyotype change, chromosome rearrangement, gene amplification and deletion, transposable element, and DNA methylation. Detection of genome-wide DNA polymorphisms by high-throughput sequencer enabled to identify sequence diversity derived from anther culturing and genomic locations of heritable traits. Furthermore, it will provide an invaluable resource to identify molecular markers and genes associated with diverse traits of agronomical importance.The online version of this article (doi:10.1186/1939-8433-6-6) contains supplementary material, which is available to authorized users. Advances in genome sequencing technologies have aided in the discovery of millions of genome-wide DNA polymorphisms, single nucleotide polymorphisms (SNPs) and insertion-deletions (InDels). These are invaluable resources in analyzing genetic diversity in a population and in establishing the linkage relationship between genomes and heritable traits , which exhibited new agronomically important traits. Also, Dongjin, which is an elite cultivar in Korea, was resequenced to estimate the difference in genomic sequences between a cultivar developed from anther culturing and a cultivar developed by a conventional breeding method. Further genetic research will link sequence diversity with genic factors involved in anther culturing techniques. Also, this study confirms the idea that anther cultures provide valuable resources for developing genetic diversity and for breeding in rice.6 bps  and, on average, 61× coverage of the Nipponbare reference genome. The raw reads, which were high quality with Phred Quality Value +33 (> Q20), were used to analyze genetic variations in these five accessions .We performed whole genome resequencing of five Korean rice accessions including three anther culture lines , their progenitor cultivar (Hwayeong), and an additional Korean japonica rice cultivar (Dongjin). The sequencing results yielded 118,243 × 10Nipponbare. The mapping ratio which is a portion of reads that uniquely mapped onto Nipponbare genome in different accessions varied from 87% (207 × 106 out of 237 × 106 reads) in HY-04 to 89% (197 × 106 out of 220 × 106 reads) in Dongjin  of SNPs than BLB. They showed higher frequencies of substitutions but lower frequencies of InDels than Hwayeong and BLB. The total number of SNPs varied across on each chromosome. Over 50% of Dongjin’s SNPs were located on chromosome 11 and 12 while over 50% of Hwayeong and its anther culture derived lines SNPS were located on chromosome 8 and 11  out of 1,154,063 SNPs were found in a gene region, but only 57,146 SNPs  occurred in a coding region  was used to locate the 1,154,063 DNA polymorphisms detected between all five accessions and the n Figure . The ratn Figure  but lowen Figure .Figure 2We also analyzed whether the detected SNPs were novel SNPs or SNPs reported on the NCBI’s dbSNP. The highest percentage of novel SNPs was shown in Dongjin with only 29.48% common SNPs and 70.52% novel SNPs. The ratio of novel SNPs in HY-04 and HY-08 were nearly 4% lower than Hwayeong and BLB. In HY-04 and HY-08, chromosome 9 had the least difference between common SNPs and novel SNPs at 3.83% and 2.72%, respectively. In Hwayeong and BLB, chromosome 8 showed the least difference between common SNPs and novel SNPs  were identified. These candidate SNPs have the possibility of being associated with a unique phenotype or agronomical trait in each cultivar or line. The lsSNPs were classified as those not previously reported in the dbSNP. Unique SNPs were detected in each of these lines. It was estimated that the portion of lsSNPs is 1 to 3% of the total SNPs  were located in the coding regions. Among these 50 cSNPs, six SNPs were detected as non-synonymous SNP (nsSNPs) and 44 SNPs were synonymous SNP. The lines BLB and HY-08 carried fewer SNPs, 13 and 14, respectively, in this gene. The difference in the number of SNPs between HY-04 and BLB or HY-08 is correlated with the difference in the number of SNPs in the coding region. Only four and five cSNPs are present in BLB and in HY-08, respectively. For the Os07g0645700 gene, 54 cSNPs were detected on the CDS in HY-08 and there were 22 nsSNPs. BLB contained 40 cSNPs in the coding region but the number of nsSNPs was only three. Also HY-04 had five nsSNPs in this gene.We analyzed the five genes that had the highest number of SNPs within a genic region in each of the five accessions. The genes To estimate the functional relationship of SNPs with genes in which SNPs reside, these genes were functionally classified based on GO. When we examined gene groups that carried one or more nsSNP, we discovered that all the accessions had plenty of SNPs in genes closely related to nucleotide binding (GO:0000166) and ATP binding GO:0005524)  elements, which is a new class of miniature inverted-repeat transposable elements, are activated in cells derived from anther cultures where mPing elements are deleted from original sites and reinserted into new loci. Barret et al.  derived from Hwayeong via anther culturing. HY-08 and HY-04 have a high yielding ability and BLB has resistance to bacterial blight. These lines were subjected to whole-genome sequencing using a high-throughput sequencer. We also performed sequencing on Dongjin, which is an elite cultivar in Korea. All of the lines are in a japonica genetic background.Nipponbare as a reference genome to discover genome-wide DNA polymorphisms. The uniquely mapped reads from these accessions covered > 95% of the reference genome, providing an average coverage of 54.6× across the genome  than Hwayeong and its progenies obtained from an anther cultivar (average density of 0.45 SNP/kb). SNPs were concentrated (> 50%) on chromosome 11 and 12 of Dongjin and on chromosome 8 and 11 of the anther culture lines and Hwayeong. Among Hwayeong and its progenies, HY-04 and HY-08 had more detected SNPs than Hwayeong and BLB. Particularly the ratio of SNPs on chromosome 1 was 5 times higher in HY-04 and HY-08 than Hwayeong. HY-04 and HY-08 exhibit high yield among them, which is a distinguishable agricultural trait from Hwayeong. Based on the study of Miura et al.  in coding regions. Of these, the number of nsSNP was 5,222 (2.34%). HY-04 contained 14,829 cSNPs (5.23%) of which 7,638 were nsSNPs (2.69%)  in Hwayeong contained one or more SNPs and the total number of SNPs was 39,029, which corresponds to 7.13 SNPs per gene .The five genes that had the highest number of cSNPs in a genic region were investigated. As a result, variations were detected in genes related to immunity, such as apoptosis and signal transduction. All accessions included the genes Yamamoto et al.  clarifieThe genetic diversity between the mother cultivar and its descendants obtained from anther cultivars was analyzed by revealing DNA polymorphisms, including single nucleotide polymorphisms, insertions and deletions among the five Korean rice accessions. The analysis estimated differences in genomic sequences between accessions using the frequency and distribution of SNPs in the genome, the five genes that had the largest number of SNPs in the coding regions and lsSNPs. The lsSNPs will be useful to select candidate SNPs that could have been associated with unique phenotypes or agronomical traits in each accessions. Furthermore, DNA polymorphisms will provide an invaluable resource to identify molecular markers and genes associated with diverse traits of agronomical importance.Genomic DNA was extracted from five Korean rice accessions, including three anther culture lines , their progenitor cultivar (Hwayeong), and a Korean elite japonica cultivar (Dongjin), and prepared following the manufacturer’s protocols (Illumina). Fragments of the library were paired-end sequenced using Illumina’s Hiseq 2000. The length of all sequences generated was 101 nucleotides. In Dongjin, we performed whole-genome resequencing by two massive parallel sequencing including Illumina Hiseq 2000 and 454 GS FLX. The raw reads that were high quality with Phred Quality Values > Q20 (ASCII Character Code +33) on basis of Sanger Quality were used to analyze genetic variations in five accessions. The “Q20” value indicates an accuracy of 99% for the base called.Oryza sativa L. cv. Nipponbare was used as the reference sequence  was constructed and annotated to analyze structure and gene function.The five Korean rice accessions belong to the japonica rice variety. Therefore, dbSNP The NCBI’s SNP database (dbSNP) provides valuable information from whole-genome sequencing and Next Generation Sequencing (http://www.ncbi.nlm.nih.gov/projects/SNP/).Nipponbare using CLC Assembly Cell  with the following parameters: alignment mode, local; similarity, 95%; HSP coverage 100%; gap cost, 3; deletion cost, 3; and mismatch cost, 2. SNPs were detected by comparison alignment with the Nipponbare sequence as a reference. To classify whether mismatches were sequencing errors or genomic variations, parameters were set as follows: minimum depth, 30; minimum variant frequency, 35%; least mismatch count, 20; and homo/heterozygote fold change, 2. RAP-DB was utilized to locate the discovered SNPs. SNPs were annotated as genic and intergenic based on positional information from the genome. DNA polymorphisms in genic regions were classified as coding sequence (CDS), untranslated regions (UTRs), and introns. DNA polymorphisms in the coding region were separated into synonymous SNPs and non-synonymous SNPs by amino acid substitutions. Also, SNPs were classified into two types, homozygous and heterozygous SNPs, based on the mismatch frequency if more than two bases shared the identity position.A large number of paired-end reads were assembled on to genomic sequences of the japonica rice cultivar O. sativa provided on dbSNP is based on genome build 3. We redefined the SNP position information based on build 5. To update the refSNP to genome build 5, we reconstructed the refSNP position information based on 4,521,605 refSNPs reported in dbSNP  position information of http://www.geneontology.org/). Finally, the lsSNPs were classified as those not previously reported in the dbSNP. Unique SNPs were detected in each accession.To estimate the functional relationship of the SNPs with genes, we performed the three analyses. First, the five genes that had the highest number of SNPs within a genic region were selected and the functions of genes were compared between each accession. Second, genes were functionally classified based on Gene Ontology  under the accession numbers; Dongjin , Hwayeong [ERP001620], BLB [ERP001655], HY-04 [ERP001653], HY-08 [ERP001654].The resequencing data from the five Korean rice accessions have been submitted to EMBL-EBI (IS, UH, GS, HS, HJ, JH, TH: Genomics Division, National Academy of Agricultural Science, Rural Development Administration, Suwon 441–707, Republic of Korea. CD: Department of Biochemistry, Gyeongsang National University, Jinju 660–701, Republic of Korea. GA: Department of plant molecular systems biotechnology and Crop biotech institute, Kyung Hee university, Yongin 446–701, Republic of Korea.


