Identification Of Genomic Regions Research Articles

Genomic regions, candidate genes, and pleiotropic variants associated with physiological and anatomical indicators of heat stress response in lactating sows

BackgroundHeat stress (HS) poses significant threats to the sustainability of livestock production. Genetically improving heat tolerance could enhance animal welfare and minimize production losses during HS events. Measuring phenotypic indicators of HS response and understanding their genetic background are crucial steps to optimize breeding schemes for improved climatic resilience. The identification of genomic regions and candidate genes influencing the traits of interest, including variants with pleiotropic effects, enables the refinement of genotyping panels used to perform genomic prediction of breeding values and contributes to unraveling the biological mechanisms influencing heat stress response. Therefore, the main objectives of this study were to identify genomic regions, candidate genes, and potential pleiotropic variants significantly associated with indicators of HS response in lactating sows using imputed whole-genome sequence (WGS) data. Phenotypic records for 18 traits and genomic information from 1,645 lactating sows were available for the study. The genotypes from the PorcineSNP50K panel containing 50,703 single nucleotide polymorphisms (SNPs) were imputed to WGS and after quality control, 1,622 animals and 7,065,922 SNPs were included in the analyses.ResultsA total of 1,388 unique SNPs located on sixteen chromosomes were found to be associated with 11 traits. Twenty gene ontology terms and 11 biological pathways were shown to be associated with variability in ear skin temperature, shoulder skin temperature, rump skin temperature, tail skin temperature, respiration rate, panting score, vaginal temperature automatically measured every 10 min, vaginal temperature measured at 0800 h, hair density score, body condition score, and ear area. Seven, five, six, two, seven, 15, and 14 genes with potential pleiotropic effects were identified for indicators of skin temperature, vaginal temperature, animal temperature, respiration rate, thermoregulatory traits, anatomical traits, and all traits, respectively.ConclusionsPhysiological and anatomical indicators of HS response in lactating sows are heritable but highly polygenic. The candidate genes found are associated with important gene ontology terms and biological pathways related to heat shock protein activities, immune response, and cellular oxidative stress. Many of the candidate genes with pleiotropic effects are involved in catalytic activities to reduce cell damage from oxidative stress and cellular mechanisms related to immune response.

Genetic analysis of scab disease resistance in common bean (Phaseolus vulgaris) varieties using GWAS and functional genomics approaches

IntroductionScab is a fungal disease of common beans caused by the pathogen Elsinoë phaseoli. The disease results in major economic losses on common beans, and there are efforts to develop integrated pest management strategies to control the disease. Modern computational biology and bioinformatics tools were utilized to identify scab disease resistance genes in the common bean by identification of genomic regions and genes associated with resistance to scab disease during natural infection in the field.MethodsA diverse set of common bean accessions were analyzed for genetic association with scab disease resistance using a Genome-Wide Association Study design of infected plants and non-infected plants (controls). A fixed and random model circulating probability unification model of these two covariates that considers a minor allele frequency threshold value of 0.03 were deployed during the analysis. Annotation of genes proteins with significant association values was conducted using a machine learning algorithm of support vector machine on prPred using python3 on Linux Ubuntu 18.04 computing platform with an accuracy of 0.935.ResultsCommon bean accessions tested showed varying phenotypes of susceptibility to scab disease. Out of 179 accessions, 16 and 163 accessions were observed to be resistant and susceptible to scab disease, respectively. Genomic analysis revealed a significant association on chromosome one SNP S1_6571566 where the protein-coding sequence had a resistant possibility of 55% and annotated to the Enhancer of Poly-comb like protein.ConclusionThe significant differences in the phenotypic variability for scab disease indicate wide genetic variability among the common bean accessions. The resistant gene associated with scab disease was successfully identified by GWAS analysis. The identified common bean accessions resistant to scab disease can be adopted into breeding programs as sources of resistance.

Identification of genomic regions and pathways associated with traits related to rumen acidosis in feedlot Nellore cattle.

