Significant Quantitative Trait Loci Research Articles

Behavioral phenotypes revealed during reversal learning are linked with novel genetic loci in diversity outbred mice

Impulsive behavior and impulsivity are heritable phenotypes that are strongly associated with risk for substance use disorders. Identifying the neurogenetic mechanisms that influence impulsivity may also reveal novel biological insights into addiction vulnerability. Our past studies using the BXD and Collaborative Cross (CC) recombinant inbred mouse panels have revealed that behavioral indicators of impulsivity measured in a reversal-learning task are heritable and are genetically correlated with aspects of intravenous cocaine self-administration. Genome-wide linkage studies in the BXD panel revealed a quantitative trait locus (QTL) on chromosome 10, but we expect to identify additional QTL by testing in a population with more genetic diversity. To this end, we turned to Diversity Outbred (DO) mice; 392 DO mice (156 males, 236 females) were phenotyped using the same reversal learning test utilized previously. Our primary indicator of impulsive responding, a measure that isolates the relative difficulty mice have with reaching performance criteria under reversal conditions, revealed a genome-wide significant QTL on chromosome 7 (max LOD score = 8.73, genome-wide corrected p<0.05). A measure of premature responding akin to that implemented in the 5-choice serial reaction time task yielded a suggestive QTL on chromosome 17 (max LOD score = 9.14, genome-wide corrected <0.1). Candidate genes were prioritized (2900076A07Rik, Wdr73 and Zscan2) based upon expression QTL data we collected in DO and CC mice and analyses using publicly available gene expression and phenotype databases. These findings may advance understanding of the genetics that drive impulsive behavior and enhance risk for substance use disorders.

Genome-Wide Association Studies Revealed Significant QTLs and Candidate Genes Associated with Backfat and Loin Muscle Area in Pigs Using Imputation-Based Whole Genome Sequencing Data.

Improvement of carcass features is an essential goal in pig genetic breeding programs. Backfat (BF) and loin muscle area (LMA) are important carcass production metrics and useful indicators of pig production performance and lean meat rate. However, the genetic architecture of BF and LMA traits remains elusive. To identify quantitative trait loci (QTLs) and genes associated with these traits, we performed a genome-wide association study (GWAS) using imputation-based whole genome sequencing data for four phenotypes (adjusted 100 kg BF and LMA, adjusted 100 kg BF EBV and LMA EBV) in 1131 pigs from 3 breeds (French Yorkshire, Landrace, and Duroc). After genotype imputation and quality control, 14,163,315 single nucleotide polymorphisms (SNPs) were retained for further analysis. For the adjusted 100 kg BF trait, using the 2-LOD drop method, a QTL with a 13.4 Kb interval (2.91 to 2.93 Mb on SSC2) and containing a SHANK2 gene was defined. In addition, two QTLs with 135.40 Kb (from 66.10 to 66.23 Mb) and 3.12 Kb (from 66.886 to 66.889 Mb) intervals containing CCND2 and TSPAN11 genes, respectively, were found on SSC5. For the BF-EBV trait, two QTLs (128.77 Kb from 66.10 to 66.23 Mb on SSC5 and 42.10 Kb from 2.89 to 2.93 Mb on SSC2) were identified. Notably, CCND2 and SHANK2 were the only candidate genes in their respective QTL interval. Furthermore, we detected a 3.33 Kb (66.106 to 66.110 Mb on SSC2) haplotype block which was detected as affecting the BF_EBV trait, which only contained the CCND2 gene. Thus, we suggested CCND2 and SHANK2 as strong candidate genes for regulating the BF trait for pigs. The empirical confidence intervals of the QTLs were 1.14 Mb (165.65 to 166.79 Mb on SSC6) for adjusted 100 kg LMA and 1.49 Mb (165.26-166.74 Mb on SSC6) for LMA-EBV. These two confidence intervals contained 13 and 28 annotated genes, respectively. Our results provide a deeper understanding of the genetic basis of pig carcass traits. The identified molecular markers will be useful for selecting breeding lines for breeding pigs with superior carcass traits.