Increasing food production is essential to meet the demands of a growing human population, with its rising income levels and nutritional expectations. To address the demand, plant breeders seek new sources of genetic variation to enhance the productivity, sustainability and resilience of crop varieties. Here we launch a high-resolution, open-access research platform to facilitate genome-wide association mapping in rice, a staple food crop. The platform provides an immortal collection of diverse germplasm, a high-density single-nucleotide polymorphism data set tailored for gene discovery, well-documented analytical strategies, and a suite of bioinformatics resources to facilitate biological interpretation. Using grain length, we demonstrate the power and resolution of our new high-density rice array, the accompanying genotypic data set, and an expanded diversity panel for detecting major and minor effect QTLs and subpopulation-specific alleles, with immediate implications for rice improvement. Understanding the link between genotype and phenotype can facilitate efforts by breeders to utilize natural variation and develop new crop varieties. Here the authors present a diverse germplasm collection, a high-density genotyping array and a set of bioinformatic tools to enable association mapping in rice. Oryza sativa) is a staple food that feeds 3 billion people1567de novo assemblies within three subpopulations910Oryza speciesRice (Genome-wide association studies (GWAS) offer a powerful strategy for understanding the genetic basis of complex traits. This approach has been particularly productive for rice, where major associations have been detected for important traits, including grain size, grain weight, flowering time, disease resistance and abiotic stress tolerance, among others13141517182021O. rufipogon, is a partially (35%) outcrossing species complex broadly dispersed across tropical South, South-East and Eastern Asia. It consists of locally or regionally adapted subpopulations with both perennial and annual formsO. sativa began ∼10,000–12,000 years ago, and human selection was accelerated by inbreeding which retained and fixed many favourable alleles of large effect. The unique combinations of locally adapted allele complexes in different subpopulations provide ideal characteristics for GWAS, including both universal and population-specific large effect alleles, extended linkage disequilibrium (LD) within some subpopulations that is advantageous for mapping with low marker coverage, rapid LD decay within other subpopulations offering improved mapping resolution and an abundance of well-partitioned genetic variation among subpopulations. These properties, in combination with a small, tractable genome (380 Mb), and the ability to produce immortal panels comprised of thousands of inbred, homozygous individuals, make it possible to evaluate the same traits in different environments simultaneously, and to evaluate a variety of different traits on the same germplasm over time. The ability to make controlled matings and to generate large populations each generation provides a powerful system for validating loci and for harnessing their value by introgressing favourable alleles into other genetic backgrounds.Rice has been particularly amenable to GWAS largely because of its evolutionary and domestication history. The wild ancestor of Asian rice, Here, we report the development of an association mapping panel consisting of 1,568 diverse inbred rice varieties and a genotyping data set generated using a high-density rice array (HDRA) comprised of 700,000 single-nucleotide polymorphisms (SNPs). The HDRA represents the most densely populated genotyping array available for any organism at this time, based on the number of SNPs/kb interrogated across the genome. We explore the value of these resources for GWAS using grain length as the phenotype, and use numerous analytical techniques to identify significant associations that uncover both major and minor QTLs. Further, we demonstrate distinct advantages of cross-population mapping where we gain power by directly accounting for large effect alleles from within the mapping model. We show how this may lead to the identification of population-specific haplotypes, which are of particular value to the plant breeder.et al.2526The GWAS resources and data sets generated in this project are designed to facilitate the collection of phenotypic information on a wide range of traits and characteristics , while 55% of SNPs map to intergenic regions , or ∼1 SNP every 0.54 kb across the rice genome. It was designed to efficiently capture most of the haplotype variation observed in a discovery panel consisting of 16M SNPs (generated by sequencing 125 rice genomes at ∼7 × genome coverage) and to maximize the inclusion of non-synonymous SNPs see . An esti regions . Non-syn regions , are fouO. sativa , with aus and indica comprising the INDICA varietal group, and tropical japonica, temperate japonica and aromatic comprising the JAPONICA varietal group151629INDICA and JAPONICA, and lower-case letters to indicate subpopulations.) Using a cutoff of 70% ancestry, accessions were classified into one of the five major subpopulation groups, or into one of three admixture classes: admixed INDICA (aus-indica), admixed JAPONICA  or admixed INDICA-JAPONICA , the second PC separates the aus and the indica subpopulations (10.44%), while the third PC separates the three JAPONICA subpopulations (6.06%). LD decays rapidly with distance in all populations , has been cloned and characterized and the most common functional polymorphism is a C≥A transition that occurs in the second exon of the gene. Using genetic transformation, Takano-Kai et al.O. sativa, making them unlikely to be detected using GWASIn this study we investigated the potential to resolve both major- and minor-effect GWA-QTLs using the new HDRA genotypic data set and grain length as a phenotype. Grain length is a highly heritable phenotype, with broad sense heritability of 0.976. A major QTL for grain size was previously identified on rice chromosome 3 in a number of studies across different genetic backgrounds and environments34GRAIN WIDTH 5 (GW5) and GRAIN SIZE 5 38GW5, the functional polymorphism is a 1,212 bp deletion in the reference genome (cv. Nipponbare) that removes the only exon of the gene, resulting in a short, wide, heavy grain38GS5, polymorphisms in the promoter region leading to differential gene expression were associated with grain size4142434445464748495051525354Rice chromosome 5 carries two closely linked genetic loci associated with grain size that have been positionally cloned and functionally characterized, namely P value=4.48e−17, while when RDP1 and 2 are used, the MS-SNP is detected at P value=1.48e−55 and explains 15.9% of the variation  and 16.8 kb (SNP 3.16712500) upstream of the transcriptional start site of GS3, and explain 6% and 5.8% of the phenotypic variation, respectively ALL with two SNP covariates  as co-variates in the GWA models. When all samples were evaluated together, additional peaks were detected on all 12 rice chromosomes, with the most significant located on chromosome 10 . The MS-variates .INDICA (aus+indica+admixed aus-indica) and JAPONICA  located within a 100-kb window on either side of the MS-SNP. The functional SNP in the GS3 gene (SNP 3.16732086) on chromosome 3 was consistently identified as the MS-SNP with the highest PVE and allele effect in all analyses, while on chromosome 5, different but closely linked SNPs (mapping within ∼12 kb of each other) identified the same peak in different analyses  and both of the peaks detected in JAPONICA were also identified in ALL, but no peaks were shared between INDICA and JAPONICA. This can be explained by the differences in allele frequencies, allele effects and per cent variance explained by the SNPs associated with grain length in each group.We also performed GWAS independently for the two varietal groups, analyses . When thanalysis . One of indica and tropical japonica subpopulations, the two major peaks on chromosomes 3 and 5 were clearly visible, while in aus, a minor peak was identified several kb away from GS3 and no peak was observed near GW5. In temperate japonica, a very wide peak was observed 1.4 Mb to the left of GS3 along with a minor peak at GW5. These results suggest the possibility that different causal genes in the GS3 region may contribute to the observed phenotypic variation in the aus and temperate japonica subpopulations. When SNP covariates were applied to the subpopulation-specific analyses, we discovered additional minor peaks associated with grain length in each. Notably, aus had twice as many significant minor peaks as indica ; PGL1 encodes an atypical non-DNA-binding bHLH that interacts in vivo with ANTAGONIST OF PGL1 (APG) and increases grain length and weight in transgenic rice. PGL1-APG potentially represents a new grain length- and weight-controlling pathway56aus co-localizes with qLWR2, a QTL for length-to-width ratio detected in a cross between an indica and a japonicaALL and in tropical japonica co-localizes with a fine-mapped QTL (qGL7) controlling grain length, also detected in an indica X japonica crossaus is located in-between the candidate genes APGSGL/SRS344Short Grain Length (SGL) is the causal gene of a small and round seed mutant  and encodes a protein member of the kinesin 13 family. On chromosome 8, a peak detected in ALL as well as in the aus subpopulation co-localizes with the grain size gene GW8/OsSPL16 In many cases, GWAS peaks were found to encompass previously described genes or QTLs associated with grain length or shape . A minorL16 ref. . This geGS3) and SNP-5.5371749 (GW5) as covariates. We detected a significant interaction between the MS-SNP at GW5 and several SNPs in a ∼100 kb region on chromosome 4 (P=1.86e−21), while no significant interactions with GS3 were identified. The chromosome 4 region showed no significant effect on grain size when tested independently, only as an interaction. The minor allele frequency (MAF) for the most significant epistatic-SNP (SNP-4.4260961) is 10% across all subpopulations; it is essentially fixed in aus, indica and temperate japonica and segregates only in tropical japonica (MAF=24%). This suggests that both epistasis and differences in allele frequency contribute to the distinctive genetic architectures associated with grain length in the different subpopulations. The SNPs with significant P values for the GW5 interaction define a region on chromosome 4 containing 14 genes. Among these, the most notable is a gene encoding a C2H2 zinc-finger transcription factor . Further investigation on the potential impact of this gene (or region) on grain length is warranted.To determine whether the major genes on chromosomes 3 and 5 interact epistatically with other loci, we performed a covariate vs SNP interaction scan using SNP-3.16732086 (GS3 region was observed in the aus subpopulation (aus (SNP-3.16709886) is located 18 kb to the left of GS3 (GS3 (SNP-3.16732086) is fixed for the wild-type allele in aus, and therefore not significant. The aus MS-SNP-3.16709886 is also significant in ALL and in joint INDICA when SNP-3.16732086 (the GS3 FNP) is included as a covariate in the GWAS model  confer shorter grain34aus MS-SNP is associated with longer grains  based on HDRA genotypes for the 1,146 rice lines phenotyped for grain length . The most common temperate japonica haplotypes, EH1 and EH2 (83%) carry the wild-type allele at SNP-3.16732086, the common tropical japonica haplotypes, EH7, EH6 and EH5 (87%) carry the derived (long grain) GS3 allele . The mutation marked by SNP-3.16732086 is known to have occurred in a japonica background then introgressed into indica (EH7 and EH18), but it is notably rare in aus and was not observed in any of the aus varieties in our panel.Our GWAS results point to a potentially novel source of variation in or near n length . The EHsaus haplotype is EH10 (62%) and the common indica haplotype is EH19 (40.9%). Two aus accessions carry the common japonica haplotype EH1, 12 accessions carry EH3 and two carry the recombinant EH9 haplotype, while 40 additional aus varieties are distributed among seven aus-specific haplotypes: three with the derived allele at SNP-3.16709886 (EH15/16/17) and four with the wt allele (EH11–14). These seven haplotypes are similar to EH3, but are differentiated by specific recombination break points within the aus background. Varieties carrying EH15/16/17 have significantly longer grains than those carrying the common aus haplotype EH10  also carry a second SNP . The third MS-SNP  that assays one SNP approximately every 0.54 kb across the rice genome and is enriched for SNPs in and around genes.In terms of SNP density, the HDRA offers more SNPs per kb than the highest density commercial human genotyping array  and surpasses the largest publicly available genotyping platform in any crop species, namely a maize array with 600,000 SNPs, or 1 SNP per 4 kb ref. . While a5The ability to identify both large- and small-effect QTL associated with a phenotype of interest is of great interest to breeders. By including the most significant SNP(s) from each experiment as a covariate(s) in the GWA model, we demonstrate our ability to identify both common and subpopulation-specific alleles. The high heritability of grain length suggests that this trait may be conditioned by only a few genes of large effect, but the range of variation for grain size detected in this collection of germplasm (4.2–7.3 mm) and the combination of both natural and artificial selection that have influenced trait expression in different subpopulations and environments, hint at greater complexity. Here, we demonstrate that, in addition to well-characterized genes of large effect, our approach allows for the detection of numerous genetic factors of small effect that contribute to the highly valued grain quality characteristics that distinguish local rice varieties, supported by the fact that several peaks co-localize with known QTL regions and candidate genes related to grain shape and/or size. In cases where well-characterized grain size genes do not co-locate with GWAS peaks, it is presumably because the functional alleles at these loci occur at low frequency in our diversity panel, or have immeasurably small allele effects in the context of other loci segregating for grain length. GWAS peaks identified in regions where no QTL for grain size has been mapped to date provide new opportunities for gene discovery.temperate japonica varieties that have near universally short, wide grains and are adapted to cooler seasons and the long days of higher latitudes. Long, slender grains are preferred in South Asia and parts of South East Asia where indica varieties are grown; short, thin grains are prized in traditional aus-growing regions such as Bangladesh and southeastern parts of India, and very long, thin, aromatic grains are the specialty of the basmati and sadri-growing provinces of India, Pakistan, Afganistan and Iran58Grain length is one of many traits for which different cultures and commercial markets show strong and often opposing preferenceset al.In a companion paper by Crowell In addition to the SNP data set, genetic resources and analytical strategies presented here, we have also developed a suite of bioinformatics tools to facilitate the analysis of GWAS data . These tindica, 13% aus, 25% temperate japonica, 25% tropical japonica, 3% aromatic and 18% admixed accessions; the RDP2 consisted of 35% indica, 11% aus, 12% temperate japonica, 23% tropical japonica, 2% aromatic and 17% admixed accessions; the NIAS panel consisted of 39% indica, 23% aus, 15% temperate japonica, 5% tropical japonica, 0% aromatic and 18% admixed accessions (The germplasm collections from which accessions used in this study were drawn are summarized in 166162cessions .http://irri.org/our-work/seeds), (ii) the USDA-ARS National Small Grains Collection (NSGC), Aberdeen, ID, USA, which is part of the National Plant Germplasm System (www.ars-grin.gov/npgs) and (iii) the NIAS Genebank in the National Germplasm Collection in Tsukuba, Japan (http://www.gene.affrc.go.jp). Because of the observed heterogeneity in the gene bank accessions, all materials were purified for two generations via single seed descent before genotyping. The purified lines analyzed here can be considered representative haplotypes from the original, heterogeneous landrace accessions available in the gene banks.Seeds were originally obtained from (i) the International Rice Genebank Collection at the International Rice Research Institute (IRRI) in the Philippines . All locations of exons, introns and UTR regions from the MSUv7 gene annotation were extracted using Galaxy's Gene BED To Exon/Intron/Codon tool. Assignment of SNPs to the extracted genomic features was determined by detecting overlaps with each feature's locus using the UCSC Browser's liftOver tool (https://genome.ucsc.edu/util.html). For those SNPs that overlapped an exon, further analysis was done using Galaxy's Amino Acid changes (aaChanges) tool in order to determine the character  of each SNP's induced mutation. A script written in Python was used to merge and integrate all the results from the previous steps and assign each HDRA SNP to one or more functional categories. SNPs were classified as UTR5, UTR3, exonic, intronic based on overlap with the regions of the same name. In addition, SNPs were assigned to PPRs defined as segments within 2 kb upstream from the transcription start site. SNPs overlapping the PPRs were determined as described above. Since many SNPs were associated with more than one putative function, precedence was established for assigning SNPs to a primary category for counting purposes. The primary category was assigned using a Python script that assigned SNPs in the following priority order: exonic, intronic, UTR (5′/3′), PPR. The primary category assignment for each SNP was used as the basis for the rest of the functional analyses.A total of 66,152 gene models were downloaded from the MSU Rice Genome Annotation Project version 7 in GFF3 format. Data were converted to the UCSC Browser's BED format and then uploaded to a local instance of the Galaxy Project bioinformatics server  by applying the svd function in the R software packageALL) as well as for INDICA and JAPONICA varietal groups. Since we do not have an outgroup, we plotted only minor allele frequencies, thus the frequency values do not exceed 0.5 on the plots , we identified lines that belonged unambiguously to each