Quantitative Trait Loci Mapping Research Articles

Dissecting the complex genetic basis of pre- and post-harvest traits in Vitis vinifera L. using genome-wide association studies.

Addressing the pressing challenges in agriculture necessitates swift advancements in breeding programs, particularly for perennial crops like grapevines. Moving beyond the traditional biparental quantitative trait loci (QTL) mapping, we conducted a genome-wide association study (GWAS) encompassing 588 Vitis vinifera L. cultivars from a Chilean breeding program, spanning three seasons and testing 13 key yield-related traits. A strong candidate gene, Vitvi11g000454, located on chromosome 11 and related to plant response to biotic and abiotic stresses through jasmonic acid signaling, was associated with berry width and holds potential for enhancing berry size in grape breeding. We also mapped novel QTL associated with post-harvest traits across chromosomes 2, 4, 9, 11, 15, 18, and 19, broadening our grasp on the genetic intricacies dictating fruit post-harvest behavior, including decay, shriveling, and weight loss. Leveraging gene ontology annotations, we drew parallels between traits and scrutinized candidate genes, laying a robust groundwork for future trait-feature identification endeavors in plant breeding. We also highlighted the importance of carefully considering the choice of the response variable in GWAS analyses, as the use of best linear unbiased estimators (BLUEs) corrections in our study may have led to the suppression of some common QTL in grapevine traits. Our results underscore the imperative of pioneering non-destructive evaluation techniques for long-term conservation traits, offering grape breeders and cultivators insights to improve post-harvest table grape quality and minimize waste.

RicePilaf: a post-GWAS/QTL dashboard to integrate pangenomic, coexpression, regulatory, epigenomic, ontology, pathway, and text-mining information to provide functional insights into rice QTLs and GWAS loci.

As the number of genome-wide association study (GWAS) and quantitative trait locus (QTL) mappings in rice continues to grow, so does the already long list of genomic loci associated with important agronomic traits. Typically, loci implicated by GWAS/QTL analysis contain tens to hundreds to thousands of single-nucleotide polmorphisms (SNPs)/genes, not all of which are causal and many of which are in noncoding regions. Unraveling the biological mechanisms that tie the GWAS regions and QTLs to the trait of interest is challenging, especially since it requires collating functional genomics information about the loci from multiple, disparate data sources. We present RicePilaf, a web app for post-GWAS/QTL analysis, that performs a slew of novel bioinformatics analyses to cross-reference GWAS results and QTL mappings with a host of publicly available rice databases. In particular, it integrates (i)pangenomic information from high-quality genome builds of multiple rice varieties, (ii)coexpression information from genome-scale coexpression networks, (iii)ontology and pathway information, (iv)regulatory information from rice transcription factor databases, (v)epigenomic information from multiple high-throughput epigenetic experiments, and (vi)text-mining information extracted from scientific abstracts linking genes and traits. We demonstrate the utility of RicePilaf by applying it to analyze GWAS peaks of preharvest sprouting and genes underlying yield-under-drought QTLs. RicePilaf enables rice scientists and breeders to shed functional light on their GWAS regions and QTLs, and it provides them with a means to prioritize SNPs/genes for further experiments. The source code, a Docker image, and a demo version of RicePilaf are publicly available at https://github.com/bioinfodlsu/rice-pilaf.

QTL Mapping Using RIL Population.

Genetic maps are an excellent tool for the analysis of important traits, the development of which is the result of the combined expression of several genes, enabling the genomic localization of the factors determining them. Such features, characterized by a normal distribution of values, are referred to as quantitative or polygenic. The analysis of their genetic background using a chromosome map is called the mapping of quantitative traits loci (QTL). QTL analysis is a statistical method of determining the genetic association of phenotypic data (trait measurements) with genotypic data (DNA markers assigned to linkage groups).There are numerous tools developed for QTL mapping. This chapter introduces Windows QTL Cartographer with Composite Interval Mapping (CIM) method, which estimates the QTL position by combining interval mapping with multiple regression. The genotypic and phenotypic data used in the exemplary QTL mapping procedure were obtained for the recombinant inbred line (RIL) population of rye. Plant height, assessed in three seasons, was the exemplary trait under study.

