UNIVERSITY OF CALGARY

A Comparison of Low - Versus High - Fertility Holstein Bulls

For Identification of Fertility Markers

by

Habib Allah Shojaei Saadi

A THESIS

SUBMITTED TO THE FACULTY OF GRADUATE STUDIES

IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE

DEGREE OF MASTER OF MEDICAL SCIENCE

DEPARTMENT OF MEDICAL SCIENCES

CALGARY, ALBERTA

DECEMBER, 2011

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FACULTY OF GRADUATE STUDIES

The undersigned certify that they have read, and recommend to the Faculty of Graduate

Studies for acceptance, a thesis entitled "A comparison of low- versus high-fertility

Holstein bulls for identification of fertility markers" submitted by Habib Allah Shojaei

Saadi in partial fulfilment of the requirements of the degree of Master of Medical

Sciences.

Supervisor, Dr. Jacob C Thundathil. Department of Medical Sciences

Dr. Frans van der Hoorn. Department of Biochemistry and Molecular Biology

Dr. John Kastelic. Department of Medical Sciences

Dr. Leluo Guan. Department of Medical Science

Dr. Robert McCorkell. Faculty of Veterinary Medicine

Date

ii Abstract

The objectives were to compare low versus high-fertile bulls for testicular physical characteristics, sperm characteristics, expression patterns of testicular genes, and sperm protein profiles for identification of fertility markers in Holstein bulls used for artificial insemination (AI). Ten Holstein bulls (4-5 y old) were classified as either low- fertility (LF) or high-fertility (HF; n=5 each), based on adjusted 56-d non-return rates

(NRR; range 48.0 to 74.0%). Testicular physical characteristics were not significantly different between the two groups. Several indices of sperm motion (based on computer- assisted sperm analysis) at post-thaw and post-swim up were correlated with NRR.

Thirty-one protein spots differed between total protein extracted from LF and HF sperm.

However, ASB5 was the only common gene differentially expressed between LF and HF bulls (P < 0.05). In conclusion, fertility of mature Holstein bulls maintained in a commercial AI center was not predicted by testicular physical characteristics, but evaluation of sperm characteristics and genomic and proteomic approaches have considerable promise to predict fertility potential in Holstein bulls.

iii Acknowledgements

Foremost, I would like to express my sincere gratitude to my supervisor Dr. Jacob

Thundathil for his patience, motivation, enthusiasm, and assistance. His guidance helped me throughout the research and writing of this thesis.

This is a great opportunity to appreciate Dr. Frans van der Hoorn for his support, encouragement and valuable advice in scientific discussions. I gratefully thank Dr. John

Kastelic for all of his constructive criticism during the period of this study and time commitment for critically reading this thesis and my manuscripts. My sincere thanks to

Dr. Leluo Guan for sharing her expertise on microarray analysis and providing me a great opportunity to work in her laboratory at the University of Alberta.

I take the opportunity to acknowledge Natural Sciences and Engineering Research

Council of Canada (NSERC), Agriculture and Food Council, Alberta Livestock Industry

Development Fund, Semex Alliance, L'Alliance Boviteq (LAB) inc. and Westgen and

University of Calgary for financial assistance and support for this study. I also thank the

University of Calgary, faculty of Veterinary Medicine for the UCVM graduate student entrance award and Faculty of Medicine, Department of Medical Sciences, for travel awards.

Special thanks and gratitude to Dr. Esmail Behboodi for his advice, comments, insight and inspiration throughout my work and life.

I also acknowledge Mr. Doug Nickel for his help and technical support. Thanks to the past and present members of Thundathil lab, who provided a very friendly lab environment and during the period of this project: Drs. Ajitkumar Menon, Sulochana

Krishna Kumar, Gayatheri Rajamanickam and Ms. Alysha Dance

iv Many thanks to Dr. Amin Rezvanfar, Dr. Sadegh Karimi, Dr. Adel Pezeshki, Dr.

Sepideh Abbasi & Dr. Mustafa Gozlan, Yasha and Majid for their moral support.

Last but not the least, I thank Mahboubeh, Mona & Hamed being supportive and caring siblings.

v Dedication

This thesis is dedicated to my parents who have supported me all the way since the

beginning of my studies and offered me unconditional love and support.

Also, this thesis is dedicated to my wife who has been a great source of motivation

and inspiration.

vi Table of Contents

Approval Page ii Abstract iii Acknowledgements i v Dedication vi Table of Contents vii List of Tables ix List of Figures and Dlustrations x

CHAPTER ONE: INTRODUCTION 1 1.1 Background 1 1.2 Relevant literature review 1 1.2.1 Testicular physical characteristics 1 1.2.2 Sperm motion characteristics 4 1.2.3 Sperm plasma membrane integrity 8 1.2.4 Sperm selection through sodium hyaluronate swim-up medium 10 1.2.5 Transcriptomics 11 1.2.6 Proteomics 13 1.3 Objectives and hypothesis 18

CHAPTER TWO: MATERIALS AND METHODS 19 2.1 Testicular physical characteristics 19 2.1.1 Selection of bulls 19 2.1.2 Evaluation of testicular physical characteristics 20 2.2 Evaluation of sperm characteristics 21 2.2.1 Evaluation of sperm motion characteristics 21 2.2.2 Evaluation of sperm plasma membrane viability 22 2.2.3 Evaluation of sperm characteristics after swim-up 23 2.2.3.1 Swim-up procedure 23 2.2.3.2 Sperm motion characteristics 24 2.2.3.3 Determination of sperm concentration 24 2.2.3.4 Evaluation of sperm viability 25 2.3 Transcriptome analysis 25 2.3.1 Microarray hybridization and data analysis 25 2.3.1.1 Preparation of slides 27 2.3.1.2 Reverse transcription 27 2.3.2 Bioinformatics 29 2.3.3 Q-PCR analysis 30 2.3.4 Evaluation of the ASB5 protein expression in testis 31 2.4 Proteomics 32 2.4.1 Semen samples 32 2.4.2 Two-dimensional gel electrophoresis 32 2.4.2.1 Extraction and quantification of total proteins 32 2.4.2.2 Rehydration of IPG strips 33 2.4.2.3 Isoelectric focusing 33 2.4.2.4 Second dimension 34

vii 2.4.2.5 Staining, imaging and gel analysis 34 2.4.2.6 Determination of the pi and molecular mass of DE proteins 36 2.5 Statistical analyses 36

CHAPTER THREE: RESULTS 38 3.1.1 Testicular physical characteristics 38 3.1.2 Testicular echotexture 38 3.1.3 Scrotal thermography 38 3.2 Sperm characteristics 39 3.2.1 Sperm motion characteristics 39 3.2.2 Sperm plasma membrane viability 39 3.2.3 Sperm concentration 40 3.3 Transcriptome analysis using microarray 48 3.3.1 Bioinformatics: 56 3.3.2 ASB5 protein expression in testes: 67 3.4 Proteomics 68 3.4.1 Sperm protein profile 68

CHAPTER FOUR: DISCUSSION 73

REFERENCES 87

viii List of Tables

Table 1. Fertility data for low- versus high-fertility Holstein bulls used in the present study 20

Table 2. Motion characteristics (mean ± SD) of frozen-thawed sperm from high- versus low-fertility Holstein bulls 41

Table 3. Mean (± SD) sperm motion characteristics after swim-up in high- versus low-fertility Holstein bulls 42

Table 4. Correlation coefficients between sperm motility end points and non-return rate (NRR) in Holstein bulls 43

Table 5. Viability of frozen-thawed sperm and its correlation with NRR in high- versus low-fertility Holstein bulls 44

Table 6. The number of differentially expressed genes with 2-fold and higher changes between high- and low-fertility bulls 48

Table 7. Two genes differentially expressed (DE) in common between all low- and high-fertility bulls 55

Table 8. Three experiments calculating ACt. for ASB5 for all HF and LF bulls 60

Table 9. Mean (± SD) ACt values for ASB5 in HF and LF bulls based on 3 replicates....61

Table 10. Mean(± SD) fold change for ASB5 gene expression in HF vs. LF bulls 61

Table 11. Differentially expressed sperm proteins between high- versus low-fertility Holstein bulls 70

ix List of Figures and Illustrations

Figure 1. CASA end points and their definitions, (figure from Minitube , Sperm Vision ™, Canada) 6

Figure 2. CASA end points and their definitions (continued figure from Minitube , Sperm Vision ™, Canada) 7

Figure 3. Study design: Dye swap (Cy3 vs Cy5) method for 3 high-fertility versus 3 low-fertility bulls (2 replicates) 26

Figure 4. Schematic representation of sperm motility patterns at post-thaw between low- vs high-fertility Holstein bulls 45

Figure 5. Motion characteristics of frozen-thawed sperm from Holstein bulls, post- thaw and post-swim up 46

Figure 6. Viability of Holstein bull sperm post-thaw 47

Figure 7. Volcano plot which displays fold changes versus respective level of statistical significance of high-fertility bull No. 1 vs all 3 low-fertility bulls 49

Figure 8. Volcano plot which displays fold changes versus respective statistical significance of high-fertility bull No. 2 vs all 3 low-fertility bulls 50

Figure 9. Volcano plot which displays fold changes versus respective level of significance of high-fertility bull No. 3 vs all 3 low-fertility bulls 51

Figure 10. Variation among 3 HF bulls according to gene expression and heat map chart 52

Figure 11. Variation among 3 LF bulls according to the gene expression and heat map chart 53

Figure 12. Heat map showing the cluster obtained from oneway ANOVA 54

Figure 13. Protein sequence of ASB5 56

Figure 14. Bovine EST profile of ASB5 57

Figure 15. Human EST profile of ASB5 57

Figure 16. Murine EST profile of ASB5 58

Figure 17. Fluorescent intensity of SYBR green across cycles representing relative concentration of ASB5 transcripts from low- versus high-fertility (LF and HF, respectively) bulls 62

Figure 18. Melting curves of ASB5 for both low- and high-fertility (LF and HF,

x respectively) bulls 63

Figure 19. Target titration for ASB5 to validate the ACt difference per cycle 64

Figure 20. Expression of ADK1 in LF and HF bulls 65

Figure 21. Mean transcript abundance (ACt) of ADK1 between low- versus high- fertility bulls 66

Figure 22. Immunoblotting of ASB5 antibody against total testicular protein from both LF and HF bulls, with expression of ASB5 proteins 67

Figure 23. Differentially expressed spots (light and dark double lines) on a 2D gel with its pi and MW 69

Figure 24. The standard protein gel image used for calibrating 2-D gels from high- and low-fertility bulls 71

Figure 25. Calibrated (with a standard protein gel) fused image of all samples with differentially expressed spots 72

xi List of Symbols, Abbreviations and Nomenclature

Symbol Definition

ADK1 adenylate kinase-1 AI artificial insemination AK1 adenylate kinase isoenzyme 1 ALH amplitude of lateral head displacement AM acetylated membrane ANK ankyrin repeats ASB ankyrin repeat-containing proteins with a socs box BBSE bull breeding soundness evaluation BCF beat cross frequency CAGE cap-analysis gene expression CASA computer assisted sperm analysis DE differentially expressed EGF epidermal growth factor ESI-MS electrospray ionization mass spectrometry EST expressed sequence tag PLC flow cytometry GPI glycosyl phosphatidyl inositol HA hyaluronic acid HF high-fertility DBF isoelectric focusing IVF in vitro fertilization KEGG Kyoto encyclopaedia of genes and genome LC-ESI-MS-MS liquid chromatography electrospray ionisation tandem mass spectrometry LF low-fertility LIN linearity MALDI-MS mass spectrometry matrix-assisted laser desorption/ionization MMPs matrix metalloproteinases MW molecular weight NRR non return rate PEBP1 phosphatidylethanolamine-binding protein 1 PGK1 phosphoglycerate kinase 1 PI propidium iodide Pi isoelectric point RCDC reducing agent and detergent compatible SAGE serial analysis of gene expression SC scrotal circumference SST scrotal surface temperature STR straightness TIMP2 tissue inhibitor of metalloproteinase-2

xii TVC testicular vascular cone VCL curvilinear velocity VSL straight-line velocity VAP average path velocity WOB wobble coefficient

xiii 1

Chapter One: INTRODUCTION

1.1 Background

Bulls maintained in commercial AI centers are selected, based on genetic merit, through progeny testing. This process takes at least 4 y and is extremely expensive.

Furthermore, due to the emphasis on genetic selection for production merit, a selected sire may have suboptimal fertility and semen production, thereby substantially limiting his value. There are several reports that elite bulls (with satisfactory semen characteristics) maintained in commercial AI centers differ in field fertility (NRR; Non-

Return Rate)1'2. Since semen from elite bulls is often used for breeding hundreds (or thousands) of females, accurately identifying bulls that produce large numbers of fertile cryopreserved sperm is critically important3.

Traditionally, bull fertility was predicted based on bull breeding soundness evaluation (BBSE), which includes assessments of physical soundness and semen quality.

Although this approach will likely identify bulls that are grossly abnormal, it will not predict variations in fertility of bulls that are producing apparently normal semen4.

Therefore, further research is warranted to identify the underlying causes of these variations in fertility.

1.2 Relevant literature review

1.2.1 Testicular physical characteristics

Several non-invasive methods for examining bulls have been used to predict semen production potential and fertility, including scrotal circumference (SC), testicular dimensions, scrotal neck length and circumference, and scrotal morphology5"11. These 2 physical traits identified bulls with profound abnormalities and substantially reduced reproductive potential, but their usefulness in predicting fertility of dairy bulls with apparently normal semen remains unknown.

Testicular mass, which is related to sperm production potential, can be estimated indirectly by scrotal circumference (SC), or directly by measuring testicular length, width, and depth12. Under field conditions, a bull's semen production potential is commonly estimated by measuring SC12. Furthermore, SC is also related to percentages of motile and morphologically normal sperm13'14; there was a positive linear regression with sperm motility and epididymal sperm reserves, and a negative linear regression with primary sperm defects7. In addition, SC is positively correlated with conception/pregnancy rates15. However, the relationship between scrotal circumference and fertility in bulls producing satisfactory semen sample remains unknown.

Among techniques to evaluate testicular physical characteristics ultrasonography is a non-invasive means of assessing testicular structure and function16, and may be useful for predicting reproductive potential9'11'17. Furthermore, a scrotal infrared thermogram provided detailed information regarding a bull's ability to maintain testicular temperature cooler than core body temperature8, which is critical for normal spermatogenesis. Scrotal surface temperature (SST) of the entire scrotum (at the top and bottom of the testes), the SST gradient (difference between SST at the top and bottom of testes), and left to right symmetry have been used to evaluate the ability of bulls to

o regulate testicular temperature .

Scrotal morphology has also been used as an indirect evaluation of the ability of bulls to regulate testicular temperature5. Scrotal morphology is subjectively assessed on a 3 scale of 1-5 (1: extremely short scrotum without a distinct scrotal neck; 5: extremely long scrotal neck with scrotum below hocks)17.

