Advances in molecular genetic techniques applied to selection for litter size in goats (Capra hircus): a review

Potential Candidate Genes Associated with Litter Size in Goats: A Review

This review examines genetic markers associated with litter size in goats, a key reproductive trait impacting productivity in small ruminant farming. Goats play a vital socioeconomic role in both low- and high-income regions; however, their productivity remains limited due to low reproductive efficiency. Litter size, influenced by multiple genes and environmental factors, directly affects farm profitability and sustainability by increasing the output per breeding cycle. Recent advancements in genetic research have identified key genes and pathways associated with reproductive traits, including gonadotropin-releasing hormone (GnRH), inhibin (INHAA), Kit ligand (KITLG), protein phosphatase 3 catalytic subunit alpha (PPP3CA), prolactin receptor (PRLR), POU domain class 1 transcription factor 1 (POU1F1), anti-Müllerian hormone (AMH), bone morphogenetic proteins (BMP), growth differentiation factor 9 (GDF9), and KISS1 and suppressor of mothers against decapentaplegic (SMAD) family genes, among others. These genes regulate crucial physiological processes such as folliculogenesis, hormone synthesis, and ovulation. Genome-wide association studies (GWASs) and transcriptomic analyses have pinpointed specific genes linked to increased litter size, highlighting their potential in selective breeding programs. By incorporating genomic data, breeding strategies can achieve higher selection accuracy, accelerate genetic gains, and improve reproductive efficiency. This review emphasizes the importance of genetic markers in optimizing litter size and promoting sustainable productivity in goat farming.

Whole-Genome Resequencing to Identify Selection Signatures Associated with High Fertility in Lüliang Black Goat

Lüliang black goat (LBG) is a unique livestock genetic resource of great significance for the local agriculture and economic development of Shanxi, China. However, the kidding rate of LBG is relatively low, which limits efforts to improve the reproductive performance and economic benefits of this breed. Therefore, improving the kidding characteristics of LBG is crucial for increasing its economic benefits. In this study, 20 LBG does were selected for whole-genome resequencing and divided into two groups: 10 in the T group (does with three consecutive kiddings of twin kids) and 10 in the S group (does with three consecutive kiddings of single kids). Based on whole-genome resequencing data, this study comprehensively assessed the population structure and genetic diversity of LBG and explored the related genes that affect reproductive performance. Three selection signal analysis methods-Fst (Fixation Index), π (nucleotide diversity), and XP-CLR (Cross Population Composite Likelihood Ratio)-were applied to screen a total of 838 genes, and enrichment analysis was performed to identify genes closely related to the reproductive performance of LBG, including ENPP3, APC, and GLI2. A generalized linear model was used to conduct a correlation analysis between non-synonymous mutations in the three genes and the number of kids produced. Two loci that were significantly correlated with kidding number were identified (p < 0.05): GLI2 g.63400363 C>T and GLI2 g.63417538 C>T. In general, the LBG population has high genetic diversity and good prospects for genetic improvement. The findings revealed that mining high-fecundity selection characteristics provides a basis for research on goat reproductive mechanisms.

Association of litter size with the ruminal microbiome structure and metabolomic profile in goats

