Unveiling genetic signatures associated with resilience to neonatal diarrhea in lambs through two GWAS approaches.

Neonatal diarrhea presents a significant global challenge due to its multifactorial etiology, resulting in high morbidity and mortality rates, and substantial economic losses. While molecular-level studies on genetic resilience/susceptibility to neonatal diarrhea in farm animals are scarce, prior observations indicate promising research directions. Thus, the present study utilizes two genome-wide association approaches, pKWmEB and MLM, to explore potential links between genetic variations in innate immunity and neonatal diarrhea in Karacabey Merino lambs. Analyzing 707 lambs, including 180 cases and 527 controls, revealed an overall prevalence rate of 25.5%. The pKWmEB analysis identified 13 significant SNPs exceeding the threshold of ≥ LOD 3. Moreover, MLM detected one SNP (s61781.1) in the SLC22A8 gene (p-value, 1.85eE-7), which was co-detected by both methods. A McNemar's test was conducted as the final assessment to identify whether there are any major effective markers among the detected SNPs. Results indicate that four markers-oar3_OAR1_122352257, OAR17_77709936.1, oar3_OAR18_17278638, and s61781.1-have a substantial impact on neonatal diarrhea prevalence (odds ratio: 2.03 to 3.10; statistical power: 0.88 to 0.99). Therefore, we propose the annotated genes harboring three of the associated markers, TIAM1, YDJC, and SLC22A8, as candidate major genes for selective breeding against neonatal diarrhea.

Discovering New QTNs and Candidate Genes Associated with Rice-Grain-Related Traits within a Collection of Northeast Core Set and Rice Landraces.

Grain-related traits are pivotal in rice cultivation, influencing yield and consumer preference. The complex inheritance of these traits, involving multiple alleles contributing to their expression, poses challenges in breeding. To address these challenges, a multi-locus genome-wide association study (ML-GWAS) utilizing 35,286 high-quality single-nucleotide polymorphisms (SNPs) was conducted. Our study utilized an association panel comprising 483 rice genotypes sourced from a northeast core set and a landraces set collected from various regions in India. Forty quantitative trait nucleotides (QTNs) were identified, associated with four grain-related traits: grain length (GL), grain width (GW), grain aroma (Aro), and length-width ratio (LWR). Notably, 16 QTNs were simultaneously identified using two ML-GWAS methods, distributed across multiple chromosomes. Nearly 258 genes were found near the 16 significant QTNs. Gene annotation study revealed that sixty of these genes exhibited elevated expression levels in specific tissues and were implicated in pathways influencing grain quality. Gene ontology (GO), trait ontology (TO), and enrichment analysis pinpointed 60 candidate genes (CGs) enriched in relevant GO terms. Among them, LOC_Os05g06470, LOC_Os06g06080, LOC_Os08g43470, and LOC_Os03g53110 were confirmed as key contributors to GL, GW, Aro, and LWR. Insights from QTNs and CGs illuminate rice trait regulation and genetic connections, offering potential targets for future studies.

Multi-locus genome-wide association studies reveal the dynamic genetic architecture of flowering time in chrysanthemum.