Characteristics of the scrotum, testes and testicular vascular cone (TVC) were associated with sperm production17; increased sperm production was associated with increased testicular volume, SC, and the top to bottom SST gradient. A more pendulous scrotum provides increased surface area for exposure of the TVC region, facilitating heat loss. In that regard, scrotal shape had a positive regression with the testicular subtunic temperature gradient in Bos taurus beef bulls9. However, the association of this testicular physical characteristic to fertility in Holstein bulls producing apparently normal semen remains unknown. There were positive correlations between SST and deep testicular temperature, indicating that scrotal thermography could be used to assess deep testicular temperature7.

In addition, ultrasonographic evaluations of the diameter of the TVC and thickness of the fat covering the TVC were indicative of the ability of scrotum and testes to regulate testicular temperature, and were associated with semen production and semen 1 ft quality . Subtle changes in the scrotum and testes (detectable by scrotal thermography and testicular ultrasonography) may result in production of sperm that are apparently normal in morphology, yet have impaired fertility, due to altered structure and function at the submicroscopic level, leading to variations in fertility among AI sires. Consistent with this hypothesis, beef bulls with an abnormal SST pattern6 (based on infrared thermography), but with satisfactory semen quality, achieved lower pregnancy rates to natural mating than those with a normal or questionable SST pattern. However, the relationship between SST and fertility in dairy bulls remains unknown. 4

1.2.2 Sperm motion characteristics

Sperm motion characteristics are associated with fertilizing ability19. Subjective "\r\ evaluation of sperm motility is inaccurate ; its reliability is highly dependent on the skills of the investigator21. For example, coefficients of variation between technicians and laboratories were 20% and up to 37%, respectively22'23, providing clear justification for the need to standardize semen analysis22,24. Although visual assessment of sperm motility is very subjective25, Computer Assisted Sperm Analysis (CASA) objectively assesses sperm motion characteristics with high accuracy and reproducibility26,27. However, due to recent conflicting evidence that the CASA parameter taken as the best index vary between studies28,29 .The reason for this controversy is that many of the sperm motility measurements derived from CASA analysis are significantly correlated with each other and subsequently there are significant variations in measurement techniques among studies. Therefore, due to this fact it is not surprising to state that, the association between

CASA end points and bull fertility is not definitive.

The CASA system is a very useful and objective method of assessing sperm motion characteristics , including: curvilinear distance (DCL, jo.m), the distance of sperm head along its actual trajectory; the average path distance (DAP, jxm): the average path of the sperm head trajectory; straightline distance (DSL, ^m): the straight line distance from its first to its last position of sperm head; curvilinear velocity (VCL, jim/s): time average velocity of the sperm head along its actual path; average path velocity (VAP, nm/s), the average velocity of the sperm head along its average trajectory; straight-line velocity

(VSL, nm/s), time average velocity of the sperm head along a straight line from its first position to its last position; linearity (LIN,%), the ratio between VSL and VCL; 5 straightness (STR, %), the ratio between VSL and VAP; wobble coefficient (WOB, %), the ratio between VAP and VCL; mean amplitude of lateral head displacement (ALH, jim), the average value of the variation of the actual sperm head trajectory about its average trajectory; and beat cross frequency (BCF, Hz), the frequency at which the actual sperm trajectory crossed the average path trajectory; and hyperactivated motility by defining the cut-off values (ALH >7 [Am, LIN <0.65 and VCL >80 urn) for hyperactivated sperm, as reported previously31. These sperm kinematic parameters are illustrated in Figures 1 and 2. 6

Figure 1. CASA end points and their definitions, (figure from Minitube, Sperm Vision ™, Canada)

Actual Path DCL/VCL

Average Path DAP/VAP

DCL - Distance: Curve Line (microns) = sum of the distance point of 1-19 (Green Line). DAP - Distance: Average Path (microns) = average path distance (Red Line). DSL - Distance: Straight Line (microns) = distance from point 1 to point 19 (Black Line). VCL- Velocity: Curve Line: (microns per second) = sum of distance point to point of 1-19 (Green Line) divided by time. VAP - Velocity: Average Path (microns per second) = average path distance (Red Line) divided by time. VSL - Velocity: Straight Line (microns per second) = distance form point 1 to point 19 (Black Line) divided by time 7

Figure 2. CASA end points and their definitions (continued figure from Minitube, Sperm Vision ™, Canada)

DCL/VCL

DAP/VAP 14 12 13

7 ALH 15 11 18 BCF 10 16 X 19 17

1 / ^ 20 DSL/VSL s

LIN: Linearity (VSL/VCL) = linearity of the curvilinear trajectory STR: Straightness (VSL/VAP) = straightness of the average path WOB: Wobble (VAP/VCL) = degree of oscillation of the actual sperm head trajectory about its average path. BCF: brat cross frequency (hertz) = time average rate that actual sperm trajectory crosses The average path trajectory. ALH: amplitude of lateral head displacement (microns) = maximum amplitude of variation Of the actual sperm head trajectory about its average trajectory. AOC: average orientation change (degrees) = degree average of the change in orientation Of sperm head. Although high correlations between several CASA parameters and in vivo fertility *)7 in in various animal species have been recently reported (horses , cattle , swine there is considerable disagreement regarding the relationship between sperm motion characteristics and fertility29'33'34. Reasons for this controversy may be due to various confounding factors such as fresh versus frozen semen32, breed31, or sample size33. The

VCL is indicative of sperm vigor35 and was significantly correlated with NRR30.

Moreover, VCL was the most significant sperm motion characteristic related to IVF success36 .

Furthermore, VCL and VAP were considered as fertility predictors as they were indicative of sperm capacitation status24. Similarly, VAP and VSL were significantly related to in vitro fertility in cattle31'37, whereas Sukcharoen et al., (1995)38 and Jeulin et al. (1996) reported positive correlations between ALH and in vivo fertility. Regardless, further studies are required to determine the reliability of these parameters in predicting bull fertility29.

1.2.3 Sperm plasma membrane integrity

Various staining protocols have been developed to detect membrane integrity of mammalian sperm. Plasma membrane integrity is usually assessed after staining cells with membrane-impermeable dyes or alternatively with acetylated membrane (AM) permeable probes that are selectively de-esterified within the cell, become membrane impermeable, and are thus entrapped in viable cells40. Several staining methods have been used historically (e.g. eosin-nigrosin), as well as the fluorescent probes carboxyfluorescein diacetate, propidium iodide (PI), SYBR14, and Hoechst 33258. Some 9 of these methods may be unreliable; in some species, sperm are partially stained (eosin- nigrosin), or they may overestimate the number of non-viable sperm (fluorescent probes)41 .

Analysis of sperm viability using flow cytomery provides numerous advantages compared to traditional microscopy-based evaluation of sperm viability, including analysis of large numbers of sperm in a short interval, thereby eliminating subjectivity and improving reproducibility42. Garner et al., 199443 reported that the combination of

SYBR-14 and PI was effective for assessing the viability of fresh or cryopreserved sperm; furthermore, proportions of living and dead sperm could be readily quantified using flow cytometry (FLC)43. Evaluating the sperm plasmalemma integrity using

SYBR14/PI yielded three stained sperm populations: green (viable), red (dead), and dual stained (moribund)42"44. Moribund sperm are formed as a relatively rapid transition between living and dead sperm. It has been suggested that higher quality semen samples may be identified based on the rapidity of changes between viable and moribund sperm43.

Staining the semen sample with SYBR14/PI and analyzing with FLC can accurately and rapidly detect these three populations. In several studies, viability as well as motility of bull sperm were correlated with non-return rate (NRR)20. Moribund sperm were characterized by a compromised sperm membrane; they undergo a transition from a living to a moribund state, and ultimately die. Although it was suggested that the rate of transition of live sperm to a moribund state may predict semen quality43'45, critical evaluation of the association of this end point with field fertility has not been reported.

Apparently, the importance of moribund cells and the transition rate from viable sperm to dead sperm have not been investigated. 10

1.2.4 Sperm selection through sodium hyaluronate swim-up medium.

A swim-up method has been used46 to separate highly motile sperm from dead and nonviable sperm, which mimicked sperm selection during sperm transport through the female genital tract47,48. This procedure selected sperm with better quality chromatin and fewer morphological defects49, which resulted in higher cleavage rate when used for

IVF50. Interestingly, for human semen, the swim-up procedure selects a sperm population with longer average telomere size and lower frequency of sperm cells with fragmented

DNA51.

Various swim-up procedures have been used to select motile sperm from post- thaw semen52. Hallap et al. (2005)52 reported that characteristics of bull sperm selected through a conventional swim-up procedure had a significant relationship with fertility.

However, the association between post swim-up sperm characteristics using Na hyaluronate and fertility (classified according to the criteria of North American AI centers) remains unknown.

It is well established that the female genital tract is strongly selective against morphologically abnormal sperm, and furthermore, that only limited numbers of sperm reach the site of fertilization . Cervical mucus plays a critical role in selecting motile, morphologically normal sperm with better DNA integrity and adequate telomere size .

Hyaluronic acid (HA), which has a molecular weight, structure, and viscosity similar to the constituent glycoprotein of cervical mucus23, has been incorporated in swim-up preparations, by including a layer of HA between post-thaw semen and post-swim up medium. Incorporation of HA into a swim-up preparation mimics (in vitro) the interaction of sperm with cervical mucus and facilitates selection of motile, viable sperm 11 in post-thaw semen50. Furthermore, evaluating motion characteristics of post-swim up sperm may be more representative of sperm present in the female reproductive tract following insemination. To our knowledge, there has not been any study evaluating the motion characteristics of sperm recovered by this modified swim-up procedure and their correlation with in vivo fertility. Post swim-up sperm motion characteristics, concentration, and viability may provide indirect evidence for their ability to reach the site of fertilization in the female reproductive tract and remain viable50'54"56.

1.2.5 Transcriptomics

Transcriptomics are tools and techniques applied to the global analysis of gene expression. Technologies for genome-wide analysis of gene expression include spotted and oligonucleotide microarrays, developed with sequences a priori, or de novo sequencing-based approaches such as SAGE (serial analysis gene expression) and CAGE

(cap-analysis gene expression)57. Most importantly, these various transcriptomic technologies enable simultaneous assessment of tens of thousands of genes, instead of working on a gene-by-gene basis and also revealing and providing valuable information regarding the gene(s) which might be involved in a particular metabolic path or function.

Recent advances in genomics and the outcome of new technologies for large-scale gene expression analyses have greatly improved our knowledge of male reproduction, making it possible to investigate the molecular mechanisms underlying this process at a genome-wide level57. For example, several studies have used microarray technologies to

so identify genes (in mammalian testes) which are important for spermatogenesis . 12

Isolation of RNA from testicular biopsies is routinely applied in functional genomics of human male infertility59 to evaluate gene(s) related to male fertility. To date, there have apparently been no microarray studies, at a testicular level, to characterize candidate genes related to fertility in bulls with a range in fertility potential. It was recently reported that LF and HF bulls differ in mRNA (transcripts) profile which were already expressed in sperm during spermatogenesis60. Furthermore, it has been suggested that these sperm transcripts have potential roles in fertilization and early embryonic development in mammals61. Perhaps LF and HF bulls have different gene expression patterns at the testicular level. Therefore, using a DNA microarray technique to identify important candidate genes differentially expressed in testes of LF versus HF bulls has potential to identify fertility markers.

The large-scale analysis of gene expression can be done through two distinct strategies. In sequencing-based approaches such as SAGE and CAGE, small DNA fragments (10-14 bp) are generated from cDNAs and subcloned in a DNA library; thereafter, the abundance of each tag is correlated to the level of expression of the corresponding gene. The high-throughput sequencing of libraries corresponding to various samples gives access to quantitative data on gene expression. Conversely, oligonucleotide microarrays are based on the ability of complementary DNA or RNA fragments to hybridize together58. Two classes of arrays are frequently used: in spotted

DNA microarrays, microdroplets of long complementary DNA fragments are spotted on a chip. The cDNAs prepared from two samples are labeled with fluorescent dyes and hybridized simultaneously on the chip. The ratio of the two fluorescence signals emitted by each spot determines the relative expression of the corresponding gene. With in situ- 13 synthesized microarrays, 2 sets of 11 to 25 bp probes are directly synthesized for each gene on the chip. Biotinylated cRNAs are produced from cDNAs and hybridized individually on the chip, and RNA abundance is determined with a peroxidase assay.

1.2.6 Proteomics

The term proteomics, which reflects both 'protein' and 'genome', was coined by

Marc Wilkins in 1994. Whereas the genetic background of individual cells of an organism remains the same, transcripts and expression of proteins vary from cell to cell, according to time, environmental stimuli, and/or stress57. Proteomics includes the study of temporal dynamics of proteins expressed in a specific biological compartment at a specific time, including structural alterations and post-translational modifications62.

Since protein diversity cannot be fully characterized by gene expression analyses alone, a comprehensive proteomic analysis, coupled with gene expression analysis, may provide a better understanding of the biological process under investigation.

Several strategies have been reported for proteomic analysis. The first strategy dealing with the high-throughput analysis of proteins aims to systematically identify the protein content of a biological sample. Classically, proteins extracted from a whole organ or isolated cells are separated by 2-dimensional-gel electrophoresis. Each detectable spot is then excised from the gel and subjected to trypsin digestion. The resulting peptides are listed by MALDI-MS (mass spectrometry matrix-assisted laser desorption/ionization) mass spectrometry and the corresponding proteins are identified. 14

Recently, progress made with highly sensitive mass spectrometry enabled scientists to avoid the complex two-dimensional separation process. A trypsin-digested protein sample is separated by liquid chromatography and directly injected in an ESI-MS

(electrospray ionization mass spectrometry), where the peptides are identified by tandem mass spectrometry (MS/MS). An intermediate way is to pre-fractionate the samples through 1-dimensional-gel electrophoresis. Bands containing hundreds of proteins are then sliced off the gel and trypsin-treated before they are identified by LC-ESI-MS/MS sequencing. Quantification can also be considered with proteomics, either by electrophoresis-based or MS-based methods.

Sperm functions such as motility, capacitation, acrosome reaction, zona binding are regulated by sperm proteins already present in sperm without additional protein synthesis by activation, modification, or subcellular relocalization of proteins57. Sperm maturation in epididymis consists of sequential modifications, of the sperm surface during which immature sperm progressively lose or modify most of their testicular surface proteins and gain new transient or permanent proteins in well- organized membrane protein domains . Several studies have been done at the level of global proteomic analysis of sperm from several species, including mice64, rats65, cattle66, and fruit flies67, which provided valuable information regarding sperm function and its conservation across species.