Genome-wide QTL mapping and RNA-seq reveal the genetic variation influencing growth traits in giant grouper (Epinephelus lanceolatus)

Genetic improvement of growth traits is a major target of grouper aquaculture and breeding. As one of the largest groupers, the giant grouper (Epinephelus lanceolatus) has excellent growth performance, although the genetic basis of its growth traits has been rarely studied. In this study, we successfully constructed a high-density genetic linkage map with 2988 SNPs generated by genotype-by-sequencing of 178 individuals, which belong to an F1 full-sibling family. The length of the map was 3231.5 cM with an average interval of 1.21 cM. Then, we performed genome-wide QTL (quantitative trait locus) mapping for five growth traits including all length, body length, body height, body thickness, and body weight in the giant grouper and identified six growth-associated QTLs, which explained 4.65–12.56% of the phenotypic variance. These QTLs were distributed on five linkage groupers (LGs) of our sex-averaged linkage map with two QTLs on LG11, four QTLs on LG7, LG10, LG15, and LG23. The genes identified within the significant QTLs were validated using qPCR and the results showed six significantly upregulated genes (kalrn, ypel1, supt7l, lacs5, ccnd2, mybpc2) in tissues (muscle, fat, liver, gill, etc.) of the fast vs slow growth groups were highlighted as promising candidates. Further, RNA-seq analysis revealed 484 differentially expressed genes (DEGs) between fast/slow growth groups that play roles in the RNA transport, metabolic pathways, PPAR signaling pathway, and carbon metabolism pathways. Notably, 27 DEGs were detected in the identified growth-associated-QTL regions. Those candidate genes shared between QTL mapping and DEGs may play important roles in regulating cell growth, signal transduction, carbohydrate metabolism and skeletal development. Overall, our findings are useful for improving the genetic process for molecular marker-assisted selection and provide new insights into elucidating the molecular mechanism of growth variation in this species.

Combining QTL mapping and RNA-Seq Unravels candidate genes for Alfalfa (Medicago sativa L.) leaf development

BackgroundLeaf size affects crop canopy morphology and photosynthetic efficiency, which can influence forage yield and quality. It is of great significance to mine the key genes controlling leaf development for breeding new alfalfa varieties. In this study, we mapped leaf length (LL), leaf width (LW), and leaf area (LA) in an F1 mapping population derived from a cultivar named ZhongmuNo.1 with larger leaf area and a landrace named Cangzhou with smaller leaf area.ResultsThis study showed that the larger LW was more conducive to increasing LA. A total of 24 significant quantitative trait loci (QTL) associated with leaf size were identified on both the paternal and maternal linkage maps. Among them, nine QTL explained about 11.50–22.45% phenotypic variation. RNA-seq analysis identified 2,443 leaf-specific genes and 3,770 differentially expressed genes. Combining QTL mapping, RNA-seq alalysis, and qRT-PCR, we identified seven candidate genes associated with leaf development in five major QTL regions.ConclusionOur study will provide a theoretical basis for marker-assisted breeding and lay a foundation for further revealing molecular mechanism of leaf development in alfalfa.

The Genetic Architecture of Meat Quality Traits in a Crossbred Commercial Pig Population.

Meat quality is of importance in consumer acceptance and purchasing tendency of pork. However, the genetic architecture of pork meat quality traits remains elusive. Herein, we conducted genome-wide association studies to detect single nucleotide polymorphisms (SNPs) and genes affecting meat pH and meat color (L*, lightness; a*, redness; b*, yellowness) in 1518 three-way crossbred pigs. All individuals were genotyped using the GeneSeek Porcine 50K BeadChip. In sum, 30 SNPs and 20 genes are found to be associated with eight meat quality traits. Notably, we detect one significant quantitative trait locus (QTL) on SSC15 with a 143 kb interval for meat pH (pH_12h), together with the most promising candidate TNS1. Interestingly, two newly identified SNPs located in the TTLL4 gene demonstrate the highest phenotypic variance of pH_12h in this QTL, at 2.67%. The identified SNPs are useful for the genetic improvement of meat quality traits in pigs by assigning higher weights to associated SNPs in genomic selection.

