scholarly journals Title: Meta-Analysis of Heifer Traits Identified Reproductive Pathways in Bos indicus Cattle

Genes ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 768
Author(s):  
Muhammad S. Tahir ◽  
Laercio R. Porto-Neto ◽  
Cedric Gondro ◽  
Olasege B. Shittu ◽  
Kimberley Wockner ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Molecular Mechanisms ◽  
Meta Analysis ◽  
Reproductive Traits ◽  
Significant Snps ◽  
Genomic Region ◽  
Chromosome 8 ◽  
Positional Candidate ◽  
Brahman Cattle ◽  
Genomic Regions

Fertility traits measured early in life define the reproductive potential of heifers. Knowledge of genetics and biology can help devise genomic selection methods to improve heifer fertility. In this study, we used ~2400 Brahman cattle to perform GWAS and multi-trait meta-analysis to determine genomic regions associated with heifer fertility. Heifer traits measured were pregnancy at first mating opportunity (PREG1, a binary trait), first conception score (FCS, score 1 to 3) and rebreeding score (REB, score 1 to 3.5). The heritability estimates were 0.17 (0.03) for PREG1, 0.11 (0.05) for FCS and 0.28 (0.05) for REB. The three traits were highly genetically correlated (0.75–0.83) as expected. Meta-analysis was performed using SNP effects estimated for each of the three traits, adjusted for standard error. We identified 1359 significant SNPs (p-value < 9.9 × 10−6 at FDR < 0.0001) in the multi-trait meta-analysis. Genomic regions of 0.5 Mb around each significant SNP from the meta-analysis were annotated to create a list of 2560 positional candidate genes. The most significant SNP was in the vicinity of a genomic region on chromosome 8, encompassing the genes SLC44A1, FSD1L, FKTN, TAL2 and TMEM38B. The genomic region in humans that contains homologs of these genes is associated with age at puberty in girls. Top significant SNPs pointed to additional fertility-related genes, again within a 0.5 Mb region, including ESR2, ITPR1, GNG2, RGS9BP, ANKRD27, TDRD12, GRM1, MTHFD1, PTGDR and NTNG1. Functional pathway enrichment analysis resulted in many positional candidate genes relating to known fertility pathways, including GnRH signaling, estrogen signaling, progesterone mediated oocyte maturation, cAMP signaling, calcium signaling, glutamatergic signaling, focal adhesion, PI3K-AKT signaling and ovarian steroidogenesis pathway. The comparison of results from this study with previous transcriptomics and proteomics studies on puberty of the same cattle breed (Brahman) but in a different population identified 392 genes in common from which some genes—BRAF, GABRA2, GABR1B, GAD1, FSHR, CNGA3, PDE10A, SNAP25, ESR2, GRIA2, ORAI1, EGFR, CHRNA5, VDAC2, ACVR2B, ORAI3, CYP11A1, GRIN2A, ATP2B3, CAMK2A, PLA2G, CAMK2D and MAPK3—are also part of the above-mentioned pathways. The biological functions of the positional candidate genes and their annotation to known pathways allowed integrating the results into a bigger picture of molecular mechanisms related to puberty in the hypothalamus–pituitary–ovarian axis. A reasonable number of genes, common between previous puberty studies and this study on early reproductive traits, corroborates the proposed molecular mechanisms. This study identified the polymorphism associated with early reproductive traits, and candidate genes that provided a visualization of the proposed mechanisms, coordinating the hypothalamic, pituitary, and ovarian functions for reproductive performance in Brahman cattle.

scholarly journals Genomic Scan for Selection Signature Reveals Fat Deposition in Chinese Indigenous Sheep with Extreme Tail Types

Animals ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 773 ◽  
Author(s):  
Fuping Zhao ◽  
Tianyu Deng ◽  
Liangyu Shi ◽  
Wenwen Wang ◽  
Qin Zhang ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Coat Color ◽  
Reproductive Traits ◽  
Bioinformatic Analysis ◽  
Selection Signatures ◽  
Selection Signature ◽  
Positional Candidate ◽  
Indigenous Sheep ◽  
Tibetan Sheep ◽  
Genomic Regions

