HOMER for Analysis of Hi-C Data and Assessment of Composite Structure of the X Chromosome.

Hi-C reads, which represent ligation events between different regions of the genome, must be processed into matrices of interaction frequencies for downstream analysis. Here, I describe a procedure for mapping Hi-C reads to the genome and conversion of mapped reads into the HOMER tag directory format and interaction matrix format for visualization with Juicebox. The method is demonstrated for the mouse composite X chromosome in which reads from the active and inactive X chromosomes are combined after mock DMSO treatment or targeted degradation of cohesin.

Micro-C Analysis Workflow Using Pairtools and Juicer.

Three-dimensional (3D) chromosome structures are closely related to various chromosomal functions, and deep analysis of the structures is crucial for the elucidation of the functions. In recent years, chromosome conformation capture (3C) techniques combined with next-generation sequencing analysis have been developed to comprehensively reveal 3D chromosome structures. Micro-C is one such method that can detect the structures at nucleosome resolution. In this chapter, I provide a basic method for Micro-C analysis. I present and discuss a series of data analyses ranging from mapping to basic downstream analyses, including loop detection.

Read Mapping for Hi-C Analysis.

Hi-C is a popular ligation-based technique to detect 3D physical chromosome structure within the nucleus using cross-linking and next-generation sequencing. As an unbiased genome-wide assay based on chromosome conformation capture, it provides rich insights into chromosome structure, dynamic chromosome folding and interactions, and the regulatory state of a cell. Bioinformatics analyses of Hi-C data require dedicated protocols as most genome alignment tools assume that both paired-end reads will map to the same chromosome, resulting in large two-dimensional matrices as processed data. Here, we outline the necessary steps to generate high-quality aligned Hi-C data by separately mapping each read while correcting for biases from restriction enzyme digests. We introduce our own custom open-source pipeline, which enables users to select an aligner of their choosing with high accuracy and performance. This enables users to generate high-resolution datasets with fast turnaround and fewer unmapped reads. Finally, we discuss recent innovations in experimental techniques, bioinformatics techniques, and their applications in clinical testing for diagnostics.

Processing and Visualization of Protec-Seq Data for the Generation of Calibrated, Genome-Wide Double Double-Strand Break (dDSB) Maps.

This chapter describes the computational pipeline for the processing and visualization of Protec-Seq data, a method for purification and genome-wide mapping of double-stranded DNA protected by a specific protein at both ends. In the published case, the protein of choice was Saccharomyces cerevisiae Spo11, a conserved topoisomerase-like enzyme that makes meiotic double-strand breaks (DSBs) to initiate homologous recombination, ensuring proper segregation of homologous chromosomes and fertility. The isolated DNA molecules were thus termed double DSB (dDSB) fragments and were found to represent 34 to several hundred base-pair long segments that are generated by Spo11 and are enriched at DSB hotspots, which are sites of topological stress. In order to allow quantitative comparisons between dDSB profiles across experiments, we implemented calibrated chromatin immunoprecipitation sequencing (ChIP-Seq) using the meiosis-competent yeast species Saccharomyces kudriavzevii as calibration strain. Here, we provide a detailed description of the computational methods for processing, analyzing, and visualizing Protec-Seq data, comprising the download of the raw data, the calibrated genome-wide alignments, and the scripted creation of either arc plots or Hi-C-style heatmaps for the illustration of chromosomal regions of interest. The workflow is based on Linux shell scripts (including wrappers for publicly available, open-source software) as well as R scripts and is highly customizable through its modular structure.

Fine-mapping of a major QTL controlling plant height by BSA-seq and transcriptome sequencing in cotton.