COX7A2L genetic variants determine cardiorespiratory fitness in mice and human

Mitochondrial respiratory complexes form superassembled structures called supercomplexes. COX7A2L is a supercomplex-specific assembly factor in mammals, although its implication for supercomplex formation and cellular metabolism remains controversial. Here we identify a role for COX7A2L for mitochondrial supercomplex formation in humans. By using human cis-expression quantitative trait loci data, we highlight genetic variants in the COX7A2L gene that affect its skeletal muscle expression specifically. The most significant cis-expression quantitative trait locus is a 10-bp insertion in the COX7A2L 3′ untranslated region that increases messenger RNA stability and expression. Human myotubes harboring this insertion have more supercomplexes and increased respiration. Notably, increased COX7A2L expression in the muscle is associated with lower body fat and improved cardiorespiratory fitness in humans. Accordingly, specific reconstitution of Cox7a2l expression in C57BL/6J mice leads to higher maximal oxygen consumption, increased lean mass and increased energy expenditure. Furthermore, Cox7a2l expression in mice is induced specifically in the muscle upon exercise. These findings elucidate the genetic basis of mitochondrial supercomplex formation and function in humans and show that COX7A2L plays an important role in cardiorespiratory fitness, which could have broad therapeutic implications in reducing cardiovascular mortality.

Integrating multi-locus genome-wide association studies with transcriptomic data to identify genetic loci underlying adult root trait responses to drought stress in flax (Linum usitatissimum L.)

Water stress is a major constraint on crop production and, root systems are one of the key features of plants determining drought tolerance and yield. In this study, five root morphological traits and their stability indices were evaluated at the reproductive stage on an association panel consisting of 120 diverse Linum usitatissimum accessions grown under well-watered and water-limiting conditions. To identify quantitative trait loci (QTL) and candidate genes positively influencing root traits under drought, combined multi-locus genome-wide association studies (ML-GWAS) and transcriptomic data analysis were carried out. A total of 112 QTL were identified accounting for 0.45–24.28 % of the phenotypic variation for root-related traits. Fifty QTL were detected by at least two ML-GWAS models, and 26 were co-located with previously reported QTL associated with yield-related traits under drought and early root and shoot development. Phenotypic differences between two contrasting subsets of accessions for the traits assessed were attributable to the accumulation of positive QTL alleles (PQTL), where the subset with the largest number of PQTL registered 154 % and 69 % greater total root length and yield under drought stress, respectively, than the subset with the fewest PQTL. Transcriptomic data analysis identified 766 differentially expressed genes (DEGs) responsive to drought stress in 108 QTL. Annotation of the 766 DEGs yielded functional genes involved in root development, stomatal closure, ROS (reactive oxygen species) scavenging, and hormone responses, among others. Taken together, the combined use of GWAS and transcriptomic data analyses provide the foundation for our enhanced understanding of root trait morphological changes in response to drought stress, and to achieve superior yield resilience/stability under water shortages in flax through enhanced molecular breeding. All data supporting the findings of this study are available within the paper and within its Supplementary data • Large genetic variation observed for adult root traits under drought and irrigated conditions. • Root traits explained 25–32 % of yield variation under drought stress. • A total of 112 QTL were identified for root traits and their stability indices in flax. • Twenty-six QTL co-located with previously reported QTL for yield traits under drought and root and shoot development. • Transcriptomic data analysis identified 766 drought responsive differentially expressed genes within the LD blocks of 108 significant QTL.

Genetic factors underlying anaerobic germination in rice: Genome-wide association study and transcriptomic analysis.

