Recipient Organization
PENNSYLVANIA STATE UNIVERSITY
408 Old Main
UNIVERSITY PARK,PA 16802-1505
Performing Department
(N/A)
Non Technical Summary
While the current Cattle FAANG project excels in comprehensively understanding genomic regulatory elements in a wide-ranging set of adult and fetal cattle tissues, there is a significant knowledge gap regarding the regulatory dynamics of development and differentiation across the cattle lifecycle in each tissue, which determines economic traits in animal health and production. This study aims to fill this gap, focusing on male reproduction, which is imperative as the cattle industry relies on artificial insemination (AI) practices. The project comprises three specific aims: 1) Determine the temporal transcriptome dynamics and gene regulatory networks during bovine testis development, 2) Determine germ cell-specific transcriptome dynamics and gene regulatory networks in different germ cells during spermatogenesis, and 3) Determine the testis-biased genes and identify e/sQTL, as well as transcriptome-wide association studies (TWAS) of male fertility traits. To achieve these aims, we will annotate and integrate transcriptional profiles and chromatin states at a whole-genome level across the four developmental stages of testes and five different types of germ cells during spermatogenesis. Additionally, single-cell transcriptomics and chromatin states will provide insights into the regulatory dynamics of bovine germ cell differentiation events. Lastly, we will identify bull fertility-associated genomic variants within the annotated regulatory elements in the testis. TWAS with eVariants and colocalization of eQTLs and GWAS loci will enhance our ability to detect candidate causal genes for male fertility traits. This project is highly innovative, crucial, and significant for completing the bovine genome annotation and understanding the transcriptomics underlying testis development and spermatogenesis in ruminants.
Animal Health Component
70%
Research Effort Categories
Basic
30%
Applied
70%
Developmental
0%
Goals / Objectives
This project comprises three specific aims: 1) Determine the temporal transcriptome dynamics and gene regulatory networks during bovine testis development, 2) Determine germ cell-specific transcriptome dynamics and gene regulatory networks in different germ cells during spermatogenesis, and 3) Determine the testis-biased genes and identify cis-e/sQTL, as well as transcriptome-wide association studies (TWAS) of male fertility traits. To achieve these aims, we will annotate and integrate transcriptional profiles and chromatin states at a whole-genome level across the four developmental stages of testes and five different types of germ cells during spermatogenesis. Additionally, single-cell transcriptomics and chromatin states will provide insights into the regulatory dynamics of bovine germ cell differentiation events. Lastly, we will identify bull fertility-associated genomic variants within the annotated regulatory elements in the testis. TWAS with eVariants and colocalization of cis-eQTLs and GWAS loci will enhance our ability to detect candidate causal genes for male fertility traits.
Project Methods
We will take the following research approaches/methods:1. Conduct a time-course testis transcriptome analysis at four developmental stages of testes: fetal gonads, prepubertal testes, pubertal testes, and mature testes. Sequence data from RNA-seq, small RNA-seq, ATAC-seq, and ChIP-seq assays will be integrated for functional annotation and gene regulatory network construction.Two sets of bovine testis tissues will be included in this project. The first set is used in our pilot study, which includes 3 fetal gonads, 4 prepubertal, 4 pubertal, and 4 mature testes. These testis samples are from Hereford bulls and will be used for functional annotation, as Herefordwas used for the bovine reference genome sequenceand the cattle FAANG project. Non-testis tissues from the two Hereford bulls of cattle FAANG will be used as controls to identify testis-biased genes.The second set of 80 prepubertal testes will be collected from Angus or crossbred young bull calves during castration at the Penn State Beef Center or local farms close to the Penn State University. These samples will be grouped according to age: newborn to 1 month (n≥25), 1-3 months (n≥25), and >3 months (n≥25), corresponding to the emergence of gonocytes, SSCs, and meiotic spermatocytes during early testis development. Additionally, transcriptome and genotypic data from 118 mature testes are available for this project, allowing us to conduct a comparative analysis and identify testis developmental stage-specific e/sQTL.RNA-seq, small RNA-seq, ATAC-seq and ChIP-seq of 7 histone marks(H3K27ac, H3K4me1, H3K4me3, H3K9me3, H3K27me3, H3K36me1, and CTCF)will be performed.After removing adapter sequences, low-quality bases, and poly-A tails from the RNA sequence, the clean reads will be aligned to the ARS-UCD1.2 cattle reference genome for gene annotation using parameters designed in the cattle FAANG project and the standardized FAANG bioinformatics pipeline. ChIP-seq and ATAC-seq peaks will be called by Model-based Analysis of ChIP-Seq (MACS2). We then will use ChromeHMM to predict the genome-wide chromatin states in each sample.A comprehensive catalog of dataset from this project including chromatin states, regulatory elements and transcriptome of testis developmental