KEY MESSAGE: The dynamic genetic architecture of flowering time in chrysanthemum was elucidated by GWAS. Thirty-six known genes and 14 candidate genes were identified around the stable QTNs and QEIs, among which ERF-1 was highlighted. Flowering time (FT) adaptation is one of the major breeding goals in chrysanthemum, a multipurpose ornamental plant. In order to reveal the dynamic genetic architecture of FT in chrysanthemum, phenotype investigation of ten FT-related traits was conducted on 169 entries in 2 environments. The broad-sense heritability of five non-conditional FT traits, i.e., budding (FBD), visible coloring (VC), early opening (EO), full-bloom (OF) and decay period (DP), ranged from 56.93 to 84.26%, which were higher than that of the five derived conditional FT traits (38.51-75.13%). The phenotypic variation coefficients of OF_EO and DP_OF were relatively large ranging from 30.59 to 36.17%. Based on 375,865 SNPs, the compressed variance component mixed linear model 3VmrMLM was applied for a multi-locus genome-wide association study (GWAS). As a result, 313 quantitative trait nucleotides (QTNs) were identified for the non-conditional FT traits in single-environment analysis, while 119 QTNs and 67 QTN-by-environment interactions (QEIs) were identified in multi-environment analysis. As for the conditional traits, 343 QTNs were detected in single-environment analysis, and 119 QTNs and 83 QEIs were identified in multi- environment analysis. Among the genes around stable QTNs and QEIs, 36 were orthologs of known FT genes in Arabidopsis and other plants; 14 candidates were mined by combining the transcriptomics data and functional annotation, including ERF-1, ACA10, and FOP1. Furthermore, the haplotype analysis of ERF-1 revealed six elite accessions with extreme FBD. Our findings contribute to the understanding of dynamic genetic architecture of FT and provide valuable resources for future chrysanthemum molecular breeding programs.

Breeding effects on durum wheat traits detected using GWAS and haplotype block analysis.

Introduction: The recent boosting of genomic data in durum wheat (Triticum turgidum subsp. durum) offers the opportunity to better understand the effects of breeding on the genetic structures that regulate the expression of traits of agronomic interest. Furthermore, the identification of DNA markers useful for marker-assisted selection could also improve the reliability of technical protocols used for variety protection and registration. Methods: Within this motivation context, 123 durum wheat accessions, classified into three groups: landraces (LR), ancient (OC) and modern cultivars (MC), were evaluated in two locations, for 34 agronomic traits, including UPOV descriptors, to assess the impact of changes that occurred during modern breeding. Results: The association mapping analysis, performed with 4,241 SNP markers and six multi-locus-GWAS models, revealed 28 reliable Quantitative Trait Nucleotides (QTNs) related to plant morphology and kernel-related traits. Some important genes controlling flowering time and plant height were in linkage disequilibrium (LD) decay with QTNs identified in this study. A strong association for yellow berry was found on chromosome 6A (Q.Yb-6A) in a region containing the nadh-ubiquinone oxidoreductase subunit, a gene involved in starch metabolism. The Q.Kcp-2A harbored the PPO locus, with the associated marker (Ku_c13700_1196) in LD decay with Ppo-A1 and Ppo-A2. Interestingly, the Q.FGSGls-2B.1, identified by RAC875_c34512_685 for flag leaf glaucosity, mapped less than 1 Mb from the Epistatic inhibitors of glaucousness (Iw1), thus representing a good candidate for supporting the morphological DUS traits also with molecular markers. LD haplotype block approach revealed a higher diversity, richness and length of haploblocks in MC than OC and LR (580 in LR, 585 in OC and 612 in MC), suggesting a possible effect exerted by breeding programs on genomic regions associated with the agronomic traits. Discussion: Our findings pave new ways to support the phenotypic characterization necessary for variety registration by using a panel of cost-effectiveness SNP markers associated also to the UPOV descriptors. Moreover, the panel of associated SNPs might represent a reservoir of favourable alleles to use in durum wheat breeding and genetics.

Identification of southern corn rust resistance QTNs in Chinese summer maize germplasm via multi-locus GWAS and post-GWAS analysis.

Southern corn rust (SCR) caused by Puccinia polysora Underw is a major disease leading to severe yield losses in China Summer Corn Belt. Using six multi-locus GWAS methods, we identified a set of SCR resistance QTNs from a diversity panel of 140 inbred lines collected from China Summer Corn Belt. Thirteen QTNs on chromosomes 1, 2, 4, 5, 6, and 8 were grouped into three types of allele effects and their associations with SCR phenotypes were verified by post-GWAS case-control sampling, allele/haplotype effect analysis. Relative resistance (RRR) and relative susceptibility (RRs) catering to its inbred carrier were estimated from single QTN and QTN-QTN combos and epistatitic effects were estimated for QTN-QTN combos. By transcriptomic annotation, a set of candidate genes were predicted to be involved in transcriptional regulation (S5_145, Zm00001d01613, transcription factor GTE4), phosphorylation (S8_123, Zm00001d010672, Pgk2- phosphoglycerate kinase 2), and temperature stress response (S6_164a/S6_164b, Zm00001d038806, hsp101, and S5_211, Zm00001d017978, cellulase25). The breeding implications of the above findings were discussed.

