Systems genetics and bioinformatics analyses using ESR1-correlated genes identify potential candidates underlying female bone development.

Estrogen receptor α (ESR1) is involved in E2 signaling and plays a major role in postmenopausal bone loss. However, the molecular network underlying ESR1 has not been explored. We used systems genetics and bioinformatics to identify important genes associated with Esr1 in postmenopausal bone loss. We identified ~2300 Esr1-coexpressed genes in female BXD bone femur, functional analysis of which revealed 'osteoblast signaling' as the most enriched pathway. PPI network led to the identification of 25 'female bone candidates'. The gene-regulatory analysis revealed RUNX2 as a key TF. ANKRD1 and RUNX2 were significantly different between osteoporosis patients and healthy controls. Sp7, Col1a1 and Pth1r correlated with multiple femur bone phenotypes in BXD mice. miR-3121-3p targeted Csf1, Ankrd1, Sp7 and Runx2. ß-estradiol treatment markedly increased the expression of these candidates in mouse osteoblast. Our study revealed that Esr1-correlated genes Ankrd1, Runx2, Csf1 and Sp7 may play important roles in female bone development.

Identification of QTLs and candidate genes for water-soluble protein content in soybean seeds.

Soybean represents a vital source of premium plant-based proteins for human nutrition. Importantly, the level of water-soluble protein (WSP) is crucial for determining the overall quality and nutritional value of such crops. Enhancing WSP levels in soybean plants is a high-priority goal in crop improvement. This study aimed to elucidate the genetic basis of WSP content in soybean seeds by identifying quantitative trait loci (QTLs) and set the foundation for subsequent gene cloning and functional analysis. Using 180 F10 recombinant inbred lines generated by crossing the high-protein soybean cultivar JiDou 12 with the wild variety Ye 9, our researcher team mapped the QTLs influencing protein levels, integrating Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and gene expression profiling to identify candidate genes. During the 2020 and 2022 growing seasons, a standard bell-shaped distribution of protein content trait data was observed in these soybean lines. Eight QTLs affecting protein content were found across eight chromosomes, with LOD scores ranging from 2.59 to 7.30, explaining 4.15-11.74% of the phenotypic variance. Notably, two QTLs were newly discovered, one with a elite allele at qWSPC-15 from Ye 9. The major QTL, qWSPC-19, on chromosome 19 was stable across conditions and contained genes involved in nitrogen metabolism, amino acid biosynthesis, and signaling. Two genes from this QTL, Glyma.19G185700 and Glyma.19G186000, exhibited distinct expression patterns at maturity, highlighting the influence of these genes on protein content. This research revealed eight QTLs for WSP content in soybean seeds and proposed a gene for the key QTL qWSPC-19, laying groundwork for gene isolation and enhanced soybean breeding through the use of molecular markers. These insights are instrumental for developing protein-rich soybean cultivars.

Genome-wide association study identifies genomic regions associated with key reproductive traits in Korean Hanwoo cows.