It is a unique feature that fat can be deposited in sheep tails and rumps. To elucidate the genetic mechanism underlying this trait, we collected 120 individuals from three Chinese indigenous sheep breeds with extreme tail types, namely large fat-tailed sheep (n = 40), Altay sheep (n = 40), and Tibetan sheep (n = 40), and genotyped them using the Ovine Infinium HD SNP BeadChip. Then genomic scan for selection signatures was performed using the hapFLK. In total, we identified 25 genomic regions exhibiting evidence of having been under selection. Bioinformatic analysis of the genomic regions showed that selection signatures related to multiple candidate genes had a demonstrated role in phenotypic variation. Nine genes have documented association with sheep tail types, including WDR92, TBX12, WARS2, BMP2, VEGFA, PDGFD, HOXA10, ALX4, and ETAA1. Moreover, a number of genes were of particular interest, including RXFP2 associated with the presence/absence and morphology of horns; MITF involved in coat color; LIN52 and SYNDIG1L related to the number of teats; MSRB3 gene associated with ear sizes; LTBP2 considered as a positional candidate genes for number of ribs; JAZF1 regulating lipid metabolism; PGRMC2, SPAG17, TSHR, GTF2A1, and LARP1B implicated with reproductive traits. Our findings provide insights into fat tail formation and a reference for carrying out molecular breeding and conservation in sheep.

Meta-analysis of grain iron and zinc associated QTLs identified hotspot chromosomal regions and positional candidate genes for breeding biofortified rice

Plant Science ◽  
2019 ◽  
Vol 288 ◽  
pp. 110214 ◽  
Author(s):  
Qasim Raza ◽  
Awais Riaz ◽  
Muhammad Sabar ◽  
Rana Muhammad Atif ◽  
Khurram Bashir
Keyword(s):  
Candidate Genes ◽  
Meta Analysis ◽  
Positional Candidate ◽  
Iron And Zinc

scholarly journals RAPID COMMUNICATION: Multi-breed validation study unraveled genomic regions associated with puberty traits segregating across tropically adapted breeds1

2019 ◽  
Vol 97 (7) ◽  
pp. 3027-3033 ◽  
Author(s):  
Thaise P Melo ◽  
Marina R S Fortes ◽  
Gerardo A Fernandes Junior ◽  
Lucia G Albuquerque ◽  
Roberto Carvalheiro
Keyword(s):  
Candidate Genes ◽  
Genome Wide Association Study ◽  
Meta Analysis ◽  
Reference Population ◽  
High Linkage Disequilibrium ◽  
P Value ◽  
Early Puberty ◽  
Sexual Precocity ◽  
Tropical Conditions ◽  
Genomic Regions

Abstract An efficient strategy to improve QTL detection power is performing across-breed validation studies. Variants segregating across breeds are expected to be in high linkage disequilibrium (LD) with causal mutations affecting economically important traits. The aim of this study was to validate, in a Tropical Composite cattle (TC) population, QTL associations identified for sexual precocity traits in a Nellore and Brahman meta-analysis genome-wide association study. In total, 2,816 TC, 8,001 Nellore, and 2,210 Brahman animals were available for the analysis. For that, genomic regions significantly associated with puberty traits in the meta-analysis study were validated for the following sexual precocity traits in TC: age at first corpus luteum (AGECL), first postpartum anestrus interval (PPAI), and scrotal circumference at 18 months of age (SC). We considered validated QTL those underpinned by significant markers from the Nellore and Brahman meta-analysis (P ≤ 10–4) that were also significant for a TC trait, i.e., presenting a P-value of ≤10–3 for AGECL, PPAI, or SC. We also considered as validated QTL those regions where significant markers in the reference population were at ±250 kb from significant markers in the validation population. Using this criteria, 49 SNP were validated for AGECL, 4 for PPAI, and 14 for SC, from which 5 were in common with AGECL, totaling 62 validated SNP for these traits and 30 candidate genes surrounding them. Considering just candidate genes closest to the top SNP of each chromosome, for AGECL 8 candidate genes were identified: COL8A1, PENK, ENSBTAG00000047425, BPNT1, ADAMTS17, CCHCR1, SUFU, and ENSBTAG00000046374. For PPAI, 3 genes emerged as candidates (PCBP3, KCNK10, and MRPS5), and for SC 8 candidate genes were identified (SNORA70, TRAC, ASS1, BPNT1, LRRK1, PKHD1, PTPRM, and ENSBTAG00000045690). Several candidate regions presented here were previously associated with puberty traits in cattle. The majority of emerging candidate genes are related to biological processes involved in reproductive events, such as maintenance of gestation, and some are known to be expressed in reproductive tissues. Our results suggested that some QTL controlling early puberty seem to be segregating across cattle breeds adapted to tropical conditions.

