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This study used financial socialization theory to examine the direct and indirect association between financial socialization (from parents, peers, and teachers) and financial well-being (FWB) via financial self-efficacy (FSE). Data were collected from Pakistan in early 2020. Our data analysis using the partial least square structural equation modeling approach revealed surprising results. We found that an association between financial socialization from peers and FWB does not exist both directly and indirectly via FSE. Furthermore, the results showed that the association of financial socialization from parents and teachers with FWB is completely mediated by FSE. Other results indicated partial mediation of FSE in the association between early childhood consumer experience and FWB. Our findings imply that learning from others' financial experiences builds young consumers' confidence in dealing with financial matters, which, in turn, helps improve their FWB. We suggest policymakers to consider these findings in designing policies related to the young consumers of developing nations. [ABSTRACT FROM AUTHOR]

Biologically informed single nucleotide polymorphisms (SNPs) impact genomic prediction accuracy of the target traits. Our previous genomics, proteomics, and transcriptomics work identified candidate genes related to puberty and fertility in Brahman heifers. We aimed to test this biological information for capturing heritability and predicting heifer fertility traits in another breed i.e. Tropical Composite. The SNP from the identified genes including 10 kilobases (kb) region on either side were selected as biologically informed SNP set. The SNP from the rest of the Bos taurus genes including 10-kb region on either side were selected as biologically uninformed SNP set. Bovine high-density (HD) complete SNP set (628,323 SNP) was used as a control. Two populations—Tropical Composites (N = 1331) and Brahman (N = 2310)—had records for three traits: pregnancy after first mating season (PREG1, binary), first conception score (FCS, score 1 to 3), and rebreeding score (REB, score 1 to 3.5). Using the best linear unbiased prediction method, effectiveness of each SNP set to predict the traits was tested in two scenarios: a 5-fold cross-validation within Tropical Composites using biological information from Brahman studies, and application of prediction equations from one breed to the other. The accuracy of prediction was calculated as the correlation between genomic estimated breeding values and adjusted phenotypes. Results show that biologically informed SNP set estimated heritabilities not significantly better than the control HD complete SNP set in Tropical Composites; however, it captured all the observed genetic variance in PREG1 and FCS when modeled together with the biologically uninformed SNP set. In 5-fold cross-validation within Tropical Composites, the biologically informed SNP set performed marginally better (statistically insignificant) in terms of prediction accuracies (PREG1: 0.20, FCS: 0.13, and REB: 0.12) as compared to HD complete SNP set (PREG1: 0.17, FCS: 0.10, and REB: 0.11), and biologically uninformed SNP set (PREG1: 0.16, FCS: 0.10, and REB: 0.11). Across-breed use of prediction equations still remained a challenge: accuracies by all SNP sets dropped to around zero for all traits. The performance of biologically informed SNP was not significantly better than other sets in Tropical Composites. However, results indicate that biological information obtained from Brahman was successful to predict the fertility traits in Tropical Composite population. [ABSTRACT FROM AUTHOR]

Context. Studies have shown that favourable genetic correlations exist between female and male fertility traits. However, investigations regarding these correlations in Australian tropical beef cattle are limited to either pedigree or single-breed analysis. Aim. The study aims to use genomic information to estimate genetic parameters of six female and seven male fertility traits measured during the first 2 years of life, in two tropical breeds. Methods. Single-, bivariate and multi-trait models were used to analyse fertility data from Brahman (BB; 996 cows and 1022 bulls); and Tropical Composite (TC; 1091 cows and 998 bulls) cattle genotyped with high-density singlenucleotide polymorphism chip assay. Key results. Heritability estimates in BB cows ranged from low (0.07 ± 0.04) for days to calving at the first calving opportunity (DC1, days) to high (0.57 ± 0.08) for age at first corpus luteum (AGECL, days). In BB bulls, estimates varied from low (0.09 ± 0.05) for sperm motility (score 1-5) to high (0.64 ± 0.06) for scrotal circumference (SC) measured at 24 months (SC24, cm). Similarly, heritability estimates in TC cows were low (0.04 ± 0.03) for DC1 and high (0.69 ± 0.02) for AGECL. In TC bulls, the heritability was low (0.09 ± 0.05) for sperm motility and high (0.69 ± 0.07) for SC24. Within-sex for both breeds, blood concentrations of insulin growth-factor 1 (IGF1) measured in cows at 18 months (IGF1c) were negatively correlated with female fertility phenotypes. In BB, across-sex, bulls' blood concentration of IGF1 measured at 6 months (IGF1b) was a good indicator trait for the following four female traits: AGECL, the first postpartum anoestrus interval, age at first calving and DC1. In TC, IGF1b and percentage normal sperm were good predictors of female fertility phenotypes. Conclusions. The heritability estimates and genomic correlations from the present study generally support and confirmed the earlier estimates from pedigree analyses. The findings suggest that selection for female fertility traits will benefit male fertility, and vice versa. Implications. Heritability estimates and genomic correlations suggest that we can select for fertility traits measured early in life, with benefits within and across sex. Using traits available through veterinary assessment of bull fertility as selection indicators will enhance bull and cow fertility, which can lead to better breeding rates in tropical herds. [ABSTRACT FROM AUTHOR]