BACKGROUND: Conducting genome-wide association studies (GWAS) for reproductive traits in Hanwoo cattle, including age at first calving (AFC), calving interval (CI), gestation length (GL), and number of artificial inseminations per conception (NAIPC), is of paramount significance. These analyses provided a thorough exploration of the genetic basis of these traits, facilitating the identification of key markers for targeted trait improvement. Breeders can optimize their selection strategies, leading to more efficient and sustainable breeding programs, by incorporating genetic insights. This impact extends beyond individual traits and contributes to the overall productivity and profitability of the Hanwoo beef cattle industry. Ultimately, GWAS is essential in ensuring the long-term genetic resilience and adaptability of Hanwoo cattle populations. The primary goal of this study was to identify significant single nucleotide polymorphisms (SNPs) or quantitative trait loci (QTLs) associated with the studied reproductive traits and subsequently map the underlying genes that hold promise for trait improvement. RESULTS: A genome-wide association study of reproductive traits identified 68 significant single nucleotide polymorphisms (SNPs) distributed across 29 Bos taurus autosomes (BTA). Among them, BTA14 exhibited the highest number of identified SNPs (25), whereas BTA6, BTA7, BTA8, BTA10, BTA13, BTA17, and BTA20 exhibited 8, 5, 5, 3, 8, 2, and 12 significant SNPs, respectively. Annotation of candidate genes within a 500 kb region surrounding the significant SNPs led to the identification of ten candidate genes relevant to age at first calving. These genes were: FANCG, UNC13B, TESK1, TLN1, and CREB3 on BTA8; FAM110B, UBXN2B, SDCBP, and TOX on BTA14; and MAP3K1 on BTA20. Additionally, APBA3, TCF12, and ZFR2, located on BTA7 and BTA10, were associated with the calving interval; PAX1, SGCD, and HAND1, located on BTA7 and BTA13, were linked to gestation length; and RBM47, UBE2K, and GPX8, located on BTA6 and BTA20, were linked to the number of artificial inseminations per conception in Hanwoo cows. CONCLUSIONS: The findings of this study enhance our knowledge of the genetic factors that influence reproductive traits in Hanwoo cattle populations and provide a foundation for future breeding strategies focused on improving desirable traits in beef cattle. This research offers new evidence and insights into the genetic variants and genome regions associated with reproductive traits and contributes valuable information to guide future efforts in cattle breeding.

Genome-wide association analysis identify candidate genes for feed efficiency and growth traits in Wenchang chickens.

BACKGROUND: Wenchang chickens are one of the most popular local chicken breeds in the Chinese chicken industry. However, the low feed efficiency is the main shortcoming of this breed. Therefore, there is a need to find a more precise breeding method to improve the feed efficiency of Wenchang chickens. In this study, we explored important candidate genes and variants for feed efficiency and growth traits through genome-wide association study (GWAS) analysis. RESULTS: Estimates of genomic heritability for growth and feed efficiency traits, including residual feed intake (RFI) of 0.05, average daily food intake (ADFI) of 0.21, average daily weight gain (ADG) of 0.24, body weight (BW) at 87, 95, 104, 113 days of age (BW87, BW95, BW104 and BW113) ranged from 0.30 to 0.44. Important candidate genes related to feed efficiency and growth traits were identified, such as PLCE1, LAP3, MED28, QDPR, LDB2 and SEL1L3 genes. CONCLUSION: The results identified important candidate genes for feed efficiency and growth traits in Wenchang chickens and provide a theoretical basis for the development of new molecular breeding technology.

Identification of candidate genes for Fusarium head blight resistance from QTLs using RIL population in wheat.

Fusarium head blight (FHB) stands out as one of the most devastating wheat diseases and leads to significantly grain yield losses and quality reductions in epidemic years. Exploring quantitative trait loci (QTL) for FHB resistance is a critical step for developing new FHB-resistant varieties. We previously constructed a genetic map of unigenes (UG-Map) according to the physical positions using a set of recombinant-inbred lines (RILs) derived from the cross of 'TN18 × LM6' (TL-RILs). Here, the number of diseased spikelets (NDS) and relative disease index (RDI) for FHB resistance were investigated under four environments using TL-RILs, which were distributed across 13 chromosomes. A number of 36 candidate genes for NDS and RDI from of 19 stable QTLs were identified. The average number of candidate genes per QTL was 1.89, with 14 (73.7%), two (10.5%), and three (15.8%) QTLs including one, two, and 3-10 candidate genes, respectively. Among the 24 candidate genes annotated in the reference genome RefSeq v1.1, the homologous genes of seven candidate genes, including TraesCS4B02G227300 for QNds/Rdi-4BL-4553, TraesCS5B02G303200, TraesCS5B02G303300, TraesCS5B02G303700, TraesCS5B02G303800 and TraesCS5B02G304000 for QNds/Rdi-5BL-9509, and TraesCS7A02G568400 for QNds/Rdi-7AL-14499, were previously reported to be related to FHB resistance in wheat, barely or Brachypodium distachyon. These genes should be closely associated with FHB resistance in wheat. In addition, the homologous genes of five genes, including TraesCS1A02G037600LC for QNds-1AS-2225, TraesCS1D02G017800 and TraesCS1D02G017900 for QNds-1DS-527, TraesCS1D02G018000 for QRdi-1DS-575, and TraesCS4B02G227400 for QNds/Rdi-4BL-4553, were involved in plant defense responses against pathogens. These genes should be likely associated with FHB resistance in wheat.

