Prenatal skeletal muscle development genetically determines postnatal muscle characteristics such as growth and meat quality in pigs. However, the molecular mechanisms underlying prenatal skeletal muscle development remain unclear. Here, we performed the first genome-wide analysis of chimeric RNAs, single nuclear polymorphisms (SNPs) and allele-specific expression (ASE) in prenatal skeletal muscle in pigs. We identified 14,810 protein coding genes and 163 high-confidence chimeric RNAs expressed in prenatal skeletal muscle. More than 94.5% of the chimeric RNAs obeyed the canonical GT/AG splice rule and were trans-splicing events. Ten and two RNAs were aligned to human and mouse chimeric transcripts, respectively. We detected 106,457 high-quality SNPs , which were mostly (89.09%) located within QTLs for production traits. The high proportion of non-exonic SNPs revealed the incomplete annotation status of the current swine reference genome. ASE analysis revealed that 11,300 heterozygous SNPs showed allelic imbalance, whereas 131 ASE variants were located in the chimeric RNAs. Moreover, 4 ASE variants were associated with various economically relevant traits of pigs. Taken together, our data provide a source for studies of chimeric RNAs and biomarkers for pig breeding, while illuminating the complex transcriptional events underlying prenatal skeletal muscle development in mammals. Muscle fibers are the basic structural and functional units of skeletal muscle2Gene expression profiles during tissue and organ development are complex. Multiple transcript types, including long non-coding RNA, chimeric RNA, and circular RNA, as well as transcriptional events, including alternative splicing and allele-specific expression (ASE), contribute to the complexity of the transcriptome and provide significant obstacles to the achievement of a comprehensive understanding of the genetic basis of skeletal muscle development97812131415Chimeric RNA molecules, also known as fusion transcripts, are composed of exons from two genes located at different genomic loci18211823PRKAG3) gene, which is associated with high glycogen content in pig skeletal musclecis-regulatory variation30Biomarkers and information regarding allele-specific expression (ASE) associated with muscle growth are important in animal breeding. SNPs are the most abundant type of DNA sequence polymorphism and serve as powerful genetic markers in pig breeding252627In this study, we used high-throughput transcriptome sequencing to systematically explore transcriptional events associated with prenatal skeletal muscle development in pigs. We first carried out systematic identification and characterization of protein coding genes and chimeric RNAs. Subsequently, we analyzed SNPs and ASE in prenatal skeletal muscle of Tongcheng pigs. This study provides a resource of chimeric RNAs, SNPs, and ASE that illuminates the molecular events underlying prenatal porcine skeletal muscle development and allows the development of molecular markers for pig breeding.Sus scrofa genome assembly 10.2. RPKM values were calculated to allow measurement of the expression levels of protein coding genes. Using RPKM >0.1 as a threshold, we detected 14,810 protein coding genes (PCGs) (Table S1), accounting for 68.54% of the PCGs included in the Ensembl release 78 mart database, indicating that most known PCGs were expressed in prenatal porcine skeletal muscle, while confirming that RNA-seq was an effective method for identifying PCGs with low expression levels. The read coverage of the RNA-seq data and the expression levels of the PCGs in the Sus scrofa reference genome are shown in ACTC1, TNNC2, ACTA1, TNNC1, MYL3, ACTA2, MYH3, and MYL1, were significantly enriched as expected; this phenomenon could be explained by the formation of the majority of muscle fibers during secondary myogenesisEEF1G, EEF1B2, EEF2, EIF4G2), ribosome biogenesis (RPS and RPL family genes), and regulation of ATPase activity , which play essential roles in protein synthesis and fulfilling the energy requirements of prenatal skeletal muscle development, were significantly enriched (ACTB) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH)Samples of prenatal skeletal muscle from Tongcheng pigs were analyzed using RNA-seq with a paired-end sequencing strategy on an Illumina HiSeq 2000 instrument. A total of 55.02 million 90-bp pair-end high-quality reads were obtained, of which 83.9% were mapped to enriched . Two widSus scrofa genome is shown in 18Based on our transcriptome sequencing data, we identified chimeric RNAs associated with prenatal skeletal muscle development using the ChimeraScanTo determine whether homologues of the chimeric RNAs identified in the current study exist in other species, we aligned them to chimeric transcripts from the human, mouse, and fruit fly genomes in the ChiTaRS2.1 databaseTo validate the reliability of the group of identified chimeric RNAs, we selected 29 chimeric RNAs for RT-PCR verification in the same prenatal porcine skeletal muscle used for RNA sequencing analysis. The primers were designed to span the fusion junction of the chimeric RNAs. The vast majority of selected chimeric RNAs (20/29) were amplified by RT-PCR and confirmed by direct sequencing . The consistency of the RT-PCR and prediction results suggests that the group of identified chimeric RNAs is sufficiently reliable for further research.NDUFS4. ssc-chimeric-113 was highly expressed in the results from the FusionMap (ranking 6th with 151 seed counts) and ChimeraScan (ranking 8th with a score of 139) analyses. The NDUFS4 gene (NADH dehydrogenase (ubiquinone) Fe-S protein 4, 18kDa (NADH-coenzyme Q reductase)) is highly expressed in skeletal muscle and potentially related to intramuscular fat deposition in pigsNDUFS4 was significantly associated with loin muscle areaNDUFS4 might play an important role in skeletal muscle development. The ENSSSCG00000024947 and NDUFS4 genes are both located on chromosome 16, but on different strands. Our transcriptome sequencing data confirmed that ssc-chimeric-113 was abundantly expressed, as evidenced by 37 spanning reads across the fusion junction ; 93.6% of the variants  were deposited in the dbSNP database, indicating the high quality and reliability of our SNP analysis. At the same time, we detected 6,955 novel SNPs. Our results have increased the number of known SNPs in S. scrofa.We identified 106,457 high quality SNPs in transcripts expressed in prenatal skeletal muscle (Table S6). The number of SNPs within each chromosome was directly proportional to chromosome length and gene number. Chromosome 1 contained the most SNPs, whereas chromosome 16 contained the fewest SNPs . The pro41The distribution of the discovered SNPs within various genomic features was analyzed using Ensembl’s Variant Effect Predictorp < 0.05). These genes containing nonsynonymous SNPs were mainly involved in the response to DNA damage stimulus, DNA repair, the cellular response to stress, DNA metabolic processes, and the cell cycle (p < 0.01)  . MoreoveS. scrofa quantitative trait loci (QTLs) deposited in the AnimalQTLdbNext, we queried the set of 106,457 high-quality SNPs to determine their presence in cis- and trans-regulatory genetic variation. Genome-wide ASE analysis is an effective method for inferring the existence of cis-regulatory variants30p < 0.001), which suggested an enrichment of nonsynonymous variants in ASE. In addition, we detected 131 ASE SNPs located in the chimeric RNAs.Gene expression is influenced by NR3C1) was associated with relative flare fatSCD)) and rs81215882 (located in phosphoglucomutase 1 (PGM1)) were significantly associated with average daily weight gain49ALDH18A1) was associated with hematological traitscis-regulatory variations might be associated with phenotypic divergence in pigs. Additionally, the rs340729607 (T/A) variant introduced a premature stop codon in exon 7 of mitochondrial ribosomal protein L1 (MRPL1), indicating nonsense-mediated decay. Unfortunately, we did not detect ASE variants in the chimeric RNAs generated from genes reported to influence economically important traits in the GWASs.GWASs have reported a large number of SNPs associated with phenotypes of various economic traits in pigs. To illuminate the functional impacts of SNPs, we examined whether SNPs reported by previous GWASs exhibited ASE in our study. Surprisingly, we identified 4 ASE variants reported by previous GWASs. Of these, SNP rs335265740 in the 3′-UTR of nuclear receptor subfamily 3, group C, member 1 (glucocorticoid receptor)  at 5 time points . All samples were maintained in liquid nitrogen until use.All animal experiments were performed according to the procedures defined by national and local animal welfare bodies and were approved by the Institutional Animal Care and Use Committee at the Institute of Animal Science, Chinese Academy of Agricultural Sciences. The Total RNA was extracted using Trizol  following the manufacturer’s protocol. RNA integrity was measured using an Agilent 2100 Bioanalyzer. Only samples with RNA Integrity Number (RIN) values greater than eight were used for sequencing. Library construction and Solexa sequencing were performed using methods described previouslyS. scrofa reference genome (assembly 10.2)After filtering low quality reads, clean reads were mapped against the S. scrofa assembly 10.2)ChimeraScan (version 0.4.3)To validate the identified chimeric RNAs, total RNA from prenatal porcine skeletal muscle was reverse-transcribed into cDNA using the RevertAid First Strand cDNA Synthesis Kit  according to the manufacturer’s protocols. The chimeric cDNA containing the fusion junction was amplified by PCR as follows: an initial denaturation at 94 °C for 3 min, followed by 34 cycles of denaturation at 95 °C for 15 s, annealing at 60 °C for 30 s, and elongation at 72 °C for 20 s, and a final extension for 5 min at 68 °C. The PCR products were confirmed by direct sequencing.https://www.broadinstitute.org/gatk/guide/best-practices?bpm=RNAseq). Stringent parameters were used to minimize detection of false-positive SNPs. Clusters of at least 3 SNPs within a window of 35 bases were filtered out. Hard filtering values, including Fisher strand values (FS > 30.0), qual by depth values (QD < 2.0), and read depth value (DP < 5), were selected. SNPs located on unplaced scaffolds and mitochondria were not included in this study. SNP annotation was performed using in-house Perl scripts and Ensembl’s Variant Effect PredictorThe Genome Analysis Toolkit (GATK version 3.3) packageThe ASEReadCounter toolhttp://david.abcc.ncifcrf.gov/)http://www.biomart.org/) before performing the GO and KEGG pathway analyses. We set the EASE value to 0.05 for the enrichment analysis. Significantly enriched GO biological process terms were summarized and visualized using REVIGO (http://revigo.irb.hr/)Gene ontology (GO) and KEGG pathway enrichment analyses were performed with the Database for Annotation, Visualization, and Integrated Discovery (DAVID) website (Accession code: The RNA-seq raw data from this study have been deposited in the NCBI Sequence Read Archive with accession number SRP066035. (http://www.ncbi.nlm.nih.gov/Traces/sra/).How to cite this article: Yang, Y. et al. Transcriptome analysis revealed chimeric RNAs, single nucleotide polymorphisms and allele-specific expression in porcine prenatal skeletal muscle. Sci. Rep.6, 29039; doi: 10.1038/srep29039 (2016).


