Next Generation Sequencing and Whole Genome Selection in Aquaculture

237 Pages·2011·16.34 MB·English

by  Zhanjiang (John) Liu

Next Generation Sequencing and Whole
Genome Selection in Aquaculture
Next Generation Sequencing and Whole Genome Selection in Aquaculture Edited by Zhanjiang (John) Liu
© 2011 Blackwell Publishing Ltd. ISBN: 978-0-813-80637-2
Next Generation Sequencing
and Whole Genome Selection
in Aquaculture
Edited by
Zhanjiang (John) Liu
Auburn University
A John Wiley & Sons, Ltd., Publication
Edition fi rst published 2011
© 2011 Blackwell Publishing Ltd.
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Library of Congress Cataloging-in-Publication Data
Next generation sequencing and whole genome selection in aquaculture / [edited by]
Zhanjiang (John) Liu.
p. cm.
Includes bibliographical references and index.
ISBN 978-0-8138-0637-2 (hardcover : alk. paper)
1. Gene mapping. 2. Fishes–Breeding. 3. Shellfi sh–Breeding. I. Liu, Zhanjiang.
QH445.2.N49 2011
639.8–dc22
2010030977
A catalog record for this book is available from the U.S. Library of Congress.
Set in 10 on 12 pt Dutch 801 BT by Toppan Best-set Premedia Limited
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1 2011
Contents
Preface vii
List of Contributors ix
Chapter 1. Genomic Variations and Marker Technologies
for Genome-based Selection 3
Zhanjiang (John) Liu
Chapter 2. Copy Number Variations 21
Jianguo Lu and Zhanjiang (John) Liu
Chapter 3. Next Generation DNA Sequencing Technologies and
Applications 35
Qingshu Meng and Jun Yu
Chapter 4. Library Construction for Next Generation Sequencing 57
Huseyin Kucuktas and Zhanjiang (John) Liu
Chapter 5. SNP Discovery through De Novo Deep Sequencing Using
the Next Generation of DNA Sequencers 69
Geoffrey C. Waldbieser
Chapter 6. SNP Discovery through EST Data Mining 91
Shaolin Wang and Zhanjiang (John) Liu
Chapter 7. SNP Quality Assessment 109
Shaolin Wang, Hong Liu, and Zhanjiang (John) Liu
Chapter 8. SNP Genotyping Platforms 123
Eric Peatman
Chapter 9. SNP Analysis with Duplicated Fish Genomes:
Differentiation of SNPs, Paralogous Sequence Variants,
and Multisite Variants 133
Cecilia Castaño Sánchez, Yniv Palti, and Caird Rexroad
Chapter 10. Genomic Selection for Aquaculture: Principles and Procedures 151
Anna K. Sonesson
Chapter 11. Genomic Selection in Aquaculture: Methods and Practical
Considerations 165
Ashok Ragavendran and William M. Muir
Chapter 12. Comparison of Index Selection, BLUP, MAS, and Whole
Genome Selection 185
Zhenmin Bao
Index 219
Color plates appear between pages 108 and 109.
v
Preface
Over the last 25 years of genomics development, molecular markers have been a
major limiting factor. That was true for human genomics, animal genomics, as well
as for aquaculture genomics. As a result, the goals of genomic research have been a
moving target based on the availability of molecular markers. Scientists celebrated
at each stage of marker development, from the classical restriction fragment length
polymorphism (RFLP), microsatellites, random amplifi ed polymorphic DNA
(RAPD), amplifi ed fragment length polymorphism (AFLP), to the most recent
marker type of single- nucleotide polymorphisms (SNPs). The demands for molecular
markers keep increasing from thousands to tens of thousands, to the current level of
hundreds of thousands or millions of polymorphic markers per species to fully mark
and map the genomes. Such limitations were imposed mostly because of the lack of
the whole genome sequences in many species, especially in aquaculture species.
Finally, in the last few years, this bottleneck is to be released due to advances in next
generation sequencing technologies. Now, with the powerful second generation and
third generation sequencing technologies, many gigabases of nucleotide sequences
can be generated in just a few hours, and thousands of thousands of SNPs, among
other types of polymorphisms, can be discovered.
Since the start of this book project, sequencing technologies have evolved and
matured to such a level that they are now widely used, even with aquaculture species.
Huge numbers of SNPs are being discovered, validated, and applied to aquaculture
genome research. This brings aquaculture genome research to the same level as ter-
restrial livestock genomics where whole genome - based selection can be conducted.
As a result, this book is focused on providing a basic description of next generation
sequencing technologies, genomic copy number variations, SNP discovery, validation,
and applications to whole genome - based selection. It can be said that whole genome
selection is a direct result of genome research, and it perhaps represents the most
powerful genome - based technologies. Since its proposal in 2001 by Meuwissen et al.
( Genetics 157:1819 – 1829 ), whole genome - based selection has become the center and
future direction for animal breeding. It will certainly fi nd its way for application in
aquaculture.
This book has 12 chapters: genome variations and traits; copy number variations;
next generation sequencing technologies; methods and protocols for library construc-
tion for the next generation sequencing; SNP discovery through sequencing reduced
representation libraries; SNP mining from expressed sequence tag (EST) databases;
SNP quality assessment; SNP genotyping platforms; complexities of SNP analysis in
duplicated teleost fi sh genomes; whole genome - based selection: principles and pro-
cedures; whole genome - based selection: methods and practical considerations; and
comparative analysis of conventional index selection, best linear unbiased prediction