The success of rice (Oryza sativa L.) germination and survival under submerged conditions is mainly determined by the rapid growth of the coleoptile to reach the water surface. Previous reports have shown the presence of genetic variability within rice accessions in the levels of flooding tolerance during germination or anaerobic germination (AG). Although many studies have focused on the physiological mechanisms of oxygen stress, few studies have explored the breadth of natural variation in AG tolerance-related traits in rice. In this study, we evaluated the coleoptile lengths of a geographically diverse rice panel of 241 accessions, including global accessions along with elite breeding lines and released cultivars from the United States, under the normal and flooded conditions in laboratory and greenhouse environments. A genome-wide association study (GWAS) was performed using a 7K single-nucleotide polymorphism (SNP) array and the phenotypic data of normal coleoptile length, flooded coleoptile length, flooding tolerance index, and survival at 14 d after seeding (DAS). Out of the 30 significant GWAS quantitative trait loci (QTL) regions identified, 14 colocalized with previously identified candidate genes of AG tolerance, whereas 16 were potentially novel. Two rice accessions showing contrasting phenotypic responses to AG stress were selected for the transcriptomics study. The combined approach of GWAS and transcriptomics analysis identified 77 potential candidate genes related to AG tolerance. The findings of our study may assist rice improvement programs in developing rice cultivars with robust tolerance under flooding stress during germination and the early seedling stage.

Identification of novel major and minor quantitative trait loci associated with bacterial blight resistance in rice from Oryza nivara‐derived wild introgression lines

AbstractWild species are known to be reservoir for agronomically important traits including disease resistance in crops. Bacterial blight (BB) is one of the major diseases of rice causing significant yield reduction, and host plant resistance plays a major role in the management of the disease. In this study, we employed backcross introgression lines (BILs) of ‘Swarna’ containing wild introgressions from two accessions of Oryza nivara IRGC81848 and IRGC81832 in order to map quantitative trait loci (QTLs) for BB resistance. A total of 22 and 43 QTLs for BB resistance were detected respectively on 12 chromosomes, which explained between 2.5% to 18.09% of the phenotypic variance in the two populations. Of the significant QTLs, qBB‐1‐1 (RM259‐RM9) and qBB‐10‐1 (RM474‐RM271) were detected across the two populations and the resistance contributing alleles were from donor wild accessions. Two major QTLs in ‘Swarna’/O. nivara IRGC81848 (NPS lines) and seven QTLs in ‘Swarna’/O. nivara IRGC81832 (NPK lines) were consistently detected across the years in the respective populations. Novel QTLs qBB‐10‐1 and qBB‐12‐1 are identified as candidate genomic regions for further fine mapping. These stable QTLs identified can be utilized for enhancing BB resistance in elite rice genotypes via marker‐assisted or genomic selection strategies.

Quantitative trait loci mapping reveals important genomic regions controlling root architecture and shoot biomass under nitrogen, phosphorus, and potassium stress in rapeseed (Brassica napus L.).

Plants rely on root systems for nutrient uptake from soils. Marker-assisted selection helps breeders to select desirable root traits for effective nutrient uptake. Here, 12 root and biomass traits were investigated at the seedling stage under low nitrogen (LN), low phosphorus (LP), and low potassium (LK) conditions, respectively, in a recombinant inbred line (RIL) population, which was generated from Brassica napus L. Zhongshuang11 and 4D122 with significant differences in root traits and nutrient efficiency. Significant differences for all the investigated traits were observed among RILs, with high heritabilities (0.43–0.74) and high correlations between the different treatments. Quantitative trait loci (QTL) mapping identified 57, 27, and 36 loci, explaining 4.1–10.9, 4.6–10.8, and 4.9–17.4% phenotypic variances under LN, LP, and LK, respectively. Through QTL-meta analysis, these loci were integrated into 18 significant QTL clusters. Four major QTL clusters involved 25 QTLs that could be repeatedly detected and explained more than 10% phenotypic variances, including two NPK-common and two specific QTL clusters (K and NK-specific), indicating their critical role in cooperative nutrients uptake of N, P, and K. Moreover, 264 genes within the four major QTL clusters having high expressions in roots and SNP/InDel variations between two parents were identified as potential candidate genes. Thirty-eight of them have been reported to be associated with root growth and development and/or nutrient stress tolerance. These key loci and candidate genes lay the foundation for deeper dissection of the NPK starvation response mechanisms in B. napus.

