Identification of Genomic Regions Implicated in Susceptibility to Schistosoma mansoni Infection in a Murine Backcross Genetic Model

Only a small number of infected people are highly susceptible to schistosomiasis, showing high levels of infection or severe liver fibrosis. The susceptibility to schistosome infection is influenced by genetic background. To assess the genetic basis of susceptibility and identify the chromosomal regions involved, a backcross strategy was employed to generate high variation in schistosomiasis susceptibility. This strategy involved crossing the resistant C57BL/6J mouse strain with the susceptible CBA/2J strain. The resulting F1 females (C57BL/6J × CBA/2J) were then backcrossed with CBA/2J males to generate the backcross (BX) cohort. The BX mice exhibited a range of phenotypes, with disease severity varying from mild to severe disease, lacking a fully resistant group. We observed four levels of infection intensity using cluster and principal component analyses and K-means based on parasitological, pathological, and immunological trait measurements. The mice were genotyped with 961 informative SNPs, leading to the identification of 19 new quantitative trait loci (QTL) associated with parasite burden, liver lesions, white blood cell populations, and antibody responses. Two QTLs located on chromosomes 15 and 18 were linked to the number of granulomas, liver lesions, and IgM levels. The corresponding syntenic human regions are located in chromosomes 8 and 18. None of the significant QTLs had been reported previously.

Genome-wide association study revealed the genomic regions associated with skin pigmentation in an Ogye x White Leghorn F2 chicken population

Skin color in chickens is an economically important trait that determines the first impression of a consumer toward a broiler and can ultimately affect consumer choice in the market. Therefore, identification of genomic regions associated with skin color is crucial for increasing the sales value of chickens. Although previous studies have attempted to reveal the genetic markers associated with the skin coloration in chickens, most were limited to investigations of candidate genes, such as melanin-related genes, and focused on case/control studies based on a single or small population. In this study, we performed a genome-wide association study (GWAS) on 770 F2 intercrosses produced by an experimental population of 2 chicken breeds, namely Ogye and White Leghorns, with different skin colors. The GWAS demonstrated that the L* value among the 3 skin color traits is highly heritable, and the genomic regions located on 2 chromosomes (20 and Z) were detected to harbor SNPs significantly associated with the skin color trait, accounting for most of the total genetic variance. Particular genomic regions spanning a ∼2.94 Mb region on GGA Z and a ∼3.58 Mb region on GGA 20 were significantly associated with skin color traits, and in these regions, certain candidate genes, including MTAP, FEM1C, GNAS, and EDN3, were found. Our findings could help elucidate the genetic mechanisms underlying chicken skin pigmentation. Furthermore, the candidate genes can be used to provide a valuable breeding strategy for the selection of specific chicken breeds with ideal skin coloration.

Comprehensive meta-analysis of QTL and gene expression studies identify candidate genes associated with Aspergillus flavus resistance in maize

Aflatoxin (AF) contamination, caused by Aspergillus flavus, compromises the food safety and marketability of commodities, such as maize, cotton, peanuts, and tree nuts. Multigenic inheritance of AF resistance impedes conventional introgression of resistance traits into high-yielding commercial maize varieties. Several AF resistance-associated quantitative trait loci (QTLs) and markers have been reported from multiple biparental mapping and genome-wide association studies (GWAS) in maize. However, QTLs with large confidence intervals (CI) explaining inconsistent phenotypic variance limit their use in marker-assisted selection. Meta-analysis of published QTLs can identify significant meta-QTLs (MQTLs) with a narrower CI for reliable identification of genes and linked markers for AF resistance. Using 276 out of 356 reported QTLs controlling resistance to A. flavus infection and AF contamination in maize, we identified 58 MQTLs on all 10 chromosomes with a 66.5% reduction in the average CI. Similarly, a meta-analysis of maize genes differentially expressed in response to (a)biotic stresses from the to-date published literature identified 591 genes putatively responding to only A. flavus infection, of which 14 were significantly differentially expressed (-1.0 ≤ Log2Fc ≥ 1.0; p ≤ 0.05). Eight MQTLs were validated by their colocalization with 14 A. flavus resistance-associated SNPs identified from GWAS in maize. A total of 15 genes were physically close between the MQTL intervals and SNPs. Assessment of 12 MQTL-linked SSR markers identified three markers that could discriminate 14 and eight cultivars with resistance and susceptible responses, respectively. A comprehensive meta-analysis of QTLs and differentially expressed genes led to the identification of genes and makers for their potential application in marker-assisted breeding of A. flavus-resistant maize varieties.

