Comparative Metabolomic Profiling of Eggs from 3 Diverse Chicken Breeds Using GC-MS Analysis

Eggs, as a crucial source of essential nutrients for consumers, possess a high nutritional value owing to their rich composition of vital components essential for human health. While previous research has extensively investigated genetic factors influencing egg quality, there has been a limited focus on exploring the impact of specific strains, particularly within the African context, on the polar metabolite profile of eggs. In this extensive study, we conducted an untargeted analysis of the chemical composition of both albumen and yolk from 3 distinct strains of hens-Blue Holland, Sasso, and Wassache-raised under identical feeding conditions. Utilizing gas chromatography coupled with mass spectrometry (GC-MS), we meticulously examined amino acids, carbohydrates, fatty acids, and other small polar metabolites. In total, 38 and 44 metabolites were identified in the whites and yolk, respectively, of the 3 studied strains. The application of chemometric analysis revealed notable differences in metabolite profiles with 8 relevant metabolites in each egg part. These metabolites include amino acids (N-α-Acetyl-L-lysine, lysine, L-valine, L-Tryptophan), fatty acids (oleic acid, linoleic acid, palmitic acid and stearic acid), and carbohydrates (d-glucose, maltose, lactose). These findings shed light on strain-specific metabolic nuances within eggs, emphasizing potential nutritional implications. The ensuing discussion delves into the diverse metabolic pathways influenced by the identified metabolites, offering insights that contribute to a broader understanding of egg composition and its significance in tailoring nutritional strategies for diverse populations.

Genetic diversity and population structure of cowpea [Vigna unguiculata (L.) Walp.] accessions from Togo using SSR markers

Cowpea [Vigna unguiculata (L.) Walp.] is a crop with significant agronomic and nutritional value. In Togo, the crop is very appreciated by local people. It is the third food habit in Togo after maize and rice. However, several accessions of cowpea cultivated in Togo are now prone to extinction, creating a risk of genetic erosion. It is therefore urgent to assess the genetic diversity of accessions in order to set up a good conservation program. To achieve this, genetic diversity and phylogenetic relationships among 70 accessions of cowpea collected in the five (5) administrative regions of Togo were assessed using Simple Sequence Repeat (SSR) molecular markers. The twenty-eight SSR primers used in this study generated a total of 164 alleles with an average of 5.82 alleles per locus. Polymorphic Information Content (PIC) values ranged from 0.20 to 0.89 with an average value of 0.58. Population structure analysis using model-based revealed that the cowpea germplasm was grouped into two subpopulations. The analysis of molecular variance (AMOVA) revealed that 98% of genetic variation existed among accessions within regions. The fixation index (Fst) value, which was 0.069 was low, indicating relatively low population differentiation. The phylogenetic analysis grouped the 70 accessions into two main groups that can be further divided into four groups independent of their origins. This study provides a foundation for a Togolese cowpea germplasm conservation program and can serve for the selection of parental material for further studies aimed at the genetic improvement of local germplasm.

Study of the Sars-CoV-2 genomic data generation to evaluate the introduction of genomics in epidemiological surveillance and public health decision making

Introduction

the limited number of equipped laboratories and the lack of expertise left Africa lagging behind in terms of contribution in genomic data generation. The COVID-19 pandemic has drawn the attention of all public health stakeholders so that it can be used as a marker of the efforts that public health systems can produced. The main purpose of the present analytical study was to evaluate the contribution of the African continent in the genomic surveillance of SARS-CoV-2.

Methods

data from the two most popular genomic databases on SARS-CoV-2 (GISAID EpiCov and NCBI Virus) were extracted and analyzed. Comparisons were made using the sequencing ratio which represents the number of genomic sequence published over one thousands confirmed cases.

Results

considering continental blocks, the Africa occupied the fourth place after Oceania, Europe and North America based on sequencing ratios. However, when the considered comparison parameter is the number of sequences, the African continent was the fifth contributor after Europe, North America, Asia and South America.

Conclusion

the study showed that African countries have effectively integrated the genomic data generation in the public health response strategies but the effective use of these data for a perfect surveillance is not clearly established. There is a need for capacity building in genomic data analyses for a better response to public health threats in Africa.

