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We describe a systems biology approach for the genetic dissection of complex traits based on applying gene network theory to the results from genome-wide associations. The associations of singlenucleotide polymorphisms (SNP) that were individually associated with a primary phenotype of interest, age at puberty in our study, were explored across 22 related traits. Genomic regions were surveyed for genes harboring the selected SNP. As a result, an association weight matrix (AWM) was constructed with as many rows as genes and as many columns as traits. Each {i, j} cell value in the AWMcorresponds to the z-score normalizedadditive effect of the ith gene (via its neighboringSNP)onthe jth trait. Columnwise, theAWM recovered the genetic correlations estimated via pedigree-based restricted maximum-likelihood methods. Rowwise, a combination of hierarchical clustering, gene network, and pathway analyses identified genetic drivers that would have been missed by standard genome-wide association studies. Finally, the promoter regions of the AWM-predicted targets of three key transcription factors (TFs), estrogen-related receptor γ (ESRRG), Pal3 motif, bound by a PPAR-γ homodimer, IR3 sites (PPARG), and Prophet of Pit 1, PROP paired-like homeobox 1 (PROP1), were surveyed to identify binding sites corresponding to those TFs. Applied to our case, the AWM results recapitulate the known biology of puberty, captured experimentally validated binding sites, and identified candidate genes.

Harsh tropical environments impose serious challenges to poorly adapted species. In beef cattle, tropical adaptation in the form of temperature and disease resistance, coupled with acclimatization to seasonal and limited forage, comes at a cost to production efficiency. Prominent among these costs is a delayed onset of puberty, a challenging phenotype to manipulate through traditional breeding mechanisms. Recently, system biology approaches, including gene networks, have been applied to the genetic dissection of complex phenotypes. We aimed at developing and studying gene networks underlying cattle puberty. Our starting material comprises the association results of ~50,000 SNP on 22 traits, including age at puberty, and two cattle breed populations: Brahman (n = 843) and Tropical Composite (n = 866). We defined age at puberty as the age at first corpus luteum (AGECL). By capturing the genes harbouring mutations minimally associated (P < 0.05) to AGECL or to a set of traits related with AGECL, we derived a gene network for each breed separately and a third network for the combined dataset. At the intersection of the three networks, we identified candidate genes and pathways that were in common to both breeds. Resulting from these analyses, we identified an enrichment of genes involved in axon guidance, cell adhesion, ErbB signalling, and glutamate activity, pathways that are known to affect pulsatile release of GnRH, which is necessary for the onset of puberty. Furthermore, we employed network connectivity and centrality parameters along with a regulatory impact factor metric to identify the key transcription factors (TF) responsible for the molecular regulation of puberty. As a novel finding, we report five TF (HIVEP3, TOX, EYA1, NCOA2 and ZFHX4) located in the network intersecting both breeds and interacting with other TF forming a regulatory network that harmonises with the recent literature of puberty. Finally, we support our network predictions with evidence derived from gene expression in hypothalamic tissue of adult cows.

Puberty in cattle is regulated by an endocrine axis which includes a complex milieu of neuropeptides in the hypothalamus and pituitary gland. The neuropeptidome of hypothalamic-pituitary tissue of pre- (PRE) and post-pubertal (POST) Bos indicus-influenced heifers was characterized, followed by quantitative analysis of 51 fertility-related neuropeptides in these tissues. Comparison of peptide abundances with gene expression levels allowed assessment of post-transcriptional peptide processing. Based on classical cleavage, 233 mature neuropeptides from 35 precursor proteins were detected in hypothalamus and pituitary gland tissues of three PRE and three POST Brangus heifers. In the pre-pubertal hypothalamus a greater diversity of neuropeptides (30.2%) were identified relative to post-pubertal heifers, while in the pituitary gland ~50 % more neuropeptides were detected in the post-pubertal heifers. Neuro tissues of PRE and POST heifers revealed abundance differences (p < 0.05) in peptides from protein precursors involved in packaging and processing (e.g. the granin family and ProSAAS) or neuron stimulation (PENK, CART, POMC, cerebellins). On its own, the transcriptome data of the precursor genes could not predict the neuropeptide profile in the exact same tissues in several cases. This provides further evidence of the importance of differential processing of the neuropeptide precursors in the pituitary before and after puberty.

The association between sperm morphology characteristics and DNA conformation and integrity is still controversial. In bulls, major morphological sperm abnormalities have been associated with reduced fertility, and morphological assessment is used to provide an indication of potential fertility of the individual. Sperm DNA fragmentation and damage has a negative effect on embryo development and subsequently fertility, with bull spermatozoa generally displaying low levels of DNA damage and tight chromatin. However, sensitive methods for detecting chromatin damage may reveal associations with morphological defects. The objective was to determine whether morphological sperm abnormalities and variables expressing sperm DNA integrity and protamination are correlated in bulls, using the sperm chromatin structure assay (SCSA) and the sperm protamine deficiency assay (SPDA). Electroejaculated samples (n = 1009) from two-year-old tropically adapted bulls were split and fixed and submitted to microscopic sperm morphology assessment, and snap-frozen for sperm nuclear integrity assessments by SPDA and SCSA. For SPDA, the variables were defective (MCB) and deprotaminated (HCB), and for SCSA, the variables were DNA fragmentation index (DFI) and high DNA stainability (HDS). HCB correlated with DFI; sKen 2 = 0.317 and HDS; 0.098, and MCB correlated with DFI; 0.183 (p < 0.001). The percentage of morphological normal spermatozoa was correlated negatively to DFI; sKen 2 = À0.168, MCB; À0.116 and HCB; À0.137 (p < 0.001). HCB and DFI were both positively correlated to head defects, proxi-mal droplets, and spermatogenic immaturity, but not to distal droplets, vacuoles, or diadems. Sperm DNA integrity and protam-ination, using the SCSA and SPDA, respectively, in bulls show associations with morphological parameters, particularly with head shape abnormalities and indicators of spermatogenic immaturity, including proximal droplets. The vacuoles and diadem defects were not correlated with sperm nuclear integrity, and hence, these are likely physiological features that may not directly affect sperm chromatin configuration.