Quantitative trait locus (QTL) mapping and transcriptome profiling identify QTLs and candidate genes associated with heat stress response during reproductive development in Camelina sativa

AbstractCamelina sativa (L.) Crantz is a low‐input oilseed crop that has great potential in providing sustainable feedstock for biofuels and bioproducts. Climate change is threatening production of camelina with rising global temperatures. Elucidating the genetic response to high temperatures is essential for successful breeding of heat‐tolerant camelina varieties. Here, we report a combinatorial approach to identifying candidate genes associated with heat stress by quantitative trait locus (QTL) mapping and comparative transcriptome profiling. A population of recombinant inbred lines (RILs) was grown in a controlled growth chamber under the high‐temperature regimes for 14 days beginning at the onset of the reproductive stage. Several traits related to seed production were evaluated at maturity. The QTL analysis identified several regions with co‐located traits on chromosomes 8, 10, and 12. Two RILs with contrasting phenotypic responses to heat stress were chosen for gene expression profiling via RNA sequencing. Multiple pathways and genes were found to be strongly affected by heat stress, and many genes expressed differently between the two RILs. Several genes identified within the QTL regions were considered strong candidates that may control heat tolerance during reproduction in camelina. These studies provide resources for future studies that may assist in improving the heat tolerance of camelina.

Development of Gossypium hirsutum-Gossypium raimondii introgression lines and its usages in QTL mapping of agricultural traits

Gossypium raimondii (2n=2x=26, D5), an untapped wild species, is the putative progenitor of the D-subgenome of G. hirsutum (2n=4x=52, AD1), an extensively cultivated species. Here, we developed a G. hirsutum (recipient)-G. raimondii (donor) introgression population to exploit favorable QTLs/genes and mapped potential quantitative trait loci (QTLs) from wild cotton species. The introgression population consists of 256 lines with an introgression rate of 52.33% of the genome G. raimondii. The range of introgression segment length was 0.03-19.12 Mb, with an average of 1.22 Mb. The coverage of total introgression fragments was 386.98 Mb from G. raimondii. Further genome-wide association analysis (Q+K+MLM) and QTL mapping (RSTEP-LRT) identified 59 common QTLs, including 14 stable QTLs and 6 common QTL (co-QTL) clusters, and one hotspot of MIC. The common QTLs for seed index showed all positive additive effects, while the common QTLs for boll weight were all negative additive effects, indicating that the linkage between seed index and boll weight could be broken. QTLs for lint percentage showed positive effect and could be beneficial for improving cotton yield. Most QTLs for fiber quality had negative additive effects, implying these QTLs were domesticated/improved in G. hirsutum. A few fiber quality QTLs showed positive additive effects, which could be used to improve cotton fiber quality. These introgression lines developed would be useful for molecular marker-assisted breeding and facilitate us to map QTLs precisely for mining desirable genes from the wild species G. raimondii to improve cultivated cotton in future via a design-breeding approach.

Identification of three large full-sib families of Quercus rubra for genetic mapping in an isolated planting outside the species’ range in Germany

Abstract Forest tree breeding faces challenges due to long generation times and high costs. To address these issues, the concept of “breeding without breeding” (BwB) offers the opportunity to accelerate breeding cycles by using naturally generated half- sib and full-sib families. An isolated population of trees may provide an ideal environment to identify full-sib families for genetic mapping without the need for controlled pollination. In this study, paternity analysis based on genotyping of 16 SSR markers in 1232 seedlings identified three large full-sib families of Quercus rubra (Qr_N - Qr_W with 576 siblings, Qr_N - Qr_S with 175 siblings and 124 siblings in the family Qr_P - Qr_11). Paternity assignments were effectively corroborated by segregation analysis, resulting in large F1 full-sib families for further experiments such as Quantitative Trait Locus (QTL) mapping.

