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Age-related macular degeneration (AMD), the most prevalent visual disorder among the elderly, is confirmed as a multifactorial disease. Studies demonstrated that genetic factors play an essential role in its pathogenesis. Our study aimed to make a relatively comprehensive study about biological functions of AMD related genes and crosstalk of their enriched pathways. 1691 AMD genetic studies were reviewed, GO enrichment and pathway crosstalk analyses were conducted to elucidate the biological features of these genes and to demonstrate the pathways that these genes participate. Moreover, we identified novel AMD-specific genes using shortest path algorithm in the context of human interactome. We retrieved 176 significantly AMD-related genes. GO results showed that the most significant term in each of these three GO categories was: signaling receptor binding (PBH = 4.835 × 10-7), response to oxygen-containing compound (PBH = 2.764 × 10-21), and extracellular space (PBH = 2.081 × 10-19). The pathway enrichment analysis showed that complement pathway is the most enriched. The pathway crosstalk study showed that the pathways could be divided into two main modules. These two modules were connected by cytokine-cytokine receptor interaction pathway. 42 unique genes potentially participating AMD development were obtained. The aberrant expression of the mRNA of FASN and LRP1 were validated in AMD cell and mouse models. Collectively, our study carried out a comprehensive analysis based on genetic association study of AMD and put forward several evidence-based genes for future study of AMD. [ABSTRACT FROM AUTHOR]

Invertases (INVs) can irreversibly hydrolyze sucrose into fructose and glucose, which play principal roles in carbon metabolism and responses to various stresses in plants. However, little is known about the INV family in bamboos, especially their potential function in drought stress. In this study, 29 PeINVs were identified in moso bamboo (Phyllostachys edulis). They were clustered into alkaline/neutral invertase (NINV) and acid invertase (AINV) groups based on the gene structures, conserved motifs, and phylogenetic analysis results. The collinearity analysis showed nine segmental duplication pairs within PeINVs, and 25 pairs were detected between PeINVs and OsINVs. PeINVs may have undergone strong purification selection during evolution, and a variety of stress and phytohormone-related regulatory elements were found in the promoters of PeINVs. The tissue-specific expression analysis showed that PeINVs were differentially expressed in various moso bamboo tissues, which suggested that they showed functional diversity. Both the RNA-seq and quantitative real-time PCR results indicated that four PeINVs were significantly upregulated under drought stress. Co-expression network and Pearson’s correlation coefficient analyses showed that these PeINVs co-expressed positively with sugar and water transport genes (SWTGs), and the changes were consistent with sugar content. Overall, we speculate that the identified PeINVs are spatiotemporally expressed, which enables them to participate in moso bamboo growth and development. Furthermore, PeINVs, together with SWTGs, also seem to play vital roles in the response to drought stress. These results provide a comprehensive information resource for PeINVs, which will facilitate further study of the molecular mechanism underlying PeINVs involvement in the response to drought stress in moso bamboo.

BackgroundIn the evolutionary time scale, selection shapes the genetic variation and alters the architecture of genome in the organisms. Selection leaves detectable signatures at the genomic coordinates that provide clues about the protein-coding regions. Sahiwal is a valuable indicine cattle adapted to tropical environments with desirable milk attributes. Insights into the genomic regions under putative selection may reveal the molecular mechanisms affecting the quantitative and other important traits. To understand this, the present investigation was undertaken to explore signatures of selection in the genome of Sahiwal cattle using a medium-density genotyping INDUS chip.ResultDe-correlated composite of multiple selection signals (DCMS), which combines five different univariate statistics, was computed in the dataset to detect the signatures of selection in the Sahiwal genome. Gene annotations, Quantitative Trait Loci (QTL) enrichment, and functional analyses were carried out for the identification of significant genomic regions. A total of 117 genes were identified, which affect a number of important economic traits. The QTL enrichment analysis highlighted 14 significant [False Discovery Rate (FDR)-corrected p-value ≤ 0.05] regions on chromosomes BTA 1, 3, 6, 11, 20, and 21. The top three enriched QTLs were found on BTA 6, 20, and 23, which are associated with exterior, health, milk production, and reproduction traits. The present study on selection signatures revealed some key genes related with coat color (PDGFRA, KIT, and KDR), facial pigmentation (LEF), milk fat percent (MAP3K1, HADH, CYP2U1, and SGMS2), sperm membrane integrity (OSTC), lactation persistency (MRPS30, NNT, CCL28, HMGCS1, NIM1K, ZNF131, and CCDC152), milk yield (GHR and ZNF469), reproduction (NKX2-1 and DENND1A), and bovine tuberculosis susceptibility (RNF144B and PAPSS1). Further analysis of candidate gene prioritization identified four hub genes, viz., KIT, KDR, MAP3K1, and LEF, which play a role in coat color, facial pigmentation, and milk fat percentage in cattle. Gene enrichment analysis revealed significant Gene ontology (GO) terms related to breed-specific coat color and milk fat percent.ConclusionThe key candidate genes and putative genomic regions associated with economic traits were identified in Sahiwal using single nucleotide polymorphism data and the DCMS method. It revealed selection for milk production, coat color, and adaptability to tropical climate. The knowledge about signatures of selection and candidate genes affecting phenotypes have provided a background information that can be further utilized to understand the underlying mechanism involved in these traits in Sahiwal cattle.

