Epigenetic Pattern on the Human Y Chromosome Is Evolutionarily Conserved

Zhang, Minjie; Wang, Chuan‐Chao; Yang, Caiyun; Meng, Hao; Agbagwa, Ikechukwu O.; Wang, Ling-Xiang; Wang, Yingzhi; Yan, Shi; Ren, Shancheng; Sun, Yinghao; Pei, Gang; Liu, Xin; Liu, Jiang; Li, Jin; Li, Hui; Sun, Yingli

doi:10.1371/journal.pone.0146402

Cited by 14 publications

(16 citation statements)

References 54 publications

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“…“CpG islands” in the 5’ regulatory regions of many genes (~56%), are involved in transcription down-regulation and histone deacetylase recruitment (4,5). The pattern of methylation has both allele-specific and evolutionary conservation, as well as tissue-specific and cell-specific variations (6-8). …”

Section: Introductionmentioning

confidence: 99%

The NCI-60 Methylome and Its Integration into CellMiner

et al. 2017

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A unique resource for systems pharmacology and genomic studies is the NCI-60 cancer cell line panel, which provides data for the largest publicly available library of compounds with cytotoxic activity (~21,000 compounds), including 108 FDA-approved and 70 clinical trial drugs as well as genomic data, including whole-exome sequencing, gene and microRNA transcripts, DNA copy number, and protein levels. Here we provide the first readily usable genome-wide DNA methylation database for the NCI-60, including 485,577 probes from the Infinium HumanMethylation450k BeadChip array, which yielded DNA methylation signatures for 17,559 genes integrated into our open access CellMiner version 2.0 (https://discover.nci.nih.gov/cellminer). Among new insights, transcript versus DNA methylation correlations revealed the epithelial/mesenchymal gene functional category as being influenced most heavily by methylation. DNA methylation and copy number integration with transcript levels yielded an assessment of their relative influence for 15,798 genes, including tumor suppressor, mitochondrial, and mismatch repair genes. Four forms of molecular data were combined, providing rationale for microsatellite instability for 8 out of the 9 cell lines in which it occurred. Individual cell line analyses showed global methylome patterns with overall methylation levels ranging from 17 to 84%. A six-gene model including PARP1, EP300, KDM5C, SMARCB1 and UHRF1 matched this pattern. Additionally, promoter methylation of two translationally relevant genes Schlafen 11 (SLFN11) and methylguanine methyltransferase (MGMT) served as indicators of therapeutic resistance or susceptibility, respectively. Overall, our database provides a resource of pharmacological data that can reinforce known therapeutic strategies and identify novel drugs and drug targets across multiple cancer types.

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Section: Introductionmentioning

confidence: 99%

The NCI-60 Methylome and Its Integration into CellMiner

et al. 2017

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“…Epigenetically regulated gene expression during spermatogenesis is critical for development of fertility. During the different steps of spermatogenesis, several epigenetic modifications involving DNA methylations and histone modifications occur; reviewed in [41]. While primordial germ cells undergo a process of demethylation and deacetylation, a progressive DNA methylation occurs in spermatogonia with establishment of paternal methylation.…”

Section: Discussionmentioning

confidence: 99%

Genes located in Y-chromosomal regions important for male fertility show altered transcript levels in cryptorchidism and respond to curative hormone treatment

Gegenschatz‐Schmid¹,

Verkauskas

Stadler

et al. 2019

Basic Clin. Androl.

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Background Undescended (cryptorchid) testes in patients with defective mini-puberty and low testosterone levels contain gonocytes that fail to differentiate normally, which impairs the development of Ad spermatogonia and ultimately leads to adult infertility. Treatment with the gonadotropin-releasing hormone agonist GnRHa increases luteinizing hormone and testosterone and rescues fertility in the majority of pathological cryptorchid testes. Several Y-chromosomal genes in the male-specific Y region (MSY) are essential for spermatogenesis, testis development and function, and are associated with azoospermia, infertility and cryptorchidism. In this study, we analyzed the expression of MSY genes in testes with Ad spermatogonia (low infertility risk patients) as compared to testes lacking Ad spermatogonia (high infertility risk) before and after curative GnRHa treatment, and in correlation to their location on the Y-chromosome. Results Twenty genes that are up- or down-regulated in the Ad- group are in the X-degenerate or the ampliconic region, respectively. GnRHa treatment increases mRNA levels of 14 genes in the ampliconic region and decreases mRNA levels of 10 genes in the X-degenerate region. Conclusion Our findings implicate Y-chromosomal genes, including USP9Y, UTY, TXLNGY, RBMY1B, RBMY1E, RBMY1J and TSPY4 , some of which are known to be important for spermatogenesis, in the curative hormonal treatment of cryptorchidism-induced infertility.

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“…Each of these proteins contains 20 random models and 100 lowest scoring models from 10,000 decoys generated using ROSETTA de novo structure prediction followed by all-atom refinement. [39] Improvement of current Rosetta decoys over original decoys is based on addition of side chains to the backbone models and removal of steric clashes. In generating optimal decoy sets following four important points were considered [40] : (1) decoy set should contain conformations for a wide variety of different proteins to overcome the over-fitting problem, (2) native and decoy structures conformation should be less than 4 Å root-mean-squared distance, (3) decoys conformation should be at least close to local minima of energy function, and (4) native structure information should not be used to construct decoys.…”

Section: Decoy Datasetsmentioning

confidence: 99%

sDFIRE: Sequence‐specific statistical energy function for protein structure prediction by decoy selections

et al. 2016

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An important unsolved problem in molecular and structural biology is the protein folding and structure prediction problem. One major bottleneck for solving this is the lack of an accurate energy to discriminate near-native conformations against other possible conformations. Here we have developed sDFIRE energy function, which is an optimized linear combination of DFIRE (the Distance-scaled Finite Ideal gas Reference state based Energy), the orientation dependent (polar-polar and polar-nonpolar) statistical potentials, and the matching scores between predicted and model structural properties including predicted main-chain torsion angles and solvent accessible surface area. The weights for these scoring terms are optimized by three widely used decoy sets consisting of a total of 134 proteins. Independent tests on CASP8 and CASP9 decoy sets indicate that sDFIRE outperforms other state-of-the-art energy functions in selecting near native structures and in the Pearson's correlation coefficient between the energy score and structural accuracy of the model (measured by TM-score).

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Epigenetic Pattern on the Human Y Chromosome Is Evolutionarily Conserved

Cited by 14 publications

References 54 publications

The NCI-60 Methylome and Its Integration into CellMiner

The NCI-60 Methylome and Its Integration into CellMiner

Genes located in Y-chromosomal regions important for male fertility show altered transcript levels in cryptorchidism and respond to curative hormone treatment

sDFIRE: Sequence‐specific statistical energy function for protein structure prediction by decoy selections

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