Genetic dissection of maize (Zea mays L.) chlorophyll content using multi-locus genome-wide association studies.

BACKGROUND: The chlorophyll content (CC) is a key factor affecting maize photosynthetic efficiency and the final yield. However, its genetic basis remains unclear. The development of statistical methods has enabled researchers to design and apply various GWAS models, including MLM, MLMM, SUPER, FarmCPU, BLINK and 3VmrMLM. Comparative analysis of their results can lead to more effective mining of key genes. RESULTS: The heritability of CC was 0.86. Six statistical models (MLM, BLINK, MLMM, FarmCPU, SUPER, and 3VmrMLM) and 1.25 million SNPs were used for the GWAS. A total of 140 quantitative trait nucleotides (QTNs) were detected, with 3VmrMLM and MLM detecting the most (118) and fewest (3) QTNs, respectively. The QTNs were associated with 481 genes and explained 0.29-10.28% of the phenotypic variation. Additionally, 10 co-located QTNs were detected by at least two different models or methods, three co-located QTNs were identified in at least two different environments, and six co-located QTNs were detected by different models or methods in different environments. Moreover, 69 candidate genes within or near these stable QTNs were screened based on the B73 (RefGen_v2) genome. GRMZM2G110408 (ZmCCS3) was identified by multiple models and in multiple environments. The functional characterization of this gene indicated the encoded protein likely contributes to chlorophyll biosynthesis. In addition, the CC differed significantly between the haplotypes of the significant QTN in this gene, and CC was higher for haplotype 1. CONCLUSION: This study's results broaden our understanding of the genetic basis of CC, mining key genes related to CC and may be relevant for the ideotype-based breeding of new maize varieties with high photosynthetic efficiency.

Integrated multi-locus genome-wide association studies and transcriptome analysis for seed yield and yield-related traits in Brassica napus.

Rapeseed (Brassica napus L.), the third largest oil crop, is an important source of vegetable oil and biofuel for the world. Although the breeding and yield has been improved, rapeseed still has the lowest yield compared with other major crops. Thus, increasing rapeseed yield is essential for the high demand of vegetable oil and high-quality protein for live stocks. Silique number per plant (SN), seed per pod (SP), and 1000-seed weight (SW) are the three important factors for seed yield in rapeseed. Some yield-related traits, including plant height (PH), flowering time (FT), primary branch number (BN) and silique number per inflorescence (SI) also affect the yield per plant (YP). Using six multi-locus genome-wide association study (ML-GWAS) approaches, a total of 908 yield-related quantitative trait nucleotides (QTNs) were identified in a panel consisting of 403 rapeseed core accessions based on whole-genome sequencing. Integration of ML-GWAS with transcriptome analysis, 79 candidate genes, including BnaA09g39790D (RNA helicase), BnaA09g39950D (Lipase) and BnaC09g25980D (SWEET7), were further identified and twelve genes were validated by qRT-PCRs to affect the SW or SP in rapeseed. The distribution of superior alleles from nineteen stable QTNs in 20 elite rapeseed accessions suggested that the high-yielding accessions contained more superior alleles. These results would contribute to a further understanding of the genetic basis of yield-related traits and could be used for crop improvement in B. napus.

Multi-Locus Genome-Wide Association Studies to Characterize Fusarium Head Blight (FHB) Resistance in Hard Winter Wheat.