This study tested the hypothesis that LCn-3 PUFA cardioprotection is underpinned by peroxidation, upregulating antioxidant activity to reduce I/R-induced lipid oxidation, and the mechanisms of this nutritional preconditioning contrast to mechanisms of IPC. Rats were fed: fish oil (LCn-3 PUFA); sunflower seed oil (n-6 PUFA); or beef tallow  enriched diets for six weeks. Isolated hearts were subject to: 180 min normoxic perfusion; a 30 min coronary occlusion ischaemia protocol then 120 min normoxic reperfusion; or a 3 × 5 min global IPC protocol, 30 min ischaemia, then reperfusion. Dietary LCn-3 PUFA raised basal: membrane docosahexaenoic acid (22:6n-3 DHA); fatty acid peroxidisability index; concentrations of lipid oxidation products; and superoxide dismutase (MnSOD) activity (but not CuZnSOD or glutathione peroxidase). Infarct size correlated inversely with basal MnSOD activity (r2 = 0.85) in the ischaemia protocol and positively with I/R-induced lipid oxidation (lipid hydroperoxides (LPO), r2 = 0.475; malondialdehyde (MDA), r2 = 0.583) across ischaemia and IPC protocols. While both dietary fish oil and IPC infarct-reduction were associated with reduced I/R-induced lipid oxidation, fish oil produced nutritional preconditioning by prior LCn-3 PUFA incorporation and increased peroxidisability leading to up-regulated mitochondrial SOD antioxidant activity.Reactive oxygen species paradoxically underpin both ischaemia/reperfusion (I/R) damage and ischaemic preconditioning (IPC) cardioprotection. Long-chain omega-3 polyunsaturated fatty acids (LC Therefore, the cardioprotective benefit of fish oil appears to mimic the more sustained, repeatable protection of late IPC and other persistent preconditioning stimuli [n-3 PUFA [Regular consumption of fish or fish oil reduces cardiovascular mortality , often wc events . Ischaemrct size ,6 and prrct size , and morrct size , as earlrct size . In contustained ,8,9. Theustained  of conti stimuli ,12,13. Mn-3 PUFA  share win-3 PUFA  the capan-3 PUFA found in fish oil: 20:5n-3 eicosapentaenoic acid (EPA) and 22:6n-3 docosahexaenoic acid (DHA) with their numerous bisallylic carbon atoms, are more susceptible to peroxidation and generation of damaging reactive oxygen species than are shorter, less unsaturated fatty acids such as 18:2n-6 linoleic acid and 20:4n-6 arachidonic acid [Myocardial ischaemia and reperfusion (I/R) stimulates production of reactive oxygen species (ROS) and depletes antioxidants in the heart, creating oxidative stress, oxidation of biomolecules and cell damage. Paradoxically, these free radicals also act as triggers of IPC ,16. The nic acid , which rn-3 PUFA into myocardial membranes increases their peroxidation potential and basal fatty acid oxidation, which by their constant presence, in turn increases endogenous antioxidant enzymes to confer physiological cardioprotective actions against I/R-stimulated oxidative stress. We propose that this will contrast to the mechanism of early IPC cardioprotection.The current study tested the hypothesis that incorporation of LCn-6 PUFA or LCn-3 PUFA as the source of fat. The diets were based on the American Institute of Nutrition AIN93 rat diet, containing all essential vitamins and minerals with gelatine as a component of the protein source. The diet was prepared with 10% (dry wt) fat (23% metabolisable energy as fat) consisting of: 7% beef tallow plus 3% olive oil (SF diet); 5% sunflower seed oil plus 5% olive oil (n-6 PUFA diet); or 7% fish oil (Nu-Mega high DHA tuna fish oil) plus 3% olive oil (LCn-3 PUFA diet). In addition to delivering diets rich in saturated fat, n-6 PUFA or n-3 PUFA, the oil blends in the LCn-3 PUFA diet and the n-6 PUFA diet were designed to deliver similar total PUFA, and the oil blends in the LCn-3 PUFA diet and the SF diet were designed to deliver similar total n-6 PUFA, as previously described [Fifty-four male Wistar rats were randomly assigned to three experimental dietary groups. For six weeks they were fed one of three iso-energetic diets containing either predominantly saturated animal fat, Animal care and experiments were conducted with the approval of the University of Wollongong, Animal Care and Ethics Committee according to the guidelines of the National Health and Medical Research Council, Australia, Australian Code of Practice for the Care and Use of Animals for Scientific Purposes .−1 i.p.), the thorax was opened, the heart was rapidly excised, submerged in ice-cold perfusate to arrest beating, and immediately perfused by an aortic cannula in the Langendorff mode at a constant pressure of 75 mmHg delivering warm (37 °C) Krebs–Henseleit bicarbonate buffer gassed with 5% CO2 in O2 [After six weeks of feeding, rats were anaesthetised  was separated into groups of n = 6 and randomly assigned to one of three perfusion protocols for 180 min after initial 30 min equilibration perfusion (n = 6 per diet): Hearts were perfused throughout with oxygenated Krebs–Henseleit solution.Control normoxia protocol (Ischaemia protocol (n = 6 per diet): Hearts were normoxically perfused for 30 min followed by 30 min index-ischaemia and 120 min normoxic reperfusion. Index-ischaemia was induced by occluding the left anterior descending coronary artery.Ischaemic preconditioning (IPC) protocol (n = 6 per diet): Hearts were subjected to three cycles of five minutes global ischaemia (zero perfusion), each followed by five minutes normoxic reperfusion, prior to the 30 min index-ischaemia then 120 min normoxic reperfusion .Each dietary group . Hearts were then cut into 2 mm slices. The central slice was incubated in a buffer containing triphenyl-tetrazolium chloride and sodium phosphate (pH 7.4), then stored in 10% formalin until photographed and analysed for infarct size. Infarct size was reported as a percentage of the zone at risk. The remaining slices were separated into non-ischaemic (non-I) and ischaemic (ISCH) segments . SamplesConcentrations of LPO were measured by modification of the ferric thiocyanate assay using a colorimetric assay kit  and were expressed per mg of protein. Concentrations of malondialdehyde (MDA) were measured in thawed tissue homogenates by reverse-phase HPLC with fluorescence detection .Endogenous: Total superoxide dismutase (SOD) activity and CuZnSOD activity were measured in ventricle sections of: ISCH tissue; and non-I tissue using a BIOXYTECH®-SOD-525™ assay kit . The activity of mitochondrial SOD activated by manganese (MnSOD) was calculated as the difference between total SOD and CuZnSOD. The activity of SOD was expressed per mg of tissue protein. Glutathione peroxidase (GPX) activity was measured in ventricle sections of: ISCH; and non-I ventricle using BIOXYTECH®GPx-340TM assay kit  and was expressed per mg of tissue protein. Exogenous: Myocardial vitamin E  was measured by HPLC with electrochemical detection, using a modification of the method described by Yang [ by Yang .Total lipids were extracted from 100 to 200 mg samples of ventricular myocardium using a modification of the Folch method . Phosphoversus non-I tissue main effects. Tukey’s HSD test was used for post-hoc pairwise comparison of individual means and interactions. Within dietary groups, ISCH and non-I sections of the same hearts were compared using repeated measures ANOVA. Statistical analyses were performed using Statistix software, version 10 . Linear regression analysis with Pearson’s correlation was performed to determine linear associations between lipid oxidation products, antioxidants and infarct size using Prism for Windows, version 6 . Statistical significance was accepted at p < 0.05.Results were expressed as mean ± SEM. Data were analysed by two-way analysis of variance (ANOVA) for diet and treatment main effects  and by multi-way ANOVA for diet, treatment and ISCH n-6 PUFA 351 ± 5 g; LCn-3 PUFA 352 ± 6 g. Six weeks: SF 460 ± 11 g; n-6 PUFA 457 ± 8 g; LCn-3 PUFA 480 ± 9 g. Change: SF 112 ± 7 g; n-6 PUFA 109 ± 9 g; LCn-3 PUFA 128 ± 7 g. n = 18 per diet).Neither the starting body weight, the final body weight nor the change in body weight over six weeks differed between dietary groups  was greater in phospholipid of LCn-3 PUFA hearts than in either n-6 PUFA or SF hearts (p < 0.05) (n-3 PUFA hearts contained significantly lower concentrations of linoleic (18:2n-6) and arachidonic acids (20:4n-6) compared with n-6 PUFA or SF hearts. Total n-3 PUFA was greater in LCn-3 PUFA hearts compared with either n-6 PUFA or SF hearts, and lower in n-6 PUFA than SF hearts (p < 0.05). The total concentration of n-6 PUFA was lower in LCn-3 PUFA hearts than in either n-6 PUFA or SF hearts and greater in n-6 PUFA than SF hearts (p < 0.05).The relative concentration of DHA (22:6 < 0.05) . The LCnn-3 PUFA than in either n-6 PUFA or SF hearts (p < 0.05), which were not significantly different from each other.No significant dietary differences were observed in the membrane phospholipid total saturated fatty acids or total PUFA. The SF hearts had greater concentrations of total monounsaturated fatty acids (MUFA). Membrane unsaturation index (UI) and peroxidisability index A were siThe basal and non-I tissue derived from the three perfusion protocols exhibited no significant between protocol differences in tissue concentrations of lipid oxidation products LPO or MDA or anti-oxidants within any dietary group (pooled data shown in n-3 PUFA than in either n-6 PUFA or SF hearts and greater in n-6 PUFA than SF hearts (p < 0.05) (n-3 PUFA than in either n-6 PUFA or SF hearts (p < 0.05), which were not different from each other  A. The coch other B.n-3 PUFA hearts, than in SF or n-6 PUFA hearts (−1 protein): SF 15.3 ± 0.9; n-6 PUFA 16.9 ± 0.7; LCn-3 PUFA 17.4 ± 0.6 n = 18) (p > 0.05) or GPX : SF 19.2 ± 1.5; n-6 PUFA 19.7 ± 1.5; LCn-3 PUFA 21 ± 1.2 n = 15). The concentration of α-tocopherol was significantly greater in n-6 PUFA hearts than in either LCn-3 PUFA or SF hearts (p < 0.05) : SF 6.1 ± 0.4; n-6 PUFA 6.9 ± 0.2; LCn-3 PUFA 5.9 ± 0.6 n = 15).The activity of MnSOD in basal and non-I tissue was significantly greater in LCA hearts C. In basIschaemia: The concentrations of LPO (n-6 PUFA and SF hearts (p < 0.01) but not in LCn-3 PUFA hearts. The concentrations of LPO and MDA in the ISCH region were significantly greater in SF hearts than in LCn-3 PUFA hearts . Pairwise comparison indicated that this IPC difference was evident in SF and n-6 PUFA diets only.ry group A,B, nor n-6 PUFA fed rats but not significantly changed within LCn-3 PUFA hearts : SF 50 ± 1 n = 6; n-6 PUFA 47 ± 1 n = 6; LCn-3 PUFA n = 6 11 ± 1 n = 6, (p < 0.05)). In hearts subjected to the IPC + ischaemia protocol, the infarct size was significantly smaller in the SF and n-6 PUFA hearts than in the corresponding ischaemia group (p < 0.05). There was no significant difference within the LCn-3 PUFA diet. (IPC + ischaemia infarct size (% Iz/r): SF 13 ± 1 n = 6; n-6 PUFA 12 ± 1 n = 6; LCn-3 PUFA 10 ± 1 n = 6).In hearts subjected to the ischaemia perfusion protocol, infarct size was significantly smaller in LCIschaemia protocol: Infarct size was positively associated with lipid oxidation biomarker production in the ISCH region, independent of diet , yet paradoxically reduced the measured oxidative damage following I/R. While the increased myocardial peroxidation potential was associated with an increase in basal fatty acid peroxidation, confirming effects of DHA feeding recorded in plasma and liver [n-3 PUFA supplementation reflects both the low level generation of ROS through lipid peroxidation [n-3 PUFA continuous presence as a membrane component, it also provides a persistent tolerance to I/R injury. This persistent preconditioning is also observed with repeated stresses like exercise and heat exposure [A diet rich in LCnd liver , it alsond liver . In