A current guide to candidate gene association studies.

Important factors contribute to a gained momentum in candidate gene association studies (CGASs), including the generalized use of next-generation sequencing (NGS), growing opportunities for hospital-based research, and the availability of open-source databases and bioinformatics tools. This article summarizes the general principles and analytical methods as a guide to CGASs in today's favorable context.

High-throughput diagnostic markers for foliar fungal disease resistance and high oleic acid content in groundnut.

BACKGROUND: Foliar diseases namely late leaf spot (LLS) and leaf rust (LR) reduce yield and deteriorate fodder quality in groundnut. Also the high oleic acid content has emerged as one of the most important traits for industries and consumers due to its increased shelf life and health benefits. RESULTS: Genetic mapping combined with pooled sequencing approaches identified candidate resistance genes (LLSR1 and LLSR2 for LLS and LR1 for LR) for both foliar fungal diseases. The LLS-A02 locus housed LLSR1 gene for LLS resistance, while, LLS-A03 housed LLSR2 and LR1 genes for LLS and LR resistance, respectively. A total of 49 KASPs markers were developed from the genomic regions of important disease resistance genes, such as NBS-LRR, purple acid phosphatase, pentatricopeptide repeat-containing protein, and serine/threonine-protein phosphatase. Among the 49 KASP markers, 41 KASPs were validated successfully on a validation panel of contrasting germplasm and breeding lines. Of the 41 validated KASPs, 39 KASPs were designed for rust and LLS resistance, while two KASPs were developed using fatty acid desaturase (FAD) genes to control high oleic acid levels. These validated KASP markers have been extensively used by various groundnut breeding programs across the world which led to development of thousands of advanced breeding lines and few of them also released for commercial cultivation. CONCLUSION: In this study, high-throughput and cost-effective KASP assays were developed, validated and successfully deployed to improve the resistance against foliar fungal diseases and oleic acid in groundnut. So far deployment of allele-specific and KASP diagnostic markers facilitated development and release of two rust- and LLS-resistant varieties and five high-oleic acid groundnut varieties in India. These validated markers provide opportunities for routine deployment in groundnut breeding programs.

QTL mapping and candidate gene mining of seed size and seed weight in castor plant (Ricinus communis L.).

BACKGROUND: Castor (Ricinus communis L., 2n = 2x = 20) is an important industrial crop, due to its oil is very important to the global special chemical industry. Seed size and seed weight are fundamentally important in determining castor yield, while little is known about it. In this study, QTL analysis and candidate gene mining of castor seed size and seed weight were conducted with composite interval mapping (CIM), inclusive composite interval mapping (ICIM) and marker enrichment strategy in 4 populations, i.e., populations F2, BC1, S1-1 and S1-2, derived from 2 accessions with significant phenotypic differences. RESULTS: In the QTL primary mapping, 2 novel QTL clusters were detected in marker intervals RCM520-RCM76 and RCM915-RCM950. In order to verify their accuracy and to narrow their intervals, QTL remapping was carried out in populations F2 and BC1. Among them, 44 and 30 QTLs underlying seed size and seed weight were detected in F2 population using methods CIM and ICIM-ADD respectively, including 4-9 and 3-5 ones conferring each trait were identified with a phenotypic variation explained ranged from 37.92 to 115.81% and 32.86-45.98% respectively. The remapping results in BC1 population were consistent with those in F2 population. Importantly, 3 QTL clusters (i.e. QTL-cluster1, QTL-cluster2 and QTL-cluster3) were found in marker intervals RCM74-RCM76 (37.1 kb), RCM930-RCM950 (259.8 kb) and RCM918-RCM920 (172.9 kb) respectively; in addition, all of them were detected again, the former one was found in the S1-2 population, and the latter two were found simultaneously in the populations S1-1 and S1-2. Finally, 6 candidate genes (i.e. LOC8266555, LOC8281168, LOC8281151, LOC8259066, LOC8258591 and LOC8270077) were screened in the above QTL clusters, they were differentially expressed in multiple seed tissues of both parents, signifying the potential role in regulating seed size and seed weight. CONCLUSION: The above results not only provide new insights into the genetic structure of seed size and seed weight in castor, but also lay the foundation for the functional identification of these candidate genes.

