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Post-implantation analysis of genomic variations in the progeny from developing fetus to birth

Human Genomics volume 18, Article number: 79 (2024) Cite this article

Abstract

The analysis of genomic variations in offspring after implantation has been infrequently studied. In this study, we aim to investigate the extent of de novo mutations in humans from developing fetus to birth. Using high-depth whole-genome sequencing, 443 parent-offspring trios were studied to compare the results of de novo mutations (DNMs) between different groups. The focus was on fetuses and newborns, with DNA samples obtained from the families’ blood and the aspirated embryonic tissues subjected to deep sequencing. It was observed that the average number of total DNMs in the newborns group was 56.26 (54.17–58.35), which appeared to be lower than that the multifetal reduction group, which was 76.05 (69.70–82.40) (F = 2.42, P = 0.12). However, after adjusting for parental age and maternal pre-pregnancy body mass index (BMI), significant differences were found between the two groups. The analysis was further divided into single nucleotide variants (SNVs) and insertion/deletion of a small number of bases (indels), and it was discovered that the average number of de novo SNVs associated with the multifetal reduction group and the newborn group was 49.89 (45.59–54.20) and 51.09 (49.22–52.96), respectively. No significant differences were noted between the groups (F = 1.01, P = 0.32). However, a significant difference was observed for de novo indels, with a higher average number found in the multifetal reduction group compared to the newborn group (F = 194.17, P < 0.001). The average number of de novo indels among the multifetal reduction group and the newborn group was 26.26 (23.27–29.05) and 5.17 (4.82–5.52), respectively. To conclude, it has been observed that the quantity of de novo indels in the newborns experiences a significant decrease when compared to that in the aspirated embryonic tissues (7–9 weeks). This phenomenon is evident across all genomic regions, highlighting the adverse effects of de novo indels on the fetus and emphasizing the significance of embryonic implantation and intrauterine growth in human genetic selection mechanisms.

Introduction

The mechanisms of genetic selection are of utmost importance in the progression of human reproduction, encompassing the maturation of gametes, formation of fertilized eggs, emergence of cleavage embryos, development of blastocysts, implantation of embryos, and formation of pregnancy embryos, ultimately culminating in the birth of offspring. The precise expression of genetic material serves as the fundamental basis for the normal development of progeny [1]. Genomic variations, which are directed by the reference of the genome sequence, encompass modifications to the structural base pair composition or sequence arrangement of genes. These includes copy number variations (CNVs), single nucleotide variants (SNVs), and insertion/deletion of a small number of bases (indels) [2]. The occurrence of de novo SNVs and indels has been reported at an average rate of approximately 70 de novo mutations (DNMs) per individual [3]. These variations represent significant targets for the operation of genetic selection mechanisms.

Certain genomic variations that are specific to certain regions or types can result in various complications during pregnancy, including but not limited to oocyte maturation impairment, fertilization anomalies, diminished embryonic developmental potential, biochemical pregnancies, and miscarriages, which ultimately lead to pregnancy termination [4]. It is widely accepted that embryonic chromosomal abnormalities are the primary cause of early pregnancy loss, accounting for more than 50% of early miscarriages. These abnormalities can include anomalies in chromosome numbers and structure, such as microdeletions and duplications of chromosomal fragments [5, 6]. By means of genetic selection, the majority of offspring with severe illnesses and developmental abnormalities are effectively prevented from being born, thereby significantly enhancing the genetic stability of the human population. Gaining a deeper understanding of how the quantity of each type of genomic variation evolves during offspring development can facilitate our comprehension of this mechanism and enable more targeted research on the genetic safety of offspring in clinical practice.