Genome-wide association study reveals a genomic region on SSC7 simultaneously associated with backfat thickness, skin thickness and carcass length in a Large White × Tongcheng advanced generation intercross resource population

In order to identify important genetic markers associated with backfat thickness, skin thickness and carcass length, we first constructed Large White × Tongcheng (Chinese local breed), an advanced generation intercross population, then performed a genome-wide association study (GWAS) to reveal the key genomic region associated with these traits through whole genome sequencing. The GWAS results of backfat thickness, skin thickness and carcass length showed that all the most significant SNPs associated with these three traits were located on SSC7, and that 14.9, 27.0 and 21.1% of phenotypic variances were explained by these three SNPs, respectively. Through linkage disequilibrium analysis, we found that a 66.9 kb (30.23-30.31 Mb) genetic region was overlapped among these three traits, and that NUDT3 and HMGA1 were identified as major candidate genes for backfat thickness and carcass length, and GRM4 as a potential candidate gene for skin thickness. In addition, 13 highly linked SNPs significantly associated with the three traits were also identified in overlapped region, and three completely linked SNPs formed two haplotypes Q and q. The backfat thickness of individuals with the qq genotype was significantly lower than that of individuals with the QQ genotype, but their carcass length and skin thickness were significantly higher than those with the QQ genotype. Our detected candidate genes and SNPs will provide the foundation for genetic improvement of these three traits.

Chromosome groups 5, 6 and 7 harbor major quantitative trait loci controlling root traits in bread wheat (Triticum aestivum L.)

Identifying genomic regions for root traits in bread wheat can help breeders develop climate-resilient and high-yielding wheat varieties with desirable root traits. This study used the recombinant inbred line (RIL) population of Synthetic W7984 × Opata M85 to identify quantitative trait loci (QTL) for different root traits such as rooting depth (RD), root dry mass (RM), total root length (RL), root diameter (Rdia) and root surface areas (RSA1 for coarse roots and RSA2 for fine roots) under controlled conditions in a semi-hydroponic system. We detected 14 QTL for eight root traits on nine wheat chromosomes; we discovered three QTL each for RD and RSA1, two QTL each for RM and RSA2, and one QTL each for RL, Rdia, specific root length and nodal root number per plant. The detected QTL were concentrated on chromosome groups 5, 6 and 7. The QTL for shallow RD (Q.rd.uwa.7BL: Xbarc50) and high RM (Q.rm.uwa.6AS: Xgwm334) were validated in two independent F₂ populations of Synthetic W7984 × Chara and Opata M85 × Cascade, respectively. Genotypes containing negative alleles for Q.rd.uwa.7BL had 52% shallower RD than other Synthetic W7984 × Chara population lines. Genotypes with the positive alleles for Q.rm.uwa.6AS had 31.58% higher RM than other Opata M85 × Cascade population lines. Further, we identified 21 putative candidate genes for RD (Q.rd.uwa.7BL) and 13 for RM (Q.rm.uwa.6AS); TraesCS6A01G020400, TraesCS6A01G024400 and TraesCS6A01G021000 identified from Q.rm.uwa.6AS, and TraesCS7B01G404000, TraesCS7B01G254900 and TraesCS7B01G446200 identified from Q.rd.uwa.7BL encoded important proteins for root traits. We found germin-like protein encoding genes in both Q.rd.uwa.7BL and Q.rm.uwa.6AS regions. These genes may play an important role in RM and RD improvement. The identified QTL, especially the validated QTL and putative candidate genes are valuable genetic resources for future root trait improvement in wheat.