There may be an increased risk of metabolic disorders, such as rumen acidosis, in cattle fed high-concentrate diets, particularly those from Bos taurus indicus genotypes, which have shown to be more sensitive to ruminal acidification. Therefore, this study aimed to estimate (co)variance components and identify genomic regions and pathways associated with ruminal acidosis in feedlot Nellore cattle fed high-concentrate diets. It was utilized a dataset containing a total of 642 Nellore bulls that were genotyped from seven feedlot nutrition studies. The GGP Indicus 35k panel was used with the single step genome-wide association study methodology in which the effects of the markers were obtained from the genomic values estimated by the GBLUP model. A bivariate model to estimate genetic correlations between the economically important traits and indicator traits for acidosis was used. The traits evaluated in this study that were nutritionally related to rumen acidosis included average daily gain (ADG), final body weight, time spent eating (TSE), time spent ruminating, rumenitis score (RUM), rumen absorptive surface area (ASA), rumen keratinized layer thickness (KER) and hot carcass weight (HCW). The identified candidate genes were mainly involved in the negative or non-regulation of the apoptotic process, salivary secretion, and transmembrane transport. The genetic correlation between HCW and ASA was low positive (0.27 ± 0.23), and between ADG and ASA was high moderate (0.58 ± 0.59). A positive genetic correlation between RUM and all performance traits was observed, and TSE correlated negatively with HCW (-0.33 ± 0.21), ASA (-0.75 ± 0.48), and KER (-0.40 ± 0.27). The genetic association between economically important traits and indicator traits for acidosis suggested that Nellore cattle may be more sensitive to acidosis in feedlot systems.

Identification of genomic region and candidate genes underlying carotenoid accumulation in soybeans using next generation sequencing-based bulk segregant analysis

The improvement of soybean seed carotenoid contents is indispensably important owing to its beneficial role to human health and nutrition. However, the genetic architecture underlying soybean carotenoid biosynthesis remains largely unknown. In the present study, we employed the next generation sequencing-based bulked-segregant analysis for identifying new genomic regions governing seed carotenoids in 1551 natural soybean accessions. The genomic DNA samples of individual plants with extreme phenotype were pooled to form two bulks with high (50 accessions) and low (50 accessions) carotenoid contents for Illumina sequencing. A total of 125.09 Gbp of clean bases and 89.82% of Q30 were obtained and the average alignment efficiency was 99.45% with average coverage depth of 62.20× and 99.75% genome coverage. Based on the G’ method analysis, a total of 16 candidate genomic loci with a total length 20.41 Mb were found to be related to the trait. Of these loci, the most significant region displaying the highest elevated G’-value was found in chromosome 06 at a position of 18.53-22.67 Mb, and chromosome 19 at a genomic region intervals of 8.36-10.94, 12.06-13.79 and 18.45-20.26 Mbs, and were preferably taken to identify the key candidate genes. In these regions, 250 predicted genes were found and analyzed to get 90 significantly enriched (P<0.05) gene ontology (GO)-terms. Based on ANNOVAR analysis, 50 genes with non-synonymous and stopgained mutations were preferentially selected as potential candidate genes. Of which, following their gene annotation function and high significant haplotype variation in various environments, five genes were identified as the most promising candidate genes regulating soybean seed carotenoid accumulation, and suggested for further functional validation studies. Collectively, understanding the genetic bases of carotenoid pigments and identifying genes underpinning carotenoid accumulation via bulked-segregant analysis sequencing (BSA-seq) approach provide new insight for exploring future molecular breeding of high carotenoid content in soybean cultivars.

Identification of genomic regions, genetic variants and gene networks regulating candidate genes for lipid metabolism in pig muscle