The genetic selection mechanism, in fact, plays a crucial role in all stages of embryonic development. With the advent of assisted reproductive technology (ART), individuals now have the opportunity to conduct in vitro research on gametes and embryos at all stages of development. Furthermore, the introduction of whole genome sequence (WGS) technology has spurred investigations of DNMs in humans at the whole genome level. Based on the available literature, the majority of studies have focused on the genomic variation of oocyte, cleavage embryos, and blastocysts. Previous research, which included copy number variation sequencing (CNV-seq) data [7,8,9], has demonstrated that high frequency aneuploidy and large fragment (> 2 Mb) of pathogenic CNVs were present in oocytes, cleavage embryos and blastocysts, but were largely absent in reduced fetal tissue during early implantation of embryos. However, there is limited research that has delved deeply into chromosomal variation from fetus to birth after implantation, and even less is known about the timing and frequency of these variants. A recent study of limited scope has provided evidence indicating that there were no significant differences observed in the number of DNMs per child for various methods of conception [10]. As such, the present study aims to estimate the differences in de novo variation between early gestational fetal tissue and newborns when subsequent to implantation. DNMs which are known to cause most human genetic diseases, some adverse perinatal outcomes, and congenital and developmental diseases of the offspring, were selected as the target of this study [11]. WGS was conducted on parent-offspring trios to identify DNMs.

Materials and methods

Ethical approval and study subjects

The present study was conducted under the auspices of a license obtained from the Human Genetic Resource in China ([2021] CJ0522). The Institutional Review Board of the School of Medicine, Zhejiang University, China, granted ethical approval for this project (approval number: 20,180,127), and written informed consent was obtained from all participants. The study population was divided into two groups: the multifetal reduction group and the newborn group.

The multifetal reduction group

Between December 2018 and July 2021, a total of 57 multifetal reduction tissues were collected. The study invited 46 couples who had undergone in in-vitro fertilization (IVF) and 11 couples who had undergone intracytoplasmic sperm injection (ICSI) to donate blood samples for DNA extraction to aid in ongoing research. The multiple pregnancies in question were a result of IVF and ICSI, and all fetuses were either triplets or part of a gemellary pregnancy. Multifetal reduction was performed at 7–9 weeks after the fetal heartbeat was observed, reducing the number of fetuses from triplets to twins or from twins to a singleton. The most accessible gestational sac was selected and aligned with the puncture guideline on the screen. Or choose to the fetus with a relatively small gestational sac, if the surgical path allows. After introducing the needle into the fetal echoes, suction was applied repeatedly using a 50-mL syringe until all fetal parts were aspirated. The analysis was conducted on a total fetus that did not contain chorionic villi from the volunteered reduction.

The newborn group

Between December 2018 and October 2020, a total of 306 families who had undergone ART were recruited for a study. This group consisted of 189 families who had undergone IVF and 117 families who had undergone ICSI, resulting in a total of 386 infants (234 IVF and 152 ICSI). The couples were invited to donate blood samples for DNA extraction to assist in ongoing research, and parental consent was obtained for the collection of umbilical cord blood from the offspring at the time of delivery. General paediatric examinations were conducted at birth to identify any obvious somatic abnormalities in the children.

The criteria for exclusion from participation in this study included the inability of any subject to undergo blood or tissue sampling, the presence of known chromosomal abnormalities in either parent, the use of IVF/ICSI following the donation of oocytes or semen, and a history of chemotherapy or radiation therapy for malignancy in either parent. The baseline characteristics of each individual were meticulously collected.

Sequencing and variant calling

For each household, we extracted genomic DNA (gDNA) from both the father and mother, as well as from the multifetal reduction tissues or neonate umbilical cord blood following live birth (triple DNA sample set). WGS libraries were prepared using a Universal DNA Library Prep Set in accordance with the manufacturer’s protocol (MGI; Cat: 1,000,017,571). The gDNA was fragmented, ligated with an adaptor after end repair and A-tailing, amplified, and sequenced at the China National GeneBank. A minimum of 500 million 100 bp paired-end reads were obtained from each sample on the DNBSEQ-T1 platform.

After implementing quality control measures and filtering out low-quality reads, short variants of SNVs and indels of each sample were identified by the Sentieon pipeline [12] based on the human reference genome (GRCh37). Subsequently, we utilized the module of variants quality score recalibration (VQSR) within the Genome Analysis Toolkit (GATK v3.4.46) as described by McKenna, A., et al. (2010) [13]. This enabled us to acquire high-confidence variants for all autosomes and X chromosomes (tranche 0.99). For each trio, individual genome variant call format files (gVCF) were jointly genotyped using Genotype GVCFs, and variants that passed the filter of VQSR were obtained for further analysis.

