scholarly journals Quantitative trait loci (QTL) underlying phenotypic variation in bioethanol-related processes in Neurospora crassa

2019 ◽  
Author(s):  
Joshua C. Waters ◽  
Deval Jhaveri ◽  
Justin C. Biffinger ◽  
Kwangwon Lee
Keyword(s):  
Quantitative Trait Loci ◽  
Neurospora Crassa ◽  
Quantitative Trait ◽  
Natural Variation ◽  
Consolidated Bioprocessing ◽  
Single Step ◽  
Bioethanol Production ◽  
New Genes ◽  
Trait Loci ◽  
Major Qtl

AbstractBioethanol production from lignocellulosic biomass has received increasing attention over the past decade. Many attempts have been made to reduce the cost of bioethanol production by combining the separate steps of the process into a single-step process known as consolidated bioprocessing. This requires identification of organisms that can efficiently decompose lignocellulose to simple sugars and ferment the pentose and hexose sugars liberated to ethanol. There have been many attempts in engineering laboratory strains by adding new genes or modifying genes to expand the capacity of an industrial microorganism. There has been less attention in improving bioethanol-related processes utilizing natural variation existing in the natural ecotypes. In this study, we sought to identify genomic loci contributing to variation in saccharification of cellulose and fermentation of glucose in the fermenting cellulolytic fungus Neurospora crassa through quantitative trait loci (QTL) analysis. We identified one major QTL contributing to fermentation of glucose and multiple putative QTL’s underlying saccharification. Understanding the natural variation of the major QTL gene would provide new insights in developing industrial microbes for bioethanol production.

scholarly journals Quantitative Trait Loci Controlling Light and Hormone Response in Two Accessions ofArabidopsis thaliana

Genetics ◽  
2002 ◽  
Vol 160 (2) ◽  
pp. 683-696 ◽  
Author(s):  
Justin O Borevitz ◽  
Julin N Maloof ◽  
Jason Lutes ◽  
Tsegaye Dabi ◽  
Joanna L Redfern ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Natural Variation ◽  
Red Light ◽  
Light Response ◽  
Environment Interaction ◽  
Isogenic Line ◽  
Hormone Response ◽  
New Genes ◽  
Trait Loci

AbstractWe have mapped quantitative trait loci (QTL) responsible for natural variation in light and hormone response between the Cape Verde Islands (Cvi) and Landsberg erecta (Ler) accessions of Arabidopsis thaliana using recombinant inbred lines (RILs). Hypocotyl length was measured in four light environments: white, blue, red, and far-red light and in the dark. In addition, white light plus gibberellin (GA) and dark plus the brassinosteroid biosynthesis inhibitor brassinazole (BRZ) were used to detect hormone effects. Twelve QTL were identified that map to loci not previously known to affect light response, as well as loci where candidate genes have been identified from known mutations. Some QTL act in all environments while others show genotype-by-environment interaction. A global threshold was established to identify a significant epistatic interaction between two loci that have few main effects of their own. LIGHT1, a major QTL, has been confirmed in a near isogenic line (NIL) and maps to a new locus with effects in all light environments. The erecta mutation can explain the effect of the HYP2 QTL in the blue, BRZ, and dark environments, but not in far-red. LIGHT2, also confirmed in an NIL, has effects in white and red light and shows interaction with GA. The phenotype and map position of LIGHT2 suggest the photoreceptor PHYB as a candidate gene. Natural variation in light and hormone response thus defines both new genes and known genes that control light response in wild accessions.

scholarly journals Quantitative trait loci (QTL) underlying phenotypic variation in bioethanol-related processes in Neurospora crassa

PLoS ONE ◽  
2020 ◽  
Vol 15 (2) ◽  
pp. e0221737
Author(s):  
Joshua C. Waters ◽  
Deval Jhaveri ◽  
Justin C. Biffinger ◽  
Kwangwon Lee
Keyword(s):  
Quantitative Trait Loci ◽  
Neurospora Crassa ◽  
Phenotypic Variation ◽  
Quantitative Trait ◽  
Trait Loci

scholarly journals Quantitative Trait Loci Mapping for Spot Blotch Resistance in Two Biparental Mapping Populations of Bread Wheat

2020 ◽  
Vol 110 (12) ◽  
pp. 1980-1987 ◽  
Author(s):  
Xinyao He ◽  
Susanne Dreisigacker ◽  
Carolina Sansaloni ◽  
Etienne Duveiller ◽  
Ravi P. Singh ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Bipolaris Sorokiniana ◽  
Physical Distance ◽  
Spot Blotch ◽  
Breeding Lines ◽  
Chromosome 5B ◽  
Trait Loci ◽  
Mapping Populations ◽  
Major Qtl