The intramuscular fat content and fatty acid composition of porcine meat have a significant impact on its quality and nutritional value. This research aimed to investigate the expression of 45 genes involved in lipid metabolism in the longissimus dorsi muscle of three experimental pig backcrosses, with a 25% of Iberian background. To achieve this objective, we conducted an expression Genome-Wide Association Study (eGWAS) using gene expression levels in muscle measured by high-throughput real-time qPCR for 45 target genes and genotypes from the PorcineSNP60 BeadChip or Axiom Porcine Genotyping Array and 65 single nucleotide polymorphisms (SNPs) located in 20 genes genotyped by a custom-designed Taqman OpenArray in a cohort of 354 animals. The eGWAS analysis identified 301 eSNPs associated with 18 candidate genes (ANK2, APOE, ARNT, CIITA, CPT1A, EGF, ELOVL6, ELOVL7, FADS3, FASN, GPAT3, NR1D2, NR1H2, PLIN1, PPAP2A, RORA, RXRA and UCP3). Three cis-eQTL (expression quantitative trait loci) were identified for GPAT3, RXRA, and UCP3 genes, which indicates that a genetic polymorphism proximal to the same gene is affecting its expression. Furthermore, 24 trans-eQTLs were detected, and eight candidate regulatory genes were located in these genomic regions. Additionally, two trans-regulatory hotspots in Sus scrofa chromosomes 13 and 15 were identified. Moreover, a co-expression analysis performed on 89 candidate genes and the fatty acid composition revealed the regulatory role of four genes (FABP5, PPARG, SCD, and SREBF1). These genes modulate the levels of α-linolenic, arachidonic, and oleic acids, as well as regulating the expression of other candidate genes associated with lipid metabolism. The findings of this study offer novel insights into the functional regulatory mechanism of genes involved in lipid metabolism, thereby enhancing our understanding of this complex biological process.

PSVII-5 Detection and Characterization of Copy Number Variation Regions in Three Selection Lines of Nellore Cattle

Abstract Copy number variations (CNV) can partially explain phenotypic variability in complex traits. Therefore, we aimed to identify and characterize CNV regions (CNVR) in Nellore cattle from three selection lines. These selection lines were established in 1981 and consist of a line selected based on heavier postweaning weight (NeS, n = 245), a line selected based on heavier postweaning weight and reduced residual feeding Intake (NeT, n = 556), and a line selected based on average postweaning weight (NeC, n = 114). Genotypes (GGP Indicus HD and GGP Indicus 50K panel) of 928 animals were analyzed. The CNV identification was performed per SNP panel using the PennCNV software. After identifying the CNVs, quality control was performed and the following exclusion criteria were used: Log R ratio &amp;gt; 0.30, B allele frequency "drift” &amp;lt; 0.01, and guanine-cytosine wave factor &amp;lt; 0.05. CNVR were determined by grouping individual CNVs with at least one overlapping base pair. The exclusive regions present in at least 10% of the animals from each population were identified. The GALLO R package was used for the annotation of genes in these regions, and the WebGestaltR package was used for the Gene Ontology analyses. Eight-hundred-and-twenty-three CNVRs (143 losses, 650 gains, and 30 mixed), 1,493 CNVRs (327 losses, 1,113 gains, and 53 mixed), and 482 CNVRs (90 losses, 378 gains, and 14 mixed) were identified in the NeS, NeT, and NeC lines, respectively. The CNVRs covered 1.61%, 2.54%, and 0.94% of the cattle genome in NeS, NeT, and NeC, respectively. Only 32 CNVRs were identified in at least 10% of the animals in NeS, 33 in NeT, and 25 in NeC. Of these regions, 2 are NeS exclusive, 4 are NeT exclusive, and 6 are NeC exclusive. Eight candidate genes in NeS, 20 candidate genes in NeT, and 16 genes in NeC overlapped with the exclusive regions. We identified some important genes such as SLC15A1 in NeS herd that have functions associated to nutrient absorption, MAPK1 identified in the NeT population is involved in a wide variety of cellular processes such as proliferation, differentiation, transcription regulation and development, and IQCA1L in the NeC population is involved in ATP activity. The genes identified are involved in 5 biological processes, such as response to growth factor, in NeT, and in 1 biological process (response to endoplasmic reticulum stress) in NeC. The differences observed in CNVR improve our understanding of the genetic architecture of the three Nellore selection schemes, given that the identification of genes in the CNVR allows the identification of genomic regions and biological processes that could be associated with the phenotypic differences between selection lines.