Fusarium head blight (FHB), caused by the fungus Fusarium graminearum Schwabe is an important disease of wheat that causes severe yield losses along with serious quality concerns. Incorporating the host resistance from either wild relatives, landraces, or exotic materials remains challenging and has shown limited success. Therefore, a better understanding of the genetic basis of native FHB resistance in hard winter wheat (HWW) and combining it with major quantitative trait loci (QTLs) can facilitate the development of FHB-resistant cultivars. In this study, we evaluated a set of 257 breeding lines from the South Dakota State University (SDSU) breeding program to uncover the genetic basis of native FHB resistance in the US hard winter wheat. We conducted a multi-locus genome-wide association study (ML-GWAS) with 9,321 high-quality single-nucleotide polymorphisms (SNPs). A total of six distinct marker-trait associations (MTAs) were identified for the FHB disease index (DIS) on five different chromosomes including 2A, 2B, 3B, 4B, and 7A. Further, eight MTAs were identified for Fusarium-damaged kernels (FDK) on six chromosomes including 3B, 5A, 6B, 6D, 7A, and 7B. Out of the 14 significant MTAs, 10 were found in the proximity of previously reported regions for FHB resistance in different wheat classes and were validated in HWW, while four MTAs represent likely novel loci for FHB resistance. Accumulation of favorable alleles of reported MTAs resulted in significantly lower mean DIS and FDK score, demonstrating the additive effect of FHB resistance alleles. Candidate gene analysis for two important MTAs identified several genes with putative proteins of interest; however, further investigation of these regions is needed to identify genes conferring FHB resistance. The current study sheds light on the genetic basis of native FHB resistance in the US HWW germplasm and the resistant lines and MTAs identified in this study will be useful resources for FHB resistance breeding via marker-assisted selection.

Elucidating the genetic architecture controlling antioxidant status and ionic balance in barley under salt stress.

KEY MESSAGE: Association genetic analysis empowered us to identify candidate genes underlying natural variation of morpho-physiological, antioxidants, and grain yield-related traits in barley. Novel intriguing genomic regions were identified and dissected. Salinity stress is one of the abiotic stresses that influence the morpho-physiological, antioxidants, and yield-related traits in crop plants. The plants of a core set of 138 diverse barley accessions were analyzed after exposure to salt stress under field conditions during the reproductive phase. A genome-wide association scan (GWAS) was then conducted using 19,276 single nucleotide polymorphisms (SNPs) to uncover the genetic basis of morpho-physiological and grain-related traits. A wide range of responses to salt stress by the accessions was explored in the current study. GWAS detected 263 significantly associated SNPs with the antioxidants, K+/Na+ content ratio, and agronomic traits. Five genomic regions harbored interesting putative candidate genes within LD ± 1.2 Mbp. Choromosome 2H harbored many candidate genes associated with the antioxidants ascorbic acid (AsA) and glutathione (GSH), such as superoxide dismutase (SOD), ascorbate peroxidase (APX), and glutathione reductase (GR), under salt stress. Markedly, an A:C SNP at 153,773,211 bp on chromosome 7H is located inside the gene HORVU.MOREX.r3.7HG0676830 (153,772,300-153,774,057 bp) that was annotated as L-gulonolactone oxidase, regulating the natural variation of SOD_S and APX_S. The allelic variation at this SNP reveals a negative selection of accessions carrying the C allele, predominantly found in six-rowed spring landraces originating from Far-, Near-East, and central Asia carrying photoperiod sensitive alleles having lower activity of enzymatic antioxidants. The SNP-trait associations detected in the current study constitute a benchmark for developing molecular selection tools for antioxidant compound selection in barley.

Identification of QTNs Associated With Flowering Time, Maturity, and Plant Height Traits in Linum usitatissimum L. Using Genome-Wide Association Study.

