Noncoding deletions reveal a gene that is critical for intestinal function.

Large-scale genome sequencing is poised to provide a substantial increase in the rate of discovery of disease-associated mutations, but the functional interpretation of such mutations remains challenging. Here we show that deletions of a sequence on human chromosome 16 that we term the intestine-critical region (ICR) cause intractable congenital diarrhoea in infants1,2. Reporter assays in transgenic mice show that the ICR contains a regulatory sequence that activates transcription during the development of the gastrointestinal system. Targeted deletion of the ICR in mice caused symptoms that recapitulated the human condition. Transcriptome analysis revealed that an unannotated open reading frame (Percc1) flanks the regulatory sequence, and the expression of this gene was lost in the developing gut of mice that lacked the ICR. Percc1-knockout mice displayed phenotypes similar to those observed upon ICR deletion in mice and patients, whereas an ICR-driven Percc1 transgene was sufficient to rescue the phenotypes found in mice that lacked the ICR. Together, our results identify a gene that is critical for intestinal function and underscore the need for targeted in vivo studies to interpret the growing number of clinical genetic findings that do not affect known protein-coding genes.

Target gene overexpression and enhanced metabolism confer resistance to nicosulfuron in Eriochloa villosa (Thunb.).

Eriochloa villosa (Thunb.) Kunth is a troublesome weed widely distributed in maize (Zea mays L.) fields in Northeast China. Many populations of E. villosa have evolved resistance to nicosulfuron herbicides, which inhibit acetolactate synthase (ALS). The objectives of this research were to confirm that E. villosa is resistant to nicosulfuron and to investigate the basis of nicosulfuron resistance. Whole-plant dose-response studies revealed that the R population had not developed a high level of cross-resistance and exhibited greater resistant (25.62-fold) to nicosulfuron than that of the S population and had not yet developed a high level of cross-resistance. An in vitro ALS activity assay demonstrated that the I50 of nicosulfuron was 6.87-fold greater in the R population than the S population. However, based on ALS gene sequencing, the target ALS gene in the R population did not contain mutations. Quantitative real-time polymerase chain reaction (qRT-PCR) revealed that ALS gene expression between the R and S populations was significantly different after nicosulfuron application, but no differences were observed in the gene copy number. After the cytochrome P450 inhibitor malathion or the GST inhibitor NBD-Cl was applied, the resistant E. villosa population exhibited increased sensitivity to nicosulfuron. Based on the activities of GSTs and P450s, the activities of the R population were greater than those of the S population after nicosulfuron application. This is the first report that the resistance of E. villosa to ALS inhibitors results from increased target gene expression and increased metabolism. These findings provide a theoretical foundation for the effective control of herbicide-resistant E. villosa.

Residue dynamics of florpyrauxifen-benzyl and its effects on bacterial community structure in paddy soil of Northeast China.

Florpyrauxifen-benzyl is an herbicide that has been developed in recent years. Its degradation mode in paddy soil environments is not clear. In this study, the degradation dynamics in paddy soil and water were studied by ultrahigh-performance liquid chromatography. Microbial degradation was the main degradation pathway. Using third-generation high-throughput sequencing technology, the changes in the soil bacterial community structure were studied. After 30 days of application, compared with the control group (F0), the abundance of Sphingomonas, Lysobacter, and Flavisolibacter in the recommended and repeated application groups (F1, F5 and F10) increased significantly, and uncultured bacterium and Terrimonas decreased significantly. Compared with the F0 and F1 groups, the species diversity of the F0 and F1 groups showed a significant increase over time. The species diversity of the F5 and F10 groups decreased significantly on Days 5 and 15. On Day 30, the recovery even exceeded that of the control group. Luteimonas and five other genera were positively correlated with herbicide residues, and Pseudolabrys and two other genera were negatively correlated. Repeated application showed a significant effect on the structure of the soil bacterial community, mainly showing a trend of a significant decrease in the initial stage and gradual recovery in the later stage. The results will guide the safe and rational use of florpyrauxifen-benzyl and provide a scientific basis for florpyrauxifen-benzyl dynamic supervision of environmental pollution and protection of black soil in Northeast China.