Although the genetic correlations between complex traits have been estimated for more than a century, only recently we have started to map and understand the precise localization of the genomic region(s) that underpin these correlations. Reproductive traits are often genetically correlated. Yet, we don't fully understand the complexities, synergism, or trade-offs between male and female fertility. In this study, we used reproductive traits in two cattle populations (Brahman; BB, Tropical Composite; TC) to develop a novel framework termed correlation scan (CS). This framework was used to identify local regions associated with the genetic correlations between male and female fertility traits. Animals were genotyped with bovine high-density single nucleotide polymorphisms (SNPs) chip assay. The data used consisted of ~1000 individual records measured through frequent ovarian scanning for age at first corpus luteum (AGECL) and a laboratory assay for serum levels of insulin growth hormone (IGF1 measured in bulls, IGF1b, or cows, IGF1c). The methodology developed herein used correlations of 500-SNP effects in a 100-SNPs sliding window in each chromosome to identify local genomic regions that either drive or antagonize the genetic correlations between traits. We used Fisher's Z-statistics through a permutation method to confirm which regions of the genome harboured significant correlations. About 30% of the total genomic regions were identified as driving and antagonizing genetic correlations between male and female fertility traits in the two populations. These regions confirmed the polygenic nature of the traits being studied and pointed to genes of interest. For BB, the most important chromosome in terms of local regions is often located on bovine chromosome (BTA) 14. However, the important regions are spread across few different BTA's in TC. Quantitative trait loci (QTLs) and functional enrichment analysis revealed many significant windows co-localized with known QTLs related to milk production and fertility traits, especially puberty. In general, the enriched reproductive QTLs driving the genetic correlations between male and female fertility are the same for both cattle populations, while the antagonizing regions were population specific. Moreover, most of the antagonizing regions were mapped to chromosome X. These results suggest regions of chromosome X for further investigation into the trade-offs between male and female fertility. We compared the CS with two other recently proposed methods that map local genomic correlations. Some genomic regions were significant across methods. Yet, many significant regions identified with the CS were overlooked by other methods. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

High fertility and early puberty in Bos indicus heifers are desirable and genetically correlated traits in beef production. The hypothalamus–pituitary–ovarian (HPO) axis synthesizes steroid hormones, which contribute to the shift from the pre-pubertal state into the post-pubertal state and influence subsequent fertility. Understanding variations in abundance of proteins that govern steroid synthesis and ovarian signaling pathways remains crucial to understanding puberty and fertility. We used whole ovaries of six pre-pubertal and six post-pubertal Brahman heifers to conduct differential abundance analyses of protein profiles between the two physiological states. Extracted proteins were digested into peptides followed by identification and quantification with massspectrometry (MS) by sequential window acquisition of all instances of theoretical fragment ion mass spectrometry (SWATH-MS). MS and statistical analysis identified 566 significantly differentially abundant (DA) proteins (adjusted p < 0.05), which were then analyzed for gene ontology and pathway enrichment. Our data indicated an up-regulation of steroidogenic proteins contributing to progesterone synthesis at luteal phase post-puberty. Proteins related to progesterone signaling, TGF-β, retinoic acid, extracellular matrix, cytoskeleton, and pleiotrophin signaling were DA in this study. The DA proteins probably relate to the formation and function of the corpus luteum, which is only present after ovulation, post-puberty. Some DA proteins might also be related to granulosa cells signaling, which regulates oocyte maturation or arrest in ovaries prior to ovulation. Ten DA proteins were coded by genes previously associated with reproductive traits according to the animal quantitative trait loci (QTL) database. In conclusion, the DA proteins and their pathways were related to ovarian activity in Bos indicus cattle. The genes that code for these proteins may explain some known QTLs and could be targeted in future genetic studies. [ABSTRACT FROM AUTHOR]