Early flowering, maturity, and plant height are important traits for linseed to fit in rice fallows, for rainfed agriculture, and for economically viable cultivation. Here, Multi-Locus Genome-Wide Association Study (ML-GWAS) was undertaken in an association mapping panel of 131 accessions, genotyped using 68,925 SNPs identified by genotyping by sequencing approach. Phenotypic evaluation data of five environments comprising 3 years and two locations were used. GWAS was performed for three flowering time traits including days to 5%, 50%, and 95% flowering, days to maturity, and plant height by employing five ML-GWAS methods: FASTmrEMMA, FASTmrMLM, ISIS EM-BLASSO, mrMLM, and pLARmEB. A total of 335 unique QTNs have been identified for five traits across five environments. 109 QTNs were stable as observed in ≥2 methods and/or environments, explaining up to 36.6% phenotypic variance. For three flowering time traits, days to maturity, and plant height, 53, 30, and 27 stable QTNs, respectively, were identified. Candidate genes having roles in flower, pollen, embryo, seed and fruit development, and xylem/phloem histogenesis have been identified. Gene expression of candidate genes for flowering and plant height were studied using transcriptome of an early maturing variety Sharda (IC0523807). The present study unravels QTNs/candidate genes underlying complex flowering, days to maturity, and plant height traits in linseed.

Multi-Locus GWAS for Grain Weight-Related Traits Under Rain-Fed Conditions in Common Wheat (Triticum aestivum L.).

In wheat, a multi-locus genome-wide association study (ML-GWAS) was conducted for the four grain weight-related traits (days to anthesis, grain filling duration, grain number per ear, and grain weight per ear) using data recorded under irrigated (IR) and rain-fed (RF) conditions. Seven stress-related indices were estimated for these four traits: (i) drought resistance index (DI), (ii) geometric mean productivity (GMP), (iii) mean productivity index (MPI), (iv) relative drought index (RDI), (v) stress tolerance index (STI), (vi) yield index, and (vii) yield stability index (YSI). The association panel consisted of a core collection of 320 spring wheat accessions representing 28 countries. The panel was genotyped using 9,627 single nucleotide polymorphisms (SNPs). The genome-wide association (GWA) analysis provided 30 significant marker-trait associations (MTAs), distributed as follows: (i) IR (15 MTAs), (ii) RF (14 MTAs), and (iii) IR+RF (1 MTA). In addition, 153 MTAs were available for the seven stress-related indices. Five MTAs co-localized with previously reported QTLs/MTAs. Candidate genes (CGs) associated with different MTAs were also worked out. Gene ontology (GO) analysis and expression analysis together allowed the selection of the two CGs, which may be involved in response to drought stress. These two CGs included: TraesCS1A02G331000 encoding RNA helicase and TraesCS4B02G051200 encoding microtubule-associated protein 65. The results supplemented the current knowledge on genetics for drought tolerance in wheat. The results may also be used for future wheat breeding programs to develop drought-tolerant wheat cultivars.

Advances and Challenges for QTL Analysis and GWAS in the Plant-Breeding of High-Yielding: A Focus on Rapeseed.

Yield is one of the most important agronomic traits for the breeding of rapeseed (Brassica napus L), but its genetic dissection for the formation of high yield remains enigmatic, given the rapid population growth. In the present review, we review the discovery of major loci underlying important agronomic traits and the recent advancement in the selection of complex traits. Further, we discuss the benchmark summary of high-throughput techniques for the high-resolution genetic breeding of rapeseed. Biparental linkage analysis and association mapping have become powerful strategies to comprehend the genetic architecture of complex agronomic traits in crops. The generation of improved crop varieties, especially rapeseed, is greatly urged to enhance yield productivity. In this sense, the whole-genome sequencing of rapeseed has become achievable to clone and identify quantitative trait loci (QTLs). Moreover, the generation of high-throughput sequencing and genotyping techniques has significantly enhanced the precision of QTL mapping and genome-wide association study (GWAS) methodologies. Furthermore, this study demonstrates the first attempt to identify novel QTLs of yield-related traits, specifically focusing on ovule number per pod (ON). We also highlight the recent breakthrough concerning single-locus-GWAS (SL-GWAS) and multi-locus GWAS (ML-GWAS), which aim to enhance the potential and robust control of GWAS for improved complex traits.