scholarly journals Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Miguel Gozalo-Marcilla ◽  
Jaap Buntjer ◽  
Martin Johnsson ◽  
Lorena Batista ◽  
Federico Diez ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Genetic Variance ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Insulin Signalling ◽  
Additive Genetic Variance ◽  
Genomic Region ◽  
Carcass Composition ◽  
Backfat Thickness ◽  
Genomic Regions

Abstract Background Backfat thickness is an important carcass composition trait for pork production and is commonly included in swine breeding programmes. In this paper, we report the results of a large genome-wide association study for backfat thickness using data from eight lines of diverse genetic backgrounds. Methods Data comprised 275,590 pigs from eight lines with diverse genetic backgrounds (breeds included Large White, Landrace, Pietrain, Hampshire, Duroc, and synthetic lines) genotyped and imputed for 71,324 single-nucleotide polymorphisms (SNPs). For each line, we estimated SNP associations using a univariate linear mixed model that accounted for genomic relationships. SNPs with significant associations were identified using a threshold of p < 10–6 and used to define genomic regions of interest. The proportion of genetic variance explained by a genomic region was estimated using a ridge regression model. Results We found significant associations with backfat thickness for 264 SNPs across 27 genomic regions. Six genomic regions were detected in three or more lines. The average estimate of the SNP-based heritability was 0.48, with estimates by line ranging from 0.30 to 0.58. The genomic regions jointly explained from 3.2 to 19.5% of the additive genetic variance of backfat thickness within a line. Individual genomic regions explained up to 8.0% of the additive genetic variance of backfat thickness within a line. Some of these 27 genomic regions also explained up to 1.6% of the additive genetic variance in lines for which the genomic region was not statistically significant. We identified 64 candidate genes with annotated functions that can be related to fat metabolism, including well-studied genes such as MC4R, IGF2, and LEPR, and more novel candidate genes such as DHCR7, FGF23, MEDAG, DGKI, and PTN. Conclusions Our results confirm the polygenic architecture of backfat thickness and the role of genes involved in energy homeostasis, adipogenesis, fatty acid metabolism, and insulin signalling pathways for fat deposition in pigs. The results also suggest that several less well-understood metabolic pathways contribute to backfat development, such as those of phosphate, calcium, and vitamin D homeostasis.

scholarly journals Genomic analysis of GBS data reveals genes associated with facial pigmentation in Xinyang blue-shelled layers

2020 ◽  
Vol 63 (2) ◽  
pp. 483-491
Author(s):  
Haobin Hou ◽  
Xiaoliang Wang ◽  
Caiyun Zhang ◽  
Yingying Tu ◽  
Wenwei Lv ◽  
...  
Keyword(s):  
Skin Color ◽  
Genome Wide Association Study ◽  
Laying Hens ◽  
Genomic Analysis ◽  
Significant Snps ◽  
Pure Line ◽  
Genomic Region ◽  
High Quality Snps ◽  
A Genome ◽  
Genomic Regions

Abstract. Facial pigmentation is an important economic trait of chickens, especially for laying hens, which will affect the carcass appearance of eliminated layers. Therefore, identifying the genomic regions and exploring the function of this region that contributes to understanding the variation of skin color traits is significant for breeding. In the study, 291 pure-line Xinyang blue-shelled laying hens were selected, of which 75 were dark-faced chickens and 216 were white-faced chickens. The population was sequenced and typed by GBS genotyping technology. The obtained high-quality SNPs and pigmentation phenotypes were analyzed by a genome-wide association study (GWAS) and a FST scan. Based on the two analytical methods, we identified a same genomic region (10.70–11.60 Mb) on chromosome 20 with 68 significant SNPs (−log 10(P)>6), mapped to 10 known genes, including NPEPL1, EDN3, GNAS, C20orf85, VAPB, BMP7, TUBB1, ELMO2, DDX27, and NCOA5, which are associated with dermal hyperpigmentation.