QTL Mapping for Adult-Plant Resistance to Leaf Rust in Italian Wheat Cultivar Libellula.

Wheat leaf rust (Lr), which is caused by Puccinia triticina Eriks. (Pt), is one of the most important wheat diseases affecting wheat production globally. Using resistant wheat cultivars is the most economical and environmentally friendly way to control leaf rust. The Italian wheat cultivar Libellula has demonstrated good resistance to Lr in field studies. To identify the genetic basis of Lr resistance in 'Libellula', 248 F6 recombinant inbred lines from the cross 'Libellula'/'Huixianhong' was phenotyped for Lr severity in seven environments: the 2014/2015, 2016/2017, 2017/2018, and 2018/2019 cropping seasons at Baoding, Hebei Province, and the 2016/2017, 2017/2018, and 2018/2019 crop seasons at Zhoukou, Henan Province. Bulked segregant analysis and simple sequence repeat markers were then used to identify the quantitative trait loci (QTLs) for Lr adult-plant resistance in the population. Six QTLs were consequently detected and designated as QLr.hebau-1AL and QLr.hebau-1AS that were presumed to be new and QLr.hebau-1BL, QLr.hebau-3AL, QLr.hebau-4BL, and QLr.hebau-7DS that were identified at similar physical positions as previously reported QTLs. Based on chromosome positions and molecular marker tests, QLr.hebau-1BL and QLr.hebau-7DS share similar flanking markers with Lr46 and Lr34, respectively. Lr46 and Lr34 are race nonspecific adult plant resistance (APR) genes for leaf rust and stripe rust and powdery mildew. QLr.hebau-4BL showed multiple disease resistance to leaf rust, stripe rust, Fusarium head blight, and powdery mildew. The QTL identified in this study, as well as their closely linked markers, may potentially be used in marker-assisted selection in wheat breeding.

Genomic and co-expression network analyses reveal candidate genes for oil accumulation based on an introgression population in Upland cotton (Gossypium hirsutum).

Integrated QTL mapping and WGCNA condense the potential gene regulatory network involved in oil accumulation. A glycosyl hydrolases gene (GhHSD1) for oil biosynthesis was confirmed in Arabidopsis, which will provide useful knowledge to understand the functional mechanism of oil biosynthesis in cotton. Cotton is an economical source of edible oil for the food industry. The genetic mechanism that regulates oil biosynthesis in cottonseeds is essential for the genetic enhancement of oil content (OC). To explore the functional genomics of OC, this study utilized an interspecific backcross inbred line population to dissect the quantitative trait locus (QTL) interlinked with OC. In total, nine OC QTLs were identified, four of which were novel, and each QTL explained 3.62-34.73% of the phenotypic variation of OC. The comprehensive transcript profiling of developing cottonseeds revealed 3,646 core genes differentially expressed in both inbred parents. Functional enrichment analysis determined 43 genes were annotated with oil biosynthesis processes. Implementation of weighted gene co-expression network analysis showed that 803 differential genes had a significant correlation with the OC phenotype. Further integrated analysis identified seven important genes located in OC QTLs. Of which, the GhHSD1 gene located in stable QTL qOC-Dt3-1 exhibited the highest functional linkages with the other network genes. Phylogenetic analysis showed significant evolutionary differences in the HSD1 sequences between oilseed- and starch- crops. Furthermore, the overexpression of GhHSD1 in Arabidopsis yielded almost 6.78% higher seed oil. This study not only uncovers important genetic loci for oil accumulation in cottonseed, but also provides a set of new candidate genes that potentially influence the oil biosynthesis pathway in cottonseed.

Genetic analysis of stay green related traits in maize with major gene plus polygenes mixed model.