The Yunshang black goat is a renowned mutton specialist breed mainly originating from China that has excellent breeding ability with varying litter sizes. Litter size is an important factor in the economics of goat farming. However, ruminal microbiome structure might be directly or indirectly regulated by pregnancy-associated factors, including litter sizes. Therefore, the current experiment aimed to evaluate the association of different litter sizes (low versus high) with ruminal microbiome structure by 16S rRNA gene sequencing and metabolomic profiling of Yunshang black does. A total of twenty does of the Yunshang Black breed, approximately aged between 3 and 4 years, were grouped (n = 10 goats/group) into low (D-l) and high (D-h) litter groups according to their litter size (the lower group has ≤ 2 kids/litter and the high group has ≧ 3 kids/litter, respectively). All goats were sacrificed, and collected ruminal fluid samples were subjected to 16S rRNA sequencing and LC-MS/MC Analysis for ruminal microbiome and metabolomic profiling respectively. According to PCoA analysis, the ruminal microbiota was not significantly changed by the litter sizes among the groups. The Firmicutes and Bacteroidetes were the most dominant phyla, with an abundance of 55.34% and 39.62%, respectively. However, Ruminococcaceae_UCG-009, Sediminispirochaeta, and Paraprevotella were significantly increased in the D-h group, whereas Ruminococcaceae_UCG-010 and Howardella were found to be significantly decreased in the D-l group. The metabolic profiling analysis revealed that litter size impacts metabolites as 29 and 50 metabolites in positive and negative ionic modes respectively had significant differences in their regulation. From them, 16 and 24 metabolites of the D-h group were significantly down-regulated in the positive ionic mode, while 26 metabolites were up-regulated in the negative ionic mode for the same group. The most vibrant identified metabolites, including methyl linoleate, acetylursolic acid, O-desmethyl venlafaxine glucuronide, melanostatin, and arginyl-hydroxyproline, are involved in multiple biochemical processes relevant to rumen roles. The identified differential metabolites were significantly enriched in 12 different pathways including protein digestion and absorption, glycerophospholipid metabolism, regulation of lipolysis in adipocytes, and the mTOR signaling pathway. Spearman's correlation coefficient analysis indicated that metabolites and microbial communities were tightly correlated and had significant differences between the D-l and D-h groups. Based on the results, the present study provides novel insights into the regulation mechanisms of the rumen microbiota and metabolomic profiles leading to different fertility in goats, which can give breeders some enlightenments to further improve the fertility of Yunshang Black goats.

Genetic variation in the BLM gene and its expression in the ovaries is closely related to kidding number in goats

Bloom (BLM) helicase plays an important role in DNA replication and the maintenance of genome integrity. BLM protein deficiency, which plays a vital role in the sperm-egg union and germ-cell development during reproduction, can lead to severe DNA damage in goats. However, the effect of BLM protein deficiency on goat litter size has not been reported. Herein, we studied the association between the genetic variation in the BLM gene and the number of kids per litter in Guizhou white goats. We explored differences in the expression of the BLM protein in the follicles of single and multi-kid nanny goats. We also analyzed the effects of dysregulated BLM gene expression on the proliferation and apoptosis of ovarian granulosa cells and the expression of genes related to follicle development in goats. Five single nucleotide polymorphism (SNP) loci, including the non-synonymous mutations g.38179 A > G, g.40626 G > C and g.89621 T > G; the intron synonymous mutation g.56961 G > A and the exon synonymous mutation g.65796 C > T were found in the BLM gene. All SNPs loci were in Hardy-Weinberg equilibrium, and correlation analysis showed that the g.65796 C > T and g.89621 T > G loci polymorphism was strongly associated with litter size in the first three litters (P < 0.05). The diplogenotype Hap 2/2 (AAGGAACCTT) showed no significant difference in litter size between different births, indicating that the diploid genotype is stable in different litter sizes. Bioinformatics analysis showed that three non-synonymous mutation loci (p.T488A, p.A662S, and p.S1373A) could affect BLM protein stability, and mutations in p.T488A and p.S1373A led to changes in amino acid polarity and associated interactions. qPCR results showed that the expression level of the BLM gene in the uterus and ovaries of TT genotype nanny goats was significantly higher than that of GG genotype nanny goats. Indirect immunofluorescence assay (IF) showed that the BLM protein was significantly overexpressed in both the primordial and growing follicles of nanny goats with multiple kids (P < 0.01). Disrupting BLM gene expression in the ovarian granulosa cells down-regulated the expression of the Cyp19A1 gene. It also significantly inhibited the proliferation of follicles and induces early apoptosis of the granulosa cells. These findings confirm that polymorphism in the BLM gene is closely related to the littering traits of Guizhou white goats, and it affects the reproductive performance of nanny goats by regulating the development of the oocytes and granulosa cells. This work provides new evidence on the regulatory effect of the BLM gene on the litter size of nanny goats.