A first insight into the genetics of maturity trait in Runner × Virginia types peanut background

'Runner' and 'Virginia', the two main market types of Arachis hypogaea subspecies hypogaea, differ in several agricultural and industrial characteristics. One such trait is time to maturation (TTM), contributing to the specific environmental adaptability of each subspecies. However, little is known regarding TTM's genetic and molecular control in peanut in general, and particularly in the Runner/Virginia background. Here, a recombinant inbred line population, originating from a cross between an early-maturing Virginia and a late-maturing Runner type, was used to detect quantitative trait loci (QTL) for maturity. An Arachis SNP-array was used for genotyping, and a genetic map with 1425 SNP loci spanning 24 linkage groups was constructed. Six significant QTLs were identified for the maturity index (MI) trait on chromosomes A04, A08, B02 and B04. Two sets of stable QTLs in the same loci were identified, namely qMIA04a,b and qMIA08_2a,b with 11.5%, 8.1% and 7.3%, 8.2% of phenotypic variation explained respectively in two environments. Interestingly, one consistent QTL, qMIA04a,b, overlapped with the previously reported QTL in a Virginia × Virginia population having the same early-maturing parent ('Harari') in common. The information and materials generated here can promote informed targeting of peanut idiotypes by indirect marker-assisted selection.

Identification of Quantitative Trait Loci Associated with Bacterial Leaf Spot Resistance in Baby Leaf Lettuce.

Spring mix is a popular packaged salad that contains lettuce (Lactuca sativa L.) as one of its main ingredients. Plants for baby leaf lettuce (BLL) production are grown at very high densities, which enhances the occurrence of bacterial leaf spot (BLS) caused by Xanthomonas hortorum pv. vitians (Xhv), a disease that can make the crop unmarketable. The market demands disease-free, high-quality BLL all year round. Growing highly BLS-resistant cultivars will reduce loss of yield and quality, thus minimizing economic detriment to lettuce and spring mix growers. The research objectives were to identify lettuce accessions resistant to BLS and associated quantitative trait loci (QTL). A total of 495 lettuce accessions were screened with six isolates (BS0347, BS2861, BS3127, L7, L44, and Sc8B) of Xhv. Accessions showing overall high-level resistance to all tested Xhv isolates were 'Bunte Forellen', PI 226514, 'La Brillante', ARM09-161-10-1-4, 'Grenadier', 'Bella', PI 491210, 'Delight', and 'Romana Verde del Mercado'. Genome-wide association studies of BLS resistance by mixed linear model analyses identified significant QTLs on four lettuce chromosomes (2, 4, 6, and 8). The most significant QTL was on Chromosome 8 (P = 1.42 × 10-7), which explained 6.7% of total phenotypic variation for the disease severity. Accessions with a high level of resistance detected in this study are valuable resources for lettuce germplasm improvement. Molecular markers closely linked to QTLs can be considered for marker-assisted selection to develop new BLL lettuce cultivars with resistance to multiple races of Xhv.

A significant quantitative trait locus on chromosome Z and its impact on egg production traits in seven maternal lines of meat-type chicken

BackgroundEgg production is economically important in the meat-type chicken industry. To better understand the molecular genetic mechanism of egg production in meat-type chicken, genetic parameter estimation, genome-wide association analyses combined with meta-analyses, Bayesian analyses, and selective sweep analyses were performed to screen single nucleotide polymorphisms (SNPs) and other genetic loci that were significantly associated with egg number traits in 11,279 chickens from seven material lines.ResultsYellow-feathered meat-type chickens laid 115 eggs at 43 weeks of age and white-feathered chickens laid 143 eggs at 60 weeks of age, with heritability ranging from 0.034–0.258. Based on meta-analyses and selective sweep analyses, one region (10.81–13.05 Mb) on chromosome Z was associated with egg number in all lines. Further analyses using the W2 line was also associated with the same region, and 29 SNPs were identified that significantly affected estimation of breeding value of egg numbers. The 29 SNPs were identified as having a significant effect on the egg number EBV in 3194 birds in line W2. There are 36 genes in the region, with glial cell derived neurotrophic factor, DAB adaptor protein 2, protein kinase AMP-activated catalytic subunit alpha 1, NAD kinase 2, mitochondrial, WD repeat domain 70, leukemia inhibitory factor receptor alpha, complement C6, and complement C7 identified as being potentially affecting to egg number. In addition, three SNPs (rs318154184, rs13769886, and rs313325646) associated with egg number were located on or near the prolactin receptor gene.ConclusionOur study used genomic information from different chicken lines and populations to identify a genomic region (spanning 2.24 Mb) associated with egg number. Nine genes and 29 SNPs were identified as the most likely candidate genes and variations for egg production. These results contribute to the identification of candidate genes and variants for egg traits in poultry.