Fine mapping of a major QTL, qECQ8, for rice taste quality.

BACKGROUND: Rice ECQ (eating and cooking quality) is an important determinant of rice consumption and market expansion. Therefore, improvement of ECQ is one of the primary goals in rice breeding. However, ECQ-related quantitative trait loci (QTL) have not yet been fully revealed. The present study aimed to identify a major effect QTL for rice taste, an important component of ECQ via genotyping-by-sequencing, to reveal the associated molecular mechanisms, and to predict key candidate genes. RESULTS: A population of F9 recombinant inbred lines resulting from a cross between R668 (national standard of high-quality third class) and R838 (common edible rice) was used to construct a high-density genetic map (2,295.062 cM). The map comprises 639,504 markers distributed on 12 linkage elements with an average genetic distance of 0.004 cM. We detected a major taste-related QTL, qECQ8, which explained 41.4% of phenotypic variance and had LOD values of 4.42-7.73. Using a five-generation NIL population from the backcross of "Ganxiangzhan No. 1" carrying qECQ8 with the recurrent parent R838 (without qECQ8), we narrowed qECQ8 to a 187.5 kb interval between markers M33 and M37 on Chr8. Comparative transcriptomic analysis revealed that photosynthesis, glyoxylate and dicarboxylate metabolism, carbon fixation in photosynthetic organisms, and alpha-linolenic acid metabolism were induced in developing seeds of lines containing qECQ8. Furthermore, we identified two candidate genes in the qECQ8 region, including LOC_Os08g30550 (zinc knuckle family protein), a major candidate for genetic-assisted breeding of high-quality rice. CONCLUSION: Our findings provide important genetic resources for targeted improvement of rice taste quality and may facilitate the genetic breeding of rice ECQ.

Genome-wide association study of kernel colour traits and mining of elite alleles from the major loci in maize.

BACKGROUND: Maize kernel colour is an important index for evaluating maize quality and value and mainly entails two natural pigments, carotenoids and anthocyanins. To analyse the genetic mechanism of maize kernel colour and mine single nucleotide polymorphisms (SNPs) related to kernel colour traits, an association panel including 244 superior maize inbred lines was used to measure and analyse the six traits related to kernel colour in two environments and was then combined with the about 3 million SNPs covering the whole maize genome in this study. Two models (Q + K, PCA + K) were used for genome-wide association analysis (GWAS) of kernel colour traits. RESULTS: We identified 1029QTLs, and two SNPs contained in those QTLs were located in coding regions of Y1 and R1 respectively, two known genes that regulate kernel colour. Fourteen QTLs which contain 19 SNPs were within 200 kb interval of the genes involved in the regulation of kernel colour. 13 high-confidence SNPs repeatedly detected for specific traits, and AA genotypes of rs1_40605594 and rs5_2392770 were the most popular alleles appeared in inbred lines with higher levels. By searching the confident interval of the 13 high-confidence SNPs, a total of 95 candidate genes were identified. CONCLUSIONS: The genetic loci and candidate genes of maize kernel colour provided in this study will be useful for uncovering the genetic mechanism of maize kernel colour, gene cloning in the future. Furthermore, the identified elite alleles can be used to molecular marker-assisted selection of kernel colour traits.