De novo mutation identification

We called DNMs using the DeNovoGear [14] TrioDeNovo [15] and GATK Genotype Refinement workflows [13]. The results that were found to be consistent by three pipelines were designated as DNM, provided they satisfied the following criteria: (1) passing the VQSR filter in the offspring; (2) genotype quality (GQ) greater than 90 in the offspring; (3) GQ greater than 30 in both parents; (4) read depth (DP) between 20 and 150 in the offspring; (5) DP greater than 20 in both parents; (6) alternative allele fraction greater than 0.2; and (7) located on the autosomes. To assess the accuracy of our identification method, we selected all DNMs from 5 trios and subjected them to Sanger sequencing (BGI TECH SOLUTIONS (BEIJING LIUHE) CO., LIMITED) to validate these variants. We extracted sequences in the vicinity of the variant sites and designed PCR primers for all these sites using the Primer Design Tool from NCBI.

De novo mutation interpretation

The DNMs were systematically classified as pathogenic, likely pathogenic, benign, likely benign and uncertain significance, employing InterVar based on a multitude of factors including but not limited to allele frequencies across populations, evolutionary conservation metrics, and predictive functional annotations [16].

Statistical analysis

The data have been presented as the mean value along with a 95% confidence interval [CI]. The Student’s t-test has been employed to analyze the data, which conforms to a Gaussian distribution. Furthermore, Chi-square tests have been utilized to compare count data across different groups. Additionally, a covariates test has been conducted to eliminate any potential impact of clinical background information. All statistical analyses were conducted using IBM SPSS 26.0. A significance level of P < 0.05 was deemed statistically significant.

Result

Clinical data

As illustrated in Fig. 1, Our research encompassed a total of 57 fetuses and 386 neonates, selected in accordance with the corresponding criteria. Based on clinical features, we established two distinct groups: the multifetal reduction group and the newborn group. The clinical background information of both groups is presented in Table 1. The parental age for the newborn group was 32.16 (31.78–32.53) and 33.88 (33.40–34.36), respectively, which was slightly higher than that of the multifetal reduction group. The maternal pre-pregnancy body mass index (BMI) in the multifetal reduction group was 22.14 (21.34–22.94) and in the newborn group was 21.49 (21.22–21.75). There was no significant difference in the age of the parents or the maternal pre-pregnancy BMI between the two groups (P > 0.05). The distribution of the DNMs between the two groups is discussed below.

Fig. 1
figure 1

Flowchart of the main results of the study

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Table 1 Parental characteristics between the two groups
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De novo events in the progeny from developing fetus to birth subsequent to implantation

The sequencing results show a WGS depth of 30X ∼ 40X per sample, yielding approximately 120G of data and sequencing quality of Q20 > 95% and Q30 > 85%. Based on the quantity of bases affected by the mutation, DNMs can be classified into categories: SNVs and indels. For the purposes of this study, only de novo SNVs and indels were analyzed. The genomic region in which DNMs occur can be divided into ten distinct groups based on their biological function including downstream, exonic, intergenic, intronic, ncRNA-exonic, ncRNA-intronic, splicing, upstream, UTR3, and UTR5. In this study, we focused on three major genetic regions, which were analyzed as follows: the downstream and upstream regions were classified as intergenic regions, while the ncRNA-intronic and splicing regions were categorized as intronic regions. Finally, the ncRNA-exonic, UTR3, and UTR5 regions were grouped as exonic regions.

