Genomic regions responsible for accumulation of grain iron concentration (Fe), grain zinc concentration (Zn), grain protein content (PC) and thousand kernel weight (TKW) were investigated in 286 recombinant inbred lines (RILs) derived from a cross between an old Indian wheat variety WH542 and a synthetic derivative (Triticum dicoccon PI94624/Aegilops squarrosa [409]//BCN). RILs were grown in six environments and evaluated for Fe, Zn, PC, and TKW. The population showed the continuous distribution for all the four traits, that for pooled Fe and PC was near normal, whereas, for pooled Zn, RILs exhibited positively skewed distribution. A genetic map spanning 2155.3cM was constructed using microsatellite markers covering the 21 chromosomes and used for QTL analysis. 16 quantitative trait loci (QTL) were identified in this study. Four QTLs (QGFe.iari-2A, QGFe.iari-5A, QGFe.iari-7A and QGFe.iari-7B) for Fe, five QTLs (QGZn.iari-2A, QGZn.iari-4A, QGZn.iari-5A, QGZn.iari-7A and QGZn.iari-7B) for Zn, two QTLs (QGpc.iari-2A and QGpc.iari-3A) for PC, and five QTLs (QTkw.iari-1A, QTkw.iari-2A, QTkw.iari-2B, QTkw.iari-5B and QTkw.iari-7A) for TKW were identified. The QTLs together explained 20.0%, 32.0%, 24.1% and 32.3% phenotypic variation, respectively, for Fe, Zn, PC and TKW. QGpc.iari-2A was consistently expressed in all the six environments, whereas, QGFe.iari-7B and QGZn.iari-2A were identified in two environments each apart from pooled mean. QTkw.iari-2A and QTkw.iari-7A, respectively, were identified in four and three environments apart from pooled mean. A common region in the interval of Xgwm359-Xwmc407 on chromosome 2A was associated with Fe, Zn, and PC. One more QTL for TKW was identified on chromosome 2A but in a different chromosomal region (Xgwm382-Xgwm359). Two more regions on 5A (Xgwm126-Xgwm595) and 7A (Xbarc49-Xwmc525) were found to be associated with both Fe and Zn. A QTL for TKW was identified (Xwmc525-Xbarc222) in a different chromosomal region on the same chromosome (7A). This reflects at least a partly common genetic basis for the four traits. It is concluded that fine mapping of the regions of the three chromosomes of A genome involved in determining the accumulation of Fe, Zn, PC, and TKW in this mapping population may be rewarding.

/pdf/molecular-mapping-of-the-grain-iron-and-zinc-concentration-3wpofql3wg.pdf

Molecular mapping of the grain iron and zinc concentration, protein content and thousand kernel weight in wheat (Triticum aestivum L.).

TaGW2 is an orthologue of rice gene OsGW2, which encodes E3 RING ubiquitin ligase and controls the grain size in rice. In wheat, three copies of TaGW2 have been identified and mapped on wheat homoeologous group 6 viz. TaGW2-6A, TaGW2-6B and TaGW2-6D. In the present study, using as many as 207 Indian wheat genotypes, we identified four SNPs including two novel SNPs (SNP-988 and SNP-494) in the promoter sequence of TaGW2-6A. All the four SNPs were G/A or A/G substitutions (transitions). Out of the four SNPs, SNP-494 was causal, since it was found associated with grain weight. The mean TGW (41.1 g) of genotypes with the allele SNP-494_A was significantly higher than mean TGW (38.6 g) of genotypes with the allele SNP-494_G. SNP-494 also regulates the expression of TaGW2-6A so that the wheat genotypes with SNP-494_G have higher expression and lower TGW and the genotypes with SNP-494_A have lower expression but higher TGW. Besides, SNP-494 was also found associated with grain length-width ratio, awn length, spike length, grain protein content, peduncle length and plant height. This suggested that gene TaGW2-6A not only controls grain size, but also controls other agronomic traits. In the promoter region, SNP-494 was present in ‘CGCG’ motif that plays an important role in Ca2+/calmodulin mediated regulation of genes. A user-friendly CAPS marker was also developed to identify the desirable allele of causal SNP (SNP-494) for use in marker-assisted selection for improvement of grain weight in wheat. Using four SNPs, five haplotypes were identified; of these, Hap_5 (G_A_G_A) was found to be a desirable haplotype having significantly higher grain weight (41.13g) relative to other four haplotypes (36.33-39.16 g).

/pdf/identification-of-novel-snp-in-promoter-sequence-of-tagw2-6a-34kzypz7qv.pdf

Identification of Novel SNP in Promoter Sequence of TaGW2-6A Associated with Grain Weight and Other Agronomic Traits in Wheat (Triticum aestivum L.).

Due to the increased economic demand for livestock, the number of livestock is increasing. Because of human interference, the survival of wild animals is threatened in the face of competition, particularly in co-inhabited grazing pastures. This may lead to differences in the adaptability between wild and domestic animals, as well as nutritional deficiencies in wild animals. The gut microbiota is closely associated with host health, nutrition, and adaptability. However, the gut microbiota diversity and functions in domestic and wild animals in co-inhabited areas are unclear. To reveal the adaptability of wild and domestic animals in co-inhabited areas based on gut microbiota, we assessed the gut microbiota diversity. This study was based on the V3-V4 region of 16S rRNA and gut microbiota functions according to the metagenome analysis of fresh fecal samples in wild goitered gazelles (Gazella subgutturosa) and domestic sheep (Ovis aries) in the Qaidam Basin. The wild and domestic species showed significant differences in alpha- and beta-diversities. Specifically, the alpha-diversity was lower in goitered gazelles. We speculated that the nutritional and habitat status of the goitered gazelles were worse. The gut microbiota functions in the gazelles were enriched in metabolism and cellular processes based on the KEGG database. In summary, we reasoned that gut microbiota can improve the adaptability of goitered gazelles through energy maintenance by the functions of gut microbiota in the face of nutritional deficiencies. These findings highlight the importance of gut microbiota diversity to improve the adaptability of goitered gazelles, laying a foundation for the conservation of wild goitered gazelles. In addition, we further provide management suggestions for domestic sheep in co-inhabited grazing pastures.