(BLUP) selection, marker - assisted selection, and whole genome - based selection.
The last three chapters each address the theory and principles of whole genome -
based selection, but from different perspectives. These chapters were intentionally
included from authors with different experiences. As genome selection is still in its
vii
viii Preface
infancy, its theories are still evolving, and yet the practical effectiveness still needs to
be validated by future experimentation. The inclusion of chapters written by experts
of different perspectives should provide readers some comfort as to where genome
selection is going in aquaculture. Chapter 10 was written by Anna Sonesson, who is
a member of the group that proposed the theory of whole genome selection in
Norway; Chapter 11 was written by Ashok Ragavendran and Bill Muir, the latter of
whom has worked with a whole genome selection project in poultry in the United
States, but with a good knowledge of aquaculture; and Chapter 12 was written by
Zhenmin Bao, who is an expert in aquaculture and aquaculture breeding programs
in China.
This book was written to bridge genome - based technologies with aquaculture
breeding programs. It should be useful to academic professionals, research scientists,
graduate students and college students in agriculture, as well as for students of aqua-
culture and fi sheries. I am grateful to all the contributors of this book. It is their great
experience and efforts that made this book possible. I am grateful to postdoctoral
fellows and graduate students in my laboratory and in the Aquatic Genomics Unit at
Auburn University for their proofreading and technical assistance. I have had a year
of pleasant experience interacting with Susan Engelken, Editorial Program
Coordinator, and with Justin Jeffryes, Commissioning Editor for Plant Science,
Agriculture, and Aquaculture with Wiley - Blackwell of John Wiley & Sons.
During the course of writing and editing this book, I have worked extremely hard
as the Associate Dean for Research while also fulfi lling my duty and passion as a
professor and graduate adviser. As a consequence, I could not possibly work as hard
as I wished to fulfi ll my responsibility as a father of my three lovely daughters: Elise,
Lisa, and Lena Liu. I wish to express my appreciation for their independence and
great progress.
Finally, this book is a product of the encouragement of my lovely wife, Dongya
Gao. As I always say, my mother always expects a lot of me, and my wife always
makes sure that I deliver the high expectations. This book, therefore, is dedicated to
my extremely supportive wife.
Zhanjiang (John) Liu
List of Contributors
Zhenmin Bao Zhanjiang (John) Liu
Key Lab of Marine Genetics and The Fish Molecular Genetics and
Breeding Biotechnology Laboratory
Ministry of Education Department of Fisheries and Allied
College of Marine Life Science Aquacultures and Program of Cell and
Ocean University of China Molecular Biosciences
Qingdao, China Aquatic Genomics Unit
Auburn University
Cecilia Casta ñ o S á nchez Auburn, AL 36849 USA
United States Department of
Agriculture/Agricultural Research Jianguo Lu
Service The Fish Molecular Genetics and
National Center for Cool and Cold Biotechnology Laboratory
Water Aquaculture Department of Fisheries and Allied
Kearneysville, WV 25430 USA Aquacultures and Program of Cell and
Molecular Biosciences
Huseyin Kucuktas Aquatic Genomics Unit
The Fish Molecular Genetics and Auburn University
Biotechnology Laboratory Auburn, AL 36849 USA
Department of Fisheries and Allied
Aquacultures and Program of Cell and Qingshu Meng
Molecular Biosciences CAS Key Laboratory of Genome
Aquatic Genomics Unit Science and Information
Auburn University Beijing Institute of Genomics
Auburn, AL 36849 USA Chinese Academy of Sciences
Beijing 100029, China
Hong Liu
The Fish Molecular Genetics and William M. Muir
Biotechnology Laboratory Pulse Molecular Evolutionary Genetics
Department of Fisheries and Allied Program and Department of Animal
Aquacultures and Program of Cell and Sciences
Molecular Biosciences Room G406 Lilly Hall
Aquatic Genomics Unit 915 West State Street
Auburn University Purdue University
Auburn, AL 36849 USA West Lafayette, IN 47907 USA
ix
x List of Contributors
Yniv Palti Anna K. Sonesson
USDA/ARS Nofi ma Marine AS
National Center for Cool and Cold PO Box 5010, 1432 Å s
Water Aquaculture Norway
Kearneysville, WV 25430 USA
Geoffrey C. Waldbieser
Eric Peatman USDA, Agricultural Research Service
The Fish Molecular Genetics and Catfi sh Genetics Research Unit
Biotechnology Laboratory 141 Experiment Station Road
Department of Fisheries and Allied Stoneville, MS 38776 USA
Aquacultures and Program of Cell and
Molecular Biosciences Shaolin Wang
Aquatic Genomics Unit The Fish Molecular Genetics and
Auburn University Biotechnology Laboratory
Auburn, AL 36849 USA Department of Fisheries and Allied
Aquacultures and Program of Cell and
Ashok Ragavendran Molecular Biosciences
Pulse Molecular Evolutionary Genetics Aquatic Genomics Unit
Program and Department of Animal Auburn University
Sciences Auburn, AL 36849 USA
Room G406 Lilly Hall
915 West State Street Jun Yu
Purdue University CAS Key Laboratory of Genome
West Lafayette, IN 47907 USA Science and Information
Beijing Institute of Genomics
Caird Rexroad III Chinese Academy of Sciences
United States Department of Beijing 100029, China
Agriculture/Agricultural
Research Service
National Center for Cool and Cold
Water Aquaculture
Kearneysville, WV 25430 USA
Genomic DNA
Evenly spaced features
Array with features designed
from genome sequences
R
Cy3 label e
Df
Ner
Ae
n
c
e