stage will be deposited to the EBI FAANG database, and UCSC Track Hubs for easy visualization of ATAC, ChIP, and RNA/sRNA-seq integration in the genome region of interest. To annotate the transcriptomic regulation dynamics, we will identify transcription factors (TFs) binding to the open chromatin regions using chromVAR program.2.Examine the dynamics of germ cell transcriptome by RNA-seq anddeterminechromatin landscapes of germ cells byATAC-seq and ChIP-seq.Testis tissues will be collected from mature dairy A.I. bulls (n=3) with normal-to-high fertility provided by Select Sires or beef bulls (n=3) from USDA-ARS with genotype and phenotype records. The collagenase digestion will be used to obtain single cell suspensions. These suspensions will be used for fluorescence-activated cell sorting (FACS) to enrich Type A spermatogonia (SG), pachytene spermatocytes (PS), round spermatids (RS), and condensing spermatids (CS),with Leydig cells (LC) and Sertoli cells (SC) as controls. In addition, testicular sperm (TS) will also be collected from the fresh testes.Two approaches will be employed for generating coding and non-coding sequencing data. Approach A involves routine RNA-seq and small RNA-seq on five different stages of germ cells (n=3) (SG, PS, RS, CS, and TS) and two types of non-germ cells (LC and SC). Approach B utilizes single cell genomics by pooling germ cells from three mature bulls for scRNA-seq using the 10X Genomics platform.A WGCNA gene network for each type of germ cells will be built and compared.Once we have the data matrices from scRNA-seq and scATAC-seq, we will integrate them using the Seurat v3 R package, enabling joint visualization of scRNA-seq data with classified scATAC-seq cells and peak-to-gene links,3.Identify genome-wide testis-biased genes/transcripts. We will compare all annotated transcripts, including coding and non-coding, obtained from different developmental stages of testes and different types of germ and non-germ cells to those transcripts obtained from non-testis tissues in the cattle FAANG project to identify testis-biased genes/transcripts.4.Identify allelic variants associated with testis-expressed genes and cis-e/sQTL. Weaim to analyze a large size of testis samples from ~500 bulls.We will take the following steps to identify cis-e/sQTLs:a.RNA-seq alignment tothe ARS-UCD1.2 cattle reference genome.b. Expression and splicing quantification: We will conduct a meta-analysis for 500 testis samples from this point forward. Gene expression values, measured by transcripts per million (TPM), will be inferred using featureCounts. For eQTL mapping, we will first use TMM to normalize read counts between samples, followed by the inverse normal transformation for each gene across samples. To identify splicing events, we will use Leafcutter to calculate 'percent spliced-in' (PSI) values for excised-intron clusters.c. Genotyping and imputation: To identify allelic variants associated with testis-expressed genes and alternative splicing events, we will genotype all animals whose testis are used in RNA-seq andwill use an imputation approach being applied to the CattleGTEx project.After filtering with a MAF ≤ 0.05 and dosage R-squared (DR2) ≤ 0.8, samples that are genotyped and imputed successfully will be used for subsequent e/sQTL mapping.c. cis-e/sQTL mapping: We will employ the methods detailed in Mapel et al., (2023) and Liu et al. (2022) to detect cis-eQTL. Additionally, we will also conduct a meta-analysis to integrate the e/sQTL results of the developmental stages using the METAL tool.5.TWAS and colocalization of e/sQTL and GWAS loci.We will conduct TWAS based on reproductive phenotypes fromthe following populations:1) ≥500 genotyped Holstein AI bulls with sperm production traits from Select Sires.2) ≥ 300 genotyped (or sequenced) beef bulls with semen quality and sperm fertility traitsfrom USDA-ARS, Miles City, MT.3) Eighty-five sequenced AI bulls with suboptimal fertility, and detailed sperm phenotypes measured by image-based flow cytometry for the morphological defects.4) GWAS results from 1800 Angus bulls characterized by 9 sperm fertility traits, including semen volume, sperm concentration, number, initial motility, post-thaw motility, % of normal spermatozoa, and primary and secondary abnormalities.5) e/sQTL results from 118 mature bulls, along with GWAS results, pertaining to a fertility trait measured by sire insemination success in 3,736 bulls.6)over 5200 QTLs for sperm quality and male fertility-related traitsreported in the Cattle QTLdb.WewillintegrateQTL and molQTL throughTWAS analysis,To explore the molecular mechanisms of action behinds molQTL, we will use the Genomic Association Tester (GAT) to test whether e/sQTL are significantly enriched in certain chromatin states generated in Aim 1&2,such as promoters and enhancers. We will consider enrichments with FDR < 0.05 as significant.To validate the top few eGenes and eVariants, we will perform the following analyses: i) Genotype-expression correlation;ii) Allelic imbalance analysis; and iii)Cell and tissue-specificity expression.6. Communicateresults to appropriate audiences and the public.To harness the collective strength of the community and facilitate widespread access to information, all data, including raw sequence and processed datasets, will be uploaded to the cattle FAANG, NRSP8 (https://www.animalgenome.org/) and CattleGTEx databases (http://cgtex.roslin.ed.ac.uk/).