Construction of a circRNA- lincRNA-lncRNA-miRNA-mRNA ceRNA regulatory network identifies genes and pathways linked to goat fertility

Background: There is growing interest in the genetic improvement of fertility traits in female goats. With high-throughput genotyping, single-cell RNA sequencing (scRNA-seq) is a powerful tool for measuring gene expression profiles. The primary objective was to investigate comparative transcriptome profiling of granulosa cells (GCs) of high- and low-fertility goats, using scRNA-seq. Methods: Thirty samples from Ji'ning Gray goats (n = 15 for high fertility and n = 15 for low fertility) were retrieved from publicly available scRNA-seq data. Functional enrichment analysis and a literature mining approach were applied to explore modules and hub genes related to fertility. Then, interactions between types of RNAs identified were predicted, and the ceRNA regulatory network was constructed by integrating these interactions with other gene regulatory networks (GRNs). Results and discussion: Comparative transcriptomics-related analyses identified 150 differentially expressed genes (DEGs) between high- and low-fertility groups, based on the fold change (≥5 and ≤-5) and false discovery rate (FDR <0.05). Among these genes, 80 were upregulated and 70 were downregulated. In addition, 81 mRNAs, 58 circRNAs, 8 lincRNAs, 19 lncRNAs, and 55 miRNAs were identified by literature mining. Furthermore, we identified 18 hub genes (SMAD1, SMAD2, SMAD3, SMAD4, TIMP1, ERBB2, BMP15, TGFB1, MAPK3, CTNNB1, BMPR2, AMHR2, TGFBR2, BMP4, ESR1, BMPR1B, AR, and TGFB2) involved in goat fertility. Identified biological networks and modules were mainly associated with ovary signature pathways. In addition, KEGG enrichment analysis identified regulating pluripotency of stem cells, cytokine-cytokine receptor interactions, ovarian steroidogenesis, oocyte meiosis, progesterone-mediated oocyte maturation, parathyroid and growth hormone synthesis, cortisol synthesis and secretion, and signaling pathways for prolactin, TGF-beta, Hippo, MAPK, PI3K-Akt, and FoxO. Functional annotation of identified DEGs implicated important biological pathways. These findings provided insights into the genetic basis of fertility in female goats and are an impetus to elucidate molecular ceRNA regulatory networks and functions of DEGs underlying ovarian follicular development.

Litter size influences rumen microbiota and fermentation efficiency, thus determining host early growth in goats

Introduction

Multiple litters are accompanied by low birth weight, low survival rates, and growth rates in goats during early life. Regulating rumen microbiota structure can indirectly or directly affect host metabolism and animal growth. However, the relationship between high litter size and rumen microbiome, rumen fermentation, and growth performance in goat kids is unclear.

Methods

In the present study, thirty 6-month-old, female goats were investigated, of which 10 goats were randomly chosen from single, twin and triplet goats respectively, and their birth weight was recorded. From birth, all goats were subjected to the same feed and management practices. Individual weaning and youth body weight were measured, and the rumen fluid samples were collected to characterize the bacterial communities and to determine the ruminal volatile fatty acids (VFA), free amino acids (AA), and free fatty acids (FA) concentration of those young goats.

Results and Discussion

Compared with the single and twin goats, triplet goats have lower weaning and youth body weight and average daily gain (ADG). Ruminal propionate, butyrate, and total VFA were decreased in triplet goats. Meanwhile, ruminal AA, such as branched chain amino acids (BCAA), essential amino acids (EAA), unsaturated fatty acids (UFA), and monounsaturated fatty acids (MUFA) were decreased, while saturated fatty acids (SFA) and odd and branched chain fatty acids (OBCFA) were increased in triplet goats. Our results also revealed that litter size significantly affected the rumen bacterial communities, and triplet goats had a lower the Firmicutes: Bacteroidota ratio, the abundance of Firmicutes phylum, Rikenellaceae family, and Rikenellaceae RC9 gut group, and had a higher proportion of Prevotellaceae family, and several genera of Prevotellaceae, such as Prevotella, and unclassified f Prevotellaceae. Furthermore, Spearman's correlation network analysis showed that the changes in the rumen bacteria were associated with changes in rumen metabolites. In conclusion, this study revealed that high litter size could bring disturbances to the microbial communities and decrease the rumen fermentation efficiency and growth performance, which can be utilized to better understand variation in microbial ecology that will improve growth performance in triplet goats.