Identification of genomic regions and genes associated with subclinical ketosis in periparturient dairy cows

Identification of genomic regions and genes associated with subclinical ketosis in periparturient dairy cows

Overview of SNPs Associated with Trans Fat Content in Cow’s Milk

Lipids consumed with milk derivatives are one of the main parts of the human diet. Trans fatty acids in milk are causing a debate about their impact on the incidence of cardiovascular disease, pathological abnormalities, and cancer. The fatty acid profile of milk is influenced by a large number of different factors, one of which is genetic. The development of genetic studies, including Genome-Wide Association Studies (GWAS), may help define genomic regions associated with fatty acid content in milk, including trans fatty acids. This article provides an overview of international studies on the identification of genomic regions and SNPs associated with the trans fatty acids in cow’s milk. The results are based on research of cattle such as Norwegian Red cattle, Holstein, Jersey, and Brown Swiss. The presented review shows that 68 SNPs were localized on chromosomes 1, 2, 4–6, 8–10, 12, 14–20, 22–25, and 27–29. Further research in this direction will provide new information that will serve as an impetus for the creation of modern breeding technologies and increase the performance of the manufacture of high-quality dairy products. The search for genetic markers associated with the content of TFA in milk is a promising direction in agricultural science and will allow more complete breeding work with cattle.

Genome-wide mapping of signatures of selection using a high-density array identified candidate genes for growth traits and local adaptation in chickens

BackgroundAvailability of single nucleotide polymorphism (SNP) genotyping arrays and progress in statistical analyses have allowed the identification of genomic regions and genes under selection in chicken. In this study, SNP data from the 600 K Affymetrix chicken array were used to detect signatures of selection in 23 local Italian chicken populations. The populations were categorized into four groups for comparative analysis based on live weight (heavy vs light) and geographical area (Northern vs Southern Italy). Putative signatures of selection were investigated by combining three extended haplotype homozygosity (EHH) statistical approaches to quantify excess of haplotype homozygosity within (iHS) and between (Rsb and XP-EHH) groups. Presence of runs of homozygosity (ROH) islands was also analysed for each group.ResultsAfter editing, 541 animals and 313,508 SNPs were available for statistical analyses. In total, 15 candidate genomic regions that are potentially under selection were detected among the four groups: eight within a group by iHS and seven by combining the results of Rsb and XP-EHH, which revealed divergent selection between the groups. The largest overlap between genomic regions identified to be under selection by the three approaches was on chicken chromosome 8. Twenty-one genomic regions were identified with the ROH approach but none of these overlapped with regions identified with the three EHH-derived statistics. Some of the identified regions under selection contained candidate genes with biological functions related to environmental stress, immune responses, and disease resistance, which indicate local adaptation of these chicken populations.ConclusionsCompared to commercial lines, local populations are predominantly reared as backyard chickens, and thus, may have developed stronger resistance to environmental challenges. Our results indicate that selection can play an important role in shaping signatures of selection in local chicken populations and can be a starting point to identify gene mutations that could have a useful role with respect to climate change.

Identification of Genomic Regions and Candidate Genes Associated with Body Weight and Body Conformation Traits in Karachai Goats.

The objective of this study was to identify the SNPs and candidate genes related to body weight and seven body conformation traits at the age of 8 months in the Russian aboriginal Karachai goats (n = 269) by conducting genome-wide association studies (GWAS), using genotypes generated by Goat SNP BeadChip (Illumina Inc., USA). We identified 241 SNPs, which were significantly associated with the studied traits, including 47 genome-wide SNPs (p < 10−5) and 194 suggestive SNPs (p < 10−4), distributed among all goat autosomes except for autosome 23. Fifty-six SNPs were common for two and more traits (1 SNP for six traits, 2 SNPs for five traits, 12 SNPs for four traits, 20 SNPs for three traits, and 21 SNPs for two traits), while 185 SNPs were associated with single traits. Structural annotation within a window of 0.4 Mb (±0.2 Mb from causal SNPs) revealed 238 candidate genes. The largest number of candidate genes was identified at Chr13 (33 candidate genes for the five traits). The genes identified in our study were previously reported to be associated with growth-related traits in different livestock species. The most significant genes for body weight were CRADD, HMGA2, MSRB3, MAX, HACL1 and RAB15, which regulate growth processes, body sizes, fat deposition, and average daily gains. Among them, the HMGA2 gene is a well-known candidate for prenatal and early postnatal development, and the MSRB3 gene is proposed as a candidate gene affecting the growth performance. APOB, PTPRK, BCAR1, AOAH and ASAH1 genes associated with withers height, rump height and body length, are involved in various metabolic processes, including fatty acid metabolism and lipopolysaccharide catabolism. In addition, WDR70, ZBTB24, ADIPOQ, and SORCS3 genes were linked to chest width. KCNG4 was associated with rump height, body length and chest perimeter. The identified candidate genes can be proposed as molecular markers for growth trait selection for genetic improvement in Karachai goats.