Genome-wide quantitative trait loci mapping on Verticillium wilt resistance in 300 chromosome segment substitution lines from Gossypium hirsutum × Gossypium barbadense

Cotton Verticillium wilt (VW) is a devastating disease seriously affecting fiber yield and quality, and the most effective and economical prevention measure at present is selection and extension of Gossypium varieties harboring high resistance to VW. However, multiple attempts to improve the VW resistance of the most widely cultivated upland cottons have made little significant progress. The introduction of chromosome segment substitution lines (CSSLs) provide the practical solutions for merging the superior genes related with high yield and wide adaptation from Gossypium hirsutum and VW resistance and the excellent fiber quality from Gossypium barbadense. In this study, 300 CSSLs were chosen from the developed BC5F3:5 CSSLs constructed from CCRI36 (G. hirsutum) and Hai1 (G. barbadense) to conduct quantitative trait locus (QTL) mapping of VW resistance, and a total of 40 QTL relevant to VW disease index (DI) were identified. Phenotypic data were obtained from a 2-year investigation in two fields with two replications per year. All the QTL were distributed on 21 chromosomes, with phenotypic variation of 1.05%-10.52%, and 21 stable QTL were consistent in at least two environments. Based on a meta-analysis, 34 novel QTL were identified, while 6 loci were consistent with previously identified QTL. Meanwhile, 70 QTL hotspot regions were detected, including 44 novel regions. This study concentrates on QTL identification and screening for hotspot regions related with VW in the 300 CSSLs, and the results lay a solid foundation not only for revealing the genetic and molecular mechanisms of VW resistance but also for further fine mapping, gene cloning and molecular designing in breeding programs for resistant cotton varieties.

Association Analysis of Salt Tolerance in Asiatic cotton (Gossypium arboretum) with SNP Markers

Salinity is not only a major environmental factor which limits plant growth and productivity, but it has also become a worldwide problem. However, little is known about the genetic basis underlying salt tolerance in cotton. This study was carried out to identify marker-trait association signals of seven salt-tolerance-related traits and one salt tolerance index using association analysis for 215 accessions of Asiatic cotton. According to a comprehensive index of salt tolerance (CIST), 215 accessions were mainly categorized into four groups, and 11 accessions with high salinity tolerance were selected for breeding. Genome-wide association studies (GWAS) revealed nine SNP rich regions significantly associated with relative fresh weight (RFW), relative stem length (RSL), relative water content (RWC) and CIST. The nine SNP rich regions analysis revealed 143 polymorphisms that distributed 40 candidate genes and significantly associated with salt tolerance. Notably, two SNP rich regions on chromosome 7 were found to be significantly associated with two salinity related traits, RFW and RSL, by the threshold of −log₁₀P ≥ 6.0, and two candidate genes (Cotton_A_37775 and Cotton_A_35901) related to two key SNPs (Ca7_33607751 and Ca7_77004962) were possibly associated with salt tolerance in G. arboreum. These can provide fundamental information which will be useful for future molecular breeding of cotton, in order to release novel salt tolerant cultivars.

Quantitative Trait Locus Mapping for Verticillium wilt Resistance in an Upland Cotton Recombinant Inbred Line Using SNP-Based High Density Genetic Map

Verticillium wilt (VW) caused by Verticillium dahlia Kleb is one of the most destructive diseases of cotton. Numerous efforts have been made to improve the resistance of upland cotton against VW, with little progress achieved due to the paucity of upland cotton breeding germplasms with high level of resistance to VW. Gossypium barbadense was regarded as more resistant compared to upland cotton; however, it is difficult to apply the resistance from G. barbadense to upland cotton improvement because of the hybrid breakdown and the difficulty to fix resistant phenotype in their interspecific filial. Here we reported QTLs related to VW resistance identified in upland cotton based on 1 year experiment in greenhouse with six replications and 4 years investigations in field with two replications each year. In total, 119 QTLs of disease index (DI) and of disease incidence (DInc) were identified on 25 chromosome of cotton genome except chromosome 13 (c13). For DI, 62 QTLs explaining 3.7-12.2% of the observed phenotypic variations were detected on 24 chromosomes except c11 and c13. For DInc, 59 QTLs explaining 2.3-21.30% of the observed PV were identified on 19 chromosomes except c5, c8, c12-c13, c18-c19, and c26. Seven DI QTLs were detected to be stable in at least environments, among which six have sGK9708 alleles, while 28 DInc QTLs were detected to be stable in at least environments. Eighteen QTL clusters containing 40 QTLs were identified on 13 chromosomes (c1-c4, c6-c7, c10, c14, c17 c20-c22, and c24-c25). Most of the stable QTLs aggregated into these clusters. These QTLs and clusters identification can be an important step toward Verticillium wilt resistant gene cloning in upland cotton and provide useful information to understand the complex genetic bases of Verticillium wilt resistance.