KEY MESSAGE: GhSOT (GH_D05G3950) plays a negative role in regulating plant height development by modulating the GA signaling. Plant height is an important indicator affecting mechanical harvesting for cotton. Therefore, understanding the genes associated with the plant height is crucial for cotton breeding and production. In this study, we used bulk segregant analysis sequencing to identify a new quantitative trait locu (QTL) called qPH5.1, which is linked to plant height. Local QTL mapping using seven kompetitive allele-specific PCR (KASP) markers and linkage analysis successfully narrowed down qPH5.1 to ~ 0.34 Mb region harbored five candidate genes. Subsequently, RNA sequencing (RNA-seq) analysis and examination of expression patterns revealed that GhSOT exhibited the highest likelihood of being the candidate gene responsible for the plant height at this locus. Seven SNP site variations were identified in the GhSOT promoter between the two parents, and Luciferase experiments confirmed that the promoter of GhSOT from cz3 enhances downstream gene expression more effectively. Additionally, suppression of GhSOT in cz3 resulted in the restoration of plant height, further emphasizing the functional significance of this gene. Application of exogenous gibberellin acid (GA) significantly restored plant height in cz3, as demonstrated by RNA-seq analysis and exogenous hormone treatment, which revealed alterations in genes associated with GA signaling pathways. These results reveal GhSOT is a key gene controlling plant height, which may affect plant height by regulating GA signaling.

Map-based cloning of LPD, a major gene positively regulates leaf prickle development in eggplant.

KEY MESSAGE: A critical gene for leaf prickle development (LPD) in eggplant was mapped on chromosome E06 and was confirmed to be SmARF10B through RNA interference using a new genetic transformation technique called SACI developed in this study Prickles on eggplant pose challenges for agriculture and are undesirable in cultivated varieties. This study aimed to uncover the genetic mechanisms behind prickle formation in eggplant. Using the F2 and F2:3 populations derived from a cross between the prickly wild eggplant, YQ, and the prickle-free cultivated variety, YZQ, we identified a key genetic locus (LPD, leaf prickle development) on chromosome E06 associated with leaf prickle development through BSA-seq and QTL mapping. An auxin response factor gene, SmARF10B, was predicted as the candidate gene as it exhibited high expression in YQ's mature leaves, while being significantly low in YZQ. Downregulating SmARF10B in YQ through RNAi using a simple and efficient Agrobacterium-mediated genetic transformation method named Seedling Apical Cut Infection (SACI) developed in this study substantially reduced the size and density of leaf prickles, confirming the role of this gene in prickle development. Besides, an effective SNP was identified in SmARF10B, resulting in an amino acid change between YQ and YZQ. However, this SNP did not consistently correlate with prickle formation in eight other eggplant materials examined. This study sheds light on the pivotal role of SmARF10B in eggplant prickle development and introduces a new genetic transformation method for eggplant, paving the way for future research in this field.

Identification and characterization of sulphotransferase (SOT) genes for tolerance against drought and heat in wheat and six related species.

BACKGROUND: Sulphotransferase (SOT) enzyme (encoded by a conserved family of SOT genes) is involved in sulphonation of a variety of compounds, through transfer of a sulphuryl moiety from 3'phosphoadenosine- 5'phosphosulphate (PAPS) to a variety of secondary metabolites. The PAPS itself is derived from 3'adenosine-5'phosphosulphate (APS) that is formed after uptake of sulphate ions from the soil. The process provides tolerance against abiotic stresses like drought and heat in plants. Therefore, a knowledge of SOT genes in any crop may help in designing molecular breeding methods for improvement of tolerance for drought and heat. METHODS: Sequences of rice SOT genes and SOT domain (PF00685) of corresponding proteins were both used for identification of SOT genes in wheat and six related species (T. urartu, Ae. tauschii, T. turgidum, Z. mays, B. distachyon and Hordeum vulgare), although detailed analysis was conducted only in wheat. The wheat genes were mapped on individual chromosomes and also subjected to synteny and collinearity analysis. The proteins encoded by these genes were examined for the presence of a complete SOT domain using 'Conserved Domain Database' (CDD) search tool at NCBI. RESULTS: In wheat, 107 TaSOT genes, ranging in length from 969 bp to 7636 bp, were identified and mapped onto individual chromosomes. SSRs (simple sequence repeats), microRNAs, long non-coding RNAs (lncRNAs) and their target sites were also identified in wheat SOT genes. SOT proteins were also studied in detail. An expression assay of TaSOT genes via wheat RNA-seq data suggested engagement of these genes in growth, development and responses to various hormones and biotic/abiotic stresses. CONCLUSIONS: The results of the present study should help in further functional characterization of SOT genes in wheat and other related crops.