Spot blotch (SB), caused by Bipolaris sorokiniana, is a major fungal disease of wheat in South Asia and South America. Two biparental mapping populations with 232 F2:7 progenies each were generated, with CIMMYT breeding lines CASCABEL and KATH as resistant parents and CIANO T79 as the common susceptible parent. The two populations were evaluated for field SB resistance in CIMMYT’s Agua Fria station for three consecutive cropping seasons, with artificial inoculation. Genotyping was done with the DArTseq platform and approximately 1,500 high quality and nonredundant markers were used for quantitative trait loci (QTL) mapping. In both populations, a major QTL was found on chromosome 5A in the Vrn-A1 region, explaining phenotypic variations of 13.5 to 25.9%, which turned up to be less- or nonsignificant when days to heading and plant height were used as covariates in the analysis, implying a disease escape mechanism. Another major QTL was located on chromosome 5B in CASCABEL, accounting for 8.9 to 21.4% of phenotypic variation. Minor QTL were found on 4A and 4B in CASCABEL; 1B, 4B, and 4D in KATH; and 1B, 2B, and 4B in CIANO T79. Through an analysis of QTL projection onto the IWGSC Chinese Spring reference genome, the 5B QTL in CASCABEL was mapped in the Sb2 region, delimited by the single nucleotide polymorphism marker wsnp_Ku_c50354_55979952 and the simple sequence repeat marker gwm213, with a physical distance of about 14 Mb to the Tsn1 locus.

scholarly journals Genome-wide Association Study for Carcass Primal Cut Yields Using Single-step Bayesian Approach in Hanwoo Cattle

2021 ◽  
Vol 12 ◽  
Author(s):  
Masoumeh Naserkheil ◽  
Hossein Mehrban ◽  
Deukmin Lee ◽  
Mi Na Park
Keyword(s):  
Quantitative Trait Loci ◽  
Candidate Genes ◽  
Quantitative Trait ◽  
Single Step ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Trait Loci ◽  
Genomic Regions ◽  
Hanwoo Cattle

The importance of meat and carcass quality is growing in beef cattle production to meet both producer and consumer demands. Primal cut yields, which reflect the body compositions of carcass, could determine the carcass grade and, consequently, command premium prices. Despite its importance, there have been few genome-wide association studies on these traits. This study aimed to identify genomic regions and putative candidate genes related to 10 primal cut traits, including tenderloin, sirloin, striploin, chuck, brisket, top round, bottom round, shank, flank, and rib in Hanwoo cattle using a single-step Bayesian regression (ssBR) approach. After genomic data quality control, 43,987 SNPs from 3,745 genotyped animals were available, of which 3,467 had phenotypic records for the analyzed traits. A total of 16 significant genomic regions (1-Mb window) were identified, of which five large-effect quantitative trait loci (QTLs) located on chromosomes 6 at 38–39 Mb, 11 at 21–22 Mb, 14 at 6–7 Mb and 26–27 Mb, and 19 at 26–27 Mb were associated with more than one trait, while the remaining 11 QTLs were trait-specific. These significant regions were harbored by 154 genes, among which TOX, FAM184B, SPP1, IBSP, PKD2, SDCBP, PIGY, LCORL, NCAPG, and ABCG2 were noteworthy. Enrichment analysis revealed biological processes and functional terms involved in growth and lipid metabolism, such as growth (GO:0040007), muscle structure development (GO:0061061), skeletal system development (GO:0001501), animal organ development (GO:0048513), lipid metabolic process (GO:0006629), response to lipid (GO:0033993), metabolic pathways (bta01100), focal adhesion (bta04510), ECM–receptor interaction (bta04512), fat digestion and absorption (bta04975), and Rap1 signaling pathway (bta04015) being the most significant for the carcass primal cut traits. Thus, identification of quantitative trait loci regions and plausible candidate genes will aid in a better understanding of the genetic and biological mechanisms regulating carcass primal cut yields.

scholarly journals The genetic and molecular origin of natural variation for the fragrance trait in an elite Malaysian aromatic rice through quantitative trait loci mapping using SSR and gene-based markers