Target-site and non-target-site based resistance to clodinafop-propargyl in wild oats (Avena fatua L.).

Wild oat (Avena fatua L.) is a common and problematic weed in wheat fields in China. In recent years, farmers found it increasingly difficult to control A. fatua using acetyl-CoA carboxylase (ACCase)-inhibiting herbicides. The purpose of this study was to identify the molecular basis of clodinafop-propargyl resistance in A. fatua. In comparison to the S1496 population, whole dose response studies revealed that the R1623 and R1625 populations were 71.71- and 67.76-fold resistant to clodinafop-propargyl, respectively. The two resistant A. fatua populations displayed high resistance to fenoxaprop-p-ethyl (APP) and low resistance to clethodim (CHD) and pinoxaden (PPZ), but they were still sensitive to the ALS inhibitors mesosulfuron-methyl and pyroxsulam. An Ile-2041-Asn mutation was identified in both resistant individual plants. The copy number and relative expression of the ACCase gene in the resistant population were not significantly different from those in the S1496 population. Under the application of 2160 g ai ha -1 of clodinafop-propargyl, the fresh weight of the R1623 population was reduced to 74.9%; however, pretreatment with the application of the cytochrome P450 inhibitor malathion and the GST inhibitor NBD-Cl reduced the fresh weight to 50.91% and 47.16%, respectively, which proved the presence of metabolic resistance. This is the first report of an Ile-2041-Asn mutation and probable metabolic resistance in A. fatua, resulting in resistance to clodinafop-propargyl.

Identification of Pathogens and Evaluation of Resistance and Genetic Diversity of Maize Inbred Lines to Stalk Rot in Heilongjiang Province, China.

Maize stalk rot, caused by multiple pathogens, is a serious soilborne disease worldwide. Composition of pathogens causing maize stalk rot and resistance of maize inbred lines in Heilongjiang Province, China, are not well understood. In this study, 138 fungal isolates were collected from different maize-producing areas in Heilongjiang Province, which were identified as Fusarium graminearum (23.2%), F. subglutinans (18.9%), F. cerealis (18.9%), Bipolaris zeicola (13.0%), F. brachygibbosum (13.0%), F. temperatum (7.2%), and F. proliferatum (5.8%). Among them, F. graminearum (>20%) was the predominant species among the isolates causing maize stalk rot. B. zeicola had not previously been reported causing maize stalk rot in China. Resistance of 67 maize inbred lines to maize stalk rot was assessed, and 24 lines (35.8% of them) were highly resistant or resistant, indicating that approximately 65% of these lines were susceptible to maize stalk rot. Maize inbred lines were analyzed using simple sequence repeat markers and divided into five genetic groups with 12 pairs of primers. Additionally, analysis of molecular variance indicated that 44.2% of the genetic variation in disease resistance was distributed among populations. This study provides insight into the genetic diversity of inbred maize and may contribute useful information for breeding stalk rot disease-resistant hybrids, and facilitates development of effective strategies for managing this destructive disease complex.

Rapid identification of a candidate nicosulfuron sensitivity gene (Nss) in maize (Zea mays L.) via combining bulked segregant analysis and RNA-seq.