Since sperm functions are regulated by proteins already present in sperm without additional protein synthesis, content and activity of specific sperm proteins present in sperm influence sperm function and may serve as markers for fertility. A preliminary study detected differential expression of proteins in bulls with varying fertility66. These 15 proteins include those involved in energy production (pyruvate kinase; PKM2) and oxidative respiration (Cyclooxygenase 3 and ATP5B, gene encoding a subunit of mitochondrial ATP synthase protein), sperm capacitation and actin polymerization, essential for incorporation of sperm into egg cytoplasm and for sperm nuclei decondensation (Epidermal Growth Factor; EGF signaling), acrosome reaction, fertilization and embryo development (phospholipase-C; PLC), and sperm chromatin decondensation after sperm-oocyte fusion (casein kinase 2; CKII).

Two-dimensional gel electrophoresis has been used to study sperm proteome in males of several species, including humans68, cattle60, swine69, and sheep70. Studies aimed at identifying causes of infertility in humans71 or putative molecular markers associated with high fertility phenotype in bulls72 have yielded considerable data on functionally important sperm proteins. Compared to sperm from low-fertility bulls, sperm from high- fertility bulls have a higher content of proteins involved in energy metabolism, cell communication, spermatogenesis, and motility66. This study employed differential detergent fractionation multidimensional protein identification technology (DDF-Mud

PIT) which identified 125 putative biomarkers of fertility. In fact, DDF-Mud PIT technology is much more accurate than 2D gel electrophoresis and can provide more candidate proteins compared to 2D gel electrophoresis techniques.

Furthermore, sperm proteins from low- versus high-fertility Nellore (Bos indicus) bulls producing acceptable semen samples had differential expression of sperm membrane proteins based on 2-dimensional gel electrophoresis73. In addition , it was recently reported (in Holstein bulls) that the expression patterns of the alpha 4 subunit of

Na+/K+ATPase (ATP1A4), tissue inhibitor of metalloproteinase-2 (TIMP-2), testicular 16 isoform of angiotensin converting enzyme (tACE), and hexokinase-1 differed between morphologically normal and abnormal sperm obtained from the same bull74, suggesting differential expression of proteins with altered structure and function of sperm.

Na+/K+ATPase, an integral membrane protein with 2 subunits, a (110 kDa) and the glycosylated P (55 kDa), is active in testes and sperm75. Inhibition of Na+/K+ATPase induced tyrosine phosphorylation and capacitation in bull sperm30. The expression of this protein is modulated in response to increased testicular temperature and is associated with sperm function74.

There are two isozymes for angiotensin converting Enzyme (ACE); somatic ACE

(150-180 kDa) is part of the renin-angiotensin system (regulates blood pressure76), whereas tACE (90-110 kDa) is expressed only in mammalian testes and sperm. The tACE has only the C-terminal domain of somatic ACE, including the hydrophobic membrane anchor and the short cytoplasmic tail, and a specific N-terminal (60 amino acids). The extracellular domain of this protein is cleaved during epididymal maturation of sperm; the released ACE remains physiologically active in the epididymis and seminal plasma21. Based on knockout models, the testicular isozyme of ACE is involved in sperm transport (in the female tract) and sperm-oocyte binding. Furthermore, tACE is involved in cleavage of soluble glycosyl phosphatidyl inositol (GPI)-anchored proteins from sperm

(essential for sperm-oocyte binding)77.

The matrix metalloproteinases (MMPs) are proteolytic enzymes that degrade protein components of the extracellular matrix. The requirement to break physical barriers during fertilization suggested involvement of MMPs, along with their tissue inhibitors (TIMPs: tissue inhibitor of metalloproteinase-2)77; therefore, their content or 17 activity might affect fertility. Consistent with this hypothesis, a 24-kDa heparin binding protein (TIMP-2) in bovine seminal fluid was postulated to have a role in bull fertility2.

Although the candidate proteins described above were differentially expressed in bulls following increased testicular temperature, their potential use in predicting fertility in bulls producing apparently normal sperm remains unknown. Since these proteins are differentially expressed in normal versus morphologically abnormal sperm induced by elevated testicular temperature, they may be markers for fertility in bulls. However, fertility of bulls producing apparently normal sperm may be modulated by proteins different from these candidate markers. Therefore, a comprehensive comparison of the presence and content of sperm proteins from LF versus HF bulls using 2-D gel electrophoresis, in conjunction with evaluation of the above-described candidate markers by immunoblotting, may enable characterization of differences between LF and HF bulls in expression of sperm proteins. In addition to identifying specific proteins that are correlated with fertility, this approach should yield a 2-D gel electrophoresis-based proteomic map of LF and HF bulls, which could be included in the bull selection model.

Furthermore, these 2-D gels will also enable us to determine the effect of fertility on post­ radiational modifications, e.g. tyrosine phosphorylation. In that regard, changes in tyrosine phosphoproteins may be associated with fertility, as it is an indication of the inherent tendency of sperm to undergo cryopreservation-associated capacitation60 which reduces fertility of frozen-thawed semen2'78. Perhaps bulls prone to premature capacitation can be identified by screening fresh semen. 18

1.3 Objectives and hypothesis

This project is based on the general hypothesis that LF versus HF bulls differ in testicular physical characteristics, sperm function, expression patterns of testicular genes, and sperm proteins. Specific objectives of this study were to compare LF versus HF bulls for their testicular physical characteristics (testicular width and length, SST, TVC, SC and ultrasonography); sperm motion characteristics using a CASA system; sperm viability evaluation at post-thaw and post-swim up; expression patterns of testicular gene(s) related to fertility; and expression profiles of sperm proteins. On a long-term basis, it is expected that the results from these studies can be applied to predicting fertility of bulls early in life. 19

Chapter Two: MATERIALS AND METHODS

2.1 Testicular physical characteristics

This project was approved by the Animal Care Committee of the University of

Calgary (Project # M09078).

2.1.1 Selection of bulls

Ten Holstein bulls (4-5 y old) maintained under uniform feeding and housing conditions at an AI centre (Gencor, Guelph, ON, Canada), were selected for this study.

All bulls were classified as satisfactory breeders, based on a standard breeding soundness examination4. These bulls were classified as either low- or high-fertility (LF and HF, respectively; 5 bulls per group), based on an adjusted 56-d nonreturn rate (NRR) to an average of 392 first-service inseminations (range in NRR, 48.0 to 74.0%; Table 1) during progeny testing. Environmental factors such as herd, year, month of insemination, age of cow at insemination, technician and genetic group or breed of service as well as semen price were considered as biases which can affect the NRR and were taken into consideration to adjust and calculate the NRR accordingly79. According to industry standards, any bull with a fertility score that deviates from the breed average (67%) by

3% is considered as either low or high fertility (3% below or above breed average, respectively). 20

Table 1. Fertility data for low- versus high-fertility Holstein bulls used in the present study Fertility No. Fertsol® Repeatability NRR" Bull status services 1 439 6.7 65 74 2 474 4.1 67 72 3 High 380 3.9 62 71 4 295 3.8 56 71 5 501 3.6 68 71 6 553 -7.2 70 60 7 213 -7.6 47 60 8 Low 341 -12.3 59 55 9 346 -13.9 59 54 10 387 -19.0 62 49 aFertsol (fertility solution) is a product of the Canadian Dairy Network bull fertility system; it is presented as a percent deviation from breed average (defined as "0"). bNRR = nonreturn rate

2.1.2 Evaluation of testicular physical characteristics

All testicular physical evaluations were done by Dr. Kastelic, Tom Kroetsch and

Dr. Thundathil, and the data analyzed by Randy Wilde.

Scrotal circumference (SC) and scrotal neck circumference were measured with a Coulter

Scrotal Tape (Trueman Mfg, Edmonton, AB, Canada); scrotal neck length and testicular length and width were measured with calipers; and testicular echotexture and testicular vascular cone diameter were assessed with ultrasonography (Aloka 500 with a 7.5 MHz, linear-array transducer; Aloka, Tokyo, Japan). Testicular echotexture measured by an ultrasonography transducer oriented vertically, parallel to the long axis of the testis. An ultrasound image of each testis was recorded and were subsequently digitized and mean 21 and standard deviation (S.D.) of pixel intensity (echotexture) of the testicular parenchyma were determined in an area below the tunica albuginea on a scale of 1 (white) to 255

OA (black) using image analysis software . The vascular cones were examined ultrasonically at the dorsal aspect (top vascular cone to skin distance) and the point where the vascular cone attached to the testicle (bottom vascular cone to skin distance)18. Scrotal thermograms were measured using a thermography camera (Model S60; FLIR Systems

Ltd., Burlington, ON, Canada). The camera was adjusted for ambient temperature, mounted on a tripod, and placed approximately 1 m behind the posterior surface of the scrotum. The scrotal surface temperature (SST) at the top and bottom of the testes and average scrotal surface temperatures overlying each testis were determined. Differences between SST at the top and bottom of the testes (SST gradient, SSTG)28, were determined with image analysis software (ThermaCAM™ Researcher, Version 2.8 SR-2;

FLIR Systems Ltd.).

Scrotal morphology was subjectively assessed on a scale of 1-5 (1: bulls with an extremely short scrotal neck; 5: bulls with an extremely pendulous scrotal neck). To ensure reproducibility, measurements were done twice, 1 wk apart, and the average used for statistical analysis.

2.2 Evaluation of sperm characteristics

2.2.1 Evaluation of sperm motion characteristics

Four ejaculates were collected using artificial vagina from each bull and cryopreserved (according to industry standards) for evaluation of forward progressive motility, analysis of morphology and acrosome, viability and sperm membrane 22 integrity)81. From each ejaculate, 3 straws were thawed (37 °C water bath for 30 s), emptied by pushing the cotton plug of the straws using a metal stylet, the frozen-thawed semen pooled, and motion characteristics evaluated using CASA (Sperm Vision;

Minitube, Ingersoll, ON, Canada). An aliquot (4 y,L) of the pooled sample was loaded into a pie-warmed (37 °C) Leija slide (Nieuw-Vennep, The Netherlands), and 7 fields per sample were analyzed, using the bovine sperm motility program (30 frames/object; 60 Hz frame rate; and 22 to 60 [xm2 sperm head surface detection). Total motility (TM) was defined as the percentage of sperm with an average orientation change of the head (AOC)

>5° and mean velocity (VAP) >20 urn's. Motile sperm with VAP >55 urn's, STR

(VSL/VAP) >75%, and LIN (VCL/VAP) >35% were considered progressively motile77.

In addition, the following were evaluated: curvilinear distance (DCL, (im), the average path distance (DAP, |im), distance straight line (DSL, |xm) curvilinear velocity (VCL, jam/s), straight-line velocity (VSL, |xm/s), average path velocity (VAP, nm/s), linearity

(LIN,%), straightness (STR, %), wobble coefficient (WOB, %), the ratio between VAP and VCL; mean amplitude of lateral head displacement (ALH, fim), and beat cross frequency (BCF, Hz), the frequency at which the actual sperm trajectory crossed the average path trajectory.

2.2.2 Evaluation of sperm plasma membrane viability

Plasma membrane integrity (viability) of post-thaw sperm was assessed using the

Live/Dead sperm kit (Invitrogen Canada, Burlington, ON, Canada) containing SYBR14 and propidium iodide (PI). SYBR14 stains nuclei of viable sperm green, whereas dead sperm, and those with compromised membrane integrity, are stained red by PI42. Post- 23 thaw sperm suspensions (lxlO6 sperm/mL) from each ejaculate (total of 40 samples) were stained with SYBR14 (final concentration of 100 nM) and PI (24 jaM) and incubated at room temperature (-20 °C) for 10 min, and analyzed using flow cytometry

(FACScan Becton Dickinson, San Jose, CA, USA). The excitation laser was argon (488 nm). As the initial step towards flow cytometry analysis, the gate for the side scatter

(SSC-H; proportional to granularity) and forward scatter (FSC-H; low-angle forward light scatter and is roughly proportional to the diameter of the cell were adjusted to identify the events). Subsequently, fluorescence detector 1 (FL1-H; which detects emitted photons in the wavelength of 515-545 nm) was used for detecting SYBR-14 fluorescence from live sperm, whereas fluorescence detector 2 (FL2-H; wavelength range, 561-583 nm) was used to detect PI fluorescence. Furthermore, compensation was applied to have minimal emission overlap. Sperm with compromised and damaged plasma membrane which emitted both green and red fluorescence were considered moribund. A minimum of 15000 events were recorded for each sperm sample. CellQuest Pro™ v.3.3 (BD

Biosciences, San Jose, CA, USA) was used for acquiring and calculating the proportion of live, moribund, and dead sperm. The rate of conversion of live to moribund sperm was determined by expressing moribund sperm as a percentage of total number of moribund and viable sperm.

2.2.3 Evaluation of sperm characteristics after swint-up

2.2.3.1 Swim-up procedure

A swim-up procedure with sodium hyaluronate55,56 was used to recover motile sperm for CASA and viability assays. Briefly, 3 straws of frozen semen (0.25 mL each) 24 from an ejaculate were thawed, pooled, and aspirated into a siliconized, sealed sterile pasture pipette. The semen sample was overlaid with 100 |aL of equilibrated sodium hyaluronate (10 mg/mL MAP-5; Bioniche, Belleville, ON, Canada) prepared by mixing

FERT-TALP medium containing 6 mg/mL fatty acid-free BSA, 50 ng/mL gentamicin, 25 jimol sodium pyruvate, 20 |xmol penicillamine, 10 |xmol hypotaurine, 1 [imol epinephrine, 5 jig/mL heparin82, and sodium hyaluronate (1:1, v/v) and incubated at 39

°C in 5 % CO2 and under high humidity for at least 2 h prior to use. This preparation was carefully overlaid with 200 jiL FERT-TALP medium. After 45 min of incubation at 39

°C and in 5% CO2, approximately the upper 70% of the swim up medium (-150 |iL) containing highly motile sperm were collected using a pipette, and transferred to the pre- warmed micro-centrifuge tube, for the experiments described below.

2.2.3.2 Sperm motion characteristics

Sperm motion characteristics were evaluated by CASA, as described above

(section 2.2.1).

2.2.3.3 Determination of sperm concentration

The concentration of sperm present in swim-up medium was determined using a hemocytometer and expressed as a percentage of viable sperm present in the post-thaw semen sample, as follows:

[(Post swim-up sperm concentration -f concentration of the viable sperm existing in the post-thaw sample) x 100]. 25

2.2.3.4 Evaluation of sperm viability

Sperm concentration after swim-up (using sodium hyaluronate) was not adequate for flow cytometry-based analysis of sperm viability. Therefore, post swim-up sperm were stained for viability, as described above, fixed with 0.2% glutaraldehyde, and visually evaluated for the proportion of live and dead sperm using a fluorescence microscope (Axioskop 40, Carl Zeiss, Jena, Germany) at 400 x. Sperm with complete green fluorescence were considered viable, whereas those with partial or complete red fluorescence (PI staining) were considered nonviable.

