genomic prediction of additive and non-additive effects in a pine breeding and simulated population

123 Pages·2016·2.02 MB·English

JANEO EUSTÁQUIO DE ALMEIDA FILHO

GENOMIC PREDICTION OF ADDITIVE AND NON-ADDITIVE EFFECTS IN A PINE
BREEDING AND SIMULATED POPULATION

Thesis presented to the Universidade
Federal de Viçosa as part of the
requirements of Genetics and Breeding
Graduate Program for the achievement of
the title of Doctor Scientiae.

VIÇOSA
MINAS GERAIS-BRASIL
2016

JANEO EUSTÁQUIO DE ALMEIDA FILHO

GENOMIC PREDICTION OF ADDITIVE AND NON-ADDITIVE EFFECTS IN A PINE
BREEDING AND SIMULATED POPULATION

Thesis presented to the Universidade
Federal de Viçosa as part of the
requirements of Genetics and Breeding
Graduate Program for the achievement of
the title of Doctor Scientiae.

APPROVED: 17th February, 2016.

_______________________________ _______________________________
Camila Ferreira Azevedo Cosme Damião Cruz

_______________________________ _______________________________
Matias Kirst Messias Gonzaga Pereira
(Co-adviser)

_________________________________
Fabyano Fonseca e Silva
(Adviser)
“We are heirs of our own acts”
André Luiz

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To God, source of love.
To my lovely Solange for her adorable company.
To my father Janeo (In Memoriam).
To my mother Narah, for her love.
To my brother, my great friend.
To my grandmother Ireny for her unconditional love.
To my grandparents.
To everybody who dream with something better.

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ACKNOWLEDGEMENTS
First, I would like to thank God and Jesus for my life and for giving me strength and
inspiration during my life, and for being my safe harbor and comfort in times of hardship.
I would like to thank my advisor Dr. Fabyano Fonseca e Silva for his friendship,
guidance and concern about my success as a student.
I would like to thank my co-advisor Dr. Marcos Deon Vilela de Resende for all
lessons and time spent in teaching me. I appreciate him for his dedication in giving me
new knowledge and for being interested in propagating his knowledge.
I am very thankful to my co-advisor Dr. Matias Kirst for receiving me at the Forest
Genomics Laboratory in University of Florida, also because he had been attentive with my
progress and committed to the success of our research.
I would like to thank Dr. Márcio Resende Jr for his friendship, competent scientific
help and all the support during my time at University of Florida.
I would like to thank Dr. Patricio Munoz for his valuable support, interest in our
research and his excellent background on genomic selection in breeding.
I would like to thank Dr. Leonardo Lopes Bhering for his friendship and for receiving
me at the Laboratory of Biometrics in the Federal University of Viçosa.
I would like to thank Dr. Cosme Damião Cruz for being an example of professor
and always be available for the students.
I wish to thank Dr. Cosme D. Cruz, Dr. Camila F. Azevedo, Dr. Matias Kirst and Dr.
Messias G. Pereira for their contribution and time in my thesis defense.
I would like to thank the Federal University of Viçosa and my graduate program
Genética e Melhoramento for the opportunity to have a great education; I also wish to
thank the University of Florida for the great structure and the opportunity to improve my
research.
I am very thankful to Solange, for her lovely company, care, and valuable
fellowship.
I am very thankful to my grandmother Ireny, because she always took care of me,
and for her love in my personal formation.
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I am very thankful to my mother Narah, for her love and concern about my personal
formation.
I am very thankful to my brother Gabriel and my grandparents Ruth, Juarez (In
Memoriam) and Pedro for all their support throughout my life; I would also like to thank
my father (In Memoriam) and my whole family.
I want to thank my friends at the Laboratory of Biometrics: Leonardo Azevedo,
Leonardo Correa, Lidiane, Andrei, Lizandra, Rafael, Humberto, Nadson, Bruno
Ermelindo, Vinicius, Edson, Michele, Juan, Matoso, Afonso, Ândrea, and Ana Maria for
the enjoyable company.
I want to thank my friends at UFV Caillet, Thais, Angélia, also I would like to thank
the all friends that I met in Viçosa.
I wish to thank the people from Forest Genomics Laboratory mainly: Rodrigo,
Justyna, Cintia, Flora, Annette and Chris Dervinis, for the nice time in the lab.
I would like to give a special thank for João Filipi for his help during my time at UFV
and UF. Also, I wish to thank João, Luciano and Hélcio for receiving me in their home for
a while.
I am very thankful to the secretaries of the graduate program Geńtica e
Melhoramento at UFV, Edna, Rita, Odilon and Marco Túlio, for the competent support.
I am very thankful to Kelly and Márcio for assisting my personal needs in
Gainesville. Also, I wish to thank Márcio, Kelly, Barbara, Leandro, Rodrigo, Ediene, João,
Higino for the enjoyable moments in Gainesville.
I thank Dr. Rosana Vianello for her support at Embrapa Arroz e Feijão, I would also
like to thank the colleagues from the Laboratory of Biotechnology at Embrapa Arroz e
Feijão: Paula, Gabriel, Stella, Wendell, João, Lorraine... for their pleasant company.
I wish to thank Giselle Davi for her friendship and her valuable help.
I wish to thank Jeff's family for having received me at their home in Gainesville, and
for the nice moments that I had there.
I would like to thank Ana Amélia e Josi all the support in Gainesville.
I am very thankful for GenMelhor, and the friends that I made there, for trying to
improve our education quality at UFV.
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I would like to thank Father Bill and his wife Kathy and everybody from covenant
church of Gainesville, for the agreeable moments and attention with me.
I wish to thank the people from the English school in the Baptist Church for the
lessons.
I want to thank my friends from Camilo Chaves: Geraldo, Aparecida, Angelina,
Alexandre, Denizar, Maurício, Eduardo, João Bosco, Nalusa (In Memoriam), Suelly for
making my Saturdays in Viçosa special.
Everybody who has motivated me and directly or indirectly contributed to this work,
my sincere thanks.
Finally, I wish to thank every Brazilian who has worked hard and contributed with
my education through their taxes.