Genome-Wide Association Study of QTLs Conferring Resistance to Bacterial Leaf Streak in Rice.

Bacterial leaf streak (BLS) is a devastating rice disease caused by the bacterial pathogen, Xanthomonas oryzae pv. oryzicola (Xoc), which can result in severe damage to rice production worldwide. Based on a total of 510 rice accessions, trialed in two seasons and using six different multi-locus GWAS methods (mrMLM, ISIS EM-BLASSO, pLARmEB, FASTmrMLM, FASTmrEMMA and pKWmEB), 79 quantitative trait nucleotides (QTNs) reflecting 69 QTLs for BLS resistance were identified (LOD > 3). The QTNs were distributed on all chromosomes, with the most distributed on chromosome 11, followed by chromosomes 1 and 5. Each QTN had an additive effect of 0.20 (cm) and explained, on average, 2.44% of the phenotypic variance, varying from 0.00-0.92 (cm) and from 0.00-9.86%, respectively. Twenty-five QTNs were detected by at least two methods. Among them, qnBLS11.17 was detected by as many as five methods. Most of the QTNs showed a significant interaction with their environment, but no QTNs were detected in both seasons. By defining the QTL range for each QTN according to the LD half-decay distance, a total of 848 candidate genes were found for nine top QTNs. Among them, more than 10% were annotated to be related to biotic stress resistance, and five showed a significant response to Xoc infection. Our results could facilitate the in-depth study and marker-assisted improvement of rice resistance to BLS.

Multi-locus genome-wide association mapping for spike-related traits in bread wheat (Triticum aestivum L.).

BACKGROUND: Bread wheat (Triticum aestivum L.) is one of the most important cereal food crops for the global population. Spike-layer uniformity (the consistency of the spike distribution in the vertical space)-related traits (SLURTs) are quantitative and have been shown to directly affect yield potential by modifying the plant architecture. Therefore, these parameters are important breeding targets for wheat improvement. The present study is the first genome-wide association study (GWAS) targeting SLURTs in wheat. In this study, a set of 225 diverse spring wheat accessions were used for multi-locus GWAS to evaluate SLURTs, including the number of spikes per plant (NSPP), spike length (SL), number of spikelets per spike (NSPS), grain weight per spike (GWPS), lowest tiller height (LTH), spike-layer thickness (SLT), spike-layer number (SLN) and spike-layer uniformity (SLU). RESULTS: In total, 136 significant marker trait associations (MTAs) were identified when the analysis was both performed individually and combined for two environments. Twenty-nine MTAs were detected in environment one, 48 MTAs were discovered in environment two and 59 MTAs were detected using combined data from the two environments. Altogether, 15 significant MTAs were found for five traits in one of the two environments, and four significant MTAs were detected for the two traits, LTH and SLU, in both environments i.e. E1, E2 and also in combined data from the two environments. In total, 279 candidate genes (CGs) were identified, including Chaperone DnaJ, ABC transporter-like, AP2/ERF, SWEET sugar transporter, as well as genes that have previously been associated with wheat spike development, seed development and grain yield. CONCLUSIONS: The MTAs detected through multi-locus GWAS will be useful for improving SLURTs and thus yield in wheat production through marker-assisted and genomic selection.

Genome-wide association mapping reveals key genomic regions for physiological and yield-related traits under salinity stress in wheat (Triticum aestivum L.).

A genome-wide association study (GWAS) was conducted using six different multi-locus GWAS models and 35K SNP array to demarcate genomic regions underlying reproductive stage salinity tolerance. Marker-trait association analysis was performed for salt tolerance indices (STI) of 11 morpho-physiological traits, and the actual concentrations of Na+ and K+, and the Na+/K+ ratio in flag leaf. A total of 293 significantly associated quantitative trait nucleotides (QTNs) for 14 morpho-physiological traits were identified. Of these 293 QTNs, 12 major QTNs with R2 ≥ 10.0% were detected in three or more GWAS models. Novel major QTNs were identified for plant height, number of effective tillers, biomass, grain yield, thousand grain weight, Na+ and K+ content, and the Na+/K+ ratio in flag leaf. Moreover, 48 candidate genes were identified from the associated genomic regions. The QTNs identified in this study could potentially be targeted for improving salinity tolerance in wheat.