Genome-wide association study of fiber quality traits in US upland cotton (Gossypium hirsutum L.).

KEY MESSAGE: A GWAS in an elite diversity panel, evaluated across 10 environments, identified genomic regions regulating six fiber quality traits, facilitating genomics-assisted breeding and gene discovery in upland cotton. In this study, an elite diversity panel of 348 upland cotton accessions was evaluated in 10 environments across the US Cotton Belt and genotyped with the cottonSNP63K array, for a genome-wide association study of six fiber quality traits. All fiber quality traits, upper half mean length (UHML: mm), fiber strength (FS: g tex-1), fiber uniformity (FU: %), fiber elongation (FE: %), micronaire (MIC) and short fiber content (SFC: %), showed high broad-sense heritability (> 60%). All traits except FE showed high genomic heritability. UHML, FS and FU were all positively correlated with each other and negatively correlated with FE, MIC and SFC. GWAS of these six traits identified 380 significant marker-trait associations (MTAs) including 143 MTAs on 30 genomic regions. These 30 genomic regions included MTAs identified in at least three environments, and 23 of them were novel associations. Phenotypic variation explained for the MTAs in these 30 genomic regions ranged from 6.68 to 11.42%. Most of the fiber quality-associated genomic regions were mapped in the D-subgenome. Further, this study confirmed the pleiotropic region on chromosome D11 (UHML, FS and FU) and identified novel co-localized regions on D04 (FU, SFC), D05 (UHML, FU, and D06 UHML, FU). Marker haplotype analysis identified superior combinations of fiber quality-associated genomic regions with high trait values (UHML = 32.34 mm; FS = 32.73 g tex-1; FE = 6.75%). Genomic analyses of traits, haplotype combinations and candidate gene information described in the current study could help leverage genetic diversity for targeted genetic improvement and gene discovery for fiber quality traits in cotton.

Effect of Chromosomal Localization of NGS-Based Markers on Their Applicability for Analyzing Genetic Variation and Population Structure of Hexaploid Triticale.

This study aimed to determine whether using DNA-based markers assigned to individual chromosomes would detect the genetic structures of 446 winter triticale forms originating from two breeding companies more effectively than using the entire pool of markers. After filtering for quality control parameters, 6380 codominant single nucleotide polymorphisms (SNPs) markers and 17,490 dominant diversity array technology (silicoDArT) markers were considered for analysis. The mean polymorphic information content (PIC) values varied depending on the chromosomes and ranged from 0.30 (2R) to 0.43 (7A) for the SNPs and from 0.28 (2A) to 0.35 (6R) for the silicoDArTs. The highest correlation of genetic distance (GD) matrices based on SNP markers was observed among the 5B-5R (0.642), 5B-7B (0.626), and 5A-5R (0.605) chromosomes. When silicoDArTs were used for the analysis, the strongest correlations were found between 5B-5R (0.732) and 2B-5B (0.718). A Bayesian analysis showed that SNPs (total marker pool) allowed for the identification of a more complex structure (K = 4, ΔK = 2460.2) than the analysis based on silicoDArTs (K = 2, ΔK = 128). Triticale lines formed into groups, ranging from two (most of the chromosomes) to four (7A) groups depending on the analyzed chromosome when SNP markers were used for analysis. Linkage disequilibrium (LD) varied among individual chromosomes, ranging from 0.031 for 1A to 0.228 for 7R.

QTL Mapping of Fiber- and Seed-Related Traits in Chromosome Segment Substitution Lines Derived from Gossypium hirsutum × Gossypium darwinii.