group based on FastSTRUCTURE results (>70% ancestry). We discarded SNPs with >33% missing data and with fewer than three individuals carrying the minor allele. The samples consisted of 469 individuals  from indica; 170 individuals  from aus; 356 lines  from tropical japonica; and 229 lines  from temperate japonica. We moved 4,000-SNP windows along each chromosome. In each window, we calculated LD between all pairs of markers, using only lines with pairwise complete data. As measures of LD, we calculated r2 (the square of the correlation coefficient between SNP states) and the absolute value of D' r2. As we calculated LD, we noted the distances between SNP markers. We then assigned the distances to 500 bins and calculated mean LD within each band of distances.To assess LD among SNP markers in each of the Three replicates of the complete set of samples were grown in the 2011 wet season in IRRI fields in the Philippines, using standard crop management practices for irrigation and pest control. A subset of 129 accessions that spanned the range in grain lengths observed during 2011 was also grown during the dry season of 2012 at IRRI and grain length measured on these varieties was used to estimate broad sense heritabilityσ2 is the experimental error variance, r is replicates and e is environments. For both the full set (2011) and the subset (2012), grain was harvested at maturity and stored for 6 weeks under controlled relative humidity, to equilibrate for moisture content. A sample of paddy (10 g) was dehulled , and polished by placing grains into 10 ml capsules with fused aluminium oxide and then abrading gently for 1 h in a paint shaker. Grain length was measured on an average of 75 individual grains from each of three biological replicates, with a Cervitec Grain Inspector 1625 . A significance threshold of 10% false discovery rate  for every test as well as the additive genetic variance explained (without the random effects term). For total fixed effect genetic variance explained (relevant when two or more marker terms are included—see below), we extracted the residuals from an initial model fit with dummy marker terms substituted with random genotypes to produce the same degrees of freedom as each model of interest and calculated the variance. We subtracted this from the phenotypic variance to get the variance explained by the kinship matrix random effects term. In the model tests including fixed genetic effect terms, we subtracted this value from the total model variance explained to obtain the variance explained by the additive genetic effects of the markers. In the additive linear mixed model genotype variables were coded as AA=−1, AB=0, BB=1. Allele effects correspond to the regression coefficient. This is the expected absolute change in grain length for each B (non-reference) allele with twice this value equal to the expected grain length difference between the BB and AA homozygotes. This corresponds to the standard additive effects quantitative genetic model, where the dominance deviation d is constrained to be d=0 (co-dominant locus).To calculate PVE and report this for all tests in the EMMAX results, we modified EMMAX C source code to perform this calculation using the model term variance that EMMAX already extracts to conduct the P value and PVE were reported for these terms in every test as well as these values for the scan marker. As expected, fixed terms specified in this way generated similar allele effects, P values and PVEs as they did in their single marker test in the initial GWAS scan. Finally, we tested interactions of scan markers with these fixed covariate terms by modifying EMMAX source to calculate an epistatic interaction term as −1 for AA/AA, 0 for AA/BB and BB/AA and +1 for BB/BB; and 0 for any combination including a heterozygote genotype. This interaction term, as well as the independent effect term(s) for the specified markers, was inserted into the mixed-model fixed effect matrix . As with the independent covariate SNP terms, interaction effect size, P value and PVEs were output for all genome-wide tests.To perform a GWAS analysis for possible epistatic interaction effects with SNPs detected as highly significant in our single-marker scans, we modified further modified the EMMAX to allow specific markers to be specified on the command line as fixed model covariates. The modified EMMAX would then select these markers out of the input data and include the genotypes at these SNPs (more than one may be specified) as additive fixed-effect independent model terms in addition to markers being tested one-by-one in the genome-wide scan (the ‘scan marker'). Allele effect size, GS3 and the aus-specific peak in the region were constructed on the 1,146 O. sativa accessions from RDP1 and 2 genotyped with the HDRA and phenotyped for grain length. The HDRA carries a total of 424 total SNPs in the 190 kb region. SNPs with a MAF>0.05 and <3% missing data were initially selected. SNPs were then filtered based on a frequency test; only SNPs with a significant frequency difference between the INDICA and JAPONICA varietal groups . The final set of SNPs used in constructing the haplotype map in EHs spanning a 190 kb region flanking Accession codes: SNP information has been deposited in the NCBI dbSNP database (batch ID 1062024) and the GEO database (accession ID: GSE71553).How to cite this article: McCouch, S. R. et al. Open access resources for genome-wide association mapping in rice. Nat. Commun. 7:10532 doi: 10.1038/ncomms10532 (2016).Supplementary Figure 1-5, Supplementary Tables 1-2 and Supplementary ReferencesRDP1&2 germplasm collection. “This table presents the entire RDP1 and RDP2 collections, a subset of which (denoted with the presence of a HDRA assay id in the third column) were genotyped using the HDRA. Detailed column descriptors can be found under the table.Summary of SNP polymorphisms for each rice diversity panel and subpopulationP values, allele effects and percent variance explained (PVE) for the most significant SNP in each GWAS peak identified with and without SNP covariatesList of candidate genes, loci and QTL regions mapped for grain length, weight, or other grain shape traits, included in our analysisRaw genotype data (HDRA SNPs) in the region of the aus-specific peak. This was the raw data used in the construction of the haplotype map in Figure 6.GWAS Pipeline


Oryza sativa L.) is the staple food of more than half of the world’s population. The identification of genetic diversity in local varieties of rice compared with that of improved or introduced varieties is important in breeding elite varieties for sustainable agriculture. Array-based single nucleotide polymorphism (SNP) detection is a useful technique for such studies and breeding applications.Rice  and genetic diversity. Analysis of molecular variance showed that 90.61 % of genetic variation was a result of differences within sub-groups.We developed a 5291-SNP genome-wide array and used it to genotype 471 Our results revealed that SNP analysis clustered local varieties, introduced varieties, and improved varieties into three clear sub-groups. The distribution of parameter PIC values on sub-group genomes revealed that genetic differentiation among them might not be on a genome-wide scale, but rather on selected loci or chromosomal intervals. The result of Gene Ontology enrichment analysis showed that genes nearby those selected SNPs associated different molecular functions or various traits among sub-groups.The online version of this article (doi:10.1186/s12863-016-0361-x) contains supplementary material, which is available to authorized users. Oryza sativa L.) is the staple food for more than 3.5 billion people worldwide, which represents around half of the world’s population. Importantly, rice is the staple food in China and throughout Asia. Tracing back the history of rice breeding in China, several different stages of development can be observed: (1) the beginning of systematic rice breeding in 1919; (2) the use of pure line selection as the most common method of breeding from the 1920s to the 1940s; and (3) extensive national cooperation in rice breeding involving various effective breeding methods, such as the use of local varieties as parents, and the introduction of foreign varieties after 1949 , encoding the polycomb repressive complex2 (PRC2) key subunit together with SDG711, and the PRC2-mediated epigenetic repression of gene expression was shown to be involved in the accurate photoperiod control of rice flowering . These SNPs were then associated with cloned genes in the Rice Data Center [http://www.ricedata.cn/gene/], and 187 SNPs were found to be cloned or reported.Out of 5291 SNPs, 3787 located within a 1 kb region and with aliases starting with “LOC_Os” coordinates were found by BLAST analysis of the MSU6.0 annotation of the genome of Nipponbare  and an ad hoc statistic ΔK [O and genetic variation within and among different populations were evaluated using AMOVA implemented in Arlequin suite v3.5 [r2) was computed using TASSEL v4.0 [We conducted individual level PCA using NTSYS-pc v2.1 software  to inveser v3.25 . A modeler v3.25 , 30. Theistic ΔK  were useite v3.5 . The LD SEL v4.0  to evaluAll relevant data are available within the manuscript and its additional files.