GREAP: a comprehensive enrichment analysis software for human genomic regions

The rapid development of genomic high-throughput sequencing has identified a large number of DNA regulatory elements with abundant epigenetics markers, which promotes the rapid accumulation of functional genomic region data. The comprehensively understanding and research of human functional genomic regions is still a relatively urgent work at present. However, the existing analysis tools lack extensive annotation and enrichment analytical abilities for these regions. Here, we designed a novel software, Genomic Region sets Enrichment Analysis Platform (GREAP), which provides comprehensive region annotation and enrichment analysis capabilities. Currently, GREAP supports 85 370 genomic region reference sets, which cover 634 681 107 regions across 11 different data types, including super enhancers, transcription factors, accessible chromatins, etc. GREAP provides widespread annotation and enrichment analysis of genomic regions. To reflect the significance of enrichment analysis, we used the hypergeometric test and also provided a Locus Overlap Analysis. In summary, GREAP is a powerful platform that provides many types of genomic region sets for users and supports genomic region annotations and enrichment analyses. In addition, we developed a customizable genome browser containing >400 000 000 customizable tracks for visualization. The platform is freely available at http://www.liclab.net/Greap/view/index.

Insights into the Genomic Regions and Candidate Genes of Senescence-Related Traits in Upland Cotton via GWAS

Senescence is the last stage of plant development and is controlled by both internal and external factors. Premature senescence significantly affects the yield and quality of cotton. However, the genetic architecture underlying cotton senescence remains unclear. In this study, genome-wide association studies (GWAS) were performed based on 3,015,002 high-quality SNP markers from the resequencing data of 355 upland cotton accessions to detect genomic regions for cotton senescence. A total of 977 candidate genes within 55 senescence-related genomic regions (SGRs), SGR1-SGR55, were predicted. Gene ontology (GO) analysis of candidate genes revealed that a set of biological processes was enriched, such as salt stress, ethylene processes, and leaf senescence. Furthermore, in the leaf senescence GO term, one candidate gene was focused on: Gohir.A12G270900 (GhMKK9), located in SGR36, which encodes a protein of the MAP kinase kinase family. Quantitative real-time PCR (qRT-PCR) analysis showed that GhMKK9 was up-regulated in old cotton leaves. Overexpression of GhMKK9 in Arabidopsis accelerated natural leaf senescence. Virus-induced gene silencing (VIGS) of GhMKK9 in cotton increased drought tolerance. These results suggest that GhMKK9 is a positive regulator and might be involved in drought-induced senescence in cotton. The results provide new insights into the genetic basis of cotton senescence and will be useful for improving cotton breeding in the future.

Pipeline for generating stable large genomic deletions in zebrafish, from small domains to whole gene excisions

Here we describe a short feasibility study and methodological framework for the production of stable, CRISPR/Cas9-based, large genomic deletions in zebrafish, ranging from several base pairs (bp) to hundreds of kilobases (kb). Using a cocktail of four single guide RNAs (sgRNAs) targeting a single genomic region mixed with a marker-sgRNA against the pigmentation gene tyrosinase, we demonstrate that one can easily and accurately excise genomic regions such as promoters, protein domains, specific exons, or whole genes. We exemplify this technique with a complex gene family, neurexins, composed of three duplicated genes with multiple promoters and intricate splicing processes leading to thousands of isoforms. We precisely deleted small regions such as their transmembrane domains (150 bp deletion in average) to their entire genomic locus (300 kb deletion for nrxn1a for instance). We find that both the concentration and ratio of Cas9/sgRNAs are critical for the successful generation of these large deletions and, interestingly, that in our study, their transmission frequency does not seem to decrease with increasing distance between sgRNA target sites. Considering the growing reports and debate about genetically compensated small indel mutants, the use of large-deletion approaches is likely to be widely adopted in studies of gene function. This strategy will also be key to the study of non-coding genomic regions. Note that we are also describing here a custom method to produce the sgRNAs, which proved to be faster and more robust than the ones traditionally used in the community to date.