Invertases (INVs) can irreversibly hydrolyze sucrose into fructose and glucose, which play principal roles in carbon metabolism and responses to various stresses in plants. However, little is known about the INV family in bamboos, especially their potential function in drought stress. In this study, 29 PeINV s were identified in moso bamboo (Phyllostachys edulis). They were clustered into alkaline/neutral invertase (NINV) and acid invertase (AINV) groups based on the gene structures, conserved motifs, and phylogenetic analysis results. The collinearity analysis showed nine segmental duplication pairs within PeINV s, and 25 pairs were detected between PeINV s and OsINV s. PeINV s may have undergone strong purification selection during evolution, and a variety of stress and phytohormone-related regulatory elements were found in the promoters of PeINV s. The tissue-specific expression analysis showed that PeINV s were differentially expressed in various moso bamboo tissues, which suggested that they showed functional diversity. Both the RNA-seq and quantitative real-time PCR results indicated that four PeINV s were significantly upregulated under drought stress. Co-expression network and Pearson's correlation coefficient analyses showed that these PeINV s co-expressed positively with sugar and water transport genes (SWTG s), and the changes were consistent with sugar content. Overall, we speculate that the identified PeINV s are spatiotemporally expressed, which enables them to participate in moso bamboo growth and development. Furthermore, PeINV s, together with SWTG s, also seem to play vital roles in the response to drought stress. These results provide a comprehensive information resource for PeINV s, which will facilitate further study of the molecular mechanism underlying PeINV s involvement in the response to drought stress in moso bamboo. [ABSTRACT FROM AUTHOR]

Background: In the evolutionary time scale, selection shapes the genetic variation and alters the architecture of genome in the organisms. Selection leaves detectable signatures at the genomic coordinates that provide clues about the protein-coding regions. Sahiwal is a valuable indicine cattle adapted to tropical environments with desirable milk attributes. Insights into the genomic regions under putative selection may reveal the molecular mechanisms affecting the quantitative and other important traits. To understand this, the present investigation was undertaken to explore signatures of selection in the genome of Sahiwal cattle using a medium-density genotyping INDUS chip. Result: De-correlated composite of multiple selection signals (DCMS), which combines five different univariate statistics, was computed in the dataset to detect the signatures of selection in the Sahiwal genome. Gene annotations, Quantitative Trait Loci (QTL) enrichment, and functional analyses were carried out for the identification of significant genomic regions. A total of 117 genes were identified, which affect a number of important economic traits. The QTL enrichment analysis highlighted 14 significant [False Discovery Rate (FDR)-corrected p -value ≤ 0.05] regions on chromosomes BTA 1, 3, 6, 11, 20, and 21. The top three enriched QTLs were found on BTA 6, 20, and 23, which are associated with exterior, health, milk production, and reproduction traits. The present study on selection signatures revealed some key genes related with coat color (PDGFRA, KIT , and KDR), facial pigmentation (LEF), milk fat percent (MAP3K1, HADH, CYP2U1 , and SGMS2), sperm membrane integrity (OSTC), lactation persistency (MRPS30, NNT, CCL28, HMGCS1, NIM1K, ZNF131 , and CCDC152), milk yield (GHR and ZNF469), reproduction (NKX2-1 and DENND1A), and bovine tuberculosis susceptibility (RNF144B and PAPSS1). Further analysis of candidate gene prioritization identified four hub genes, viz., KIT, KDR, MAP3K1 , and LEF , which play a role in coat color, facial pigmentation, and milk fat percentage in cattle. Gene enrichment analysis revealed significant Gene ontology (GO) terms related to breed-specific coat color and milk fat percent. Conclusion: The key candidate genes and putative genomic regions associated with economic traits were identified in Sahiwal using single nucleotide polymorphism data and the DCMS method. It revealed selection for milk production, coat color, and adaptability to tropical climate. The knowledge about signatures of selection and candidate genes affecting phenotypes have provided a background information that can be further utilized to understand the underlying mechanism involved in these traits in Sahiwal cattle. [ABSTRACT FROM AUTHOR]

The genetic resources available for the commercially important fish species Yellowtail kingfish (YTK) (Seriola lalandi) are relative sparse. To overcome this, we aimed (1) to develop a linkage map for this species, and (2) to identify markers/variants associated with economically important traits in kingfish (with an emphasis on body weight). Genetic and genomic analyses were conducted using 13,898 single nucleotide polymorphisms (SNPs) generated from a new high-throughput genotyping by sequencing platform, Diversity Arrays Technology (DArTseqTM) in a pedigreed population comprising 752 animals. The linkage analysis enabled to map about 4,000 markers to 24 linkage groups (LGs), with an average density of 3.4 SNPs per cM. The linkage map was integrated into a genome-wide association study (GWAS) and identified six variants/SNPs associated with body weight (P < 5e-8) when a multi-locus mixed model was used. Two out of the six significant markers were mapped to LGs 17 and 23, and collectively they explained 5.8% of the total genetic variance. It is concluded that the newly developed linkage map and the significantly associated markers with body weight provide fundamental information to characterize genetic architecture of growth-related traits in this population of YTK S. lalandi.