The average number of total DNMs in the newborns was observed to be 56.26 (54.17–58.35), which appeared to be lower than that in the multifetal reduction group, which was 76.05 (69.70–82.40) (F = 2.42, P = 0.12). However, after adjusting for parental age and maternal pre-pregnancy BMI, significant differences were observed between the two groups (F = 50.60, P < 0.001). Furthermore, we categorized the total number of DNMs into various genetic regions and found that the distribution of DNMs in genome sections varied. Notably, the number of DNMs per capita in intergenic and intronic regions was found to be the highest among all the groups. The average number of DNMs in intergenic regions was found to be 44.30 (40.47–48.13) in the multifetal reduction group and 30.80 (29.59–32.02) in the newborns (F = 3.72, P = 0.05). Similarly, the average number of DNMs in intronic regions was 29.84 (27.23–32.46) in the multifetal reduction group and 23.79 (22.84–24.74) in the newborns (F = 0.05, P = 0.83). After adjusting for parental age and maternal pre-pregnancy BMI, it was determined that the observed differences were statistically significant. The average number of DNMs in exonic regions was 1.89 (1.49–2.30) in the multifetal reduction group and 1.60 (1.45–1.75) in the newborns (F = 0.86, P = 0.35).There is no difference between groups in statistics. These findings are presented in Fig. 2; Table 2.

Fig. 2
figure 2

The average number of DNMs catalogued between the multifetal reduction group and the newborns. (A) The occurrence of the average number of total DNMs, de novo SNVs and de novo indels in the two groups. The results revealed a statistically significant decrease in the average number of total DNMs and de novo indels in newborns (P < 0.001). (B). The distribution of various genome regions in total DNMs, de novo SNVs and de novo indels. The average number of total DNMs were significantly differences between the two groups in both intergenic and intronic regions. There were significantly differences in the number of de novo indels across all regions examined (P < 0.001). (C) The distribution of various mutation modes in de novo SNVs, specifically C > T, G > A, A > G, and T > C, was analyzed. No significant differences were noted in the frequency of base exchange between the two groups (P > 0.05). *** indicates P < 0.001

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Table 2 The average number of DNMs catalogued between the multifetal reduction group and the newborns
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Distribution of de novo SNVs

After conducting phased DNMs in two cohorts, we proceeded to perform similar workflows on de novo SNVs and indels separately. Our findings revealed that tthe average number of de novo SNVs associated with the multifetal reduction group and the newborns was 49.89 (45.59–54.20) and 51.09 (49.22–52.96), respectively. Notably, no significantly differences were observed between the groups (F = 1.01, P = 0.32). Furthermore, we subdivided the total number of de novo SNVs into different genetic regions and found no significant difference between the groups.

Out of the various modes of mutation, the four primary types, namely, C > T, G > A, A > G, and T > C, demonstrated the highest frequency of occurrence, with frequencies of 9.84 (9.39–10.29), 9.95 (9.50-10.41), 7.17 (6.81–7.53), and 6.93 (6.57–7.29) per newborn, respectively. Similarly, with frequencies of 9.98 (8.89–11.07), 9.84 (8.58–11.1), 6.54 (5.71–7.38) and 6.39 (5.60–7.17) per fetus in the multifetal reduction group, respectively. There was no significant difference observed in the frequency of base exchange between the two groups.

The extant literature reports indicate a correlation between DNMs and paternal age. Our own observations, after adjusting for parental age and maternal pre-pregnancy BMI using a multivariable regression model, reveal a similar directionality between the two groups. These findings are presented in Fig. 2; Table 2.

Distribution of de novo indels

It appears that indels occur at lower frequencies than SNVs, likely due to their larger size which collectively affects more base pairs. The average number of de novo indels among the multifetal reduction group and the newborns was 26.26 (23.27–29.05) and 5.17 (4.82–5.52) respectively, and a statistically significant difference was observed (F = 194.17, P < 0.001). The study also found significant differences in the number of de novo indels in intergenic, intronic, and exonic regions, which remained significant even after correcting for clinical background information. The multifetal reduction group had an average of 16.28 de novo indels in intergenic regions, 9.37 in intronic regions, and 0.49 in exonic regions. In contrast, newborns had averages of 2.63, 2.36, and 0.15, respectively. All comparisons were statistically significant (P < 0.001). These results are presented in Fig. 2; Table 2.