thisxidation  and up-rxidation . This alxidation  not onlyexposure . In contFish oil-induced chronic increases in basal lipid oxidation directly correlated with basal MnSOD antioxidant activity in myocardium, which in turn was negatively correlated with the I/R-induced increase in lipid oxidation. This interdependence, which reflects the contrasting damaging influence and homeostatic signalling roles of ROS in ischaemia and IPC, can explain some of the lack of consistent correlation between oxidation products and anti-oxidants and sometime failure of oxidation markers to serve as clear criteria for defining oxidative stress . The effn-6 PUFA or MUFA enriched diets. In the current study, the n-6 PUFA rich diet with its elevated vitamin E content did not change the membrane fatty acid composition sufficiently to modulate either membrane peroxidisability index or endogenous antioxidant enzyme activity relative to the low PUFA saturated fat enriched diet, and hearts from those diets were equally highly susceptible to oxidative damage. This is consistent with previous findings that both membrane effects and cardioprotective effects of n-6 PUFA are readily lost as the PUFA content is diluted by other fat sources [n-3 PUFA, which sustain membrane composition [n-3 PUFA intakes can be pro-arrhythmic  [Fish oil induced increases in antioxidant expression and reduced lipid peroxidation products were also reported in hepatic and renal tissue of immune suppressed mice ,30 and h sources ,33. Thisposition ,35, and position ,32,33,36 kg man) , perhaps kg man) .n-3 PUFA exert protection from ischaemia by activating signalling pathways that resemble those involved in late IPC or exercise, and we describe this as “nutritional preconditioning”. The current study used a LCn-3 PUFA intake equivalent to more than 30 g of fish oil per day in humans [The present study suggests that LCn humans . Howevern humans ). This in humans . In skeln humans .n-3 PUFA derived from eating fish [n-3 PUFA found in myocardium, DHA is also the main fatty acid underpinning the cardiac effects of fish and fish oil [n-3 PUFA content, since similar total PUFA content was provided in the n-6 and LCn-3 PUFA diets; similar n-6 PUFA was provided in the SF and LCn-3 PUFA diets; and low saturated fat was provided in the n-6 PUFA diet, all without effect.The present study deliberately used a high DHA fish oil, which does not reflect the composition of most nutritional supplement fish oils, but rather reflects the main LCing fish ,40. As tn-3 PUFA hearts was restricted to the mitochondrial form of SOD (MnSOD or SOD2) with CuZnSOD and GSx unchanged. This suggests localisation of the primarily influence of LCn-3 PUFA to the mitochondria. Increased MnSOD activity is similarly selectively implicated in the sustained cardioprotection elicited by heat stress and in late, delayed or second window of IPC [2 consumption [2+ handling [The increased expression of antioxidants within LCw of IPC , whereassumption , all prosumption ,43,44. Fhandling  and highhandling ,46,47, lhandling  and now n-3 highly polyunsaturated fatty acids by feeding fish oil, increased the basal peroxidation of cellular fatty acids, which in turn increased the activity of endogenous mitochondrial antioxidant superoxide dismutase. When these hearts were acutely subjected to regional I/R, the stimulated lipid oxidation and myocardial damage were reduced. The increase in peroxidation index of myocardial membranes through fatty acid compositional change and associated chronic mild elevation in lipid peroxidation products provokes a persistent physiological stress that might better be described as “oxidative shielding” [This study confirmed that increasing myocardial membrane percentage content of long chain ielding” , which iielding” . The obsielding” , effects


Facial asymmetries are commonly used as a proxy for human developmental imprecision resulting from inbreeding, and thus reduced genetic heterozygosity. Several environmental factors influence human facial asymmetry , but the generalizability of findings on genetic stressors has been limited in humans by sample characteristics  and indirect genetic assessment (inference from pedigrees). In a sample of 3215 adult humans from the Rotterdam Study, we therefore studied the relationship of facial asymmetry, estimated from nine mid-facial landmarks, with genetic variation at 102 single nucleotide polymorphism (SNP) loci recently associated with facial shape variation. We further tested whether the degree of individual heterozygosity is negatively correlated with facial asymmetry. An ANOVA tree regression did not identify any SNP relating to either fluctuating asymmetry or total asymmetry. In a general linear model, only age and sex—but neither heterozygosity nor any SNP previously reported to covary with facial shape—was significantly related to total or fluctuating asymmetry of the midface. Our study does not corroborate the common assumption in evolutionary and behavioral biology that morphological asymmetries reflect heterozygosity. Our results, however, may be affected by a relatively small degree of inbreeding, a relatively stable environment, and an advanced age in the Rotterdam sample. Further large-scale genetic studies, including gene expression studies, are necessary to validate the genetic and developmental origin of morphological asymmetries. In a recent study by Liu and co-workers, 102 single nucleotide polymorphism (SNP) loci were associated with variation in the mid-face  of humans with European ancestry For bilaterally symmetric traits, developmental instability during non-pathological growth is commonly estimated by the degree of individual morphological asymmetry, computed here as the shape difference (Procrustes distance) between a facial configuration and its reflection We thus assessed the association of facial TA and FA with (i) variation at the 102 SNPs reported to covary with facial shape as well as with (ii) heterozygosity  estimated from these SNPs. Our sample consists of 3215 adult humans of both sexes from non-isolated, non-inbred human samples of the “Rotterdam Study” cohorts studied by Liu et al. PRDM16) gene, paired box 3 (PAX3), tumor protein p63 (TP63), collagen alpha-1 (XVII) chain (COL17A1), and the uncharacterized gene locus chromosome 5 open reading frame 50 (C5orf50). PRMD16, PAX3 and TP63 encode transcription factors, and COL17A1 encodes the alpha chain of type XVII collagen, which is a transmembrane protein.Liu et al. determined the following candidate genes to be related to adult human mid-facial variation PRDM16 had been previously linked to orofacial development in general, and cleft palate formation in particular  was associated with the alae of the nose and their distance to the tip of the nose , the SNPs subsumed under PAX3 (represented by rs974448) with the distances between Nasion and the centers of the eyeballs, and the SNP related to TP63 (rs17447439) with the distance between the centers of the left and right eyeballs. The distances between Zygion and Nasion as well as the distances between the center of the eyeballs and Nasion were related to an SNP thought to represent C5orf50 (rs6555969). Finally, the latter two distances were also detected in relation to an SNP categorized as corresponding to COL17A1 (rs805722) With respect to facial morphology, the Deviations from perfect symmetry in bilaterally symmetrical facial traits are not only caused by detrimental genetic variants and mutations on single locations, but may occur for various genetic and environmental reasons within the non-pathological range of variation. Total asymmetry (TA) in general, and facial fluctuating asymmetry (FA) in particular, are well-established indicators for this kind of developmental instability or imprecision , genetica priori prediction about which allele might promote facial symmetry could be derived. For the second objective of this study, we hypothesized that the degree of individual heterozygosity, as assessed through the 102 SNP loci, should be negatively correlated with facial FA and TA.The first objectives of our study are to relate genetic variation at (i) the 102 SNP loci as well as at (ii) the five SNPs that reached genome-wide significance with regard to European facial shape variation (based on the data from The ANOVA tree regression identified no SNP (among the 102 SNPs) that were significantly associated with FA or TA. We therefore do not present any multivariate models based on all 102 SNPs here.P<10−8, P = 0.05 for FA and P = 0.04 for TA, respectively). All one-way interactions between sex, age and HL are non-significant and were therefore removed from the final model , cohort, as well as the 5 SNPs associated with mid-facial distances in the study of Liu et al. al model .African south of the Sahara ancestry” have, on average, lower HL scores than individuals from “East Asia”  was uncorrelated with either TA or FA in the faces of these 3215 Rotterdam Study individuals. This absence of correlation cannot result from any bottom or ceiling effect of the Netherland samples because the sample averages and variances are well within the range of several other human populations of European ancestry from the 1000 Genomes project  and 3.PAX3 gene. This SNP is situated in an AT-rich low-complexity sequence, but without known regulative function. However, this SNP is apparently in the same linkage disequilibrium (LD) block as the PAX3 intronic SNP rs7559271, which was significantly associated with the Nasion-to-Midendocanthion distance (n-men 3D dist) in another study PAX3 gene . Along this line, Attanasio and colleagues PAX3 presumably comprise sequence motifs for enhancer binding, but none of these sequences include any SNPs used in Liu et al. PAX3 gene expression. Furthermore, the other four studied SNPs have not been linked to specific processes or functions. Accordingly, the test for a correlation between variation at these loci and facial asymmetry was explorative and proved to be non-significant. Nevertheless, this analysis opens a wide array of prospects for future research that are discussed at the end of the article. Apart from these five SNPs, a promising candidate might be also the SNP rs10843104 at 12p11.22: it is linked to the parathyroid hormone-like hormone (PTHLH) gene, which is involved in regulating cellular and organ growth as well as in endochondral bone development, and is required for skeletal homeostasis.In the GWAS by Liu et al. Most previous articles on genetic aspects of facial and dental asymmetry are based on the comparison of endogamous (and often isolated and inbred) populations with more exogamous ones such as . Typicalper seThe higher the degree of heterozygosity at protein-coding genes or at linked loci (non-random association), the better adapted the individual is to buffer against perturbations. In this context, three hypothetical mechanisms are suggested: i) “The direct effect hypothesis” states that multilocus fitness-enhancing heterozygosity may result from a functional overdominance at the locus http://www.ncbi.nlm.nih.gov/projects/SNP/). Based on our data and the NCBI SNP database, we have also no hint for effects other than additive, because we did not find any known epistatic effects associated with the 102 SNPs discovered by the study of Liu et al. With regard to our study, we did not find any known allozymatic association with the 102 SNPs related to facial morphology  The sample was initially not collected for investigating facial asymmetry, which potentially introduces some limitations of our study. The participants' age range (45 to 93 years) is far beyond early adulthood so that environmental effects with aging might have added to facial asymmetries . The 