Gut Microbiota Plasticity Influences the Adaptability of Wild and Domestic Animals in Co-inhabited Areas.

Kernel length is an important target trait in barley (Hordeum vulgare L.) breeding programs. However, the number of known quantitative trait loci (QTLs) controlling kernel length is limited. In the present study, we aimed to identify major QTLs for kernel length, as well as putative candidate genes that might influence kernel length in wild barley. A recombinant inbred line (RIL) population derived from the barley cultivar Baudin (H. vulgare ssp. vulgare) and the long-kernel wild barley genotype Awcs276 (H.vulgare ssp. spontaneum) was evaluated at one location over three years. A high-density genetic linkage map was constructed using 1,832 genome-wide diversity array technology (DArT) markers, spanning a total of 927.07 cM with an average interval of approximately 0.49 cM. Two major QTLs for kernel length, LEN-3H and LEN-4H, were detected across environments and further validated in a second RIL population derived from Fleet (H. vulgare ssp. vulgare) and Awcs276. In addition, a systematic search of public databases identified four candidate genes and four categories of proteins related to LEN-3H and LEN-4H. This study establishes a fundamental research platform for genomic studies and marker-assisted selection, since LEN-3H and LEN-4H could be used for accelerating progress in barley breeding programs that aim to improve kernel length.

/pdf/mapping-and-validation-of-major-quantitative-trait-loci-for-dcc9bt2x65.pdf

Mapping and validation of major quantitative trait loci for kernel length in wild barley (Hordeum vulgare ssp. spontaneum).

Micronutrient and protein malnutrition is recognized among the major global health issues. Genetic biofortification is a cost-effective and sustainable strategy to tackle malnutrition. Genomic regions governing grain iron concentration (GFeC), grain zinc concentration (GZnC), grain protein content (GPC), and thousand kernel weight (TKW) were investigated in a set of 163 recombinant inbred lines (RILs) derived from a cross between cultivated wheat variety WH542 and a synthetic derivative (Triticum dicoccon PI94624/Aegilops tauschii [409]//BCN). The RIL population was genotyped using 100 simple-sequence repeat (SSR) and 736 single nucleotide polymorphism (SNP) markers and phenotyped in six environments. The constructed genetic map had a total genetic length of 7,057 cM. A total of 21 novel quantitative trait loci (QTL) were identified in 13 chromosomes representing all three genomes of wheat. The trait-wise highest number of QTL was identified for GPC (10 QTL), followed by GZnC (six QTL), GFeC (three QTL), and TKW (two QTL). Four novel stable QTL (QGFe.iari-7D.1, QGFe.iari-7D.2, QGPC.iari-7D.2, and QTkw.iari-7D) were identified in two or more environments. Two novel pleiotropic genomic regions falling between Xgwm350-AX-94958668 and Xwmc550-Xgwm350 in chromosome 7D harboring co-localized QTL governing two or more traits were also identified. The identified novel QTL, particularly stable and co-localized QTL, will be validated to estimate their effects on different genetic backgrounds for subsequent use in marker-assisted selection (MAS). Best QTL combinations were identified by the estimation of additive effects of the stable QTL for GFeC, GZnC, and GPC. A total of 11 RILs (eight for GZnC and three for GPC) having favorable QTL combinations identified in this study can be used as potential donors to develop bread wheat varieties with enhanced micronutrients and protein.

/pdf/identification-of-novel-genomic-regions-for-biofortification-18u37p3hfk.pdf

Identification of Novel Genomic Regions for Biofortification Traits Using an SNP Marker-Enriched Linkage Map in Wheat (Triticum aestivum L.).

TGW is an important
agronomic trait that influences the yield and milling quality of wheat. In this
paper, after having investigated the phenotype of TGW from 114 ITMI recombinant
inbred genealogies in 4 years in Qaidam Basin, a typical plateau oasis
agricultural area, and having combined 1410 molecular markers, 7 major QTL loci
of the thousand gain weight were screened out with the aid of QTL network
software. These loci included qTgw1B (42.6 cm), qTgw2A(77.9 cm), qTgw2D1 (25.4 cm), qTgw2D2 (51.8 cm),
qTgw6A1 (56.1 cm), qTgw6A2 (62.2 cm) and qTgw7A(75.7 cm) with their genetic contribution
rates between 3.29% - 19.36%. There were two epistatic effect loci2A-2D and2A-6B with their genetic contribution rates as 2.3%
and 5.3% respectively. The quantitative genetic locus positioning of thousand
hexaploid wheat grain weight in Qaidam Basin can assist us in better
understanding the genetic regulatory network formed by TGW, and can also
provide a theoretical basis for improving thousand wheat grain weight in this
ecological area.

/pdf/qtl-positioning-of-thousand-wheat-grain-weight-in-qaidam-1y0s9a7ug9.pdf

QTL Positioning of Thousand Wheat Grain Weight in Qaidam Basin

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QTL Positioning of Thousand Wheat Grain Weight in Qaidam Basin