Identification and Validation of High LD Hotspot Genomic Regions Harboring Stem Rust Resistant Genes on 1B, 2A (Sr38), and 7B Chromosomes in Wheat

Stem rust caused by Puccinia graminis f. sp. tritici Eriks. is an important disease of common wheat globally. The production and cultivation of genetically resistant cultivars are one of the most successful and environmentally friendly ways to protect wheat against fungal pathogens. Seedling screening and genome-wide association study (GWAS) were used to determine the genetic diversity of wheat genotypes obtained on stem rust resistance loci. At the seedling stage, the reaction of the common stem rust race QFCSC in Nebraska was measured in a set of 212 genotypes from F_3:6 lines. The results indicated that 184 genotypes (86.8%) had different degrees of resistance to this common race. While 28 genotypes (13.2%) were susceptible to stem rust. A set of 11,911 single-nucleotide polymorphism (SNP) markers was used to perform GWAS which detected 84 significant marker-trait associations (MTAs) with SNPs located on chromosomes 1B, 2A, 2B, 7B and an unknown chromosome. Promising high linkage disequilibrium (LD) genomic regions were found in all chromosomes except 2B which suggested they include candidate genes controlling stem rust resistance. Highly significant LD was found among these 59 significant SNPs on chromosome 2A and 12 significant SNPs with an unknown chromosomal position. The LD analysis between SNPs located on 2A and Sr38 gene reveal high significant LD genomic regions which was previously reported. To select the most promising stem rust resistant genotypes, a new approach was suggested based on four criteria including, phenotypic selection, number of resistant allele(s), the genetic distance among the selected parents, and number of the different resistant allele(s) in the candidate crosses. As a result, 23 genotypes were considered as the most suitable parents for crossing to produce highly resistant stem rust genotypes against the QFCSC.

Uncovering Novel Genomic Regions and Candidate Genes for Senescence-Related Traits by Genome-Wide Association Studies in Upland Cotton (Gossypium hirsutum L.)

Senescence in plants is a complex trait, which is controlled by both genetic and environmental factors and can affect the yield and quality of cotton. However, the genetic basis of cotton senescence remains relatively unknown. In this study, we reported genome-wide association studies (GWAS) based on 185 accessions of upland cotton and 26,999 high-quality single-nucleotide polymorphisms (SNPs) to reveal the genetic basis of cotton senescence. To determine cotton senescence, we evaluated eight traits/indices. Our results revealed a high positive correlation (r>0.5) among SPAD value 20 days after topping (SPAD20d), relative difference of SPAD (RSPAD), nodes above white flower on topping day (NAWF0d), nodes above white flower 7 days after topping (NAWF7d), and number of open bolls on the upper four branches (NB), and genetic analysis revealed that all traits had medium or high heritability ranging from 0.53 to 0.86. Based on a multi-locus method (FASTmrMLM), a total of 63 stable and significant quantitative trait nucleotides (QTNs) were detected, which represented 50 genomic regions (GWAS risk loci) associated with cotton senescence. We observed three reliable loci located on chromosomes A02 (A02_105891088_107196428), D03 (D03_37952328_38393621) and D13 (D13_59408561_60730103) because of their high repeatability. One candidate gene (Ghir_D03G011060) was found in the locus D03_37952328_38393621, and its Arabidopsis thaliana homologous gene (AT5G23040) encodes a cell growth defect factor-like protein (CDF1), which might be involved in chlorophyll synthesis and cell death. Moreover, qRT-PCR showed that the transcript level of Ghir_D03G011060 was down-regulated in old cotton leaves, and virus-induced gene silencing (VIGS) indicated that silencing of Ghir_D03G011060 resulted in leaf chlorosis and promoted leaf senescence. In addition, two candidate genes (Ghir_A02G017660 and Ghir_D13G021720) were identified in loci A02_105891088_107196428 and D13_59408561_60730103, respectively. These results provide new insights into the genetic basis of cotton senescence and will serve as an important reference for the development and implementation of strategies to prevent premature senescence in cotton breeding programs.