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CONTENTS
RESUMO ........................................................................................................................ xi
ABSTRACT ................................................................................................................... xiii
GENERAL INTRODUCTION ........................................................................................... 1
CHAPTER I ..................................................................................................................... 4
LITERATURE REVIEW ................................................................................................... 4
GENOMIC SELECTION ............................................................................................ 4
PREDICTION WITH MARKERS AND PEDIGREE .................................................... 7
POLYGENIC AND OLIGOGENIC TRAITS ................................................................ 9
NON-ADDITIVE EFFECTS ..................................................................................... 11
ACCURACY ............................................................................................................ 14
PERSPECTIVE OF PREDICTIONS IN BREEDING: LARGE DATA SET IS COMING
................................................................................................................................... 15
GENOMIC PREDICTION IN PINE BREEDING ....................................................... 17
STATISTIC MODELS FOR GENOMIC SELECTION .............................................. 21
WHOLE-GENOME REGRESSIONS ....................................................................... 22
ESTIMATION OF A AND D AND EPISTASIS ......................................................... 22
BREEDING AND DOMINANCE DEVIATION VALUES AND CROSS PREDICTION
................................................................................................................................... 22
DISTRIBUTIONS ASSUMED FOR REGRESSION COEFFICIENTS ...................... 23
Bayesian Ridge Regression (BRR) ...................................................................... 23
Bayes A ................................................................................................................ 24
BayesB ................................................................................................................. 25
BayesCπ .............................................................................................................. 27
Bayesian Lasso (BL) ............................................................................................ 28
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WGR variance components ................................................................................. 30
Individual models ................................................................................................. 30
Choice of hyper-parameters ................................................................................. 33
CHAPTER II .................................................................................................................. 35
THE CONTRIBUTION OF DOMINANCE TO PHENOTYPE PREDICTION IN A PINE
BREEDING AND SIMULATED POPULATION .............................................................. 35
ABSTRACT ............................................................................................................. 35
INTRODUCTION ..................................................................................................... 36
MATERIALS AND METHODS ................................................................................. 38
Loblolly pine population data ................................................................................ 38
Simulated Data ..................................................................................................... 38
Statistical methods ............................................................................................... 41
Breeding value and dominance deviation ............................................................. 44
Variance components and heritability estimation ................................................. 44
Validation ............................................................................................................. 44
RESULTS ................................................................................................................ 45
Heritability ............................................................................................................ 45
Additive and additive-dominance model prediction in the CCLONES population . 45
Genetic properties of the simulated population .................................................... 46
Genetic properties of the simulated population .................................................... 47
Dominance reduces the overall accuracy of prediction models ............................ 48
Models that incorporate dominance are only more accurate when d2 is high ....... 48
Accuracy of predicting additive and dominance effects, and phenotypes ............ 49
Additive-dominance models improve accuracy of progeny selection only for
oligogenic traits with high dominance...................................................................... 52
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