2.3 Transcriptome analysis

Testes from 3 LF and 3 HF bulls were collected post mortem and pieces of testicular tissue (-3x3 cm2) were snap frozen in liquid nitrogen. Total RNA was extracted using the RNA-Easy Column method (Qiagen, Crawley, UK) according to the manufacturer's instructions. The quality and quantity of RNA was measured with a bioanalyzer (Agilent Technologies, Palo Alto, CA, USA).

2.3.1 Microarray hybridization and data analysis

The microarray probe refers to the DNA sequence bound to the solid-surface (spotted slide preparation) support in the microarray, whereas the target is the "unknown" sequence of interest, which is extracted from given samples and is undergone several procedures (mRNA extraction, cDNAsynthesis, mRNA amplification, in vitro transcription, and labeling). In general terms, probes are synthesized and immobilized as discrete features, or spots. Each feature contains millions of identical probes. The target is fluorescently labelled (i.e. Cy3 /Cy5) and then hybridized to the probe microarray. A 26 successful hybridization event between the labeled target and the immobilized probe will result in an increase of fluorescence intensity over a background level, which can be measured using a fluorescent scanner. Data obtained from scanned slides will be normalized and analyzed by specific software. The last step would be using bioinformatics tools to obtain the comprehensive information on differentially expressed genes.

All steps of microarray procedures were performed at Dr. Guan's laboratory

(Functional genomics, University of Alberta, Edmonton). Expression of testicular genes in LF versus HF bulls was analyzed using a two-color microarray (Cy5 and Cy3). The following combination of hybridizations was used to account for variation among individual bulls within a group and affinity of the dyes.

Figure 3. Study design: Dye swap (Cy3 vs Cy5) method for 3 high-fertility versus 3 low-fertility bulls (2 replicates). Low fertile 1x2 (Cy3 vs. Cy5) & (Cy5 vs.Cy3) 4 slides

Low fertile 2x2 (Cy3 vs. Cy5) & (Cy5 vs.Cy3) 4 slides "\ {Low fertile 3x2 (Cy3 vs. Cy5) & (Cy5 vs.Cy3) 4 slides .

•Low fertile 1 x 2 (Cy3 vs. Cy5) & (Cy5 vs.Cy3) -• 4 slides High fertile 2 Low fertile 2x2 (Cy3 vs. Cy5) & (Cy5 vs.Cy3) •*•4 slides >-36 slides .Low fertile 3x2 (Cy3 vs. Cy5) & (Cy5 vs.Cy3) 4 slides

' Low fertile 1 x 2 (Cy3 vs. Cy5) & (Cy5 vs.Cy3) +• 4 slides High fertile 3 Low fertile 2x2 (Cy3 vs. Cy5) & (Cy5 vs.Cy3) -M slides Low fertile 3x2 (Cy3 vs. Cy5) & (Cy5 vs.Cy3) 4 slides 27

2.3.1.1 Preparation of slides

Duplicates of 24,000 bovine oligonucleotide probes were spotted onto a ultragap slide (Corning) using Q-array 2 (Genetix, Hampshire, UK) for microarray.

2.3.1.2 Reverse transcription

One (ig of total RNA was reverse-transcribed as described below: mixed RNA with 1 |il of T7 oligo(dT) primer, adjusted the volume to 12 [xl and incubated for 10 min at 70 °C. Then, 8 fxL of reverse transcriptase master mix was added and the resulting mixture was incubated for 2 hr at 42 °C. To synthesize the second strand cDNA, 80 [xL of second strand of master mix was added to each sample and incubated for 2 h at 16 °C and the preparation frozen immediately. In order to purify cDNA, 250 jtl cDNA binding buffer was added to each sample and the mixture passed through a cDNA filter cartilage.

The filter cartridge was washed with 500 jxL of washing buffer and eluted cDNA in 9 [xL nuclease free water at 50-55 °C. The elution step was repeated once.

In vitro transcription (IVT) of biotin labeled aRNA: For this, 26 jiL of IVT master mix was added to each sample, mixed and incubated for 4-14 h at 37 °C and then 60 |xL of nuclease-free water was added to each sample. In order to purify aRNA, 350 [xL of aRNA binding buffer was added to each sample, followed by 250 jxL of 100% ethanol.

After mixing, samples were passed through an aRNA filter cartridge, washed with 650

|xL washing buffer and aRNA eluted with 100 jiL of preheated nuclease-free water. The quantity of the aRNA was assessed with a Nanodrop.

aRNA dye coupling: An aliquot of AlexaFlour Dye (Cy3 & Cye5; Applied

Biosystems, Foster City, CA, USA) was resuspended in DMSO. Vacuum dried aRNA (5 28 to 20(xg was resuspended in 9 of coupling buffer, and 11 §xl of reconstituted

AlexaFlour dye was added to this aRNA preparation, mixed and incubated for 30 min at room temperature in the dark for 1 h. Subsequently, 4.5 jiL of 4 M hydroxylamine were added to this preparation, mixed and incubated for 15 min at room temperature in the dark.

To purify the labeled aRNA, 105 jiL of aRNA binding buffer and 75 jiL of 100% ethanol was added to the mix. Samples were passed through labeled aRNA cartridges, washed with 500 |iL of washing buffer and eluted labeled aRNA with 3 x 10 [xL of preheated (50-60 °C) nuclease free water.

aRNA hybridization: Labeled aRNA was dried and reconstituted in 9 [iL of water for fragmentation, a step necessary for proper hybridization. After fragmentation of labeled aRNA, 5 jig of these samples were diluted into the hybridization solution and then hybridized for 16-20 h inside the Hyb oven (Genetix, Christchurch, Dorset, UK) at

42 °C. Hybridized slides were washed with warmed up (42 °C) low-stringency buffer

(2 X saline-sodium citrate [SSC] and 0.5% sodium dodecyl sulfate [SDS]), high- stringency buffer (0.5 X SSC and 0.2% SDS), and 0.05 X SSC. Hybridized slides were scanned at 5 |j.m resolution and their signal intensities were detected by Q-Scan (Genetix,

New Milton, UK)83.

For this part of the study, for each experiment, 4 slides were used, including dye swaps, and 2 technical replicates. Therefore, each gene was represented 8 times in the statistical analysis Data analysis was performed by the microarray facility, University of

Calgary, Calgary, AB, Canada, using GeneSpring Version 11.5 (Agilent Technologies,

Palo Alto, CA, USA). Differences in gene expression levels between LF versus HF bulls 29 were analyzed using analysis of variance (ANOVA). The criterion for the detection of

Differentially Expressed (DE) genes was twofold or greater change in expression level, with P <0.05, which was adjusted by quantile normalization (a method to make the distributions of the transformed spot intensities as similar as possible across the microarrays)84. The quality filter of 95% was used to eliminate data from probes in any group that had an intensity variation larger than 5%. The following process was performed to obtain candidate genes:

Since the GeneSpring software considered each sample stained with just 1 dye

(either Cy3 or Cy5) as a separate file, followed by calculating an average value for both dyes for statistical comparisons, data were normalized using the "quantile" method. After data were normalized, comparison was done in 3 groups; in each group, 1 HF bull was compared to all 3 LF bulls. The next step was to identify genes which differed among all

3 bulls in each group. In order to identify only genes which were significantly different between LF and HF bulls, the variation of the bulls in each group were considered and the differentially expressed genes in common between groups were determined.

2.3.2 Bioinformatics

Gene Ontology was used to suggest the possible function of DE genes

(Differentially Expressed), and the KEGG pathway database (Kyoto Encyclopedia of

Genes and Genomes) was used to indicate the possible role of DE genes in biological processes. 30

2.3.3 Q-PCR analysis

To validate and confirm the microarray results, qPCR was performed. Briefly, total RNA for each sample was extracted from 30 mg of frozen tissue which was disrupted using a

Qiagen tissue lyser, followed by passage through a Qiashredder (Qiagen) spin column according to the manufacturer's instructions. Total RNA was purified using the RNeasy plus mini kit (Qiagen) according to the manufacturer's instructions.

Reverse transcription of the mRNA was performed using a combination of oligo dT primers and random nonamers using the Quantitect reverse transcription kit (Qiagen) according to manufacturer's instructions and the resultant cDNA was stored at -20 °C before PCR analysis. Specific primers for the amplification of the ACTB (accession number NM_173979) housekeeping gene were: sense, 5'-

CCAACCGTGAGAAGATGACC-3'; antisense, 5'- CCAGAGGCATACAGGGACAG-

3'. Specific primers for the amplification of ASB5 (accession number NM_001075744) were: 5'- GTTACACGAAGCCTGCCTTG-3'; antisense,5'-

GTGAGCACGCGTTGAATAAG-3'. Real time PCR was carried out in triplicate with the Quantitect SYBR green PCR kit (Qiagen) using an Eppendorf realplex 4 Mastercycler

(Eppendorf Canada, Mississauga, ON) and conditions were optimized to achieve a linear relationship between initial RNA concentration and the PCR product (R2 > 0.99) with

>95% efficiency. The amplification was performed as follows: 95 °C, 15 s; 55 °C, 30 s;

72 °C 30 s; for a total of 45 cycles. The specificity of the primers was confirmed by melting curve analysis as well as DNA-PAGE analysis which confirmed the expected amplicon sizes of 97 and 119 bp for ACTB and ASB5, respectively. Realplex 2.0 software (Eppendorf) was used to determine the threshold cycle numbers (Ct). Subtracting the Ct of the housekeeping gene (ACTB) from the Ct of the target gene yielded the ACt values (ACT = CT (target gene) - CT (endogenous reference gene)) for each test sample in the HF and LF groups. Then, the fold change calculated based on

2"Aaq (AACT = average ACT (sample of interest) - average ACT (reference sample)).

Melting curve and titration was also obtained85.

2.3.4 Evaluation of the ASB5 protein expression in testis

To evaluate the expression of the ASB5 protein in testis, ASB5 antibody (ProSci

Inc., Poway, CA, USA) was used. Testes from the same samples used in the microarray study (3 LF vs 3 HF bulls) were used for total protein extraction. After extraction, the amount of extracted proteins was quantified using a DC™ Protein Assay (Bio-Rad,

City?, ON, Canada). A protein immunoblotting technique (Western Blot) was used to evaluate expression of the ASB5 protein. The extracted proteins were mixed 1:5 with

Laemmli's sample buffer (5X); 100 ng of total protein was loaded in each lane of an SDS polyacrylamide gel (3% stacking, 15% resolving). Moreover, in order to evaluate the expression of ASB5 protein in sperm, total extracted protein from sperm was used, as well as fetal muscle lysate (ProSci Inc Poway, CA, USA) as a positive control.

Electrophoresis was carried out at a constant voltage of 100 volts. Electrotransfer to nitrocellulose membranes was done at a constant voltage of 100 volts for 1 h. Non­ specific binding sites were blocked with skim milk (3% w/v), and membranes were immunoblotted with ASB5 antibody (ProSci Inc.). Immunoreactive bands were detected using enhanced chemiluminescence. 32

2.4 Proteomics

2.4.1 Semen samples

Three ejaculates (over the course of 2 wk) were collected (using an artificial vagina) from each bull. Sperm were separated from seminal plasma by centrifugation

(10,000 x g for 10 min) and the resulting sperm pellets were washed twice in TALPH

(700 x g for 10 min). Sperm and seminal plasma were snap-frozen in liquid nitrogen and stored in liquid nitrogen until use.

2.4.2 Two-dimensional gel electrophoresis

Two-dimensional (2D) gel electrophoresis86, as used for somatic cells, was modified and conducted as described below.

2.4.2.1 Extraction and quantification of total proteins

Sperm pellets were thawed on ice and 100 jiL of these pellets were added to 300 jiL of the extraction buffer containing 8 M Urea (Bio Ultra Pure Urea Molecular Biology

Grade, Bioshop Canada Inc., Burlington, ON, Canada), 2 M Thiourea (Thiourea

Proteomics Grade, Bioshop Canada Inc.), 20 mM Dithiothreitol (DDT; DL-

Dithiothreitol, Sigma Aldrich Inc. St. Louis MO, USA), 1.2 mM Tributyl Phosphate

(TBP; TBP reducing agent, Bio-Rad Laboratories, Hercules, CA, USA), 4% CHAPS w/v

(CHAPS Anagrade, Anatrace, Maumee, OH, USA), and a lx concentration of a protease inhibitor Cocktail (Protease Inhibitor Cocktail Tables complete Mini EDTA-free; Roche,

Mannheim, Germany). These preparations were maintained on ice for 1 h and frequently vortexed (3000 rpm). These sperm preparations were centrifuged for 10 min at 10000 x g 33 and frozen at -80 °C. A small aliquot of protein preparation from each sample was used for protein quantitation (RC DC Protein Assay; Bio-Rad, Mississauga, ON, Canada).

2.4.2.2 Rehydration of IPG strips

Immobilized pH gradient (IPG) strips (17 cm, pH 3-10 Nonlinear; Bio-Rad)

were used. Strips were passively rehydrated overnight at room temperature with 300 |xg

protein in extraction buffer. Prior to rehydration, total protein (2 (ig /[AL in extraction

buffer), was mixed 1:1 with extraction buffer containing 1% (v/v) broad-range ampholytes (3-10; Bio-Rad), 0.2% (v/v) each of 5 narrow-range ampholytes (Bio-Rad),

3-5,4-6, 5-7, 7-9, 8-10, acrylamide monomer (3% v/v), and bromophenol blue (0.002%

w/v). All components were added in one step and thoroughly mixed by vortexing. The

IPG strip was laid, gel side down, in a rehydration tray containing the protein preparation, and the strip was overlaid with mineral oil to prevent evaporation.

2.4.2.3 Isoelectric focusing

Isoelectric focusing (IEF) was performed on a Protean DEF Cell (Bio-Rad) at 17

°C, using a focusing tray designed for 21 cm IPG strips. Chromatography paper (3 mm thick; Fisher Scientific, Toronto, ON, Canada) was used to make 3-cm electrode wicks. A larger focusing tray was used to accommodate longer electrode wicks, which enhanced removal of salts87. The IEF procedure consisted of 4 steps of voltage modulation: 1) voltage was ramped to 250 volts for 15 min and the de-salting step was repeated once; 2) voltage was linearly ramped to 4,000 volts over 2 h, with a maximum of 50 ^A/gel; 3) the IPG strips were focused at 4,000 volts for a total of 75,000 volt-hours; and 4) strips 34 were held at 500 volts until removed from the IEF Cell. During Steps 1-3, electrode wicks were changed as needed to remove salts and facilitate linear ramping. After Step 4, strips were sequentially equilibrated with equilibration buffer to coat proteins with dodecyl sulphate and to reduce and alkylate cysteines: focused IPG strips were sequentially equilibrated in equilibration buffer (6.0 M urea, 375 mM Tris, 20% glycerol, and 2% sodium dodecyl sulfate and 130 mM DTT) for 10 min, followed by alkylation for

10 min in buffer containing 350 mM acrylamide monomer.