KEY MESSAGE: A candidate nicosulfuron sensitivity gene Nss was identified by combining bulked segregant analysis and RNA-seq. Multiple mutations of this gene were discovered in nicosulfuron-sensitive maize compared with the tolerant. It has been demonstrated that variabilities exist in maize response to nicosulfuron. Two nicosulfuron-sensitive inbred lines (HB39, HB41) and two tolerant inbred lines (HB05, HB09) were identified via greenhouse and field trials. Genetic analysis indicated that the sensitivity to nicosulfuron in maize was controlled by a single, recessive gene. To precisely and rapidly map the nicosulfuron sensitivity gene (Nss), two independent F2 segregating populations, Population A (HB41 × HB09) and Population B (HB39 × HB05), were constructed. By applying bulked segregant RNA-Seq (BSR-Seq), the Nss gene was, respectively, mapped on the short arm of chromosome 5 (chr5: 1.1-15.3 Mb) and (chr5: 0.5-18.2 Mb) using two populations, with 14.2 Mb region in common. Further analysis revealed that there were 43 and 119 differentially expressed genes in the mapping intervals, with 18 genes in common. Gene annotation results showed that a cytochrome P450 gene (CYP81A9) appeared to be the candidate gene of Nss associated with nicosulfuron sensitivity in maize. Sequence analysis demonstrated that two common deletion mutations existed in the sensitive maize, which might lead to the nicosulfuron sensitivity in maize. The results will make valuable contributions to the understanding of molecular mechanism of herbicide sensitivity in maize.

De novo mutations in epileptic encephalopathies.

Epileptic encephalopathies are a devastating group of severe childhood epilepsy disorders for which the cause is often unknown. Here we report a screen for de novo mutations in patients with two classical epileptic encephalopathies: infantile spasms (n = 149) and Lennox-Gastaut syndrome (n = 115). We sequenced the exomes of 264 probands, and their parents, and confirmed 329 de novo mutations. A likelihood analysis showed a significant excess of de novo mutations in the ∼4,000 genes that are the most intolerant to functional genetic variation in the human population (P = 2.9 × 10(-3)). Among these are GABRB3, with de novo mutations in four patients, and ALG13, with the same de novo mutation in two patients; both genes show clear statistical evidence of association with epileptic encephalopathy. Given the relevant site-specific mutation rates, the probabilities of these outcomes occurring by chance are P = 4.1 × 10(-10) and P = 7.8 × 10(-12), respectively. Other genes with de novo mutations in this cohort include CACNA1A, CHD2, FLNA, GABRA1, GRIN1, GRIN2B, HNRNPU, IQSEC2, MTOR and NEDD4L. Finally, we show that the de novo mutations observed are enriched in specific gene sets including genes regulated by the fragile X protein (P < 10(-8)), as has been reported previously for autism spectrum disorders.

Incorporating Functional Information in Tests of Excess De Novo Mutational Load.

A number of recent studies have investigated the role of de novo mutations in various neurodevelopmental and neuropsychiatric disorders. These studies attempt to implicate causal genes by looking for an excess load of de novo mutations within those genes. Current statistical methods for assessing this excess are based on the implicit assumption that all qualifying mutations in a gene contribute equally to disease. However, it is well established that different mutations can have radically different effects on the ultimate protein product and, as a result, on disease risk. Here, we propose a method, fitDNM, that incorporates functional information in a test of excess de novo mutational load. Specifically, we derive score statistics from a retrospective likelihood that incorporates the probability of a mutation being damaging to gene function. We show that, under the null, the resulting test statistic is distributed as a weighted sum of Poisson random variables and we implement a saddlepoint approximation of this distribution to obtain accurate p values. Using simulation, we have shown that our method outperforms current methods in terms of statistical power while maintaining validity. We have applied this approach to four de novo mutation datasets of neurodevelopmental and neuropsychiatric disorders: autism spectrum disorder, epileptic encephalopathy, schizophrenia, and severe intellectual disability. Our approach also implicates genes that have been implicated by existing methods. Furthermore, our approach provides strong statistical evidence supporting two potentially causal genes: SUV420H1 in autism spectrum disorder and TRIO in a combined analysis of the four neurodevelopmental and neuropsychiatric disorders investigated here.

The Intolerance of Regulatory Sequence to Genetic Variation Predicts Gene Dosage Sensitivity.