102 SNPs were reported to be associated with the mid-facial landmarks used in the study, but the relatively small number of SNPs may limit the representative value in terms of an individual's total heterozygosity cf. . Also, tDespite all these limitations, the data provided by the study of Liu et al. We used the data set provided by Liu et al. 3 (up sampled from 0.66×0.7×0.8 mm3 using zero padding in the frequency domain), a repetition time (TR) of 13.8 ms, an echo time (TE) of 2.8 ms, an inversion time (TI) of 400 ms, and a flip angle of 20°. The corresponding imaging protocol included a 3D T1-weighted fast RF gradient recalled acquisition in steady state with an inversion recovery prepulse The Rotterdam Study is an ongoing prospective cohort study, which started in 1990, in order to follow mid-adults from the city of Rotterdam (the Netherlands) over time for a variety of diseases Eh and Ej are the expected heterozygosities of the loci that an individual bears in homozygosis (h) and in heterozygosis (j), respectively. This index thus varies between 0  and 1 .Individual heterozygosity was estimated by the homozygosity by loci (HL) index http://www.1000genomes.org/): African ancestry in Southwest USA , Utah residents with Northern and Western European ancestry from the CEPH collection , Han Chinese in Beijing, China , Han Chinese South , Colombian in Medellín, Colombia , Finnish in Finland , British in England and Scotland , Iberian populations in Spain , Japanese in Tokyo, Japan , Luhya in Webuye, Kenya , Mexican ancestry in Los Angeles, California , Puerto Rican in Puerto Rico , Toscans in Italy , and Yoruba in Ibadan, Nigeria . We extracted the SNP data from the 1000 Genomes database using SPSmart (http://spsmart.cesga.es/engines.php), which is a web-based tool for accessing and combining large-scale genomic databases of SNPs We compared the average and the variation of the HL scores of the RS1 and RS2 samples Zygion left/right, Alare left/right, centers of the eyeballs, Nasion, Pronasale, Subnasale) were automatically localized on each scan (r>0.99) The positions of the nine mid-facial landmarks  and total asymmetry (TA) were approached through a geometric morphometric method e.g., . This waFA and TA scores were each regressed on the genotype data of the 102 SNPs using an ANOVA tree regression (R library rpart). We further calculated two separate general linear models regressing i) the FA scores and ii) the TA scores on age, sex , homozygosity by loci  and the 5 SNPs known to significantly influence distances within a face  for regressions and general linear models (GLMs), as well as Mathematica 8 to compute total and fluctuating asymmetry scores for each individual. According to Liu et al., genome-wide significance was set at


Recently, in vitro studies have demonstrated that adiponectin has antiangiogenic and tumor growth-limiting properties. Additionally, serum adiponectin levels have been associated with the risk of several cancers; specifically, serum adiponectin was significantly lower in lung cancer patients with advanced-stage disease. In this study, we examined the association of adiponectin gene promoter variations associated with adiponectin gene expression and plasma levels in non-small cell lung cancer (NSCLC) in a Han Chinese population. A total of 319 patients with NSCLC and 489 healthy individuals were recruited to evaluate the association of four adiponectin gene promoter single-nucleotide polymorphisms (SNPs)  with NSCLS risk. Additionally, we constructed haplotypes of these four SNPs and evaluated the association of these haplotypes with NSCLS risk. Our results showed that among these four SNPs, only SNP-12140G>A was associated with NSCLC risk(P<0.05). The haplotype analysis showed that no haplotype was associated with NSCLC after performing a Bonferroni correction (P>0.05). Additionally, an association analysis of the four SNPs stratified into pathologic stages I+II and III+IV showed that these SNPs did not exhibit significant differences between pathologic stages I+II and III+IV. Moreover, we did not observe any differences in allele and genotype frequency for these SNPs between adenocarcinoma and squamous cell carcinoma. Our results indicated that the G allele of SNP-12140may be a risk factor for NSCLC  in this Han Chinese population. Lung cancer is one of the leading causes of cancer deaths worldwide and has a 5-year survival rate of approximately 15%. In Chinet al. found that serum adiponectin was not significantly different in patients with lung cancer compared with controls, though it was significantly lower in patients with advanced-stage disease, suggesting that adiponectin could be a potential marker for lung cancer progression[et al. provided evidence for a direct effect of adiponectin on the proliferation and inflammation status of A549 cells, which supported the hypothesis that adiponectin plays a protective role in the lung and suggested that adiponectin could be a promising therapeutic target in lung diseases[Adiponectin is an adipose tissue-secreted protein that acts as an endogenous insulin sensitizer by binding to insulin receptors. Previouogression. Recentl diseases.et al. reported that adiponectin promoter single-nucleotide polymorphisms (SNPs) are associated with adiponectin concentrations[et al. later demonstrated that adiponectin promoter SNPs regulate adiponectin promoter activity[adiponectin promoter variations may have an impact on cancer risk.In 2006, Heid ntrations. Laumen  activity. TherefoWe previously reported the association of two adiponectin gene promoter SNPs (SNP-12410G>A and SNP-11377C>G) with NSCLC risk in a Han Chinese population, and the results showed that SNP-12140G>A (rs266730) is associated with increased NSCLC risk. To confThis protocol was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Review Boards of the No.1 and No.3 Affiliated Hospitals of Kunming Medical University. All participants provided written informed consent.The case group included 319 patients  who were diagnosed with NSCLC at the No.1 and No.3 Affiliated Hospitals of Kunming Medical University from July 2012 to May 2014. The histological type of lung cancer was identified according to the World Health Organization (WHO 2004) classifications. The pathologic stage was determined according to the International System for Staging Lung Cancer . Based oadiponectin promoter SNPs, namely SNP-12140G>A (rs266730), SNP-11426A>G (rs16861194), SNP-11391G>A (rs17200539) and SNP-11377C>G (rs266729), were genotyped using PCR amplification with a TaqMan assay. Primers and probes were purchased from Applied Biosystems . Selected PCR products were characterized by direct sequencing on a 3100 Genetic Analyzer .Genomic DNA was extracted from peripheral lymphocytes using a standard hydroxybenzene-chloroform method. Four 2 test was used to determine differences in allele, genotype and haplotype frequencies between the NSCLC and control groups, and the odds ratios (OR) with associated 95% confidence intervals (CIs) of allele-specific risks were calculated. Bonferroni correction was used for testing multiple comparisons. The association between each SNP and NSCLC was analyzed for the mode of inheritance using SNPStats software [The allele and genotype frequencies of the four SNPs were calculated by the direct-counting method. Hardy-Weinberg equilibrium (HWE) was tested for the SNPs in both the NSCLC and control groups. The linkage disequilibrium (LD) and haplotype frequencies (deduced from the phenotype) were calculated based on the genotyping results by the expectation-maximization algorithm in SHEsis software, 26.A χ2software . The Akasoftware . The staThe allele and genotype frequencies for SNP-12140G>A, SNP-11426A>G, SNP-11391G>A and SNP-11377C>G in the NSCLC and control groups are listed in Tables Significant LD (D') values between theSNP-12140G>A, SNP-11426A>G and SNP-11377C>G loci were found in all individuals. The D' value was 0.899 between SNP-12140G>A and SNP-11426A>G, 0.857 between SNP-12140G>A and SNP-11377C>G and 0.864 between SNP-11426A>G and SNP-11377C>G. Based on the LD result, we calculated the haplotypes of these three SNPs, and There were no differences in the allele and genotype frequencies forSNP-12140G>A, SNP-11426A>G and SNP-11377C>G between pathologic stages I+II and III+IV .Our results revealed no differences in the allele and genotype frequencies for SNP-12140G>A, SNP-11426A>G and SNP-11377C>G between AC and SCC.et al. found that serum adiponectin was not significantly different in patients with lung cancer compared with controls but that it was significantly lower in patients at advanced disease stages, suggesting that adiponectin could be a potential marker for lung cancer progression[et al. then undertook a meta-analysis to exploit the causal relevance of circulating adiponectin with cancer; their findings demonstrated that genetically higher circulating adiponectin conferred a protective effect against lung cancer but a risk for colorectal cancer[Recent evidence has demonstrated that adiponectin has antiproliferative and proapoptotic effects in breast cancer cell lines in vitro, 10. In ogression.Pei et aal cancer.et al. investigated the association of SNPs in the adiponectin gene  with NSCLC[et al. failed to observe an association for SNP-11377C>G (rs266729), which is located in the adiponectin promoter, with NSCLC[et al. reported that rs2241766 was associated with adiponectin levels, with the GG genotype correlating with increased adiponectin levels compared with the TT genotype [et al. also observed that the rs2241766 GG genotype or G allele was associated with significantly higher circulating adiponectin levels than the TT genotype, without heterogeneity[et al. and Yang et al. indicated that the G allele of rs2241766 was a potential protection factor for cancer risk[In 2011, Cui ith NSCLC, and theith NSCLC. Althougith NSCLC, their rgenotype . In addincer risk, 32. Theet al. found that SNP-11426A>G, SNP-11391G>Aand SNP-11377C>G within the adiponectin promoter were regulatory SNPs for adiponectin promoter activity[adiponectin promoter SNPs to evaluate the association of these SNPs and their haplotypes with NSCLC in a Han Chinese population. Our results confirmed our previous finding that the G allele of the adiponectin promoter SNP-12140G>A is a risk factor for NSCLC[et al. reported that adiponectin gene promoter SNP-11377C>G is associated with colorectal cancer risk[et al. failed to observe an association between SNP-11377C>G and colorectal cancer risk in patients from the UK[et al. may be due to differences between ethnic groups, differential environmental effects or false-positive results[et al. reported an interesting finding that genetically elevated circulating adiponectin may confer a protective effect against lung cancer but a risk for colorectal cancer[et al. [adiponectin promoter activity, gene expression, plasma adiponectin level and, ultimately, NSCLC risk. Unfortunately, to date, the role of SNP-12140G>A in adiponectin promoter activity and gene expression has not been tested. Therefore, the function of this SNP in adiponectin promoter activity and gene expression should be investigated in the future. It was an interesting finding that only SNP-12140G>A was associated with NSCLC in our study. Our data showed that SNP-12140G>A just was partly in linkage disequilibrium with SNP-11426A>G and SNP-11377C>G. Therefore, we assumed this could be possible one of causes of the divergence that only SNP-12140G>A associated with NSCLC in this Han Chinese population, but not SNP-11426A>G and SNP-11377C>G.In 2009, Laumen  activity. Consequfor NSCLC and thatncer risk. Howeverom the UK, statinge results. Pei et al cancer. Thus, tr[et al. , indicatet al. found that adiponectin level was not significantly different between lung cancer individuals compared with controls, though it was significantly lower in patients with advanced disease stage[In this study, we also observed that there were no differences in allele and genotype frequency for SNP-12140G>A, SNP-11426A>G and SNP-11377C>G between AC and SCC . In addiThere were other several limitations in the present study. A relatively small sample size may limit the statistical power of our study. The statistical power for the effect of SNP-12140G>A was calculated using PS software ,and we fadiponectin promoter SNP-12140G>A, SNP-11426A>G and SNP-11377C>G and NSCLC in a Han Chinese population and found that the G allele of SNP-12140G>A is a risk factor for NSCLC; individuals with the SNP-12140G>A GG genotype showed increased risk for NSCLC under log-addictive models. In the future, larger scale studies are needed to better clarify and examine the association of adiponectin gene promoter variations with NSCLC susceptibility. Moreover, the function of SNP-12140 in adiponectin promoter activity and gene expression should be investigated.In this study, we performed an association study for S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.