Characterization of circular RNA profiles of oviduct reveal the potential mechanism in prolificacy trait of goat in the estrus cycle

The mammalian oviduct is functionally highly diverse during the estrus cycle. It provides a suitable milieu for oocyte maturation, sperm capacitation, fertilization, early embryo development and transportation. While there have been many studies of molecular mechanisms on the kidding number of goats, a systematic analysis by which the underlying circular RNAs (circRNAs) changes in the oviduct related to prolificacy traits is lacking. Herein, we present a comprehensive circRNA atlas of the oviduct among high- and low-fecundity goats in the follicular phase (FH vs. FL), luteal phase (LH vs. LL), and estrus cycle (FH vs. LH; FL vs. LL) to unravel their potential regulatory mechanisms in improving kidding number. We generated RNA sequencing data, and identified 4,078 circRNAs from twenty sampled Yunshang black goats. Many of these circRNAs are exon-derived and differentially expressed between each comparison group. Subsequently, eight differentially expressed (DE) circRNAs were validated by RT‒qPCR, which was consistent with the RNA-seq data. GO and KEGG enrichment analyses suggested that numerous host genes of DE circRNAs were involved in the hormone secretion, gamete production, fertilization, and embryo development processes. The competing endogenous RNA (ceRNA) interaction network analysis revealed that 2,673 circRNA–miRNA–mRNA axes (including 15 DE circRNAs, 14 miRNAs, and 1,699 mRNAs) were formed, and several target genes derived from the ceRNA network were associated with oviduct functions and reproduction, including SMAD1, BMPR1B, IGF1, REV1, and BMP2K. Furthermore, miR-15a-5p, miR-181b-5p, miR-23b-5p, miR-204-3p, and miR-145-5p might play important roles in reproduction. Finally, a novel circRNA, circIQCG, was identified as potentially involved in embryo development. Overall, our study provides a resource of circRNAs to understand the oviductal function and its connection to prolificacy trait of goats in the differentiation estrus cycle.

Status quo of genetic improvement in local goats: a review

This review aims to summarize and synthesize the fragmented information available on the genetic improvement of local goats (criollo, indigenous, native) on the American and other continents, where populations with these goats have an important role in food security and the economy of rural communities, as well as in conservation of biodiversity and productivity improvement. Topics such as the current state of goat production globally, conservation programs, resistance to parasites and diseases, use of phenotypical characteristics and genomic information, and molecular markers for genetic improvement are addressed. The main challenges, opportunities, and limitations described in recent literature concerning local goats in the immediate future are discussed.

Prediction ability for growth and maternal traits using SNP arrays based on different marker densities in Nellore cattle using the ssGBLUP

This study aimed to investigate the prediction ability for growth and maternal traits using different low-density customized SNP arrays selected by informativeness and distribution of markers across the genome employing single-step genomic BLUP (ssGBLUP). Phenotypic records for adjusted weight at 210 and 450 days of age were utilized. A total of 945 animals were genotyped with high-density chip, and 267 individuals born after 2008 were selected as validation population. We evaluated 11 scenarios using five customized density arrays (40 k, 20 k, 10 k, 5 k and 2 k) and the HD array was used as desirable scenario. The GEBV predictions and BIF (Beef Improvement Federation) accuracy were obtained with BLUPF90 family programs. Linear regression was used to evaluate the prediction ability, inflation, and bias of GEBV of each customized array. An overestimation of partial GEBVs in contrast with complete GEBVs and increase of BIF accuracy with the density arrays diminished were observed. For all traits, the prediction ability was higher as the array density increased and it was similar with customized arrays higher than 10 k SNPs. Level of inflation was lower as the density array increased of and was higher for MW210 effect. The bias was susceptible to overestimation of GEBVs when the density customized arrays decreased. These results revealed that the BIF accuracy is sensible to overestimation using low-density customized arrays while the prediction ability with least 10,000 informative SNPs obtained from the Illumina BovineHD BeadChip shows accurate and less biased predictions. Low-density customized arrays under ssGBLUP method could be feasible and cost-effective in genomic selection.