Noncoding sequence contains pathogenic mutations. Yet, compared with mutations in protein-coding sequence, pathogenic regulatory mutations are notoriously difficult to recognize. Most fundamentally, we are not yet adept at recognizing the sequence stretches in the human genome that are most important in regulating the expression of genes. For this reason, it is difficult to apply to the regulatory regions the same kinds of analytical paradigms that are being successfully applied to identify mutations among protein-coding regions that influence risk. To determine whether dosage sensitive genes have distinct patterns among their noncoding sequence, we present two primary approaches that focus solely on a gene's proximal noncoding regulatory sequence. The first approach is a regulatory sequence analogue of the recently introduced residual variation intolerance score (RVIS), termed noncoding RVIS, or ncRVIS. The ncRVIS compares observed and predicted levels of standing variation in the regulatory sequence of human genes. The second approach, termed ncGERP, reflects the phylogenetic conservation of a gene's regulatory sequence using GERP++. We assess how well these two approaches correlate with four gene lists that use different ways to identify genes known or likely to cause disease through changes in expression: 1) genes that are known to cause disease through haploinsufficiency, 2) genes curated as dosage sensitive in ClinGen's Genome Dosage Map, 3) genes judged likely to be under purifying selection for mutations that change expression levels because they are statistically depleted of loss-of-function variants in the general population, and 4) genes judged unlikely to cause disease based on the presence of copy number variants in the general population. We find that both noncoding scores are highly predictive of dosage sensitivity using any of these criteria. In a similar way to ncGERP, we assess two ensemble-based predictors of regional noncoding importance, ncCADD and ncGWAVA, and find both scores are significantly predictive of human dosage sensitive genes and appear to carry information beyond conservation, as assessed by ncGERP. These results highlight that the intolerance of noncoding sequence stretches in the human genome can provide a critical complementary tool to other genome annotation approaches to help identify the parts of the human genome increasingly likely to harbor mutations that influence risk of disease.

Utilizing population controls in rare-variant case-parent association tests.

There is great interest in detecting associations between human traits and rare genetic variation. To address the low power implicit in single-locus tests of rare genetic variants, many rare-variant association approaches attempt to accumulate information across a gene, often by taking linear combinations of single-locus contributions to a statistic. Using the right linear combination is key-an optimal test will up-weight true causal variants, down-weight neutral variants, and correctly assign the direction of effect for causal variants. Here, we propose a procedure that exploits data from population controls to estimate the linear combination to be used in an case-parent trio rare-variant association test. Specifically, we estimate the linear combination by comparing population control allele frequencies with allele frequencies in the parents of affected offspring. These estimates are then used to construct a rare-variant transmission disequilibrium test (rvTDT) in the case-parent data. Because the rvTDT is conditional on the parents' data, using parental data in estimating the linear combination does not affect the validity or asymptotic distribution of the rvTDT. By using simulation, we show that our new population-control-based rvTDT can dramatically improve power over rvTDTs that do not use population control information across a wide variety of genetic architectures. It also remains valid under population stratification. We apply the approach to a cohort of epileptic encephalopathy (EE) trios and find that dominant (or additive) inherited rare variants are unlikely to play a substantial role within EE genes previously identified through de novo mutation studies.

Systematic assessment of imputation performance using the 1000 Genomes reference panels.

Genotype imputation has been widely adopted in the postgenome-wide association studies (GWAS) era. Owing to its ability to accurately predict the genotypes of untyped variants, imputation greatly boosts variant density, allowing fine-mapping studies of GWAS loci and large-scale meta-analysis across different genotyping arrays. By leveraging genotype data from 90 whole-genome deeply sequenced individuals as the evaluation benchmark and the 1000 Genomes Project data as reference panels, we systematically examined four important issues related to genotype imputation practice. First, in a study of imputation accuracy, we found that IMPUTE2 and minimac have the best imputation performance among the three popular imputing software evaluated and that using a multi-population reference panel is beneficial. Second, the optimal imputation quality cutoff for removing poorly imputed variants varies according to the software used. Third, the major contributing factors to consistently poor imputation are low variant heterozygosity, high sequence similarity to other genomic regions, high GC content, segmental duplication and being far from genotyping markers. Lastly, in an evaluation of the imputability of all known GWAS regions, we found that GWAS loci associated with hematological measurements and immune system diseases are harder to impute, as compared with other human traits. Recommendations made based on the above findings may provide practical guidance for imputation exercise in future genetic studies.