scholarly journals Runs of homozygosity analysis reveals consensus homozygous regions affecting production traits in Chinese Simmental beef cattle

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Guoyao Zhao ◽  
Yuqiang Liu ◽  
Qunhao Niu ◽  
Xu Zheng ◽  
Tianliu Zhang ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Candidate Genes ◽  
Average Length ◽  
Snp Array ◽  
Reproductive Traits ◽  
Farm Animals ◽  
Production Traits ◽  
Runs Of Homozygosity ◽  
Exact Test ◽  
Genomic Regions

Abstract Background Genomic regions with a high frequency of runs of homozygosity (ROH) are related to important traits in farm animals. We carried out a comprehensive analysis of ROH and evaluated their association with production traits using the BovineHD (770 K) SNP array in Chinese Simmental beef cattle. Results We detected a total of 116,953 homozygous segments with 2.47Gb across the genome in the studied population. The average number of ROH per individual was 99.03 and the average length was 117.29 Mb. Notably, we detected 42 regions with a frequency of more than 0.2. We obtained 17 candidate genes related to body size, meat quality, and reproductive traits. Furthermore, using Fisher’s exact test, we found 101 regions were associated with production traits by comparing high groups with low groups in terms of production traits. Of those, we identified several significant regions for production traits (P < 0.05) by association analysis, within which candidate genes including ECT2, GABRA4, and GABRB1 have been previously reported for those traits in beef cattle. Conclusions Our study explored ROH patterns and their potential associations with production traits in beef cattle. These results may help to better understand the association between production traits and genome homozygosity and offer valuable insights into managing inbreeding by designing reasonable breeding programs in farm animals.

scholarly journals Identification of Candidate Genes Controlling Fiber Quality Traits in Upland Cotton Through Integration of Meta-QTL, Significant SNP and Transcriptomic Data

2020 ◽  
Author(s):  
XU Shudi ◽  
Zhenyuan Pan ◽  
Feifan Yin ◽  
Qingyong Yang ◽  
Zhongxu Lin ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Cotton Fiber ◽  
Molecular Mechanisms ◽  
Fiber Strength ◽  
Fiber Quality ◽  
Significant Snps ◽  
Fiber Development ◽  
Computational Technique ◽  
Quality Traits ◽  
Fiber Quality Traits

Abstract Background Meta-analysis of quantitative trait locus (QTL) is a computational technique to identify consensus QTL and refine QTL positions on the consensus map from multiple mapping studies. The combination of meta-QTL intervals, significant SNPs and transcriptome analysis has been widely used to identify candidate genes in various plants. Results In our study, 884 QTL associated with cotton fiber quality traits from 12 studies were used for meta-QTL analysis based on reference genome TM-1, as a result, 74 meta-QTL were identified, including 19 meta-QTL for fiber length (FL), 18 meta-QTL for fiber strength (FS), 11 meta-QTL for fiber uniformity (FU), 11 meta-QTL for fiber elongation (FE), and 15 meta-QTL for micronaire (MIC). Combined with 8589 significant SNPs associated with fiber quality traits collected from 15 studies, 297 candidate genes were identified in the meta-QTL intervals, 20 of which showed high expression specifically in the developing fibers. According to the function annotations, some of the 20 key candidate genes are associated with the fiber development. Conclusions This study provides not only stable QTLs used for marker-assisted selection (MAS), but also candidate genes to uncover the molecular mechanisms for cotton fiber development.