Genetic dissection of flowering time in flax (Linum usitatissimum L.) through single- and multi-locus genome-wide association studies.

In a rapidly changing climate, flowering time (FL) adaptation is important to maximize seed yield in flax (Linum usitatissimum L.). However, our understanding of the genetic mechanism underlying FL in this multipurpose crop remains limited. With the aim of dissecting the genetic architecture of FL in flax, a genome-wide association study (GWAS) was performed on 200 accessions of the flax core collection evaluated in four environments. Two single-locus and six multi-locus models were applied using 70,935 curated single nucleotide polymorphism (SNP) markers. A total of 40 quantitative trait nucleotides (QTNs) associated with 27 quantitative trait loci (QTL) were identified in at least two environments. The number of QTL with positive-effect alleles in accessions was significantly correlated with FL (r = 0.77 to 0.82), indicating principally additive gene actions. Nine QTL were significant in at least three of the four environments accounting for 3.06-14.71% of FL variation. These stable QTL spanned regions that harbored 27 Arabidopsis thaliana and Oryza sativa FL-related orthologous genes including FLOWERING LOCUS T (Lus10013532), FLOWERING LOCUS D (Lus10028817), transcriptional regulator SUPERMAN (Lus10021215), and gibberellin 2-beta-dioxygenase 2 (Lus10037816). In silico gene expression analysis of the 27 FL candidate gene orthologous suggested that they might play roles in the transition from vegetative to reproductive phase, flower development and fertilization. Our results provide new insights into the QTL architecture of flowering time in flax, identify potential candidate genes for further studies, and demonstrate the effectiveness of combining different GWAS models for the genetic dissection of complex traits.

Optimized permutation testing for information theoretic measures of multi-gene interactions.

BACKGROUND: Permutation testing is often considered the "gold standard" for multi-test significance analysis, as it is an exact test requiring few assumptions about the distribution being computed. However, it can be computationally very expensive, particularly in its naive form in which the full analysis pipeline is re-run after permuting the phenotype labels. This can become intractable in multi-locus genome-wide association studies (GWAS), in which the number of potential interactions to be tested is combinatorially large. RESULTS: In this paper, we develop an approach for permutation testing in multi-locus GWAS, specifically focusing on SNP-SNP-phenotype interactions using multivariable measures that can be computed from frequency count tables, such as those based in Information Theory. We find that the computational bottleneck in this process is the construction of the count tables themselves, and that this step can be eliminated at each iteration of the permutation testing by transforming the count tables directly. This leads to a speed-up by a factor of over 103 for a typical permutation test compared to the naive approach. Additionally, this approach is insensitive to the number of samples making it suitable for datasets with large number of samples. CONCLUSIONS: The proliferation of large-scale datasets with genotype data for hundreds of thousands of individuals enables new and more powerful approaches for the detection of multi-locus genotype-phenotype interactions. Our approach significantly improves the computational tractability of permutation testing for these studies. Moreover, our approach is insensitive to the large number of samples in these modern datasets. The code for performing these computations and replicating the figures in this paper is freely available at https://github.com/kunert/permute-counts .

Genome-Wide Association Study and QTL Meta-Analysis Identified Novel Genomic Loci Controlling Potassium Use Efficiency and Agronomic Traits in Bread Wheat.