Maize is one of the main food crops in the world, and cultivating high-yield and high-quality maize varieties is of great significance in addressing food security issues. Leaves are crucial photosynthetic organs in maize, and leaf senescence can result in the degradation of chlorophyll. This, in turn, impacts photosynthetic activity and the accumulation of photosynthetic products. Delaying leaf senescence and increasing carbon assimilation can enhance grain yield and biomass production. The stay green of maize is an important trait closely related to yield, feed quality and resistance. Therefore, this study employed multi-generation joint analysis of major genes and a polygene model to investigate the genetic inheritance of stay green-related traits. Four populations (P1, P2, F1 and F2) were obtained by crossing T01 (stay green) × Xin3 (non-stay green) and T01 (stay green) × Mo17 (non-stay green) under two environments. Six stay green-related traits, including visual stay green (VSG), number of green leaves (GLNM), SPAD value of ear leaf at anthesis (SPADS), SPAD value of ear leaf at maturity (SPADM), absolute green leaf area (GLAD), grain yield per plant (GYP), displayed continuous variations with kurtosis and skewness values of absolute value less than 1 and distribution close to normal. They were characterized by typical inheritance of quantitative traits, with these traits demonstrating the transgressive segregation. The correlation analysis among the traits revealed that five stay green traits have a positive impact on yield. VSG, GLNM and SPADM in the two populations were regulated by the two major genes of additive effects plus additive-dominance polygene model with a major gene heritability varying from 89.03 to 95.95% in the F2 generation. GLAD in TMF2 was controlled by two major genes of equal-additive dominance effects with high heritability (93.47%). However, in TXF2, GLAD was regulated by two major genes of additive-dominance interaction effects plus additive-dominance polygene model. These results provide important genetic information for breeding, which could guide the improvement of stay green-related traits. They also lay a foundation for quantitative trait loci mapping of the stay stay-green traits in maize.

Identification of Increased Grain Length 1 (IGL1), a novel gene encoded by a major QTL for modulating grain length in rice.

A novel quantitative trait locus qIGL1, which performed a positive function in regulating grain length in rice, was cloned by the map-based cloning approach; further studies revealed that it corresponded to LOC_Os03g30530, and the IGL1 appeared to contribute to lengthening and widening of the cells on the surface of grain hulls. Grain length is a prominent determinant for grain weight and appearance quality of rice. In this study, we conducted quantitative trait locus mapping to determine a genomic interval responsible for a long-grain phenotype observed in a japonica cultivar HD385. This led to the identification of a novel QTL for grain length on chromosome 3, named qIGL1 (for Increased Grain Length 1); the HD385 (Handao 385)-derived allele showed enhancement effects on grain length, and such an allele as well as NIP (Nipponbare)-derived allele was designated qigl1 HD385 and qIGL1NIP, respectively. Genetic analysis revealed that the qigl1HD385 allele displayed semidominant effects on grain length. Fine mapping further narrowed down the qIGL1 to an ~ 70.8-kb region containing 9 open reading frames (ORFs). A comprehensive analysis indicated that LOC_Os03g30530, which corresponded to ORF6 and carried base substitutions and deletions in HD385 relative to NIP, thereby causing changes or losses of amino-acid residues, was the true gene for qIGL1. Comparison of grain traits between a pair of near-isogenic lines (NILs), termed NIL-igl1HD385 and NIL-IGL1NIP, discovered that introduction of the igl1HD385 into the NIP background significantly resulted in the elevations of grain length and 1000-grain weight. Closer inspection of grain surfaces revealed that the cell length and width in the longitudinal direction were significantly longer and greater, respectively, in NIL-igl1HD385 line compared with in NIL-IGL1NIP line. Hence, our studies identified a new semidominant natural allele contributing to the increase of grain length and further shed light on the regulatory mechanisms of grain length.