A narrow genetic basis limits further the improvement of modern Gossypium hirsutum cultivar. The abundant genetic diversity of wild species provides available resources to solve this dilemma. In the present study, a chromosome segment substitution line (CSSL) population including 553 individuals was established using G. darwinii accession 5-7 as the donor parent and G. hirsutum cultivar CCRI35 as the recipient parent. After constructing a high-density genetic map with the BC1 population, the genotype and phenotype of the CSSL population were investigated. A total of 235 QTLs, including 104 QTLs for fiber-related traits and 132 QTLs for seed-related traits, were identified from four environments. Among these QTLs, twenty-seven QTLs were identified in two or more environments, and twenty-five QTL clusters consisted of 114 QTLs. Moreover, we identified three candidate genes for three stable QTLs, including GH_A01G1096 (ARF5) and GH_A10G0141 (PDF2) for lint percentage, and GH_D01G0047 (KCS4) for seed index or oil content. These results pave way for understanding the molecular regulatory mechanism of fiber and seed development and would provide valuable information for marker-assisted genetic improvement in cotton.

DiffGR: Detecting Differentially Interacting Genomic Regions from Hi-C Contact Maps.

Recent advances in high-throughput chromosome conformation capture (Hi-C) techniques have allowed us to map genome-wide chromatin interactions and uncover higher-order chromatin structures, thereby shedding light on the principles of genome architecture and functions. However, statistical methods for detecting changes in large-scale chromatin organization such as topologically associating domains (TADs) are still lacking. Here, we proposed a new statistical method, DiffGR, for detecting differentially interacting genomic regions at the TAD level between Hi-C contact maps. We utilized the stratum-adjusted correlation coefficient to measure similarity of local TAD regions. We then developed a nonparametric approach to identify statistically significant changes of genomic interacting regions. Through simulation studies, we demonstrated that DiffGR can robustly and effectively discover differential genomic regions under various conditions. Furthermore, we successfully revealed cell type-specific changes in genomic interacting regions in both human and mouse Hi-C datasets, and illustrated that DiffGR yielded consistent and advantageous results compared with state-of-the-art differential TAD detection methods. The DiffGR R package is published under the GNU General Public License (GPL) ≥ 2 license and is publicly available at https://github.com/wmalab/DiffGR.

Determination of single or paired-kernel-rows is controlled by two quantitative loci during maize domestication.

KEY MESSAGE: qPEDS1, a major quantitative trait locus that determines kernel row number during domestication, harbors the proposed causal gene Zm00001d033675, which may affect jasmonic acid biosynthesis and determine the fate of spikelets. Maize domestication has achieved the production of maize with enlarged ears, enhancing grain productivity dramatically. Kernel row number (KRN), an important yield-related trait, has increased from two rows in teosinte to at least eight rows in modern maize. However, the genetic mechanisms underlying this process remain unclear. To understand KRN domestication, we developed a teosinte-maize BC2F7 population by introgressing teosinte into a maize background. We identified one line, Teosinte ear rank1 (Ter1), with only 5-7 kernel rows which is fewer than those in almost all maize inbred lines. We detected two quantitative trait loci underlying Ter1 and fine-mapped the major one to a 300-kb physical interval. Two candidate genes, Zm674 and Zm675, were identified from 26 maize reference genomes and teosinte bacterial artificial chromosome sequences. Finally, we proposed that Ter1 affects jasmonic acid biosynthesis in the developing ear to determine KRN by the fate of spikelets. This study provides novel insights into the genetic and molecular mechanisms underlying KRN domestication and candidates for de novo wild teosinte domestication.

SlJMJ14, identified via QTL­seq and fine mapping, controls flowering time in tomatoes.

KEY MESSAGE: A major QTL, qLF2.1, for flowering time in tomatoes, was fine mapped to chromosome 2 within a 51.37-kb interval, and the SlJMJ14 gene was verified as the causal gene by knockout. Tomato flowering time is an important agronomic trait that affects yield, fruit quality, and environmental adaptation. In this study, the high-generation inbred line 19108 with a late-flowering phenotype was selected for the mapping of the gene that causes late flowering. In the F2 population derived from 19108 (late flowering) × MM (early flowering), we identified a major late-flowering time quantitative trait locus (QTL) using QTL-seq, designated qLF2.1. This QTL was fine mapped to a 51.37-kb genomic interval using recombinant analysis. Through functional analysis of homologous genes, Solyc02g082400 (SlJMJ14), encoding a histone demethylase, was determined to be the most promising candidate gene. Knocking out SlJMJ14 in MM resulted in a flowering time approximately 5-6 days later than that in the wild-type plants. These results suggest that mutational SlJMJ14 is the major QTL for the late-flowering phenotype of the 19108 parental line.