Restriction site associated DNA sequencing (RAD-seq), a next-generation sequencing technology, has greatly facilitated genetic linkage mapping studies in outbred species. RAD-seq is capable of discovering thousands of genetic markers for linkage mapping across many individuals, and can be applied in species with or without a reference genome. Although several analytical tools are available for RAD-seq data, alternative strategies are necessary for improving the marker quality and hence the genetic mapping accuracy.Populus deltoides × P. simonii. Two rough references were assembled from the whole-genome sequencing reads of the two parents separately. Based on the parental reference sequences, 3442 high-quality single nucleotide polymorphisms (SNPs) were identified that segregate in the ratio of 1:1. The maternal linkage map of P. deltoides was constructed with 2012 SNPs, containing 19 linkage groups and spanning 4067.16 cM of the genome with an average distance of 2.04 cM between adjacent markers, while the male map of P. simonii consisted of 1430 SNPs and the same number of linkage groups with a total length of 4356.04 cM and an average interval distance of 3.09 cM. Collinearity between the parental linkage maps and the reference genome of P. trichocarpa was also investigated. Compared with the result on the basis of the existing reference genome, our strategy identified more high-quality SNPs and generated parental linkage groups that nicely match the karyotype of Populus.We demonstrate a strategy for constructing dense genetic linkage maps in hybrid forest trees by combining RAD-seq and whole-genome sequencing technologies. We performed RAD-seq of 150 progeny and whole-genome sequencing of the two parents in an F1 hybrid population of Populus.The strategy of simultaneously using RAD and whole-genome sequencing technologies can be applied to constructing high-density genetic maps in forest trees regardless of whether a reference genome exists. The two parental linkage maps constructed here provide more accurate genetic resources for unraveling quantitative trait loci and accelerating molecular breeding programs, as well as for comparative genomics in The online version of this article (doi:10.1186/s12864-016-3003-9) contains supplementary material, which is available to authorized users. Populus trichocarpa [P. euphratica [Picea abies [Picea glauca [Pinus taeda [Eucalyptus grandis [Forests cover about 30 % of Earth’s land area and are of significant economic and ecological importance . Althougchocarpa  and P. ephratica ), three ea abies , Picea ga glauca  and Pinuus taeda ), and Eu grandis . The ava grandis –13. MoreEucalyptus [Populus [Over the past two decades, more and more linkage maps have been constructed for a large number of forest trees , 14. Onecalyptus  and Popu[Populus , they al[Populus .Next-generation DNA sequencing (NGS) technologies can produce tremendous amounts of DNA sequence data at a consistently low cost, allowing us to obtain thousands of SNPs for genetic mapping. However, it is infeasible to apply whole-genome sequencing directly to hundreds of individuals in a mapping population because the total expense would be so high that most research projects cannot afford it. Therefore, several DNA library preparation methods for NGS have been developed to solve this problem by reducing genome complexity and adding DNA barcodes to samples . These mPopulus deltoides × P. simonii. The female parent P. deltoides has the characteristics of fast growth and resistance to disease but a poor rooting ability, while the male parent P. simonii has strong hardiness in cold, heat, drought and other bad conditions, and an excellent regeneration ability. The hybrids of the two parents display significant difference in morphological and physiological traits, providing a permanent material for mapping QTLs. Short paired-end (PE) reads of whole-genome sequencing data with high coverage from each parent were de novo assembled into contigs, forming a rough reference sequence of the parent. Based on each of the two parental reference sequences, two SNP datasets were identified and validated with each other to generate a high-quality SNP dataset for linkage mapping. Consequently, two high-quality parental linkage maps were constructed, each with a number of linkage groups that matched the karyotype of Populus perfectly. Collinearity between the parental linkage maps and the reference genome of P. trichocarpa was also investigated. Compared with the result of linkage mapping based solely on the reference genome of Populus [In this study, we performed RAD-seq data analysis for genetic mapping by combining the use of RAD-seq data from the progeny with the whole-genome sequencing data of their parents in an F1 hybrid population of  Populus , our strP. deltoides and P. simonii, which was generated in 2011 in Xiashu Forest Farm of Nanjing Forestry University, Jurong, Jiangsu Province, China [The mapping material was a population of interspecific F1 hybrids between e, China . We selee, China .We performed RAD sequencing of the 150 progeny and whole-genome sequencing of the two parents. The RAD library for the progeny was constructed following the protocol described by Baird et al.  with a fThe raw sequencing data were processed to clean the data with the same standard quality control pipelines in the two companies (i.e. BGI and BMK), and then to obtain high quality (HQ) data using NGS QC toolkit . First, k-mer lengths were used and the optimal assembly was selected according to several parameters such as N50 and average contig length.To improve the quality of genome assembly, we used the Perl program ErrorCorrectReads.pl in ALLPATHS-LG  to correP. deltoides ‘I-69’ and the male P. simonii ‘L-3’. We performed SNP calling and genotyping across the hybrid F1 population based on the two parental rough genome sequences and the reference genome sequence of P. trichocarpa separately [mem command with default parameters;mapping the filtered HQ reads from each individual to a reference genome sequence to generate a sequence alignment/map (SAM) format file using the BWA filtering out those records having an edit distance greater than 9 or best alignment score less than 60 or second-best alignment score greater than the best alignment score in the SAM file of each individual;converting the filtered SAM file to BAM format and then sorting and indexing with SAMtools;samtools mpileup –g –I for all individuals;producing BCF files with the command bcftools call –m –v for each parent;generating VCF files with the command filtering SNPs from the parental VCF files such that each SNP has a mapping quality score of at least 20 and a read coverage depth (DP) of at least 5, and merging the two parental SNP datasets into a list site file;bcftools call –m –f GQ –T using the list site file generated in step (6);for all individuals, including the two parents, creating VCF files with the command calling genotypes at all the list sites for each individual and filtering using stringent conditions with DP ≥ 10 and genotyping quality (GQ) > 50;generating a SNP genotype dataset for the common SNP sites across the two parents and all 150 progeny.The two sets of contigs assembled above were considered to be the rough genome sequences of the female parately , using tparately , SAMtoolparately ), and seP. deltoides, P. simonii and P. trichocarpa, denoted by PD, PS and PT, respectively. The SNPs in those datasets were further filtered for linkage mapping according to Mendel’s law of segregation.Finally, three SNP genotype datasets were generated on the basis of the genome sequences of p < .01) or had more than 10 % missing genotypes in the population, it was removed from linkage analysis. To use the SNPs called from the two parental rough genome sequences, the SNP loci that were identical between the filtered PD and PS datasets, at which each individual has the same genotype in the two datasets , were chosen for linkage mapping. Because the overwhelming majority of SNPs were found to segregate in the ratio of 1:1 in the mapping population, we had to construct two parental linkage maps using the traditional pseudo-testcross mapping strategy [ab×aa, and the paternal linkage map with the identical SNPs of segregation type aa×ab. For each linkage map construction, two-point linkage analysis was first performed for all pairs of SNP loci and then SNP markers were grouped under a logarithm of odds (LOD score) threshold using the software FsLinkageMap. Next, SNP markers in each linkage group were ordered three times using JoinMap with the maximum likelihood mapping method and once using FsLinkageMap. The optimal order was chosen as the mapping order of the linkage group according to the four ordering results with the two software packages and the ordering criterion of the minimum sum of adjacent recombination fractions [http://www.mayura.com).We performed chi-squared tests on all the SNPs in the PD, PS and PT datasets generated above to check whether they follow Mendel’s law of segregation. If a SNP deviated seriously from the Mendelian segregation ratio  and 258,870,468 (79 %) high-quality reads for the parents ‘I-69’ and ‘L-3’, respectively, and an average of 13,001,952 (97 %) high-quality reads for the progeny. The final high-quality dataset of each parent was used for de novo assembly and each individual dataset for SNP genotype calling  based on the three SNP datasets PD, PS and PT separately. After a series of filtering procedures , 6513 SNPs with segregation type of ely Fig. . If the aa×ab, following the Mendelian segregation ratio of 1:1 with p ≥ .01 and genotyped in at least 90 % of the progeny, the datasets generated from PD, PS and PT were denoted by PD2, PS2 and PT2, respectively. Also, the identical SNP datasets between PD2 and PS2, between PD2 and PT2, between PS2 and PT2, and among the three datasets PD2, PS2 and PT2 were denoted by PDS2, PDT2, PST2, and PDST2, respectively. The numbers of SNPs contained in these datasets are shown in Fig. For those SNPs having the segregation type P. deltoides ‘I-69’ and the paternal P. simonii ‘L-3’, respectively. To improve mapping efficiency, when two or more SNPs were identical (i.e. complete linkage) within PDS1 or PDS2, and adjacent SNPs were within 1 kb on a contig, a single SNP was chosen to represent the group for linkage analysis. This reduced the number of SNPs in PDS1 from 2973 to 2012 and in PDS2 from 1979 to 1430. The final 2012 SNPs with segregation type ab×aa were