Whole-genome analysis of hard winter wheat germplasm identifies genomic regions associated with spike and kernel traits.

Genetic dissection of yield component traits including spike and kernel characteristics is essential for the continuous improvement in wheat yield. Genome-wide association studies (GWAS) have been frequently used to identify genetic determinants for spike and kernel-related traits in wheat, though none have been employed in hard winter wheat (HWW) which represents a major class in US wheat acreage. Further, mostof these studies relied on assembled diversity panels instead of adapted breeding lines, limiting the transferability of results to practicalwheat breeding. Here we assembled a population of advanced/elite breeding lines and well-adapted cultivars and evaluated over four environments for phenotypic analysis of spike and kernel traits. GWAS identified 17 significant multi-environment marker-trait associations (MTAs) for various traits, representing 12 putative quantitative trait loci (QTLs), with five QTLs affecting multiple traits. Four of these QTLs mapped on three chromosomes 1A, 5B, and 7A for spike length, number of spikelets per spike (NSPS), and kernel length are likely novel. Further, a highly significant QTL was detected on chromosome 7AS that has not been previously associated with NSPS and putative candidate genes were identified in this region. The allelic frequencies of important quantitative trait nucleotides (QTNs)were deduced in a larger set of 1,124 accessions which revealed the importance of identified MTAs in the US HWW breeding programs. The results from this study could be directly used by thebreeders to select the lines with favorable alleles for making crosses, and reported markers will facilitate marker-assisted selection of stable QTLs for yield components in wheat breeding.

Multivariate genome-wide association study of depression, cognition, and memory phenotypes and validation analysis identify 12 cross-ethnic variants

To date, little is known about the pleiotropic genetic variants among depression, cognition, and memory. The current research aimed to identify the potential pleiotropic single nucleotide polymorphisms (SNPs), genes, and pathways of the three phenotypes by conducting a multivariate genome-wide association study and an additional pleiotropy analysis among Chinese individuals and further validate the top variants in the UK Biobank (UKB). In the discovery phase, the participants were 139 pairs of dizygotic twins from the Qingdao Twins Registry. The genome-wide efficient mixed-model analysis identified 164 SNPs reaching suggestive significance (P < 1 × 10−5). Among them, rs3967317 (P = 1.21 × 10−8) exceeded the genome-wide significance level (P < 5 × 10−8) and was also demonstrated to be associated with depression and memory in pleiotropy analysis, followed by rs9863698, rs3967316, and rs9261381 (P = 7.80 × 10−8−5.68 × 10−7), which were associated with all three phenotypes. After imputation, a total of 457 SNPs reached suggestive significance. The top SNP chr6:24597173 was located in the KIAA0319 gene, which had biased expression in brain tissues. Genes and pathways related to metabolism, immunity, and neuronal systems demonstrated nominal significance (P < 0.05) in gene-based and pathway enrichment analyses. In the validation phase, 12 of the abovementioned SNPs reached the nominal significance level (P < 0.05) in the UKB. Among them, three SNPs were located in the KIAA0319 gene, and four SNPs were identified as significant expression quantitative trait loci in brain tissues. These findings may provide evidence for pleiotropic variants among depression, cognition, and memory and clues for further exploring the shared genetic pathogenesis of depression with Alzheimer’s disease.

Linkage Mapping Reveals QTL for Flowering Time-Related Traits under Multiple Abiotic Stress Conditions in Maize.