Identification of Genomic Regions and Candidate Genes for Litter Traits in French Large White Pigs Using Genome-Wide Association Studies.

Simple SummarySow reproductive performance is crucial in the entire pig industry. However, the heritability of reproductive traits is slowthat it is difficult to make great genetic progress by traditional breeding methods. Therefore, in this study, we performed genome-wide association analyses of litter traits in French White sows to explore genes related to sow reproductive traits and we finally detected a notable region (10.72–11.06 Mb on chromosome 7) and four promising genes (JARID2, PDIA6, FLRT2 and DICER1). The results of this study provide a theoretical basis for subsequent molecular breeding.The reproductive traits of sows are one of the important economic traits in pig production, and their performance directly affects the economic benefits of the entire pig industry. In this study, a total of 895 French Large White pigs were genotyped by GeneSeek Porcine 50K SNP Beadchip and four phenotypic traits of 1407 pigs were recorded, including total number born (TNB), number born alive (NBA), number healthy piglets (NHP) and litter weight born alive (LWB). To identify genomic regions and genes for these traits, we used two approaches: a single-locus genome-wide association study (GWAS) and a single-step GWAS (ssGWAS). Overall, a total of five SNPs and 36 genomic regions were identified by single-locus GWAS and ssGWAS, respectively. Notably, fourof all five significant SNPs were located in 10.72–11.06 Mb on chromosome 7, were also identified by ssGWAS. These regions explained the highest or second highest genetic variance in the TNB, NBA and NHP traits and harbor the protein coding gene ENSSSCG00000042180. In addition, several candidate genes associated with litter traits were identified, including JARID2, PDIA6, FLRT2 and DICER1. Overall, these novel results reflect the polygenic genetic architecture of the litter traits and provide a theoretical reference for the following implementation of molecular breeding.

Overview of Identified Genomic Regions Associated with Various Agronomic and Physiological Traits in Barley under Abiotic Stresses

Climate change has caused breeders to focus on varieties that are able to grow under unfavorable conditions, such as drought, high and low temperatures, salinity, and other stressors. In recent decades, progress in biotechnology and its related tools has provided opportunities to dissect and decipher the genetic basis of tolerance to various stress conditions. One such approach is the identification of genomic regions that are linked with specific or multiple characteristics. Cereal crops have a key role in supplying the energy required for human and animal populations. However, crop products are dramatically affected by various environmental stresses. Barley (Hordeum vulgare L.) is one of the oldest domesticated crops that is cultivated globally. Research has shown that, compared with other cereals, barley is well adapted to various harsh environmental conditions. There is ample literature regarding these responses to abiotic stressors, as well as the genomic regions associated with the various morpho-physiological and biochemical traits of stress tolerance. This review focuses on (i) identifying the tolerance mechanisms that are important for stable growth and development, and (ii) the applicability of QTL mapping and association analysis in identifying genomic regions linked with stress-tolerance traits, in order to help breeders in marker-assisted selection (MAS) to quickly screen tolerant germplasms in their breeding cycles. Overall, the information presented here will inform and assist future barley breeding programs.

Identification of Genomic Regions and Sources for Wheat Blast Resistance through GWAS in Indian Wheat Genotypes.

Wheat blast (WB) is a devastating fungal disease that has recently spread to Bangladesh and poses a threat to the wheat production in India, which is the second-largest wheat producing country in the world. In this study, 350 Indian wheat genotypes were evaluated for WB resistance in 12 field experiments in three different locations, namely Jashore in Bangladesh and Quirusillas and Okinawa in Bolivia. Single nucleotide polymorphisms (SNPs) across the genome were obtained using DArTseq® technology, and 7554 filtered SNP markers were selected for a genome-wide association study (GWAS). All the three GWAS approaches used identified the 2NS translocation as the only major source of resistance, explaining up to 32% of the phenotypic variation. Additional marker-trait associations were located on chromosomes 2B, 3B, 4D, 5A and 7A, and the combined effect of three SNPs (2B_180938790, 7A_752501634 and 5A_618682953) showed better resistance, indicating their additive effects on WB resistance. Among the 298 bread wheat genotypes, 89 (29.9%) carried the 2NS translocation, the majority of which (60 genotypes) were CIMMYT introductions, and 29 were from India. The 2NS carriers with a grand mean WB index of 6.6 showed higher blast resistance compared to the non-2NS genotypes with a mean index of 46.5. Of the 52 durum wheats, only one genotype, HI 8819, had the 2NS translocation and was the most resistant, with a grand mean WB index of 0.93. Our study suggests that the 2NS translocation is the only major resistance source in the Indian wheat panel analysed and emphasizes the urgent need to identify novel non-2NS resistance sources and genomic regions.