2.4.2.4 Second dimension

The second dimension was carried out on large format polyacrylamide gels (18 x

18 x 0.1 cm), with 12% resolving gels. The focused IPG strip was sealed to the top of the stacking gel with 0.5% low melting agarose solution in 375 mM Tris and 0.007% bromophenol blue; 5 [iL kD marker (Unstained Protein Molecular, Fermentas Canada

Inc., Burlington, ON, Canada) was used. Electrophoresis was carried out in a cold room

(4 °C) using pre-chilled running buffer (Tris/Glycine/SDS Buffer for SDS-PAGE applications; BioShop, Burlington, ON, Canada). Gels were run in a Protean II xi Cell tank (Bio-Rad) at a constant current of 24 mA/gel for ~ 8 h, with a maximum limit of 300 volts. To minimize technical variation, 8 gels were cast and run simultaneously.

2.4.2.5 Staining, imaging and gel analysis

After completion of the second dimension, gels were fixed overnight in 10% methanol and 7% acetic acid. Gels were washed with double deionised water, 3 or 4 times over 1 h to remove fixative, followed by overnight staining with SyproRuby (Bio- Rad). Stained gels were de-stained in fixative solution (10% methanol and 7% acetic acid) for 30 min, followed by washing 4 times in double deionised water for 1 h. Gels were imaged with ProXpress Proteomic Imaging System (PerkinElmer, Waltham MA,

USA). Gel images were acquired with a maximum spot intensity (50-55 x 103 pixels).

Analysis and comparisons of gel images was done using gel analysis software, Delta2D

4.0 (Decodon, Greifswald, Germany). The Delta2D program used algorithms to make match-vectors between the same spots on different gels. Spot detection was performed on a virtual gel, made by fusing all the gels to a single gel containing every spot present in each of the original gels, using Delta2D software. All spots detected were manually reviewed and any spots picked up erroneously by the software, e.g. speckles or poorly resolved spots, were deleted. Detected spots were transferred to the original gels and normalized spot volumes were calculated. Spot boundaries in every gel were made by

Delta2D and did not depend on the virtual image. To enable quantitative comparative spot analysis, normalization occurred at 3 stages; first at 2D-PAGE by loading an identical amount of protein; second at gel imaging by acquiring a consistent maximum spot intensity (50-55 x 103 pixels); and third at analysis, using Delta2D by expressing normalized spot volumes as a fraction of the sum of all spot volumes in the gel88.

To select the highly differentially expressed (DE) protein spots, the following criteria were used: (i) significant difference in protein expression with greater than 2-fold difference in relative expression levels (Wilcoxon Rank Sum Test, P < 0.05; 15 gels each for LF and for HF bulls); and (ii) 100% reproducibility (coefficient of variation = o/ji. <

1) across the sample population analyzed OQ. 36

2.4.2.6 Determination of the pi and molecular mass of DE proteins

Since the Delta2D software was unable to determine the actual pH and IE points of detected spots on the gels, a separate 2D gel electrophoresis using a standard protein kit (SERVA Proteome Markers, 5 vials; SERVA Electrophoresis GmbH, Heidelberg,

Germany) was conducted. The standard consists of 8 proteins (cytochrome C, myoglobin,

B-lactoglobulin, glucose-1-dehydrogenase, lipase, catalase, albumin, and glucose oxidase), with a pi range from 5.5 to 9.8 and a molecular weight range from 11.7 to 77.0 kDa. The enclosed glucose-1-dehydrogenase has a molecular weight of 113.000 Da, but in the presence of urea (8 M) and SDS, will dissociate into 4 subunits with an apparent molecular weight of 28 kDa each. The proteins are present in equal weight proportions

(each -13 ng/protein).

After running the standard gel and obtaining the image as described above, the image was uploaded in the Delta2D software and gels were calibrated according to the detected spots on the standard gel with identified molecular mass and pi.

2.5 Statistical analyses

A General Linear Model (GLM) procedure was used to compare testicular physical characteristics (SC, scrotal neck length, scrotal neck circumference, testicular length and width, testicular echotexture, diameter of TVC, bottom SST, top SST, and

SST gradient) and viability between high- versus low-fertility bulls (separate analysis for each end point). A Mixed Models procedure was used to compare sperm motion characteristics between high- and low-fertility bulls. Pearsons's correlation coefficients were calculated to determine the relationship between the in vivo fertility (NRR) and various sperm motion and viability end points. All analyses were conducted using SAS software (SAS Institute, Cary, NC, USA), and P<0.05 was considered significant. Data were reported as mean ± SD. 38

Chapter Three: Results

3.1.1 Testicular physical characteristics

Testicular width was reduced for LF vs HF bulls (77.3 ± 3.2 vs 81.8 ± 2.5 mm; P

< 0.05). Despite numerical differences in SC (37.3 ± 1.4 vs 39.8 ± 2.8cm), there were no significant differences in LF vs HF bulls for scrotal neck circumference (23.1 ±3.4 vs

24.8 ± 3.0 cm), scrotal neck length (10.5 ± 2.1 vs 10.6 ± 1.8 cm), testicular length (130.8

± 6.5 vs 131.5 ± 5.5 mm). Furthermore, there was no significant difference between fertility groups for scrotal morphology (2.6 ± 0.8 vs 2.5 ± 0.5 for LF and HF bulls, respectively).

3.1.2 Testicular echotexture

There were no significant differences between LF and HF bulls for echotexture of testicular parenchyma (142.1 ± 18.4 vs 135.3 ± 9.5) or diameter of the testicular vascular cone (31.0 ± 4.5 vs 32.5 ± 3.3 mm).

3.1.3 Scrotal thermography

There were no significant differences between LF and HF bulls for scrotal surface temperature at the top (31.9 ± 1.3 vs 31.6 ± 0.8 °C, mean ± SD) and bottom (28.7 ±1.4 vs 29.2 ± 0.6 °C) of the scrotum, or average scrotal surface temperatures overlying individual testis (30.3 ±2.1 and 30.4 ± 1.4) were not significantly different between HF and LF bulls. Scrotal temperature gradients between scrotal areas corresponding to the top and bottom of the testes (3.3 ± 1.3 vs 2.4 ± 0.8 °C), were not significantly different between the two groups 39

3.2 Sperm characteristics

3.2.1 Sperm motion characteristics

Immediately after thawing, sperm from LF bulls had lower (P < 0.05) ALH. Total motility and progressive motility were lower (P < 0.05) in LF bulls (Table 2; Figure 5).

Post-swim up ALH was lower (P < 0.05) in LF compared to HF bulls (Table 3; Figure 5).

Consistent with this observation, LIN, STR, WOB, VSL, and DSL after swim-up were higher (P < 0.05) in LF vs HF bulls (Table 3).

The LIN, STR and BCF of frozen-thawed sperm were negatively correlated with

NRR (Table 4), whereas all end points for velocity (VCL, VAP and VSL) and distance

(DCL, DAP, DSL), as well as ALH and total and progressive motility, were positively correlated with NRR (Table 4; Figure 5). Furthermore, for post-swim up sperm, WOB,

LIN, STR, BCF, and DSL were negatively correlated with NRR (Table 4), whereas, only

VSL and ALH were positively correlated with NRR. The percentage of hyperactivated sperm post-thaw was lower (P < 0.01) in LF compared to HF bulls (3.2 ± 3.4 vs 9.6 ± 3.0, respectively). Moreover, this end point was significantly correlated (r = 0.83, P < 0.001) with fertility (Table 4).

3.2.2 Sperm plasma membrane viability

In LF versus HF bulls, the percentage of viable sperm post-thaw was lower (P

< 0.0001), there was a lower percentage of dead (P < 0.001) and moribund cells (P <

0.05), and rate of conversion of live to moribund sperm was lower (P < 0.001; Table 5 and Figure 6). Proportion of dead (r = -0.43, P < 0.01) and moribund (r = -0.33, P < 0.05) sperm, and also rate of conversion of live to moribund sperm (r = -0.43, P < 0.01) were 40 negatively correlated with NRR (Table 5 and Figure 6). Percentage viable sperm post swim-up was lower (63.0 ± 1.17 vs 70.0 ± 1.42, P < 0.01) in LF versus HF bulls, and positively correlated with NRR (r = 0.78, P < 0.01).

3.2.3 Sperm concentration

Mean concentrations of viable sperm (3 straws) in LF vs HF bulls were 26.8 ± 4.8 x 106 vs 30.0 ± 6.2 x 106, respectively, for post-thaw semen, and were 1.6 ± 4.4 x 106 vs

2.2 ± 2.8 x 106 for post-swim up sperm. Furthermore, LF bulls had a lower (P < 0.001) concentration of sperm in the swim-up medium (expressed as a percentage of viable sperm in the post-thaw semen) compared to HF bulls (5.0 ± 6.2vs. 8.0 ± 3.8 %, respectively). 41

Table 2. Motion characteristics (mean ± SD) of frozen-thawed sperm from high- versus low-fertility Holstein bulls.

End point Fertility

Abbreviation High Low

Motility (%) -- 63.2 ± 6.2a 52.6 ± 9.4b

Progressive motility (%) — 57.0 ± 6.2a 45.6 ± 11.0b Distance: Curve line (|im) DCL 48.4 ± 3.2 38.6 ± 9.4

Distance: Average path (fam) DAP 26.9 ± 1.4 23.0 ± 4.0 Distance: Straight line (^m) DSL 20.8 ± 1.2 18.6 ±2.6 Velocity: Curve line (|im/s) VCL 109.8 ± 7.8 86.6 ±22.1 Velocity: Average path (jim/s) VAP 61.2 ±3.6 51.8 ±9.6 Velocity: Straight line (nm/s) VSL 47.2 ± 2.8 41.6 ±6.4 Linearity LIN 0.4 ± 0.0 0.4 ±0.0 Straightness STR 0.8 ± 0.0 0.8 ± 0.0 Wobbliness WOB 0.6 ±0.0 0.6 ±0.0 Beat cross frequency (Hz) BCF 22.8 ± 0.6 24.6 ± 2.6 Amplitude of lateral head ALH 5.2±0.4a 3.6 ± l.lb displacement (fim)

Hyperactivated1 sperm (%) — 9.6 ± 3.0° 3.2 ± 3.4d abWithin a row, means without a common superscript differed (P < 0.05). cdWithin a row, means without a common superscript differed (P < 0.01). Hyperactivated sperm calculated based on (ALH > 7 |im, LIN < 60, and VCL > 120 pirn) 42

Table 3. Mean (± SD) sperm motion characteristics after swim-up in high- versus low-fertility Holstein bulls End point Fertility

Abbreviation High Low

Distance: Curve line (jim) DCL 100.4 ± 7.6 94.6 ± 13.2 Distance: Average path (jim) DAP 41.8 ±3.2 43.6 ±4.6 Distance: Straight line (nm) DSL 28.6 ± 4.4a 34.0 ± 5.6b Velocity: Curve line (fim/s) VCL 210.4 ± 16.2 197.2 ± 26.8 Velocity: Average path (jim/s) VAP 87.8 ± 7.4 91.2 ±9.4 Velocity: Straight line (fim/s) VSL 60.0 ± 9.4a 71.4 ± 11.5b Linearity LIN 0.2 ± 0.0a 0.4 ± 0.0b Straightness STR 0.6 ± 0.0a 0.8 ± 0.0b Wobbliness WOB 0.4 ± 0.0a 0.5 ± 0.0b Beat cross frequency (Hz) BCF 20.2 ±1.8 22.0 ± 3.2 Amplitude of lateral head ALH 7.0 ± 0.4a 6.0 ±0.1b displacement (jim) abWithin a row, means without a common superscript differed (P < 0.05). 43

Table 4. Correlation coefficients between sperm motility end points and non-return rate (NRR) in Holstein bulls.

Motility end point Post-thaw Post-swim up

Mean ± SD r Mean ± SD r

Motility (%) 57.8 ± 8.0 0.73 -- —

Progressive motility (%) 51.2 ±8.9 0.70* -- — DCL (nm) 43.6 ± 8.4 0.75* 97.0 ±7.9 0.58 DAP (|im) 24.0 ± 3.5 0.71* 42.6 ±1.9 0.42 ** DSL (nm) 19.6 ±2.1 0.66* 31.4 ±3.8 -0.83 VCL (nm/s) 98.2 ± 20.0 0.74* 203.0 ± 17 0.60 VAP (nm/s) 56.4 ± 8.4 0.70* 89.4 ±4.1 0.33 * •* VSL (nm/s) 44.4 ± 5.2 0.67 65.8 ±8.1 0.81 *** LIN 0.4 ±0.1 - 0.74* 0.4 ±0.1 -0.85 * *** STR 0.8 ±0.0 -0.73 0.8 ±0.1 -0.86 ** WOB 0.6 ±0.0 -0.60 0.4 ±0.0 -0.82 BCF 23.6 ± 2.0 - 0.70* 21.2 ±2.1 -0.67* ** ** ALH (fim) 4.4 ± 1.1 0.80 6.4 ± 0.9 0.79 ** Hyperactivated sperm (%) 6.4 ±4.2 0.82 -- — * P < 0.05 "P<0.01 *"P< 0.001 44

Table 5. Viability of frozen-thawed sperm and its correlation with NRR in high versus low-fertility Holstein bulls.

Viability end points (%) High-fertility Low-fertility Correlation with NRR Mean ± SD Mean ± SD Mean ± SD r

SYBR14 positive 60.6 ± 9.7a 49.4 ± 8.0b 55.0 ± 10.4 0.45*

PI positive 30.8 ± 8.8° 41.0 ±7.9d 35.9 ± 9.7 -0.43*

Moribund 8.4 ± 1.6e 9.4 ± 1.2f 9.0 ± 1.5 -0.33**

Moribund/total viable1 12.6 ± 3.4C 16.4 ± 3.1d 14.4 ± 3.7 -0.43*

"''Within adjacent columns, means without a common superscript differed (P < 0.001) cdWithin adjacent columns, means without a common superscript differed (P < 0.01) efWithin adjacent columns, means without a common superscript differed (P < 0.05) *P<0.01 **P < 0.05 'Total viable = moribund population + viable population 45

Figure 4. Schematic representation of sperm motility patterns at post-thaw between low- vs high-fertility Holstein bulls.

A) Sperm from high-fertility bulls with high amplitude and low frequency motility patterns; and B) sperm from low-fertility bulls with low amplitude and high frequency motility patterns. The dashed line represents the average path distance, whereas the continuous line represents the actual sperm head trajectory (curvilinear distance). 46

Figure 5. Motion characteristics of frozen-thawed sperm from Holstein bulls, post- thaw and post-swim up.