Gene ◽  
2015 ◽  
Vol 555 (2) ◽  
pp. 101-107 ◽  
Author(s):  
Farahnaz Sadat Golestan Hashemi ◽  
Mohd Y. Rafii ◽  
Mohd Razi Ismail ◽  
Mahmud Tengku Muda Mohamed ◽  
Harun A. Rahim ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Natural Variation ◽  
Aromatic Rice ◽  
Quantitative Trait Loci Mapping ◽  
Trait Loci ◽  
Molecular Origin ◽  
Gene Based Markers

scholarly journals Mapping of quantitative trait loci for purple stigma and purple apiculus in rice by using a Zhenshan 97B/Minghui 63 RIL population

2021 ◽  
Author(s):  
Jiping Tong ◽  
Zhengshu Han ◽  
Aonan Han
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Indica Rice ◽  
Phenotypic Variance ◽  
Chromosome 6 ◽  
Rice Varieties ◽  
Morphological Marker ◽  
Ril Population ◽  
Trait Loci ◽  
Major Qtl

Anthocyanin pigmentation is an important morphological marker that is commonly used to identify rice varieties and for linkage analysis. The following study investigates the genetic factors involved in the purple stigma (Ps) and purple apiculus (Pa) traits of an important indica rice cross between Zhenshan 97 (purple stigma and purple apiculus) and Minghui 63 (grey stigma and colourless apiculus). A recombinant inbred line (RIL) population derived from this cross was used for quantitative trait loci (QTL) mapping of the purple stigma and purple apiculus traits. As a result, one major QTL for the purple stigma trait, temporarily designated qPS-1-1, and one major QTL for the purple apiculus trait, temporarily designated qPA-1-1, were mapped to the short arm of chromosome 6 in the interval between the two markers Y4073L and *P. The LOD peaks of qPS-1-1 and qPA-1-1 were 44.0127 and 173.3585, respectively. In addition, qPS-1-1 and qPA-1-1 explained 66.7416% and 98.6441% of the total phenotypic variance, respectively. The Zhenshan 97 allele increased the purple stigma trait by approximately 8.0355% (for qPS-1-1) and 9.8863% (for qPA-1-1). Moreover, since qPS-1-1 and qPA-1-1 were strongly correlated, they were also located in the same vicinity of the C gene on the short arm of chromosome 6, which suggested that the two QTL might be the same. By comparing these and previous results, it was deduced that qPS-1-1 or qPA-1-1 was the C gene and was pleiotropic for both the colouration of the apiculus and the colouration of the stigma in rice.

scholarly journals Conditional Mapping Identified Quantitative Trait Loci for Grain Protein Concentration Expressing Independently of Grain Yield in Canadian Durum Wheat

2021 ◽  
Vol 12 ◽  
Author(s):  
Yuefeng Ruan ◽  
Bianyun Yu ◽  
Ron E. Knox ◽  
Wentao Zhang ◽  
Asheesh K. Singh ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Grain Yield ◽  
Durum Wheat ◽  
Quantitative Trait ◽  
Protein Concentration ◽  
Grain Protein ◽  
Phenotypic Variance ◽  
Grain Protein Concentration ◽  
Trait Loci ◽  
Major Qtl

Grain protein concentration (GPC) is an important trait in durum cultivar development as a major determinant of the nutritional value of grain and end-use product quality. However, it is challenging to simultaneously select both GPC and grain yield (GY) due to the negative correlation between them. To characterize quantitative trait loci (QTL) for GPC and understand the genetic relationship between GPC and GY in Canadian durum wheat, we performed both traditional and conditional QTL mapping using a doubled haploid (DH) population of 162 lines derived from Pelissier × Strongfield. The population was grown in the field over 5 years and GPC was measured. QTL contributing to GPC were detected on chromosome 1B, 2B, 3A, 5B, 7A, and 7B using traditional mapping. One major QTL on 3A (QGpc.spa-3A.3) was consistently detected over 3 years accounting for 9.4–18.1% of the phenotypic variance, with the favorable allele derived from Pelissier. Another major QTL on 7A (QGpc.spa-7A) detected in 3 years explained 6.9–14.8% of the phenotypic variance, with the beneficial allele derived from Strongfield. Comparison of the QTL described here with the results previously reported led to the identification of one novel major QTL on 3A (QGpc.spa-3A.3) and five novel minor QTL on 1B, 2B and 3A. Four QTL were common between traditional and conditional mapping, with QGpc.spa-3A.3 and QGpc.spa-7A detected in multiple environments. The QTL identified by conditional mapping were independent or partially independent of GY, making them of great importance for development of high GPC and high yielding durum.

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