Identification of genomic regions affecting grain peroxidase activity in bread wheat using genome-wide association study

BackgroundPeroxidase (POD) activity plays an important role in flour-based product quality, which is mainly associated with browning and bleaching effects of flour. Here, we performed a genome-wide association study (GWAS) on POD activity using an association population consisted with 207 wheat world-wide collected varieties. Our study also provide basis for the genetic improvement of flour color-based quality in wheat.ResultsTwenty quantitative trait loci (QTLs) were detected associated with POD activity, explaining 5.59–12.67% of phenotypic variation. Superior alleles were positively correlated with POD activity. In addition, two SNPs were successfully developed to KASP (Kompetitive Allele-Specific PCR) markers. Two POD genes, TraesCS2B02G615700 and TraesCS2D02G583000, were aligned near the QTLs flanking genomic regions, but only TraesCS2D02G583000 displayed significant divergent expression levels (P < 0.001) between high and low POD activity varieties in the investigated association population. Therefore, it was deduced to be a candidate gene. The expression level of TraesCS2D02G583000 was assigned as a phenotype for expression GWAS (eGWAS) to screen regulatory elements. In total, 505 significant SNPs on 20 chromosomes (excluding 4D) were detected, and 9 of them located within 1 Mb interval of TraesCS2D02G583000.ConclusionsTo identify genetic loci affecting POD activity in wheat grain, we conducted GWAS on POD activity and the candidate gene TraesCS2D02G583000 expression. Finally, 20 QTLs were detected for POD activity, whereas two QTLs associated SNPs were converted to KASP markers that could be used for marker-assisted breeding. Both cis- and trans-acting elements were revealed by eGWAS of TraesCS2D02G583000 expression. The present study provides genetic loci for improving POD activity across wide genetic backgrounds and largely improved the selection efficiency for breeding in wheat.

21 Unravelling Transmission Ratio Distortion Across the Genome of a Crossbreed Beef Cattle Population

Abstract Transmission ratio distortion (TRD) is a process when one allele from either parent is preferentially transmitted to the offspring. The identification of genomic regions affected by TRD might help in the detection of lethal alleles or potential genes affecting reproduction. Here, we investigated TRD in crossbreed beef cattle population aiming to identify genomic regions showing altered deviations in segregation that could be affecting reproduction performance. A total of 237 genotyped animals were used including 46 sires, 80 dams, and 111 parent-offspring (trios). The predominant breeds of these animals were Angus (61.83%), Simmental (18.99%), Gelbvieh (6.12%), Charolais (3.65%), Hereford (2.46%) and Limousin (1.57%). After excluding SNPs with minor allele frequency lower than 0.05 and call-rate lower than 0.90, a total of 369,902 autosomal SNPs were retained for further analyses. The SNP-by-SNP analysis was performed within a Bayesian framework using TRDscanv.2.0 software, using 100,000 iterations, with 10,000 iterations being discarded as burn-in. As table 1 shows, 33 SNPs were identified with TRD, considering a Bayes Factor (BF)≥100 and the approximate empirical null distribution of TRD at 0.01% margin error. Among them, 26 SNPs were parent-unspecific and 7 SNPs were parent-specific TRD. For parent-specific TRD, 214 were identified for sire- and 162 for dam-TRD (BF≥100). Among them, 4 SNPs were detected with sire- and dam-TRD in opposite direction of preference of transmission. Preliminary functional and positional analysis was performed using the list of TRD regions with BF≥100 and the approximate empirical null distribution of TRD at 0.01% margin error. For sire-TRD, 14% of the identified QTL (n = 254) were related to non-return rate. For dam-TRD, 21 regions related to conception rate were found (1.5%) and 13 regions related to stillbirth (0.93%). Haplotype analysis is in progress to identify additional candidate regions and alleles with TRD to better understand this phenomenon in a crossbreed beef population.