Pinpointing Genomic Regions Associated with Root System Architecture in Rice Through an Integrative Meta-Analysis Approach

2021 ◽  
Author(s):  
Parisa Daryani ◽  
Hadi Darzi Ramandi ◽  
Sara Dezhsetan ◽  
Raheleh Mirdar Mansuri ◽  
Ghasem Hosseini Salekdeh ◽  
...  
Keyword(s):  
Drought Stress ◽  
Root System ◽  
Candidate Genes ◽  
System Architecture ◽  
Meta Analysis ◽  
Root System Architecture ◽  
Stress Conditions ◽  
Yield Potential ◽  
Analysis Approach ◽  
Genomic Regions

Abstract Root system architecture (RSA) is an important factor for facilitating water and nutrient uptake from deep soils and adaptation to drought stress conditions. In the present research, an integrated meta-analysis approach was employed to find candidate genes and genomic regions involved in rice RSA traits. A whole-genome meta-analysis was performed for 425 initial QTLs reported in 34 independent experiments controlling RSA traits under control and drought stress conditions in the previous twenty years. Sixty-four consensus meta-QTLs (MQTLs) were detected, unevenly distributed on twelve rice chromosomes. The confidence interval (CI) of the identified MQTLs was obtained as 0.11-14.23 cM with an average of 3.79 cM, which was 3.88 times narrower than the mean CI of the original QTLs. Interestingly, 52 MQTLs were co-located with SNP peak positions reported in rice genome-wide association studies (GWAS) for root morphological traits. The genes located in these RSA related MQTLs were detected, and explored to find the drought-responsive genes in the rice root based on the RNA-seq and microarray data. Multiple RSA and drought tolerance associated genes were found in the MQTLs including the genes involved in auxin biosynthesis or signaling (e.g. YUCCA, WOX, AUX/IAA, ARF), root angle (DRO1-related genes), lateral root development (e.g. DSR, WRKY), root diameter (e.g. OsNAC5), plant cell wall (e.g. EXPA) and lignification (e.g. C4H, PAL, PRX and CAD). The genes located both in the SNP peak positions and in the high-overview-index MQTLs for root architecture traits are suggested as novel candidate genes for further functional analysis.. The promising candidate genes and MQTLs would be applicable to genetic engineering and MQTL-assisted breeding of root phenotypes aimed at improving yield potential, stability and performance in a water-stressed environment.

Identification of genomic regions controlling plasma FSH concentrations in Meishan-White Composite boars

2001 ◽  
Vol 6 (3) ◽  
pp. 145-151 ◽  
Author(s):  
G. A. ROHRER ◽  
T. H. WISE ◽  
D. D. LUNSTRA ◽  
J. J. FORD
Keyword(s):  
Plasma Levels ◽  
Reproductive Traits ◽  
Chromosome 8 ◽  
Ovulation Rate ◽  
Glycoprotein Hormones ◽  
Elevated Plasma ◽  
Large White ◽  
Entire Genome ◽  
Genetic Mechanisms ◽  
Genomic Regions

The Chinese Meishan (ME) breed of pig is unique for many reproductive traits. Compared with Western breeds of swine, ME females reach puberty earlier, ovulate more ova per estrus, and have greater uterine capacity, while intact males (boars) have smaller testes and extremely elevated plasma levels of pituitary-derived glycoprotein hormones. In an effort to identify the genetic mechanisms controlling the elevated plasma levels of pituitary-derived glycoprotein hormones [in particular, follicle-stimulating hormone (FSH)] and to determine whether some of these genetic factors are also responsible for differences in other phenotypes, we scanned the entire genome for regions that affected plasma FSH in boars from a Meishan-White Composite (equal contributions of Chester White, Landrace, Large White, and Yorkshire) resource population. Initially, the entire genome of 121 boars was scanned for regions that potentially influenced plasma FSH. The most significant genomic regions were further studied in a total of 436 boars. Three genomic regions located on chromosomes 3, 10, and X apparently possess genes that significantly affect FSH level, and one region provided suggestive evidence for the presence of FSH-controlling genes located on chromosome 8. The region on the X chromosome also affected testes size. Similar genomic regions to those identified on chromosomes 3, 8, and 10 in this study have been identified to affect ovulation rate in female litter mates, supporting the hypothesis that plasma FSH in pubertal boars and ovulation rate in females is controlled by a similar set of genes.

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