Construction of a high-density genetic map by specific locus amplified fragment sequencing (SLAF-seq) and its application to Quantitative Trait Loci (QTL) analysis for boll weight in upland cotton (Gossypium hirsutum.)

BACKGROUND

Upland Cotton (Gossypium hirsutum) is one of the most important worldwide crops it provides natural high-quality fiber for the industrial production and everyday use. Next-generation sequencing is a powerful method to identify single nucleotide polymorphism markers on a large scale for the construction of a high-density genetic map for quantitative trait loci mapping.

RESULTS

In this research, a recombinant inbred lines population developed from two upland cotton cultivars 0-153 and sGK9708 was used to construct a high-density genetic map through the specific locus amplified fragment sequencing method. The high-density genetic map harbored 5521 single nucleotide polymorphism markers which covered a total distance of 3259.37 cM with an average marker interval of 0.78 cM without gaps larger than 10 cM. In total 18 quantitative trait loci of boll weight were identified as stable quantitative trait loci and were detected in at least three out of 11 environments and explained 4.15-16.70 % of the observed phenotypic variation. In total, 344 candidate genes were identified within the confidence intervals of these stable quantitative trait loci based on the cotton genome sequence. These genes were categorized based on their function through gene ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis and eukaryotic orthologous groups analysis.

CONCLUSIONS

This research reported the first high-density genetic map for Upland Cotton (Gossypium hirsutum) with a recombinant inbred line population using single nucleotide polymorphism markers developed by specific locus amplified fragment sequencing. We also identified quantitative trait loci of boll weight across 11 environments and identified candidate genes within the quantitative trait loci confidence intervals. The results of this research would provide useful information for the next-step work including fine mapping, gene functional analysis, pyramiding breeding of functional genes as well as marker-assisted selection.

Identification of stable quantitative trait loci (QTLs) for fiber quality traits across multiple environments in Gossypium hirsutum recombinant inbred line population

BACKGROUND

The identification of quantitative trait loci (QTLs) that are stable and consistent across multiple environments and populations plays an essential role in marker-assisted selection (MAS). In the present study, we used 28,861 simple sequence repeat (SSR) markers, which included 12,560 Gossypium raimondii (D genome) sequence-based SSR markers to identify polymorphism between two upland cotton strains 0-153 and sGK9708. A total of 851 polymorphic primers were finally selected and used to genotype 196 recombinant inbred lines (RIL) derived from a cross between 0 and 153 and sGK9708 and used to construct a linkage map. The RIL population was evaluated for fiber quality traits in six locations in China for five years. Stable QTLs identified in this intraspecific cross could be used in future cotton breeding program and with fewer obstacles.

RESULTS

The map covered a distance of 4,110 cM, which represents about 93.2 % of the upland cotton genome, and with an average distance of 5.2 cM between adjacent markers. We identified 165 QTLs for fiber quality traits, of which 47 QTLs were determined to be stable across multiple environments. Most of these QTLs aggregated into clusters with two or more traits. A total of 30 QTL clusters were identified which consisted of 103 QTLs. Sixteen clusters in the At sub-genome comprised 44 QTLs, whereas 14 clusters in the Dt sub-genome that included 59 QTLs for fiber quality were identified. Four chromosomes, including chromosome 4 (c4), c7, c14, and c25 were rich in clusters harboring 5, 4, 5, and 6 clusters respectively. A meta-analysis was performed using Biomercator V4.2 to integrate QTLs from 11 environmental datasets on the RIL populations of the above mentioned parents and previous QTL reports. Among the 165 identified QTLs, 90 were identified as common QTLs, whereas the remaining 75 QTLs were determined to be novel QTLs. The broad sense heritability estimates of fiber quality traits were high for fiber length (0.93), fiber strength (0.92), fiber micronaire (0.85), and fiber uniformity (0.80), but low for fiber elongation (0.27). Meta-clusters on c4, c7, c14 and c25 were identified as stable QTL clusters and were considered more valuable in MAS for the improvement of fiber quality of upland cotton.

