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ABSTRACT:
PROVIDER: PRJNA935708 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Bos taurus, Heifers, (Post diet supplement)Transcriptome
| PRJNA935321 | ENA
Project description:The objective was to study the transcriptomic changes in adipose tissue in the early stages of lactation, specifically in Bos Taurus, Holstein dairy cattle as a function of milk production and genetic merit. Chip quality backgrounds averaged below 50 units, and 3'/5' bias on control genes < 2.0. Correlations among replicates were > 0.85. The design was a simple paired sampling, with time (30 d prepartum and 14 d postpartum as the sampling times. There was no dietary manipulation. Animals were all first calving Holstein heifers, all raised on the same farm on the same diet
2010-05-27 | E-GEOD-21535 | biostudies-arrayexpress
Project description:Puberty is a complex physiological event measured by various indicator traits in genetic improvement programs of beef cattle; thus, developing a more complete understanding of the genes and regulatory pathways and networks involved in puberty will provide knowledge to help improve genetic selection strategies. Herein, 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 for cattle to achieve puberty (i.e., longissimus dorsi muscle, fat, and liver). These tissues were collected from pre (PRE)- and post (POST)-pubertal Brangus (3/8 Brahman; Bos indicus x 5/8 Angus; Bos taurus) heifers derived from a population of cattle used to identify QTL associated with fertility traits. 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 RNA-Seq, GWAS, and bovine transcription factors. RNA-Seq of 8 tissues among PRE and POST Brangus heifers revealed 1515 differentiallyexpressed and 943 tissue-specific genes within the 17,832 genes confirmed by metrics of RNA-Seq analysis. Combining the results from RNA-Seq and GWAS indentified a total of 25 QTL associated to heifer fertility. The hypothalamus experienced the most notable up-regulation of genes via puberty. Complementary omics procedures revealed 2,450 co-expressed genes across the 8 tissues relative to puberty. The PRE network had 372,861 connections whereas the POST network had 328,357 connections. A sub-network from this process revealed key transcriptional regulators (i.e., PITX2, FOXA1, TSG1D1, DACH2, LHX4, PROP1 and SIX6). Results from multiples sources of omics data will facilitate the design of breeding strategies to improve fertility in Bos indicus-influenced composite cattle. Sixty-one samples from PRE and POST pubertal composite beef heifers were analyzed with RNA-Seq. The transcriptome of five reproductive tissues (i.e. hypothalamus, pituitary gland, ovary, uterus, and endometrium) as well as tissues known to be relevant to metabolism andbody morphometrics needed for cattle to achieve puberty (i.e.,) was characterized. These tissues were collected from pre (PRE)- and post (POST)-pubertal Brangus (3/8 Brahman x 5/8 Angus) heifers derived from a population of cattle used to identify QTL associated with fertility. Total RNA was purified using a Trizol protocol (Invitrogen, Carlsbad, CA). Sequencing libraries were made using TruSeq RNA Sample Preparation kit of Illumina (San Diego, CA).
2014-02-28 | E-GEOD-55435 | biostudies-arrayexpress
Project description:Puberty is a complex physiological event measured by various indicator traits in genetic improvement programs of beef cattle; thus, developing a more complete understanding of the genes and regulatory pathways and networks involved in puberty will provide knowledge to help improve genetic selection strategies. Herein, 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 for cattle to achieve puberty (i.e., longissimus dorsi muscle, fat, and liver). These tissues were collected from pre (PRE)- and post (POST)-pubertal Brangus (3/8 Brahman; Bos indicus x 5/8 Angus; Bos taurus) heifers derived from a population of cattle used to identify QTL associated with fertility traits. 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 RNA-Seq, GWAS, and bovine transcription factors. RNA-Seq of 8 tissues among PRE and POST Brangus heifers revealed 1515 differentiallyexpressed and 943 tissue-specific genes within the 17,832 genes confirmed by metrics of RNA-Seq analysis. Combining the results from RNA-Seq and GWAS indentified a total of 25 QTL associated to heifer fertility. The hypothalamus experienced the most notable up-regulation of genes via puberty. Complementary omics procedures revealed 2,450 co-expressed genes across the 8 tissues relative to puberty. The PRE network had 372,861 connections whereas the POST network had 328,357 connections. A sub-network from this process revealed key transcriptional regulators (i.e., PITX2, FOXA1, TSG1D1, DACH2, LHX4, PROP1 and SIX6). Results from multiples sources of omics data will facilitate the design of breeding strategies to improve fertility in Bos indicus-influenced composite cattle.
2014-02-28 | GSE55435 | GEO
Project description:Here we describe a genome-wide analysis of copy number variations (CNVs) in Chinese domestic cattle by using array comparative genomic hybridization (array CGH) and quantitative PCR (qPCR). We conducted array CGH analysis on 30 male cattle individuals, animals from consisting of 12 breeds of Bos taurus/Bos indicus, 1 Bos grunniens and and two ones of Bubalus bubalis breeds for with beef, and/or dairy or dual purpose. We identified over 470 candidate CNV regions (CNVRs) in Bos B. taurus/B. indicus; 118 candidate CNV regions (CNVRs) in B. grunniens, 139 CNVRs in B. bubalis. Furthermore, based on the Y haplotypes of B. taurus/ B. indicus, Wwe also identified 69, 337, and 251 candidate CNV regions (CNVRs) in the sub-groups of Y1, Y2 and Y3 haplotypes.
2014-12-30 | GSE47086 | GEO
Project description:Copy number variations (CNVs) have been demonstrated as crucial substrates for evolution, adaptation and breed formation. Chinese indigenous cattle breeds exhibit a broad geographical distribution and diverse environmental adaptability. Here, we analyzed the population structure and adaptation to high altitude of Chinese indigenous cattle based on genome-wide CNVs derived from the high-density BovineHD SNP array. We successfully detected the genome-wide CNVs of 318 individuals from 24 Chinese indigenous cattle breeds and 37 yaks as outgroups. A total of 5,818 autosomal CNV regions (683 bp - 4,477,860 bp in size), covering ~14.34% of the bovine genome (UMD3.1), were identified, showing abundant CNV resources. Neighbor-joining clustering, principal component analysis (PCA), and population admixture analysis based on these CNVs support that most Chinese cattle breeds are hybrids of Bos taurus taurus (hereinafter to be referred as Bos taurus) and Bos taurus indicus (Bos indicus). The distribution patterns of the CNVs could to some extent be related to the geographical backgrounds of the habitat of the breeds, and admixture among cattle breeds from different districts. We analyzed the selective signatures of CNVs positively involved in high-altitude adaptation using pairwise Fst analysis within breeds with a strong Bos taurus background (taurine-type breeds) and within Bos taurus×Bos indicus hybrids, respectively. CNV-overlapping genes with strong selection signatures (at top 0.5% of Fst value), including LETM1 (Fst = 0.490), TXNRD2 (Fst=0.440) and STUB1 (Fst=0.420) within taurine-type breeds, and NOXA1 (Fst = 0.233), RUVBL1 (Fst=0.222) and SLC4A3 (Fst=0.154) within hybrids, were potentially involved in the adaptation to hypoxia. Thus, we provide a new profile of population structure from the CNV aspects of Chinese indigenous cattle and new insights into high-altitude adaptation in cattle.
2020-02-21 | GSE142218 | GEO