Ictalurus punctatus). A total of 8.4 million candidate SNPs were identified by using next generation sequencing. On average, the channel catfish genome harbors one SNP per 116 bp. Approximately 6.6 million, 5.3 million, 4.9 million, 7.1 million and 6.7 million SNPs were detected in the Marion, Thompson, USDA103, Hatchery strain, and wild population, respectively. The allele frequencies of 407,861 SNPs differed significantly between the domestic and wild populations. With these SNPs, 23 genomic regions with putative selective sweeps were identified that included 11 genes. Although the function for the majority of the genes remain unknown in catfish, several genes with known function related to aquaculture performance traits were included in the regions with selective sweeps. These included hypoxia-inducible factor 1β· HIFιβ ¨ and the transporter gene ATP-binding cassette sub-family B member 5 (ABCB5). HIF1β· is important for response to hypoxia and tolerance to low oxygen levels is a critical aquaculture trait. The large numbers of SNPs identified from this study are valuable for the development of high-density SNP arrays for genetic and genomic studies of performance traits in catfish.Domestication and selection for important performance traits can impact the genome, which is most often reflected by reduced heterozygosity in and surrounding genes related to traits affected by selection. In this study, analysis of the genomic impact caused by domestication and artificial selection was conducted by investigating the signatures of selection using single nucleotide polymorphisms (SNPs) in channel catfish ( Strong selection can lead to significant allele frequency shifts with alleles directly affecting a trait reaching high frequencies. Due to genetic linkage, alleles nearby on the chromosome also change in frequency, leaving signatures of a selective sweep Gasterosteus aculeatus) Salmo salar) In contrast, hard selective sweeps can be readily detected as they result in an increase of a specific allele, and hence, are more useful for the detection of genes underlining the performance traits. Studies of selective sweeps due to domestication in teleost fish are limited because most selective breeding of fish has been in the last 50 years, and there are few active selection programs for fish. Selective sweeps have been identified from fish species such as three-spined stickleback (Oncorhynchus mykiss) Danio rerio) Lepomis gibbosus) Salmo trutta) et al.Ictalurus punctatus).Domestication is one kind of selection involving the removal of some selection pressure typical of natural environments but intensification of others relevant to farming conditions Genomic impact of domestication has not been well studied in fish species. Previous studies have shown morphological, behavioral and growth changes in channel catfish during domestication Molecular markers have been developed from catfish All procedures involving the handling and treatment of used fish during this study were approved by the Auburn University Institutional Animal Care and Use Committee (AU-IACUC) prior to initiation of the project. A total of 150 channel catfish, with 30 individuals from each of Marion, Thompson, USDA103, one outbred commercial strain (hereafter referred to as Hatchery), and one wild population were used for this study. The four aquaculture strains were from different geographic locations within the United States, which possess different production traits such as growth rate, disease resistance and feed conversion efficiency The fish were euthanized with tricaine methanesulfonate (MS 222) at 300 mg/l before blood collection. For each individual, 500 µl blood was collected for DNA isolation, placed into 5 ml lysis buffer immediately, and then into a water bath at 55°C for 12 h. Total DNA was isolated using the DNeasy Blood & Tissue Kit  following the manufacturer's protocol. Equal amounts of DNA (100 µg) from each individual were pooled for sequencing, one pool for each strain.http://www.ncbi.nlm.nih.gov/sra).Sequencing was conducted commercially at HudsonAlpha Genomic Services Lab . Genomic libraries were prepared with the Paired-end Sequencing Sample Preparation Kit  with 5 µg of genomic DNA for all strains, according to the manufacturer’s instructions. For each strain, the prepared DNA library was sequenced on one lane of the Illumina HiSeq 2000 platform for 100-bp paired-end reads. The short reads were deposited in the NCBI Sequence Read Archive (SRA) under Accession number SRA075234 (N = P(A)-P(Q), where A is the criterion of the minimal quality score. In this project, A = 20 (Phred score); Q is the Phred quality score of each base. This value would be negative for bases with quality scores below 20. For every base, the software calculated the running sum of this value. The part of the sequence not trimmed will be the region between the first positive value of the running sum and the highest value of the running sum. Everything before and after this region was trimmed.Sequence mapping was performed using CLC Genomics Workbench . Before mapping, raw sequence reads were trimmed to remove adaptor sequences, ambiguous nucleotides (N’s), extreme short reads (<30 bp) and low quality sequences  using CLC Genomics Workbench. The quality of each sequence was assessed as follows: First, convert Q  was converted to an error probability (P):The clean reads from each strain were then aligned with the preliminary catfish genome assembly (unpublished data). The mapping parameters were set as: mismatch cost of 2, deletion cost of 3 and insertion cost of 3. The highest scoring matches that shared ≥95% similarity with the reference sequence across ≥90% of their length were included in the alignment. The mapping output was converted into BAM format www.animalgenome.org/repository/pub/auburn2014.0530/).SNPs were identified from the pooled data from all the strains using the SAMtools (version 0.1.18) SNPs with significantly different allele frequency ratios were identified between domestic catfish strains and the wild population (hereafter referred to as significant SNPs). Two-tailed Fisher’s exact test was performed with the statistical significance level of false discovery rate corrected P value ≤0.01. Significant SNPs were categorized into three groups based on their location: 1) in the coding regions, 2) near the coding regions and 3) on non-coding regions. Near the coding regions means the SNP is located on non-coding regions but within 100 bp from the coding regions.Hp) score was calculated using the formula Hp = 2ΣnMAJΣnMIN/(ΣnMAJ + ΣnMIN)2nMAJ was the sum of the major allele reads, and ΣnMIN was the sum of the minor allele reads for all significant SNPs in one window. The Hp score was calculated based on 20 kb sliding window across the genome. Windows with less than five significant SNPs were not used for calculation. Putative selective sweeps were identified from windows with −log2(Hp) score ≥4.With the availability of significant SNPs, genomic regions with selective sweeps were identified from the four domestic strains by detecting the genome regions with extremely low heterozygosity. The pooled heterozygosity  not only affects the SNP applicability for future genetic studies because it directly determines the polymorphism information content of the SNP markers, but MAF also has an impact on the identification of quality SNPs. In general, the relationship curve can be arbitrarily divided into two phases: In the first phase, when minor allele counts were set as 2–4, the total number of SNPs was reduced sharply, while in the second phase, when minor allele reads were set as greater than 4, the total number of SNPs was also reduced, but at a much reduced rate, suggesting that minor allele reads of 4–6 may be appropriate for data in the present work . Thus, tIn addition to the initial assessment of these factors, the percentage of sequences that were included for SNP identification were examined. As shown in A total of more than 13 million potential single nucleotide variations were observed at the most relaxed set of criteria, i.e., minimum read depth of 20, maximum read depth is set as excluding the top 2% of all reads, and minor allele read counts of 2. At our selected set of criteria, a total of 8,395,720 (∼8.4 million) putative SNPs (hereafter referred to as SNPs) were identified .These 8.4 million SNPs were subsequently used for the assessment of the distribution of minor allele frequencies. The MAF of each identified SNP was estimated based on the reference number and variant allele reads observed in the reference mapping. Approximately 4 million SNPs have an estimated MAF ≤10% . Over 4.Putative SNPs identified from each of the five strains were shown in SNPs that were observed from only one strain were considered as putative strain-specific SNPs. SNPs that were polymorphic in all strains were considered as common SNPs. Approximately, 2.7 million common SNPs were identified. The number of strain-specific SNPs identified from each of the five strains varied from 66,487 to 143,126, accounting for 0.9%, 2.9%, 2.2%, 1.3%, and 1.7% of SNPs that were identified from that strain, respectively .As shown in A total of 237,655 (58.3%) significant SNPs were assigned to 29 tentative chromosomes based on the catfish linkage map pH) was calculated in 20-kb windows based on the major and minor alleles of significant SNPs, and were then log transformed. Most of the windows (73.5%) had the log-transformed pH scores between 1 and 1.5, indicating high levels of heterozygosity  had the most significant pH score, which was followed by ATP-binding cassette sub-family B member 5 (ABCB5).A total of 11 genes were found from these genomic regions with selective sweeps . These gIn this study, next generation sequencing was conducted for multiple individuals from four aquaculture strains and one wild population to identify SNPs for determination of genomic impact of domestication. The large numbers of SNPs identified from this study will be useful for the development of high density SNP arrays for genetic and genomic analysis in catfish Pooled sequencing has been utilized as an efficient and reliable approach for detecting and genotyping SNPs from populations In that regards, reasonable criteria for SNP identification were set at a minimum read depth of 30, maximum read depth of 300, and minor allele count of 5, and 8.4 million putative SNPs were identified from five different catfish strains. On average, there was one SNP every 116 bp in channel catfish genome. Approximately, 66,000–143,000 SNPs were identified as strain-specific for each strain , which iet al.Liu SNPs with significant differences in allele frequency between domestic and wild catfish populations were identified to provide insight into genomic impact of domestication and selection. Compared with all the SNPs identified from channel catfish, significant SNPs were approximately 5% of the total SNPs, indicating that the vast majority of genomic regions have not been affected by domestication or selection. Additional analysis was conducted to determine the position and genes associated with significant SNPs. The vast majority of significant SNPs (87.2%) were located in the non-coding DNA sequences, while 12.8% of the significant SNPs were found in coding regions of catfish genes. This proportion of SNPs associated with genes is greater than the proportion of gene sequences from the whole genome sequences, suggesting that domestication and selection may have had a greater impact on genes than on intergenic regions.The significant SNPs were distributed on each of the catfish chromosomes . ChromospH scores) for the domestic populations using significant SNPs with the assumption that artificial selection by domestication tends to create runs of homozygosity A concern regarding the analysis of channel catfish was sampling since this species occupies a large geographical range, populations can be large and numerous domestic and wild populations exist. Assuming that all domesticated populations and a broad representation of wild populations can be achieved, significant SNPs between the domestic and wild populations could be used to reveal solid selective sweeps caused by domestication and selection. However, based on the nature of catfish industry, it is difficult to sequence large enough samples that can represent all genetic variations that exist in all domestic and wild strains. Therefore, we fully acknowledge the difficulties involved in the sampling of the domestic and wild populations for an aquatic species, however, analysis of putative selective sweeps should still provide insights into the potential impact of domestication on genome evolution. To identify hard type selective sweeps in domestic catfish caused by selective breeding, we analyzed the pooled heterozygosity  and ATP-Binding Cassette, Sub-Family B, Member 5 (ABCB5), were located in the first two strongest hard sweeps , mediates aryl hydrocarbon signaling and facilitates gene activation by dimerization with aryl hydrocarbon receptor (AHR) In the present study, we identified 11 genes from 9 of the 23 genomic regions with selective sweeps . Two gend sweeps . HIF-1β ABCB5 is a member of ATP-Binding Cassette transporter gene family and only exists in vertebrates ABCB5 was also significantly associated with tumor progression and recurrence, acting as an energy-dependent drug efflux transporter and function during the multidrug resistance process ABCB5 gene that was exclusively associated with childhood obesity ABCB5 was located in the second strongest selective sweep region Click here for additional data file.