Quantitative trait loci and candidate genes associated with freezing tolerance of winter triticale (\xd7\u2009Triticosecale Wittmack)

Freezing tolerance of triticale is a major trait contributing to its winter hardiness. The identification of genomic regions — quantitative trait loci (QTL) and molecular markers associated with freezing tolerance in winter hexaploid triticale — was the aim of this study. For that purpose, a new genetic linkage map was developed for the population of 92 doubled haploid lines derived from ‘Hewo’ × ‘Magnat’ F1 hybrid. Those lines, together with parents were subjected to freezing tolerance test three times during two winter seasons. Plants were grown and cold-hardened under natural fall/winter conditions and then subjected to freezing in controlled conditions. Freezing tolerance was assessed as the plants recovery (REC), the electrolyte leakage (EL) from leaves and chlorophyll fluorescence parameters (JIP) after freezing. Three consistent QTL for several fluorescence parameters, electrolyte leakage, and the percentage of the survived plants were identified with composite interval mapping (CIM) and single marker analysis (SMA). The first locus Qfr.hm-7A.1 explained 9% of variation of both electrolyte leakage and plants recovery after freezing. Two QTL explaining up to 12% of variation in plants recovery and shared by selected chlorophyll fluorescence parameters were found on 4R and 5R chromosomes. Finally, main locus Qchl.hm-5A.1 was detected for chlorophyll fluorescence parameters that explained up to 19.6% of phenotypic variation. The co-located QTL on chromosomes 7A.1, 4R and 5R, clearly indicated physiological and genetic relationship of the plant survival after freezing with the ability to maintain optimal photochemical activity of the photosystem II and preservation of the cell membranes integrity. The genes located in silico within the identified QTL include those encoding BTR1-like protein, transmembrane helix proteins like potassium channel, and phosphoric ester hydrolase involved in response to osmotic stress as well as proteins involved in the regulation of the gene expression, chloroplast RNA processing, and pyrimidine salvage pathway. Additionally, our results confirm that the JIP test is a valuable tool to evaluate freezing tolerance of triticale under unstable winter environments.

Identification of stable quantitative trait loci and candidate genes for sweetness and acidity in tablegrape using a highly saturated single‐nucleotide polymorphism‐based linkage map

Background and Aims Identifying the genes that participate in the sweetness and acidity of the berry is key, because these traits are quintessential to the flavour and quality of fresh grapes and wine. In this study we focused on the identification of genomic regions that host genes associated with sweetness and acidity in tablegrapes. Methods and Results A highly saturated genetic map was prepared using a Ruby Seedless × Sultanina cross (RxS; n = 138) genotyped using an SNPlex-type platform, and quantitative trait loci (QTLs) were mapped. In the integrated map of this population, 1731 markers were distributed along the 19 linkage groups (LGs) of the species. Three significant QTLs, two in LG5 and one in LG8, were associated with fructose/glucose ratio, TA and tartaric acid concentration; these QTLs explained up to 20% of the phenotypic variance for these traits. Eight candidate genes located within the confidence intervals of the sugar and TA QTLs were chosen and their expression profiles analysed from flowering to berry ripening. A Genome-Wide Association Study (GWAS) analysis revealed the association of single-nucleotide polymorphisms in the same regions as QTLs. Conclusions Quantitative trait loci significant for sugar and acidity were identified on a tablegrape high-quality genetic map; furthermore, an association between acidity or sugar concentration and expression changes for candidate genes was also observed. Significance of the Study These findings could become the basis to develop selection tools for the breeding of these traits in tablegrape.

Identification of genomic regions that exhibit sexual dimorphism for size and muscularity in cattle.