CONCLUSION

Multiple environmental evaluations of an intraspecific RIL population were conducted to identify stable QTLs. Meta-QTL analyses identified a common chromosomal region that plays an important role in fiber development. Therefore, QTLs identified in the present study are an ideal candidate for MAS in cotton breeding programs to improve fiber quality.

Identification of stable quantitative trait loci (QTLs) for fiber quality traits across multiple environments in Gossypium hirsutum recombinant inbred line population

BACKGROUND

The identification of quantitative trait loci (QTLs) that are stable and consistent across multiple environments and populations plays an essential role in marker-assisted selection (MAS). In the present study, we used 28,861 simple sequence repeat (SSR) markers, which included 12,560 Gossypium raimondii (D genome) sequence-based SSR markers to identify polymorphism between two upland cotton strains 0-153 and sGK9708. A total of 851 polymorphic primers were finally selected and used to genotype 196 recombinant inbred lines (RIL) derived from a cross between 0 and 153 and sGK9708 and used to construct a linkage map. The RIL population was evaluated for fiber quality traits in six locations in China for five years. Stable QTLs identified in this intraspecific cross could be used in future cotton breeding program and with fewer obstacles.

RESULTS

The map covered a distance of 4,110 cM, which represents about 93.2 % of the upland cotton genome, and with an average distance of 5.2 cM between adjacent markers. We identified 165 QTLs for fiber quality traits, of which 47 QTLs were determined to be stable across multiple environments. Most of these QTLs aggregated into clusters with two or more traits. A total of 30 QTL clusters were identified which consisted of 103 QTLs. Sixteen clusters in the At sub-genome comprised 44 QTLs, whereas 14 clusters in the Dt sub-genome that included 59 QTLs for fiber quality were identified. Four chromosomes, including chromosome 4 (c4), c7, c14, and c25 were rich in clusters harboring 5, 4, 5, and 6 clusters respectively. A meta-analysis was performed using Biomercator V4.2 to integrate QTLs from 11 environmental datasets on the RIL populations of the above mentioned parents and previous QTL reports. Among the 165 identified QTLs, 90 were identified as common QTLs, whereas the remaining 75 QTLs were determined to be novel QTLs. The broad sense heritability estimates of fiber quality traits were high for fiber length (0.93), fiber strength (0.92), fiber micronaire (0.85), and fiber uniformity (0.80), but low for fiber elongation (0.27). Meta-clusters on c4, c7, c14 and c25 were identified as stable QTL clusters and were considered more valuable in MAS for the improvement of fiber quality of upland cotton.

CONCLUSION

Multiple environmental evaluations of an intraspecific RIL population were conducted to identify stable QTLs. Meta-QTL analyses identified a common chromosomal region that plays an important role in fiber development. Therefore, QTLs identified in the present study are an ideal candidate for MAS in cotton breeding programs to improve fiber quality.

High Resolution Consensus Mapping of Quantitative Trait Loci for Fiber Strength, Length and Micronaire on Chromosome 25 of the Upland Cotton (Gossypium hirsutum L.)

Cotton (Gossypium hirsutum L.) is an important agricultural crop that provides renewable natural fiber resources for the global textile industry. Technological developments in the textile industry and improvements in human living standards have increased the requirement for supplies and better quality cotton. Upland cotton 0-153 is an elite cultivar harboring strong fiber strength genes. To conduct quantitative trait locus (QTL) mapping for fiber quality in 0-153, we developed a population of 196 recombinant inbred lines (RILs) from a cross between 0-153 and sGK9708. The fiber quality traits in 11 environments were measured and a genetic linkage map of chromosome 25 comprising 210 loci was constructed using this RIL population, mainly using simple sequence repeat markers and single nucleotide polymorphism markers. QTLs were identified across diverse environments using the composite interval mapping method. A total of 37 QTLs for fiber quality traits were identified on chromosome 25, of which 17 were stably expressed in at least in two environments. A stable fiber strength QTL, qFS-chr25-4, which was detected in seven environments and was located in the marker interval between CRI-SNP120491 and BNL2572, could explain 6.53%-11.83% of the observed phenotypic variations. Meta-analysis also confirmed the above QTLs with previous reports. Application of these QTLs could contribute to improving fiber quality and provide information for marker-assisted selection.