Some variations of human genome  are markers of hereditary diseases and drug responses. Analysis of them can help to improve treatment. Computer-based analysis of millions of SNPs in the 1000 Genomes project makes a search for SNP markers more targeted. Here, we combined two computer-based approaches: DNA sequence analysis and keyword search in databases. In the binding sites for TATA-binding protein (TBP) in human gene promoters, we found candidate SNP markers of gender-biased autoimmune diseases, including rs1143627 [cachexia in rheumatoid arthritis ]; rs11557611 [demyelinating diseases ]; rs17231520 and rs569033466 [both: atherosclerosis comorbid with related diseases ]; rs563763767 [Hughes syndrome-related thrombosis ]; rs2814778 [autoimmune diseases (excluding multiple sclerosis and rheumatoid arthritis) underlying hypergammaglobulinemia in women]; rs72661131 and rs562962093 (both: preterm delivery in pregnant diabetic women); and rs35518301, rs34166473, rs34500389, rs33981098, rs33980857, rs397509430, rs34598529, rs33931746, rs281864525, and rs63750953 . Validation of these predicted candidate SNP markers using the clinical standards may advance personalized medicine. Recent studies  showed tOverall, sex differences in immune capabilities and autoimmune diseases are an established fact, and precise clinical observations in patients and experiments on animal models underlie the mainstream scientific research aimed at elucidating these phenomena in clinical practice. The gender-biased interactions between microorganisms and the human host , 16; thePostgenomic SNP identification is a part of the 1000 Genomes project , whose rTBP gene is lethal because RNA polymerase II binds to the TBP–DNA complex to induce formation of the transcription preinitiation complex  of the human genes from the default version of the reference human genome ; here, we used the current major assembly release GRCh38(NCBI)/hg38(UCSC) [in the terms used by the UCSC Genome Browser ”].Our heuristic interpretation of our predicted cases of significant overexpression or underexpression of the human genes is shown in italics in the second rightmost column of Tables Table IL1B gene (interleukin 1β) in its promoter contains a known SNP marker of intractable Graves’ disease (rs1143627)  than the affinity corresponding to the ancestral allele . This significant increase in affinity of TBP for the minor variant of the IL1B promoter corresponds (IL1B in patients with Graves’ disease (The human 1143627) . This pa1143627) . This SNresponds –65 to ov disease .IL1B overexpression, we performed a primary keyword search for “IL1B overexpression” as a biochemical marker of “gender-biased autoimmune diseases” in various databases . Therefore, we propose rs1143627 as a candidate SNP marker for this pathology  contains the known SNP marker of type 1 diabetes after neonatal diabetes mellitus (rs5505) (The human (rs5505) ; this mu(rs5505) , and inc(rs5505) . We pred(rs5505)  insulin (rs5505) –108.in vivo insulin deficiency is a possible cause of demyelinating disease  contains a minor variant of the promoter: the deletion G–72GGCGGACATACATATAC–54 between positions −72 and −54, which was implicated in hyperalphalipoproteinemia that reduces atherosclerosis risk  contains the known SNP marker (rs2276109) of a reduced risk of chronic asthma in children and in smokers  contain seven known SNP markers  of resistance to malaria and thalassemia (Cooley’s anemia) (HBB and HBD (Table The human  anemia) . These S anemia)  Table 2 anemia)  because  anemia  BD Table , where aBD Table  showing BD Table .ACKR1 gene  contains the known SNP rs2814778 marker of malaria resistance  contains a biomedical SNP marker of hypertension in diabetes (rs16887226)  , with th6887226) . The EMS6887226)  and redu6887226)  is suppo6887226) . Near th6887226)  because dotoxins  and of adotoxins . Lastly,dotoxins  between dotoxins .APOA1 gene (apolipoprotein A-I) contains the −35A → C substitution inside a proven TATA box . This substitution reduces the expression of this gene and thus is the SNP marker of hematuria, fatty liver, and obesity  contains the known SNP rs563763767 marker of the high risk of myocardial infarction and thromboembolism whose molecular cause is F3 overexpression  contains the known SNP marker of resistance to parasites (rs111426889)  . A prima1426889)  showing ng women . Then, tng women . Thus, wng women .NOS2 gene (inducible nitric oxide synthase 2) contains the −51T → C substitution as a known SNP marker of epilepsy  contains a known SNP marker (rs72661131) of variable immunodeficiency  contains the known SNP marker of resistance to methotrexate treatment in children with acute lymphoblastic leukemia (rs10168) (The human rs10168) . This SNrs10168) . A primars10168)  because rs10168) . Next, trs10168) , 165 shors10168) , 163.SOD1 gene (soluble superoxide dismutase 1) contains the known SNP marker of familial amyotrophic lateral sclerosis (rs1143627) (in silico (in vitro experiments (The human 1143627)  caused bn silico  and proveriments . Althougeriments . It showeriments . It is weriments ; this sieriments  of the aKD) values of the TBP-promoter affinity that were predicted in silico , Goodman–Kruskal’s generalized , Spearman’s rank correlation , and Kendall’s rank correlation . On the other hand, Figure r = 0.77 (α < 0.0025), γ = 0.65 (α < 0.0025), R = 0.81 (α < 0.0025), and τ = 0.65 (α < 0.0025). Thus, eight statistical tests indicated the robustness of the correlation between our predicted values (Tables KD) values  values . This roThis study is focused on the TBP-binding site because it is the best-studied site upstream of the transcriptional start of any mRNA in the genome, where RNA polymerase II binds to the anchoring TBP–DNA complex at the stage of preinitiation complex formation . As contAPOA1 gene, when obesity was caused by their accelerated development and maturation, can modify the diet and lifestyle of their children to reduce the excess body fat before an imbalance of the immune system causes atherosclerosis. Moreover, two candidate SNP markers predicted by us (rs16887226 and rs544850971) would be interesting to obese postmenopausal women with the minor alleles of these SNPs who developed low resistance to endotoxins; these women can resort to training and dietary changes in order to restore this resistance  and empirical in vitro values  and biomedical evidence (two rightmost columns in Tables −6) to borderline significance (α < 0.05), the proposed markers should be tested according to proper biomedical standards and protocols prior to application to clinical practice. For the best targeting of our analysis, we arranged the ancestral and minor alleles of each candidate SNP marker of autoimmune diseases by KD values expressed as affinity of TBP’s binding to synthetic aptamers of double-stranded DNA 26 bp long, as we predicted for in vitro conditions (KD values vary from 1 to 60 nM, whereas their variation among alleles of a certain SNP is within 1 nM, which is less than 2% of the KD range. Thus, the allelic variation is too small for accurate experimental determination of differences in KD without consideration of additional data on the expected range of the values to be measured. That is why the predicted KD values (Tables Finally, it is worth noting that our analysis of the candidate SNP markers of autoimmune diseases Tables –3 will mnditions . We founs Tables –73.Here we predicted candidate SNP markers of gender-biased autoimmune complications of monogenic diseases Tables –3. They MP, manuscript writing; LS, manuscript editing; DR, software development and application; OA, data compilation; PP, data analysis; and NK, conceived of and supervised the study.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.