Sexual dimorphism, the phenomenon whereby males and females of the same species are distinctive in some aspect of appearance or size, has previously been documented in cattle for traits such as growth rate and carcass merit using a quantitative genetics approach. No previous study in cattle has attempted to document sexual dimorphism at a genome level; therefore, the objective of the present study was to determine whether genomic regions associated with size and muscularity in cattle exhibited signs of sexual dimorphism. Analyses were undertaken on 10 linear-type traits that describe the muscular and skeletal characteristics of both males and females of five beef cattle breeds: 1,444 Angus (AA), 6,433 Charolais (CH), 1,129 Hereford, 8,745 Limousin (LM), and 1,698 Simmental. Genome-wide association analyses were undertaken using imputed whole-genome sequence data for each sex separately by breed. For each single-nucleotide polymorphism (SNP) that was segregating in both sexes, the difference between the allele substitution effect sizes for each sex, in each breed separately, was calculated. Suggestively (P ≤ 1 × 10-5) sexually dimorphic SNPs that were segregating in both males and females were detected for all traits in all breeds, although the location of these SNPs differed by both trait and breed. Significantly (P ≤ 1 × 10-8) dimorphic SNPs were detected in just three traits in the AA, seven traits in the CH, and three traits in the LM. The vast majority of all segregating autosomal SNPs (86% in AA to 94% in LM) had the same minor allele in both males and females. Differences (P ≤ 0.05) in allele frequencies between the sexes were observed for between 36% (LM) and 66% (AA) of the total autosomal SNPs that were segregating in both sexes. Dimorphic SNPs were located within a number of genes related to muscularity and/or size including the NAB1, COL5A2, and IWS1 genes on BTA2 that are located close to, and thought to be co-inherited with, the MSTN gene. Overall, sexual dimorphism exists in cattle at the genome level, but it is not consistent by either trait or breed.

Genetic characterization of flour quality and bread‐making traits in a spring wheat nested association mapping population

AbstractImproving grain protein content and flour quality is an important goal for wheat (Triticum aestivum L.) breeding programs. Identification of genomic regions and markers associated with quality traits can help enrich wheat breeding germplasm with favorable alleles. This study was carried out to identify genetic loci controlling bread‐making quality traits in a nested association mapping population of 230 lines. Lines were evaluated for grain protein content and three gluten aggregation traits from the Brabender GlutoPeak instrument: peak maximum time (PMT), maximum torque (MT), and aggregation energy (AE). The strongest positive correlation was observed between AE and MT (r = .87), whereas the strongest negative correlation was between PMT and MT (r = −.46). We identified 25 quantitative trait loci (QTL) associated with these traits on 14 chromosomes, of which three QTL were common between MT and AE. Quantitative trait loci explaining the largest variations were observed for grain protein content and AE, with QTL that explained 13% of the observed variation for each trait. Nearly 62% of the discovered QTL were of medium effect, as the median percentage of observed phenotypic variation explained by the detected QTL was 7% (range of 4–13%). Based on QTL analysis and marker screening results, the populations discussed in this study are segregating for the known alleles of the high‐molecular‐weight glutenin gene Glu‐D1. As some lines have better phenotypic performance relative to the elite common parent RB07, crossing these lines with elite breeding lines can help increase the frequency of alleles contributing to improve flour quality traits.

Identification of genomic regions at seedling related traits in response to aluminium toxicity using a new high-density genetic map in rice (Oryza sativa L.)

Aluminium toxicity is adversely affecting the rice growth and production in acidic soils of developing countries. Rice is popular and stable crop which meets food requirements of about 50% world population. A set of 122 rice backcross recombinant inbreed lines (BRILs) derived from a cross between Japonica (cv.02428) and Indica (Changhui/891) was grown in nutrient solution. High density linkage map generated by using 3075 highly stable SNP markers. Relative root length (RRL) was used as standard criteria for aluminium tolerance. A total of 23 QTLs were detected in the current study for six traits across all experimental conditions. Regarding RRL, three QTLs qCRL-6, qSRL-6, and qRRL-6 were found stable and common QTLs across all environments. Out of these three QTLs, qRRL-6 with higher heritability estimates (H2 = 96.59%) was novel QTL with a positive additive effect. In addition, shoot length (SL), shoot fresh weight (SFW), root fresh weight (RFW), shoot dry weight (SDW) and root dry weight (RDW) were used and identified QTLs, qSSL-11, qRRFW-1, and qRRDW-1 and qRRDW-8 which were newly reported QTLs. Three pleiotropic QTLs qRRFW-1, qRSDW-1, and qRRDW-1 were also reported and these QTLs would facilitate to improve Al tolerance by MAS selection and QTLs pyramiding.