assigned to 19 linkage groups  and LG19 (3.33 cM). Interestingly, it was noted that DLG19 has more number of SNPs 45) than SLG19 (35) while its length (106.87 cM) is significantly shorter than that of the later (159.97 cM). This could be explained by the recombination suppression phenomenon possibly occurred on chromosome 19 in the female parent due to the sex determination through a ZW system in  than SLGP. trichocarpa  SNPs on the maternal linkage map and 1157 (80.9 %) SNPs on the paternal linkage map segregated identically to at least one SNP in the PT1 or PT2 dataset, in which each SNP has its position information on the reference genome of .2 % SNPsHere we demonstrated a novel strategy for constructing high-quality genetic linkage maps in forest trees by combining the use of RAD-seq with whole-genome resequencing technologies. This genetic mapping strategy may be applicable to most outbred forest species in which no reference genome is available. With the plummeting cost of NGS, it is feasible for most laboratories to perform RAD-seq across tens to hundreds of individuals and to sequence the whole genomes of their two parents in an F1 hybrid population. Assemblies from the parental whole-genome sequencing reads can be used as rough references, and RAD-seq reads of each progeny as well as the reads from each parent can be aligned to them separately. Thus, hundreds of thousands of SNPs could be discovered and genotyped across the population with available software packages designed for NGS data, and then thousands of high-quality SNP markers may be selected for genetic linkage mapping, in terms of the Mendelian segregation ratio, the fraction of missing genotypes and other features such as mapping quality and read coverage depth. Two SNP genotype datasets are generally derived from the two parental rough reference genomes and can validate each other using the Hamming distance across the individuals to improve mapping data quality substantially. After obtaining such a large number of high-quality SNP genotypes across the F1 mapping population, current linkage mapping tools are applied with the strategy of choosing the best marker orders  to construct parent-specific dense linkage maps.https://phytozome.jgi.doe.gov/pz/portal.html), the assembled rough reference sequences of the two parents, P. deltoides and P. simonii, may be more appropriate for SNP and genotype calling in our mapping population, because there are divergences between the P. trichocarpa reference genome and the two parental genomes. Furthermore, the reference genome assembly is not perfect with, to date, more than one thousand scaffolds still unassigned to any chromosomes. In a previous study [P. trichocarpa for SNP marker discovery and obtained 20 linkage groups for each parental linkage map, each with one linkage group ambiguously assigned to any chromosome. In contrast, in this study, we used the parental rough reference sequences and RAD-seq data from only half of the progeny to generate 19 linkage groups in each parental linkage map, which perfectly matches the karyotype of Populus (2n = 38).RAD-seq has been extensively applied to SNP and RAD marker discovery across populations in species with or without a reference sequence , 35. Wheus study , we mappaa×ab and the other ab×aa, cannot provide any recombination information [ab×ab or ab×cd should be identified as bridges to link the two types of SNPs segregating in 1:1 ratio. With the decreasing cost of NGS, this could be resolved by resequencing the whole genomes instead of RAD-seq across many individuals in the mapping population to identify more fully informative SNPs.Like most genetic mapping studies in forest trees , 46, 47,ormation , the twoWe used 150 progeny for calling genotypes from RAD-seq data and for the subsequent construction of the genetic linkage maps. Such a moderate sample size can provide enough information to estimate the recombination fraction accurately between any two genetic markers that follow a Mendelian segregation ratio of 1:1. Because there are only four combined genotypes for a pair of markers each with a segregation ratio of 1:1, the average count of the combined genotypes was about 38 in our mapping population, which led to an expected LOD score of 5.36 for two moderately linked loci with a recombination fraction of 0.30 , 50. ThiP. deltoides and P. simonii constructed here with high density and quality perfectly match the karyotype of Populus, and provide important genetic resources for identifying QTLs, accelerating molecular breeding programs and performing comparative genomics in Populus.Assembled contigs of whole-genome PE reads from each parent in an F1 hybrid population can be used as a rough reference for performing SNP calling and genotyping with RAD-seq data across the whole population. The two SNP genotype datasets each based on one parental reference can confirm each other to generate a high-quality genotype dataset for linkage mapping. This strategy could be applied to highly heterozygous undomesticated forest trees with or without a reference genome to construct high-density genetic linkage maps, which is difficult with traditional molecular markers. Both of the parental genetic linkage maps of


Single base level information from next-generation sequencing (NGS) allows for the quantitative assessment of biological phenomena such as mosaicism or allele-specific features in healthy and diseased cells. Such studies often present with computationally challenging burdens that hinder genome-wide investigations across large datasets that are now becoming available through the 1,000 Genomes Project and The Cancer Genome Atlas (TCGA) initiatives.We present ASEQ, a tool to perform gene-level allele-specific expression (ASE) analysis from paired genomic and transcriptomic NGS data without requiring paternal and maternal genome data. ASEQ offers an easy-to-use set of modes that transparently to the user takes full advantage of a built-in fast computational engine. We report its performances on a set of 20 individuals from the 1,000 Genomes Project and show its detection power on imprinted genes. Next we demonstrate high level of ASE calls concordance when comparing it to AlleleSeq and MBASED tools. Finally, using a prostate cancer dataset we report on a higher fraction of ASE genes with respect to healthy individuals and show allele-specific events nominated by ASEQ in genes that are implicated in the disease.ASEQ can be used to rapidly and reliably screen large NGS datasets for the identification of allele specific features. It can be integrated in any NGS pipeline and runs on computer systems with multiple CPUs, CPUs with multiple cores or across clusters of machines.The online version of this article (doi:10.1186/s12920-015-0084-2) contains supplementary material, which is available to authorized users. Next-generation sequencing (NGS) provides unprecedented single base level information of the human genome and transcriptome and opens up the investigation of previously unexplored biological questions. By integrating information from individuals’ genetic makeup accessible in sequencing reads, it is possible to quantitatively estimate DNA somatic lesion clonality and infer tumor evolution, mosaicisms, or allele specific expression and binding -5. Allelpileup), which is fundamental in ASE studies, ASEQ combines the power of multi-threaded computation with samtools C APIs, a programming library that offers rapid random access functionalities to indexed alignment files  ; otherwise the method calls homozygous genotype, either for the reference or the alternative base. The second method, binom, implements a binomial test with probabilities p and q for the reference and the alternative allele, respectively. To account for the reference bias mapping [The auxiliary GENOTYPE mode determines the genotype at each input SNP position. The GENOTYPE mode is not designed to discover SNPs, but rather to compute the genotype of an input sample at known SNP positions . Given a list of known SNPs the application first computes the pileup from each NGS data file using the fast PILEUP computational engine and then determines the genotype calls for each sample independently. To perform genotype calls the tool offers two strategies. The first method,  mapping , we applgene model input that requires a list of coding heterozygous SNPs of the sample and a list of genes start/end coordinates; (ii) the transcript model input that requires a list of heterozygous SNPs of the sample and a list of transcripts with exonic coordinates. In the gene model option ASEQ matches coding SNPs and gene coordinates, whereas in the transcript model option transcript specific exon coordinates are considered for each SNP. The input list of heterozygous SNPs can be generated through the GENOTYPE mode or any other suitable SNPs genotyping tool, e.g. GATK [The main ASE mode performs allele specific expression analysis. Two input options are implemented: (i) the .g. GATK . Figure a, ASEQ returns a positive ASE result if the proportion of SNPs passing the test (denoted as ASE score) is greater than a predefined threshold . For all gene-sample pair without available heterozygous SNPs or RNA-seq data coverage below a user-specified threshold, the application returns a flag of not available for ASE calculation. Additionally, when multiple samples are investigated, the application also returns an ASE gene flag if it shows ASE in at least N samples available for the gene ASE calculation . As output, ASEQ provides both sample-based and aggregated ASE results.Given a gene, the list of coding heterozygous SNPs for a study individual and the RNA-seq data file, the application performs the heterozygosity test on the RNA data at each input SNP position . A position is annotated as showing ASE, when a non-heterozygous call in NGS RNA-seq data is detected. To control for false positive ASE calls due to different depths of coverage between the DNA- and the RNA-seq data, the application performs an additional statistical test on the reference and alternative alleles counts proportions from the DNA and the RNA NGS data (Fisher Exact Test), whenever the DNA coverage information is available. For each sample and each gene with available heterozygous SNPs in the sample For each execution mode the user can specify the minimum base quality score, the minimum read quality score and the minimum depth of coverage for the pileup computations and the significance threshold for the statistical tests used in the GENOTYPE and ASE modes .D of SNPs in coding regions per gene, a value I representing the frequency of heterozygous SNPs per individual and assuming that: (i) one SNP is sufficient to perform ASE analysis on a gene, (ii) heterozygous SNPs are uniformly distributed across the genome of an individual and (iii) SNPs are independent, we can estimate the upper-limit of the number Ta of genes available for ASE calculation:M is the maximum observed number of coding SNPs overlapping a gene, Di is the number of genes with i overlapping coding SNPs and 1 − P(X = 0) with X = Binom is the probability that at least one of these i SNPs is heterozygous. To verify the validity of the formula we inspected the setting of the well represented Caucasian population in the HapMap dataset. Figure D of SNPs per gene reflecting dbsnp 138 and UCSC hg19 gene catalogue and Figure Ta calculation. In this setting the empirically assessed value I = 0.3 results in Ta = 6612 ASE suitable genes (23%) that is a valid over-approximation of the observed distribution . We tested the PILEUP mode against the canonical ols tool . Both mpWe next tested the performances with respect to the size of the input NGS data files adopting two strategies: random