Background: Asian buffaloes (Bubalus bubalis) have an important socioeconomic role. The majority of the population is situated in developing countries. Due to the scarce resources in these countries, very few species-specific biotechnology tools exist and a lot of cattle-derived technologies are applied to buffaloes. However, the application of cattle genomic tools to buffaloes is not straightforward and, as results suggested, despite genome sequences similarity the genetic polymorphisms are different. Results: The first SNP chip genotyping platform designed specifically for buffaloes has recently become available. Herein, a genome-wide association study (GWAS) and gene network analysis carried out in buffaloes is presented. Target phenotypes were six milk production and four reproductive traits. GWAS identified SNP with significant associations and suggested candidate genes that were specific to each trait and also genes with pleiotropic effect, associated to multiple traits. Conclusions: Network predictions of interactions between these candidate genes may guide further molecular analyses in search of disruptive mutations, help select genes for functional experiments and evidence metabolism differences in comparison to cattle. The cattle SNP chip does not offer an optimal coverage of buffalo genome, thereafter the development of new buffalo-specific genetic technologies is warranted. An annotated reference genome would greatly facilitate genetic research, with potential impact to buffalo-based dairy production.

In this chapter we describe the Association Weight Matrix (AWM), a novel procedure to exploit the results from genome-wide association studies (GWAS) and, in combination with network inference algorithms, generate gene networks with regulatory and functional significance. In simple terms, the AWM is a matrix with rows represented by genes and columns represented by phenotypes. Individual {i, j}th elements in the AWM correspond to the association of the SNP in the ith gene to the jth phenotype. While our main objective is to provide a recipe-like tutorial on how to build and use AWM, we also take the opportunity to briefly reason the logic behind each step in the process. To conclude, we discuss the impact on AWM of issues like the number of phenotypes under scrutiny, the density of the SNP chip and the choice of contrast upon which to infer the cause-effect regulatory interactions.

Background: Previous genome-wide association analyses identified QTL regions in the X chromosome for percentage of normal sperm and scrotal circumference in Brahman and Tropical Composite cattle. These traits are important to be studied because they are indicators of male fertility and are correlated with female sexual precocity and reproductive longevity. The aim was to investigate candidate genes in these regions and to identify putative causative mutations that influence these traits. In addition, we tested the identified mutations for female fertility and growth traits. Results: Using a combination of bioinformatics and molecular assay technology, twelve non-synonymous SNPs in eleven genes were genotyped in a cattle population. Three and nine SNPs explained more than 1% of the additive genetic variance for percentage of normal sperm and scrotal circumference, respectively. The SNPs that had a major influence in percentage of normal sperm were mapped to LOC100138021 and TAF7L genes; and in TEX11 and AR genes for scrotal circumference. One SNP in TEX11 was explained ~13% of the additive genetic variance for scrotal circumference at 12 months. The tested SNP were also associated with weight measurements, but not with female fertility traits.

Puberty is a complex physiological event by which animals mature into an adult capable of sexual reproduction. In order to enhance our understanding of the genes and regulatory pathways and networks involved in puberty, we characterized the transcriptome of five reproductive tissues (i.e. hypothalamus, pituitary gland, ovary, uterus, and endometrium) as well as tissues known to be relevant to growth and metabolism needed to achieve puberty (i.e., longissimus dorsi muscle, adipose, and liver). These tissues were collected from pre-and post-pubertal Brangus heifers (3/8 Brahman; Bos indicus x 5/8 Angus; Bos taurus) derived from a population of cattle used to identify quantitative trait loci associated with fertility traits (i.e., age of first observed corpus luteum (ACL), first service conception (FSC), and heifer pregnancy (HPG)). In order to exploit the power of complementary omics analyses, pre-and post-puberty co-expression gene networks were constructed by combining the results from genome-wide association studies (GWAS), RNA-Seq, and bovine transcription factors. Eight tissues among pre-pubertal and post-pubertal Brangus heifers revealed 1,515 differentially expressed and 943 tissue-specific genes within the 17,832 genes confirmed by RNA-Seq analysis. The hypothalamus experienced the most notable up-regulation of genes via puberty (i.e., 204 out of 275 genes). Combining the results of GWAS and RNA-Seq, we identified 25 loci containing a single nucleotide polymorphism (SNP) associated with ACL, FSC, and (or) HPG. Seventeen of these SNP were within a gene and 13 of the genes were expressed in uterus or endometrium. Multi-tissue omics analyses revealed 2,450 co-expressed genes relative to puberty. The pre-pubertal network had 372,861 connections whereas the post-pubertal network had 328,357 connections. A sub-network from this process revealed key transcriptional regulators (i.e., PITX2, FOXA1, DACH2, PROP1, SIX6, etc.). Results from these multi-tissue omics analyses improve understanding of the number of genes and their complex interactions for puberty in cattle. This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Data Availability: The authors confirm that all data underlying the findings are fully available without restriction. The number of unique reads and RPKM of each gene within each of the 61 samples are publically available at the Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/; accession number GSE55435).