The MADS-box transcription factor CsAGL9 plays essential roles in seed setting in Camellia sinensis

The number of seed setting (NSS) is an important biological trait that affects tea propagation and yield. In this study, the NSS of an F1 tea population (n = 324) generated via a cross between ‘Longjing 43’ and ‘Baihaozao’ was investigated at two locations in two consecutive years. Quantitative trait locus (QTL) mapping of the NSS was performed, and 10 major QTLs were identified. In total, 318 genes were found in these 10 QTLs intervals, and 11 key candidate genes were preliminarily identified. Among them, the MADS-box transcription factor AGAMOUS LIKE 9 (CsAGL9, CSS0037962) located in the most stable QTL (qNSS2) was identified as a key gene affecting the NSS. CsAGL9 overexpression in Arabidopsis promoted early flowering and significantly decreased the length and number of pods and number of seeds per pod. Transcriptome analysis demonstrated that the auxin pathway, a key hormone pathway regulating plant reproduction, was highly affected in the transgenic lines. The auxin pathway was likewise the most prominent in the gene co-expression network study of CsAGL9 in tea plants. In summary, we identified CsAGL9 is essential for seed setting using QTL mapping integrated with RNA-seq, which shed a new light on the mechanism NSS of seed setting in tea plants.

Exploring the Regulation and Function of Rpl3l in the Development of Early-Onset Dilated Cardiomyopathy and Congestive Heart Failure Using Systems Genetics Approach.

Cardiomyopathies, diseases affecting the myocardium, are common causes of congestive heart failure (CHF) and sudden cardiac death. Recently, biallelic variants in ribosomal protein L3-like (RPL3L) have been reported to be associated with severe neonatal dilated cardiomyopathy (DCM) and CHF. This study employs a systems genetics approach to gain understanding of the regulatory mechanisms underlying the role of RPL3L in DCM. Genetic correlation, expression quantitative trait loci (eQTL) mapping, differential expression analysis and comparative functional analysis were performed using cardiac gene expression data from the patients and murine genetic reference populations (GRPs) of BXD mice (recombinant inbred strains from a cross of C57BL/6J and DBA/2J mice). Additionally, immune infiltration analysis was performed to understand the relationship between DCM, immune cells and RPL3L expression. Systems genetics analysis identified high expression of Rpl3l mRNA, which ranged from 11.31 to 12.16 across murine GRPs of BXD mice, with an ~1.8-fold difference. Pathways such as "diabetic cardiomyopathy", "focal adhesion", "oxidative phosphorylation" and "DCM" were significantly associated with Rpl3l. eQTL mapping suggested Myl4 (Chr 11) and Sdha (Chr 13) as the upstream regulators of Rpl3l. The mRNA expression of Rpl3l, Myl4 and Sdha was significantly correlated with multiple echocardiography traits in BXD mice. Immune infiltration analysis revealed a significant association of RPL3L and SDHA with seven immune cells (CD4, CD8-naive T cell, CD8 T cell, macrophages, cytotoxic T cell, gamma delta T cell and exhausted T cell) that were also differentially infiltrated between heart samples obtained from DCM patients and normal individuals. RPL3L is highly expressed in the heart tissue of humans and mice. Expression of Rpl3l and its upstream regulators, Myl4 and Sdha, correlate with multiple cardiac function traits in murine GRPs of BXD mice, while RPL3L and SDHA correlate with immune cell infiltration in DCM patient hearts, suggesting important roles for RPL3L in DCM and CHF pathogenesis via immune inflammation, necessitating experimental validations of Myl4 and Sdha in Rpl3l regulation.

QTL Mapping and Genetic Map for the Ornamental Sunflower in China

Quantitative trait locus (QTL) mapping and genetic map are of great significance for ornamental sunflowers in China. In this study, a total of 956.50 Mbp data were obtained, the average Q30 was 93.76%, the average GC content was 42.43%, and the GC distribution of the parents and F2 population of the ornamental sunflowers was normal. At the same time, the double-end comparison efficiency of control data was 90.28%, and the enzyme digestion efficiency was 92.01%. The Specific-Locus Amplified Fragment (SLAF) library construction was normal. Furthermore, a total of 734,893 SLAF markers were obtained, among which 127,855 were polymorphic SLAF markers and 38,908 could be used for genetic map construction, and the effective polymorphism of the parents was 5.29%. Moreover, we constructed a total of 17 linkage groups, with 6181 markers in the QTL mapping, the total map distance was 2608.66 cM, the marker integrity in the figure above was 99%, the proportion of double exchange was 0.05, the sequencing depth of the parents was 42.455 × , and the progeny was 9.24 × . The relationship of traits (plant height, stem diameter, disk diameter, number of petals, leaf number, stigma color, petal color, petiole color) and QTL mapping was closely related to show the best of ornamental effect.