Association of the KiSS1 gene with litter size in Cyprus and Iraqi black goats

Aim:

The study investigated the genetic polymorphism of the kisspeptin (KiSS1) gene and its relationship with litter size in Cyprus and Iraqi black goats.

Materials and Methods:

Blood samples (n=124) were collected from the two goat breeds reared at the Agricultural Research-Ruminant Research Station Breeding Station, Baghdad, Iraq. Genomic DNA was isolated using a DNA extraction kit. Polymerase chain reaction (PCR) was used to amplify the KiSS1 gene. All PCR products were sequenced and samples were used for further analysis using NCBI-Blast online on the exon 1 (595 bp) region of the KiSS1 gene.

Results:

The results of this study revealed a significantly (P<0.05) larger litter size of the Cyprus goat breed than in the Iraqi black goats in the first and second parity. Three (893G/C, 973C/A, and 979T/G) substitutions relative to the KiSS1 gene reference sequence (GenBank ID: J × 047312.1, KC989928.1) were identified. Only the mutation g893G>C was identified as a single nucleotide polymorphism (SNP) associated with litter size. Furthermore, the average alleles in KiSS1 gene of both types of goats 0.567 and 0.3715 GG, were recorded. The genotyping at locus g893C>G was demonstrating domination of fecundity quality litter size, Both genotypes SNP of GC were classified at this marked region of KiSS1 gene.

Conclusion:

The study concluded that the role of the KiSS1 gene in fecundity, revealing the status of this gene as an indicator in the assisted of caprine breeding selection.

Combined approaches to reveal genes associated with litter size in Yunshang black goats

Intensive artificial selection has been imposed in Yunshang black goats, the first black specialist mutton goat breed in China, with a breeding object of improving reproductive performance, which has contributed to reshaping of the genome including the characterization of SNP, ROH and haplotype. However, variation in reproductive ability exists in the present population. A WGS was implemented in two subpopulations (polytocous group, PG, and monotocous group, MG) with evident differences of litter size. Following the mapping to reference genome, and SNP calling and pruning, three approaches - GWAS, ROH analysis and detection of signatures of selection - were employed to unveil candidate genes responsible for litter size. Consequently, 12 candidate genes containing OSBPL8 with the minimum P-value were uncovered by GWAS. Differences were observed in the pattern of ROH between two subpopulations that shared similar low inbreeding coefficients. Two ROH hotspots and 12 corresponding genes emerged from ROH pool association analysis. Based on the nS_L statistic, 15 and 61 promising genes were disclosed under selection for MG and PG respectively. Of them, some promising genes participate in ovarian function (PPP2R5C, CDC25A, ESR1, RPS26 and SERPINBs), seasonal reproduction (DIO3, BTG1 and CRYM) and metabolism (OSBPL8, SLC39A5 and SERPINBs). Our study pinpointed some novel promising genes influencing litter size, provided a comprehensive insight into genetic makeup of litter size and might facilitate selective breeding in goats.

Goat Genomic Resources: The Search for Genes Associated with Its Economic Traits

Goat plays a crucial role in human livelihoods, being a major source of meat, milk, fiber, and hides, particularly under adverse climatic conditions. The goat genomics related to the candidate gene approach is now being used to recognize molecular mechanisms that have different expressions of growth, reproductive, milk, wool, and disease resistance. The appropriate literature on this topic has been reviewed in this article. Several genetic characterization attempts of different goats have reported the existence of genotypic and morphological variations between different goat populations. As a result, different whole-genome sequences along with annotated gene sequences, gene function, and other genomic information of different goats are available in different databases. The main objective of this review is to search the genes associated with economic traits in goats. More than 271 candidate genes have been discovered in goats. Candidate genes influence the physiological pathway, metabolism, and expression of phenotypes. These genes have different functions on economically important traits. Some genes have pleiotropic effect for expression of phenotypic traits. Hence, recognizing candidate genes and their mutations that cause variations in gene expression and phenotype of an economic trait can help breeders look for genetic markers for specific economic traits. The availability of reference whole-genome assembly of goats, annotated genes, and transcriptomics makes comparative genomics a useful tool for systemic genetic upgradation. Identification and characterization of trait-associated sequence variations and gene will provide powerful means to give positive influences for future goat breeding program.