Post-thaw Post-Swim up Post-Swim up

Post-thaw Post-Swim up Post-thaw Post-Swim up

Within a time (post-thaw or post-swim up), means without a common superscript differed (P < 0.05). DSL = straight line distance; LIN = linearity; VSL= straight line velocity; ALH = amplitude of lateral head displacement. LF = Low-fertility bulls; HF= High-fertility bulls 47

Figure 6. Viability of Holstein bull sperm post-thaw.

High-fertility bulls Low-fertility bulls 12.63% 16.35% CRLMS CRLMS

ISYBR14 Positive • PI positive • Moribund ISYBR14 Positive • PI positive • Moribund

Proportion of viable (r = 0.5; P < 0.05), moribund (r = -0.3; P < 0.05) and dead (r = -0.4; P < 0.05) sperm, and moribund sperm expressed as a proportion of total live sperm (moribund population + viable population) (r = -0.4; P < 0.05) were correlated to NRR. Conversion Rate of Live to Moribund Sperm (CRLMS) was significantly higher in low- fertility versus high-fertility bulls, and CRLMS was negatively correlated to fertility. 48

3.3 Transcriptome analysis using microarray

Based on microarray analysis using GeneSifter software, there were 53,43 and 46

genes with >2-fold changes in expression between HF and LF samples (Table 6); among

these, only 4,11 and 11 genes, respectively, commonly differed between HF versus LF

bulls (Figures 7-9).

Table 6. The number of differentially expressed genes with 2-fold and higher changes between high- and low-fertility bulls. No. genes (>2-fold change) The absolute maximum change value for each of the HF bulls Down regulated Up regulated HF #1 HF #2 HF #3 HF bull #1 vs 3 LF bulls 18 35 13.3 6.2 12.1

HF bull #2 vs 3 LF bulls 14 29 6.3 6.3 7.0

HF bull #3 vs 3 LF bulls 9 37 4.6 5.1 7.3 49

Figure 7. Volcano plot which displays fold changes versus respective level of statistical significance of high-fertility bull No. 1 vs all 3 low-fertility bulls.

.9 VtalanoPtot ! TatOanlito ; SdectedTest: TTotuipalned 5- .1 1 — j- ! p^kKConputatan: A«ymp>ullc i it Wipt ICMipuneCwn;^ " PBfWBrnO(TPo\)* • ' 'I | II ! i ItaaftSUmary --- - - t P* P<005 P <0.02 K0.01 P<0.0... P<0.0... TJm j FCal C i 84 13 13 10 3 1 • -- - FC>L1 S6 13 10 3 1 S a uo •C > LS 18 11 11 9 3 1 O • • FC>Z0 w4 4 4 4 4 2 1 o • "C >3.0 1 1 1 1 1 1 # 24 • b|Kcte

fc.64725 9.4775794E-5 0.00288367 81.100362 9.157365E-8 7.692187E-6 iM i- K. 19415 9.5109275E~4 0.007989179 -2 Bt.52067 2.9452494E-4 0.00618S024 I og2 (Fold change) - " W'.i ./ alert,*

There were only 4 genes (red colour) which significantly differed from HF bull No.1 and all 3 LF bulls (based on a >2-fold difference in expression level). 50

Figure 8. Volcano plot which displays fold changes versus respective statistical significance of high-fertility bull No. 2 vs all 3 low-fertility bulls.

OMPcranitf EkfTCflrion Report Volcano Hot TeMOeKj^aon SdaeMTat: TTe*ti*pifr«d 7- IMMkjtcmputtlan: Mdnpteic HJIpit Testing Correction: DertnW l tothtoeiq 6

5 -J t Pri P <0.05 P<0.02 P<0.01 P<0.... P<0.... PC* M 21 22 18 11 6 PC> LI 73 2B 22 !• 11 « 4- 4- -i- B PC > 1.5 33 22 IS a 11 « PC >2.0 14 It 10 9 7 C PC > 3.0 4 4 4 4 4 4 btwdt... 1 0 0 0 0

r

Bt. 96393 0.0012135132 0.006752708 20317.0(948552... 6.3993444E-4 0.004886772 1 -3 -2 -1 0 Bt62175 0.006741837 0.024622362 1 20473.CX949591... 2.7447413E-6 5.097258E-5 a Bl. 13451 0.0039432826 0.016018428 1 R.28280 2.333705E-6 5.097258E-5 log2(Fold changt) Bt.100362 1.021102E-9 8.577257E-8 Bt.72769 9.W1WW7 0.016018428 'W afatp* HHiMiMil ~~

There were only 11 genes (red colour) which significantly differed from HF bull No. 2 and all 3 LF bulls (based on a >2-fold difference in expression level). 51

Figure 9. Volcano plot which displays fold changes versus respective level of significance of high-fertility bull No. 3 vs all 3 low-fertility bulls.

VotanoPtot TertOeaotpion - • MkMIM: TTotunpM fKMbeeoMpulaVon: 0»>wpWlc nwpi lOTvwnKwK PppMiiMiMry •= 5 KmttSmmmy ?U « 31 2S 19 u < PC > L5 30 25 X IS 13 5 a 3 •C >2.0 11 11 » s • 4 o PC >3.0 s 5 A 2 2 2 E*pecte... 1 0 0 0 0 . H •

. "• S •' • 1 •*1- V •i i.- iV.16 itf;nii4n i»ffe^Ti:iiii^¥r i ifrar

•188760 4.5131738E-4 0.0031592217 ->| 19129.CV976001. 8.0541625E-8 2.2551656B-6 I * It.35016 0.002841881 0.011367524 Bt 13451 0.004354531 0.015240858 Bt64725 4.139416E-6 0.0027736E-5 Bt.100362 1.1078753E-8 4.6530764E-7 tog2(Fo)d change) Bt.16582 8.6746516E-4 0.004554192 Sdactp*

There were only 11 genes (red colour) which significantly differed from HF bull No.3 and all 3LF bull (based on a >2-fold difference in expression level).

Based on heat maps (graphical representation of data where the values taken by a variable in a two-dimensional table are represented as colors; Figures 10 and 11), there was wide variation among bulls within each fertility group. Finally, after normalization and statistical analysis (Qneway ANOVA) there were no substantial difference in gene expression patterns among these bulls (Figure 12). Consequently, only two genes were identified as differentially expressed between HF and LF bulls. 52

Figure 10. Variation among 3 HF bulls according to gene expression and heat map chart agnaaiaiaitaM

Gene ID Bt10608 9t«lSD Bt65O10 BtlS9S 17197_(X72.., 82_1*28:L.. Bt8S006 2231_145B4... 4453_112S7... Bt4141 Bt 42045 23134.5372... Bt22071 Bt 27106 Bt 49319 Bt58652

HF bull #1 HF bull #2 HF bull #3

Each line represents one gene and different colors represent different levels of gene expression. This heat map created from clustering advanced analysis operation, considering >2-fold change with Hierarchical clustering Algorithm. 53

Figure 11. Variation among 3 LF bulls according to the gene expression and heat map chart laaaia

Gene ID

Bt88760 Bt81468 Bt 15553 8t97M9 BLS2M0 Bt35016 Bt29715 BL6915 Bt 64557 Bt552 Bt643 BtM36 12D77_1085... BtUBSS 16388_1443... 17180 CX72...

LF bull #1 LF bull #2 LF bull #3

Each line represents one gene and different colors represent different levels of gene expression. This heat map was created from clustering advanced analysis operation, considering >2-fold change with Hierarchical clustering Algorithm. 54

Figure 12. Heat map showing the cluster obtained from oneway ANOVA.

Gene ID

Bt17985 BtSfrW 210S4.CX95.

C07... 20UL13904. R.65+H Bt 21826 Bt. 46583 2083Q_CX95... Bt.22389 19330_CV97. 17797_CN6. 19306_CV97... Bt.99106 Sample Sample Sample Sample Sample Sample Sample Sample #1 #2 #J #4 #5 #6 #7 #8

Each line represents one gene and different colors represent different levels of gene expression. This heat map created from clustering advanced analysis operation with hierarchical clustering algorithm. Cluster obtained from oneway ANOVA corrected with P < 0.05 for comparison of the genes from 1 HF bull vs all 3 LF bulls together. The same color (yellow) indicated that there was no substantial difference in gene expression patterns among these bulls. 55

To determine genes that are significantly differed between HF and LF bulls, the differentially expressed genes in common between groups were determined. Only 2 genes were commonly found to significantly differ between all HF versus LF bulls (Table 7).

Table 7. Two genes differentially expressed (DE) in common between all low- and high-fertility bulls.

Gene ID Fold changes in high- vs Gene name Gene symbol low-fertility bulls

Bt. 64725 23 fold up regulation in HF bulls ankyrin repeat and SOCS box containing 5 ASB5

seauence has been retired: current entrv" is BL52067 2.6 fold up regulation in HF bulls AKD1 BU7503 56

3.3.1 Bioinformatics:

The NCBI database (UniGene) listed the following information regarding these 2 genes:

ASB5is located on Chromosome 27; a role for intracellular signal transduction has been assigned for this gene.

Figure 13. Protein sequence of ASB5 1 msmveenrpf aqqlsnvyft ilslfcfklf vkislailsh fyivkgnrke aariaaefyg 61 vtqgrgswad rsplheaasq grllalrtll sqgynvnavt idhvtplhea clgdhvacar 121 tllqaganvn aitidgvtpl fnacsqgsts ctellleyga kpqlesclps ptheaaskgh 181 hecleilisw gvdvdqdiph lgtplyvacm sqqfhcvrkl lyagadvqkg kywdtplhaa 241 aqqscteivn lllefgadin akntdllrpv dvatsnslve rlllqheatp sslcqlcrlc 301 irnyigrprl hlipqlqlpt llqnflqyr

The homology of this gene was also checked using HomoloGene in NCBI; its conservation among species is an indicator of its importance. The Expressed Sequence

Tag (EST) profile of this gene was also obtained and compared among cattle, mice, and humans (Figures 14-16). Although expression of this gene was reported in the human and mouse testis, there was no evidence regarding its expression in the bovine testis. muscle 452 27/59616 Figure 14. Bovine EST profile of ASB5. omasum 0 0 /2241 ovary 0 0 /47154 rumen 0 /44084 salivary gland 0 0 /1217 seminal vesicle 0 0 /1275 skin 0 /35377 testis 0 0 /14168 uterus 0 /22978

muscle 120 13/107709 Figure 15. Human EST profile of ASB5.

nerve 190 i^ 3 /15760

ovary 0 0 /102045

placenta O 0 /280776

prostate 10 2 /189408

salivary gland 0 0 /20155

skin 0 0 /210552

spleen 0 0 /53961

stomach 0 0 /96591

testis 3 /330371

uterus 0 /232829 muscle 623 >17/27256 Figure 16. Murine EST profile of ASB5.

skin 0 0 /114950

spinal cord 0 0 /21805

spleen 10 '1 /94430

stomach 33 >1 /29435

sympathetic 0 0 /9045 ganglion

testis -1 /113759

thymus 0 /116168

uterus 0 /6842

LEGEND

Restricted pools are represented by orange border Liver I98 13/131488 Lung 0/282332 X \ Transcripts Gene EST/ Total EST in pool Pool Per million (TPM) Name Spot intensity based on TPM According to the KEGG (Kyoto Encyclopedia of Genes and Genome) database the

ASB5 protein is involved in Protein modification and protein ubiquitination.

Based on q-PCR, actin primers had better % efficiency (the efficiency of the reaction can be calculated by the following equation: E = 10(-l/slope) -1. The efficiency of the PCR should be 90-110% meaning doubling of the amplicon at each cycle) compared to PGK primers (101.64 vs 94.17 % respectively).

Analyzing the raw data obtained from q-PCR and calculating the ACt. for ASB5 in HF vs. LF bulls was calculated (3.69 ± 0.59 vs 4.77 ± 0.98 respectively; Tables 8 and

9). The mean fold change of ASB5 gene expression was calculated based on 2"AACt

(Table 10) and the result showed that ASB5 2.24 ± 0.87 higher expressed in HF bulls vs

LF bulls. Fluorescent intensity of S YBR green across cycles representing relative concentration of ASB5 transcripts was obtained and showed the difference among samples (Figure 17). The melting curve showed a good quality of the qPCR by showing just one pick per each sample (Figure 18). The results obtained from target titration for

ASB5 validated the Ct difference per cycle as one unit difference of Ct representing two fold changes in cycle (Figure 19). 60

Table 8. Three experiments calculating ACt. for ASB5 for all HF and LF bulls.

Exp. #1 Ct. SYBR (ASB5) Ct. SYBR (ACTB)

Rep. Rep. Rep. Rep. Rep. Rep. Ave. ± SD Ave. 1 SD #1 #2 #3 #1 #2 #3 ACt (ASB5-ACTB). HF #1 21.39 21.32 21.43 21.38±0.06 17.5 17.43 17.42 17.45 ±0.04 3.93 HF #2 20.73 20.69 20.58 20.70 ± 0.13 17.21 17.14 17.29 17.21 ±0.08 3.49 HF #3 20.90 20.85 20.57 20.77 ±0.18 18.23 18.17 18.48 18.29 ±0.16 2.48 LF#1 22.29 22.15 22.13 22.19 ±0.09 16.83 16.97 17.16 16.99 ±0.17 5.20 LF #2 22.83 22.51 22.71 22.68 ±0.16 17.27 17.20 17.82 17.43 ± 0.34 5.25 LF #3 20.87 20.72 20.68 20.76 ±0.10 17.04 16.93 17.61 17.19 ± 0.37 3.57

Exp. #2 Ct. SYBR (ASB5) Ct. SYBR (ACTB)

Rep. Rep. Rep. Rep. Rep. Rep. Ave. ± SD Ave. ± SD #1 #2 #3 #1 #2 #3 ACt (ASB5-ACTB). HF #1 21.94 22.0 21.84 21.93 ± 0.08 17.46 17.61 17.75 17.61 ±0.14 4.32 HF #2 21.67 21.30 21.32 21.43 ±0.21 17.32 18.36 18.09 17.92 ± 0.54 3.51 HF #3 20.69 20.65 20.66 20.66 ±0.02 16.86 16.96 17.13 16.98 ± 0.14 3.68 LF#1 23.64 23.50 23.67 23.60 ±0.09 17.61 17.94 18.03 17.86 ±0.25 5.74 LF #2 22.78 22.98 23.05 22.94 ±0.14 17.53 17.99 17.94 17.82 ±0.25 5.12 LF #3 21.61 21.72 21.67 21.67 ±0.06 17.69 17.85 17.93 17.82 ± 0.12 3.85

Exp. #3 Ct. SYBR (ASB5) Ct. SYBR (ACTB)

Rep. Rep. Rep. Rep. Rep. Rep. Ave. ± SD Ave. ± SD #1 #2 #3 #1 #2 #3 ACt (ASB5-ACTB). HF#1 22.91 22.92 22.96 22.93 ±0.03 18.32 18.32 17.73 18.12 ± 0.34 4.81 HF #2 22.42 22.16 22.33 22.30 ±0.13 18.76 18.79 18.82 18.79 ±0.03 3.51 HF#3 20.99 21.15 21.05 21.06 ±0.08 17.37 17.68 17.66 17.57 ± 0.18 3.49 LF #1 24.09 24.22 24.71 24.34 ±0.32 18.55 18.91 18.79 18.75 ± 0.18 5.59 LF #2 23.27 23.57 23.59 23.47 ±0.18 18.04 18.55 18.68 18.42 ±0.33 5.05 LF#3 22.37 22.15 22.17 22.23 ±0.12 18.47 18.84 18.7 18.67 ±0.19 3.56

Ct (threshold cycle): threshold cycle reflects the cycle number at which the fluorescence generated within a reaction crosses the threshold. ACt = Ct (sample) - Ct(input or internal control). Exp. = Experiment. Rep. = replicate. LF = Low-fertility bulls; HF = High- fertility bulls. 61

Table 9. Mean (± SD) ACt values for ASB5 in HF and LF bulls based on 3 replicates.