Identification of quantitative trait loci and candidate genes for grain superoxide dismutase activity in wheat.

BACKGROUND: Superoxide dismutase (SOD) can greatly scavenge reactive oxygen species (ROS) in plants. SOD activity is highly related to plant stress tolerance that can be improved by overexpression of SOD genes. Identification of SOD activity-related loci and potential candidate genes is essential for improvement of grain quality in wheat breeding. However, the loci and candidate genes for relating SOD in wheat grains are largely unknown. In the present study, grain SOD activities of 309 recombinant inbred lines (RILs) derived from the 'Berkut' × 'Worrakatta' cross were assayed by photoreduction method with nitro-blue tetrazolium (NBT) in four environments. Quantitative trait loci (QTL) of SOD activity were identified using inclusive composite interval mapping (ICIM) with the genotypic data of 50 K single nucleotide polymorphism (SNP) array. RESULTS: Six QTL for SOD activity were mapped on chromosomes 1BL, 4DS, 5AL (2), and 5DL (2), respectively, explaining 2.2 ~ 7.4% of the phenotypic variances. Moreover, QSOD.xjau-1BL, QSOD.xjau-4DS, QSOD.xjau-5 A.1, QSOD.xjau-5 A.2, and QSOD.xjau-5DL.2 identified are likely to be new loci for SOD activity. Four candidate genes TraesCS4D01G059500, TraesCS5A01G371600, TraesCS5D01G299900, TraesCS5D01G343100LC, were identified for QSOD.xjau-4DS, QSOD.xjau-5AL.1, and QSOD.xjau-5DL.1 (2), respectively, including three SOD genes and a gene associated with SOD activity. Based on genetic effect analysis, this can be used to identify desirable alleles and excellent allele variations in wheat cultivars. CONCLUSION: These candidate genes are annotated for promoting SOD production and inhibiting the accumulation of ROS during plant growth. Therefore, lines with high SOD activity identified in this study may be preferred for future wheat breeding.

Genetic insights into superior grain number traits: a QTL analysis of wheat-Agropyron cristatum derivative pubing3228.

BACKGROUND: Agropyron cristatum (L.) is a valuable genetic resource for expanding the genetic diversity of common wheat. Pubing3228, a novel wheat-A. cristatum hybrid germplasm, exhibits several desirable agricultural traits, including high grain number per spike (GNS). Understanding the genetic architecture of GNS in Pubing3228 is crucial for enhancing wheat yield. This study aims to analyze the specific genetic regions and alleles associated with high GNS in Pubing3228. METHODS: The study employed a recombination inbred line (RIL) population derived from a cross between Pubing3228 and Jing4839 to investigate the genetic regions and alleles linked to high GNS. Quantitative Trait Loci (QTL) analysis and candidate gene investigation were utilized to explore these traits. RESULTS: A total of 40 QTLs associated with GNS were identified across 16 chromosomes, accounting for 4.25-17.17% of the total phenotypic variation. Five QTLs (QGns.wa-1D, QGns.wa-5 A, QGns.wa-7Da.1, QGns.wa-7Da.2 and QGns.wa-7Da.3) accounter for over 10% of the phenotypic variation in at least two environments. Furthermore, 94.67% of the GNS QTL with positive effects originated from Pubing3228. Candidate gene analysis of stable QTLs identified 11 candidate genes for GNS, including a senescence-associated protein gene (TraesCS7D01G148000) linked to the most significant SNP (AX-108,748,734) on chromosome 7D, potentially involved in reallocating nutrients from senescing tissues to developing seeds. CONCLUSION: This study provides new insights into the genetic mechanisms underlying high GNS in Pubing3228, offering valuable resources for marker-assisted selection in wheat breeding to enhance yield.