QTL Mapping of Trichome Traits and Analysis of Candidate Genes in Leaves of Wheat (Triticum aestivum L.).

Trichome plays an important role in heat dissipation, cold resistance, water absorption, protection of leaves from mechanical damage, and direct exposure to ultraviolet rays. It also plays an important role in the photosynthesis, transpiration, and respiration of plants. However, the genetic basis of trichome traits is not fully understood in wheat. In this study, wheat DH population (Hanxuan 10 × Lumai 14) was used to map quantitative trait loci (QTL) for trichome traits in different parts of flag leaf at 10 days after anther with growing in Zhao County, Hebei Province, and Taigu County, Shanxi Province, respectively. The results showed that trichome density (TD) was leaf center > leaf tip > leaf base and near vein > middle > edge, respectively, in both environments. The trichome length (TL) was leaf tip > leaf center > leaf base and edge > middle > near vein. Significant phenotypic positive correlations were observed between the trichome-related traits of different parts. A total of 83 QTLs for trichome-related traits were mapped onto 18 chromosomes, and each one accounted for 2.41 to 27.99% of the phenotypic variations. Two QTL hotspots were detected in two marker intervals: AX-95232910~AX-95658735 on 3A and AX-94850949~AX-109507404 on 7D. Six possible candidate genes (TraesCS3A02G406000, TraesCS3A02G414900, TraesCS3A02G440900, TraesCS7D02G145200, TraesCS7D02G149200, and TraesCS7D02G152400) for trichome-related traits of wheat leaves were screened out according to their predicted expression levels in wheat leaves. The expression of these genes may be induced by a variety of abiotic stresses. The results provide the basis for further validation and functional characterization of the candidate genes.

CmWAT6.1, mined by high-density genetic map-based QTL mapping, enhances waterlogging tolerance in chrysanthemum

High-density genetic maps are a valuable tool for quantitative trait locus (QTL) mapping and gene discovery for important traits in plants. However, such work in chrysanthemum remains largely unexplored, primarily owing to its large genome and complex genetic background. In this study, a high-density map containing 11,941 SNP bins spanning a total of 2967.76 cM in 27 linkage groups (LGs) with an average intermarker distance of 0.26 cM was developed with a genotyping by sequencing (GBS) approach. A total of 34 QTL clusters for waterlogging tolerance (WAT) were detected via multiple-QTL mapping (MQM) algorithms. A total of 186 candidate genes within these QTL clusters were mined in combination with transcriptome data. One key candidate gene within the QTL cluster cWAT6.1, which belongs to group VII ethylene response factors (CmWAT6.1), was proven to be a positive regulator of WAT in chrysanthemum. Furthermore, transcriptomic assays of transgenic and wild-type chrysanthemums under normal conditions as well as further experiments provided evidence that CmWAT6.1 regulated WAT by promoting cell wall formation and lignin biosynthesis and coordinating oligosaccharide metabolic processes. This study represents important progress in gene mining through forward genetics, provides valuable genetic resources for further WAT improvement and provides new insight into the molecular mechanism of WAT in chrysanthemum.