Variation in flowering plays a major role in maize photoperiod adaptation during long-term domestication. It is of high value to investigate the genetic basis of maize flowering under a wide range of environmental conditions in order to overcome photoperiod sensitivity or enhance stress tolerance. A recombinant inbred line (RIL) population derived from a cross between Huangzaosi and Mo17, composed of 121 lines and genotyped by 8329 specifically developed markers, was field evaluated in two consecutive years under two planting densities (67,500 and 120,000 plants ha−1) and two water treatments (normal irrigation and drought stress at the flowering stage). The days to silking (DTS), days to anthesis (DTA), and anthesis to silking interval (ASI) were all evaluated. Within the RIL population, DTS and DTA expanded as planting density and water deficit increased. For DTA, DTS, ASI, and ASI-delay, a total of 22, 17, 21, and 11 QTLs were identified, respectively. More than two significant QTLs were identified in each of the nine chromosomal intervals. Under diverse conditions and locations, six QTLs (quantitative trait locus) for DTS and DTA were discovered in Chr. 8: 118.13–125.31 Mb. Three chromosome regions, Chr. 3: 196.14–199.89 Mb, Chr. 8: 169.02–172.46 Mb, and Chr. 9: 128.12–137.26 Mb, all had QTLs for ASI-delay under normal and stress conditions, suggesting their possible roles in stress tolerance enhancement. These QTL hotspots will promote early-maturing or multiple abiotic stress-tolerant maize breeding, as well as shed light on the development of maize varieties with a broad range of adaptations.

Linkage analysis and residual heterozygotes derived near isogenic lines reveals a novel protein quantitative trait loci from a Glycine soja accession.

Modern soybean [Glycine max (L.) Merr] cultivars have low overall genetic variation due to repeated bottleneck events that arose during domestication and from selection strategies typical of many soybean breeding programs. In both public and private soybean breeding programs, the introgression of wild soybean (Glycine soja Siebold and Zucc.) alleles is a viable option to increase genetic diversity and identify new sources for traits of value. The objectives of our study were to examine the genetic architecture responsible for seed protein and oil using a recombinant inbred line (RIL) population derived from hybridizing a G. max line (‘Osage’) with a G. soja accession (PI 593983). Linkage mapping identified a total of seven significant quantitative trait loci on chromosomes 14 and 20 for seed protein and on chromosome 8 for seed oil with LOD scores ranging from 5.3 to 31.7 for seed protein content and from 9.8 to 25.9 for seed oil content. We analyzed 3,015 single F4:9 soybean plants to develop two residual heterozygotes derived near isogenic lines (RHD-NIL) populations by targeting nine SNP markers from genotype-by-sequencing, which corresponded to two novel quantitative trait loci (QTL) derived from G. soja: one for a novel seed oil QTL on chromosome 8 and another for a novel protein QTL on chromosome 14. Single marker analysis and linkage analysis using 50 RHD-NILs validated the chromosome 14 protein QTL, and whole genome sequencing of RHD-NILs allowed us to reduce the QTL interval from ∼16.5 to ∼4.6 Mbp. We identified two genomic regions based on recombination events which had significant increases of 0.65 and 0.72% in seed protein content without a significant decrease in seed oil content. A new Kompetitive allele-specific polymerase chain reaction (KASP) assay, which will be useful for introgression of this trait into modern elite G. max cultivars, was developed in one region. Within the significantly associated genomic regions, a total of eight genes are considered as candidate genes, based on the presence of gene annotations associated with the protein or amino acid metabolism/movement. Our results provide better insights into utilizing wild soybean as a source of genetic diversity for soybean cultivar improvement utilizing native traits.