Transcriptome sequencing and expression analysis in peanut reveal the potential mechanism response to Ralstonia solanacearum infection.

BACKGROUND: Bacterial wilt caused by Ralstonia solanacearum severely affects peanut (Arachis hypogaea L.) yields. The breeding of resistant cultivars is an efficient means of controlling plant diseases. Therefore, identification of resistance genes effective against bacterial wilt is a matter of urgency. The lack of a reference genome for a resistant genotype severely hinders the process of identification of resistance genes in peanut. In addition, limited information is available on disease resistance-related pathways in peanut. RESULTS: Full-length transcriptome data were used to generate wilt-resistant and -susceptible transcript pools. In total, 253,869 transcripts were retained to form a reference transcriptome for RNA-sequencing data analysis. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of differentially expressed genes revealed the plant-pathogen interaction pathway to be the main resistance-related pathway for peanut to prevent bacterial invasion and calcium plays an important role in this pathway. Glutathione metabolism was enriched in wilt-susceptible genotypes, which would promote glutathione synthesis in the early stages of pathogen invasion. Based on our previous quantitative trait locus (QTL) mapping results, the genes arahy.V6I7WA and arahy.MXY2PU, which encode nucleotide-binding site-leucine-rich repeat receptor proteins, were indicated to be associated with resistance to bacterial wilt. CONCLUSIONS: This study identified several pathways associated with resistance to bacterial wilt and identified candidate genes for bacterial wilt resistance in a major QTL region. These findings lay a foundation for investigation of the mechanism of resistance to bacterial wilt in peanut.

Genome-wide analysis of AP2/ERF transcription factors that regulate fruit development of Chinese prickly ash.

BACKGROUND: AP2/ERF is a large family of plant transcription factor proteins that play essential roles in signal transduction, plant growth and development, and responses to various stresses. The AP2/ERF family has been identified and verified by functional analysis in various plants, but so far there has been no comprehensive study of these factors in Chinese prickly ash. Phylogenetic, motif, and functional analyses combined with transcriptome analysis of Chinese prickly ash fruits at different developmental stages (30, 60, and 90 days after anthesis) were conducted in this study. RESULTS: The analysis identified 146 ZbAP2/ERF genes that could be classified into 15 subgroups. The motif analysis revealed the presence of different motifs or elements in each group that may explain the functional differences between the groups. ZbERF13.2, ZbRAP2-12, and ZbERF2.1 showed high levels of expression in the early stages of fruit development. ZbRAP2-4, and ZbERF3.1 were significantly expressed at the fruit coloring stage (R2 and G2). ZbERF16 were significantly expressed at fruit ripening and expression level increased as the fruit continued to develop. Relative gene expression levels of 6 representative ZbAP2/ERFs assessed by RT-qPCR agreed with transcriptome analysis results. CONCLUSIONS: These genes identified by screening can be used as candidate genes that affect fruit development. The results of the analysis can help guide future genetic improvement of Chinese prickly ash and enrich our understanding of AP2/ERF transcription factors and their regulatory functions in plants.

Identification of soybean mosaic virus strain SC7 resistance loci and candidate genes in soybean [Glycine max (L.) Merr.].

Soybean [Glycine max (L.) Merr.] is an important legume crop worldwide, which provides abundant plant protein and oil for human beings. Soybean mosaic virus (SMV) can cause serious damage to the yield and quality of soybean, but it is difficult to control SMV with chemicals, breeding SMV-resistant varieties has become the most effective way to control the disease. Therefore, it is important to identify SMV resistance genes from soybean resources and apply them to soybean breeding. In this study, the disease rates (DRs) of 219 soybean accessions to SMV strain SC7 in two environments were investigated. A high-density NJAU 355 K SoySNP array was used for genome-wide association study (GWAS) of DR. A 274 kb region on chromosome 15 (1,110,567 bp to 1,384,173 bp) was repeatedly detected in two environments. Six new significant single nucleotide polymorphisms (SNPs) on chromosome 15 were identified. Four of these six SNPs were located within two candidate genes, Glyma.15G015700 and Glyma.15G015800. The elite haplotype Glyma.15G015700Hap I with low DR exhibited strong resistance to SC7. The expression of Glyma.15G015700 in the SMV-resistant accession increased significantly after inoculation with SC7. Furthermore, most of the proteins predicted to interact with Glyma.15G015700 are heat shock proteins, which have been shown to be related to disease resistance. In summary, new SMV resistance loci and a new candidate gene, Glyma.15G015700, were identified and might be utilized in further soybean disease resistance breeding.

