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Epigenetics in Male Reproduction: A Practical Introduction to the Informatics of Next Generation Sequencing

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Epigenetics and Human Reproduction

Part of the book series: Epigenetics and Human Health ((EHH))

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Abstract

At fertilization, the male germ cell conveys a richly layered genetic landscape consisting of both DNA and its associated epigenetic information. A systems level understanding of these forms of information could reveal some of the origins of idiopathic male infertility. Characterizing the genetic and epigenetic contributions to fertilization could also offer insight into the root causes of aberrant development. Perhaps some of these elements reflect the fetal origins of adult disease. As a host of new tools and techniques emerge, we have the opportunity to reassess our models of gametogenesis in the male. The challenge is no longer to construct biological models from sparse data but to assimilate a wealth of data being generated by high throughput technologies. By aggregating data from multiple high throughput and targeted experiments, bioinformatics offers potential insight into how genetic and epigenetic information are utilized in the sperm-oocyte system. In this chapter, we will review online resources that can aid in conducting an epigenetic investigation as well as describing approaches to managing second and third generation deep sequencing data.

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Abbreviations

CDC:

Centers for Disease Control and Prevention

CpG:

CG dinucleotides (linked by a phosphor diester bond hence CpG)

DGE:

Differential gene expression

DoE:

Department of Energy

gDNA:

Genomic DNA

HAT:

Histone acetyltransferase

HDAC:

Histone deacetylase

HMT:

Histone methyltransferase

ICR:

Imprinting control region

JGI:

Joint genome initiative

miRNA:

Micro RNA

NGS:

Next generation sequencing, also referred to as second generation sequencing or “now generation” sequencing (Illumina)

piRNA:

Piwi-interacting RNA

rasiRNA:

Repeat associated small interacting RNAs

sncRNA:

Small non coding RNA

snoRNA:

Small nucleolar RNA

SNP:

Single nucleotide polymorphism

TByte:

Tera Byte, 1012 bytes, 1,000 gigabytes or 1,000,000 megabytes

WGS:

Whole genome sequencing

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Acknowledgments

This work is supported in part by the NIH grant HD36512, the Presidential Research Enhancement Program in Computational Biology and the Charlotte B. Failing Professorship to SAK. We gratefully acknowledge the use of the UCSC genome browser (http://genome.ucsc.edu/) and the Ensembl genome browser (http://www.ensembl.org) that were used in the creation of some of the illustrations.

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Authors and Affiliations

  1. Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, MI, USA

    Adrian E. Platts, Claudia Lalancette & Stephen A. Krawetz

  2. Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA

    Adrian E. Platts, Claudia Lalancette & Stephen A. Krawetz

  3. Institute for Scientific Computing, Wayne State University, Detroit, MI, USA

    Stephen A. Krawetz

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  1. Adrian E. Platts
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  2. Claudia Lalancette
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  3. Stephen A. Krawetz
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Correspondence to Stephen A. Krawetz .

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Editors and Affiliations

  1. INSERM U309, Labo. Biologie Moléculaire et, Institut Albert Bonniot, La Tronche CX, 38706, France

    Sophie Rousseaux

  2. INSERM U309, Labo. Biologie Moléculaire et, Institut Albert Bonniot, La Tronche CX, 38706, France

    Saadi Khochbin

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Platts, A.E., Lalancette, C., Krawetz, S.A. (2011). Epigenetics in Male Reproduction: A Practical Introduction to the Informatics of Next Generation Sequencing. In: Rousseaux, S., Khochbin, S. (eds) Epigenetics and Human Reproduction. Epigenetics and Human Health. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14773-9_10

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