sampling of reads Figure B and ranb. In Figure For a direct comparison with other tools implementing parallel pileup computation strategies, we compared ASEQ performances against GATK Pileup module htperc and binom are comparable  scored > =97% and > =92%, respectively (for depth of coverage > =10), and mean FDR scored <0.3% in both cases , meaning that the majority of heterozygous SNPs on the gene support ASE. The prevalence of high ASE scores may suggest that ASE mechanisms involving most part of the whole gene (e.g. whole-gene ASE) are relatively more common.To investigate the extent of ASE in a human dataset, we selected 20 individuals from 1,000 Genomes Project collection for which matched WES and RNA-seq data are publicly available. We considered all coding SNPs from dbsnp 138 CEU catalogue present in UCSC hg19 gene catalogue and considered the same gene catalogue to create our gene model by means of RSEQtools . Using tgold-standard to test ASE analysis tools, we quantify ASEQ performances by first comparing it with a trio analysis based tool, AlleleSeq [c, see Additional file P < 10− 8 Fisher Exact Test), supporting a significant concordance between the two methods  further supports the ASE detection power of ASEQ.In the absence of a lleleSeq , and witlleleSeq , and thelleleSeq . Figure P < 0.05 Fisher Exact Test, see Table Finally we investigated to what extent ASEQ is able to detect known imprinted genes, using the genomic imprinting website (geneimprint.com). On average .high ASE score (>0.5). As the distribution of ASE genes percentages in the Barbieri et al. dataset was significantly higher than in the 1,000 Genomes Project dataset   included two genes implicated in prostate cancer; specifically increased ADAM15 and decreased PXMP4 expressions [ADAM15 mRNA and protein levels are over-expressed in prostate cancer and its expression is significantly increased during metastatic progression. PXMP4 is a peroxisomal membrane protein that undergoes hypermethylation associated with gene silencing during cancer progression. Overall, these findings support the hypothesis that ASE is enriched in cancer cells.We next asked if individuals with evidence of ASE for a specific gene demonstrate corresponding differential transcript levels : Platform independentProgramming language: CLicense: MITaNote that a gene may span multiple SNPs.bNote that while ASEQ PILEUP mode returns the read count for each base separately, to have the same output data GATK Pileup mode would require an additional processing step that for simplicity here is not considered in the overall GATK Pileup execution time.cDifferent tools embed different preprocessing, filtering and processing pipelines along with different set of conditions to be satisfied for an ASE call to be made. This may result in different set of analyzable genes.


Highly favorable genomic energy measures were found to correlate with highly conserved SNP haploblocks. Moreover, the most conserved haploblocks were associated with an evolutionarily conserved regulatory element and domain.Single nucleotide polymorphisms (SNPs) represent an important type of dynamic sites within the human genome. These common variants often locally correlate within more complex multi-SNP haploblocks that are maintained throughout generations in a stable population. Information encoded in the structure of SNPs and SNP haploblock variation can be characterized through a normalized information content metric. Genodynamics is being developed as the analogous “thermodynamics” characterizing the state variables for genomic populations that are stable under stochastic environmental stresses. Since living systems have not been found to develop in the absence of environmental influences, this paper describes the analogous genomic free energy metrics in a given environment. SNP haploblocks were constructed by Haploview v4.2 for five chromosomes from phase III HapMap data, and the genomic state variables for each chromosome were calculated. An  The human genome consists of 3 billion nucleotides, most of which are fixed alleles. A significant number of sites (about 0.1%) consist of single nucleotide polymerphisms (SNPs) non-randomly distributed across the human genome. SNPs are  bi-allelic dynamic sites on the human genome whose allelic distribution reflects the homeostasis of a population within a given environment . Here, eIn developing metrics for the interaction of the human genome with its environment, the genomic environment is the stochastic bath driving variations within a locally viable population. SNPs are dynamic sites that are often highly correlated into SNP haplotypes maintained with fixed frequencies within a given stable population. Combinations of SNPs that are very highly correlated within a population are said to be in linkage disequilibrium (LD). It should be noted that certain SNP allelic combinations never appear within the population. Therefore only certain SNP haplotypes are biologically viable and generationally maintained.The dynamically independent statistical micro-states are SNP haplotypes together with SNP sites that are not in LD with any other SNPs. The linkage of several SNPs as conserved units that are passed between generations represents a type of statistical phase transition in forming complex dynamic units for a population within a given environment. It is therefore very useful to develop information metrics for SNP microstates that can quantify viable sequence variation in the human genome.Genodynamics explores nucleotide structure-function relationships of common sequence variation and population genetics, grounded in first principles of thermodynamics and statistical physics . Our useentropy quantifies the dis-order of a physical system  entropy of a SNP haploblock consisting of a set of strongly depen-dent bi-allelic SNPs is taken to be the statistical average of this additive measure: (H)n is the number of bi-allelic SNP locations in haploblock H, and h occurs in the population. This measure of maintained (dis)order takes the value of zero for a completely homogeneous population with only one haplotype  takes the form: a occurs in the population. As defined here, the entropy has no dimensional units. The total specific entropy of the genome in the specified environment is given by the sum over all genetically viable blocks, including correlated SNPs in the haploblocks, along with individual SNPs between the haploblocks that are not in LD,For bi-allelic SNPs that are not in LD, there are only 2 possible states at that location. Therefore, the specific entropy of the SNP location PopulationN, that is, GenomeS = population SGenomeN, making entropy an extensive state variable.This insures that all dynamic SNP degrees of freedom are included in calculating the genomic entropy. Because this entropy measure is additive, it also quantifies the entropy within any region of the genome. The overall entropy of a population distribution is proportional to the size of the population IC = Smax − S. Such an information measure is likewise additive due to the additive nature of the entropy , h in SNP haploblock H, h, and (H)V. In all subsequent expressions, any genomic effects that would modify the genomic volume will be neglected The statistical “genomic energy” of a population in a given environment is expected to be an additive (extensive) state variable that depends upon the entropy, the populations of various allelic constituencies, and possibly the “genomic volume” of the environment, if population pressures have a significant effect on the environment. The functional dependence of the contribution of haploblock H to the average genomic energy ET and the populations, through the Legendre transformationAs is the case for thermodynamics and statistical physics, it is quite convenient to define an additive free energy state variable that is most naturally expressed as a function of the potential of the environmental bath E = 0dT. As one recognizes that living cells have evolved their cellular functions within the warm, wet physiologic environment, one can safely conclude that a homeostatic living population distribution has evolved directly in association with the ecosystem within which it is being characterized. Thus, we assert that the evolution of living populations cannot be separated from their interchanges with the environment. In a statistical environment that is stochastically varying, it is the genomic free energy rather than the genomic energy that is minimized. The genomic free energy is a state variable that balances between conservation and variation of SNP haplotypes within an environment. Minimizing the genomic free energy optimizes the population’s survivability under environmental stresses, establishing the balance between conservation and variation in the dynamics of the population distribution.A focus on the free energy as the fundamental dynamic state variable has the advantage of inherently including environmental-genomic interchanges as necessary considerations in describing the dynamics. It is a particularly convenient parameter for describing dynamics in a fixed environmental bath for which , resulting in non-conservation of the number and SNP composition of the haploblocks. This is in marked contrast with the standard micro-units in statistical physics, whose universal energy states are only weakly dependent upon the environment, and have well defined conservation properties with regards to the creation of new states (or changing dynamic degrees of freedom). Therefore, rather than seeking universal energy measures that are independent of the genomic environment, the emphasis here will be based on establishing convenient genomic measures of the dynamics that are inseparably coupled with environmental parameters. Since the allelic potentials, given by h, the formulation will be developed in a manner that most directly interprets these genomic energy measures.For the genome, only the site locations and bi-allelic nature of the specific SNPs are conserved parameters. In addition, phase transitions involving the stability of SNP haploblock structures are common between differing populationsh given by Using the differential form for the haploblock free energy (H) from , we can (H) in any of the previous formulas with the SNP location (S). The total genomic free energy will be a sum over all SNP haploblocks and non-linked SNPs given by: Values for all of these additive genomic state variables can be likewise assigned to those SNPs that are not in linkage disequilibrium by simply replacing the particular haploblock index We further examined the condition that a stable population is defined by the genomic data. Our condition will require that the genomic free energy be a minimum under changes in the population within the local environment when the population is stable, that is, (H), while the average allelic potential at a non-linked SNP location (S).The average allelic potential within a SNP haploblock a shows the particular allele at SNP location (S).From Genomeμ, which is the sum over all block potentials and SNP potentials, is seen to vanish if the population does not increase or decrease. This means that a stable population is balanced with regards to its overall sum over allelic potentials, Genomeμ=0. The genomic free energy is lowered by a population with negative overall genomic potential Genomeμ<0 if its size increases, while if Genomeμ>0 the genomic free energy is lowered if the population decreases.Our population stability condition incorporates Hardy-Weinberg equilibrium  in populET, and allelic potential differences should directly reflect in the ratio of the frequencies of occurrence of those haplotypes within the population. A functional