Parental characteristics when divided by the number of DNMs within the group

In this study, we categorized the parental age and the maternal pre-pregnancy BMI within the multifetal reduction group or newborn group based on the number of DNMs, with the number of 60 as the cutoff point, to investigate whether there were any differences. Within the group of multifetal reduction, there was no statistically significant difference in parental age and the pre-pregnancy BMI between those with less than 60 DNMs and those with 60 or more DNMs. However, in the newborn group, The maternal age for the group with 60 or more DNMs was 33.14 (29.39–36.89), while the paternal age was 34.99 (30.16–39.82). This represented a significant increase in comparison to those individuals who had fewer than 60 DNMs (F = 4.09, P < 0.001; F = 4.67, P < 0.001, respectively) (Table 3).

Table 3 Comparison of parental characteristics devided by the number of DNMs
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Categorical on the pathogenicity of the DNMs

Next, we conducted a variant interpretation using InterVar on all of the identified variants. Upon analysis, no significant differences were observed across all groups in terms of pathogenic and likely pathogenic mutations. The pertinent data are presented in Fig. 3, while cases harboring pathogenic or likely pathogenic mutations are enumerated in Table 4.

Fig. 3
figure 3

The pathogenicity of DNMs catalogued between the multifetal reduction group and the newborns. Among the total DNMs and de novo indels, there were statistically significant differences in both variants of uncertain significance and benign results between the two groups (P < 0.001). However, no significant difference was observed in the five pathogenicity classifications of the de novo SNVs between the two groups (P > 0.05). *** indicates P < 0.001. Note P = Pathogenic; LP = Likely Pathogenic; B = Benign; LB = Likely Benign; VUS = Variant of Uncertain Significance

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Table 4 Summary of pathogenic or likely pathogenic DNMs detected
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Among the total DNMs, 86.07% and 94.82% of the variants were interpreted as having uncertain significance in the multifetal reduction group and the newborn group, respectively (F = 447.77, P < 0.001). 13.56% and 4.73% of the variants were interpreted as benign, respectively (F = 487.05, P < 0.001). There were statistically significant differences in both variants of uncertain significance and benign results between the two groups. Among the de novo SNVs, there was no difference in the five pathogenicity classifications between the two groups. Among the de novo indels, 71.16% and 99.06% of the variants were interpreted as having uncertain significance in the multifetal reduction group and the newborn group respectively, with a significant difference (F = 598.09, P < 0.001). Additionally, 28.77% and 0.55% of the variants were interpreted as benign, respectively, also showing a significant difference (F = 622.987, P < 0.001).

Discussion

The occurrence of spontaneous DNMs in the germline is known to promote evolution by providing material for natural selection to act upon. The distribution and frequency of DNMs across the genome contribute to virtually every aspect of an organism’s function and fitness [17]. Spontaneous abortion occurs in 8–20% of recognized pregnancies and typically occurring in the first trimester (7–11 weeks) [18]. Recent research reports suggest that mutations in genes responsible for proper fetal development are a more frequent cause of reproductive failures than chromosomal aberrations. Developmental disorders caused by DNMs have an average prevalence of 1 in 213 to 1 in 448 births, depending on parental age [19]. The study conducted by Kowalczyk et al. has revealed that up to 17.1% of small aberrations cannot be identified through conventional chromosome analysis. These aberrations include genes important for fetal development, and their mutations could cause spontaneous abortion [20]. However, there is a dearth of published research on DNMs that vary from the fetus to the newborn.

Our study was the first to show a significant reduction in the number of de novo indels in offspring compared to early pregnancy embryos, across all genomic regions. The differences were statistically significant even after adjusting for factors like parental age and other clinical backgrounds. The estimated indel mutation rate is approximately 4 × 10–10 per position, leading to roughly three new indels per genome per generation [21]. Data from Lithuania’s general population, using whole-exome sequencing (WES), showed a de novo indel mutation rate of 1.77 × 10 − 8 per position per generation [22]. We found that the frequency of de novel indels was about 26.16 per genome per generation in post-implantation early pregnancy embryos, which was approximately five times higher than that in the newborns (5.17 per genome per generation). It was observed that fetal mutation rates were about fivefold higher than in tissue matched adult stem cells [23]. Elevated mutation accumulation rates are common in fetal cells of various tissues, suggesting that rapid cellular expansion during development is associated with increased mutation accumulation.