Metabolite-based genome-wide association studies enable the dissection of the genetic bases of flavonoids, betaine and spermidine in wolfberry (Lycium).

Wolfberry is a plant with medicinal and food values. However, its bioactive ingredients and the corresponding genetic bases have not been determined. Here, we de novo generated a chromosome-level genome assembly for wolfberry, yielding a genome sequence of ~1.77 Gb with contig N50 of 50.55 Mb and 39 224 predicted gene models. A variation map, using 307 re-sequenced accessions, was called based on this genome assembly. Furthermore, the fruit metabolome of these accessions was profiled using 563 annotated metabolites, which separated Lycium barbarum L. and non-L. barbarum L. The flavonoids, coumarins, alkaloids and nicotinic acid contents were higher in the former than in the latter. A metabolite-based genome-wide association study mapped 156 164 significant single nucleotide polymorphisms corresponding to 340 metabolites. This included 19 219 unique lead single nucleotide polymorphisms in 1517 significant association loci, of which three metabolites, flavonoids, betaine and spermidine, were highlighted. Two candidate genes, LbUGT (evm.TU.chr07.2692) and LbCHS (evm.TU.chr07.2738), with non-synonymous mutations, were associated with the flavonoids content. LbCHS is a structural gene that interacts with a nearby MYB transcription factor (evm.TU.chr07.2726) both in L. barbarum and L. ruthenicum. Thus, these three genes might be involved in the biosynthesis/metabolism of flavonoids. LbSSADH (evm.TU.chr09.627) was identified as possibly participating in betaine biosynthesis/metabolism. Four lycibarbarspermidines (E-G and O) were identified, and only the lycibarbarspermidines O content was higher in L. barbarum varieties than in non-L. barbarum varieties. The evm.TU.chr07.2680 gene associated with lycibarbarspermidines O was annotated as an acetyl-CoA-benzylalcohol acetyltransferase, suggesting that it is a candidate gene for spermidine biosynthesis. These results provide novel insights into the specific metabolite profile of non-L. barbarum L. and the genetic bases of flavonoids, betaine and spermidine biosynthesis/metabolism.

Considerations for reporting variants in novel candidate genes identified during clinical genomic testing.

Since the first novel gene discovery for a Mendelian condition was made via exome sequencing, the rapid increase in the number of genes known to underlie Mendelian conditions coupled with the adoption of exome (and more recently, genome) sequencing by diagnostic testing labs has changed the landscape of genomic testing for rare diseases. Specifically, many individuals suspected to have a Mendelian condition are now routinely offered clinical ES. This commonly results in a precise genetic diagnosis but frequently overlooks the identification of novel candidate genes. Such candidates are also less likely to be identified in the absence of large-scale gene discovery research programs. Accordingly, clinical laboratories have both the opportunity, and some might argue a responsibility, to contribute to novel gene discovery, which should, in turn, increase the diagnostic yield for many conditions. However, clinical diagnostic laboratories must necessarily balance priorities for throughput, turnaround time, cost efficiency, clinician preferences, and regulatory constraints and often do not have the infrastructure or resources to effectively participate in either clinical translational or basic genome science research efforts. For these and other reasons, many laboratories have historically refrained from broadly sharing potentially pathogenic variants in novel genes via networks such as Matchmaker Exchange, much less reporting such results to ordering providers. Efforts to report such results are further complicated by a lack of guidelines for clinical reporting and interpretation of variants in novel candidate genes. Nevertheless, there are myriad benefits for many stakeholders, including patients/families, clinicians, and researchers, if clinical laboratories systematically and routinely identify, share, and report novel candidate genes. To facilitate this change in practice, we developed criteria for triaging, sharing, and reporting novel candidate genes that are most likely to be promptly validated as underlying a Mendelian condition and translated to use in clinical settings.