BSA-seq identified candidate genes and diagnostic KASP markers for anemone type flower in chrysanthemum

Chrysanthemum is one of the most leading commercial flower crops well-known for its flower shape diversity. Anemone type chrysanthemums receive increasing market attention that are distinguished by their pigmented and elongated disk florets. However, there are few reports on quantitative trait loci (QTL) mapping and the identification genes for anemone in chrysanthemum. In this study, bulked segregant analysis coupled with whole-genome sequencing (BSA-seq) approach was employed to detect candidate genomic regions controlling anemone type flower. Two mixed DNA pools composed of 28 anemone type and 20 non-anemone type F1 lines derived from a cross between ‘Nannong Xuefeng’ and ‘Monalisa’ together with two parents were used for high-throughput sequencing. A total of 42 consistent QTLs covering 30.00 Mb were simultaneously identified by |△(SNP/InDel-index)| and Euclidean distance (ED) algorithms based on 15,783,313 SNPs (single-nucleotide polymorphisms) and 1,546,200 small InDels (insertions and deletions). Twenty-two key candidate genes were screened out by a combination of gene functional annotation and transcriptome analysis, in which evm.model.scaffold_915.436 (CBF5), evm.model.scaffold_24.208 (U2AF65A), and a uncharacterized gene evm.model.scaffold_260.201 were highlighted by qRT-PCR. Furtherly, four associations were successfully converted to KASP (kompetitive allele specific PCR) markers, among them, the KASP markers developed for SNP locus Chr6__33961007 and Chr6__179207697 were proven to efficiently discriminate anemone and non-anemone type chrysanthemums being a couple of diagnostic markers in two populations. The results presented herein provide insights for further research on elucidating the formation mechanism of anemone type flower, and the anemone-specific KASP marker will be highly useful for applying MAS to accelerate breeding improvement of chrysanthemum.

Unraveling the causal genes and transcriptomic determinants of human telomere length

Telomere length (TL) shortening is a pivotal indicator of biological aging and is associated with many human diseases. The genetic determinates of human TL have been widely investigated, however, most existing studies were conducted based on adult tissues which are heavily influenced by lifetime exposure. Based on the analyses of terminal restriction fragment (TRF) length of telomere, individual genotypes, and gene expressions on 166 healthy placental tissues, we systematically interrogate TL-modulated genes and their potential functions. We discover that the TL in the placenta is comparatively longer than in other adult tissues, but exhibiting an intra-tissue homogeneity. Trans-ancestral TL genome-wide association studies (GWASs) on 644,553 individuals identify 20 newly discovered genetic associations and provide increased polygenic determination of human TL. Next, we integrate the powerful TL GWAS with placental expression quantitative trait locus (eQTL) mapping to prioritize 23 likely causal genes, among which 4 are functionally validated, including MMUT, RRM1, KIAA1429, and YWHAZ. Finally, modeling transcriptomic signatures and TRF-based TL improve the prediction performance of human TL. This study deepens our understanding of causal genes and transcriptomic determinants of human TL, promoting the mechanistic research on fine-grained TL regulation.

Integrated Bulk Segregant Analysis, Fine Mapping, and Transcriptome Revealed QTLs and Candidate Genes Associated with Drought Adaptation in Wild Watermelon.

Drought stress has detrimental effects on crop productivity worldwide. A strong root system is crucial for maintaining water and nutrients uptake under drought stress. Wild watermelons possess resilient roots with excellent drought adaptability. However, the genetic factors controlling this trait remain uninvestigated. In this study, we conducted a bulk segregant analysis (BSA) on an F2 population consisting of two watermelon genotypes, wild and domesticated, which differ in their lateral root development under drought conditions. We identified two quantitative trait loci (qNLR_Dr. Chr01 and qNLR_Dr. Chr02) associated with the lateral root response to drought. Furthermore, we determined that a small region (0.93 Mb in qNLR_Dr. Chr01) is closely linked to drought adaptation through quantitative trait loci (QTL) validation and fine mapping. Transcriptome analysis of the parent roots under drought stress revealed unique effects on numerous genes in the sensitive genotype but not in the tolerant genotype. By integrating BSA, fine mapping, and the transcriptome, we identified six genes, namely L-Ascorbate Oxidase (AO), Cellulose Synthase-Interactive Protein 1 (CSI1), Late Embryogenesis Abundant Protein (LEA), Zinc-Finger Homeodomain Protein 2 (ZHD2), Pericycle Factor Type-A 5 (PFA5), and bZIP transcription factor 53-like (bZIP53-like), that might be involved in the drought adaptation. Our findings provide valuable QTLs and genes for marker-assisted selection in improving water-use efficiency and drought tolerance in watermelon. They also lay the groundwork for the genetic manipulation of drought-adapting genes in watermelon and other Cucurbitacea species.