REP. #1 REP. #2 REP. #3 Ave. ACt. ± SD Group Ave. ACt. ± SD HF#1 ACt. 3.93 4.32 4.81 4.35 ± 0.44 HF#2 ACt. 3.49 3.51 3.51 3.50 ± 0.01 3.69 ± 0.59 HF#3 ACt. 2.48 3.68 3.49 3.21 ± 0.65 LFffl ACt. 5.20 5.74 5.59 5.51 ±0.17 LF#2 ACt. 5.25 5.12 5.05 5.14 ±0.28 4.77 ± 0.98 LF#3 ACt. 3.57 3.85 3.56 3.66 ±0.10

ACt = Ct (sample) - Ct (input or internal control). Rep. = replicate. LF = Low-fertility bulls; HF = High-fertility bulls.

Table 10. Mean(± SD) fold change for ASB5 gene expression in HF vs. LF bulls. Mean fold change in Ave. ACt. ± SD AACt(ACtHF- ACtLF) 2'AACt gene expression ± SD HF#1 ACt. 4.35 ± 0.44 -1.16 2.23 HF#2 ACt. 3.50 ± 0.01 HF#3 ACt. 3.21 ± 0.65 -1.64 3.12 2.24 ± 0.87 LF#1 ACt. 5.51 ±0.17 LF#2 ACt. 5.14 ±0.28 -0.45 LF#3 ACt. 3.66 ±0.10 1.37 1IW ' ' — 1 ——•••••• ••••• • ' • —• —• ' 2" (AACT = average ACT (sample of interest) - average ACT (reference sample)) 62

Figure 17. Fluorescent intensity of SYBR green across cycles representing relative concentration of ASB5 transcripts from low- versus high-fertility (LF and HF, respectively) bulls.

qPCR Assay

HF #1-ACTB £ —HF#2-ACTB c 0) HF #3-ACTB S LF #1-ACTB c 3 —LF#2-ACTB k.u 3O LF #3-ACTB ik c0) HF #1-ASB5 HF #2-ASB5 —HF#3-ASB5 LF #1-ASB5

LF #3-ASB5

5 5 15 Cycles

LF = Low-fertility bulls; HF= High-fertility bulls. 63

Figure 18. Melting curves of ASB5 for both low- and high-fertility (LF and HF, respectively) bulls.

Melting Curves ASB5 90 80 ft 70 A 60 •HF#1 50 •HF #2 § 40 •a •HF #3 30 •LF #1 20 •LF #2 10 0 ~ - rs J 1 •LF #3 Tr ^ f ~ U -10 60 65 70 75 80 85 90 95 Temperature (°C) dI/dT= SYBR green fluorescence Intensity vs Temperature. LF = Low-fertility bulls; HF= High-fertility bulls. 64

Furthermore, there was a 1 to 2 ACt difference between LF and HF, which corresponded to a 2-4 fold difference in expression of ASB5 (depending on the sample).

Efficiencies for doubling with each cycle seemed acceptable (100 +/- 10%; Figure 21).

Figure 19. Target titration for ASB5 to validate the ACt difference per cycle.

Target Titration 24 • ACTB 23 V = -j.J48Sy + 27.603 • PGK1 R2 = 0.9916 AASB5 22

21 y = -3.6541X + 26.71 20 k1 = u.yy/y

19

18 y = -3.1459X + 23. 0.9966 17 R* =

16

15 1.5 2 2.5 log(ng template)

ACTB = P Actin; PGK1 = phosphoglycerate kinase; ASB5 = ankyrin repeat-containing proteins with a SOCS box. Ct (threshold cycle): threshold cycle reflects the cycle number at which the fluorescence generated within a reaction crosses the threshold. The ACTB, PGK1 and ASB5 template were serially diluted in half (240, 120,60, and 30 ng;y axis) and the mean Ct was obtained (x axis). Therefore, according to the chart any one unit difference in Ct representing the 2-fold changes in cycle. 65

For ADKl, the same procedure as described previously was performed. However, there was no significant difference between LF versus HF bulls in transcript levels.

Furthermore, there was wide variation in transcript abundance among bulls within each of the two fertility groups (Figures 20 and 21).

Figure 20. Expression of ADKl in LF and HF bulls.

ADKl qPCR

4.5 4 3.5 3

8" I Replicate 1 2 I Replicate 2 1.5 • Replicate 3 1 I • J 0.5 1 • 1IBB 0 1 • 11 • • HF#1 HF #2 HF #3 LF #1 LF #2 LF #3 Sample

ACt = Ct (sample) - Ct(input or internal control). LF = Low-fertility bulls; HF = High- fertility bulls. LF = Low-fertility bulls; HF= High-fertility bulls. 66

Figure 21. Mean transcript abundance (ACt) of ADKl between low- versus high- fertility bulls.

ADKl qPCR

4.50

4.00

3.50

3.00

2.50 C TJ 2.00 I Group Average 1.50

1.00

0.50

0.00 1 1 HF LF Sample

ACt = Ct (sample) - Ct(input or internal control). LF = Low-fertility bulls; HF = High- fertility bulls. LF = Low-fertility bulls; HF= High-fertility bulls. 67

3.3.2 ASB5 protein expression in testes:

Western blotting experiments with anti ASB 5 (ProSci Inc., Poway, CA, USA) on protein extracts from testis and sperm demonstrated a protein band at 50 kDa. A protein band with similar molecular mass was also present in the positive control (Figure

22).

Figure 22. Immunoblotting of ASB5 antibody against total testicular protein from both LF and HF bulls, with expression of ASB5 proteins.

HF#1 HF#2 HF#3 LF#1 JLF#2 LF#3 SeSJC9& Co*fc+

Moreover, ASB5 protein was also expressed in sperm extracted total protein. LF = Low- fertility bulls; HF= High-fertility bulls. 3.4 Proteomics

3.4.1 Sperm protein profile

Two-dimensional gel electrophoresis, using frozen-thawed sperm samples from both LF and HF bulls, resolved and detected proteins along the entire pH and molecular weight range of the gel (Figure 23). There were 326 ±12 match-vectors made by

Delta2D, with 516 protein spots detected on the virtual gel image. Of these 516 spots,

103 protein spots met the inclusion criteria. Furthermore, of these 103 protein spots, 31 spots (Figure 23) had a 2-fold or greater relative expression difference considering the

False Detection Rate (FDR) [Wilcoxon Rank Sum Test/ Benjamini-Hochberg] limit of

0.02 with 0 estimation of false positive protein. Among those, 10 spots were detected as highly expressed in HF bulls (Figure 23). Using standard protein gel (Figure 24)

(consisting of 8 different proteins with defined pi and MW), the isoelectric point and molecular weight (described in section 2.4.2.6) of these protein spots were estimated

(Table 11). According to the obtained data after calibration (Figure 25) the DE spots have the range of pi from 5.29 - 7.57 and the MW range from 13 - 80 kDa. 69

Figure 23. Differentially expressed spots (light and dark double lines) on a 2D gel with its pi and MW. 3 E! 10

9 10«®

Dark double lines spots 4,7,8,9, 11,25, 26,28, 29, and 31 were highly expressed in high-fertility bulls. Table 11. Differentially expressed sperm proteins between high- versus low-fertility Holstein bulls. Protein No. Pi Molecular Weight (MW) 1 5.48 60 2 5.66 59 3 5.68 63 4 5.78 58 5 5.96 58 6 5.96 65 7 6.03 60 8 6.15 60 9 6.26 60 10 6.41 60 11 6.55 57 12 6.63 57 13 6.52 60 14 6.47 68 15 6.60 72 16 6.83 68 17 6.92 65 18 7.02 66 19 6.95 68 20 7.01 68 21 6.88 74 22 6.96 74 23 6.95 77 24 6.91 80 25 5.70 44 26 5.75 41 27 7.49 48 28 7.57 50 29 5.29 25 30 7.52 25 31 7.24 13 71

Figure 24. The standard protein gel image used for calibrating 2-D gels from high- and low-fertility bulls.

Glucose*Oxid|s

Glucose Deiytirogenase Lipase

B lactoglobulin Myo2 Myo3

rom

%

Ten standard proteins with known pi and MW were electrophoresced on a 2D gel Myo 1- 3 represents 3 types of myoglobin, each with a distinct pi and MW. 72

Figure 25. Calibrated (with a standard protein gel) fused image of all samples with differentially expressed spots.

Pi 10

116 kDa -

,7.

66.2-

45-

35.

25-

lactoglobulin

h • 18.4- • 73

Chapter Four: DISCUSSION

Elite bulls in commercial AI centers often differ in their fertility, despite meeting minimum standards for semen quality. In the present study, 10 mature Holstein bulls producing satisfactory semen (based on standard criteria), but with wide variations in fertility, were studied. Testicular physical characteristics, and characteristics of sperm motion and viability post-thaw and after swim-up, were used to identify a set of physical and sperm characteristics that were predictive of fertility. It is noteworthy that no published reports exploring associations among testicular physical characteristics, post- thaw sperm characteristics, and fertility were found.

In the present study, the fertility potential of the bulls was evaluated according to the

NRR which is the only available measure of fertility for dairy bulls. Non return rate is defined as the proportion of cows that is not subsequently re-bred within the specific period of the time after an insemination90. However, if it is not adjusted can be biased by environmental factors such as herd, year, month of insemination, age of cow at insemination, technician and genetic group or breed of service sire as well as semen price79. Misidentification of cow at subsequent service, inaccurate heating detection and recording also are those factors which are not related to fertility but may affect non return rate90. However, if all of these factors can be quantified (adjusted NRR) or be random,

NRR may be considered a reliable indicator of fertility in dairy bulls90. It is also important to be aware of that efficiency of the NRR system is dependent of the accuracy of the data collection.

In this study, testicular physical characteristics were not significantly different between the 2 groups of bulls. However, there were significant differences between 74 groups for sperm motion characteristics in frozen-thawed semen, as well as viability end points at post-thaw and after swim-up. Furthermore, these were significantly correlated with field fertility. Based on motion characteristics, sperm from HF bulls appeared to be in transition to hyperactivated motility, whereas those from LF bulls were in a progressive forward type of motility. Moreover, concentration of sperm post swim-up

(expressed as a percentage of viable sperm present in the post-thaw semen) was higher in

HF versus LF bulls and associated with NRR; this is the first report regarding the association between NRR and the proportion of moribund sperm and motion patterns in frozen-thawed sperm.

Testicular width was significantly lower for LF vs HF bulls (77.3 vs 81.8 mm).

Despite numerical differences in SC (37.3 vs 39.8 cm), this difference was not significant. Testis size is important, as bulls with larger testes produce more sperm, and in general, better quality sperm7. However, since testicular width and scrotal circumference measurements were only approximately 5.5 and 6.5% larger, respectively, in HF than LF bulls, we inferred that this difference was of limited biological relevance, despite being statistically significant for testicular width.

Ultrasonographic evaluation of testes detected no significant differences between the two groups for echotexture of testicular parenchyma or diameter of the testicular vascular cone (TVC). It was previously reported that ultrasonographic echotexture of the testis was associated with seminiferous tubule area91, sperm production7, and semen quality10 in bulls. Furthermore, thermographic evaluations of scrotal temperature patterns were similar between the two fertility groups. However, since bulls with satisfactory semen quality were used, it is not surprising that testicular physical characteristics were 75 similar among bulls.

In the present study, total and progressive motility were higher in HF bulls and were positively correlated with fertility. However, there is no consensus regarding the association of these end points with fertility. For instance, whereas some studies48,49'92 did not detect a significant correlation between total or progressive motility and fertility, others reported a significant correlation between these end points and fertility in several species (cattle19'33'93; swine29; and horses94). Therefore, based on these apparent discrepancies, we inferred that there may be submicroscopic differences in sperm motion characteristics. In that regard, when additional motion characteristics of sperm from LF and HF bulls were analyzed after sperm were thawed, ALH was significantly lower in LF vs HF bulls. Perhaps sperm from HF bulls had higher vigor just after thawing in comparison with those from LF bulls. Consistent with these results, there was a significantly lower percentage of hyperactivated sperm in LF bulls. In agreement with higher percentage of progressive motility in HF bulls we found the higher percentage of viable sperm at both post-thaw and post-swim up as well as higher sperm recovery at post- swim up in HF bulls, indicating the higher quality of sperm specifically in terms of sperm plasma membrane integrity in HF bull. In that regard, Anzar et al., 2002 reported that the percentage of necrotic or viable sperm in fresh semen was significantly related to bull fertility, indicating the higher quality of sperm in HF bulls vs LF bulls95.

Three types of sperm motility patterns have been described96: 1) forward progressive motility; 2) transition phase to hyperactivated motility; and 3) hyperactivated motility. Based on these criteria, post-thaw sperm from HF bulls apparently represented a

"transition phase" from forward progressive to hyperactivated motility. Post-thaw sperm 76 from LF bulls had a lower ALH and numerically higher linear motility representing a

"forward progressive" motility pattern, which drives the sperm in a more-or-less straight line35,96. 'Transition phase" is a motility pattern usually exhibited by physiologically normal sperm that are in progress to hyperactivation, characterized by higher VCL and increased ALH, combined with a lower LIN and WOB values96. In this study, post-thaw

ALH was significantly higher in HF bulls (reflected by high-amplitude flagellar movement) with numerically lower LIN and higher VCL values, compared to LF bulls

(Figure 4). Consistent with these results, a significantly higher percentage of sperm were hyperactivated in HF versus LF bulls at post-thaw and these end points were positively correlated with fertility. These differences in motility between HF and LF bulls may reflect structural (plasma membrane) and or functional differences in sperm between these bulls52'97.