Review on Genomic Regions and Candidate Genes Associated with Economically Important Production and Reproduction Traits in Sheep (Ovies aries)

Sheep (Ovis aries) is one of the most economically, culturally, and socially important domestic animals. They are reared primarily for meat, milk, wool, and fur production. Sheep were reared using natural selection for a long period of time to offer these traits. In fact, this production system has been slowing the productivity and production potential of the sheep. To improve production efficiency and productivity of this animal through genetic improvement technologies, understanding the genetic background of traits such as body growth, weight, carcass quality, fat percent, fertility, milk yield, wool quality, horn type, and coat color is essential. With the development and utilization of animal genotyping technologies and gene identification methods, many functional genes and genetic variants associated with economically important phenotypic traits have been identified and annotated. This is useful and presented an opportunity to increase the pace of animal genetic gain. Quantitative trait loci and genome wide association study have been playing an important role in identifying candidate genes and animal characterization. This review provides comprehensive information on the identified genomic regions and candidate genes associated with production and reproduction traits, and gene function in sheep.

Genome-wide association analysis identifies the genetic basis of fat deposition in the tails of sheep (Ovis aries)

Fat-tailed sheep (Ovis aries) can survive in harsh environments and satisfy human's intake of dietary fat. However, the animals require more feed, which increases the cost of farming. Thus, most farmers currently prefer thin-tailed, short-tailed or docked sheep. To date, the molecular mechanism of the formation of fat tails in sheep has not been completely elucidated. Here, we conducted a genome-wide association study using phenotypes and genotypes (the Ovine Infinium HD SNP BeadChip genotype data) of two breeds of contrasting tail types (78 Small-tailed and 78 Large-tailed Han sheep breeds) to identify functional genes and variants associated with fat deposition. We identified four significantly (rs416433540, rs409848439, rs408118325 and rs402128848) and three approximately associated autosomal SNPs (rs401248376, rs402445895 and rs416201901). Gene annotation indicated that the surrounding genes (CREB1, STEAP4, CTBP1 and RIP140, also known as NRIP1) function in lipid storage or fat cell regulation. Furthermore, through an X-chromosome-wide association analysis, we detected significantly associated SNPs in the OARX: 88-89 Mb region, which could be a strong candidate genomic region for fat deposition in tails of sheep. Our results represent a new genomic resource for sheep genetics and breeding. In addition, the findings provide novel insights into genetic mechanisms of fat deposition in the tail of sheep and other mammals.

Two key genomic regions harbour QTLs for salinity tolerance in ICCV 2 × JG 11 derived chickpea (Cicer arietinum L.) recombinant inbred lines

BACKGROUND

Although chickpea (Cicer arietinum L.), an important food legume crop, is sensitive to salinity, considerable variation for salinity tolerance exists in the germplasm. To improve any existing cultivar, it is important to understand the genetic and physiological mechanisms underlying this tolerance.

RESULTS

In the present study, 188 recombinant inbred lines (RILs) derived from the cross ICCV 2 × JG 11 were used to assess yield and related traits in a soil with 0 mM NaCl (control) and 80 mM NaCl (salinity) over two consecutive years. Salinity significantly (P < 0.05) affected almost all traits across years and yield reduction was in large part related to a reduction in seed number but also a reduction in above ground biomass. A genetic map was constructed using 56 polymorphic markers (28 simple sequence repeats; SSRs and 28 single nucleotide polymorphisms; SNPs). The QTL analysis revealed two key genomic regions on CaLG05 (28.6 cM) and on CaLG07 (19.4 cM), that harboured QTLs for six and five different salinity tolerance associated traits, respectively, and imparting either higher plant vigour (on CaLG05) or higher reproductive success (on CaLG07). Two major QTLs for yield in the salinity treatment (explaining 12 and 17% of the phenotypic variation) were identified within the two key genomic regions. Comparison with already published chickpea genetic maps showed that these regions conferred salinity tolerance across two other populations and the markers can be deployed for enhancing salinity tolerance in chickpea. Based on the gene ontology annotation, forty eight putative candidate genes responsive to salinity stress were found on CaLG05 (31 genes) and CaLG07 (17 genes) in a distance of 11.1 Mb and 8.2 Mb on chickpea reference genome. Most of the genes were known to be involved in achieving osmoregulation under stress conditions.

CONCLUSION

Identification of putative candidate genes further strengthens the idea of using CaLG05 and CaLG07 genomic regions for marker assisted breeding (MAB). Further fine mapping of these key genomic regions may lead to novel gene identification for salinity stress tolerance in chickpea.