A Strong Candidate Gene for Nonsyndromic Intellectual Disability Phenotype: SGSM3.

SGSM proteins are small modulator proteins interacting with proteins in the RAS signaling pathway. Studies with mouse and human tissues indicated that SGSM genes were highly expressed in the brain and could be expressed at different levels at different stages of development in fetal and adult brain tissue. It was first reported by Birnbaum et al. that the SGSM3 gene might be associated with a Mendelian inherited disease in families of Ashkenazi Jews with clinical manifestations of intellectual disability (ID). In this study, a novel homozygous stop-gain (NM_015705.6: c.1576C>T: p.(Arg526Ter)) variation was detected in the SGSM3 gene in two siblings with short stature and ID findings. The report of two cases with bi-allelic LOF variants in the SGSM3 gene from different populations with similar clinical manifestations strengthens the potential of this gene as a candidate gene for the nonsyndromic ID phenotype. Functional studies are required to investigate the signaling pathways affected by SGSM3 gene variations to produce the ID phenotype and their effect on the functioning of neurons.

Whole-exome sequencing screening for candidate genes and variants associated with primary sporadic keratoconus in Chinese patients.

The pathogenesis of keratoconus (KC) is complex, and genetic factors play an important role. The purpose of this study was to screen and analyse candidate genes and variants in Chinese patients with primary sporadic KC. Whole-exome sequencing (WES) was performed to identify candidate genes and variants in 105 unrelated Chinese patients with primary sporadic KC. Through a series of screening processes, 54 candidate variants in 26 KC candidate genes were identified in 53 KC patients (53/105, 50.5%). These 54 candidate variants included 10 previously identified variants in 9 KC candidate genes and 44 novel variants in 20 KC candidate genes. The previously identified variants occurred in 25.7% (27/105) of patients. Of these, 4 variants (COL6A5, c.5014T > G; CAST, c.1814G > A; ZNF469, c.946G > A; and MPDZ, c.3836A > G) were identified for the first time in Chinese KC patients. The novel variants occurred in 33.3% (35/105) of patients. Of the 26 screened KC candidate genes, 11 KC candidate genes (CAT, COL12A1, FLG, HKDC1, HSPG2, PLOD1, ITGA2, TFAP2B, USH2A, WNT10A, and COL6A5) were found to be potentially pathogenic in Chinese KC patients for the first time. Gene Ontology (GO) biological process (BP) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on the 26 KC candidate genes using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The results showed that the KC candidate genes were significantly enriched in biological processes such as collagen fibril organization and extracellular matrix (ECM) organization and in ECM-receptor interaction and protein digestion and absorption pathways. The results further expand the spectrum of KC candidate variants and provide a basis for further KC gene studies.

High number of candidate gene variants are identified as disease-causing in a period of 4 years.

Advances in bioinformatic tools paired with the ongoing accumulation of genetic knowledge and periodic reanalysis of genomic sequencing data have led to an improvement in genetic diagnostic rates. Candidate gene variants (CGVs) identified during sequencing or on reanalysis but not yet implicated in human disease or associated with a phenotypically distinct condition are often not revisited, leading to missed diagnostic opportunities. Here, we revisited 33 such CGVs from our previously published study and determined that 16 of them are indeed disease-causing (novel or phenotype expansion) since their identification. These results emphasize the need to focus on previously identified CGVs during sequencing or reanalysis and the importance of sharing that information with researchers around the world, including relevant functional analysis to establish disease causality.