Plasmodium falciparum isolates from 14 countries, and find evidence that they are non-recombining and co-inherited. The high degree of linkage produces a panel of relatively few single-nucleotide polymorphisms (SNPs) that is geographically informative. We design a 23-SNP barcode that is highly predictive (~92%) and easily adapted to aid case management in the field and survey parasite migration worldwide.Malaria is a major public health problem that is actively being addressed in a global eradication campaign. Increased population mobility through international air travel has elevated the risk of re-introducing parasites to elimination areas and dispersing drug-resistant parasites to new regions. A simple genetic marker that quickly and accurately identifies the geographic origin of infections would be a valuable public health tool for locating the source of imported outbreaks. Here we analyse the mitochondrion and apicoplast genomes of 711  Tracing the source of malarial infections is an important step towards monitoring and controlling the disease. Here, Preston et al. analyse sequence data from 711 isolates and design a genetic barcode based on combined mitochondrial and apicoplast genomes that is able to distinguish between malaria parasites isolated from different geographical regions. Plasmodium falciparum remains a leading cause of childhood mortality worldwide2P. falciparum  has been used to identify candidate artemisinin-resistant lociP. falciparum genotyping tool able to interrogate geographically restricted single-nucleotide polymorphisms (SNPs) would be of great value. Current barcoding approachesMalaria threatens nearly half the world’s population, and the deadliest form caused by mt) of P. falciparum is a 6-kb concatenated linear sequence, is transmitted in female gametocytes and does not recombine among lineages67mt is attractive as a potential barcoding tool. Analysis of global sequence variation in mt has revealed geographic differentiation910Plasmodium species, and show phylogenetic homology to the chloroplasts of plants and red algae1213141516apico) is a 35-kb circular sequenceapico  has not been well characterized, it is potentially greater than that in mt  owing to its larger size. To develop a robust mt/apico barcode and improve our understanding of apico evolution, a definitive analysis of apico SNP variation in multiple P. falciparum populations is needed to determine the extent of global diversity and existence of recombination.The mitochondrion genome  between mt and apico SNPs within populations, providing strong evidence that the organelles are indeed co-transmitted and non-recombining. This finding represents a breakthrough in the genetic barcoding of P. falciparum, as it reveals novel extended haplotypes specific for different geographic settings. Using SNP variation of the combined organelle genome (mt/apico) in an iterative haplotype-based classification analysis, we construct a 23-SNP barcode that identifies the region of sample origin with 92% predictive accuracy.Although there is good evidence that chloroplasts and mitochondria are co-inherited in plantsP. falciparum samples in five geographic regions: West Africa , East Africa , Southeast Asia , Oceania  and South America . The sequence coverages of mt  and apico (~100-fold) are ~22-fold and ~two-fold greater than the nuclear genome, respectively  and 488 in apico  (9mt and 12 apico) were common (MAF >5%) ; 29 were tri-allelic and two were quad-allelic  . Of the d apico ~0-fold arMAF >5%) . Multi-a-allelic . Of the d apico ~0-fold armt and apico SNP data, which revealed clustering by geographic origin of samples  than between the five regions (mean 58 SNPs with Fst >0.05). Forty-nine SNPs have MAF >1% in at least one region (Fst >0.1 (mt and 13 apico), 14 are located in genes with 8 non-synonymous (NS) changes (Fst (~0.76), mt772 (cox3) and apico6762 (orf101), are in perfect LD (r2=1) and differentiate SEA from other regions . A third SNP with high Fst (~0.88), apico26659 (rpl23), differentiates Africa (WAF and EAF) and SAM from other regions , providing strong evidence of co-inheritance of the two organelles. This genetic evidence confirms the experimentally observed and theoretically predicted processes involved in gametocytogenesis6To assess the extent of recombination between SNPs within and between ectively . By compquencies , we founmt haplotypes was previously interpreted to reflect radiation of P. falciparum out of Africa into SEA and SAMmt SNPs identifies a common haplotype in 30.0% (213/711) of samples, which is represented in four of the five regions: SAM 30.4%, WAF 37.2%, EAF 49.0%, SEA 0% and OCE 36%  haplotypes greatly increases the geographic resolution of samples (mt/apico haplotypes observed in multiple regions are most common in Africa (WAF and EAF), consistent with an African origin for this parasite species.The geographical pattern of  OCE 36% . Since t samples . Nearly mt/apico haplotypes. Using the 221 SNP loci with non-singleton alleles, we applied an iterative haplotype search algorithm that maximized predictive accuracy, while accounting for regional sample size differences and avoiding over-fitting. The minimal barcode comprises 23 SNPs , within 18 protein-coding genes (13 NS), four non-translated RNA segments and one inter-genic region N=12 (ref. 25)N=16; Guinea, N=106 (ref. 26)N=20 (ref. 27)The overall predictive accuracy of the minimal barcode is 92.1% 655/711, , compareGB4 ref. 23), eigh=12 ref. 25; Ghana106 ref. 26; Malaw=20 ref. 27) and 2P. falciparum reflects population history, demography and geographic distance; however, recombination disrupts signals of differentiation in the nuclear genome, and since organelle sequence is non-recombining it can be uniquely informative when tracing patterns of dispersal. Mitochondrial and chloroplast sequences are commonly used in DNA barcodes for animals and plantsmt and apico genomes, we have established a 23-SNP barcode that is geographically informative and robust to the effects of recombination. Rapid sequencing and genotyping technologies can be applied to small amounts of relatively low-grade parasite material, such as that sourced from finger-prick bloodspots. Exploiting uniqueness in the sequences surrounding the informative SNPs supports highly specific identification. The application of this tool has the potential to improve the management of imported cases and reduce the risk of local epidemics resulting from further transmission. Hence it will be a valuable tool for local agencies in programmes of malaria elimination and resistance containment.Worldwide genetic variation in P. falciparum radiation from Africa in the recent past, while sequence analysis using Tajima’s D metric253334cytb occurred in vitro in the presence of atovaquone-proguanil selectionmt/apico SNPs and putative artemisinin-resistant loci . We also considered nuclear SNPs known to be associated with resistance to chloroquine  and antifolates , but again found only weak correlation.The geographic differentiation seen in organelle genomes may also be subject to evolutionary forces in addition to genetic drift and migration. The presence of a core haplotype is consistent with BP1 ref. ) but fouapico (77.8%) compared with mt (31.3%) and the nuclear (61.8%) genomemt genes have low NS to S ratios, indicative of purifying selection and a conserved functional role, apico genes generally have high NS to S ratios indicative of divergence and directional selectionrp8, rps7 and tufA (apico DNA replication machineryapico-encoded proteins and 545 nuclear-encoded apicoplast proteinsapico itself (77.8% NS) rather than the nuclear genome (60.6% NS), thus supporting the DNA replication hypothesis. A similar analysis of mt-encoded proteins and 381 nuclear-encoded mitochondrial proteinsmt. This points to a conservation mechanism that is intrinsic to the mitochondrial sequence. It is also significant that the absence of recombination introduces a constraint on the selective removal of slightly deleterious mutationsmt and apico within individual parasites may allow deleterious copies to be jettisoned by intracellular selection.A striking observation is the high proportion of NS changes among coding SNPs in and tufA , the latPlasmodium species13141516The apicoplast shares evolutionary similarities with the chloroplasts of photosynthetic eukaryotes and the prokaryotic progenitors of all plastids, and is vital to the survival of P. falciparum isolates potentially has enormous practical utility in containing drug resistance and eliminating malaria. One potential limitation of the mt/apico barcode in its current form is the lack of representation of the Indian sub-continent, Central America, southern Africa and the Caribbean, owing to the scarcity of sequence data from these regions. In addition, there is a need to sample more intensively from EAF, a region of high genetic diversity, high migration and poor predictive ability. Once these data gaps are filled, the barcode can be re-calibrated to maximize its accuracy in assigning sample origin. The 23 SNPs can be modified in light of new sequence information to improve barcode specificity, especially for discriminating malaria importation from one or two known regions, in which case a minimal set can be applied. Adding genomic data from P. vivax and P. knowlesi should help broaden the scope of the barcode for pan-Plasmodium applications. Incorporating antimalarial drug-resistant lociAn ability to determine the geographic origin of mt and apico sequences are non-recombining creates a new genotyping tool that is robust to the diluting effects of recombination. Global movement of parasites threatens elimination and treatment efficacy. By mapping global patterns of organellar genome polymorphism, we will gain new insights into the extent to which P. falciparum populations worldwide are inter-connected by international malaria migration.The demonstration that P. falciparum isolates sourced from Burkina Faso and Mali27284344274328272843mt sequence data for 101 samples  were also availableRaw deep-sequence data (minimum read length 54 base pairs (bp)) were available from smalt alignment software  with default settings within an established pipeline2424All sequences were mapped uniquely onto the 3D7 reference genome  using D indicesFstD values signify an excess of low-frequency polymorphisms relative to expectation, indicating population size expansion  and/or purifying selection. Positive Tajima’s D values signify low levels of low- and high-frequency polymorphisms, indicating a decrease in population size and/or balancing selection. Fst metric values range from 0  to 1 (complete differentiation for at least one population). The Ka/Ks ratio was calculated as an indicator of selective pressure acting on a protein-coding gene (Ka) to the number of synonymous (S) substitutions per S site (Ks)Ka/Ks from 1 imply positive selection, while values decreasing from 1 imply purifying selection. LD was assessed using pairwise D' and r2 methodsFst, as well as classification and regression treewww.r-project.org).A linear discriminant analysis was performed to cluster parasite isolates on the basis of genetic information, specifically using pairwise identity by state based on SNP allele differences. SNPs identified in the nuclear genome .Supplementary Figures 1-7 and Supplementary Tables 1-5