Identification and analysis of low light responsive yield enhancing QTLs in rice.

Rice is one of the major food crops grown globally. However, during the wet season, rice suffers significant yield loss due to reduced light intensity caused by overcast clouds when the light intensity is only around 450-500 µmol/m2/s, compared to 1400-1800 µmol/m2/s in summer. This reduction in light intensity leads to a decrease in seed yield, mainly by limiting tiller or panicle numbers. Yield and its attributing parameters were recorded in one hundred thirty RILs for four consecutive wet seasons in ambient light (AL) and low light (LL, 35% light-cut using white shade net). QTL analysis was performed using Inclusive Composite Interval Mapping (ICIM) with all the phenotypic data and 927 polymorphic SNPs identified by the 7 K Infinium chip. The study identified a large QTL influencing panicle numbers and yield exclusively in lowlight on chromosome 1 (qPNLL1.1, qGYLL1.1) in four consecutive seasons with LOD > 10 and PVE > 30%. The favourable alleles are from the tolerant parent, Swarnaprabha. Another grain yield improving QTL was identified on chromosome 6 (qGYLL6.1), with LOD > 3 in three consecutive seasons. In a diverse rice panel of one hundred seventeen genotypes with five different models, association analysis identified the associated marker for panicle numbers and grain yield in LL, which is also the left marker of the newly identified QTLs for the traits under LL condition. A shade-responsive gene, monoculm 2 (MOC2, LOC_Os01g64660) inside the QTL on chromosome 1, upregulated in the tolerant parent and its QTL-carrying RILs, whereas repressed in the susceptible one. Therefore, due to its significant additive effect and validation across various genotypes, the yield-improving QTL on chromosome 1 can be directly utilised in marker-assisted selection (MAS) for developing shade-tolerant rice. This can also help reduce the yield gap between wet and dry-season rice.

Satellitome Analysis of Adalia bipunctata (Coleoptera): Revealing Centromeric Turnover and Potential Chromosome Rearrangements in a Comparative Interspecific Study.

Eukaryotic genomes exhibit a dynamic interplay between single-copy sequences and repetitive DNA elements, with satellite DNA (satDNA) representing a substantial portion, mainly situated at telomeric and centromeric chromosomal regions. We utilized Illumina next-generation sequencing data from Adalia bipunctata to investigate its satellitome. Cytogenetic mapping via fluorescence in situ hybridization was performed for the most abundant satDNA families. In silico localization of satDNAs was carried out using the CHRISMAPP (Chromosome In Silico Mapping) pipeline on the high-fidelity chromosome-level assembly already available for this species, enabling a meticulous characterization and localization of multiple satDNA families. Additionally, we analyzed the conservation of the satellitome at an interspecific scale. Specifically, we employed the CHRISMAPP pipeline to map the satDNAs of A. bipunctata onto the genome of Adalia decempunctata, which has also been sequenced and assembled at the chromosome level. This analysis, along with the creation of a synteny map between the two species, suggests a rapid turnover of centromeric satDNA between these species and the potential occurrence of chromosomal rearrangements, despite the considerable conservation of their satellitomes. Specific satDNA families in the sex chromosomes of both species suggest a role in sex chromosome differentiation. Our interspecific comparative study can provide a significant advance in the understanding of the repeat genome organization and evolution in beetles.

Cytogenetics and the Revolution of Optical Genome Mapping in the Diagnosis of Diseases.