Research on de novo indels is somewhat limited compared to that on de novo SNVs, primarily due to the current WGS technology’s limited accuracy in detecting de novo indels [24, 25]. Recent large-scale exome sequencing projects found that de novo indels can can lead to many different diseases, ranging from complex neurological diseases to rare Mendelian disorders [26, 27]. The study also shows that de novo indels could potentially harm the fetus. The presence of these indels after embryo implantation may be key to fetal health. The obstetrical epidemiological data indicates that the incidence of abortion is approximately 12% [28]. In this study, the total number of de novo indels in 9 families during the first trimester exceeded 40, resulting in an incidence of about 16% (9/57). Interestingly, none were found in the newborns with a number exceeded 40, while only two newborns had a total number of de novo indels exceeding 20, 26, and 35, respectively. While the embryo’s intrinsic characteristics or the mother’s physiological and biochemical composition may explain this phenomenon, fetuses with a high number of de novo indels did not survive later stages of prenatal development. Natural selection mechanism had a boundary in the selection of de novo indels during pregnancy. Embryos with a high frequency of de novo indels in their genome may be eliminated through fertilization, embryonic development, and selective growth. Another possible reason is that during fetal reduction, a relatively smaller gestational sac may be selected for reduction. Fetuses from smaller gestational sacs may inherently have a higher possibility of mutations and are more likely to be eliminated during later development. However, in our study, there were significant differences in benign variations of de novo indel in the fetuses compared to those in the newborns, while the variations in uncertain significance are more significant in the newborns. This phenomenon requires further research to clarify.

Previous research utilized WES to examine deceased fetuses with ultrasound anomalies, revealing diagnostic genetic variants in 20% of cases [29]. Another study evaluated diagnostic or potentially clinically relevant genetic variant in genes associated with developmental disorders in 12.5% of fetuses with structural abnormalities after 11 weeks of gestation [30], many genetic variants in this study were caused by new mutations. Nevertheless, the available literature detailing the pathogenesis that may lead to fetal demise remains insufficient in providing a comprehensive list of mutations or genes responsible for this process. In this study, we selected offspring conceived through ART. There is no evidence of increased DNM load or altered mutation spectrums in mice or humans born through ART compared to spontaneously conceived offspring [31]. Our research team also conducted the same analysis on early artificial abortion tissue and offspring born through natural conception, and found consistent trends (not yet published). However, it is widely acknowledged that infertility itself is linked to unfavorable outcomes in children [32]. To confirm this conclusion, larger sample sizes and core family sequencing results are required, and a thorough characterization of the mechanisms underlying de novo indel genesis and evolution in the human genome is necessary.

Our results show no significant difference in the frequency of de novo SNVs between the two groups.There are also no significant differences in all genomic regions, including intergenic, intronic, and exonic areas. It is suggested that the occurrence of de novo SNVs is mainly determined after successful implantation. Previous studies on humans have shown that approximately 73–78% of de novo SNVs are of paternal origin [33]. The investigators noted a rise in the overall count of de novo SNVs, specifically 1.28 de novo SNVs per year of paternal age and 0.35 de novo SNVs per year of maternal age. Additionally, both paternal and maternal age were found to be significantly linked to the number of de novo indels, with an increase of 0.071 de novo indels per year of paternal age and a smaller increase of 0.019 de novo indels per year of maternal age [34]. In this study, the parental age represented a significant increase in comparison to those individuals who had fewer than 60 DNMs in the newborn group.

In the process of interpreting our findings, it is important to acknowledge the limitations of our study. In this study, there was natural heterogeneity in the selection of samples. The embryonic tissue aspirated from the multifetal reduction group were fetal tissues, indicating sample heterogeneity with neonatal cord blood. Report has shown that mutation rates during prenatal development seem to vary among tissues [23]. Another noteworthy aspect is the fact that we were unable to distinguish the infertility factors for the rare samples of multifetal reduction group. Moreover, we could not fully investigate the parental origin of DNMs, only approximately 26% of DNMs in our study could be successfully phased and parent-of-origin called. It has been reported that 15–20% of DNMs can be successfully phased and parent-of-origin called by short-read WGS of parent-offspring trios [35]. Therefore, further exploration is required to improve the detectable rate. One potential approach to achieve this is through the use of multiplexed long-read sequencing [36]. Moreover, it is hard to figure out how those DNMs were associated with the phenotype, and the absence of information about children’s diseases restricted the clinical significance of assessing those DNMs.