The chromosome-scale genome and the genetic resistance machinery against insect herbivores of the Mexican toloache, Datura stramonium.

Plant resistance refers to the heritable ability of plants to reduce damage caused by natural enemies, such as herbivores and pathogens, either through constitutive or induced traits like chemical compounds or trichomes. However, the genetic architecture-the number and genome location of genes that affect plant defense and the magnitude of their effects-of plant resistance to arthropod herbivores in natural populations remains poorly understood. In this study, we aimed to unveil the genetic architecture of plant resistance to insect herbivores in the annual herb Datura stramonium (Solanaceae) through quantitative trait loci mapping. We achieved this by assembling the species' genome and constructing a linkage map using an F2 progeny transplanted into natural habitats. Furthermore, we conducted differential gene expression analysis between undamaged and damaged plants caused by the primary folivore, Lema daturaphila larvae. Our genome assembly resulted in 6,109 scaffolds distributed across 12 haploid chromosomes. A single quantitative trait loci region on chromosome 3 was associated with plant resistance, spanning 0 to 5.17 cM. The explained variance by the quantitative trait loci was 8.44%. Our findings imply that the resistance mechanisms of D. stramonium are shaped by the complex interplay of multiple genes with minor effects. Protein-protein interaction networks involving genes within the quantitative trait loci region and overexpressed genes uncovered the key role of receptor-like cytoplasmic kinases in signaling and regulating tropane alkaloids and terpenoids, which serve as powerful chemical defenses against D. stramonium herbivores. The data generated in our study constitute important resources for delving into the evolution and ecology of secondary compounds mediating plant-insect interactions.

TWAS revealed significant causal loci for milk production and its composition in Murrah buffaloes

Milk yield is the most complex trait in dairy animals, and mapping all causal variants even with smallest effect sizes has been difficult with the genome-wide association study (GWAS) sample sizes available in geographical regions with small livestock holdings such as Indian sub-continent. However, Transcriptome-wide association studies (TWAS) could serve as an alternate for fine mapping of expression quantitative trait loci (eQTLs). This is a maiden attempt to identify milk production and its composition related genes using TWAS in Murrah buffaloes (Bubalus bubalis). TWAS was conducted on a test (N = 136) set of Murrah buffaloes genotyped through ddRAD sequencing. Their gene expression level was predicted using reference (N = 8) animals having both genotype and mammary epithelial cell (MEC) transcriptome information. Gene expression prediction was performed using Elastic-Net and Dirichlet Process Regression (DPR) model with fivefold cross-validation and without any cross-validation. DPR model without cross-validation predicted 80.92% of the total genes in the test group of Murrah buffaloes which was highest compared to other methods. TWAS in test individuals based on predicted gene expression, identified a significant association of one unique gene for Fat%, and two for SNF% at Bonferroni corrected threshold. The false discovery rates (FDR) corrected P-values of the top ten SNPs identified through GWAS were comparatively higher than TWAS. Gene ontology of TWAS-identified genes was performed to understand the function of these genes, it was revealed that milk production and composition genes were mainly involved in Relaxin, AMPK, and JAK-STAT signaling pathway, along with CCRI, and several key metabolic processes. The present study indicates that TWAS offers a lower false discovery rate and higher significant hits than GWAS for milk production and its composition traits. Hence, it is concluded that TWAS can be effectively used to identify genes and cis-SNPs in a population, which can be used for fabricating a low-density genomic chip for predicting milk production in Murrah buffaloes.