The study of chromosomal shape, characteristics, and behavior in somatic cell division (mitosis) during growth and development and in germ cell division (meiosis) during reproduction is known as cytogenetics. Many techniques can be used for cytogenetics, including fluorescent in situ hybridization (FISH), spectral karyotyping (SKY), multicolor FISH (M-FISH), microarray, and optical genome mapping (OGM). OGM is a novel genome-wide method that can identify structural variants (SVs) and copy number variants (CNVs) with only one test. Genomic structural information that is difficult to obtain with DNA sequencing can be promptly obtained with OGM, in which large molecule lengths can be mapped at a reasonable cost. OGM is increasingly being used to investigate chromosome abnormalities in genetic disorders and human cancer, but it was first utilized in genome assembly and research. According to recent research, OGM is capable of identifying every clinically significant variation seen in trials using conventional care. OGM is being utilized to identify genomic abnormalities in patients with malignancies and constitutional illnesses. It is regarded as a revolution in the field of cytogenetics. Rather than sequencing DNA, OGM relies on DNA labeling. Currently, the OGM technique with the Saphyr system from Bionano Genomics is a widely utilized platform for cytogenetic analysis. In conclusion, OGM can now be considered a highly reliable method for the identification of chromosomal abnormalities in the diagnosis of tumors and hematological diseases.

A machine learning enhanced EMS mutagenesis probability map for efficient identification of causal mutations in Caenorhabditis elegans.

Chemical mutagenesis-driven forward genetic screens are pivotal in unveiling gene functions, yet identifying causal mutations behind phenotypes remains laborious, hindering their high-throughput application. Here, we reveal a non-uniform mutation rate caused by Ethyl Methane Sulfonate (EMS) mutagenesis in the C. elegans genome, indicating that mutation frequency is influenced by proximate sequence context and chromatin status. Leveraging these factors, we developed a machine learning enhanced pipeline to create a comprehensive EMS mutagenesis probability map for the C. elegans genome. This map operates on the principle that causative mutations are enriched in genetic screens targeting specific phenotypes among random mutations. Applying this map to Whole Genome Sequencing (WGS) data of genetic suppressors that rescue a C. elegans ciliary kinesin mutant, we successfully pinpointed causal mutations without generating recombinant inbred lines. This method can be adapted in other species, offering a scalable approach for identifying causal genes and revitalizing the effectiveness of forward genetic screens.

Genome-wide association study and selective sweep analysis uncover candidate genes controlling curd branch length in cauliflower.

Cauliflower is a distinct subspecies of the Brassica oleracea plants due to its specialized and edible floral organ. Cauliflower curd is composed of enlarged inflorescence meristems that developed by a series of precise molecular regulations. Based solely on the curd solidity, cauliflower is generally classified into two groups (compact-curd and loose-curd), where curd branch length acts as a crucial parameter to determine the curd morphological difference. Herein, to understand the genetic basis of curd branch development, we utilized a total of 298 inbred lines representing two groups of cauliflower to comprehensively investigate the causal genes and regulatory mechanisms. Phylogenetic and population structure analyses revealed that two subgroups could be further categorized into the compact-curd and the loose-curd groups, respectively. Integrating the genotype and phenotype data, we conducted a genome-wide association study for the length of the outermost branch (LOB) and secondary branch (LSB) of the curd. Sixty-four significant loci were identified that are highly associated with curd branch development. Evidence from genome-wide selective sweep analysis (FST and XP-EHH) narrowed down the major signal on chromosome 8 into an approximately 79 kb region which encodes eleven protein-coding genes. After further analysis of haplotypes, transcriptome profiling, and gene expression validation, we finally inferred that BOB08G028680, as a homologous counterpart of AtARR9, might be the causal gene for simultaneously regulating LOB and LSB traits in cauliflower. This result provides valuable information for improving curd solidity in future cauliflower breeding.

Identification and development of functional markers for purple grain genes in durum wheat (Triticum durum Desf.).