Potassium use efficiency, a complex trait, directly impacts the yield potential of crop plants. Low potassium efficiency leads to a high use of fertilizers, which is not only farmer unfriendly but also deteriorates the environment. Genome-wide association studies (GWAS) are widely used to dissect complex traits. However, most studies use single-locus one-dimensional GWAS models which do not provide true information about complex traits that are controlled by multiple loci. Here, both single-locus GWAS (MLM) and multi-locus GWAS (pLARmEB, FASTmrMLM, mrMLM, FASTmrEMMA) models were used with genotyping from 90 K Infinium SNP array and phenotype derived from four normal and potassium-stress environments, which identified 534 significant marker-trait associations (MTA) for agronomic and potassium related traits: pLARmEB = 279, FASTmrMLM = 213, mrMLM = 35, MLM = 6, FASTmrEMMA = 1. Further screening of these MTA led to the detection of eleven stable loci: q1A, q1D, q2B-1, q2B-2, q2D, q4D, q5B-1, q5B-2, q5B-3, q6D, and q7A. Moreover, Meta-QTL (MQTL) analysis of four independent QTL studies for potassium deficiency in bread wheat located 16 MQTL on 13 chromosomes. One locus identified in this study (q5B-1) colocalized with an MQTL (MQTL_11 ), while the other ten loci were novel associations. Gene ontology of these loci identified 20 putative candidate genes encoding functional proteins involved in key pathways related to stress tolerance, sugar metabolism, and nutrient transport. These findings provide potential targets for breeding potassium stress resistant wheat cultivars and advocate the advantages of multi-locus GWAS models for studying complex traits.

Combination of multi-locus genome-wide association study and QTL mapping reveals genetic basis of tassel architecture in maize.

Maize tassel architecture is a complex quantitative trait that is significantly correlated with biomass yield and grain yield. The present study evaluated the major trait of maize tassel architecture, namely, tassel branch number (TBN), in an association population of 359 inbred lines and an IBM Syn 10 population of 273 doubled haploid lines across three environments. Approximately 43,958 high-quality single nucleotide polymorphisms were utilized to detect significant QTNs associated with TBN based on new multi-locus genome-wide association study methods. There were 30, 38, 73, 40, 47, and 53 QTNs associated with tassel architecture that were detected using the FastmrEMMA, FastmrMLM, EM-BLASSO, mrMLM, pkWMEB, and pLARmEB models, respectively. Among these QTNs, 51 were co-identified by at least two of these methods. In addition, 12 QTNs were consistently detected across multiple environments. Furthermore, 19 QTLs distributed on chromosomes 1, 2, 3, 4, 6, and 7 were detected in 3 environments and the BLUP model based on 6618 bin markers, which explained 3.64-10.96% of the observed phenotypic variations in TBN. Of these, three QTLs were co-detected in two environments. One QTN associated with TBN was localized to one QTL. Approximately 55 candidate genes were detected by common QTNs and LD criteria. One candidate gene, Zm00001d016615, was identified as a putative target of the RA1 gene. Meanwhile, RA1 was previously validated to plays an important role in tassel development. In addition, the newly identified candidate genes Zm00001d003939, Zm00001d030212, Zm00001d011189, and Zm00001d042794 have been reported to involve in a spikelet meristem identity module. The findings of the present study improve our understanding of the genetic basis of tassel architecture in maize.

Dissecting the genome-wide genetic variants of milling and appearance quality traits in rice.

Higher head rice yield (HRY), which represents the proportion of intact grains that survive milling, and lower grain chalkiness (opacity) are key quality traits. We investigated the genetic basis of HRY and chalkiness in 320 diverse resequenced accessions of indica rice with integrated single- and multi-locus genome-wide association studies using 2.26 million single-nucleotide polymorphisms. We identified novel haplotypes that underly higher HRY on chromosomes 3, 6, 8, and 11, and that lower grain chalkiness in a fine-mapped region on chromosome 5. Whole-genome sequencing of 92 IRRI breeding lines was performed to identify the genetic variants of HRY and chalkiness. Rare and novel haplotypes were found for lowering chalkiness, but missing alleles hindered progress towards enhancing HRY in breeding material. The novel haplotypes that we identified have potential use in breeding programs aimed at improving these important traits in the rice crop.