A Bayesian framework for de novo mutation calling in parents-offspring trios.

MOTIVATION: Spontaneous (de novo) mutations play an important role in the disease etiology of a range of complex diseases. Identifying de novo mutations (DNMs) in sporadic cases provides an effective strategy to find genes or genomic regions implicated in the genetics of disease. High-throughput next-generation sequencing enables genome- or exome-wide detection of DNMs by sequencing parents-proband trios. It is challenging to sift true mutations through massive amount of noise due to sequencing error and alignment artifacts. One of the critical limitations of existing methods is that for all genomic regions the same pre-specified mutation rate is assumed, which has a significant impact on the DNM calling accuracy. RESULTS: In this study, we developed and implemented a novel Bayesian framework for DNM calling in trios (TrioDeNovo), which overcomes these limitations by disentangling prior mutation rates from evaluation of the likelihood of the data so that flexible priors can be adjusted post-hoc at different genomic sites. Through extensively simulations and application to real data we showed that this new method has improved sensitivity and specificity over existing methods, and provides a flexible framework to further improve the efficiency by incorporating proper priors. The accuracy is further improved using effective filtering based on sequence alignment characteristics. AVAILABILITY AND IMPLEMENTATION: The C++ source code implementing TrioDeNovo is freely available at https://medschool.vanderbilt.edu/cgg. CONTACT: bingshan.li@vanderbilt.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Position effect on FGF13 associated with X-linked congenital generalized hypertrichosis.

X-linked congenital generalized hypertrichosis (Online Mendelian Inheritance in Man 307150) is an extremely rare condition of hair overgrowth on different body sites. We previously reported linkage in a large Mexican family with X-linked congenital generalized hypertrichosis cosegregating with deafness and with dental and palate anomalies to Xq24-27. Using SNP oligonucleotide microarray analysis and whole-genome sequencing, we identified a 389-kb interchromosomal insertion at an extragenic palindrome site at Xq27.1 that completely cosegregates with the disease. Among the genes surrounding the insertion, we found that Fibroblast Growth Factor 13 (FGF13) mRNA levels were significantly reduced in affected individuals, and immunofluorescence staining revealed a striking decrease in FGF13 localization throughout the outer root sheath of affected hair follicles. Taken together, our findings suggest a role for FGF13 in hair follicle growth and in the hair cycle.

Using ERDS to infer copy-number variants in high-coverage genomes.

Although there are many methods available for inferring copy-number variants (CNVs) from next-generation sequence data, there remains a need for a system that is computationally efficient but that retains good sensitivity and specificity across all types of CNVs. Here, we introduce a new method, estimation by read depth with single-nucleotide variants (ERDS), and use various approaches to compare its performance to other methods. We found that for common CNVs and high-coverage genomes, ERDS performs as well as the best method currently available (Genome STRiP), whereas for rare CNVs and high-coverage genomes, ERDS performs better than any available method. Importantly, ERDS accommodates both unique and highly amplified regions of the genome and does so without requiring separate alignments for calling CNVs and other variants. These comparisons show that for genomes sequenced at high coverage, ERDS provides a computationally convenient method that calls CNVs as well as or better than any currently available method.

Whole-exome sequencing in undiagnosed genetic diseases: interpreting 119 trios.

PURPOSE: Despite the recognized clinical value of exome-based diagnostics, methods for comprehensive genomic interpretation remain immature. Diagnoses are based on known or presumed pathogenic variants in genes already associated with a similar phenotype. Here, we extend this paradigm by evaluating novel bioinformatics approaches to aid identification of new gene-disease associations. METHODS: We analyzed 119 trios to identify both diagnostic genotypes in known genes and candidate genotypes in novel genes. We considered qualifying genotypes based on their population frequency and in silico predicted effects we also characterized the patterns of genotypes enriched among this collection of patients. RESULTS: We obtained a genetic diagnosis for 29 (24%) of our patients. We showed that patients carried an excess of damaging de novo mutations in intolerant genes, particularly those shown to be essential in mice (P = 3.4 × 10(-8)). This enrichment is only partially explained by mutations found in known disease-causing genes. CONCLUSION: This work indicates that the application of appropriate bioinformatics analyses to clinical sequence data can also help implicate novel disease genes and suggest expanded phenotypes for known disease genes. These analyses further suggest that some cases resolved by whole-exome sequencing will have direct therapeutic implications.