The purpose of this study was to determine if the set of genomic regions inferred as accounting for the majority of genetic variation in quantitative traits remain stable over multiple generations of selection. The data set contained phenotypes for five generations of broiler chicken for body weight, breast meat, and leg score. The population consisted of 294,632 animals over 5 generations and also included genotypes of 41,036 SNP for 4,866 animals, after quality control. The SNP effects were calculated by a GWAS type analysis using single step genomic BLUP approach for generations 1 to 3, 2 to 4, 3 to 5, and 1to 5. Variances were calculated for windows of 20 SNP. The top ten windows for each trait that explained the largest fraction of the genetic variance across generations were examined. Across generations, the top 10 windows explained more than 0.5% but less than 1 % of the total variance. Also, the pattern of the windows was not consistent across generations. The windows that explained the greatest variance changed greatly among the combinations of generations, with a few exceptions. In many cases, a window identified as top for one combination, explained less than 0.1% for the other combinations. We conclude that identification of top SNP windows for a population may have little predictive power for genetic selection in the following generations for the traits here evaluated.

The purpose of this study was to determine if the set of genomic regions inferred as accounting for the majority of genetic variation in quantitative traits remain stable over multiple generations of selection. The data set contained phenotypes for five generations of broiler chicken for body weight, breast meat, and leg score. The population consisted of 294,632 animals over five generations and also included genotypes of 41,036 single nucleotide polymorphism (SNP) for 4,866 animals, after quality control. The SNP effects were calculated by a GWAS type analysis using single step genomic BLUP approach for generations 1-3, 2-4, 3-5, and 1-5. Variances were calculated for windows of 20 SNP. The top ten windows for each trait that explained the largest fraction of the genetic variance across generations were examined. Across generations, the top 10 windows explained more than 0.5% but less than 1% of the total variance. Also, the pattern of the windows was not consistent across generations. The windows that explained the greatest variance changed greatly among the combinations of generations, with a few exceptions. In many cases, a window identified as top for one combination, explained less than 0.1% for the other combinations.We conclude that identification of top SNP windows for a population may have little predictive power for genetic selection in the following generations for the traits here evaluated. [ABSTRACT FROM AUTHOR]

Age-related macular degeneration (AMD), the most prevalent visual disorder among the elderly, is confirmed as a multifactorial disease. Studies demonstrated that genetic factors play an essential role in its pathogenesis. Our study aimed to make a relatively comprehensive study about biological functions of AMD related genes and crosstalk of their enriched pathways. 1691 AMD genetic studies were reviewed, GO enrichment and pathway crosstalk analyses were conducted to elucidate the biological features of these genes and to demonstrate the pathways that these genes participate. Moreover, we identified novel AMD-specific genes using shortest path algorithm in the context of human interactome. We retrieved 176 significantly AMD-related genes. GO results showed that the most significant term in each of these three GO categories was: signaling receptor binding (P BH = 4.835 × 10 -7 ), response to oxygen-containing compound (P BH = 2.764 × 10 -21 ), and extracellular space (P BH = 2.081 × 10 -19 ). The pathway enrichment analysis showed that complement pathway is the most enriched. The pathway crosstalk study showed that the pathways could be divided into two main modules. These two modules were connected by cytokine-cytokine receptor interaction pathway. 42 unique genes potentially participating AMD development were obtained. The aberrant expression of the mRNA of FASN and LRP1 were validated in AMD cell and mouse models. Collectively, our study carried out a comprehensive analysis based on genetic association study of AMD and put forward several evidence-based genes for future study of AMD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Ren and Yu.)

The purpose of this study was to determine if the set of genomic regions inferred as accounting for the majority of genetic variation in quantitative traits remain stable over multiple generations of selection. The data set contained phenotypes for five generations of broiler chicken for body weight, breast meat, and leg score. The population consisted of 294,632 animals over five generations and also included genotypes of 41,036 single nucleotide polymorphism (SNP) for 4,866 animals, after quality control. The SNP effects were calculated by a GWAS type analysis using single step genomic BLUP approach for generations 1-3, 2-4, 3-5, and 1-5. Variances were calculated for windows of 20 SNP. The top ten windows for each trait that explained the largest fraction of the genetic variance across generations were examined. Across generations, the top 10 windows explained more than 0.5% but less than 1% of the total variance. Also, the pattern of the windows was not consistent across generations. The windows that explained the greatest variance changed greatly among the combinations of generations, with a few exceptions. In many cases, a window identified as top for one combination, explained less than 0.1% for the other combinations. We conclude that identification of top SNP windows for a population may have little predictive power for genetic selection in the following generations for the traits here evaluated.