Transcriptomic and proteomic retinal pigment epithelium signatures of age-related macular degeneration

There are currently no treatments for geographic atrophy, the advanced form of age-related macular degeneration. Hence, innovative studies are needed to model this condition and prevent or delay its progression. Induced pluripotent stem cells generated from patients with geographic atrophy and healthy individuals were differentiated to retinal pigment epithelium. Integrating transcriptional profiles of 127,659 retinal pigment epithelium cells generated from 43 individuals with geographic atrophy and 36 controls with genotype data, we identify 445 expression quantitative trait loci in cis that are asssociated with disease status and specific to retinal pigment epithelium subpopulations. Transcriptomics and proteomics approaches identify molecular pathways significantly upregulated in geographic atrophy, including in mitochondrial functions, metabolic pathways and extracellular cellular matrix reorganization. Five significant protein quantitative trait loci that regulate protein expression in the retinal pigment epithelium and in geographic atrophy are identified - two of which share variants with cis- expression quantitative trait loci, including proteins involved in mitochondrial biology and neurodegeneration. Investigation of mitochondrial metabolism confirms mitochondrial dysfunction as a core constitutive difference of the retinal pigment epithelium from patients with geographic atrophy. This study uncovers important differences in retinal pigment epithelium homeostasis associated with geographic atrophy.

Genome-Wide Association Study Identified a Quantitative Trait Locus and Two Candidate Genes on Sus scrofa Chromosome 2 Affecting Vulvar Traits of Suhuai Pigs.

Vulvar size and angle are meaningful traits in pig production. Sows with abnormal vulva generally show reproductive disorders. In order to excavate candidate loci and genes associated with pig’s vulvar traits, 270 Suhuai pigs with vulvar phenotype were genotyped by a porcine single nucleotide polymorphisms (SNP) Chip. Then, Chip data were imputed using resequenced data of 30 Suhuai pigs as a reference panel. Next, we estimated the heritability and performed a genome-wide association study (GWAS) for vulvar traits. The heritabilities for the traits vulvar length (VL), vulvar width (VW) and vulvar angle (VA) in this pig population were 0.23, 0.32 and 0.22, respectively. GWAS based on Chip data identified nine significant SNPs on the Sus scrofa chromosomes (SSC) 2, 7, 9 and 13 for VL or VW. GWAS based on imputed data identified 11 new quantitative trait loci (QTL) on SSC1, 2, 7, 8, 9, 11, 13, 16 and 17 for VL or VW. The most significant QTL for VL on SSC2 were refined to a 3.48–3.97 Mb region using linkage disequilibrium and linkage analysis (LDLA). In this refined region, FGF19 and CCND1, involved in the development of the reproductive tract, cell growth and vulvar cancer, could be new candidate genes affecting VL. Our results provided potential genetic markers for the breeding of vulvar traits in pigs and deepened the understanding of the genetic mechanism of vulvar traits.

COMPILE: a GWAS computational pipeline for gene discovery in complex genomes

BackgroundGenome-Wide Association Studies (GWAS) are used to identify genes and alleles that contribute to quantitative traits in large and genetically diverse populations. However, traits with complex genetic architectures create an enormous computational load for discovery of candidate genes with acceptable statistical certainty. We developed a streamlined computational pipeline for GWAS (COMPILE) to accelerate identification and annotation of candidate maize genes associated with a quantitative trait, and then matches maize genes to their closest rice and Arabidopsis homologs by sequence similarity.ResultsCOMPILE executed GWAS using a Mixed Linear Model that incorporated, without compression, recent advancements in population structure control, then linked significant Quantitative Trait Loci (QTL) to candidate genes and RNA regulatory elements contained in any genome. COMPILE was validated using published data to identify QTL associated with the traits of α-tocopherol biosynthesis and flowering time, and identified published candidate genes as well as additional genes and non-coding RNAs. We then applied COMPILE to 274 genotypes of the maize Goodman Association Panel to identify candidate loci contributing to resistance of maize stems to penetration by larvae of the European Corn Borer (Ostrinia nubilalis). Candidate genes included those that encode a gene of unknown function, WRKY and MYB-like transcriptional factors, receptor-kinase signaling, riboflavin synthesis, nucleotide-sugar interconversion, and prolyl hydroxylation. Expression of the gene of unknown function has been associated with pathogen stress in maize and in rice homologs closest in sequence identity.ConclusionsThe relative speed of data analysis using COMPILE allowed comparison of population size and compression. Limitations in population size and diversity are major constraints for a trait and are not overcome by increasing marker density. COMPILE is customizable and is readily adaptable for application to species with robust genomic and proteome databases.