Dandelion polysaccharides improve the emulsifying properties and antioxidant capacities of emulsions stabilized by whey protein isolate.

In this study, the effects of dandelion polysaccharide (DP) and its carboxymethylated derivative (CMDP) on the emulsifying characteristics and antioxidant capacities of emulsions stabilized by whey protein isolate (WPI) were determined. The addition of both DP and CMDP reduced the particle size and zeta potential of the emulsions. Using 1.0 % WPI and 1.0 % CMDP as emulsifier, the emulsifying activity index (EAI) and emulsifying stability index (ESI) were 32.61 ± 0.11 m2/g and 42.58 ± 0.13 min, respectively, which were higher than the corresponding values of 27.19 ± 0.18 m2/g and 36.17 ± 0.15 min with 1.0 % WPI and 1.0 % DP. Fourier-transform infrared spectroscopy (FT-IR), far-ultraviolet circular dichroism (Far-UV CD), and fluorescence (FS) spectra analyses confirmed that the α-helix and ß-sheet structures in WPI-polysaccharide complexes were reduced compared with those in pure WPI, whereas the random-coil content was enhanced by the addition of polysaccharides. Moreover, DP and CMDP effectively improved the antioxidant capacity and inhibited oxidation of the emulsions during storage. Therefore, DP and its carboxymethylated derivative exhibit great potential to be applied in the emulsion-based delivery system.

Accelerating the Phase Formation Kinetics of Alluaudite Sodium Iron Sulfate Cathodes via Ultrafast Thermal Shock.

Alluaudite sodium iron sulfate (NFS) exhibits great potential for use in sodium-ion battery cathodes due to its elevated operating potential and abundant element reserves. However, conventional solid-state methods demonstrate a low heating/cooling rate and sluggish reaction kinetics, requiring a long thermal treatment to effectively fabricate NFS cathodes. Herein, we propose a thermal shock (TS) strategy to synthesize alluaudite sodium iron sulfate cathodes using either hydrous or anhydrous raw materials. The analysis of the phase formation process reveals that TS treatment can significantly facilitate the removal of crystal water and decomposition of the intermediate phase Na2Fe(SO4)2 in the hydrous precursor. In the case of the anhydrous precursor, the kinetics of the combination reaction between Na2SO4 and FeSO4 can be also accelerated by TS treatment. Consequently, pure NFS phase formation can be completed after a substantially shorter time of post-sintering, thereby saving significant time and energy. The TS-treated NFS cathode derived from hydrous precursor exhibits higher retention after 200 cycles at 1C and better rate capability than the counterpart prepared by conventional long-term tube furnace sintering, demonstrating the great potential of this novel strategy.

Comparison of class 2 transposable elements at superfamily resolution reveals conserved and distinct features in cereal grass genomes.

BACKGROUND: Class 2 transposable elements (TEs) are the predominant elements in and around plant genes where they generate significant allelic diversity. Using the complete sequences of four grasses, we have performed a novel comparative analysis of class 2 TEs. To ensure consistent comparative analyses, we re-annotated class 2 TEs in Brachypodium distachyon, Oryza sativa (rice), Sorghum bicolor and Zea mays and assigned them to one of the five cut-and-paste superfamilies found in plant genomes (Tc1/mariner, PIF/Harbinger, hAT, Mutator, CACTA). We have focused on noncoding elements because of their abundance, and compared superfamily copy number, size and genomic distribution as well as correlation with the level of nearby gene expression. RESULTS: Our comparison revealed both unique and conserved features. First, the average length or size distribution of elements in each superfamily is largely conserved, with the shortest always being Tc1/mariner elements, followed by PIF/Harbinger, hAT, Mutator and CACTA. This order also holds for the ratio of the copy numbers of noncoding to coding elements. Second, with the exception of CACTAs, noncoding TEs are enriched within and flanking genes, where they display conserved distribution patterns, having the highest peak in the promoter region. Finally, our analysis of microarray data revealed that genes associated with Tc1/mariner and PIF/Harbinger noncoding elements have significantly higher expression levels than genes without class 2 TEs. In contrast, genes with CACTA elements have significantly lower expression than genes without class 2 TEs. CONCLUSIONS: We have achieved the most comprehensive annotation of class 2 TEs to date in these four grass genomes. Comparative analysis of this robust dataset led to the identification of several previously unknown features of each superfamily related to copy number, element size, genomic distribution and correlation with the expression levels of nearby genes. These results highlight the importance of distinguishing TE superfamilies when assessing their impact on gene and genome evolution.