Conclusions

Collectively, we have demonstrated that the occurrence of de novo SNVs in offspring is essentially determined after successful implantation. The quantity of de novo indels in neonates experiences a significant reduction in comparison to that in early pregnancy embryos post-implantation, and this trend is evident across all genomic regions, underscoring the adverse influence of de novo indels on fetal growth after implantation. Nevertheless, to validate these findings further, incorporating a wider range of samples in future studies would aid in identifying more nuanced effects and potentially uncover genetic interactions during intrauterine growth and development.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

CNVs:

Copy number variations

SNVs:

Single nucleotide variants

DNMs:

De novo mutations

ART:

Assisted reproductive technology

WGS:

Whole genome sequence

IVF:

In-vitro fertilization

ICSI:

Intracytoplasmic sperm injection

VQSR:

Variants quality score recalibration

GATK:

Genome Analysis Toolkit

gVCF:

Genome variant call format files

GQ:

Genotype quality

DP:

Read depth

CI:

Confidence interval

BMI:

Body mass index

WES:

Whole-exome sequencing

LP:

Likely pathogenic

P:

Pathogenic

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Funding

This work was supported by the National Key Research and Development Program of China [2018YFC1004900]; and the National Natural Science Foundation of China [82001625;82201843].

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Author notes

  1. Yingming Zheng, Chuanping Lin and Wen-Jing Wang contributed equally to this work.

Authors and Affiliations

  1. Department of Reproductive Endocrinology, Key Laboratory of Reproductive Genetics of National Ministry of Education, Women’s Reproductive Health Laboratory of Zhejiang Province, Women’s Hospital, School of Medicine, Zhejiang University, 1 Xueshi Road, Hangzhou, Zhejiang, 310006, China

    Yingming Zheng, Chuanping Lin, Liya Wang, Yeqing Qian, Luna Mao, Baohua Li, Yuchan Mao, Na Li, Jiayong Zheng, Qijing Wang & Fan Jin

  2. Reproductive Medical Center, the Second Affiliated Hospital of Wenzhou Medical College and Yuying Children’s hospital, Wenzhou, Zhejiang, 325027, China

    Chuanping Lin

  3. BGI Research, Shenzhen, Guangdong, 518083, China

    Wen-Jing Wang, Qing Zhou & Fang Chen

  4. Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, Zhejiang, 322100, China

    Lijun Lou

  5. Reproductive Medical Center, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310003, China

    Nan Jiang

  6. Hangzhou Women’s Hospital (Hangzhou Maternity and Child Health Care Hospital), Hangzhou, Zhejiang, 310008, China

    Chaying He

Authors
  1. Yingming Zheng
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  2. Chuanping Lin
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  4. Liya Wang
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  6. Luna Mao
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  7. Baohua Li
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  10. Na Li
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  11. Jiayong Zheng
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  15. Qing Zhou
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  16. Fang Chen
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  17. Fan Jin
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Contributions

Yingming Zheng and Chuanping Lin participated in study design and data analysis. Wen-Jing Wang, Liya Wang, and Yeqing Qian performed the laboratory experiments and DNMs analyses. Luna Mao, Baohua Li, Lijun Lou, Yuchan Mao, Na Li, Jiayong Zheng, Nan Jiang, Chaying He, and Qijing Wang collected data on subjects. Qing Zhou and Fang Chen performed the analysis for WGS and DNMs. Yingming Zheng, Chuanping Lin, and Wen-Jing Wang drafted and edited the manuscript. Fan Jin oversaw the project. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Fan Jin.

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Zheng, Y., Lin, C., Wang, WJ. et al. Post-implantation analysis of genomic variations in the progeny from developing fetus to birth. Hum Genomics 18, 79 (2024). https://doi.org/10.1186/s40246-024-00634-4

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Keywords

Human Genomics

ISSN: 1479-7364