Cy5 label
DT
Ne
As
t

Hybridization
D
C et
y e
3 c
& tio
C n
y o
5 f
r C
a N
t
io V
b
y

Figure 2.1 Principles of array comparative genome hybridization (array CGH). A large
number of evenly spaced features are designed from the reference genome sequence and
placed to an array. Equal amount of reference genome (normal genome) and test genome
DNA are labeled by differential fl uorescence, for example, Cy3 and Cy5, and hybridized to
the array. The ratios of Cy3 and Cy5 defi ne CNV. If red fl uorescence is observed, the feature
on the array has more copy numbers in the test genome than in the normal genome.
Reference Cancer
DNA DNA
+
Hybridization
Array CGH
Figure 2.2 An example of using array CGH for the detection of chromosomal segment dupli-
cations in cancer.
Next Generation Sequencing and Whole Genome Selection in Aquaculture Edited by Zhanjiang (John) Liu
© 2011 Blackwell Publishing Ltd. ISBN: 978-0-813-80637-2
Biotinylated
Hairpin adaptor
Ligation
Sheared Circularized
Genome DNA DNA fragments
Bio
Randomly
sheared
>TPGaTirG 1A,T ECnAdC ACCGCCAATATCTC454 sequencing Isolation
AGATGACACAATGGACCAAAGT
TTACGAGCGGCTGACATAGGCT Linker (+) library DNA fragments
>Pair1, End B
TGTGATCACCCGCCAATATCTC Paired ends
AGATGACACAATGGACCAAAGT
Data
analysis 0
0
0
Paired ends span 4
SVs mapping
nt0
u0
o0
C2
0
0 2000 4000 6000 8000
Span of paired ends
Figure 2.3 Principles of paired-end mapping-based CNV detection. Genomic DNA is sheared
into approximately 3-kb fragments. The genomic fragments are then ligated to biotinylated
adaptors to mark the orientation. The segments are circularized, followed by linearization at
random sites. Next generation sequencing is used to massively sequence the segments.
Bioinformatic mapping by in silico positioning of the sequences to the reference genome would
detect any size difference or orientation difference, which suggest genome structural variations
including CNVs.