We used data mining approaches to compile a list of bovine protein-coding genes involved in epigenetic processes. These genes represent 9 functional categories that contain between one (histone demethylases) and 99 (chromatin remodeling factors) genes. A total of 3091 SNP mapped to positions within 3000 bp of the 193 coding regions of those genes, including 113 SNP in transcribed regions, 2738 in intronic regions and 240 in up- or down-stream regions. For all these SNP categories, we observed differences in the allelic frequencies between Brahman and Tropical Composite cattle. These differences were larger than those observed for the entire set of 729,068 SNP (P = 1.79 x 10−5). A multidimensional scaling analysis using only the 113 SNP in transcribed regions allowed for the separation of the two populations and this separation was comparable to the one obtained with a random set of 113 SNP . To further characterize the differences between the breeds we defined a gene-differentiation metric based on the average genotypic frequencies of SNP connected to each gene and compared both cattle populations. The 10% most differentiated genes were distributed across 10 chromosomes, with significant (P < 0.05) enrichment on BTA 3 and 10. The 10% most conserved genes were located in 12 chromosomes. We conclude that there is variation between cattle populations in genes connected to epigenetic processes, and this variation can be used to differentiate cattle breeds. More research is needed to fully characterize the use of these SNP and its potential as means to further our understanding of biological variation and epigenetic processes.We evaluated the relevance of the BovineHD Illumina SNP chip with respect to genes involved in epigenetic processes. Genotypes for 729,068 SNP on two tropical cattle breeds of Australia were used: Brahman ( Bos taurus autosome (BTA) 14 that regulates the expression of various genes in the PLAG1 region and is associated with many production traits as well as reproductive phenotypes  there are SNP variations linked to genes belonging to epigenetic processes in a commercially available genotyping platform, if (2) the allelic frequency of these SNP varies between tropically adapted cattle breeds, and if (3) we could use these SNP to characterize the genetic diversity of cattle populations.We used two populations of Bos indicus  and a cross-bred Bos taurus × Bos indicus   or the BovineSNP50  .The cattle were sourced from two populations, a http://www.bioguo.org/AnimalTFDB/index.php). Similar data mining could be done for other species. The gene list used in this study is not intended to be comprehensive, but representative of the main biological processes with epigenetic consequences (Table http://www.ensembl.org) were used as unique identifiers. The resulting list of genes and transcripts was the target for SNP selection.Data mining based on literature information and publicly available databases served to compile a list of 217 bovine protein-coding genes (and their transcript variants) involved in 9 categories of epigenetic processes , (2) the list of targeted genes and transcripts, (3) the BovineHD SNP list, and (4) the Variant Effect Predictor , all mapped using the bovine UMD 3.1 assembly as reference sequence. First we identified all SNP from the BovineHD  located at targeted transcripts or within 3Kb up- or downstream. Then, using the Variant Effect Predictor, we defined each SNP position relative to its target transcript and classify them in three categories accordingly: CAT1—corresponding to SNP mapped to exons, splice site, 3′ and 5′ UTR (transcribed SNP); CAT2—corresponding to intronic SNP; and CAT3—for SNP located up- or down-stream to selected transcripts.We used four sources of information for SNP selection and annotation: (1) the annotation file of coding and non-coding transcripts  were calculated for each breed using PLINK v1.07 , and comparing its result to the average value obtain after 10 runs of 113 transcribed SNP randomly selected from the entire HD dataset.Where p0, p1, and p2 are the average genotypic frequencies for all SNP within each gene  within each breed, and BB and TC are the Brahman and Tropical Composite genotypic frequencies, respectively. The hypergeometric test was applied to evaluate the significance of the distributions of individual allelic frequency categories and also to gene-differentiation metric. The hypergeometric test was set as the number of occurrences in one domain vs. the number of occurrences in another domain, e.g., number of SNP with allelic frequency difference between BB and TC > 0.3 within all SNP vs. the same situation within epigenetic SNP. The population differentiation was also evaluated using multidimensional scaling analyses, implemented in PLINK, using only the SNP at transcribed regions  to n = 364 (BTA3) . The SNP in CAT2 were intronic (n = 2738) and in CAT3 were down- or up-stream of a transcript (up to 3 Kb) (n = 240). In order to define unique pairs of transcripts and SNP, only the closest transcript was mapped against each SNP. Therefore, if two transcripts mapped close together, and one of them had an intronic SNP and the next SNP was more than 3 Kb distant from the coding sequence, only the transcript with an intronic SNP was tagged. This step might have reduced the number of genes and transcripts that were tagged, but was needed to define unique SNP-gene pairs. As a result, 193 members of the target epigenetic transcripts contained SNP from BovineHD at or close by their coding sequence (Supplementary Table n = 1). All main biological processes with potential direct epigenetic consequence were represented by at least one gene and 14 SNP. Hence, the BovineHD panel can be used to retrieve information regarding genes related to epigenetic processes.We have evaluated the possibility of using SNP from the BovineHD panel to tag genes and transcripts involved in epigenetic processes. Out of the 729,068 SNP available, 3091 SNP could be linked to an epigenetic gene. All autosomes and the X chromosome were represented by a varying number of SNP per chromosome, from P = 1.79 × 10−5). Moreover, breaking the analyses by epigenetic SNP-categories, all had significant (P < 0.05) accumulation of SNP with allelic frequency difference > 0.3 between breeds, with higher significance for the CAT1  and CAT2 . For gene-SNP categories that had more than 10 SNP frequencies were also calculated. These averages carried large standard deviation. Nevertheless, the top 3 averages of allelic frequency differences were for intronic SNP (CAT2) at methyl-binding domain proteins, polycomb-group proteins and transcribed SNP (CAT1) at Chromatin-remodeling factors. In contrast, the top 3 averages for allelic similarity were for intronic SNP (CAT2) at histones, histone demethylases, histone deacetylases. Overall, there was a significant accumulation of SNP with divergent allelic frequency between the studied cattle breeds, and often these SNP were located in potentially functional sites within the genes involved in epigenetic processes. It has been described that several epigenetic regulatory elements are evolutionary conserved across species  defined clear separation between breeds. The breeds clustering resulting from this analysis was comparable to that of other sets of randomly selected SNP (n = 113). The correlation of Component 1 between CAT1 and the average of 10 runs of randomly selected SNP being r2 = 0.91. There is enough variability between both cattle breeds to define independent clusters in a multidimensional analyses using 113 SNP and this variation is also extended to epigenetic-related SNP.Multidimensional scaling calculated using only transcribed SNP  concentration on BTA3 and BTA10. On the other hand, the top 10% most conserved genes were distributed in 12 chromosomes (Figure The variability observed in allelic frequency was also echoed in the gene-differentiation analysis. Within transcript, the comparison of averaged genotypic frequencies in each breed clearly showed differences. The top 10% most differentiated genes were distributed across 10 chromosomes, with significant (s Figure . Here, tDNA variants can alter epigenetic processes, and also assist genomic mapping of epigenetic variance. Recently, the definition of epigenetics as changes in gene activity without changes in the DNA has been opened for re-consideration (Furey and Sethupathy, Epigenetics is a very dynamic field of research and the list of genes and transcripts involved with epigenetic processes is growing. The ongoing gene annotation process means that the list of genes considered here should be considered only as a starting point. The analysis presented here are intended as a framework for mining epigenetic information from SNP panels and in any new analysis the list of target genes and transcripts should be revisited to include the most recent annotation as well as the most recent assembly of the investigated genome.We conclude that there is variation on SNP connected to epigenetic processes between cattle breeds. This variation can be used to differentiate cattle breeds. Further investigation would confirm if SNP located near or in genes of the epigenetic machinery are useful to “tag” biological variation associated to epigenetic processes.Laercio R. Porto-Neto and Antonio Reverter designed the experiment. Laercio R. Porto-Neto, Marina R. S. Fortes, Sean M. McWilliam, Sigrid A. Lehnert, and Antonio Reverter contributed to data acquisition. Laercio R. Porto-Neto and Sean M. McWilliam contributed to data mining and bioinformatic analyses. Laercio R. Porto-Neto performed population diversity and statistical analysis. Laercio R. Porto-Neto, Marina R. S. Fortes, Sigrid A. Lehnert, and Antonio Reverter contributed to interpretation of results and drafted the manuscript. All authors approved the final version of 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.