It is well documented that the female genital tract is strongly selective against morphologically abnormal sperm, which reduces the number of sperm reaching the site of fertilization QO. Moreover, cervical mucus plays a critical role in selecting motile, morphologically normal sperm with greater nuclear stability99. Hyaluronic acid (HA) has similar molecular weight, structure and viscosity to the constituent glycoproteins of cervical mucus54 and has been used in swim-up preparations to create a barrier between post-thaw semen and the post-swim up medium55'82. This has provided an opportunity to study the interaction of sperm with cervical mucus in a laboratory setting, as well as separating motile sperm from dead and nonviable sperm present in frozen-thawed semen50. Therefore, motion characteristics of post-swim up sperm may be more representative of sperm that populate the female reproductive tract after insemination. 77

Frozen-thawed sperm from HF bulls was apparently more efficient in undergoing hyperactivation compared to LF bulls; in vivo, this could enhance their ability to cross the barriers of the female reproductive tract and reach the site of fertilization. To test this hypothesis, post-thaw sperm from LF and HF bulls were subjected to a swim-up procedure that provided a barrier (Na-hyaloronate) between post-thaw semen and the swim-up medium, and the concentration of post swim-up sperm and their motion characteristics were evaluated under capacitating conditions. Interestingly, ALH in LF bulls was significantly lower than that of HF bulls, whereas LIN, STR, WOB were significantly higher, consistent with a reduced ability of sperm from LF bulls to undergo hyperactivated motility under capacitating conditions, in agreement with motion characteristics of frozen-thawed sperm.

The concentration of sperm recovered after swim-up (expressed as a percentage of viable sperm present in the post-thaw sample) and the proportion of viable sperm post- swim-up were significantly different between HF and LF bulls, and were positively correlated with fertility. Correlations between fertility and sperm concentration after swim-up have been reported49'100. However, the experimental approach used in the present study provided an opportunity to normalize sperm concentration post swim-up.

Based on low recovery of sperm in the post swim-up preparations from LF bulls, the ability of viable sperm from LF bulls to pass through sodium hyaluronate may have been inherently compromised, which provided indirect evidence for their reduced ability to pass through the barriers of the reproductive tract and populate the site of fertilization.

Based on these results and observed differences in sperm kinematic parameters, it was postulated that sperm from LF bulls had a reduced ability to undergo hyperactivation 78 under appropriate physiological conditions, which affected their ability to pass through the female reproductive tract, and interact with oocytes, contributing to reduced fertility.

In that regard, sperm with increased mean ALH values and hyperactivated motility were more likely to be fertile24,38'101.

It has been reported that procedures associated with cryopreservation (dilution, chilling, freezing, and thawing) induce capacitation-like changes (cryo-capacitation) in bovine sperm102, and that the proportion of non-capacitated sperm present in frozen- thawed semen was positively correlated with fertility82. The observation that post-thaw sperm from HF bulls were in transition to hyperactivated motility may be a different i phenomenon than cryocapacitation . Additionally, it is crucial to take into consideration that hyperactivation is not a suitable end point for accurately estimating the percentage of capacitated cells104, and that capacitation and hyperactivation should be considered independent, as they are regulated by different pathways, although hyperactivation usually occurs during capacitation105. Moreover, it is noteworthy that sperm from HF and

LF bulls were challenged to undergo hyperactivation by providing appropriate culture conditions that were conducive for hyperactivation and capacitation.

Perhaps the reduced ability of sperm to undergo hyperactivated motility in LF bulls after swim-up compared to HF bulls was due to an inherent deficiency of sperm at structural and/or functional levels. Flow cytometry based viability assays demonstrated that frozen-thawed semen from HF bulls contained a higher proportion of viable sperm

(with an intact plasma membrane) compared to LF bulls. Furthermore, there was a significant positive correlation between viability and NRR. A subpopulation of sperm stained with both SYBR-14 and PI were observed as reported previously42"45'106"108. These 79 sperm were described as "moribund sperm", a transition stage from live to dead sperm42,43'93'95. The proportion of moribund sperm in a given semen sample appeared to remain constant during incubation at room temperature93, although the proportion of these sperm appeared to vary among bulls95. However, the biological importance of the proportion of moribund sperm cells and the conversion rate of live to moribund sperm remain unknown. In the present study, there was a significantly higher percentage of moribund sperm in LF bulls compared to HF bulls, and a significantly lower percentage of sperm underwent conversion to moribund sperm in HF bulls. Furthermore, the proportion of moribund sperm (expressed as a percentage of total live sperm) was negatively correlated with fertility. The biological relevance of this observation is that viable sperm from LF bulls were being converted to dead sperm at a faster rate, presumably reducing the availability of live sperm in the female reproductive tract.

The rate of conversion of live to moribund sperm in a given semen sample may be an indicator of fertility. Although moribund sperm already reported in FLC analyzed semen in bull42"45'106"108 but this was apparently the first report regarding the biological importance of moribund cells in the inseminate. Furthermore, since many sperm were immotile in the post swim-up sample, viability of post swim-up sperm was evaluated; it was significantly higher in HF compared to LF bulls. Although sperm from LF bulls that passed through the sodium hyaluronate were alive, perhaps at least some had compromised viability and subsequently died soon after they reached the swim-up medium.

Collectively, it seemed that sperm from LF and HF bulls differed at molecular levels, perhaps reflecting difference between these two groups of bulls during 80 spermatogenesis and spermiogenesis. Since these steps also can be evaluated at the level of transcriptomics and proteomics.

In this study, after testicular DNA microarray analysis, only the ASB5 gene was expressed at a higher level in common among HF bulls compared to LF bulls, which was also confirmed by the q-RT PCR. The ASB (Ankyrin repeat containing SOCS Box protein) proteins belong to the SOCS box proteins (suppressors of cytokine signaling), which in addition to the SOCS box, contain ankyrin motifs. Other members of the family comprise a SH2 domain (SOCS proteins), WD-40 repeats (wsb proteins), a SPRY domain (ssb proteins) or a GTPase domain (RAR-like proteins) instead of the ankyrin repeats109. Moreover, SOCS proteins are implicated in negative regulation of cytokine signaling110.

It is noteworthy that ASB5 is a member of the ASB family, which is characterized by a non-conserved N-terminus, a various number of ankyrin repeats—between 3 (asbl4) and 15 (asb2)—as well as a C-terminal SOCS box. The ASB5 amino-acid sequence revealed a putative transmembrane domain (amino acids 21-43), six ankyrin repeats

(amino acids 72-269), and the SOCS box at the C-terminus of the protein (amino acids

290-329)111.

According to the NCBI Gene database, the ASB 5 gene is conserved in the human, chimpanzee, dog, mouse, rat, chicken, and zebrafish. Furthermore, comparison of asb5 amino-acid sequences in the cow, rabbit, human, and mouse revealed >96% identity, indicating that ASB5 is highly conserved during evolution. In cattle, the ASB5 gene is located in Chromosome 27, encoding a protein containing 329 aa.

According to the NCBI database, the SOCS box is found in the C-terminal region 81 of CIS/SOCS family proteins (in combination with a SH2 domain), ASBs (ankyrin repeat-containing proteins with a SOCS box), SSBs (SPRY domain-containing proteins with a SOCS box), and WSBs (WD40 repeat-containing proteins with a SOCS box), as well as other miscellaneous proteins. The function of the SOCS box is recruitment of the ubiquitin-transferase system. In that regard, the SOCS box interacts with Elongins B and

C, Cullin-5 or Cullin-2, Rbx-1, and E2. Therefore, SOCS-box-containing proteins probably function as E3 ubiquitin ligases and mediate degradation of proteins associated through their N-terminal regions. In addition, it has been stated that the complexes of

SOCS proteins and their bound signaling molecules are targeted for the degradation pathway via interaction with elongins B and C112.

Ankyrin motifs were identified in more than 400 proteins, exerting various functions such as regulation of transcription, organization of the cytoskeleton, or control of developmental processes. On a cellular level, they mediate protein-protein interactions113.

Based on immunoblotting studies using anti-ASB5, expression of ASB5 protein was detected in bovine testis and ejaculated sperm. This is apparently the first report of this protein in bovine testis and ejaculated sperm. On the western blot a 50 kD band was observed in all samples as well as + control. However, the expected molecular mass for

ASB5 (based on its 328 aa composition) is 36 kD, not 50 kD. In the positive control

(human fetal muscle tissue lysate) the 36 kD band as well as the 50 kD band of unknown origin were detected. The 36 kD band in the positive control has the expected MW; at present we do not know if the 50 kD band in the samples as well as the + control is real and could be the result of a post translational modification process114 of ASB5, which 82 needs to be investigated.

The exact functions of individual ASB proteins are not well characterized and apparently no association of ASB5 proteins with fertility has been described. However,

Asbl knockout mice testis had reduced spermatogenesis, with less complete filling of seminiferous tubules115. Recently, it was speculated that ASB5 is associated with arteriogenesis111. It has been suggested that ASB5 contacts other signaling molecules via its ankyrin repeats. Furthermore, since ASB5 does not contain the SH2 domain necessary for protein-protein interaction, it is unlikely that substrates of ASB5 are members of the

JAK/STAT pathway. In that regard, this signaling pathway transmits information from chemical signals outside the cell, through the cell membrane, and into gene promoters on the DNA in the cell nucleus, which causes DNA transcription and activity in the cell111.

Overall, it appeared that LF and HF bulls likely differed at the level of spermatogenesis.

Furthermore, regarding the potential role of ASB5 in bull fertility and spermatogenesis, further studies including immunolocalization and production of knockout mice should also be done.

A sequence of biochemical events modify sperm during their transition in the epididymis, which is called the sperm maturation process. Membrane phospholipid composition and in cholesterol/phospholipid ratio, increases in disulfide bonds and in net surface negative charge, relocalization of surface antigens, and modification, elimination and addition of surface proteins are the major biochemical events and modifications undergone by maturing sperm116. To date, several proteins have been reported to be either eliminated from or added to sperm during epididymal transit. However, the these processes has not been fully elucidated. Both P26h [hamster], a member of the short- 83 chain dehydrogenase/reductase superfamily and P25b [bull] are transferred to the sperm head during epididymal transit117. Angiotensin I-converting enzyme (ACE), is one of the proteins that are gradually released from the sperm surface during epididymal maturation

[ram]117 by a specific proteolytic mechanism. Protein D form of epididymal secreted protein CRISP 1 (a cysteine-rich secretory Protein) associates to the rat sperm head,

MO whereas protein E form of CRISP 1 binds the rat sperm tail . Moreover, some proteins are delivered from epididymal cells to sperm through epididymosomes which play a major role in the acquisition of new proteins by maturing sperm. Epididymosomes are small membranous vesicles which are secreted in an apocrine manner into the intraluminal compartment of the epididymis116. Some of the reported proteins which are delivered by epididymosomes are; HSPA5 and "heat shock protein 90, beta (Grp94), member 1" (HSP90B1) protein disulfide isomerase associated 3 (PDIA3) and

Apolipoprotein A-I (APOA1)117. In addition, some sperm membrane proteins structurally undergo post-translational modification during epididymal transit; for example, proacrosin undergoes an alteration in oligosaccharide side-chains in guinea pig119 and

ADAM2 relocalizes from the whole sperm head to the posterior head120. Moreover, it must also be considered that, at ejaculation, sperm are mixed with the seminal plasma components and some proteins attach to them. For instance, in bull, the seminal vesicles secrete a family of proteins called bovine seminalplasma or BSP proteins which binds to the sperm membrane 1 "71 . Therefore, the ejaculated sperm protein profile representing many changes and modification of sperm during their maturation and ejaculation processes.

To evaluate the difference at proteomics level, 2D gel electrophoresis of sperm 84 plasma membrane proteins was done. This yielded 31 spots with a 2-fold or greater relative expression difference between LF and HF bulls sperm samples, indicating the difference at proteomics level between these 2 groups of bulls. In this study, 3 ejaculates per bull and 5 bulls in each group were used, which provided reasonable replication to assess variation among ejaculates and bulls. Previous studies detected differences at proteomics level related to fertility potential in bulls. For instance, Peddinti et al. recently identified 125 putative biomarkers of fertility in bulls66. The reason for this huge difference in terms of the number of the candidate is that they applied differential detergent fractionation multidimensional protein identification technology (DDF-Mud

PIT), a much more advanced and accurate technique compared to the 2D gel electrophoresis used in this study. In that study, sperm from high-fertility bulls had higher expression of proteins involved in: energy metabolism, cell communication, spermatogenesis, and cell motility. Moreover, they hypothesized that in low fertility sperm, DNA integrity may be compromised. Since we did not perform mass spectrometry to identify differentially expressed sperm proteins, there is not enough information to compare our finding with this study.

In a recent study using 2D gel electrophoresis, only 9 protein spots significantly differed between LF and HF bulls122. The use of a specific fraction of sperm plasma membrane proteins (extracted with Triton X-100) in that study may have contributed to much fewer candidate protein spots than in our study (which included a total sperm plasma membrane protein extract). In the other study, T-complex protein 1 subunits e and

0 (CCT5 and CCT8), 2 isoforms of epididymal sperm-binding protein E12 (ELSPBP1), proteasome subunit a type-6, and binder of sperm 1 (BSP1) were more expressed in the 85

LF group than in the HF group. Conversely, adenylate kinase isoenzyme 1 (AK1) and phosphatidylethanolamine-binding protein 1 (PEBP1) were more expressed in the HF group than in the LF group

According to the previous results, and considering the molecular mass and pi of proteins identified in that study and the present study, it seemed that some of the candidate spots in the present study had similar MW and pi to the previously identified proteins. For instance, protein No. 1 in the present study had MW 60 kDAand pi 5.48, which was very similar to T-complex protein 1 subunit e (CCT5; MW of 60 daltons and pi 5.6). Furthermore, spot protein No. 2 in the present study had MW 59 kDa and pi 5.66, which seemed similar to T-complex protein 1 subunit 0 (CCT8) with MW 59 daltons and pi 5.4. To identify other spots, mass spectrophotometry must be performed on selected spots, with subsequent confirmation by western blotting.

In summary, testicular physical characteristics did not account for differences in fertility among bulls producing semen that met current quality standards. However, differences between LF and HF bulls in the proportions of viable and moribund sperm and rate of conversion of viable sperm to moribund state have potential applications in fertility predictions. In addition, characteristics of sperm recovered through a sodium hyaluronate swim up medium may better reflect the ability of sperm to undergo hyperactivation and reach the site of fertilization, and thus be indicative of in vivo fertility. There were significant differences between LF and HF bulls at genomic level of testicular tissue, most likely due to differences in spermatogenesis and expression of sperm plasma membrane proteins. Further studies are required to elucidate the molecular basis of compromised viability of sperm from LF bulls, including differences in the 86 sperm plasma membrane protein profile (mass spectrometry) and testicular gene expression (creating KO mice etc.). 87

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