KEY MESSAGE: Two allelic variants of Pp-A3 and Pp-B1 were identified in purple durum wheat. Molecular markers at both loci were developed and validated on an independent panel, offering a breakthrough for wheat improvement. Purple wheats are a class of cereals with pigmented kernels of particular interest for their antioxidant and anti-inflammatory properties. Although two complementary loci (Pp-B1 and Pp-A3), responsible for purple pericarp have been pinpointed in bread wheat (Triticum aestivum L.), in durum wheat (Triticum durum Desf.) the causative genes along with functional and non-functional alleles are still unknown. Here, using a quantitative trait loci (QTL) mapping approach on a RIL population derived from purple and non-purple durum wheat genotypes, we identified three major regions on chromosomes 2A, 3A, and 7B explaining the highest phenotypic variation (> 50%). Taking advantage of the Svevo genome, a MYB was reannotated on chromosome 7B and reported as a candidate for Pp-B1. An insertion of ~ 1.6 kb within the first exon led to a non-functional allele (TdPpm1b), whereas the functional allele (TdPpm1a) was characterized and released for the first time in durum wheat. Pp-A3 was instead identified as a duplicated gene, of which only one was functional. The promoter sequencing of the functional allele (TdPpb1a) revealed six 261-bp tandem repeats in purple durum wheat, whereas one unit (TdPpb1b) was found in the yellow once. Functional molecular markers at both loci were developed to precisely discriminate purple and not purple genotypes, representing a valuable resource for selecting superior purple durum lines at early growth stages. Overall, our results expand the understanding of the function of MYB and bHLH activators in durum wheat, paving new ways to explore cis-regulatory elements at the promoter level.

Identification of candidate genes and genomic prediction of soybean fatty acid components in two soybean populations.

Soybean, a source of plant-derived lipids, contains an array of fatty acids essential for health. A comprehensive understanding of the fatty acid profiles in soybean is crucial for enhancing soybean cultivars and augmenting their qualitative attributes. Here, 180 F10 generation recombinant inbred lines (RILs), derived from the cross-breeding of the cultivated soybean variety 'Jidou 12' and the wild soybean 'Y9,' were used as primary experimental subjects. Using inclusive composite interval mapping (ICIM), this study undertook a quantitative trait locus (QTL) analysis on five distinct fatty acid components in the RIL population from 2019 to 2021. Concurrently, a genome-wide association study (GWAS) was conducted on 290 samples from a genetically diverse natural population to scrutinize the five fatty acid components during the same timeframe, thereby aiming to identify loci closely associated with fatty acid profiles. In addition, haplotype analysis and the Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed to predict candidate genes. The QTL analysis elucidated 23 stable QTLs intricately associated with the five fatty acid components, exhibiting phenotypic contribution rates ranging from 2.78% to 25.37%. In addition, GWAS of the natural population unveiled 102 significant loci associated with these fatty acid components. The haplotype analysis of the colocalized loci revealed that Glyma.06G221400 on chromosome 6 exhibited a significant correlation with stearic acid content, with Hap1 showing a markedly elevated stearic acid level compared with Hap2 and Hap3. Similarly, Glyma.12G075100 on chromosome 12 was significantly associated with the contents of oleic, linoleic, and linolenic acids, suggesting its involvement in fatty acid biosynthesis. In the natural population, candidate genes associated with the contents of palmitic and linolenic acids were predominantly from the fatty acid metabolic pathway, indicating their potential role as pivotal genes in the critical steps of fatty acid metabolism. Furthermore, genomic selection (GS) for fatty acid components was conducted using ridge regression best linear unbiased prediction based on both random single nucleotide polymorphisms (SNPs) and SNPs significantly associated with fatty acid components identified by GWAS. GS accuracy was contingent upon the SNP set used. Notably, GS efficiency was enhanced when using SNPs derived from QTL mapping analysis and GWAS compared with random SNPs, and reached a plateau when the number of SNP markers exceeded 3,000. This study thus indicates that Glyma.06G221400 and Glyma.12G075100 are genes integral to the synthesis and regulatory mechanisms of fatty acids. It provides insights into the complex biosynthesis and regulation of fatty acids, with significant implications for the directed improvement of soybean oil quality and the selection of superior soybean varieties. The SNP markers delineated in this study can be instrumental in establishing an efficacious pipeline for marker-assisted selection and GS aimed at improving soybean fatty acid components.