Planting models and deficit irrigation strategies to improve radiation use efficiency, dry matter translocation and winter wheat productivity under semi-arid regions.

The dry-land farming system of China relies on plastic film mulching and natural rainfall to mitigate damage caused by drought. However, the applications of deficit irrigation modes combined with the planting models can significantly increase production of wheat, dry matter translocation and radiation use efficiency (RUE) remains unidentified. Thus, in 2016-2018, we conducted field trials that implemented four deficit irrigation modes (IJF: irrigation at jointing and flowering stages; IF: irrigation at flowering stage; IJ: irrigation at jointing stage; NI: no irrigation) under two cultivation patterns (ridge furrow rainfall harvesting system (RF); traditional flat cultivation (TF)). The results indicated that the effects of RF system with deficit irrigation (IJF: 250 mm) could significantly increase the soil moisture, and thus enhanced LAI, In value, IPAR, RUE, and PAR capture ratio than that of TF-NI planting. This is due to decreased canopy light transmittance (LT), reflection and penetration ratio of PAR, as a result considerable improve the biomass translocation and grain yield. Owing to the very low soil water content after the seed-filling, the LAI, IPAR, and In value decreased during the seed-filling under water stress, ultimately affecting the dry matter translocation efficiency. While the IJF and IF treatments provided water for reproductive growth stage, therefore, the production of wheat and RUE were significantly maximum compared with IJ and NI irrigation mode. Under the RF system with IJF, IF, and IJ treatments the grain yield increased by 81.2%, 56.8%, 45.6% and 17.2%, then that of TF-NI treatment, respectively. The highest RUE (1.93 g MJ-1), dry-matter translocation (154.2%) and seed yield (81.2%) were obtained in the RF-IJF treatment compared with TF-NI. Therefore, the RF-IJF treatment significantly improved the earlier development and rapid plant growth, which is a suitable planting model for increasing soil moisture, LAI, RUE, DMT, and winter wheat production.

MITE-Hunter: a program for discovering miniature inverted-repeat transposable elements from genomic sequences.

Miniature inverted-repeat transposable elements (MITEs) are a special type of Class 2 non-autonomous transposable element (TE) that are abundant in the non-coding regions of the genes of many plant and animal species. The accurate identification of MITEs has been a challenge for existing programs because they lack coding sequences and, as such, evolve very rapidly. Because of their importance to gene and genome evolution, we developed MITE-Hunter, a program pipeline that can identify MITEs as well as other small Class 2 non-autonomous TEs from genomic DNA data sets. The output of MITE-Hunter is composed of consensus TE sequences grouped into families that can be used as a library file for homology-based TE detection programs such as RepeatMasker. MITE-Hunter was evaluated by searching the rice genomic database and comparing the output with known rice TEs. It discovered most of the previously reported rice MITEs (97.6%), and found sixteen new elements. MITE-Hunter was also compared with two other MITE discovery programs, FINDMITE and MUST. Unlike MITE-Hunter, neither of these programs can search large genomic data sets including whole genome sequences. More importantly, MITE-Hunter is significantly more accurate than either FINDMITE or MUST as the vast majority of their outputs are false-positives.