form that has these properties is given by: As is the case of thermodynamics, the additive allelic potentials (H)n SNPs in its state of highest variation with all mathematically possible haplotypes occurring with frequencies n(H) μ̃. The unit μ̃ will be universal across all populations of a given species, but likely differs between species. Solving the previous equation, the allelic potential of the haplotype h or allele a in an environmental bath characterized by environmental potential ET can be expressed as: (S) has n(S) = 1. Using our identifications, a lower allelic potential is then associated with a higher conservation of the SNP haplotype within the population, as high entropy is associated with large variation within the population. The ability to assign a well defined genomic energy measure for an individual haplotype once the environmental potential ET is known allows this formulation to establish biophysical measures beyond statistical statements about the population as a whole.The genomic energy labeled μ̃ will be defined as the unique allelic potential that will insure that a single  SNP will be in its state of highest variation (S) into a given allele Fixingμ ≤ 〈μ(H)〉 ≤ n(H)μ̃ .SNP haploblocks that are highly conserved relative to the whole genome will have negative block potentials, while those that are highly varying will have positive block potentials. The block potentials typically lie within the range specified by n(H) amplifies SNP haploblock allelic potentials.The number of highly correlated SNPs within the haploblock ET, the block potentials 〈μ(H)〉 and the SNP potentials 〈μ(S)〉 can only be defined for a population, the individual allelic potentials h and alleles a are unique to the individual. An individual’s overall allelic potential is not a universal parameter, but rather depends strongly upon the environment. Thus, the overall allelic potential of an individual is not an essentially fixed microphysical genomic energy state, in contrast to the energetics of particles in statistical physics. An environment within which an individual haplotype or allele has a negative allelic potential tends to conserve that characteristic, while a haplotype or allele that has a positive allelic potential provides diversity and viable genomic variation within that environment. The value of the allelic potential gives a direct measure of the dynamic (un)favorability of a haplotype as a function of the environment.One should note that while the environmental potential To demonstrate the usefulness of the previously defined genomic state variables, the parameters will be calculated using genomic data for stable populations. We choose to utilize genotype data provided by the HapMap Project on the Yoruba in Ibadan, Nigeria (YRI) and the Utah residents with ancestry from Northern and Western Europe (CEU). Because of the time involved in the calculations, we have chosen representative large, medium and small chromosomes  within the genome to examine the uniformity of the genomic potentials, and comparisons between populations.in silico analysis was performed on SNP haploblocks with the lowest genomic energy measures on chromosome 6 scanning for associated regulatory elements, signatures of positive selection, protein domains, molecular functions and biological processes using publically available bioinformatics tools =1.26 GEUs for the YRI population, and ET,(CEU)=1.12 GEUs for the CEU population.It will be assumed that the environmental potential 1≅0.90, NIC6≅0.90, NIC11≅0.89, NIC19≅0.85 and NIC22≅0.87; while the NIC values for the YRI population are: NIC1≅0.79, NIC6≅0.80, NIC11≅0.79, NIC19≅0.74 and NIC22≅0.76.The distributions of the NIC values across the genomes of the YRI and CEU populations are demonstrated in ET.The genomic energy spectra for chromosome 6 of the YRI and CEU populations are demonstrated in (H)n is the number of SNP locations in haploblock H. This indicates that those SNP haploblocks that are highly conserved are seen to have block potentials that approach the fixing potential μfixing for the given specific environment times the number of SNP locations in the block.The block potential as a function of the number of SNP locations in the haploblock for each population was examined, and this is illustrated in The number of SNP haploblocks within given intervals of NIC as a measure of the proportion of haploblocks that maintain a specific degree of variation were plotted, and bar graphs of these proportions are demonstrated in The block spectrum of SNP haploblocks in the MHC region for the populations of interest was examined. The genomic energies for the YRI population are Block 3013 is located between 6p22 and 6p21.3 bands  on chromosome 6 . It has ZNRD1, PPP1R11 and RNF39 are genes with functional proteins, whereas HCG8 and ZNRD1-AS1 are both non-coding RNAs (ncRNAs). HLA-J is a transcribed pseudogene. ZNRD1, PPP1R11, and RNF39 are highly conserved across species ranging from chimpanzee to zebrafish. These genes also display signatures of positive selection, but only in populations of European descent. Several putative and confirmed transcription factor binding sites (TFBS) are in Block 3013. Also, several broadly conserved microRNAs (miRNAs) are in Block 3013. It is worth noting that the ncRNA, ZNRD1-AS1, is a natural antisense transcript (NAT) that regulates the expression of ZNRD1.Block 7016 is located on the 6q24 band  on chromosome 6 . This blArabidopsis thaliana. Even though the protein coding genes in this block are highly conserved across species, there were no signatures of positive selection associated with any of the genes in this block. There are several putative and confirmed TFBS associated with Block 7016. Like Block 3013, Block 7016 also has several broadly conserved miRNAs. The ncRNA, RP11-54515.3, is also a NAT which regulates the expression of SHPRH and FBXO30.EPM2A, SHPRH and FBXO30 are genes with functional proteins whereas RP11-54515.3 is a ncRNA. The protein coding genes located in this block are also highly conserved across species ranging from chimpanzee to Listed in We have developed genomic energy measures for the human genome that relate the distribution of alleles within a stable population to state variables associated with the environment within which that population resides. The state variables defined by common variations utilize the entropy of the statistical distribution of alleles to establish normalized information measures for persistent dynamic units within arbitrary regions of the genome, as well as for the genome as a whole. For our initial analysis, YRI and CEU were chosen as representative populations in or very near homeostasis with their respective environments. Moreover, these populations have significant differences in the degree of variation in SNP allele and haplotype frequencies. As demonstrated in We further made comparisons of genomic energy measures between the individual SNP haploblocks within chromosome 6 which is illustrated in There is another interesting characteristic of the block potentials that was seen across all the chromosomes examined. This feature was discovered upon exploring the dependency of the block potentials upon the number of SNP locations within those haploblocks . AlthougIt was instructive to directly compare the informatics of chromosome 6 in the two populations. The NIC takes values between zero and one, where a value of zero indicates maximal variation in SNP haplotypes, while a value of one indicates complete sequence homogeneity of the population. We plotted the number of SNP haploblocks within given intervals of NIC as a measure of the proportion of haploblocks that maintain a specific degree of variation . It is cTo further examine the biophysical interpretations of genomic energies, we considered the block spectrum of SNP haploblocks in the MHC region for the populations of interest. A striking feature of comparison between the spectra is that despite the overall higher diversity in the YRI population as quantified in its considerably lower NIC when compared to the CEU population, the YRI population had genomic energies that were considerably more conserved This is also apparent from the lower value for the average block potential demonstrated by the middle dashed lines in Given that this region is important for encoding immune responses, it is expected that it would be particularly sensitive to environmental influences. Surprisingly, the most highly conserved haploblock found within any of the chromosomes thus far examined is the Block 3013 on chromosome 6 in the MHC region of the YRI population, while the most highly conserved haploblock in the CEU population is also on chromosome 6, Block 7016, though this block is not located in the MHC region. Both blocks have NIC values approaching one (complete sequence homogeneity of the population) and the protein coding genes located in these blocks are highly conserved across species, implying that these genes may play a fundamental role in the biological processes necessary for life. The protein coding genes ZNRD1, RNF39 and PPP1R11, along with the ncRNA ZNRD1-AS1, have been associated with disease states that are related to autoimmunity, immunity, and infection; while EPM2A and SHPRH have been associated with glycogen metabolism, cancer, and chemical dependency . In addiMoreover, we observed that Blocks 3013 (YRI) and 7016 (CEU) had genes that bind zinc ions and contain zinc finger (ZNF) domains. Zinc is a heavy metal that is an essential structural component of many proteins which include intracellular signaling enzymes and transcription factors . Zinc anIn summary, the use of genomic energy units (GEUs) as a biophysical metric in SNP haploblock analysis has provided insights into the inherent structure and conservation of information in the human genome. We have demonstrated that highly favorable allelic potentials correlate with highly conserved genomic information units, in this case SNP haploblocks. Furthermore, the protein coding genes associated with the haploblocks of lowest block potential have strong homology across species underlining their fundamental role in the biological processes necessary for life. In addition to this, a conserved regulatory element and an evolutionarily conserved protein domain were also found in these blocks.The development of genomic energy measures for the human genome relates the distribution of allele frequencies within a stable population to state variables associated with the environment within which that population resides. The state variables defined by the frequencies of common variants utilize the entropy of the statistical distribution of alleles to establish normalized information measures. Moreover, ‘genodynamics’ introduces more robust metrics for defining populations based on the genotypes of all individuals in the population as opposed to many current metrics based on the most frequent or common genotype in the population.The NIC of the whole genome was found to determine an overall environmental potential that is a state variable which parameterizes the extent to which the environment drives variation and diversity within the population. Once this environmental potential  has been determined, the genomic energies of individual alleles (nucleotides) and sets of alleles (haplotypes), as well as statistically averaged genomic energies for each persistent dynamic unit (haploblocks), can be directly calculated.The assignment of genomic energies to alleles within a given environment allows the parameterization of specific environmental influences upon shared alleles across populations in varying environments. We are examining simple allelic dependencies on environmental parameters for future presentation.